diff --git a/Analyse/Metabolomics_demo_pathway_analysis.ipynb b/Analyse/Metabolomics_demo_pathway_analysis.ipynb
new file mode 100644
index 0000000..55af66c
--- /dev/null
+++ b/Analyse/Metabolomics_demo_pathway_analysis.ipynb
@@ -0,0 +1,5625 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "colab_type": "text",
+        "id": "view-in-github"
+      },
+      "source": [
+        "<a href=\"https://polly.elucidata.io/manage/workspaces?action=open_polly_notebook&source=github&path=path_place_holder&kernel=elucidata/Metabolomics&machine=large\" target=\"_parent\"><img src=\"https://elucidatainc.github.io/PublicAssets/open_polly.svg\" alt=\"Open in Polly\"/></a>\n"
+      ]
+    },
+    {
+      "attachments": {
+        "elucidata_temp1.png": {
+          "image/png": 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"
+        }
+      },
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "Pollyglot"
+      },
+      "source": [
+        "![elucidata_temp1.png](attachment:elucidata_temp1.png)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "SoS"
+      },
+      "source": [
+        "# Welcome to Pollyglot Notebook."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "kernel": "Pollyglot"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\u001b[33mWARNING: The directory '/home/polly/.cache/pip' or its parent directory is not owned or is not writable by the current user. The cache has been disabled. Check the permissions and owner of that directory. If executing pip with sudo, you should use sudo's -H flag.\u001b[0m\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "typer 0.3.2 requires click<7.2.0,>=7.1.1, but you have click 8.0.4 which is incompatible.\u001b[0m\n",
+            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n",
+            "\u001b[33mWARNING: You are using pip version 21.1.3; however, version 21.3.1 is available.\n",
+            "You should consider upgrading via the '/usr/bin/python3.6 -m pip install --upgrade pip' command.\u001b[0m\n"
+          ]
+        }
+      ],
+      "source": [
+        "!sudo pip3 install polly-python --quiet"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "outputs": [],
+      "source": [
+        "from polly.auth import Polly\n",
+        "from polly.omixatlas import OmixAtlas\n",
+        "from polly.workspaces import Workspaces\n",
+        "import os\n",
+        "import plotly.express as px\n",
+        "import seaborn as sns\n",
+        "import plotly.figure_factory as ff\n",
+        "import ipywidgets as widgets\n",
+        "from ipywidgets import interact, interact_manual\n",
+        "import matplotlib.pyplot as plt\n",
+        "import seaborn as sns\n",
+        "from IPython.display import display"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "outputs": [],
+      "source": [
+        "AUTH_TOKEN=(os.environ['POLLY_REFRESH_TOKEN']) # Obtain authentication tokens\n",
+        "Polly.auth(AUTH_TOKEN)\n",
+        "omixatlas = OmixAtlas()"
+      ]
+    },
+    {
+      "attachments": {
+        "elucidata_temp2.png": {
+          "image/png": 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"
+        }
+      },
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "source": [
+        "### Data Schema\n",
+        "The transcriptomics,metabolomics data available within OmixAtlas is curated within 3 indexes/tables on the basis of the information it contains. These three indexes are:\n",
+        "\n",
+        "- Dataset level metadata (index: files): Contains curated fields like drug, disease, tissue organism, etc for each dataset.\n",
+        "\n",
+        "- Sample level metadata (index: gct_metadata): As the name suggests, this contains sample level metadata information for all samples except single-cell samples. It contains curated fields like cell lines, experimental design, etc for each sample except single-cell samples.\n",
+        "\n",
+        "- Feature level metadata (index: gct_data): This table contains feature level metadata information for all data except single-cell.\n",
+        "![elucidata_temp2.png](attachment:elucidata_temp2.png)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {
+        "kernel": "Python3",
+        "scrolled": true
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Query execution succeeded (time taken: 0.87 seconds, data scanned: 0.000 MB)\n",
+            "Fetched 3 rows\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>table_name</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>metabolomics.datasets</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>metabolomics.samples</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>metabolomics.features</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "              table_name\n",
+              "0  metabolomics.datasets\n",
+              "1   metabolomics.samples\n",
+              "2  metabolomics.features"
+            ]
+          },
+          "execution_count": 9,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "#Metadata tables in Metabolomics OA\n",
+        "query = \"SHOW TABLES IN metabolomics\"\n",
+        "res = omixatlas.query_metadata(query)\n",
+        "res"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "source": [
+        "### Querying dataset-level metadata for a disease of interest"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {
+        "kernel": "Python3",
+        "scrolled": true
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Query execution succeeded (time taken: 1.52 seconds, data scanned: 0.000 MB)\n",
+            "Fetched 32 rows\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>column_name</th>\n",
+              "      <th>column_type</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>24</th>\n",
+              "      <td>analysis_id</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>analysis_type</td>\n",
+              "      <td>array&lt;string&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25</th>\n",
+              "      <td>bucket</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>curated_cell_line</td>\n",
+              "      <td>array&lt;string&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14</th>\n",
+              "      <td>curated_cell_type</td>\n",
+              "      <td>array&lt;string&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>21</th>\n",
+              "      <td>curated_disease</td>\n",
+              "      <td>array&lt;string&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>22</th>\n",
+              "      <td>curated_drug</td>\n",
+              "      <td>array&lt;string&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>curated_organism</td>\n",
+              "      <td>array&lt;string&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>26</th>\n",
+              "      <td>curated_tissue</td>\n",
+              "      <td>array&lt;string&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>data_table_name</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>9</th>\n",
+              "      <td>data_table_version</td>\n",
+              "      <td>bigint</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>28</th>\n",
+              "      <td>data_type</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>19</th>\n",
+              "      <td>dataset_id</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>27</th>\n",
+              "      <td>dataset_source</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>description</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>18</th>\n",
+              "      <td>file_location</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>12</th>\n",
+              "      <td>file_type</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>instrument_type</td>\n",
+              "      <td>array&lt;string&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>20</th>\n",
+              "      <td>ion_mode</td>\n",
+              "      <td>array&lt;string&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>30</th>\n",
+              "      <td>is_current</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>15</th>\n",
+              "      <td>key</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>29</th>\n",
+              "      <td>measurement_unit</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>17</th>\n",
+              "      <td>package</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>11</th>\n",
+              "      <td>project_id</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>13</th>\n",
+              "      <td>publication</td>\n",
+              "      <td>array&lt;string&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>31</th>\n",
+              "      <td>region</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>16</th>\n",
+              "      <td>src_repo</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>src_uri</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>study_id</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>10</th>\n",
+              "      <td>timestamp_</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>total_num_samples</td>\n",
+              "      <td>bigint</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>23</th>\n",
+              "      <td>version</td>\n",
+              "      <td>bigint</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "           column_name    column_type\n",
+              "24         analysis_id         string\n",
+              "3        analysis_type  array<string>\n",
+              "25              bucket         string\n",
+              "5    curated_cell_line  array<string>\n",
+              "14   curated_cell_type  array<string>\n",
+              "21     curated_disease  array<string>\n",
+              "22        curated_drug  array<string>\n",
+              "0     curated_organism  array<string>\n",
+              "26      curated_tissue  array<string>\n",
+              "8      data_table_name         string\n",
+              "9   data_table_version         bigint\n",
+              "28           data_type         string\n",
+              "19          dataset_id         string\n",
+              "27      dataset_source         string\n",
+              "4          description         string\n",
+              "18       file_location         string\n",
+              "12           file_type         string\n",
+              "6      instrument_type  array<string>\n",
+              "20            ion_mode  array<string>\n",
+              "30          is_current         string\n",
+              "15                 key         string\n",
+              "29    measurement_unit         string\n",
+              "17             package         string\n",
+              "11          project_id         string\n",
+              "13         publication  array<string>\n",
+              "31              region         string\n",
+              "16            src_repo         string\n",
+              "1              src_uri         string\n",
+              "7             study_id         string\n",
+              "10          timestamp_         string\n",
+              "2    total_num_samples         bigint\n",
+              "23             version         bigint"
+            ]
+          },
+          "execution_count": 9,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "# Dataset level metadata schema for metabolomics OA\n",
+        "query = \"DESCRIBE metabolomics.datasets\"\n",
+        "res1 = omixatlas.query_metadata(query)\n",
+        "res1.sort_values(\"column_name\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 103,
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "outputs": [],
+      "source": [
+        "disease_name = 'Breast Neoplasms'"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 104,
+      "metadata": {
+        "kernel": "Python3",
+        "scrolled": true
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Query execution succeeded (time taken: 2.67 seconds, data scanned: 0.025 MB)\n",
+            "Fetched 23 rows\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>dataset_id</th>\n",
+              "      <th>disease</th>\n",
+              "      <th>organism</th>\n",
+              "      <th>tissue</th>\n",
+              "      <th>data_type</th>\n",
+              "      <th>total_num_samples</th>\n",
+              "      <th>data_table_name</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>MTBLS1066_m_mtbls1066_NEG_HILIC_LCMS</td>\n",
+              "      <td>Neoplasms</td>\n",
+              "      <td>Mus musculus</td>\n",
+              "      <td>blood plasma</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>7</td>\n",
+              "      <td>metabolomics__mtbls1066_m_mtbls1066_neg_hilic_...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>MTBLS1066_m_mtbls1066_NEG_HILIC_LCMS</td>\n",
+              "      <td>Breast Neoplasms</td>\n",
+              "      <td>Mus musculus</td>\n",
+              "      <td>blood plasma</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>7</td>\n",
+              "      <td>metabolomics__mtbls1066_m_mtbls1066_neg_hilic_...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>MTBLS1066_m_mtbls1066_NEG_RP_LCMS</td>\n",
+              "      <td>Neoplasms</td>\n",
+              "      <td>Mus musculus</td>\n",
+              "      <td>blood plasma</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>7</td>\n",
+              "      <td>metabolomics__mtbls1066_m_mtbls1066_neg_rp_lcms</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>MTBLS1066_m_mtbls1066_NEG_RP_LCMS</td>\n",
+              "      <td>Breast Neoplasms</td>\n",
+              "      <td>Mus musculus</td>\n",
+              "      <td>blood plasma</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>7</td>\n",
+              "      <td>metabolomics__mtbls1066_m_mtbls1066_neg_rp_lcms</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>MTBLS1066_m_mtbls1066_POS_HILIC_LCMS</td>\n",
+              "      <td>Neoplasms</td>\n",
+              "      <td>Mus musculus</td>\n",
+              "      <td>blood plasma</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>7</td>\n",
+              "      <td>metabolomics__mtbls1066_m_mtbls1066_pos_hilic_...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>MTBLS1066_m_mtbls1066_POS_HILIC_LCMS</td>\n",
+              "      <td>Breast Neoplasms</td>\n",
+              "      <td>Mus musculus</td>\n",
+              "      <td>blood plasma</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>7</td>\n",
+              "      <td>metabolomics__mtbls1066_m_mtbls1066_pos_hilic_...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>MTBLS1066_m_mtbls1066_POS_RP_LCMS</td>\n",
+              "      <td>Neoplasms</td>\n",
+              "      <td>Mus musculus</td>\n",
+              "      <td>blood plasma</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>7</td>\n",
+              "      <td>metabolomics__mtbls1066_m_mtbls1066_pos_rp_lcms</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>MTBLS1066_m_mtbls1066_POS_RP_LCMS</td>\n",
+              "      <td>Breast Neoplasms</td>\n",
+              "      <td>Mus musculus</td>\n",
+              "      <td>blood plasma</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>7</td>\n",
+              "      <td>metabolomics__mtbls1066_m_mtbls1066_pos_rp_lcms</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>MTBLS92_m_breastcancerlipidome_metabolite_prof...</td>\n",
+              "      <td>Neoplasms</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>blood serum</td>\n",
+              "      <td>Lipidomics</td>\n",
+              "      <td>447</td>\n",
+              "      <td>metabolomics__mtbls92_m_breastcancerlipidome_m...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>9</th>\n",
+              "      <td>MTBLS92_m_breastcancerlipidome_metabolite_prof...</td>\n",
+              "      <td>Breast Neoplasms</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>blood serum</td>\n",
+              "      <td>Lipidomics</td>\n",
+              "      <td>447</td>\n",
+              "      <td>metabolomics__mtbls92_m_breastcancerlipidome_m...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>10</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>Triple Negative Breast Neoplasms</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>none</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>27</td>\n",
+              "      <td>metabolomics__mtbls337_m_breast_cancer_metabol...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>11</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>Breast Neoplasms</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>none</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>27</td>\n",
+              "      <td>metabolomics__mtbls337_m_breast_cancer_metabol...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>12</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>Neoplasms</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>none</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>27</td>\n",
+              "      <td>metabolomics__mtbls337_m_breast_cancer_metabol...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>13</th>\n",
+              "      <td>MTBLS626_m_mtbls626_metabolite_profiling_NMR_s...</td>\n",
+              "      <td>Neoplasms</td>\n",
+              "      <td>Mus musculus</td>\n",
+              "      <td>mammary gland</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>144</td>\n",
+              "      <td>metabolomics__mtbls626_m_mtbls626_metabolite_p...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14</th>\n",
+              "      <td>MTBLS626_m_mtbls626_metabolite_profiling_NMR_s...</td>\n",
+              "      <td>Neoplasms</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>mammary gland</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>144</td>\n",
+              "      <td>metabolomics__mtbls626_m_mtbls626_metabolite_p...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>15</th>\n",
+              "      <td>MTBLS626_m_mtbls626_metabolite_profiling_NMR_s...</td>\n",
+              "      <td>Breast Neoplasms</td>\n",
+              "      <td>Mus musculus</td>\n",
+              "      <td>mammary gland</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>144</td>\n",
+              "      <td>metabolomics__mtbls626_m_mtbls626_metabolite_p...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>16</th>\n",
+              "      <td>MTBLS626_m_mtbls626_metabolite_profiling_NMR_s...</td>\n",
+              "      <td>Breast Neoplasms</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>mammary gland</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>144</td>\n",
+              "      <td>metabolomics__mtbls626_m_mtbls626_metabolite_p...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>17</th>\n",
+              "      <td>MTBLS669_m_mtbls669_NMR_spectroscopy</td>\n",
+              "      <td>Carcinoma, Intraductal, Noninfiltrating</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>none</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>12</td>\n",
+              "      <td>metabolomics__mtbls669_m_mtbls669_nmr_spectros...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>18</th>\n",
+              "      <td>MTBLS669_m_mtbls669_NMR_spectroscopy</td>\n",
+              "      <td>Hypoxia</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>none</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>12</td>\n",
+              "      <td>metabolomics__mtbls669_m_mtbls669_nmr_spectros...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>19</th>\n",
+              "      <td>MTBLS669_m_mtbls669_NMR_spectroscopy</td>\n",
+              "      <td>Breast Neoplasms</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>none</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>12</td>\n",
+              "      <td>metabolomics__mtbls669_m_mtbls669_nmr_spectros...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>20</th>\n",
+              "      <td>MTBLS669_m_mtbls669_NMR_spectroscopy</td>\n",
+              "      <td>Neoplasms</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>none</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>12</td>\n",
+              "      <td>metabolomics__mtbls669_m_mtbls669_nmr_spectros...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>21</th>\n",
+              "      <td>MTBLS678_m_mtbls678_NMR_spectroscopy</td>\n",
+              "      <td>Triple Negative Breast Neoplasms</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>none</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>33</td>\n",
+              "      <td>metabolomics__mtbls678_m_mtbls678_nmr_spectros...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>22</th>\n",
+              "      <td>MTBLS678_m_mtbls678_NMR_spectroscopy</td>\n",
+              "      <td>Neoplasms</td>\n",
+              "      <td>Homo sapiens</td>\n",
+              "      <td>none</td>\n",
+              "      <td>Metabolomics</td>\n",
+              "      <td>33</td>\n",
+              "      <td>metabolomics__mtbls678_m_mtbls678_nmr_spectros...</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                                           dataset_id  \\\n",
+              "0                MTBLS1066_m_mtbls1066_NEG_HILIC_LCMS   \n",
+              "1                MTBLS1066_m_mtbls1066_NEG_HILIC_LCMS   \n",
+              "2                   MTBLS1066_m_mtbls1066_NEG_RP_LCMS   \n",
+              "3                   MTBLS1066_m_mtbls1066_NEG_RP_LCMS   \n",
+              "4                MTBLS1066_m_mtbls1066_POS_HILIC_LCMS   \n",
+              "5                MTBLS1066_m_mtbls1066_POS_HILIC_LCMS   \n",
+              "6                   MTBLS1066_m_mtbls1066_POS_RP_LCMS   \n",
+              "7                   MTBLS1066_m_mtbls1066_POS_RP_LCMS   \n",
+              "8   MTBLS92_m_breastcancerlipidome_metabolite_prof...   \n",
+              "9   MTBLS92_m_breastcancerlipidome_metabolite_prof...   \n",
+              "10  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "11  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "12  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "13  MTBLS626_m_mtbls626_metabolite_profiling_NMR_s...   \n",
+              "14  MTBLS626_m_mtbls626_metabolite_profiling_NMR_s...   \n",
+              "15  MTBLS626_m_mtbls626_metabolite_profiling_NMR_s...   \n",
+              "16  MTBLS626_m_mtbls626_metabolite_profiling_NMR_s...   \n",
+              "17               MTBLS669_m_mtbls669_NMR_spectroscopy   \n",
+              "18               MTBLS669_m_mtbls669_NMR_spectroscopy   \n",
+              "19               MTBLS669_m_mtbls669_NMR_spectroscopy   \n",
+              "20               MTBLS669_m_mtbls669_NMR_spectroscopy   \n",
+              "21               MTBLS678_m_mtbls678_NMR_spectroscopy   \n",
+              "22               MTBLS678_m_mtbls678_NMR_spectroscopy   \n",
+              "\n",
+              "                                    disease      organism         tissue  \\\n",
+              "0                                 Neoplasms  Mus musculus   blood plasma   \n",
+              "1                          Breast Neoplasms  Mus musculus   blood plasma   \n",
+              "2                                 Neoplasms  Mus musculus   blood plasma   \n",
+              "3                          Breast Neoplasms  Mus musculus   blood plasma   \n",
+              "4                                 Neoplasms  Mus musculus   blood plasma   \n",
+              "5                          Breast Neoplasms  Mus musculus   blood plasma   \n",
+              "6                                 Neoplasms  Mus musculus   blood plasma   \n",
+              "7                          Breast Neoplasms  Mus musculus   blood plasma   \n",
+              "8                                 Neoplasms  Homo sapiens    blood serum   \n",
+              "9                          Breast Neoplasms  Homo sapiens    blood serum   \n",
+              "10         Triple Negative Breast Neoplasms  Homo sapiens           none   \n",
+              "11                         Breast Neoplasms  Homo sapiens           none   \n",
+              "12                                Neoplasms  Homo sapiens           none   \n",
+              "13                                Neoplasms  Mus musculus  mammary gland   \n",
+              "14                                Neoplasms  Homo sapiens  mammary gland   \n",
+              "15                         Breast Neoplasms  Mus musculus  mammary gland   \n",
+              "16                         Breast Neoplasms  Homo sapiens  mammary gland   \n",
+              "17  Carcinoma, Intraductal, Noninfiltrating  Homo sapiens           none   \n",
+              "18                                  Hypoxia  Homo sapiens           none   \n",
+              "19                         Breast Neoplasms  Homo sapiens           none   \n",
+              "20                                Neoplasms  Homo sapiens           none   \n",
+              "21         Triple Negative Breast Neoplasms  Homo sapiens           none   \n",
+              "22                                Neoplasms  Homo sapiens           none   \n",
+              "\n",
+              "       data_type  total_num_samples  \\\n",
+              "0   Metabolomics                  7   \n",
+              "1   Metabolomics                  7   \n",
+              "2   Metabolomics                  7   \n",
+              "3   Metabolomics                  7   \n",
+              "4   Metabolomics                  7   \n",
+              "5   Metabolomics                  7   \n",
+              "6   Metabolomics                  7   \n",
+              "7   Metabolomics                  7   \n",
+              "8     Lipidomics                447   \n",
+              "9     Lipidomics                447   \n",
+              "10  Metabolomics                 27   \n",
+              "11  Metabolomics                 27   \n",
+              "12  Metabolomics                 27   \n",
+              "13  Metabolomics                144   \n",
+              "14  Metabolomics                144   \n",
+              "15  Metabolomics                144   \n",
+              "16  Metabolomics                144   \n",
+              "17  Metabolomics                 12   \n",
+              "18  Metabolomics                 12   \n",
+              "19  Metabolomics                 12   \n",
+              "20  Metabolomics                 12   \n",
+              "21  Metabolomics                 33   \n",
+              "22  Metabolomics                 33   \n",
+              "\n",
+              "                                      data_table_name  \n",
+              "0   metabolomics__mtbls1066_m_mtbls1066_neg_hilic_...  \n",
+              "1   metabolomics__mtbls1066_m_mtbls1066_neg_hilic_...  \n",
+              "2     metabolomics__mtbls1066_m_mtbls1066_neg_rp_lcms  \n",
+              "3     metabolomics__mtbls1066_m_mtbls1066_neg_rp_lcms  \n",
+              "4   metabolomics__mtbls1066_m_mtbls1066_pos_hilic_...  \n",
+              "5   metabolomics__mtbls1066_m_mtbls1066_pos_hilic_...  \n",
+              "6     metabolomics__mtbls1066_m_mtbls1066_pos_rp_lcms  \n",
+              "7     metabolomics__mtbls1066_m_mtbls1066_pos_rp_lcms  \n",
+              "8   metabolomics__mtbls92_m_breastcancerlipidome_m...  \n",
+              "9   metabolomics__mtbls92_m_breastcancerlipidome_m...  \n",
+              "10  metabolomics__mtbls337_m_breast_cancer_metabol...  \n",
+              "11  metabolomics__mtbls337_m_breast_cancer_metabol...  \n",
+              "12  metabolomics__mtbls337_m_breast_cancer_metabol...  \n",
+              "13  metabolomics__mtbls626_m_mtbls626_metabolite_p...  \n",
+              "14  metabolomics__mtbls626_m_mtbls626_metabolite_p...  \n",
+              "15  metabolomics__mtbls626_m_mtbls626_metabolite_p...  \n",
+              "16  metabolomics__mtbls626_m_mtbls626_metabolite_p...  \n",
+              "17  metabolomics__mtbls669_m_mtbls669_nmr_spectros...  \n",
+              "18  metabolomics__mtbls669_m_mtbls669_nmr_spectros...  \n",
+              "19  metabolomics__mtbls669_m_mtbls669_nmr_spectros...  \n",
+              "20  metabolomics__mtbls669_m_mtbls669_nmr_spectros...  \n",
+              "21  metabolomics__mtbls678_m_mtbls678_nmr_spectros...  \n",
+              "22  metabolomics__mtbls678_m_mtbls678_nmr_spectros...  "
+            ]
+          },
+          "execution_count": 104,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "#using reccomendation function - searches for realted terms \n",
+        "query = f\"\"\"SELECT dataset_id,disease,organism,tissue,data_type,total_num_samples,data_table_name FROM metabolomics.datasets \n",
+        "        CROSS JOIN UNNEST(curated_disease) AS t(disease) \n",
+        "        CROSS JOIN UNNEST(curated_tissue) AS t(tissue) \n",
+        "        CROSS JOIN UNNEST(curated_organism) AS t(organism)\n",
+        "        WHERE CONTAINS(curated_disease, recommend('curated_disease', '{disease_name}', 'related'))\"\"\"\n",
+        "dataset_df = omixatlas.query_metadata(query)\n",
+        "dataset_df"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "source": [
+        "### Querying sample-level metadata for a dataset of interest"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 31,
+      "metadata": {
+        "kernel": "Python3",
+        "scrolled": true
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Query execution succeeded (time taken: 1.62 seconds, data scanned: 0.000 MB)\n",
+            "Fetched 23 rows\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>column_name</th>\n",
+              "      <th>column_type</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>14</th>\n",
+              "      <td>cohort_id</td>\n",
+              "      <td>bigint</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>11</th>\n",
+              "      <td>cohort_name</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>10</th>\n",
+              "      <td>control</td>\n",
+              "      <td>bigint</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>curated_cell_line</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>21</th>\n",
+              "      <td>curated_cell_type</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>curated_cohort_name</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>12</th>\n",
+              "      <td>curated_control</td>\n",
+              "      <td>bigint</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>curated_disease</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>9</th>\n",
+              "      <td>curated_drug</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>curated_gene_modified</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>20</th>\n",
+              "      <td>curated_genetic_modification_type</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>17</th>\n",
+              "      <td>curated_tissue</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>18</th>\n",
+              "      <td>data_id</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>dataset_id</td>\n",
+              "      <td>array&lt;string&gt;</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>id_key</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>22</th>\n",
+              "      <td>is_current</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>19</th>\n",
+              "      <td>name</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>sample_id</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>13</th>\n",
+              "      <td>src_dataset_id</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>src_repo</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>src_uri</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>16</th>\n",
+              "      <td>timestamp_</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>15</th>\n",
+              "      <td>version</td>\n",
+              "      <td>bigint</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                          column_name    column_type\n",
+              "14                          cohort_id         bigint\n",
+              "11                        cohort_name         string\n",
+              "10                            control         bigint\n",
+              "6                   curated_cell_line         string\n",
+              "21                  curated_cell_type         string\n",
+              "7                 curated_cohort_name         string\n",
+              "12                    curated_control         bigint\n",
+              "8                     curated_disease         string\n",
+              "9                        curated_drug         string\n",
+              "5               curated_gene_modified         string\n",
+              "20  curated_genetic_modification_type         string\n",
+              "17                     curated_tissue         string\n",
+              "18                            data_id         string\n",
+              "3                          dataset_id  array<string>\n",
+              "1                              id_key         string\n",
+              "22                         is_current         string\n",
+              "19                               name         string\n",
+              "4                           sample_id         string\n",
+              "13                     src_dataset_id         string\n",
+              "0                            src_repo         string\n",
+              "2                             src_uri         string\n",
+              "16                         timestamp_         string\n",
+              "15                            version         bigint"
+            ]
+          },
+          "execution_count": 31,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "# Sample level metadata schema for metabolomics OA\n",
+        "query = \"DESCRIBE metabolomics.samples\"\n",
+        "res2 = omixatlas.query_metadata(query)\n",
+        "res2.sort_values(\"column_name\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 29,
+      "metadata": {
+        "kernel": "Python3",
+        "scrolled": true
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Query execution succeeded (time taken: 1.31 seconds, data scanned: 0.527 MB)\n",
+            "Fetched 27 rows\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>src_dataset_id</th>\n",
+              "      <th>sample_id</th>\n",
+              "      <th>curated_disease</th>\n",
+              "      <th>curated_tissue</th>\n",
+              "      <th>curated_cell_line</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>HCC1937_C1</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>HCC-1937 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>HCC1937_C2</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>HCC-1937 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>HCC1937_C3</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>HCC-1937 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>HCC1937_PI1</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>HCC-1937 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>HCC1937_PI2</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>HCC-1937 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>HCC1937_PI3</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>HCC-1937 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>HCC1937_R1</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>HCC-1937 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>HCC1937_R2</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>HCC-1937 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>HCC1937_R3</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>HCC-1937 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>9</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MCF7_C1</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MCF-7 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>10</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MCF7_C2</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MCF-7 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>11</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MCF7_C3</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MCF-7 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>12</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MCF7_PI1</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MCF-7 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>13</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MCF7_PI2</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MCF-7 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MCF7_PI3</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MCF-7 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>15</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MCF7_R1</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MCF-7 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>16</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MCF7_R2</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MCF-7 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>17</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MCF7_R3</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MCF-7 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>18</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MDAMB231_C1</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MDA-MB-231 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>19</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MDAMB231_C2</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MDA-MB-231 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>20</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MDAMB231_C3</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MDA-MB-231 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>21</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MDAMB231_PI1</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MDA-MB-231 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>22</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MDAMB231_PI2</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MDA-MB-231 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>23</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MDAMB231_PI3</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MDA-MB-231 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>24</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MDAMB231_R1</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MDA-MB-231 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MDAMB231_R2</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MDA-MB-231 cell</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>26</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>MDAMB231_R3</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>none</td>\n",
+              "      <td>MDA-MB-231 cell</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                                       src_dataset_id     sample_id  \\\n",
+              "0   MTBLS337_m_breast_cancer_metabolomics_metaboli...    HCC1937_C1   \n",
+              "1   MTBLS337_m_breast_cancer_metabolomics_metaboli...    HCC1937_C2   \n",
+              "2   MTBLS337_m_breast_cancer_metabolomics_metaboli...    HCC1937_C3   \n",
+              "3   MTBLS337_m_breast_cancer_metabolomics_metaboli...   HCC1937_PI1   \n",
+              "4   MTBLS337_m_breast_cancer_metabolomics_metaboli...   HCC1937_PI2   \n",
+              "5   MTBLS337_m_breast_cancer_metabolomics_metaboli...   HCC1937_PI3   \n",
+              "6   MTBLS337_m_breast_cancer_metabolomics_metaboli...    HCC1937_R1   \n",
+              "7   MTBLS337_m_breast_cancer_metabolomics_metaboli...    HCC1937_R2   \n",
+              "8   MTBLS337_m_breast_cancer_metabolomics_metaboli...    HCC1937_R3   \n",
+              "9   MTBLS337_m_breast_cancer_metabolomics_metaboli...       MCF7_C1   \n",
+              "10  MTBLS337_m_breast_cancer_metabolomics_metaboli...       MCF7_C2   \n",
+              "11  MTBLS337_m_breast_cancer_metabolomics_metaboli...       MCF7_C3   \n",
+              "12  MTBLS337_m_breast_cancer_metabolomics_metaboli...      MCF7_PI1   \n",
+              "13  MTBLS337_m_breast_cancer_metabolomics_metaboli...      MCF7_PI2   \n",
+              "14  MTBLS337_m_breast_cancer_metabolomics_metaboli...      MCF7_PI3   \n",
+              "15  MTBLS337_m_breast_cancer_metabolomics_metaboli...       MCF7_R1   \n",
+              "16  MTBLS337_m_breast_cancer_metabolomics_metaboli...       MCF7_R2   \n",
+              "17  MTBLS337_m_breast_cancer_metabolomics_metaboli...       MCF7_R3   \n",
+              "18  MTBLS337_m_breast_cancer_metabolomics_metaboli...   MDAMB231_C1   \n",
+              "19  MTBLS337_m_breast_cancer_metabolomics_metaboli...   MDAMB231_C2   \n",
+              "20  MTBLS337_m_breast_cancer_metabolomics_metaboli...   MDAMB231_C3   \n",
+              "21  MTBLS337_m_breast_cancer_metabolomics_metaboli...  MDAMB231_PI1   \n",
+              "22  MTBLS337_m_breast_cancer_metabolomics_metaboli...  MDAMB231_PI2   \n",
+              "23  MTBLS337_m_breast_cancer_metabolomics_metaboli...  MDAMB231_PI3   \n",
+              "24  MTBLS337_m_breast_cancer_metabolomics_metaboli...   MDAMB231_R1   \n",
+              "25  MTBLS337_m_breast_cancer_metabolomics_metaboli...   MDAMB231_R2   \n",
+              "26  MTBLS337_m_breast_cancer_metabolomics_metaboli...   MDAMB231_R3   \n",
+              "\n",
+              "   curated_disease curated_tissue curated_cell_line  \n",
+              "0           Normal           none     HCC-1937 cell  \n",
+              "1           Normal           none     HCC-1937 cell  \n",
+              "2           Normal           none     HCC-1937 cell  \n",
+              "3           Normal           none     HCC-1937 cell  \n",
+              "4           Normal           none     HCC-1937 cell  \n",
+              "5           Normal           none     HCC-1937 cell  \n",
+              "6           Normal           none     HCC-1937 cell  \n",
+              "7           Normal           none     HCC-1937 cell  \n",
+              "8           Normal           none     HCC-1937 cell  \n",
+              "9           Normal           none        MCF-7 cell  \n",
+              "10          Normal           none        MCF-7 cell  \n",
+              "11          Normal           none        MCF-7 cell  \n",
+              "12          Normal           none        MCF-7 cell  \n",
+              "13          Normal           none        MCF-7 cell  \n",
+              "14          Normal           none        MCF-7 cell  \n",
+              "15          Normal           none        MCF-7 cell  \n",
+              "16          Normal           none        MCF-7 cell  \n",
+              "17          Normal           none        MCF-7 cell  \n",
+              "18          Normal           none   MDA-MB-231 cell  \n",
+              "19          Normal           none   MDA-MB-231 cell  \n",
+              "20          Normal           none   MDA-MB-231 cell  \n",
+              "21          Normal           none   MDA-MB-231 cell  \n",
+              "22          Normal           none   MDA-MB-231 cell  \n",
+              "23          Normal           none   MDA-MB-231 cell  \n",
+              "24          Normal           none   MDA-MB-231 cell  \n",
+              "25          Normal           none   MDA-MB-231 cell  \n",
+              "26          Normal           none   MDA-MB-231 cell  "
+            ]
+          },
+          "execution_count": 29,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "query = \"\"\"SELECT src_dataset_id,sample_id,curated_disease,curated_tissue,curated_cell_line FROM metabolomics.samples \n",
+        "        WHERE src_dataset_id = 'MTBLS337_m_breast_cancer_metabolomics_metabolite_profiling_NMR_spectroscopy'\"\"\"\n",
+        "samples_df = omixatlas.query_metadata(query)\n",
+        "samples_df"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "source": [
+        "### Querying feature-level metadata for a dataset of interest"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Query execution succeeded (time taken: 2.04 seconds, data scanned: 0.000 MB)\n",
+            "Fetched 13 rows\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>column_name</th>\n",
+              "      <th>column_type</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>10</th>\n",
+              "      <td>data_id</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>dataset_id</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>feature_id</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>feature_value</td>\n",
+              "      <td>double</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>id_key</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>12</th>\n",
+              "      <td>is_current</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>11</th>\n",
+              "      <td>name</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>sample_id</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>src_dataset_id</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>src_repo</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>src_uri</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>9</th>\n",
+              "      <td>timestamp_</td>\n",
+              "      <td>string</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>version</td>\n",
+              "      <td>bigint</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "       column_name column_type\n",
+              "10         data_id      string\n",
+              "5       dataset_id      string\n",
+              "0       feature_id      string\n",
+              "6    feature_value      double\n",
+              "2           id_key      string\n",
+              "12      is_current      string\n",
+              "11            name      string\n",
+              "4        sample_id      string\n",
+              "7   src_dataset_id      string\n",
+              "1         src_repo      string\n",
+              "3          src_uri      string\n",
+              "9       timestamp_      string\n",
+              "8          version      bigint"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "query = \"DESCRIBE metabolomics.features\"\n",
+        "res3 = omixatlas.query_metadata(query)\n",
+        "res3.sort_values(\"column_name\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 32,
+      "metadata": {
+        "kernel": "Python3",
+        "scrolled": true
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Query execution succeeded (time taken: 1.64 seconds, data scanned: 2.871 MB)\n",
+            "Fetched 39 rows\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>src_dataset_id</th>\n",
+              "      <th>data_id</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>_1_methylnicotinamide_chebi_16797</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>_2_aminoadipate_chebi_37024</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>_2_oxoisocaproate_chebi_48430</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_alanine_chebi_16977</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>adenosine_monophosphate_chebi_16027</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_asparagine_chebi_17196</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_aspartate_chebi_17053</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>adenosine_triphosphate_chebi_15422</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>creatine_chebi_16919</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>9</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>creatine_phosphate_chebi_17287</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>10</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>formate_chebi_30751</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>11</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>fumarate_chebi_18012</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>12</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>d_glucitol_chebi_17924</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>13</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>d_glucose_chebi_4167</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_glutamic_acid_chebi_16015</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>15</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_glutamine_chebi_18050</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>16</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>glutathione_chebi_16856</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>17</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>glycine_chebi_15428</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>18</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_isoleucine_chebi_17191</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>19</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>lactate_chebi_78320</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>20</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_leucine_chebi_15603</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>21</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_lysine_chebi_18019</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>22</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_methionine_chebi_16643</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>23</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>myo_inositol_chebi_17268</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>24</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>nad_chebi_44215</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>o_phosphocholine_chebi_18132</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>26</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>pantothenate_chebi_7916</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>27</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_phenylalanine_chebi_17295</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>28</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_proline_chebi_17203</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>29</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>pyroglutamic_acid_chebi_16010</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>30</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>serine_chebi_17822</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>31</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>sn_glycero_3_phosphocholine_chebi_16870</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>32</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>taurine_chebi_15891</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>33</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_threonine_chebi_16857</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>34</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_tryptophan_chebi_16828</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>35</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_tyrosine_chebi_17895</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>36</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>udp_n_acetylglucosamine_chebi_16264</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>37</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>l_valine_chebi_16414</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>38</th>\n",
+              "      <td>MTBLS337_m_breast_cancer_metabolomics_metaboli...</td>\n",
+              "      <td>beta_alanine_chebi_16958</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                                       src_dataset_id  \\\n",
+              "0   MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "1   MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "2   MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "3   MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "4   MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "5   MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "6   MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "7   MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "8   MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "9   MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "10  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "11  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "12  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "13  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "14  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "15  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "16  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "17  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "18  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "19  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "20  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "21  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "22  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "23  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "24  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "25  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "26  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "27  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "28  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "29  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "30  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "31  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "32  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "33  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "34  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "35  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "36  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "37  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "38  MTBLS337_m_breast_cancer_metabolomics_metaboli...   \n",
+              "\n",
+              "                                    data_id  \n",
+              "0         _1_methylnicotinamide_chebi_16797  \n",
+              "1               _2_aminoadipate_chebi_37024  \n",
+              "2             _2_oxoisocaproate_chebi_48430  \n",
+              "3                     l_alanine_chebi_16977  \n",
+              "4       adenosine_monophosphate_chebi_16027  \n",
+              "5                  l_asparagine_chebi_17196  \n",
+              "6                   l_aspartate_chebi_17053  \n",
+              "7        adenosine_triphosphate_chebi_15422  \n",
+              "8                      creatine_chebi_16919  \n",
+              "9            creatine_phosphate_chebi_17287  \n",
+              "10                      formate_chebi_30751  \n",
+              "11                     fumarate_chebi_18012  \n",
+              "12                   d_glucitol_chebi_17924  \n",
+              "13                     d_glucose_chebi_4167  \n",
+              "14              l_glutamic_acid_chebi_16015  \n",
+              "15                  l_glutamine_chebi_18050  \n",
+              "16                  glutathione_chebi_16856  \n",
+              "17                      glycine_chebi_15428  \n",
+              "18                 l_isoleucine_chebi_17191  \n",
+              "19                      lactate_chebi_78320  \n",
+              "20                    l_leucine_chebi_15603  \n",
+              "21                     l_lysine_chebi_18019  \n",
+              "22                 l_methionine_chebi_16643  \n",
+              "23                 myo_inositol_chebi_17268  \n",
+              "24                          nad_chebi_44215  \n",
+              "25             o_phosphocholine_chebi_18132  \n",
+              "26                  pantothenate_chebi_7916  \n",
+              "27              l_phenylalanine_chebi_17295  \n",
+              "28                    l_proline_chebi_17203  \n",
+              "29            pyroglutamic_acid_chebi_16010  \n",
+              "30                       serine_chebi_17822  \n",
+              "31  sn_glycero_3_phosphocholine_chebi_16870  \n",
+              "32                      taurine_chebi_15891  \n",
+              "33                  l_threonine_chebi_16857  \n",
+              "34                 l_tryptophan_chebi_16828  \n",
+              "35                   l_tyrosine_chebi_17895  \n",
+              "36      udp_n_acetylglucosamine_chebi_16264  \n",
+              "37                     l_valine_chebi_16414  \n",
+              "38                 beta_alanine_chebi_16958  "
+            ]
+          },
+          "execution_count": 32,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "query = \"SELECT src_dataset_id,data_id FROM metabolomics.features WHERE src_dataset_id = 'MTBLS337_m_breast_cancer_metabolomics_metabolite_profiling_NMR_spectroscopy'\"\n",
+        "feature_df = omixatlas.query_metadata(query)\n",
+        "feature_df"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "source": [
+        "### Querying data matrix of dataset of interest"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 33,
+      "metadata": {
+        "kernel": "Python3",
+        "scrolled": true
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Query execution succeeded (time taken: 1.07 seconds, data scanned: 0.007 MB)\n",
+            "Fetched 39 rows\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>rid</th>\n",
+              "      <th>hcc1937_c1</th>\n",
+              "      <th>hcc1937_c2</th>\n",
+              "      <th>hcc1937_c3</th>\n",
+              "      <th>hcc1937_pi1</th>\n",
+              "      <th>hcc1937_pi2</th>\n",
+              "      <th>hcc1937_pi3</th>\n",
+              "      <th>hcc1937_r1</th>\n",
+              "      <th>hcc1937_r2</th>\n",
+              "      <th>hcc1937_r3</th>\n",
+              "      <th>...</th>\n",
+              "      <th>mdamb231_c1</th>\n",
+              "      <th>mdamb231_c2</th>\n",
+              "      <th>mdamb231_c3</th>\n",
+              "      <th>mdamb231_pi1</th>\n",
+              "      <th>mdamb231_pi2</th>\n",
+              "      <th>mdamb231_pi3</th>\n",
+              "      <th>mdamb231_r1</th>\n",
+              "      <th>mdamb231_r2</th>\n",
+              "      <th>mdamb231_r3</th>\n",
+              "      <th>row_id</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>1-Methylnicotinamide_CHEBI:16797</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>24.4</td>\n",
+              "      <td>22.4</td>\n",
+              "      <td>22.2</td>\n",
+              "      <td>27.9</td>\n",
+              "      <td>27.0</td>\n",
+              "      <td>29.7</td>\n",
+              "      <td>21.9</td>\n",
+              "      <td>25.7</td>\n",
+              "      <td>21.5</td>\n",
+              "      <td>_1_methylnicotinamide_chebi_16797</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>2-Aminoadipate_CHEBI:37024</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>51.8</td>\n",
+              "      <td>48.1</td>\n",
+              "      <td>44.5</td>\n",
+              "      <td>28.7</td>\n",
+              "      <td>17.6</td>\n",
+              "      <td>28.0</td>\n",
+              "      <td>38.3</td>\n",
+              "      <td>44.6</td>\n",
+              "      <td>38.0</td>\n",
+              "      <td>_2_aminoadipate_chebi_37024</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>2-Oxoisocaproate_CHEBI:48430</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>_2_oxoisocaproate_chebi_48430</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>L-Alanine_CHEBI:16977</td>\n",
+              "      <td>396.7</td>\n",
+              "      <td>381.1</td>\n",
+              "      <td>403.8</td>\n",
+              "      <td>393.8</td>\n",
+              "      <td>370.9</td>\n",
+              "      <td>380.6</td>\n",
+              "      <td>425.1</td>\n",
+              "      <td>437.8</td>\n",
+              "      <td>433.9</td>\n",
+              "      <td>...</td>\n",
+              "      <td>77.4</td>\n",
+              "      <td>82.1</td>\n",
+              "      <td>79.8</td>\n",
+              "      <td>63.2</td>\n",
+              "      <td>53.1</td>\n",
+              "      <td>58.4</td>\n",
+              "      <td>66.7</td>\n",
+              "      <td>73.5</td>\n",
+              "      <td>72.0</td>\n",
+              "      <td>l_alanine_chebi_16977</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>Adenosine monophosphate_CHEBI:16027</td>\n",
+              "      <td>11.6</td>\n",
+              "      <td>12.5</td>\n",
+              "      <td>13.1</td>\n",
+              "      <td>6.6</td>\n",
+              "      <td>9.2</td>\n",
+              "      <td>6.6</td>\n",
+              "      <td>7.1</td>\n",
+              "      <td>8.9</td>\n",
+              "      <td>10.1</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>adenosine_monophosphate_chebi_16027</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>L-Asparagine_CHEBI:17196</td>\n",
+              "      <td>13.5</td>\n",
+              "      <td>13.5</td>\n",
+              "      <td>14.3</td>\n",
+              "      <td>8.7</td>\n",
+              "      <td>11.2</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>11.6</td>\n",
+              "      <td>12.5</td>\n",
+              "      <td>13.4</td>\n",
+              "      <td>...</td>\n",
+              "      <td>25.8</td>\n",
+              "      <td>27.0</td>\n",
+              "      <td>27.2</td>\n",
+              "      <td>24.7</td>\n",
+              "      <td>23.3</td>\n",
+              "      <td>23.5</td>\n",
+              "      <td>21.7</td>\n",
+              "      <td>19.1</td>\n",
+              "      <td>19.1</td>\n",
+              "      <td>l_asparagine_chebi_17196</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>L-Aspartate_CHEBI:17053</td>\n",
+              "      <td>103.7</td>\n",
+              "      <td>99.9</td>\n",
+              "      <td>94.0</td>\n",
+              "      <td>89.6</td>\n",
+              "      <td>80.8</td>\n",
+              "      <td>90.3</td>\n",
+              "      <td>105.1</td>\n",
+              "      <td>98.1</td>\n",
+              "      <td>98.4</td>\n",
+              "      <td>...</td>\n",
+              "      <td>67.6</td>\n",
+              "      <td>66.7</td>\n",
+              "      <td>66.5</td>\n",
+              "      <td>57.1</td>\n",
+              "      <td>51.2</td>\n",
+              "      <td>56.7</td>\n",
+              "      <td>48.0</td>\n",
+              "      <td>53.9</td>\n",
+              "      <td>49.5</td>\n",
+              "      <td>l_aspartate_chebi_17053</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>Adenosine triphosphate_CHEBI:15422</td>\n",
+              "      <td>66.3</td>\n",
+              "      <td>61.6</td>\n",
+              "      <td>67.8</td>\n",
+              "      <td>75.7</td>\n",
+              "      <td>67.7</td>\n",
+              "      <td>71.9</td>\n",
+              "      <td>70.8</td>\n",
+              "      <td>65.7</td>\n",
+              "      <td>65.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>167.3</td>\n",
+              "      <td>188.5</td>\n",
+              "      <td>181.0</td>\n",
+              "      <td>160.1</td>\n",
+              "      <td>128.8</td>\n",
+              "      <td>147.0</td>\n",
+              "      <td>151.9</td>\n",
+              "      <td>150.6</td>\n",
+              "      <td>142.3</td>\n",
+              "      <td>adenosine_triphosphate_chebi_15422</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>Creatine_CHEBI:16919</td>\n",
+              "      <td>22.5</td>\n",
+              "      <td>22.5</td>\n",
+              "      <td>21.1</td>\n",
+              "      <td>19.9</td>\n",
+              "      <td>20.1</td>\n",
+              "      <td>20.4</td>\n",
+              "      <td>22.5</td>\n",
+              "      <td>24.3</td>\n",
+              "      <td>23.1</td>\n",
+              "      <td>...</td>\n",
+              "      <td>18.8</td>\n",
+              "      <td>18.5</td>\n",
+              "      <td>18.7</td>\n",
+              "      <td>12.2</td>\n",
+              "      <td>11.2</td>\n",
+              "      <td>12.2</td>\n",
+              "      <td>16.3</td>\n",
+              "      <td>18.1</td>\n",
+              "      <td>16.9</td>\n",
+              "      <td>creatine_chebi_16919</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>9</th>\n",
+              "      <td>Creatine phosphate_CHEBI:17287</td>\n",
+              "      <td>23.5</td>\n",
+              "      <td>21.6</td>\n",
+              "      <td>24.5</td>\n",
+              "      <td>27.7</td>\n",
+              "      <td>24.6</td>\n",
+              "      <td>26.9</td>\n",
+              "      <td>23.2</td>\n",
+              "      <td>27.6</td>\n",
+              "      <td>27.8</td>\n",
+              "      <td>...</td>\n",
+              "      <td>20.6</td>\n",
+              "      <td>20.8</td>\n",
+              "      <td>18.8</td>\n",
+              "      <td>12.2</td>\n",
+              "      <td>13.1</td>\n",
+              "      <td>14.4</td>\n",
+              "      <td>19.4</td>\n",
+              "      <td>21.2</td>\n",
+              "      <td>19.6</td>\n",
+              "      <td>creatine_phosphate_chebi_17287</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>10</th>\n",
+              "      <td>Formate_CHEBI:30751</td>\n",
+              "      <td>14.5</td>\n",
+              "      <td>16.1</td>\n",
+              "      <td>13.8</td>\n",
+              "      <td>16.7</td>\n",
+              "      <td>17.8</td>\n",
+              "      <td>17.0</td>\n",
+              "      <td>18.6</td>\n",
+              "      <td>20.2</td>\n",
+              "      <td>18.8</td>\n",
+              "      <td>...</td>\n",
+              "      <td>24.7</td>\n",
+              "      <td>17.9</td>\n",
+              "      <td>19.8</td>\n",
+              "      <td>29.5</td>\n",
+              "      <td>32.3</td>\n",
+              "      <td>24.8</td>\n",
+              "      <td>19.9</td>\n",
+              "      <td>19.4</td>\n",
+              "      <td>18.4</td>\n",
+              "      <td>formate_chebi_30751</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>11</th>\n",
+              "      <td>Fumarate_CHEBI:18012</td>\n",
+              "      <td>3.4</td>\n",
+              "      <td>3.6</td>\n",
+              "      <td>3.8</td>\n",
+              "      <td>3.2</td>\n",
+              "      <td>3.0</td>\n",
+              "      <td>3.1</td>\n",
+              "      <td>3.8</td>\n",
+              "      <td>3.9</td>\n",
+              "      <td>3.7</td>\n",
+              "      <td>...</td>\n",
+              "      <td>4.1</td>\n",
+              "      <td>3.4</td>\n",
+              "      <td>3.5</td>\n",
+              "      <td>2.9</td>\n",
+              "      <td>3.2</td>\n",
+              "      <td>2.4</td>\n",
+              "      <td>3.6</td>\n",
+              "      <td>3.8</td>\n",
+              "      <td>3.3</td>\n",
+              "      <td>fumarate_chebi_18012</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>12</th>\n",
+              "      <td>D-Glucitol_CHEBI:17924</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>97.0</td>\n",
+              "      <td>88.8</td>\n",
+              "      <td>103.4</td>\n",
+              "      <td>161.1</td>\n",
+              "      <td>190.4</td>\n",
+              "      <td>128.6</td>\n",
+              "      <td>90.5</td>\n",
+              "      <td>110.0</td>\n",
+              "      <td>109.4</td>\n",
+              "      <td>d_glucitol_chebi_17924</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>13</th>\n",
+              "      <td>D-Glucose_CHEBI:4167</td>\n",
+              "      <td>168.0</td>\n",
+              "      <td>201.4</td>\n",
+              "      <td>206.8</td>\n",
+              "      <td>213.4</td>\n",
+              "      <td>170.4</td>\n",
+              "      <td>194.4</td>\n",
+              "      <td>312.2</td>\n",
+              "      <td>272.4</td>\n",
+              "      <td>336.2</td>\n",
+              "      <td>...</td>\n",
+              "      <td>165.1</td>\n",
+              "      <td>184.2</td>\n",
+              "      <td>198.4</td>\n",
+              "      <td>290.8</td>\n",
+              "      <td>240.7</td>\n",
+              "      <td>300.3</td>\n",
+              "      <td>171.3</td>\n",
+              "      <td>154.9</td>\n",
+              "      <td>154.2</td>\n",
+              "      <td>d_glucose_chebi_4167</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14</th>\n",
+              "      <td>L-Glutamic acid_CHEBI:16015</td>\n",
+              "      <td>368.0</td>\n",
+              "      <td>351.9</td>\n",
+              "      <td>388.7</td>\n",
+              "      <td>317.7</td>\n",
+              "      <td>303.4</td>\n",
+              "      <td>313.7</td>\n",
+              "      <td>367.7</td>\n",
+              "      <td>378.1</td>\n",
+              "      <td>388.4</td>\n",
+              "      <td>...</td>\n",
+              "      <td>1190.5</td>\n",
+              "      <td>1194.4</td>\n",
+              "      <td>1203.6</td>\n",
+              "      <td>924.6</td>\n",
+              "      <td>866.5</td>\n",
+              "      <td>913.1</td>\n",
+              "      <td>991.0</td>\n",
+              "      <td>1155.5</td>\n",
+              "      <td>1063.7</td>\n",
+              "      <td>l_glutamic_acid_chebi_16015</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>15</th>\n",
+              "      <td>L-Glutamine_CHEBI:18050</td>\n",
+              "      <td>450.2</td>\n",
+              "      <td>449.7</td>\n",
+              "      <td>474.6</td>\n",
+              "      <td>483.3</td>\n",
+              "      <td>448.0</td>\n",
+              "      <td>471.6</td>\n",
+              "      <td>475.0</td>\n",
+              "      <td>496.3</td>\n",
+              "      <td>514.9</td>\n",
+              "      <td>...</td>\n",
+              "      <td>389.8</td>\n",
+              "      <td>403.0</td>\n",
+              "      <td>387.5</td>\n",
+              "      <td>285.4</td>\n",
+              "      <td>249.6</td>\n",
+              "      <td>289.2</td>\n",
+              "      <td>354.2</td>\n",
+              "      <td>369.3</td>\n",
+              "      <td>366.4</td>\n",
+              "      <td>l_glutamine_chebi_18050</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>16</th>\n",
+              "      <td>Glutathione_CHEBI:16856</td>\n",
+              "      <td>207.4</td>\n",
+              "      <td>196.4</td>\n",
+              "      <td>205.9</td>\n",
+              "      <td>211.5</td>\n",
+              "      <td>191.6</td>\n",
+              "      <td>202.0</td>\n",
+              "      <td>202.4</td>\n",
+              "      <td>202.3</td>\n",
+              "      <td>207.5</td>\n",
+              "      <td>...</td>\n",
+              "      <td>376.8</td>\n",
+              "      <td>394.3</td>\n",
+              "      <td>388.8</td>\n",
+              "      <td>344.5</td>\n",
+              "      <td>320.1</td>\n",
+              "      <td>334.3</td>\n",
+              "      <td>331.9</td>\n",
+              "      <td>365.5</td>\n",
+              "      <td>355.5</td>\n",
+              "      <td>glutathione_chebi_16856</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>17</th>\n",
+              "      <td>Glycine_CHEBI:15428</td>\n",
+              "      <td>561.5</td>\n",
+              "      <td>550.2</td>\n",
+              "      <td>641.5</td>\n",
+              "      <td>709.6</td>\n",
+              "      <td>689.4</td>\n",
+              "      <td>704.7</td>\n",
+              "      <td>722.2</td>\n",
+              "      <td>761.5</td>\n",
+              "      <td>766.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>1083.3</td>\n",
+              "      <td>1106.8</td>\n",
+              "      <td>1077.4</td>\n",
+              "      <td>1031.8</td>\n",
+              "      <td>980.7</td>\n",
+              "      <td>996.2</td>\n",
+              "      <td>999.4</td>\n",
+              "      <td>1063.5</td>\n",
+              "      <td>1042.4</td>\n",
+              "      <td>glycine_chebi_15428</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>18</th>\n",
+              "      <td>L-Isoleucine_CHEBI:17191</td>\n",
+              "      <td>68.7</td>\n",
+              "      <td>67.4</td>\n",
+              "      <td>71.5</td>\n",
+              "      <td>71.8</td>\n",
+              "      <td>67.5</td>\n",
+              "      <td>69.5</td>\n",
+              "      <td>75.8</td>\n",
+              "      <td>77.5</td>\n",
+              "      <td>80.3</td>\n",
+              "      <td>...</td>\n",
+              "      <td>58.0</td>\n",
+              "      <td>59.8</td>\n",
+              "      <td>61.1</td>\n",
+              "      <td>47.2</td>\n",
+              "      <td>40.9</td>\n",
+              "      <td>47.7</td>\n",
+              "      <td>53.3</td>\n",
+              "      <td>58.9</td>\n",
+              "      <td>57.2</td>\n",
+              "      <td>l_isoleucine_chebi_17191</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>19</th>\n",
+              "      <td>Lactate_CHEBI:78320</td>\n",
+              "      <td>402.9</td>\n",
+              "      <td>447.2</td>\n",
+              "      <td>415.6</td>\n",
+              "      <td>507.4</td>\n",
+              "      <td>399.8</td>\n",
+              "      <td>419.6</td>\n",
+              "      <td>643.8</td>\n",
+              "      <td>553.5</td>\n",
+              "      <td>670.1</td>\n",
+              "      <td>...</td>\n",
+              "      <td>518.9</td>\n",
+              "      <td>512.4</td>\n",
+              "      <td>550.5</td>\n",
+              "      <td>465.0</td>\n",
+              "      <td>402.9</td>\n",
+              "      <td>466.3</td>\n",
+              "      <td>527.0</td>\n",
+              "      <td>647.5</td>\n",
+              "      <td>611.6</td>\n",
+              "      <td>lactate_chebi_78320</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>20</th>\n",
+              "      <td>L-Leucine_CHEBI:15603</td>\n",
+              "      <td>54.4</td>\n",
+              "      <td>53.8</td>\n",
+              "      <td>56.1</td>\n",
+              "      <td>53.6</td>\n",
+              "      <td>51.6</td>\n",
+              "      <td>53.3</td>\n",
+              "      <td>57.6</td>\n",
+              "      <td>56.7</td>\n",
+              "      <td>59.4</td>\n",
+              "      <td>...</td>\n",
+              "      <td>43.0</td>\n",
+              "      <td>43.5</td>\n",
+              "      <td>44.5</td>\n",
+              "      <td>36.4</td>\n",
+              "      <td>32.9</td>\n",
+              "      <td>36.8</td>\n",
+              "      <td>39.9</td>\n",
+              "      <td>45.3</td>\n",
+              "      <td>43.7</td>\n",
+              "      <td>l_leucine_chebi_15603</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>21</th>\n",
+              "      <td>L-Lysine_CHEBI:18019</td>\n",
+              "      <td>25.4</td>\n",
+              "      <td>25.2</td>\n",
+              "      <td>25.9</td>\n",
+              "      <td>23.1</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>21.4</td>\n",
+              "      <td>30.4</td>\n",
+              "      <td>29.8</td>\n",
+              "      <td>32.6</td>\n",
+              "      <td>...</td>\n",
+              "      <td>29.2</td>\n",
+              "      <td>31.1</td>\n",
+              "      <td>35.7</td>\n",
+              "      <td>32.0</td>\n",
+              "      <td>33.3</td>\n",
+              "      <td>34.2</td>\n",
+              "      <td>28.4</td>\n",
+              "      <td>33.0</td>\n",
+              "      <td>31.3</td>\n",
+              "      <td>l_lysine_chebi_18019</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>22</th>\n",
+              "      <td>L-Methionine_CHEBI:16643</td>\n",
+              "      <td>18.4</td>\n",
+              "      <td>20.5</td>\n",
+              "      <td>21.5</td>\n",
+              "      <td>22.0</td>\n",
+              "      <td>21.9</td>\n",
+              "      <td>22.3</td>\n",
+              "      <td>23.8</td>\n",
+              "      <td>24.3</td>\n",
+              "      <td>24.9</td>\n",
+              "      <td>...</td>\n",
+              "      <td>23.4</td>\n",
+              "      <td>21.9</td>\n",
+              "      <td>24.1</td>\n",
+              "      <td>21.4</td>\n",
+              "      <td>18.4</td>\n",
+              "      <td>20.6</td>\n",
+              "      <td>19.7</td>\n",
+              "      <td>19.3</td>\n",
+              "      <td>22.3</td>\n",
+              "      <td>l_methionine_chebi_16643</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>23</th>\n",
+              "      <td>myo-Inositol_CHEBI:17268</td>\n",
+              "      <td>248.0</td>\n",
+              "      <td>249.6</td>\n",
+              "      <td>255.3</td>\n",
+              "      <td>303.3</td>\n",
+              "      <td>283.6</td>\n",
+              "      <td>298.7</td>\n",
+              "      <td>249.4</td>\n",
+              "      <td>285.7</td>\n",
+              "      <td>282.4</td>\n",
+              "      <td>...</td>\n",
+              "      <td>1348.1</td>\n",
+              "      <td>1379.8</td>\n",
+              "      <td>1375.8</td>\n",
+              "      <td>1290.8</td>\n",
+              "      <td>1287.1</td>\n",
+              "      <td>1249.9</td>\n",
+              "      <td>1163.7</td>\n",
+              "      <td>1312.5</td>\n",
+              "      <td>1234.4</td>\n",
+              "      <td>myo_inositol_chebi_17268</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>24</th>\n",
+              "      <td>NAD_CHEBI:44215</td>\n",
+              "      <td>24.6</td>\n",
+              "      <td>24.2</td>\n",
+              "      <td>25.8</td>\n",
+              "      <td>25.3</td>\n",
+              "      <td>23.8</td>\n",
+              "      <td>26.2</td>\n",
+              "      <td>25.5</td>\n",
+              "      <td>25.1</td>\n",
+              "      <td>28.7</td>\n",
+              "      <td>...</td>\n",
+              "      <td>60.9</td>\n",
+              "      <td>63.4</td>\n",
+              "      <td>61.3</td>\n",
+              "      <td>59.3</td>\n",
+              "      <td>55.2</td>\n",
+              "      <td>58.4</td>\n",
+              "      <td>55.6</td>\n",
+              "      <td>59.4</td>\n",
+              "      <td>56.7</td>\n",
+              "      <td>nad_chebi_44215</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25</th>\n",
+              "      <td>O-Phosphocholine_CHEBI:18132</td>\n",
+              "      <td>363.5</td>\n",
+              "      <td>353.6</td>\n",
+              "      <td>357.1</td>\n",
+              "      <td>342.2</td>\n",
+              "      <td>336.5</td>\n",
+              "      <td>344.7</td>\n",
+              "      <td>376.2</td>\n",
+              "      <td>387.1</td>\n",
+              "      <td>369.7</td>\n",
+              "      <td>...</td>\n",
+              "      <td>374.0</td>\n",
+              "      <td>379.9</td>\n",
+              "      <td>371.5</td>\n",
+              "      <td>331.2</td>\n",
+              "      <td>328.8</td>\n",
+              "      <td>357.3</td>\n",
+              "      <td>343.1</td>\n",
+              "      <td>376.3</td>\n",
+              "      <td>364.0</td>\n",
+              "      <td>o_phosphocholine_chebi_18132</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>26</th>\n",
+              "      <td>Pantothenate_CHEBI:7916</td>\n",
+              "      <td>21.2</td>\n",
+              "      <td>21.3</td>\n",
+              "      <td>21.0</td>\n",
+              "      <td>21.8</td>\n",
+              "      <td>20.0</td>\n",
+              "      <td>22.0</td>\n",
+              "      <td>20.0</td>\n",
+              "      <td>22.9</td>\n",
+              "      <td>21.2</td>\n",
+              "      <td>...</td>\n",
+              "      <td>5.0</td>\n",
+              "      <td>4.8</td>\n",
+              "      <td>5.5</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>8.2</td>\n",
+              "      <td>7.9</td>\n",
+              "      <td>5.0</td>\n",
+              "      <td>5.7</td>\n",
+              "      <td>4.4</td>\n",
+              "      <td>pantothenate_chebi_7916</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>27</th>\n",
+              "      <td>L-Phenylalanine_CHEBI:17295</td>\n",
+              "      <td>50.7</td>\n",
+              "      <td>51.4</td>\n",
+              "      <td>51.1</td>\n",
+              "      <td>51.0</td>\n",
+              "      <td>45.8</td>\n",
+              "      <td>46.2</td>\n",
+              "      <td>52.1</td>\n",
+              "      <td>51.8</td>\n",
+              "      <td>48.3</td>\n",
+              "      <td>...</td>\n",
+              "      <td>40.0</td>\n",
+              "      <td>40.8</td>\n",
+              "      <td>41.9</td>\n",
+              "      <td>32.5</td>\n",
+              "      <td>29.3</td>\n",
+              "      <td>34.4</td>\n",
+              "      <td>37.3</td>\n",
+              "      <td>41.7</td>\n",
+              "      <td>36.3</td>\n",
+              "      <td>l_phenylalanine_chebi_17295</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>28</th>\n",
+              "      <td>L-Proline_CHEBI:17203</td>\n",
+              "      <td>44.1</td>\n",
+              "      <td>44.7</td>\n",
+              "      <td>50.2</td>\n",
+              "      <td>41.0</td>\n",
+              "      <td>42.1</td>\n",
+              "      <td>44.8</td>\n",
+              "      <td>52.2</td>\n",
+              "      <td>52.7</td>\n",
+              "      <td>54.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>136.7</td>\n",
+              "      <td>134.0</td>\n",
+              "      <td>144.7</td>\n",
+              "      <td>98.4</td>\n",
+              "      <td>90.4</td>\n",
+              "      <td>113.9</td>\n",
+              "      <td>126.3</td>\n",
+              "      <td>146.9</td>\n",
+              "      <td>142.8</td>\n",
+              "      <td>l_proline_chebi_17203</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>29</th>\n",
+              "      <td>Pyroglutamic acid_CHEBI:16010</td>\n",
+              "      <td>36.6</td>\n",
+              "      <td>34.9</td>\n",
+              "      <td>39.1</td>\n",
+              "      <td>39.7</td>\n",
+              "      <td>36.6</td>\n",
+              "      <td>38.0</td>\n",
+              "      <td>44.1</td>\n",
+              "      <td>43.1</td>\n",
+              "      <td>51.9</td>\n",
+              "      <td>...</td>\n",
+              "      <td>67.4</td>\n",
+              "      <td>68.0</td>\n",
+              "      <td>60.7</td>\n",
+              "      <td>50.6</td>\n",
+              "      <td>43.4</td>\n",
+              "      <td>55.7</td>\n",
+              "      <td>38.9</td>\n",
+              "      <td>50.5</td>\n",
+              "      <td>47.8</td>\n",
+              "      <td>pyroglutamic_acid_chebi_16010</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>30</th>\n",
+              "      <td>Serine_CHEBI:17822</td>\n",
+              "      <td>123.1</td>\n",
+              "      <td>130.7</td>\n",
+              "      <td>132.5</td>\n",
+              "      <td>147.4</td>\n",
+              "      <td>136.4</td>\n",
+              "      <td>143.2</td>\n",
+              "      <td>144.0</td>\n",
+              "      <td>152.5</td>\n",
+              "      <td>156.8</td>\n",
+              "      <td>...</td>\n",
+              "      <td>24.5</td>\n",
+              "      <td>22.6</td>\n",
+              "      <td>25.5</td>\n",
+              "      <td>34.9</td>\n",
+              "      <td>35.8</td>\n",
+              "      <td>32.2</td>\n",
+              "      <td>13.1</td>\n",
+              "      <td>16.6</td>\n",
+              "      <td>22.2</td>\n",
+              "      <td>serine_chebi_17822</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>31</th>\n",
+              "      <td>sn-Glycero-3-phosphocholine_CHEBI:16870</td>\n",
+              "      <td>154.1</td>\n",
+              "      <td>150.1</td>\n",
+              "      <td>161.1</td>\n",
+              "      <td>180.5</td>\n",
+              "      <td>165.8</td>\n",
+              "      <td>172.9</td>\n",
+              "      <td>137.1</td>\n",
+              "      <td>164.7</td>\n",
+              "      <td>164.8</td>\n",
+              "      <td>...</td>\n",
+              "      <td>62.0</td>\n",
+              "      <td>65.6</td>\n",
+              "      <td>62.3</td>\n",
+              "      <td>73.5</td>\n",
+              "      <td>71.8</td>\n",
+              "      <td>79.7</td>\n",
+              "      <td>58.3</td>\n",
+              "      <td>57.9</td>\n",
+              "      <td>57.4</td>\n",
+              "      <td>sn_glycero_3_phosphocholine_chebi_16870</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>32</th>\n",
+              "      <td>Taurine_CHEBI:15891</td>\n",
+              "      <td>151.1</td>\n",
+              "      <td>150.7</td>\n",
+              "      <td>158.1</td>\n",
+              "      <td>174.7</td>\n",
+              "      <td>161.8</td>\n",
+              "      <td>172.5</td>\n",
+              "      <td>153.4</td>\n",
+              "      <td>167.2</td>\n",
+              "      <td>168.6</td>\n",
+              "      <td>...</td>\n",
+              "      <td>298.0</td>\n",
+              "      <td>295.9</td>\n",
+              "      <td>284.5</td>\n",
+              "      <td>280.6</td>\n",
+              "      <td>295.8</td>\n",
+              "      <td>303.0</td>\n",
+              "      <td>264.4</td>\n",
+              "      <td>272.4</td>\n",
+              "      <td>264.5</td>\n",
+              "      <td>taurine_chebi_15891</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>33</th>\n",
+              "      <td>L-Threonine_CHEBI:16857</td>\n",
+              "      <td>168.2</td>\n",
+              "      <td>169.4</td>\n",
+              "      <td>176.1</td>\n",
+              "      <td>168.5</td>\n",
+              "      <td>169.8</td>\n",
+              "      <td>171.2</td>\n",
+              "      <td>178.9</td>\n",
+              "      <td>184.9</td>\n",
+              "      <td>196.9</td>\n",
+              "      <td>...</td>\n",
+              "      <td>155.6</td>\n",
+              "      <td>151.3</td>\n",
+              "      <td>156.2</td>\n",
+              "      <td>122.9</td>\n",
+              "      <td>111.8</td>\n",
+              "      <td>125.3</td>\n",
+              "      <td>157.6</td>\n",
+              "      <td>142.5</td>\n",
+              "      <td>163.3</td>\n",
+              "      <td>l_threonine_chebi_16857</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>34</th>\n",
+              "      <td>L-Tryptophan_CHEBI:16828</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>12.7</td>\n",
+              "      <td>11.7</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>9.9</td>\n",
+              "      <td>10.5</td>\n",
+              "      <td>9.0</td>\n",
+              "      <td>10.1</td>\n",
+              "      <td>10.6</td>\n",
+              "      <td>...</td>\n",
+              "      <td>8.5</td>\n",
+              "      <td>8.1</td>\n",
+              "      <td>8.5</td>\n",
+              "      <td>7.3</td>\n",
+              "      <td>6.3</td>\n",
+              "      <td>6.9</td>\n",
+              "      <td>5.8</td>\n",
+              "      <td>6.7</td>\n",
+              "      <td>7.2</td>\n",
+              "      <td>l_tryptophan_chebi_16828</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>35</th>\n",
+              "      <td>L-Tyrosine_CHEBI:17895</td>\n",
+              "      <td>42.6</td>\n",
+              "      <td>40.7</td>\n",
+              "      <td>42.1</td>\n",
+              "      <td>41.6</td>\n",
+              "      <td>39.0</td>\n",
+              "      <td>37.4</td>\n",
+              "      <td>41.2</td>\n",
+              "      <td>41.3</td>\n",
+              "      <td>43.7</td>\n",
+              "      <td>...</td>\n",
+              "      <td>33.9</td>\n",
+              "      <td>38.0</td>\n",
+              "      <td>36.0</td>\n",
+              "      <td>23.2</td>\n",
+              "      <td>20.4</td>\n",
+              "      <td>25.5</td>\n",
+              "      <td>34.2</td>\n",
+              "      <td>39.2</td>\n",
+              "      <td>33.2</td>\n",
+              "      <td>l_tyrosine_chebi_17895</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>36</th>\n",
+              "      <td>UDP-N-Acetylglucosamine_CHEBI:16264</td>\n",
+              "      <td>63.2</td>\n",
+              "      <td>61.7</td>\n",
+              "      <td>62.7</td>\n",
+              "      <td>68.4</td>\n",
+              "      <td>62.2</td>\n",
+              "      <td>71.4</td>\n",
+              "      <td>57.9</td>\n",
+              "      <td>69.1</td>\n",
+              "      <td>69.3</td>\n",
+              "      <td>...</td>\n",
+              "      <td>67.6</td>\n",
+              "      <td>66.5</td>\n",
+              "      <td>66.6</td>\n",
+              "      <td>63.2</td>\n",
+              "      <td>59.4</td>\n",
+              "      <td>60.1</td>\n",
+              "      <td>63.6</td>\n",
+              "      <td>68.9</td>\n",
+              "      <td>67.3</td>\n",
+              "      <td>udp_n_acetylglucosamine_chebi_16264</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>37</th>\n",
+              "      <td>L-Valine_CHEBI:16414</td>\n",
+              "      <td>69.8</td>\n",
+              "      <td>69.6</td>\n",
+              "      <td>72.2</td>\n",
+              "      <td>73.6</td>\n",
+              "      <td>68.7</td>\n",
+              "      <td>71.8</td>\n",
+              "      <td>75.7</td>\n",
+              "      <td>80.1</td>\n",
+              "      <td>80.5</td>\n",
+              "      <td>...</td>\n",
+              "      <td>50.8</td>\n",
+              "      <td>52.2</td>\n",
+              "      <td>54.0</td>\n",
+              "      <td>43.5</td>\n",
+              "      <td>38.8</td>\n",
+              "      <td>44.9</td>\n",
+              "      <td>48.5</td>\n",
+              "      <td>53.6</td>\n",
+              "      <td>48.9</td>\n",
+              "      <td>l_valine_chebi_16414</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>38</th>\n",
+              "      <td>beta-Alanine_CHEBI:16958</td>\n",
+              "      <td>12.4</td>\n",
+              "      <td>12.7</td>\n",
+              "      <td>13.2</td>\n",
+              "      <td>13.7</td>\n",
+              "      <td>12.8</td>\n",
+              "      <td>13.2</td>\n",
+              "      <td>13.3</td>\n",
+              "      <td>14.1</td>\n",
+              "      <td>14.5</td>\n",
+              "      <td>...</td>\n",
+              "      <td>57.2</td>\n",
+              "      <td>58.9</td>\n",
+              "      <td>59.0</td>\n",
+              "      <td>46.0</td>\n",
+              "      <td>41.6</td>\n",
+              "      <td>48.1</td>\n",
+              "      <td>49.7</td>\n",
+              "      <td>55.7</td>\n",
+              "      <td>53.3</td>\n",
+              "      <td>beta_alanine_chebi_16958</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>39 rows × 29 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                                        rid  hcc1937_c1  hcc1937_c2  \\\n",
+              "0          1-Methylnicotinamide_CHEBI:16797         0.0         0.0   \n",
+              "1                2-Aminoadipate_CHEBI:37024         0.0         0.0   \n",
+              "2              2-Oxoisocaproate_CHEBI:48430         0.0         0.0   \n",
+              "3                     L-Alanine_CHEBI:16977       396.7       381.1   \n",
+              "4       Adenosine monophosphate_CHEBI:16027        11.6        12.5   \n",
+              "5                  L-Asparagine_CHEBI:17196        13.5        13.5   \n",
+              "6                   L-Aspartate_CHEBI:17053       103.7        99.9   \n",
+              "7        Adenosine triphosphate_CHEBI:15422        66.3        61.6   \n",
+              "8                      Creatine_CHEBI:16919        22.5        22.5   \n",
+              "9            Creatine phosphate_CHEBI:17287        23.5        21.6   \n",
+              "10                      Formate_CHEBI:30751        14.5        16.1   \n",
+              "11                     Fumarate_CHEBI:18012         3.4         3.6   \n",
+              "12                   D-Glucitol_CHEBI:17924         0.0         0.0   \n",
+              "13                     D-Glucose_CHEBI:4167       168.0       201.4   \n",
+              "14              L-Glutamic acid_CHEBI:16015       368.0       351.9   \n",
+              "15                  L-Glutamine_CHEBI:18050       450.2       449.7   \n",
+              "16                  Glutathione_CHEBI:16856       207.4       196.4   \n",
+              "17                      Glycine_CHEBI:15428       561.5       550.2   \n",
+              "18                 L-Isoleucine_CHEBI:17191        68.7        67.4   \n",
+              "19                      Lactate_CHEBI:78320       402.9       447.2   \n",
+              "20                    L-Leucine_CHEBI:15603        54.4        53.8   \n",
+              "21                     L-Lysine_CHEBI:18019        25.4        25.2   \n",
+              "22                 L-Methionine_CHEBI:16643        18.4        20.5   \n",
+              "23                 myo-Inositol_CHEBI:17268       248.0       249.6   \n",
+              "24                          NAD_CHEBI:44215        24.6        24.2   \n",
+              "25             O-Phosphocholine_CHEBI:18132       363.5       353.6   \n",
+              "26                  Pantothenate_CHEBI:7916        21.2        21.3   \n",
+              "27              L-Phenylalanine_CHEBI:17295        50.7        51.4   \n",
+              "28                    L-Proline_CHEBI:17203        44.1        44.7   \n",
+              "29            Pyroglutamic acid_CHEBI:16010        36.6        34.9   \n",
+              "30                       Serine_CHEBI:17822       123.1       130.7   \n",
+              "31  sn-Glycero-3-phosphocholine_CHEBI:16870       154.1       150.1   \n",
+              "32                      Taurine_CHEBI:15891       151.1       150.7   \n",
+              "33                  L-Threonine_CHEBI:16857       168.2       169.4   \n",
+              "34                 L-Tryptophan_CHEBI:16828        11.0        12.7   \n",
+              "35                   L-Tyrosine_CHEBI:17895        42.6        40.7   \n",
+              "36      UDP-N-Acetylglucosamine_CHEBI:16264        63.2        61.7   \n",
+              "37                     L-Valine_CHEBI:16414        69.8        69.6   \n",
+              "38                 beta-Alanine_CHEBI:16958        12.4        12.7   \n",
+              "\n",
+              "    hcc1937_c3  hcc1937_pi1  hcc1937_pi2  hcc1937_pi3  hcc1937_r1  hcc1937_r2  \\\n",
+              "0          0.0          0.0          0.0          0.0         0.0         0.0   \n",
+              "1          0.0          0.0          0.0          0.0         0.0         0.0   \n",
+              "2          0.0          0.0          0.0          0.0         0.0         0.0   \n",
+              "3        403.8        393.8        370.9        380.6       425.1       437.8   \n",
+              "4         13.1          6.6          9.2          6.6         7.1         8.9   \n",
+              "5         14.3          8.7         11.2         11.0        11.6        12.5   \n",
+              "6         94.0         89.6         80.8         90.3       105.1        98.1   \n",
+              "7         67.8         75.7         67.7         71.9        70.8        65.7   \n",
+              "8         21.1         19.9         20.1         20.4        22.5        24.3   \n",
+              "9         24.5         27.7         24.6         26.9        23.2        27.6   \n",
+              "10        13.8         16.7         17.8         17.0        18.6        20.2   \n",
+              "11         3.8          3.2          3.0          3.1         3.8         3.9   \n",
+              "12         0.0          0.0          0.0          0.0         0.0         0.0   \n",
+              "13       206.8        213.4        170.4        194.4       312.2       272.4   \n",
+              "14       388.7        317.7        303.4        313.7       367.7       378.1   \n",
+              "15       474.6        483.3        448.0        471.6       475.0       496.3   \n",
+              "16       205.9        211.5        191.6        202.0       202.4       202.3   \n",
+              "17       641.5        709.6        689.4        704.7       722.2       761.5   \n",
+              "18        71.5         71.8         67.5         69.5        75.8        77.5   \n",
+              "19       415.6        507.4        399.8        419.6       643.8       553.5   \n",
+              "20        56.1         53.6         51.6         53.3        57.6        56.7   \n",
+              "21        25.9         23.1         25.0         21.4        30.4        29.8   \n",
+              "22        21.5         22.0         21.9         22.3        23.8        24.3   \n",
+              "23       255.3        303.3        283.6        298.7       249.4       285.7   \n",
+              "24        25.8         25.3         23.8         26.2        25.5        25.1   \n",
+              "25       357.1        342.2        336.5        344.7       376.2       387.1   \n",
+              "26        21.0         21.8         20.0         22.0        20.0        22.9   \n",
+              "27        51.1         51.0         45.8         46.2        52.1        51.8   \n",
+              "28        50.2         41.0         42.1         44.8        52.2        52.7   \n",
+              "29        39.1         39.7         36.6         38.0        44.1        43.1   \n",
+              "30       132.5        147.4        136.4        143.2       144.0       152.5   \n",
+              "31       161.1        180.5        165.8        172.9       137.1       164.7   \n",
+              "32       158.1        174.7        161.8        172.5       153.4       167.2   \n",
+              "33       176.1        168.5        169.8        171.2       178.9       184.9   \n",
+              "34        11.7         11.0          9.9         10.5         9.0        10.1   \n",
+              "35        42.1         41.6         39.0         37.4        41.2        41.3   \n",
+              "36        62.7         68.4         62.2         71.4        57.9        69.1   \n",
+              "37        72.2         73.6         68.7         71.8        75.7        80.1   \n",
+              "38        13.2         13.7         12.8         13.2        13.3        14.1   \n",
+              "\n",
+              "    hcc1937_r3  ...  mdamb231_c1  mdamb231_c2  mdamb231_c3  mdamb231_pi1  \\\n",
+              "0          0.0  ...         24.4         22.4         22.2          27.9   \n",
+              "1          0.0  ...         51.8         48.1         44.5          28.7   \n",
+              "2          0.0  ...          0.0          0.0          0.0           0.0   \n",
+              "3        433.9  ...         77.4         82.1         79.8          63.2   \n",
+              "4         10.1  ...          0.0          0.0          0.0           0.0   \n",
+              "5         13.4  ...         25.8         27.0         27.2          24.7   \n",
+              "6         98.4  ...         67.6         66.7         66.5          57.1   \n",
+              "7         65.0  ...        167.3        188.5        181.0         160.1   \n",
+              "8         23.1  ...         18.8         18.5         18.7          12.2   \n",
+              "9         27.8  ...         20.6         20.8         18.8          12.2   \n",
+              "10        18.8  ...         24.7         17.9         19.8          29.5   \n",
+              "11         3.7  ...          4.1          3.4          3.5           2.9   \n",
+              "12         0.0  ...         97.0         88.8        103.4         161.1   \n",
+              "13       336.2  ...        165.1        184.2        198.4         290.8   \n",
+              "14       388.4  ...       1190.5       1194.4       1203.6         924.6   \n",
+              "15       514.9  ...        389.8        403.0        387.5         285.4   \n",
+              "16       207.5  ...        376.8        394.3        388.8         344.5   \n",
+              "17       766.0  ...       1083.3       1106.8       1077.4        1031.8   \n",
+              "18        80.3  ...         58.0         59.8         61.1          47.2   \n",
+              "19       670.1  ...        518.9        512.4        550.5         465.0   \n",
+              "20        59.4  ...         43.0         43.5         44.5          36.4   \n",
+              "21        32.6  ...         29.2         31.1         35.7          32.0   \n",
+              "22        24.9  ...         23.4         21.9         24.1          21.4   \n",
+              "23       282.4  ...       1348.1       1379.8       1375.8        1290.8   \n",
+              "24        28.7  ...         60.9         63.4         61.3          59.3   \n",
+              "25       369.7  ...        374.0        379.9        371.5         331.2   \n",
+              "26        21.2  ...          5.0          4.8          5.5           8.0   \n",
+              "27        48.3  ...         40.0         40.8         41.9          32.5   \n",
+              "28        54.0  ...        136.7        134.0        144.7          98.4   \n",
+              "29        51.9  ...         67.4         68.0         60.7          50.6   \n",
+              "30       156.8  ...         24.5         22.6         25.5          34.9   \n",
+              "31       164.8  ...         62.0         65.6         62.3          73.5   \n",
+              "32       168.6  ...        298.0        295.9        284.5         280.6   \n",
+              "33       196.9  ...        155.6        151.3        156.2         122.9   \n",
+              "34        10.6  ...          8.5          8.1          8.5           7.3   \n",
+              "35        43.7  ...         33.9         38.0         36.0          23.2   \n",
+              "36        69.3  ...         67.6         66.5         66.6          63.2   \n",
+              "37        80.5  ...         50.8         52.2         54.0          43.5   \n",
+              "38        14.5  ...         57.2         58.9         59.0          46.0   \n",
+              "\n",
+              "    mdamb231_pi2  mdamb231_pi3  mdamb231_r1  mdamb231_r2  mdamb231_r3  \\\n",
+              "0           27.0          29.7         21.9         25.7         21.5   \n",
+              "1           17.6          28.0         38.3         44.6         38.0   \n",
+              "2            0.0           0.0          0.0          0.0          0.0   \n",
+              "3           53.1          58.4         66.7         73.5         72.0   \n",
+              "4            0.0           0.0          0.0          0.0          0.0   \n",
+              "5           23.3          23.5         21.7         19.1         19.1   \n",
+              "6           51.2          56.7         48.0         53.9         49.5   \n",
+              "7          128.8         147.0        151.9        150.6        142.3   \n",
+              "8           11.2          12.2         16.3         18.1         16.9   \n",
+              "9           13.1          14.4         19.4         21.2         19.6   \n",
+              "10          32.3          24.8         19.9         19.4         18.4   \n",
+              "11           3.2           2.4          3.6          3.8          3.3   \n",
+              "12         190.4         128.6         90.5        110.0        109.4   \n",
+              "13         240.7         300.3        171.3        154.9        154.2   \n",
+              "14         866.5         913.1        991.0       1155.5       1063.7   \n",
+              "15         249.6         289.2        354.2        369.3        366.4   \n",
+              "16         320.1         334.3        331.9        365.5        355.5   \n",
+              "17         980.7         996.2        999.4       1063.5       1042.4   \n",
+              "18          40.9          47.7         53.3         58.9         57.2   \n",
+              "19         402.9         466.3        527.0        647.5        611.6   \n",
+              "20          32.9          36.8         39.9         45.3         43.7   \n",
+              "21          33.3          34.2         28.4         33.0         31.3   \n",
+              "22          18.4          20.6         19.7         19.3         22.3   \n",
+              "23        1287.1        1249.9       1163.7       1312.5       1234.4   \n",
+              "24          55.2          58.4         55.6         59.4         56.7   \n",
+              "25         328.8         357.3        343.1        376.3        364.0   \n",
+              "26           8.2           7.9          5.0          5.7          4.4   \n",
+              "27          29.3          34.4         37.3         41.7         36.3   \n",
+              "28          90.4         113.9        126.3        146.9        142.8   \n",
+              "29          43.4          55.7         38.9         50.5         47.8   \n",
+              "30          35.8          32.2         13.1         16.6         22.2   \n",
+              "31          71.8          79.7         58.3         57.9         57.4   \n",
+              "32         295.8         303.0        264.4        272.4        264.5   \n",
+              "33         111.8         125.3        157.6        142.5        163.3   \n",
+              "34           6.3           6.9          5.8          6.7          7.2   \n",
+              "35          20.4          25.5         34.2         39.2         33.2   \n",
+              "36          59.4          60.1         63.6         68.9         67.3   \n",
+              "37          38.8          44.9         48.5         53.6         48.9   \n",
+              "38          41.6          48.1         49.7         55.7         53.3   \n",
+              "\n",
+              "                                     row_id  \n",
+              "0         _1_methylnicotinamide_chebi_16797  \n",
+              "1               _2_aminoadipate_chebi_37024  \n",
+              "2             _2_oxoisocaproate_chebi_48430  \n",
+              "3                     l_alanine_chebi_16977  \n",
+              "4       adenosine_monophosphate_chebi_16027  \n",
+              "5                  l_asparagine_chebi_17196  \n",
+              "6                   l_aspartate_chebi_17053  \n",
+              "7        adenosine_triphosphate_chebi_15422  \n",
+              "8                      creatine_chebi_16919  \n",
+              "9            creatine_phosphate_chebi_17287  \n",
+              "10                      formate_chebi_30751  \n",
+              "11                     fumarate_chebi_18012  \n",
+              "12                   d_glucitol_chebi_17924  \n",
+              "13                     d_glucose_chebi_4167  \n",
+              "14              l_glutamic_acid_chebi_16015  \n",
+              "15                  l_glutamine_chebi_18050  \n",
+              "16                  glutathione_chebi_16856  \n",
+              "17                      glycine_chebi_15428  \n",
+              "18                 l_isoleucine_chebi_17191  \n",
+              "19                      lactate_chebi_78320  \n",
+              "20                    l_leucine_chebi_15603  \n",
+              "21                     l_lysine_chebi_18019  \n",
+              "22                 l_methionine_chebi_16643  \n",
+              "23                 myo_inositol_chebi_17268  \n",
+              "24                          nad_chebi_44215  \n",
+              "25             o_phosphocholine_chebi_18132  \n",
+              "26                  pantothenate_chebi_7916  \n",
+              "27              l_phenylalanine_chebi_17295  \n",
+              "28                    l_proline_chebi_17203  \n",
+              "29            pyroglutamic_acid_chebi_16010  \n",
+              "30                       serine_chebi_17822  \n",
+              "31  sn_glycero_3_phosphocholine_chebi_16870  \n",
+              "32                      taurine_chebi_15891  \n",
+              "33                  l_threonine_chebi_16857  \n",
+              "34                 l_tryptophan_chebi_16828  \n",
+              "35                   l_tyrosine_chebi_17895  \n",
+              "36      udp_n_acetylglucosamine_chebi_16264  \n",
+              "37                     l_valine_chebi_16414  \n",
+              "38                 beta_alanine_chebi_16958  \n",
+              "\n",
+              "[39 rows x 29 columns]"
+            ]
+          },
+          "execution_count": 33,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "query = \"SELECT * FROM data_matrices.metabolomics__mtbls337_m_breast_cancer_metabolomics_metabolite_profiling_nmr_spectroscopy\"\n",
+        "data_df = omixatlas.query_metadata(query)\n",
+        "data_df"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 34,
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "outputs": [],
+      "source": [
+        "#making sample id comsistent across sample metadata and data matrix\n",
+        "samples_df['sample_id'] = samples_df['sample_id'].str.lower()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "source": [
+        "### Visualisations and Analysis\n",
+        "- PCA plot\n",
+        "- Comparing levels of a metabolite of interest across an attribute\n",
+        "- Differential analysis using Limma\n",
+        "- Performing MSEA\n",
+        "- Visualising differential expression in KEGG pathway"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "source": [
+        "### PCA plot"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 35,
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
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+              "        require.undef(\"plotly\");\n",
+              "        define('plotly', function(require, exports, module) {\n",
+              "            /**\n",
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+              "* Copyright 2012-2021, Plotly, Inc.\n",
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+              "* Licensed under the MIT license\n",
+              "*/\n",
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+              "/*!\n",
+              " * The buffer module from node.js, for the browser.\n",
+              " *\n",
+              " * @author   Feross Aboukhadijeh <feross@feross.org> <http://feross.org>\n",
+              " * @license  MIT\n",
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this._expand(r+1),this.words[r]=e?this.words[r]|1<<i:this.words[r]&~(1<<i),this.strip()},a.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++)e=(0|r.words[a])+(0|n.words[a])+i,this.words[a]=67108863&e,i=e>>>26;for(;0!==i&&a<r.length;a++)e=(0|r.words[a])+i,this.words[a]=67108863&e,i=e>>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},a.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o<n.length;o++)a=(e=(0|r.words[o])-(0|n.words[o])+a)>>26,this.words[o]=67108863&e;for(;0!==a&&o<r.length;o++)a=(e=(0|r.words[o])+a)>>26,this.words[o]=67108863&e;if(0===a&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},a.prototype.sub=function(t){return this.clone().isub(t)};var p=function(t,e,r){var n,i,a,o=t.words,s=e.words,l=r.words,c=0,u=0|o[0],f=8191&u,h=u>>>13,p=0|o[1],d=8191&p,m=p>>>13,g=0|o[2],v=8191&g,y=g>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,M=0|o[5],A=8191&M,S=M>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],I=8191&P,O=P>>>13,z=0|o[8],D=8191&z,R=z>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,q=0|s[1],H=8191&q,G=q>>>13,Y=0|s[2],W=8191&Y,X=Y>>>13,Z=0|s[3],J=8191&Z,K=Z>>>13,Q=0|s[4],$=8191&Q,tt=Q>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ct=st>>>13,ut=0|s[8],ft=8191&ut,ht=ut>>>13,pt=0|s[9],dt=8191&pt,mt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var gt=(c+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;c=((a=Math.imul(h,V))+(i>>>13)|0)+(gt>>>26)|0,gt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(m,U)|0,a=Math.imul(m,V);var vt=(c+(n=n+Math.imul(f,H)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,H)|0))<<13)|0;c=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(vt>>>26)|0,vt&=67108863,n=Math.imul(v,U),i=(i=Math.imul(v,V))+Math.imul(y,U)|0,a=Math.imul(y,V),n=n+Math.imul(d,H)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(m,H)|0,a=a+Math.imul(m,G)|0;var yt=(c+(n=n+Math.imul(f,W)|0)|0)+((8191&(i=(i=i+Math.imul(f,X)|0)+Math.imul(h,W)|0))<<13)|0;c=((a=a+Math.imul(h,X)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(v,H)|0,i=(i=i+Math.imul(v,G)|0)+Math.imul(y,H)|0,a=a+Math.imul(y,G)|0,n=n+Math.imul(d,W)|0,i=(i=i+Math.imul(d,X)|0)+Math.imul(m,W)|0,a=a+Math.imul(m,X)|0;var xt=(c+(n=n+Math.imul(f,J)|0)|0)+((8191&(i=(i=i+Math.imul(f,K)|0)+Math.imul(h,J)|0))<<13)|0;c=((a=a+Math.imul(h,K)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,H)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,H)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(v,W)|0,i=(i=i+Math.imul(v,X)|0)+Math.imul(y,W)|0,a=a+Math.imul(y,X)|0,n=n+Math.imul(d,J)|0,i=(i=i+Math.imul(d,K)|0)+Math.imul(m,J)|0,a=a+Math.imul(m,K)|0;var bt=(c+(n=n+Math.imul(f,$)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,$)|0))<<13)|0;c=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(A,U),i=(i=Math.imul(A,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,H)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,H)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,W)|0,i=(i=i+Math.imul(b,X)|0)+Math.imul(_,W)|0,a=a+Math.imul(_,X)|0,n=n+Math.imul(v,J)|0,i=(i=i+Math.imul(v,K)|0)+Math.imul(y,J)|0,a=a+Math.imul(y,K)|0,n=n+Math.imul(d,$)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(m,$)|0,a=a+Math.imul(m,tt)|0;var _t=(c+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;c=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(A,H)|0,i=(i=i+Math.imul(A,G)|0)+Math.imul(S,H)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,W)|0,i=(i=i+Math.imul(T,X)|0)+Math.imul(k,W)|0,a=a+Math.imul(k,X)|0,n=n+Math.imul(b,J)|0,i=(i=i+Math.imul(b,K)|0)+Math.imul(_,J)|0,a=a+Math.imul(_,K)|0,n=n+Math.imul(v,$)|0,i=(i=i+Math.imul(v,tt)|0)+Math.imul(y,$)|0,a=a+Math.imul(y,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(m,rt)|0,a=a+Math.imul(m,nt)|0;var wt=(c+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;c=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(I,U),i=(i=Math.imul(I,V))+Math.imul(O,U)|0,a=Math.imul(O,V),n=n+Math.imul(L,H)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,H)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(A,W)|0,i=(i=i+Math.imul(A,X)|0)+Math.imul(S,W)|0,a=a+Math.imul(S,X)|0,n=n+Math.imul(T,J)|0,i=(i=i+Math.imul(T,K)|0)+Math.imul(k,J)|0,a=a+Math.imul(k,K)|0,n=n+Math.imul(b,$)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,$)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(v,rt)|0,i=(i=i+Math.imul(v,nt)|0)+Math.imul(y,rt)|0,a=a+Math.imul(y,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(m,at)|0,a=a+Math.imul(m,ot)|0;var Tt=(c+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ct)|0)+Math.imul(h,lt)|0))<<13)|0;c=((a=a+Math.imul(h,ct)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(D,U),i=(i=Math.imul(D,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(I,H)|0,i=(i=i+Math.imul(I,G)|0)+Math.imul(O,H)|0,a=a+Math.imul(O,G)|0,n=n+Math.imul(L,W)|0,i=(i=i+Math.imul(L,X)|0)+Math.imul(C,W)|0,a=a+Math.imul(C,X)|0,n=n+Math.imul(A,J)|0,i=(i=i+Math.imul(A,K)|0)+Math.imul(S,J)|0,a=a+Math.imul(S,K)|0,n=n+Math.imul(T,$)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,$)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(v,at)|0,i=(i=i+Math.imul(v,ot)|0)+Math.imul(y,at)|0,a=a+Math.imul(y,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ct)|0)+Math.imul(m,lt)|0,a=a+Math.imul(m,ct)|0;var kt=(c+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;c=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(D,H)|0,i=(i=i+Math.imul(D,G)|0)+Math.imul(R,H)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(I,W)|0,i=(i=i+Math.imul(I,X)|0)+Math.imul(O,W)|0,a=a+Math.imul(O,X)|0,n=n+Math.imul(L,J)|0,i=(i=i+Math.imul(L,K)|0)+Math.imul(C,J)|0,a=a+Math.imul(C,K)|0,n=n+Math.imul(A,$)|0,i=(i=i+Math.imul(A,tt)|0)+Math.imul(S,$)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(v,lt)|0,i=(i=i+Math.imul(v,ct)|0)+Math.imul(y,lt)|0,a=a+Math.imul(y,ct)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(m,ft)|0,a=a+Math.imul(m,ht)|0;var Mt=(c+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,mt)|0)+Math.imul(h,dt)|0))<<13)|0;c=((a=a+Math.imul(h,mt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,H),i=(i=Math.imul(B,G))+Math.imul(N,H)|0,a=Math.imul(N,G),n=n+Math.imul(D,W)|0,i=(i=i+Math.imul(D,X)|0)+Math.imul(R,W)|0,a=a+Math.imul(R,X)|0,n=n+Math.imul(I,J)|0,i=(i=i+Math.imul(I,K)|0)+Math.imul(O,J)|0,a=a+Math.imul(O,K)|0,n=n+Math.imul(L,$)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,$)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(A,rt)|0,i=(i=i+Math.imul(A,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ct)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ct)|0,n=n+Math.imul(v,ft)|0,i=(i=i+Math.imul(v,ht)|0)+Math.imul(y,ft)|0,a=a+Math.imul(y,ht)|0;var At=(c+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,mt)|0)+Math.imul(m,dt)|0))<<13)|0;c=((a=a+Math.imul(m,mt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,W),i=(i=Math.imul(B,X))+Math.imul(N,W)|0,a=Math.imul(N,X),n=n+Math.imul(D,J)|0,i=(i=i+Math.imul(D,K)|0)+Math.imul(R,J)|0,a=a+Math.imul(R,K)|0,n=n+Math.imul(I,$)|0,i=(i=i+Math.imul(I,tt)|0)+Math.imul(O,$)|0,a=a+Math.imul(O,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(A,at)|0,i=(i=i+Math.imul(A,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ct)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ct)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(c+(n=n+Math.imul(v,dt)|0)|0)+((8191&(i=(i=i+Math.imul(v,mt)|0)+Math.imul(y,dt)|0))<<13)|0;c=((a=a+Math.imul(y,mt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),i=(i=Math.imul(B,K))+Math.imul(N,J)|0,a=Math.imul(N,K),n=n+Math.imul(D,$)|0,i=(i=i+Math.imul(D,tt)|0)+Math.imul(R,$)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(I,rt)|0,i=(i=i+Math.imul(I,nt)|0)+Math.imul(O,rt)|0,a=a+Math.imul(O,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(A,lt)|0,i=(i=i+Math.imul(A,ct)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ct)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(c+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,mt)|0)+Math.imul(_,dt)|0))<<13)|0;c=((a=a+Math.imul(_,mt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,$),i=(i=Math.imul(B,tt))+Math.imul(N,$)|0,a=Math.imul(N,tt),n=n+Math.imul(D,rt)|0,i=(i=i+Math.imul(D,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(I,at)|0,i=(i=i+Math.imul(I,ot)|0)+Math.imul(O,at)|0,a=a+Math.imul(O,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ct)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ct)|0,n=n+Math.imul(A,ft)|0,i=(i=i+Math.imul(A,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Lt=(c+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,mt)|0)+Math.imul(k,dt)|0))<<13)|0;c=((a=a+Math.imul(k,mt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(D,at)|0,i=(i=i+Math.imul(D,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(I,lt)|0,i=(i=i+Math.imul(I,ct)|0)+Math.imul(O,lt)|0,a=a+Math.imul(O,ct)|0,n=n+Math.imul(L,ft)|0,i=(i=i+Math.imul(L,ht)|0)+Math.imul(C,ft)|0,a=a+Math.imul(C,ht)|0;var Ct=(c+(n=n+Math.imul(A,dt)|0)|0)+((8191&(i=(i=i+Math.imul(A,mt)|0)+Math.imul(S,dt)|0))<<13)|0;c=((a=a+Math.imul(S,mt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(D,lt)|0,i=(i=i+Math.imul(D,ct)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ct)|0,n=n+Math.imul(I,ft)|0,i=(i=i+Math.imul(I,ht)|0)+Math.imul(O,ft)|0,a=a+Math.imul(O,ht)|0;var Pt=(c+(n=n+Math.imul(L,dt)|0)|0)+((8191&(i=(i=i+Math.imul(L,mt)|0)+Math.imul(C,dt)|0))<<13)|0;c=((a=a+Math.imul(C,mt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ct))+Math.imul(N,lt)|0,a=Math.imul(N,ct),n=n+Math.imul(D,ft)|0,i=(i=i+Math.imul(D,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var It=(c+(n=n+Math.imul(I,dt)|0)|0)+((8191&(i=(i=i+Math.imul(I,mt)|0)+Math.imul(O,dt)|0))<<13)|0;c=((a=a+Math.imul(O,mt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var Ot=(c+(n=n+Math.imul(D,dt)|0)|0)+((8191&(i=(i=i+Math.imul(D,mt)|0)+Math.imul(R,dt)|0))<<13)|0;c=((a=a+Math.imul(R,mt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863;var zt=(c+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,mt))+Math.imul(N,dt)|0))<<13)|0;return c=((a=Math.imul(N,mt))+(i>>>13)|0)+(zt>>>26)|0,zt&=67108863,l[0]=gt,l[1]=vt,l[2]=yt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=Mt,l[10]=At,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=It,l[17]=Ot,l[18]=zt,0!==c&&(l[19]=c,r.length++),r};function d(t,e,r){return(new m).mulp(t,e,r)}function m(t,e){this.x=t,this.y=e}Math.imul||(p=h),a.prototype.mulTo=function(t,e){var r=this.length+t.length;return 10===this.length&&10===t.length?p(this,t,e):r<63?h(this,t,e):r<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a<r.length-1;a++){var o=i;i=0;for(var s=67108863&n,l=Math.min(a,e.length-1),c=Math.max(0,a-t.length+1);c<=l;c++){var u=a-c,f=(0|t.words[u])*(0|e.words[c]),h=67108863&f;s=67108863&(h=h+s|0),i+=(o=(o=o+(f/67108864|0)|0)+(h>>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):d(this,t,e)},m.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},m.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,i=0;i<e;i++)n|=(1&t)<<e-i-1,t>>=1;return n},m.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o<a;o++)n[o]=e[t[o]],i[o]=r[t[o]]},m.prototype.transform=function(t,e,r,n,i,a){this.permute(a,t,e,r,n,i);for(var o=1;o<i;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),c=Math.sin(2*Math.PI/s),u=0;u<i;u+=s)for(var f=l,h=c,p=0;p<o;p++){var d=r[u+p],m=n[u+p],g=r[u+p+o],v=n[u+p+o],y=f*g-h*v;v=f*v+h*g,g=y,r[u+p]=d+g,n[u+p]=m+v,r[u+p+o]=d-g,n[u+p+o]=m-v,p!==s&&(y=l*f-c*h,h=l*h+c*f,f=y)}},m.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,i=0;for(r=r/2|0;r;r>>>=1)i++;return 1<<i+1+n},m.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var i=t[n];t[n]=t[r-n-1],t[r-n-1]=i,i=e[n],e[n]=-e[r-n-1],e[r-n-1]=-i}},m.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var i=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&i,r=i<67108864?0:i/67108864|0}return t},m.prototype.convert13b=function(t,e,r,i){for(var a=0,o=0;o<e;o++)a+=0|t[o],r[2*o]=8191&a,a>>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o<i;++o)r[o]=0;n(0===a),n(0==(-8192&a))},m.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},m.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),i=this.makeRBT(n),a=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),c=new Array(n),u=new Array(n),f=new Array(n),h=r.words;h.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,c,n),this.transform(o,a,s,l,n,i),this.transform(c,a,u,f,n,i);for(var p=0;p<n;p++){var d=s[p]*u[p]-l[p]*f[p];l[p]=s[p]*f[p]+l[p]*u[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,h,a,n,i),this.conjugate(h,a,n),this.normalize13b(h,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},a.prototype.mul=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},a.prototype.mulf=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),d(this,t,e)},a.prototype.imul=function(t){return this.clone().mulTo(t,this)},a.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var i=(0|this.words[r])*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,i=r%26;e[r]=(t.words[n]&1<<i)>>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var i=r.sqr();n<e.length;n++,i=i.sqr())0!==e[n]&&(r=r.mul(i));return r},a.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&a,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e<i;e++)this.words[e]=0;this.length+=i}return this.strip()},a.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},a.prototype.iushrn=function(t,e,r){var i;n(\"number\"==typeof t&&t>=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=r;if(i-=o,i=Math.max(0,i),l){for(var c=0;c<o;c++)l.words[c]=this.words[c];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,c=0;c<this.length;c++)this.words[c]=this.words[c+o];else this.words[0]=0,this.length=1;var u=0;for(c=this.length-1;c>=0&&(0!==u||c>=i);c--){var f=0|this.words[c];this.words[c]=u<<26-a|f>>>a,u=f&s}return l&&0!==u&&(l.words[l.length++]=u),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<<e;return!(this.length<=r)&&!!(this.words[r]&i)},a.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},a.prototype.maskn=function(t){return this.clone().imaskn(t)},a.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},a.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},a.prototype.addn=function(t){return this.clone().iaddn(t)},a.prototype.subn=function(t){return this.clone().isubn(t)},a.prototype.iabs=function(){return this.negative=0,this},a.prototype.abs=function(){return this.clone().iabs()},a.prototype._ishlnsubmul=function(t,e,r){var i,a,o=t.length+r;this._expand(o);var s=0;for(i=0;i<t.length;i++){a=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((a-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i<this.length-r;i++)s=(a=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(a=-(0|this.words[i])+s)>>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!==(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var c=0;c<s.length;c++)s.words[c]=0}var u=n.clone()._ishlnsubmul(i,1,l);0===u.negative&&(n=u,s&&(s.words[l]=1));for(var f=l-1;f>=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),c=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++c;for(var u=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(u),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,m=1;0==(r.words[0]&m)&&d<26;++d,m<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(u),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(c)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var c=0,u=1;0==(e.words[0]&u)&&c<26;++c,u<<=1);if(c>0)for(e.iushrn(c);c-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=i,this;for(var a=i,o=r;0!==a&&o<this.length;o++){var s=0|this.words[o];a=(s+=a)>>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:i<t?-1:1}return 0!==this.negative?0|-e:e},a.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},a.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new w(t)},a.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,\"Already a number 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numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var g={k256:null,p224:null,p192:null,p25519:null};function v(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function y(){v.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff 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0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},i(x,v),i(b,v),i(_,v),_.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(g[t])return g[t];var e;if(\"k256\"===t)e=new y;else if(\"p224\"===t)e=new x;else if(\"p192\"===t)e=new b;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new _}return g[t]=e,e},w.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},w.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},w.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},w.prototype.neg=function(t){return 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r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),o=i;return i.cmp(this.m)>=0?o=i.isub(this.m):i.cmpn(0)<0&&(o=i.iadd(this.m)),o._forceRed(this)},T.prototype.invm=function(t){return this.imod(t._invmp(this.m).mul(this.r2))._forceRed(this)}}(void 0===e||e,this)},{buffer:115}],107:[function(t,e,r){\"use strict\";e.exports=function(t){var e,r,n,i=t.length,a=0;for(e=0;e<i;++e)a+=t[e].length;var o=new Array(a),s=0;for(e=0;e<i;++e){var l=t[e],c=l.length;for(r=0;r<c;++r){var u=o[s++]=new Array(c-1),f=0;for(n=0;n<c;++n)n!==r&&(u[f++]=l[n]);if(1&r){var h=u[1];u[1]=u[0],u[0]=h}}}return o}},{}],108:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){switch(arguments.length){case 1:return f(t);case 2:return\"function\"==typeof e?c(t,t,e,!0):h(t,e);case 3:return c(t,e,r,!1);default:throw new Error(\"box-intersect: Invalid arguments\")}};var n,i=t(\"typedarray-pool\"),a=t(\"./lib/sweep\"),o=t(\"./lib/intersect\");function 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M=s[c-1];s[c-1]=s[h],s[h]=M,h=n(t,e,l,c-1,o,s,p);for(_=f*(c-1),w=f*h,T=0;T<f;++T,++_,++w){k=o[_];o[_]=o[w],o[w]=k}M=s[c-1];if(s[c-1]=s[h],s[h]=M,u<h){for(c=h-1;l<c&&o[f*(c-1)+e]===p;)c-=1;c+=1}else{if(!(h<u))break;for(l=h+1;l<c&&o[f*l+e]===p;)l+=1}}return n(t,e,r,u,o,s,o[f*u+e])};var n=t(\"./partition\")(\"lo<p0\",[\"p0\"]);function i(t,e,r,n,i,a){for(var o=2*t,s=o*(r+1)+e,l=r+1;l<n;++l,s+=o)for(var c=i[s],u=l,f=o*(l-1);u>r&&i[f+e]>c;--u,f-=o){for(var h=f,p=f+o,d=0;d<o;++d,++h,++p){var m=i[h];i[h]=i[p],i[p]=m}var g=a[u];a[u]=a[u-1],a[u-1]=g}}},{\"./partition\":112}],112:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=\"abcdef\".split(\"\").concat(e),n=[];t.indexOf(\"lo\")>=0&&n.push(\"lo=e[k+n]\");t.indexOf(\"hi\")>=0&&n.push(\"hi=e[k+o]\");return r.push(\"for(var j=2*a,k=j*c,l=k,m=c,n=b,o=a+b,p=c;d>p;++p,k+=j){var _;if($)if(m===p)m+=1,l+=j;else{for(var s=0;j>s;++s){var t=e[k+s];e[k+s]=e[l],e[l++]=t}var u=f[p];f[p]=f[m],f[m++]=u}}return m\".replace(\"_\",n.join()).replace(\"$\",t)),Function.apply(void 0,r)}},{}],113:[function(t,e,r){\"use strict\";e.exports=function(t,e){e<=128?n(0,e-1,t):function t(e,r,u){var f=(r-e+1)/6|0,h=e+f,p=r-f,d=e+r>>1,m=d-f,g=d+f,v=h,y=m,x=d,b=g,_=p,w=e+1,T=r-1,k=0;l(v,y,u)&&(k=v,v=y,y=k);l(b,_,u)&&(k=b,b=_,_=k);l(v,x,u)&&(k=v,v=x,x=k);l(y,x,u)&&(k=y,y=x,x=k);l(v,b,u)&&(k=v,v=b,b=k);l(x,b,u)&&(k=x,x=b,b=k);l(y,_,u)&&(k=y,y=_,_=k);l(y,x,u)&&(k=y,y=x,x=k);l(b,_,u)&&(k=b,b=_,_=k);for(var M=u[2*y],A=u[2*y+1],S=u[2*b],E=u[2*b+1],L=2*v,C=2*x,P=2*_,I=2*h,O=2*d,z=2*p,D=0;D<2;++D){var R=u[L+D],F=u[C+D],B=u[P+D];u[I+D]=R,u[O+D]=F,u[z+D]=B}a(m,e,u),a(g,r,u);for(var N=w;N<=T;++N)if(c(N,M,A,u))N!==w&&i(N,w,u),++w;else if(!c(N,S,E,u))for(;;){if(c(T,S,E,u)){c(T,M,A,u)?(o(N,w,T,u),++w,--T):(i(N,T,u),--T);break}if(--T<N)break}s(e,w-1,M,A,u),s(r,T+1,S,E,u),w-2-e<=32?n(e,w-2,u):t(e,w-2,u);r-(T+2)<=32?n(T+2,r,u):t(T+2,r,u);T-w<=32?n(w,T,u):t(w,T,u)}(0,e-1,t)};function n(t,e,r){for(var n=2*(t+1),i=t+1;i<=e;++i){for(var a=r[n++],o=r[n++],s=i,l=n-2;s-- >t;){var c=r[l-2],u=r[l-1];if(c<a)break;if(c===a&&u<o)break;r[l]=c,r[l+1]=u,l-=2}r[l]=a,r[l+1]=o}}function i(t,e,r){e*=2;var n=r[t*=2],i=r[t+1];r[t]=r[e],r[t+1]=r[e+1],r[e]=n,r[e+1]=i}function a(t,e,r){e*=2,r[t*=2]=r[e],r[t+1]=r[e+1]}function o(t,e,r,n){e*=2,r*=2;var i=n[t*=2],a=n[t+1];n[t]=n[e],n[t+1]=n[e+1],n[e]=n[r],n[e+1]=n[r+1],n[r]=i,n[r+1]=a}function s(t,e,r,n,i){e*=2,i[t*=2]=i[e],i[e]=r,i[t+1]=i[e+1],i[e+1]=n}function l(t,e,r){e*=2;var n=r[t*=2],i=r[e];return!(n<i)&&(n!==i||r[t+1]>r[e+1])}function c(t,e,r,n){var i=n[t*=2];return i<e||i===e&&n[t+1]<r}},{}],114:[function(t,e,r){\"use strict\";e.exports={init:function(t){var e=i.nextPow2(t);o.length<e&&(n.free(o),o=n.mallocInt32(e));s.length<e&&(n.free(s),s=n.mallocInt32(e));l.length<e&&(n.free(l),l=n.mallocInt32(e));c.length<e&&(n.free(c),c=n.mallocInt32(e));u.length<e&&(n.free(u),u=n.mallocInt32(e));f.length<e&&(n.free(f),f=n.mallocInt32(e));var r=8*e;h.length<r&&(n.free(h),h=n.mallocDouble(r))},sweepBipartite:function(t,e,r,n,i,u,f,m,g,v){for(var y=0,x=2*t,b=t-1,_=x-1,w=r;w<n;++w){var T=u[w],k=x*w;h[y++]=i[k+b],h[y++]=-(T+1),h[y++]=i[k+_],h[y++]=T}for(w=f;w<m;++w){T=v[w]+(1<<28);var M=x*w;h[y++]=g[M+b],h[y++]=-T,h[y++]=g[M+_],h[y++]=T}var A=y>>>1;a(h,A);var S=0,E=0;for(w=0;w<A;++w){var L=0|h[2*w+1];if(L>=1<<28)p(l,c,E--,L=L-(1<<28)|0);else if(L>=0)p(o,s,S--,L);else if(L<=-(1<<28)){L=-L-(1<<28)|0;for(var C=0;C<S;++C){if(void 0!==(P=e(o[C],L)))return P}d(l,c,E++,L)}else{L=-L-1|0;for(C=0;C<E;++C){var P;if(void 0!==(P=e(L,l[C])))return P}d(o,s,S++,L)}}},sweepComplete:function(t,e,r,n,i,m,g,v,y,x){for(var b=0,_=2*t,w=t-1,T=_-1,k=r;k<n;++k){var M=m[k]+1<<1,A=_*k;h[b++]=i[A+w],h[b++]=-M,h[b++]=i[A+T],h[b++]=M}for(k=g;k<v;++k){M=x[k]+1<<1;var S=_*k;h[b++]=y[S+w],h[b++]=1|-M,h[b++]=y[S+T],h[b++]=1|M}var E=b>>>1;a(h,E);var L=0,C=0,P=0;for(k=0;k<E;++k){var I=0|h[2*k+1],O=1&I;if(k<E-1&&I>>1==h[2*k+3]>>1&&(O=2,k+=1),I<0){for(var 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p(o,s,L--,C-w)}},scanComplete:function(t,e,r,n,i,s,l,c,u,f,p){for(var d=0,m=2*t,g=e,v=e+t,y=n;y<i;++y){var x=y+(1<<28),b=m*y;h[d++]=s[b+g],h[d++]=-x,h[d++]=s[b+v],h[d++]=x}for(y=c;y<u;++y){x=y+1;var _=m*y;h[d++]=f[_+g],h[d++]=-x}var w=d>>>1;a(h,w);var T=0;for(y=0;y<w;++y){var k=0|h[2*y+1];if(k<0){if((x=-k)>=1<<28)o[T++]=x-(1<<28);else{var M=p[x-=1],A=m*x,S=f[A+e+1],E=f[A+e+1+t];t:for(var L=0;L<T;++L){var C=o[L],P=l[C];if(P===M)break;var I=m*C;if(!(E<s[I+e+1]||s[I+e+1+t]<S)){for(var O=e+2;O<t;++O)if(f[A+O+t]<s[I+O]||s[I+O+t]<f[A+O])continue t;var z=r(P,M);if(void 0!==z)return z}}}}else{for(x=k-(1<<28),L=T-1;L>=0;--L)if(o[L]===x){for(O=L+1;O<T;++O)o[O-1]=o[O];break}--T}}}};var n=t(\"typedarray-pool\"),i=t(\"bit-twiddle\"),a=t(\"./sort\"),o=n.mallocInt32(1024),s=n.mallocInt32(1024),l=n.mallocInt32(1024),c=n.mallocInt32(1024),u=n.mallocInt32(1024),f=n.mallocInt32(1024),h=n.mallocDouble(8192);function p(t,e,r,n){var i=e[n],a=t[r-1];t[i]=a,e[a]=i}function d(t,e,r,n){t[r]=n,e[n]=r}},{\"./sort\":113,\"bit-twiddle\":104,\"typedarray-pool\":613}],115:[function(t,e,r){},{}],116:[function(t,e,r){\"use strict\";var n,i=\"object\"==typeof Reflect?Reflect:null,a=i&&\"function\"==typeof i.apply?i.apply:function(t,e,r){return Function.prototype.apply.call(t,e,r)};n=i&&\"function\"==typeof i.ownKeys?i.ownKeys:Object.getOwnPropertySymbols?function(t){return Object.getOwnPropertyNames(t).concat(Object.getOwnPropertySymbols(t))}:function(t){return Object.getOwnPropertyNames(t)};var o=Number.isNaN||function(t){return t!=t};function s(){s.init.call(this)}e.exports=s,e.exports.once=function(t,e){return new Promise((function(r,n){function i(){void 0!==a&&t.removeListener(\"error\",a),r([].slice.call(arguments))}var a;\"error\"!==e&&(a=function(r){t.removeListener(e,i),n(r)},t.once(\"error\",a)),t.once(e,i)}))},s.EventEmitter=s,s.prototype._events=void 0,s.prototype._eventsCount=0,s.prototype._maxListeners=void 0;var l=10;function c(t){if(\"function\"!=typeof t)throw new TypeError('The \"listener\" argument must be of type Function. 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+              "/*!\n",
+              " * The buffer module from node.js, for the browser.\n",
+              " *\n",
+              " * @author   Feross Aboukhadijeh <https://feross.org>\n",
+              " * @license  MIT\n",
+              " */\n",
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t<e?-1:t>e?1:0}Object.defineProperty(p,\"valid\",{get:function(){return this._stack.length>0}}),Object.defineProperty(p,\"node\",{get:function(){return this._stack.length>0?this._stack[this._stack.length-1]:null},enumerable:!0}),p.clone=function(){return new h(this.tree,this._stack.slice())},p.remove=function(){var t=this._stack;if(0===t.length)return this.tree;var e=new Array(t.length),r=t[t.length-1];e[e.length-1]=new n(r._color,r.key,r.value,r.left,r.right,r._count);for(var l=t.length-2;l>=0;--l){(r=t[l]).left===t[l+1]?e[l]=new n(r._color,r.key,r.value,e[l+1],r.right,r._count):e[l]=new n(r._color,r.key,r.value,r.left,e[l+1],r._count)}if((r=e[e.length-1]).left&&r.right){var c=e.length;for(r=r.left;r.right;)e.push(r),r=r.right;var u=e[c-1];e.push(new n(r._color,u.key,u.value,r.left,r.right,r._count)),e[c-1].key=r.key,e[c-1].value=r.value;for(l=e.length-2;l>=c;--l)r=e[l],e[l]=new n(r._color,r.key,r.value,r.left,e[l+1],r._count);e[c-1].left=e[c]}if(0===(r=e[e.length-1])._color){var f=e[e.length-2];f.left===r?f.left=null:f.right===r&&(f.right=null),e.pop();for(l=0;l<e.length;++l)e[l]._count--;return new s(this.tree._compare,e[0])}if(r.left||r.right){r.left?d(r,r.left):r.right&&d(r,r.right),r._color=1;for(l=0;l<e.length-1;++l)e[l]._count--;return new s(this.tree._compare,e[0])}if(1===e.length)return new s(this.tree._compare,null);for(l=0;l<e.length;++l)e[l]._count--;var h=e[e.length-2];return function(t){for(var e,r,n,s,l=t.length-1;l>=0;--l){if(e=t[l],0===l)return void(e._color=1);if((r=t[l-1]).left===e){if((n=r.right).right&&0===n.right._color){if(s=(n=r.right=i(n)).right=i(n.right),r.right=n.left,n.left=r,n.right=s,n._color=r._color,e._color=1,r._color=1,s._color=1,o(r),o(n),l>1)(c=t[l-2]).left===r?c.left=n:c.right=n;return void(t[l-1]=n)}if(n.left&&0===n.left._color){if(s=(n=r.right=i(n)).left=i(n.left),r.right=s.left,n.left=s.right,s.left=r,s.right=n,s._color=r._color,r._color=1,n._color=1,e._color=1,o(r),o(n),o(s),l>1)(c=t[l-2]).left===r?c.left=s:c.right=s;return void(t[l-1]=s)}if(1===n._color){if(0===r._color)return r._color=1,void(r.right=a(0,n));r.right=a(0,n);continue}n=i(n),r.right=n.left,n.left=r,n._color=r._color,r._color=0,o(r),o(n),l>1&&((c=t[l-2]).left===r?c.left=n:c.right=n),t[l-1]=n,t[l]=r,l+1<t.length?t[l+1]=e:t.push(e),l+=2}else{if((n=r.left).left&&0===n.left._color){if(s=(n=r.left=i(n)).left=i(n.left),r.left=n.right,n.right=r,n.left=s,n._color=r._color,e._color=1,r._color=1,s._color=1,o(r),o(n),l>1)(c=t[l-2]).right===r?c.right=n:c.left=n;return void(t[l-1]=n)}if(n.right&&0===n.right._color){if(s=(n=r.left=i(n)).right=i(n.right),r.left=s.right,n.right=s.left,s.right=r,s.left=n,s._color=r._color,r._color=1,n._color=1,e._color=1,o(r),o(n),o(s),l>1)(c=t[l-2]).right===r?c.right=s:c.left=s;return void(t[l-1]=s)}if(1===n._color){if(0===r._color)return r._color=1,void(r.left=a(0,n));r.left=a(0,n);continue}var c;n=i(n),r.left=n.right,n.right=r,n._color=r._color,r._color=0,o(r),o(n),l>1&&((c=t[l-2]).right===r?c.right=n:c.left=n),t[l-1]=n,t[l]=r,l+1<t.length?t[l+1]=e:t.push(e),l+=2}}}(e),h.left===r?h.left=null:h.right=null,new s(this.tree._compare,e[0])},Object.defineProperty(p,\"key\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].key},enumerable:!0}),Object.defineProperty(p,\"value\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].value},enumerable:!0}),Object.defineProperty(p,\"index\",{get:function(){var t=0,e=this._stack;if(0===e.length){var r=this.tree.root;return r?r._count:0}e[e.length-1].left&&(t=e[e.length-1].left._count);for(var n=e.length-2;n>=0;--n)e[n+1]===e[n].right&&(++t,e[n].left&&(t+=e[n].left._count));return t},enumerable:!0}),p.next=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.right)for(e=e.right;e;)t.push(e),e=e.left;else for(t.pop();t.length>0&&t[t.length-1].right===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(p,\"hasNext\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].right)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].left===t[e])return!0;return!1}}),p.update=function(t){var e=this._stack;if(0===e.length)throw new Error(\"Can't update empty node!\");var r=new Array(e.length),i=e[e.length-1];r[r.length-1]=new n(i._color,i.key,t,i.left,i.right,i._count);for(var a=e.length-2;a>=0;--a)(i=e[a]).left===e[a+1]?r[a]=new n(i._color,i.key,i.value,r[a+1],i.right,i._count):r[a]=new n(i._color,i.key,i.value,i.left,r[a+1],i._count);return new s(this.tree._compare,r[0])},p.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(p,\"hasPrev\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},{}],252:[function(t,e,r){var n=[.9999999999998099,676.5203681218851,-1259.1392167224028,771.3234287776531,-176.6150291621406,12.507343278686905,-.13857109526572012,9984369578019572e-21,1.5056327351493116e-7],i=[.9999999999999971,57.15623566586292,-59.59796035547549,14.136097974741746,-.4919138160976202,3399464998481189e-20,4652362892704858e-20,-9837447530487956e-20,.0001580887032249125,-.00021026444172410488,.00021743961811521265,-.0001643181065367639,8441822398385275e-20,-26190838401581408e-21,36899182659531625e-22];function a(t){if(t<0)return Number(\"0/0\");for(var e=i[0],r=i.length-1;r>0;--r)e+=i[r]/(t+r);var n=t+607/128+.5;return.5*Math.log(2*Math.PI)+(t+.5)*Math.log(n)-n+Math.log(e)-Math.log(t)}e.exports=function t(e){if(e<.5)return Math.PI/(Math.sin(Math.PI*e)*t(1-e));if(e>100)return Math.exp(a(e));e-=1;for(var r=n[0],i=1;i<9;i++)r+=n[i]/(e+i);var o=e+7+.5;return Math.sqrt(2*Math.PI)*Math.pow(o,e+.5)*Math.exp(-o)*r},e.exports.log=a},{}],253:[function(t,e,r){e.exports=function(t,e){if(\"string\"!=typeof t)throw new TypeError(\"must specify type string\");if(e=e||{},\"undefined\"==typeof document&&!e.canvas)return null;var r=e.canvas||document.createElement(\"canvas\");\"number\"==typeof e.width&&(r.width=e.width);\"number\"==typeof e.height&&(r.height=e.height);var n,i=e;try{var a=[t];0===t.indexOf(\"webgl\")&&a.push(\"experimental-\"+t);for(var o=0;o<a.length;o++)if(n=r.getContext(a[o],i))return n}catch(t){n=null}return n||null}},{}],254:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=new u(t);return r.update(e),r};var n=t(\"./lib/text.js\"),i=t(\"./lib/lines.js\"),a=t(\"./lib/background.js\"),o=t(\"./lib/cube.js\"),s=t(\"./lib/ticks.js\"),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function c(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function u(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=a(t)}var f=u.prototype;function h(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}f.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;s<3;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,a=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),c=e.bind(this,!0,(function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]})),u=!1,f=!1;if(\"bounds\"in t)for(var h=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)h[p][d]!==this.bounds[p][d]&&(f=!0),this.bounds[p][d]=h[p][d];if(\"ticks\"in t){r=t.ticks,u=!0,this.autoTicks=!1;for(p=0;p<3;++p)this.tickSpacing[p]=0}else a(\"tickSpacing\")&&(this.autoTicks=!0,f=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),f=!0,u=!0,this._firstInit=!1),f&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),u=!0),u){for(p=0;p<3;++p)r[p].sort((function(t,e){return t.x-e.x}));s.equal(r,this.ticks)?u=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(u=!0),a(\"tickSize\"),a(\"tickAngle\"),a(\"tickPad\"),c(\"tickColor\");var m=l(\"labels\");l(\"labelFont\")&&(m=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),c(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),c(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),c(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),c(\"gridColor\"),o(\"zeroEnable\"),c(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),c(\"backgroundColor\"),this._text?this._text&&(m||u)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&u&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,c=n[e],u=0;u<3;++u)if(e!==u){var f=a,h=s,p=o,d=l;c&1<<u&&(f=s,h=a,p=l,d=o),f[u]=r[0][u],h[u]=r[1][u],i[u]>0?(p[u]=-1,d[u]=0):(p[u]=0,d[u]=1)}}var m=[0,0,0],g={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var v=[0,0,0],y=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||g;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,u=o(r,n,i,a,s),f=u.cubeEdges,h=u.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,M=0;M<3;++M)this.lastCubeProps.cubeEdges[M]=f[M],this.lastCubeProps.axis[M]=h[M];var A=p;for(M=0;M<3;++M)d(p[M],M,this.bounds,f,h);e=this.gl;var S,E=m;for(M=0;M<3;++M)this.backgroundEnable[M]?E[M]=h[M]:E[M]=0;this._background.draw(r,n,i,a,E,this.backgroundColor),this._lines.bind(r,n,i,this);for(M=0;M<3;++M){var L=[0,0,0];h[M]>0?L[M]=a[1][M]:L[M]=a[0][M];for(var C=0;C<2;++C){var P=(M+1+C)%3,I=(M+1+(1^C))%3;this.gridEnable[P]&&this._lines.drawGrid(P,I,this.bounds,L,this.gridColor[P],this.gridWidth[P]*this.pixelRatio)}for(C=0;C<2;++C){P=(M+1+C)%3,I=(M+1+(1^C))%3;this.zeroEnable[I]&&Math.min(a[0][I],a[1][I])<=0&&Math.max(a[0][I],a[1][I])>=0&&this._lines.drawZero(P,I,this.bounds,L,this.zeroLineColor[I],this.zeroLineWidth[I]*this.pixelRatio)}}for(M=0;M<3;++M){this.lineEnable[M]&&this._lines.drawAxisLine(M,this.bounds,A[M].primalOffset,this.lineColor[M],this.lineWidth[M]*this.pixelRatio),this.lineMirror[M]&&this._lines.drawAxisLine(M,this.bounds,A[M].mirrorOffset,this.lineColor[M],this.lineWidth[M]*this.pixelRatio);var O=c(v,A[M].primalMinor),z=c(y,A[M].mirrorMinor),D=this.lineTickLength;for(C=0;C<3;++C){var R=k/r[5*C];O[C]*=D[C]*R,z[C]*=D[C]*R}this.lineTickEnable[M]&&this._lines.drawAxisTicks(M,A[M].primalOffset,O,this.lineTickColor[M],this.lineTickWidth[M]*this.pixelRatio),this.lineTickMirror[M]&&this._lines.drawAxisTicks(M,A[M].mirrorOffset,z,this.lineTickColor[M],this.lineTickWidth[M]*this.pixelRatio)}this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio);var F,B;function N(t){(B=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(M=0;M<3;++M){var U=A[M].primalMinor,V=A[M].mirrorMinor,q=c(x,A[M].primalOffset);for(C=0;C<3;++C)this.lineTickEnable[M]&&(q[C]+=k*U[C]*Math.max(this.lineTickLength[C],0)/r[5*C]);var H=[0,0,0];if(H[M]=1,this.tickEnable[M]){-3600===this.tickAngle[M]?(this.tickAngle[M]=0,this.tickAlign[M]=\"auto\"):this.tickAlign[M]=-1,F=1,\"auto\"===(S=[this.tickAlign[M],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),B=[0,0,0],j(M,U,V);for(C=0;C<3;++C)q[C]+=k*U[C]*this.tickPad[C]/r[5*C];this._text.drawTicks(M,this.tickSize[M],this.tickAngle[M],q,this.tickColor[M],H,B,S)}if(this.labelEnable[M]){F=0,B=[0,0,0],this.labels[M].length>4&&(N(M),F=1),\"auto\"===(S=[this.labelAlign[M],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]);for(C=0;C<3;++C)q[C]+=k*U[C]*this.labelPad[C]/r[5*C];q[M]+=.5*(a[0][M]+a[1][M]),this._text.drawLabel(M,this.labelSize[M],this.labelAngle[M],q,this.labelColor[M],[0,0,0],B,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":255,\"./lib/cube.js\":256,\"./lib/lines.js\":257,\"./lib/text.js\":259,\"./lib/ticks.js\":260}],255:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var c=(l+1)%3,u=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[c]=d;for(var m=-1;m<=1;m+=2)f[u]=m,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var g=c;c=u,u=g}var v=n(t,new Float32Array(e)),y=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:v,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:v,type:t.FLOAT,size:3,offset:12,stride:24}],y),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,v,x,b)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":258,\"gl-buffer\":263,\"gl-vao\":357}],256:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var y=0,x=0;x<2;++x){u[2]=a[x][2];for(var b=0;b<2;++b){u[1]=a[b][1];for(var _=0;_<2;++_)u[0]=a[_][0],h(l[y],u,s),y+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)c[x][k]=l[x][k]/T;p&&(c[x][2]*=-1),T<0&&(w<0||c[x][2]<c[w][2])&&(w=x)}if(w<0){w=0;for(var M=0;M<3;++M){for(var A=(M+2)%3,S=(M+1)%3,E=-1,L=-1,C=0;C<2;++C){var P=(O=C<<M)+(C<<A)+(1-C<<S),I=O+(1-C<<A)+(C<<S);o(c[O],c[P],c[I],f)<0||(C?E=1:L=1)}if(E<0||L<0)L>E&&(w|=1<<M);else{for(C=0;C<2;++C){P=(O=C<<M)+(C<<A)+(1-C<<S),I=O+(1-C<<A)+(C<<S);var O,z=d([l[O],l[P],l[I],l[O+(1<<A)+(1<<S)]]);C?E=z:L=z}L>E&&(w|=1<<M)}}}var D=7^w,R=-1;for(x=0;x<8;++x)x!==w&&x!==D&&(R<0||c[R][1]>c[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x){if((N=R^1<<x)!==w&&N!==D)F<0&&(F=N),(S=c[N])[0]<c[F][0]&&(F=N)}var B=-1;for(x=0;x<3;++x){var N;if((N=R^1<<x)!==w&&N!==D&&N!==F)B<0&&(B=N),(S=c[N])[0]>c[B][0]&&(B=N)}var j=m;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===D?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=g,q=w;for(M=0;M<3;++M)V[M]=q&1<<M?-1:1;return v};var n=t(\"bit-twiddle\"),i=t(\"gl-mat4/multiply\"),a=t(\"split-polygon\"),o=t(\"robust-orientation\"),s=new Array(16),l=new Array(8),c=new Array(8),u=new Array(3),f=[0,0,0];function h(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var i=0;i<3;++i)t[n]+=e[i]*r[4*i+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],c[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=a.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],i=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],c=s[0]/s[3]-n,u=s[1]/s[3]-i,f=l[0]/l[3]-n,h=l[1]/l[3]-i;o+=Math.abs(c*h-u*f)}return o}var m=[1,1,1],g=[0,0,0],v={cubeEdges:m,axis:g}},{\"bit-twiddle\":104,\"gl-mat4/multiply\":297,\"robust-orientation\":544,\"split-polygon\":563}],257:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var f=0;f<3;++f){for(var h=o.length/3|0,d=0;d<r[f].length;++d){var m=+r[f][d].x;o.push(m,0,1,m,1,1,m,0,-1,m,0,-1,m,1,1,m,1,-1)}var g=o.length/3|0;s[f]=h,l[f]=g-h;h=o.length/3|0;for(var v=0;v<r[f].length;++v){m=+r[f][v].x;o.push(m,0,1,m,1,1,m,0,-1,m,0,-1,m,1,1,m,1,-1)}g=o.length/3|0;c[f]=h,u[f]=g-h}var y=n(t,new Float32Array(o)),x=i(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),b=a(t);return b.attributes.position.location=0,new p(t,y,x,b,l,s,u,c)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").line,o=[0,0,0],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[1,1];function f(t){return t[0]=t[1]=t[2]=0,t}function h(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,u[0]=this.gl.drawingBufferWidth,u[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=u,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,i){var a=f(s);this.shader.uniforms.majorAxis=s,a[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=a;var o,u=h(c,r);u[t]+=e[0][t],this.shader.uniforms.offset=u,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=n,(o=f(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=f(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=f(o);a[t]=1,this.shader.uniforms.majorAxis=a,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=i;var s=f(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,i,a){if(this.gridCount[t]){var u=f(s);u[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=u;var p=h(c,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=f(o);d[t]=1,this.shader.uniforms.majorAxis=d;var m=f(l);m[t]=1,this.shader.uniforms.screenAxis=m,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,i,a){var o=f(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var u=h(c,n);u[t]+=r[0][t],this.shader.uniforms.offset=u;var p=f(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":258,\"gl-buffer\":263,\"gl-vao\":357}],258:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);r.line=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n  vec3 A = project(a);\\n  vec3 B = project(b);\\n\\n  return atan(\\n    (B.y - A.y) * resolution.y,\\n    (B.x - A.x) * resolution.x\\n  );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio =       alignOpt.y;\\nbool enableAlign =    (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n  return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n  return mod_angle((a < 0.0) ?\\n    a + TWO_PI :\\n    a\\n  );\\n}\\n\\nfloat look_upwards(float a) {\\n  float b = positive_angle(a);\\n  return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n    b - PI :\\n    b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n  // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n  // if ratio is set to 0.5 then it is 50%, 50%.\\n  // when using a higher ratio e.g. 0.75 the result would\\n  // likely be more horizontal than vertical.\\n\\n  float b = positive_angle(a);\\n\\n  return\\n    (b < (      ratio) * HALF_PI) ? 0.0 :\\n    (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n    (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n    (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n                                    0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n  return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n  float b = positive_angle(a);\\n  float div = TWO_PI / float(n);\\n  float c = roundTo(b, div);\\n  return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n  return\\n    (option >  2) ? look_round_n_directions(rawAngle + delta, option) :       // option 3-n: round to n directions\\n    (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n    (option == 1) ? rawAngle + delta :       // use free angle, and flip to align with one direction of the axis\\n    (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n    (option ==-1) ? 0.0 :                    // useful for backward compatibility, all texts remains horizontal\\n                    rawAngle;                // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n                   (axis.y == 0.0) &&\\n                   (axis.z == 0.0);\\n\\nvoid main() {\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n\\n  float beta = angle; // i.e. user defined attributes for each tick\\n\\n  float axisAngle;\\n  float clipAngle;\\n  float flip;\\n\\n  if (enableAlign) {\\n    axisAngle = (isAxisTitle) ? HALF_PI :\\n                      computeViewAngle(dataPosition, dataPosition + axis);\\n    clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n    axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n    clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n    flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n                vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n    beta += applyAlignOption(clipAngle, flip * PI);\\n  }\\n\\n  //Compute plane offset\\n  vec2 planeCoord = position.xy * pixelScale;\\n\\n  mat2 planeXform = scale * mat2(\\n     cos(beta), sin(beta),\\n    -sin(beta), cos(beta)\\n  );\\n\\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n  //Compute clip position\\n  vec3 clipPosition = project(dataPosition);\\n\\n  //Apply text offset in clip coordinates\\n  clipPosition += vec3(viewOffset, 0.0);\\n\\n  //Done\\n  gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);r.text=function(t){return i(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n  vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n  vec3 realNormal = signAxis * normal;\\n\\n  if(dot(realNormal, enable) > 0.0) {\\n    vec3 minRange = min(bounds[0], bounds[1]);\\n    vec3 maxRange = max(bounds[0], bounds[1]);\\n    vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n    gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n  } else {\\n    gl_Position = vec4(0,0,0,0);\\n  }\\n\\n  colorChannel = abs(realNormal);\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n  gl_FragColor = colorChannel.x * colors[0] +\\n                 colorChannel.y * colors[1] +\\n                 colorChannel.z * colors[2];\\n}\"]);r.bg=function(t){return i(t,c,u,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},{\"gl-shader\":335,glslify:261}],259:[function(t,e,r){(function(r){(function(){\"use strict\";e.exports=function(t,e,r,a,s,l){var u=n(t),f=i(t,[{buffer:u,size:3}]),h=o(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,a,s,l),p};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"vectorize-text\"),o=t(\"./shaders\").text,s=window||r.global||{},l=s.__TEXT_CACHE||{};s.__TEXT_CACHE={};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}var u=c.prototype,f=[0,0];u.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,f[0]=this.gl.drawingBufferWidth,f[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=f},u.unbind=function(){this.vao.unbind()},u.update=function(t,e,r,n,i){var o=[];function s(t,e,r,n,i,s){var 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m=0;m<n[d].length;++m)n[d][m].text&&s(n[d][m].x,n[d][m].text,n[d][m].font||i,n[d][m].fontSize||12,1.25,p);u[d]=(o.length/3|0)-c[d]}this.buffer.update(o),this.tickOffset=c,this.tickCount=u,this.labelOffset=f,this.labelCount=h},u.drawTicks=function(t,e,r,n,i,a,o,s){this.tickCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t]))},u.drawLabel=function(t,e,r,n,i,a,o,s){this.labelCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.labelCount[t],this.labelOffset[t]))},u.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()}}).call(this)}).call(this,t(\"_process\"))},{\"./shaders\":258,_process:524,\"gl-buffer\":263,\"gl-vao\":357,\"vectorize-text\":619}],260:[function(t,e,r){\"use 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n=t(\"extract-frustum-planes\"),i=t(\"split-polygon\"),a=t(\"./lib/cube.js\"),o=t(\"gl-mat4/multiply\"),s=t(\"gl-mat4/transpose\"),l=t(\"gl-vec4/transformMat4\"),c=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),u=new Float32Array(16);function f(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var h=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=h,s=p,c=0;c<3;++c)s[c]=o[c]=r[c];s[3]=o[3]=1,s[a]+=1,l(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,l(o,o,e),o[3]<0&&(t[a]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,f=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(u*u+f*f)}return t}var m=[new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0)],g=[0,0,0]},{\"./lib/cube.js\":256,\"extract-frustum-planes\":244,\"gl-mat4/multiply\":297,\"gl-mat4/transpose\":308,\"gl-vec4/transformMat4\":428,\"split-polygon\":563}],263:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\"),i=t(\"ndarray-ops\"),a=t(\"ndarray\"),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}var l=s.prototype;function c(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function u(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a<i;++a)r[a]=t[a];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&void 0!==t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER)r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\";if(r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=c(this.gl,this.type,this.length,this.usage,t.data,e):this.length=c(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=c(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?u(t,\"uint16\"):u(t,\"float32\"),this.length=c(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=c(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},e.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},{ndarray:479,\"ndarray-ops\":474,\"typedarray-pool\":613}],264:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\");e.exports=function(t,e){var r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,c=1/0,u=-1/0,f=1/0,h=-1/0,p=null,d=null,m=[],g=1/0,v=!1,y=0;y<r.length;y++){var x=r[y];s=Math.min(x[0],s),l=Math.max(x[0],l),c=Math.min(x[1],c),u=Math.max(x[1],u),f=Math.min(x[2],f),h=Math.max(x[2],h);var b=i[y];if(n.length(b)>o&&(o=n.length(b)),y){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(g=Math.min(g,_),v=!1):v=!0}v||(p=x,d=b),m.push(b)}var w=[s,c,f],T=[l,u,h];e&&(e[0]=w,e[1]=T),0===o&&(o=1);var k=1/o;isFinite(g)||(g=1),a.vectorScale=g;var M=t.coneSize||.5;t.absoluteConeSize&&(M=t.absoluteConeSize*k),a.coneScale=M;y=0;for(var A=0;y<r.length;y++)for(var S=(x=r[y])[0],E=x[1],L=x[2],C=m[y],P=n.length(C)*k,I=0;I<8;I++){a.positions.push([S,E,L,A++]),a.positions.push([S,E,L,A++]),a.positions.push([S,E,L,A++]),a.positions.push([S,E,L,A++]),a.positions.push([S,E,L,A++]),a.positions.push([S,E,L,A++]),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vertexIntensity.push(P,P,P),a.vertexIntensity.push(P,P,P);var O=a.positions.length;a.cells.push([O-6,O-5,O-4],[O-3,O-2,O-1])}return a};var i=t(\"./lib/shaders\");e.exports.createMesh=t(\"./create_mesh\"),e.exports.createConeMesh=function(t,r){return e.exports.createMesh(t,r,{shaders:i,traceType:\"cone\"})}},{\"./create_mesh\":265,\"./lib/shaders\":266,\"gl-vec3\":376}],265:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"gl-mat4/multiply\"),l=t(\"gl-mat4/invert\"),c=t(\"ndarray\"),u=t(\"colormap\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e,r,n,i,a,o,s,l,c,u){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=c,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=u,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=f,this._view=f,this._projection=f,this._resolution=[1,1]}var p=h.prototype;function d(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}function m(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=u({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return c(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,m=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],m=+t.vertexIntensityBounds[1];else for(var g=0;g<p.length;++g){var v=p[g];d=Math.min(d,v),m=Math.max(m,v)}else for(g=0;g<n.length;++g){v=n[g][2];d=Math.min(d,v),m=Math.max(m,v)}this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(g=0;g<n.length;++g)for(var y=n[g],x=0;x<3;++x)!isNaN(y[x])&&isFinite(y[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],y[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],y[x]));var b=0;t:for(g=0;g<r.length;++g){var _=r[g];switch(_.length){case 3:for(x=0;x<3;++x){y=n[T=_[x]];for(var w=0;w<3;++w)if(isNaN(y[w])||!isFinite(y[w]))continue t}for(x=0;x<3;++x){var T;y=n[T=_[2-x]];a.push(y[0],y[1],y[2],y[3]);var k=i[T];o.push(k[0],k[1],k[2],k[3]||0);var M,A=h;3===A.length?s.push(A[0],A[1],A[2],1):s.push(A[0],A[1],A[2],A[3]),M=p?[(p[T]-d)/(m-d),0]:[(y[2]-d)/(m-d),0],l.push(M[0],M[1]),f.push(g)}b+=1}}this.triangleCount=b,this.trianglePositions.update(a),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(f))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var c={model:r,view:n,projection:i,inverseModel:f.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};c.inverseModel=l(c.inverseModel,c.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);s(u,c.view,c.model),s(u,c.projection,u),l(u,u);for(o=0;o<3;++o)c.eyePosition[o]=u[12+o]/u[15];var h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];c.lightPosition[o]=p/h}if(this.triangleCount>0){var m=this.triShader;m.bind(),m.uniforms=c,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},e.exports=function(t,e,r){var n=r.shaders;1===arguments.length&&(t=(e=t).gl);var s=d(t,n),l=m(t,n),u=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));u.generateMipmap(),u.minFilter=t.LINEAR_MIPMAP_LINEAR,u.magFilter=t.LINEAR;var f=i(t),p=i(t),g=i(t),v=i(t),y=i(t),x=a(t,[{buffer:f,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:g,type:t.FLOAT,size:4},{buffer:v,type:t.FLOAT,size:2},{buffer:p,type:t.FLOAT,size:4}]),b=new h(t,u,s,l,f,p,y,g,v,x,r.traceType||\"cone\");return b.update(e),b}},{colormap:137,\"gl-buffer\":263,\"gl-mat4/invert\":295,\"gl-mat4/multiply\":297,\"gl-shader\":335,\"gl-texture2d\":352,\"gl-vao\":357,ndarray:479}],266:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * conePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(conePosition, 1.0);\\n  vec4 t_position  = view * conePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = conePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n  gl_Position = projection * view * conePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec3\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec3\"}]}},{glslify:438}],267:[function(t,e,r){e.exports={0:\"NONE\",1:\"ONE\",2:\"LINE_LOOP\",3:\"LINE_STRIP\",4:\"TRIANGLES\",5:\"TRIANGLE_STRIP\",6:\"TRIANGLE_FAN\",256:\"DEPTH_BUFFER_BIT\",512:\"NEVER\",513:\"LESS\",514:\"EQUAL\",515:\"LEQUAL\",516:\"GREATER\",517:\"NOTEQUAL\",518:\"GEQUAL\",519:\"ALWAYS\",768:\"SRC_COLOR\",769:\"ONE_MINUS_SRC_COLOR\",770:\"SRC_ALPHA\",771:\"ONE_MINUS_SRC_ALPHA\",772:\"DST_ALPHA\",773:\"ONE_MINUS_DST_ALPHA\",774:\"DST_COLOR\",775:\"ONE_MINUS_DST_COLOR\",776:\"SRC_ALPHA_SATURATE\",1024:\"STENCIL_BUFFER_BIT\",1028:\"FRONT\",1029:\"BACK\",1032:\"FRONT_AND_BACK\",1280:\"INVALID_ENUM\",1281:\"INVALID_VALUE\",1282:\"INVALID_OPERATION\",1285:\"OUT_OF_MEMORY\",1286:\"INVALID_FRAMEBUFFER_OPERATION\",2304:\"CW\",2305:\"CCW\",2849:\"LINE_WIDTH\",2884:\"CULL_FACE\",2885:\"CULL_FACE_MODE\",2886:\"FRONT_FACE\",2928:\"DEPTH_RANGE\",2929:\"DEPTH_TEST\",2930:\"DEPTH_WRITEMASK\",2931:\"DEPTH_CLEAR_VALUE\",2932:\"DEPTH_FUNC\",2960:\"STENCIL_TEST\",2961:\"STENCIL_CLEAR_VALUE\",2962:\"STENCIL_FUNC\",2963:\"STENCIL_VALUE_MASK\",2964:\"STENCIL_FAIL\",2965:\"STENCIL_PASS_DEPTH_FAIL\",2966:\"STENCIL_PASS_DEPTH_PASS\",2967:\"STENCIL_REF\",2968:\"STENCIL_WRITEMASK\",2978:\"VIEWPORT\",3024:\"DITHER\",3042:\"BLEND\",3088:\"SCISSOR_BOX\",3089:\"SCISSOR_TEST\",3106:\"COLOR_CLEAR_VALUE\",3107:\"COLOR_WRITEMASK\",3317:\"UNPACK_ALIGNMENT\",3333:\"PACK_ALIGNMENT\",3379:\"MAX_TEXTURE_SIZE\",3386:\"MAX_VIEWPORT_DIMS\",3408:\"SUBPIXEL_BITS\",3410:\"RED_BITS\",3411:\"GREEN_BITS\",3412:\"BLUE_BITS\",3413:\"ALPHA_BITS\",3414:\"DEPTH_BITS\",3415:\"STENCIL_BITS\",3553:\"TEXTURE_2D\",4352:\"DONT_CARE\",4353:\"FASTEST\",4354:\"NICEST\",5120:\"BYTE\",5121:\"UNSIGNED_BYTE\",5122:\"SHORT\",5123:\"UNSIGNED_SHORT\",5124:\"INT\",5125:\"UNSIGNED_INT\",5126:\"FLOAT\",5386:\"INVERT\",5890:\"TEXTURE\",6401:\"STENCIL_INDEX\",6402:\"DEPTH_COMPONENT\",6406:\"ALPHA\",6407:\"RGB\",6408:\"RGBA\",6409:\"LUMINANCE\",6410:\"LUMINANCE_ALPHA\",7680:\"KEEP\",7681:\"REPLACE\",7682:\"INCR\",7683:\"DECR\",7936:\"VENDOR\",7937:\"RENDERER\",7938:\"VERSION\",9728:\"NEAREST\",9729:\"LINEAR\",9984:\"NEAREST_MIPMAP_NEAREST\",9985:\"LINEAR_MIPMAP_NEAREST\",9986:\"NEAREST_MIPMAP_LINEAR\",9987:\"LINEAR_MIPMAP_LINEAR\",10240:\"TEXTURE_MAG_FILTER\",10241:\"TEXTURE_MIN_FILTER\",10242:\"TEXTURE_WRAP_S\",10243:\"TEXTURE_WRAP_T\",10497:\"REPEAT\",10752:\"POLYGON_OFFSET_UNITS\",16384:\"COLOR_BUFFER_BIT\",32769:\"CONSTANT_COLOR\",32770:\"ONE_MINUS_CONSTANT_COLOR\",32771:\"CONSTANT_ALPHA\",32772:\"ONE_MINUS_CONSTANT_ALPHA\",32773:\"BLEND_COLOR\",32774:\"FUNC_ADD\",32777:\"BLEND_EQUATION_RGB\",32778:\"FUNC_SUBTRACT\",32779:\"FUNC_REVERSE_SUBTRACT\",32819:\"UNSIGNED_SHORT_4_4_4_4\",32820:\"UNSIGNED_SHORT_5_5_5_1\",32823:\"POLYGON_OFFSET_FILL\",32824:\"POLYGON_OFFSET_FACTOR\",32854:\"RGBA4\",32855:\"RGB5_A1\",32873:\"TEXTURE_BINDING_2D\",32926:\"SAMPLE_ALPHA_TO_COVERAGE\",32928:\"SAMPLE_COVERAGE\",32936:\"SAMPLE_BUFFERS\",32937:\"SAMPLES\",32938:\"SAMPLE_COVERAGE_VALUE\",32939:\"SAMPLE_COVERAGE_INVERT\",32968:\"BLEND_DST_RGB\",32969:\"BLEND_SRC_RGB\",32970:\"BLEND_DST_ALPHA\",32971:\"BLEND_SRC_ALPHA\",33071:\"CLAMP_TO_EDGE\",33170:\"GENERATE_MIPMAP_HINT\",33189:\"DEPTH_COMPONENT16\",33306:\"DEPTH_STENCIL_ATTACHMENT\",33635:\"UNSIGNED_SHORT_5_6_5\",33648:\"MIRRORED_REPEAT\",33901:\"ALIASED_POINT_SIZE_RANGE\",33902:\"ALIASED_LINE_WIDTH_RANGE\",33984:\"TEXTURE0\",33985:\"TEXTURE1\",33986:\"TEXTURE2\",33987:\"TEXTURE3\",33988:\"TEXTURE4\",33989:\"TEXTURE5\",33990:\"TEXTURE6\",33991:\"TEXTURE7\",33992:\"TEXTURE8\",33993:\"TEXTURE9\",33994:\"TEXTURE10\",33995:\"TEXTURE11\",33996:\"TEXTURE12\",33997:\"TEXTURE13\",33998:\"TEXTURE14\",33999:\"TEXTURE15\",34e3:\"TEXTURE16\",34001:\"TEXTURE17\",34002:\"TEXTURE18\",34003:\"TEXTURE19\",34004:\"TEXTURE20\",34005:\"TEXTURE21\",34006:\"TEXTURE22\",34007:\"TEXTURE23\",34008:\"TEXTURE24\",34009:\"TEXTURE25\",34010:\"TEXTURE26\",34011:\"TEXTURE27\",34012:\"TEXTURE28\",34013:\"TEXTURE29\",34014:\"TEXTURE30\",34015:\"TEXTURE31\",34016:\"ACTIVE_TEXTURE\",34024:\"MAX_RENDERBUFFER_SIZE\",34041:\"DEPTH_STENCIL\",34055:\"INCR_WRAP\",34056:\"DECR_WRAP\",34067:\"TEXTURE_CUBE_MAP\",34068:\"TEXTURE_BINDING_CUBE_MAP\",34069:\"TEXTURE_CUBE_MAP_POSITIVE_X\",34070:\"TEXTURE_CUBE_MAP_NEGATIVE_X\",34071:\"TEXTURE_CUBE_MAP_POSITIVE_Y\",34072:\"TEXTURE_CUBE_MAP_NEGATIVE_Y\",34073:\"TEXTURE_CUBE_MAP_POSITIVE_Z\",34074:\"TEXTURE_CUBE_MAP_NEGATIVE_Z\",34076:\"MAX_CUBE_MAP_TEXTURE_SIZE\",34338:\"VERTEX_ATTRIB_ARRAY_ENABLED\",34339:\"VERTEX_ATTRIB_ARRAY_SIZE\",34340:\"VERTEX_ATTRIB_ARRAY_STRIDE\",34341:\"VERTEX_ATTRIB_ARRAY_TYPE\",34342:\"CURRENT_VERTEX_ATTRIB\",34373:\"VERTEX_ATTRIB_ARRAY_POINTER\",34466:\"NUM_COMPRESSED_TEXTURE_FORMATS\",34467:\"COMPRESSED_TEXTURE_FORMATS\",34660:\"BUFFER_SIZE\",34661:\"BUFFER_USAGE\",34816:\"STENCIL_BACK_FUNC\",34817:\"STENCIL_BACK_FAIL\",34818:\"STENCIL_BACK_PASS_DEPTH_FAIL\",34819:\"STENCIL_BACK_PASS_DEPTH_PASS\",34877:\"BLEND_EQUATION_ALPHA\",34921:\"MAX_VERTEX_ATTRIBS\",34922:\"VERTEX_ATTRIB_ARRAY_NORMALIZED\",34930:\"MAX_TEXTURE_IMAGE_UNITS\",34962:\"ARRAY_BUFFER\",34963:\"ELEMENT_ARRAY_BUFFER\",34964:\"ARRAY_BUFFER_BINDING\",34965:\"ELEMENT_ARRAY_BUFFER_BINDING\",34975:\"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING\",35040:\"STREAM_DRAW\",35044:\"STATIC_DRAW\",35048:\"DYNAMIC_DRAW\",35632:\"FRAGMENT_SHADER\",35633:\"VERTEX_SHADER\",35660:\"MAX_VERTEX_TEXTURE_IMAGE_UNITS\",35661:\"MAX_COMBINED_TEXTURE_IMAGE_UNITS\",35663:\"SHADER_TYPE\",35664:\"FLOAT_VEC2\",35665:\"FLOAT_VEC3\",35666:\"FLOAT_VEC4\",35667:\"INT_VEC2\",35668:\"INT_VEC3\",35669:\"INT_VEC4\",35670:\"BOOL\",35671:\"BOOL_VEC2\",35672:\"BOOL_VEC3\",35673:\"BOOL_VEC4\",35674:\"FLOAT_MAT2\",35675:\"FLOAT_MAT3\",35676:\"FLOAT_MAT4\",35678:\"SAMPLER_2D\",35680:\"SAMPLER_CUBE\",35712:\"DELETE_STATUS\",35713:\"COMPILE_STATUS\",35714:\"LINK_STATUS\",35715:\"VALIDATE_STATUS\",35716:\"INFO_LOG_LENGTH\",35717:\"ATTACHED_SHADERS\",35718:\"ACTIVE_UNIFORMS\",35719:\"ACTIVE_UNIFORM_MAX_LENGTH\",35720:\"SHADER_SOURCE_LENGTH\",35721:\"ACTIVE_ATTRIBUTES\",35722:\"ACTIVE_ATTRIBUTE_MAX_LENGTH\",35724:\"SHADING_LANGUAGE_VERSION\",35725:\"CURRENT_PROGRAM\",36003:\"STENCIL_BACK_REF\",36004:\"STENCIL_BACK_VALUE_MASK\",36005:\"STENCIL_BACK_WRITEMASK\",36006:\"FRAMEBUFFER_BINDING\",36007:\"RENDERBUFFER_BINDING\",36048:\"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE\",36049:\"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME\",36050:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL\",36051:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE\",36053:\"FRAMEBUFFER_COMPLETE\",36054:\"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\",36055:\"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\",36057:\"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\",36061:\"FRAMEBUFFER_UNSUPPORTED\",36064:\"COLOR_ATTACHMENT0\",36096:\"DEPTH_ATTACHMENT\",36128:\"STENCIL_ATTACHMENT\",36160:\"FRAMEBUFFER\",36161:\"RENDERBUFFER\",36162:\"RENDERBUFFER_WIDTH\",36163:\"RENDERBUFFER_HEIGHT\",36164:\"RENDERBUFFER_INTERNAL_FORMAT\",36168:\"STENCIL_INDEX8\",36176:\"RENDERBUFFER_RED_SIZE\",36177:\"RENDERBUFFER_GREEN_SIZE\",36178:\"RENDERBUFFER_BLUE_SIZE\",36179:\"RENDERBUFFER_ALPHA_SIZE\",36180:\"RENDERBUFFER_DEPTH_SIZE\",36181:\"RENDERBUFFER_STENCIL_SIZE\",36194:\"RGB565\",36336:\"LOW_FLOAT\",36337:\"MEDIUM_FLOAT\",36338:\"HIGH_FLOAT\",36339:\"LOW_INT\",36340:\"MEDIUM_INT\",36341:\"HIGH_INT\",36346:\"SHADER_COMPILER\",36347:\"MAX_VERTEX_UNIFORM_VECTORS\",36348:\"MAX_VARYING_VECTORS\",36349:\"MAX_FRAGMENT_UNIFORM_VECTORS\",37440:\"UNPACK_FLIP_Y_WEBGL\",37441:\"UNPACK_PREMULTIPLY_ALPHA_WEBGL\",37442:\"CONTEXT_LOST_WEBGL\",37443:\"UNPACK_COLORSPACE_CONVERSION_WEBGL\",37444:\"BROWSER_DEFAULT_WEBGL\"}},{}],268:[function(t,e,r){var 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v=0;v<o;++v)t.color[v]=h(r,i,a,g,r.RGBA,r.COLOR_ATTACHMENT0+v);0===o?(t._color_rb=p(r,i,a,r.RGBA4,r.COLOR_ATTACHMENT0),s&&s.drawBuffersWEBGL(l[0])):o>1&&s.drawBuffersWEBGL(l[o]);var y=r.getExtension(\"WEBGL_depth_texture\");y?d?t.depth=h(r,i,a,y.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):m&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):m&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):m?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(v=0;v<t.color.length;++v)t.color[v].dispose(),t.color[v]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),u(r,e),f(x)}u(r,e)}(this)}var m=d.prototype;function g(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,i=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=c(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),u(n,a),f(s)),u(n,a)}}Object.defineProperties(m,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return g(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return g(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,g(this,this._shape[0],t),t},enumerable:!1}}),m.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},m.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":352}],273:[function(t,e,r){var n=t(\"sprintf-js\").sprintf,i=t(\"gl-constants/lookup\"),a=t(\"glsl-shader-name\"),o=t(\"add-line-numbers\");e.exports=function(t,e,r){\"use strict\";var s=a(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===i.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var c=n(\"Error compiling %s shader %s:\\n\",l,s),u=n(\"%s%s\",c,t),f=t.split(\"\\n\"),h={},p=0;p<f.length;p++){var d=f[p];if(\"\"!==d&&\"\\0\"!==d){var m=parseInt(d.split(\":\")[2]);if(isNaN(m))throw new Error(n(\"Could not parse error: %s\",d));h[m]=d}}var g=o(e).split(\"\\n\");for(p=0;p<g.length;p++)if(h[p+3]||h[p+2]||h[p+1]){var v=g[p];if(c+=v+\"\\n\",h[p+1]){var y=h[p+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),c+=n(\"^^^ %s\\n\\n\",y)}}return{long:c.trim(),short:u.trim()}}},{\"add-line-numbers\":72,\"gl-constants/lookup\":268,\"glsl-shader-name\":430,\"sprintf-js\":564}],274:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=t.gl,n=o(r,l.vertex,l.fragment),i=o(r,l.pickVertex,l.pickFragment),a=s(r),u=s(r),f=s(r),h=s(r),p=new c(t,n,i,a,u,f,h);return p.update(e),t.addObject(p),p};var n=t(\"binary-search-bounds\"),i=t(\"iota-array\"),a=t(\"typedarray-pool\"),o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"./lib/shaders\");function c(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var u,f=c.prototype,h=[0,0,1,0,0,1,1,0,1,1,0,1];f.draw=(u=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var i=t.gl,a=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=a[2]-a[0],c=a[3]-a[1];u[0]=2*o/l,u[4]=2*s/c,u[6]=2*(r[0]-a[0])/l-1,u[7]=2*(r[1]-a[1])/c-1,e.bind();var f=e.uniforms;f.viewTransform=u,f.shape=this.shape;var h=e.attributes;this.positionBuffer.bind(),h.position.pointer(),this.weightBuffer.bind(),h.weight.pointer(i.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),h.color.pointer(i.UNSIGNED_BYTE,!0),i.drawArrays(i.TRIANGLES,0,n)}}),f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,c=a[2]-a[0],u=a[3]-a[1],f=l[2]-l[0],h=l[3]-l[1];t[0]=2*c/f,t[4]=2*u/h,t[6]=2*(a[0]-l[0])/f-1,t[7]=2*(a[1]-l[1])/h-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var m=i.attributes;return this.positionBuffer.bind(),m.position.pointer(),this.weightBuffer.bind(),m.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),m.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r<n||r>=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var c,u,f,p,d=t.colorLevels||[0],m=t.colorValues||[0,0,0,1],g=d.length,v=this.bounds;l?(c=v[0]=r[0],u=v[1]=o[0],f=v[2]=r[r.length-1],p=v[3]=o[o.length-1]):(c=v[0]=r[0]+(r[1]-r[0])/2,u=v[1]=o[0]+(o[1]-o[0])/2,f=v[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=v[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var y=1/(f-c),x=1/(p-u),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),M=a.mallocUint8(2*w),A=a.mallocUint32(w),S=0,E=l?b-1:b,L=l?_-1:_,C=0;C<L;++C){var P,I;l?(P=x*(o[C]-u),I=x*(o[C+1]-u)):(P=C<_-1?x*(o[C]-(o[C+1]-o[C])/2-u):x*(o[C]-(o[C]-o[C-1])/2-u),I=C<_-1?x*(o[C]+(o[C+1]-o[C])/2-u):x*(o[C]+(o[C]-o[C-1])/2-u));for(var O=0;O<E;++O){var z,D;l?(z=y*(r[O]-c),D=y*(r[O+1]-c)):(z=O<b-1?y*(r[O]-(r[O+1]-r[O])/2-c):y*(r[O]-(r[O]-r[O-1])/2-c),D=O<b-1?y*(r[O]+(r[O+1]-r[O])/2-c):y*(r[O]+(r[O]-r[O-1])/2-c));for(var R=0;R<h.length;R+=2){var F,B,N,j,U=h[R],V=h[R+1],q=s[l?(C+V)*b+(O+U):C*b+O],H=n.le(d,q);if(H<0)F=m[0],B=m[1],N=m[2],j=m[3];else if(H===g-1)F=m[4*g-4],B=m[4*g-3],N=m[4*g-2],j=m[4*g-1];else{var G=(q-d[H])/(d[H+1]-d[H]),Y=1-G,W=4*H,X=4*(H+1);F=Y*m[W]+G*m[X],B=Y*m[W+1]+G*m[X+1],N=Y*m[W+2]+G*m[X+2],j=Y*m[W+3]+G*m[X+3]}T[4*S]=255*F,T[4*S+1]=255*B,T[4*S+2]=255*N,T[4*S+3]=255*j,k[2*S]=.5*z+.5*D,k[2*S+1]=.5*P+.5*I,M[2*S]=U,M[2*S+1]=V,A[S]=C*b+O,S+=1}}}this.positionBuffer.update(k),this.weightBuffer.update(M),this.colorBuffer.update(T),this.idBuffer.update(A),a.free(k),a.free(T),a.free(M),a.free(A)},f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":275,\"binary-search-bounds\":103,\"gl-buffer\":263,\"gl-shader\":335,\"iota-array\":447,\"typedarray-pool\":613}],275:[function(t,e,r){\"use strict\";var n=t(\"glslify\");e.exports={fragment:n([\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\"]),vertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 color;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  fragColor = color;\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"]),pickFragment:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nuniform vec2 shape;\\nuniform vec4 pickOffset;\\n\\nvoid main() {\\n  vec2 d = step(.5, vWeight);\\n  vec4 id = fragId + pickOffset;\\n  id.x += d.x + d.y*shape.x;\\n\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  gl_FragColor = id/255.;\\n}\\n\"]),pickVertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nvoid main() {\\n  vWeight = weight;\\n\\n  fragId = pickId;\\n\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"])}},{glslify:438}],276:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  vec4 startPoint = project(position);\\n  vec4 endPoint   = project(nextPosition);\\n\\n  vec2 A = startPoint.xy / startPoint.w;\\n  vec2 B =   endPoint.xy /   endPoint.w;\\n\\n  float clipAngle = atan(\\n    (B.y - A.y) * screenShape.y,\\n    (B.x - A.x) * screenShape.x\\n  );\\n\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\\n    sin(clipAngle),\\n    -cos(clipAngle)\\n  ) / screenShape;\\n\\n  gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n  float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  float e = floor(log2(av));\\n  float m = av * pow(2.0, -e) - 1.0;\\n\\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n\\n  //Unpack exponent\\n  float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0;\\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n  gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return i(t,a,o,null,l)},r.createPickShader=function(t){return i(t,a,s,null,l)}},{\"gl-shader\":335,glslify:278}],277:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),u=c(new Array(1024),[256,1,4]),p=0;p<1024;++p)u.data[p]=255;var d=a(e,u);d.wrap=e.REPEAT;var m=new v(e,r,o,s,l,d);return m.update(t),m};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"gl-texture2d\"),o=new Uint8Array(4),s=new Float32Array(o.buffer);var l=t(\"binary-search-bounds\"),c=t(\"ndarray\"),u=t(\"./lib/shaders\"),f=u.createShader,h=u.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function m(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function g(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function v(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var y=v.prototype;y.isTransparent=function(){return this.hasAlpha},y.isOpaque=function(){return!this.hasAlpha},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:m(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:m(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var i=[],a=[],o=[],s=0,u=0,f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],h=t.position||t.positions;if(h){var p=t.color||t.colors||[0,0,0,1],m=t.lineWidth||1,g=!1;t:for(e=1;e<h.length;++e){var v,y,x,b=h[e-1],_=h[e];for(a.push(s),o.push(b.slice()),r=0;r<3;++r){if(isNaN(b[r])||isNaN(_[r])||!isFinite(b[r])||!isFinite(_[r])){if(!n&&i.length>0){for(var w=0;w<24;++w)i.push(i[i.length-12]);u+=2,g=!0}continue t}f[0][r]=Math.min(f[0][r],b[r],_[r]),f[1][r]=Math.max(f[1][r],b[r],_[r])}Array.isArray(p[0])?(v=p.length>e-1?p[e-1]:p.length>0?p[p.length-1]:[0,0,0,1],y=p.length>e?p[e]:p.length>0?p[p.length-1]:[0,0,0,1]):v=y=p,3===v.length&&(v=[v[0],v[1],v[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]),!this.hasAlpha&&v[3]<1&&(this.hasAlpha=!0),x=Array.isArray(m)?m.length>e-1?m[e-1]:m.length>0?m[m.length-1]:[0,0,0,1]:m;var T=s;if(s+=d(b,_),g){for(r=0;r<2;++r)i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,v[0],v[1],v[2],v[3]);u+=2,g=!1}i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,v[0],v[1],v[2],v[3],b[0],b[1],b[2],_[0],_[1],_[2],T,-x,v[0],v[1],v[2],v[3],_[0],_[1],_[2],b[0],b[1],b[2],s,-x,y[0],y[1],y[2],y[3],_[0],_[1],_[2],b[0],b[1],b[2],s,x,y[0],y[1],y[2],y[3]),u+=4}}if(this.buffer.update(i),a.push(s),o.push(h[h.length-1].slice()),this.bounds=f,this.vertexCount=u,this.points=o,this.arcLength=a,\"dashes\"in t){var k=t.dashes.slice();for(k.unshift(0),e=1;e<k.length;++e)k[e]=k[e-1]+k[e];var M=c(new Array(1024),[256,1,4]);for(e=0;e<256;++e){for(r=0;r<4;++r)M.set(e,0,r,0);1&l.le(k,k[k.length-1]*e/255)?M.set(e,0,0,0):M.set(e,0,0,255)}this.texture.setPixels(M)}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=function(t,e,r,n){return o[0]=n,o[1]=r,o[2]=e,o[3]=t,s[0]}(t.value[0],t.value[1],t.value[2],0),r=l.le(this.arcLength,e);if(r<0)return null;if(r===this.arcLength.length-1)return new g(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],a=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),c=1-a,u=[0,0,0],f=0;f<3;++f)u[f]=c*n[f]+a*i[f];var h=Math.min(a<.5?r:r+1,this.points.length-1);return new g(e,u,h,this.points[h])}},{\"./lib/shaders\":276,\"binary-search-bounds\":103,\"gl-buffer\":263,\"gl-texture2d\":352,\"gl-vao\":357,ndarray:479}],278:[function(t,e,r){arguments[4][261][0].apply(r,arguments)},{dup:261}],279:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],f=e[9],h=e[10],p=e[11],d=e[12],m=e[13],g=e[14],v=e[15];return t[0]=s*(h*v-p*g)-f*(l*v-c*g)+m*(l*p-c*h),t[1]=-(n*(h*v-p*g)-f*(i*v-a*g)+m*(i*p-a*h)),t[2]=n*(l*v-c*g)-s*(i*v-a*g)+m*(i*c-a*l),t[3]=-(n*(l*p-c*h)-s*(i*p-a*h)+f*(i*c-a*l)),t[4]=-(o*(h*v-p*g)-u*(l*v-c*g)+d*(l*p-c*h)),t[5]=r*(h*v-p*g)-u*(i*v-a*g)+d*(i*p-a*h),t[6]=-(r*(l*v-c*g)-o*(i*v-a*g)+d*(i*c-a*l)),t[7]=r*(l*p-c*h)-o*(i*p-a*h)+u*(i*c-a*l),t[8]=o*(f*v-p*m)-u*(s*v-c*m)+d*(s*p-c*f),t[9]=-(r*(f*v-p*m)-u*(n*v-a*m)+d*(n*p-a*f)),t[10]=r*(s*v-c*m)-o*(n*v-a*m)+d*(n*c-a*s),t[11]=-(r*(s*p-c*f)-o*(n*p-a*f)+u*(n*c-a*s)),t[12]=-(o*(f*g-h*m)-u*(s*g-l*m)+d*(s*h-l*f)),t[13]=r*(f*g-h*m)-u*(n*g-i*m)+d*(n*h-i*f),t[14]=-(r*(s*g-l*m)-o*(n*g-i*m)+d*(n*l-i*s)),t[15]=r*(s*h-l*f)-o*(n*h-i*f)+u*(n*l-i*s),t}},{}],280:[function(t,e,r){e.exports=function(t){var e=new Float32Array(16);return 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t[0]=1-(p+m),t[1]=f+y,t[2]=h-v,t[3]=0,t[4]=f-y,t[5]=1-(u+m),t[6]=d+g,t[7]=0,t[8]=h+v,t[9]=d-g,t[10]=1-(u+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}},{}],287:[function(t,e,r){e.exports=function(t,e){return t[0]=e[0],t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=e[1],t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=e[2],t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],288:[function(t,e,r){e.exports=function(t,e){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=e[0],t[13]=e[1],t[14]=e[2],t[15]=1,t}},{}],289:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=n,t[6]=r,t[7]=0,t[8]=0,t[9]=-r,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],290:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=0,t[2]=-r,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=r,t[9]=0,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],291:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=r,t[2]=0,t[3]=0,t[4]=-r,t[5]=n,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],292:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(r-e),l=1/(i-n),c=1/(a-o);return t[0]=2*a*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=2*a*l,t[6]=0,t[7]=0,t[8]=(r+e)*s,t[9]=(i+n)*l,t[10]=(o+a)*c,t[11]=-1,t[12]=0,t[13]=0,t[14]=o*a*2*c,t[15]=0,t}},{}],293:[function(t,e,r){e.exports=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],294:[function(t,e,r){e.exports={create:t(\"./create\"),clone:t(\"./clone\"),copy:t(\"./copy\"),identity:t(\"./identity\"),transpose:t(\"./transpose\"),invert:t(\"./invert\"),adjoint:t(\"./adjoint\"),determinant:t(\"./determinant\"),multiply:t(\"./multiply\"),translate:t(\"./translate\"),scale:t(\"./scale\"),rotate:t(\"./rotate\"),rotateX:t(\"./rotateX\"),rotateY:t(\"./rotateY\"),rotateZ:t(\"./rotateZ\"),fromRotation:t(\"./fromRotation\"),fromRotationTranslation:t(\"./fromRotationTranslation\"),fromScaling:t(\"./fromScaling\"),fromTranslation:t(\"./fromTranslation\"),fromXRotation:t(\"./fromXRotation\"),fromYRotation:t(\"./fromYRotation\"),fromZRotation:t(\"./fromZRotation\"),fromQuat:t(\"./fromQuat\"),frustum:t(\"./frustum\"),perspective:t(\"./perspective\"),perspectiveFromFieldOfView:t(\"./perspectiveFromFieldOfView\"),ortho:t(\"./ortho\"),lookAt:t(\"./lookAt\"),str:t(\"./str\")}},{\"./adjoint\":279,\"./clone\":280,\"./copy\":281,\"./create\":282,\"./determinant\":283,\"./fromQuat\":284,\"./fromRotation\":285,\"./fromRotationTranslation\":286,\"./fromScaling\":287,\"./fromTranslation\":288,\"./fromXRotation\":289,\"./fromYRotation\":290,\"./fromZRotation\":291,\"./frustum\":292,\"./identity\":293,\"./invert\":295,\"./lookAt\":296,\"./multiply\":297,\"./ortho\":298,\"./perspective\":299,\"./perspectiveFromFieldOfView\":300,\"./rotate\":301,\"./rotateX\":302,\"./rotateY\":303,\"./rotateZ\":304,\"./scale\":305,\"./str\":306,\"./translate\":307,\"./transpose\":308}],295:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],f=e[9],h=e[10],p=e[11],d=e[12],m=e[13],g=e[14],v=e[15],y=r*s-n*o,x=r*l-i*o,b=r*c-a*o,_=n*l-i*s,w=n*c-a*s,T=i*c-a*l,k=u*m-f*d,M=u*g-h*d,A=u*v-p*d,S=f*g-h*m,E=f*v-p*m,L=h*v-p*g,C=y*L-x*E+b*S+_*A-w*M+T*k;if(!C)return null;return C=1/C,t[0]=(s*L-l*E+c*S)*C,t[1]=(i*E-n*L-a*S)*C,t[2]=(m*T-g*w+v*_)*C,t[3]=(h*w-f*T-p*_)*C,t[4]=(l*A-o*L-c*M)*C,t[5]=(r*L-i*A+a*M)*C,t[6]=(g*b-d*T-v*x)*C,t[7]=(u*T-h*b+p*x)*C,t[8]=(o*E-s*A+c*k)*C,t[9]=(n*A-r*E-a*k)*C,t[10]=(d*w-m*b+v*y)*C,t[11]=(f*b-u*w-p*y)*C,t[12]=(s*M-o*S-l*k)*C,t[13]=(r*S-n*M+i*k)*C,t[14]=(m*x-d*_-g*y)*C,t[15]=(u*_-f*x+h*y)*C,t}},{}],296:[function(t,e,r){var n=t(\"./identity\");e.exports=function(t,e,r,i){var a,o,s,l,c,u,f,h,p,d,m=e[0],g=e[1],v=e[2],y=i[0],x=i[1],b=i[2],_=r[0],w=r[1],T=r[2];if(Math.abs(m-_)<1e-6&&Math.abs(g-w)<1e-6&&Math.abs(v-T)<1e-6)return n(t);f=m-_,h=g-w,p=v-T,d=1/Math.sqrt(f*f+h*h+p*p),a=x*(p*=d)-b*(h*=d),o=b*(f*=d)-y*p,s=y*h-x*f,(d=Math.sqrt(a*a+o*o+s*s))?(a*=d=1/d,o*=d,s*=d):(a=0,o=0,s=0);l=h*s-p*o,c=p*a-f*s,u=f*o-h*a,(d=Math.sqrt(l*l+c*c+u*u))?(l*=d=1/d,c*=d,u*=d):(l=0,c=0,u=0);return t[0]=a,t[1]=l,t[2]=f,t[3]=0,t[4]=o,t[5]=c,t[6]=h,t[7]=0,t[8]=s,t[9]=u,t[10]=p,t[11]=0,t[12]=-(a*m+o*g+s*v),t[13]=-(l*m+c*g+u*v),t[14]=-(f*m+h*g+p*v),t[15]=1,t}},{\"./identity\":293}],297:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],m=e[12],g=e[13],v=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*f+w*m,t[1]=x*i+b*l+_*h+w*g,t[2]=x*a+b*c+_*p+w*v,t[3]=x*o+b*u+_*d+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*f+w*m,t[5]=x*i+b*l+_*h+w*g,t[6]=x*a+b*c+_*p+w*v,t[7]=x*o+b*u+_*d+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*f+w*m,t[9]=x*i+b*l+_*h+w*g,t[10]=x*a+b*c+_*p+w*v,t[11]=x*o+b*u+_*d+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*f+w*m,t[13]=x*i+b*l+_*h+w*g,t[14]=x*a+b*c+_*p+w*v,t[15]=x*o+b*u+_*d+w*y,t}},{}],298:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t}},{}],299:[function(t,e,r){e.exports=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}},{}],300:[function(t,e,r){e.exports=function(t,e,r,n){var i=Math.tan(e.upDegrees*Math.PI/180),a=Math.tan(e.downDegrees*Math.PI/180),o=Math.tan(e.leftDegrees*Math.PI/180),s=Math.tan(e.rightDegrees*Math.PI/180),l=2/(o+s),c=2/(i+a);return t[0]=l,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=c,t[6]=0,t[7]=0,t[8]=-(o-s)*l*.5,t[9]=(i-a)*c*.5,t[10]=n/(r-n),t[11]=-1,t[12]=0,t[13]=0,t[14]=n*r/(r-n),t[15]=0,t}},{}],301:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,w,T,k,M,A,S,E=n[0],L=n[1],C=n[2],P=Math.sqrt(E*E+L*L+C*C);if(Math.abs(P)<1e-6)return null;E*=P=1/P,L*=P,C*=P,i=Math.sin(r),a=Math.cos(r),o=1-a,s=e[0],l=e[1],c=e[2],u=e[3],f=e[4],h=e[5],p=e[6],d=e[7],m=e[8],g=e[9],v=e[10],y=e[11],x=E*E*o+a,b=L*E*o+C*i,_=C*E*o-L*i,w=E*L*o-C*i,T=L*L*o+a,k=C*L*o+E*i,M=E*C*o+L*i,A=L*C*o-E*i,S=C*C*o+a,t[0]=s*x+f*b+m*_,t[1]=l*x+h*b+g*_,t[2]=c*x+p*b+v*_,t[3]=u*x+d*b+y*_,t[4]=s*w+f*T+m*k,t[5]=l*w+h*T+g*k,t[6]=c*w+p*T+v*k,t[7]=u*w+d*T+y*k,t[8]=s*M+f*A+m*S,t[9]=l*M+h*A+g*S,t[10]=c*M+p*A+v*S,t[11]=u*M+d*A+y*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t}},{}],302:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[4]=a*i+c*n,t[5]=o*i+u*n,t[6]=s*i+f*n,t[7]=l*i+h*n,t[8]=c*i-a*n,t[9]=u*i-o*n,t[10]=f*i-s*n,t[11]=h*i-l*n,t}},{}],303:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i-c*n,t[1]=o*i-u*n,t[2]=s*i-f*n,t[3]=l*i-h*n,t[8]=a*n+c*i,t[9]=o*n+u*i,t[10]=s*n+f*i,t[11]=l*n+h*i,t}},{}],304:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[4],u=e[5],f=e[6],h=e[7];e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i+c*n,t[1]=o*i+u*n,t[2]=s*i+f*n,t[3]=l*i+h*n,t[4]=c*i-a*n,t[5]=u*i-o*n,t[6]=f*i-s*n,t[7]=h*i-l*n,t}},{}],305:[function(t,e,r){e.exports=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},{}],306:[function(t,e,r){e.exports=function(t){return\"mat4(\"+t[0]+\", \"+t[1]+\", \"+t[2]+\", \"+t[3]+\", \"+t[4]+\", \"+t[5]+\", \"+t[6]+\", \"+t[7]+\", \"+t[8]+\", \"+t[9]+\", \"+t[10]+\", \"+t[11]+\", \"+t[12]+\", \"+t[13]+\", \"+t[14]+\", \"+t[15]+\")\"}},{}],307:[function(t,e,r){e.exports=function(t,e,r){var n,i,a,o,s,l,c,u,f,h,p,d,m=r[0],g=r[1],v=r[2];e===t?(t[12]=e[0]*m+e[4]*g+e[8]*v+e[12],t[13]=e[1]*m+e[5]*g+e[9]*v+e[13],t[14]=e[2]*m+e[6]*g+e[10]*v+e[14],t[15]=e[3]*m+e[7]*g+e[11]*v+e[15]):(n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],t[0]=n,t[1]=i,t[2]=a,t[3]=o,t[4]=s,t[5]=l,t[6]=c,t[7]=u,t[8]=f,t[9]=h,t[10]=p,t[11]=d,t[12]=n*m+s*g+f*v+e[12],t[13]=i*m+l*g+h*v+e[13],t[14]=a*m+c*g+p*v+e[14],t[15]=o*m+u*g+d*v+e[15]);return t}},{}],308:[function(t,e,r){e.exports=function(t,e){if(t===e){var r=e[1],n=e[2],i=e[3],a=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=a,t[11]=e[14],t[12]=i,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},{}],309:[function(t,e,r){\"use strict\";var n=t(\"barycentric\"),i=t(\"polytope-closest-point/lib/closest_point_2d.js\");function a(t,e){for(var r=[0,0,0,0],n=0;n<4;++n)for(var i=0;i<4;++i)r[i]+=t[4*n+i]*e[n];return r}function o(t,e,r,n,i){for(var o=a(n,a(r,a(e,[t[0],t[1],t[2],1]))),s=0;s<3;++s)o[s]/=o[3];return[.5*i[0]*(1+o[0]),.5*i[1]*(1-o[1])]}function s(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var i=t[n],a=e[n],o=0;o<3;++o)r[o]+=a*i[o];return r}e.exports=function(t,e,r,a,l,c){if(1===t.length)return[0,t[0].slice()];for(var u=new Array(t.length),f=0;f<t.length;++f)u[f]=o(t[f],r,a,l,c);var h=0,p=1/0;for(f=0;f<u.length;++f){for(var d=0,m=0;m<2;++m)d+=Math.pow(u[f][m]-e[m],2);d<p&&(p=d,h=f)}var g=function(t,e){if(2===t.length){for(var r=0,a=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),a+=Math.pow(e[o]-t[1][o],2);return r=Math.sqrt(r),a=Math.sqrt(a),r+a<1e-6?[1,0]:[a/(r+a),r/(a+r)]}if(3===t.length){var s=[0,0];return i(t[0],t[1],t[2],e,s),n(t,s)}return[]}(u,e),v=0;for(f=0;f<3;++f){if(g[f]<-.001||g[f]>1.0001)return null;v+=g[f]}if(Math.abs(v-1)>.001)return null;return[h,s(t,g),g]}},{barycentric:85,\"polytope-closest-point/lib/closest_point_2d.js\":508}],310:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection\\n           , inverseModel;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  gl_Position      = project(position);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * vec4(position , 1.0);\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal  = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  f_color          = color;\\n  f_data           = position;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (f_color.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], f_data)\\n  ) discard;\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:l,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},{glslify:438}],311:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"normals\"),l=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/invert\"),u=t(\"ndarray\"),f=t(\"colormap\"),h=t(\"simplicial-complex-contour\"),p=t(\"typedarray-pool\"),d=t(\"./lib/shaders\"),m=t(\"./lib/closest-point\"),g=d.meshShader,v=d.wireShader,y=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,T,k,M,A,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=u,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=c,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=g,this.edgeUVs=v,this.edgeIds=m,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=M,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=A,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function M(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function A(t){var e=n(t,g.vertex,g.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function S(t){var e=n(t,v.vertex,v.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function E(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function C(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function P(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var c=r[l],u=0;u<2;++u){var f=c[0];2===c.length&&(f=c[u]);for(var d=n[f][0],m=n[f][1],g=i[f],v=1-g,y=this.positions[d],x=this.positions[m],b=0;b<3;++b)o[s++]=g*y[b]+v*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},k.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=f({colormap:t,nshades:256,format:\"rgba\"}),n=new Uint8Array(1024),i=0;i<256;++i){for(var a=r[i],o=0;o<3;++o)n[4*i+o]=a[o];n[4*i+3]=e?255*M(i/255,e):255*a[3]}return u(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var i=[],a=[],l=[],c=[],h=[],p=[],d=[],m=[],g=[],v=[],y=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,T=t.cellNormals,k=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,A=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=s.faceNormals(r,n,A)),T||w||(w=s.vertexNormals(r,n,k));var S=t.vertexColors,E=t.cellColors,L=t.meshColor||[1,1,1,1],C=t.vertexUVs,P=t.vertexIntensity,I=t.cellUVs,O=t.cellIntensity,z=1/0,D=-1/0;if(!C&&!I)if(P)if(t.vertexIntensityBounds)z=+t.vertexIntensityBounds[0],D=+t.vertexIntensityBounds[1];else for(var R=0;R<P.length;++R){var F=P[R];z=Math.min(z,F),D=Math.max(D,F)}else if(O)if(t.cellIntensityBounds)z=+t.cellIntensityBounds[0],D=+t.cellIntensityBounds[1];else for(R=0;R<O.length;++R){F=O[R];z=Math.min(z,F),D=Math.max(D,F)}else for(R=0;R<n.length;++R){F=n[R][2];z=Math.min(z,F),D=Math.max(D,F)}this.intensity=P||(O||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n)),this.pickVertex=!(O||E);var B=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(R=0;R<n.length;++R)for(var j=n[R],U=0;U<3;++U)!isNaN(j[U])&&isFinite(j[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],j[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],j[U]));var V=0,q=0,H=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[W=G[0]],U=0;U<3;++U)if(isNaN(j[U])||!isFinite(j[U]))continue t;v.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*M((P[W]-z)/(D-z),this.opacityscale)):3===X.length?y.push(X[0],X[1],X[2],this.opacity):(y.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],x.push(Z[0],Z[1]),B?b.push(B[W]):b.push(N),_.push(R),H+=1;break;case 2:for(U=0;U<2;++U){j=n[W=G[U]];for(var Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t}for(U=0;U<2;++U){j=n[W=G[U]];p.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*M((P[W]-z)/(D-z),this.opacityscale)):3===X.length?d.push(X[0],X[1],X[2],this.opacity):(d.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],m.push(Z[0],Z[1]),g.push(R)}q+=1;break;case 3:for(U=0;U<3;++U)for(j=n[W=G[U]],Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t;for(U=0;U<3;++U){var W,X,Z,J;j=n[W=G[2-U]];i.push(j[0],j[1],j[2]),(X=S?S[W]:E?E[R]:L)?this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*M((P[W]-z)/(D-z),this.opacityscale)):3===X.length?a.push(X[0],X[1],X[2],this.opacity):(a.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)):a.push(.5,.5,.5,1),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],c.push(Z[0],Z[1]),J=w?w[W]:T[R],l.push(J[0],J[1],J[2]),h.push(R)}V+=1}}this.pointCount=H,this.edgeCount=q,this.triangleCount=V,this.pointPositions.update(v),this.pointColors.update(y),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(m),this.edgeIds.update(new Uint32Array(g)),this.trianglePositions.update(i),this.triangleColors.update(a),this.triangleUVs.update(c),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(h))}},k.drawTransparent=k.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:w.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var f,h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/h}this.triangleCount>0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind());this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind());this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind());this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};((s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0)&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],c=this.positions[r[1]],u=this.positions[r[2]],f=[(l[0]+c[0]+u[0])/3,(l[1]+c[1]+u[1])/3,(l[2]+c[2]+u[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:f}}var h=m(i,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!h)return null;var p=h[2],d=0;for(a=0;a<r.length;++a)d+=p[a]*this.intensity[r[a]];return{position:h[1],index:r[h[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[h[0]]]}},k.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=function(t,e){1===arguments.length&&(t=(e=t).gl);var r=t.getExtension(\"OES_standard_derivatives\")||t.getExtension(\"MOZ_OES_standard_derivatives\")||t.getExtension(\"WEBKIT_OES_standard_derivatives\");if(!r)throw new Error(\"derivatives not supported\");var n=A(t),s=S(t),l=E(t),c=L(t),f=C(t),h=P(t),p=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=i(t),m=i(t),g=i(t),v=i(t),y=i(t),x=a(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:m,type:t.FLOAT,size:4},{buffer:g,type:t.FLOAT,size:2},{buffer:v,type:t.FLOAT,size:3}]),b=i(t),_=i(t),w=i(t),k=i(t),M=a(t,[{buffer:b,type:t.FLOAT,size:3},{buffer:k,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:_,type:t.FLOAT,size:4},{buffer:w,type:t.FLOAT,size:2}]),I=i(t),O=i(t),z=i(t),D=i(t),R=i(t),F=a(t,[{buffer:I,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:O,type:t.FLOAT,size:4},{buffer:z,type:t.FLOAT,size:2},{buffer:D,type:t.FLOAT,size:1}]),B=i(t),N=a(t,[{buffer:B,type:t.FLOAT,size:3}]),j=new T(t,p,n,s,l,c,f,h,d,y,m,g,v,x,b,k,_,w,M,I,R,O,z,D,F,B,N);return j.update(e),j}},{\"./lib/closest-point\":309,\"./lib/shaders\":310,colormap:137,\"gl-buffer\":263,\"gl-mat4/invert\":295,\"gl-mat4/multiply\":297,\"gl-shader\":335,\"gl-texture2d\":352,\"gl-vao\":357,ndarray:479,normals:482,\"simplicial-complex-contour\":553,\"typedarray-pool\":613}],312:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[0,0,0,1,1,0,1,1]),s=i(e,a.boxVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,i){var a=this.plot,o=this.shader,c=a.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=i,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":315,\"gl-buffer\":263,\"gl-shader\":335}],313:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,o.gridVert,o.gridFrag),l=i(e,o.tickVert,o.gridFrag);return new s(t,r,a,l)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"binary-search-bounds\"),o=t(\"./shaders\");function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var c,u,f,h,p,d=s.prototype;d.draw=(c=[0,0],u=[0,0],f=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,i=t.gl,a=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,h=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,m=0;m<2;++m){var g=a[m],v=a[m+2]-g,y=.5*(o[m+2]+o[m]),x=o[m+2]-o[m];u[m]=2*v/x,c[m]=2*(g-y)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=c,r.uniforms.dataScale=u;var b=0;for(m=0;m<2;++m){f[0]=f[1]=0,f[m]=1,r.uniforms.dataAxis=f,r.uniforms.lineWidth=l[m]/(s[m+2]-s[m])*d,r.uniforms.color=h[m];var _=6*n[m].length;p[m]&&_&&i.drawArrays(i.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],i=[0,0],o=[0,0];return function(){for(var s=this.plot,c=this.vbo,u=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,m=s.viewBox,g=s.pixelRatio,v=s.screenBox,y=v[2]-v[0],x=v[3]-v[1],b=m[2]-m[0],_=m[3]-m[1],w=0;w<2;++w){var T=p[w],k=p[w+2]-T,M=.5*(d[w+2]+d[w]),A=d[w+2]-d[w];e[w]=2*k/A,t[w]=2*(T-M)/A}e[0]*=b/y,t[0]*=b/y,e[1]*=_/x,t[1]*=_/x,u.bind(),c.bind(),u.attributes.dataCoord.pointer();var S=u.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,L=s.tickMarkWidth,C=s.tickMarkColor,P=6*f[0].length,I=Math.min(a.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),l),f[0].length),O=Math.min(a.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),l),f[0].length),z=0+6*I,D=6*Math.max(0,O-I),R=Math.min(a.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),l),f[1].length),F=Math.min(a.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),l),f[1].length),B=P+6*R,N=6*Math.max(0,F-R);i[0]=2*(m[0]-E[1])/y-1,i[1]=(m[3]+m[1])/x-1,o[0]=E[1]*g/y,o[1]=L[1]*g/x,N&&(S.color=C[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(m[2]+m[0])/y-1,i[1]=2*(m[1]-E[0])/x-1,o[0]=L[0]*g/y,o[1]=E[0]*g/x,D&&(S.color=C[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,z,D)),i[0]=2*(m[2]+E[3])/y-1,i[1]=(m[3]+m[1])/x-1,o[0]=E[3]*g/y,o[1]=L[3]*g/x,N&&(S.color=C[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(m[2]+m[0])/y-1,i[1]=2*(m[3]+E[2])/x-1,o[0]=L[2]*g/y,o[1]=E[2]*g/x,D&&(S.color=C[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,z,D))}}(),d.update=(h=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),i=(this.plot.zeroLineEnable,0),a=[[],[]],o=0;o<2;++o)for(var s=a[o],l=e[o],c=r[o],u=r[o+2],f=0;f<l.length;++f){var d=(l[f].x-c)/(u-c);s.push(d);for(var m=0;m<6;++m)n[i++]=d,n[i++]=h[m],n[i++]=p[m]}this.ticks=a,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":315,\"binary-search-bounds\":103,\"gl-buffer\":263,\"gl-shader\":335}],314:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[-1,-1,-1,1,1,-1,1,1]),s=i(e,a.lineVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,i,a){var o=this.plot,c=this.shader,u=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,c.uniforms.start=s,c.uniforms.end=l,c.uniforms.width=i*o.pixelRatio,c.uniforms.color=a,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":315,\"gl-buffer\":263,\"gl-shader\":335}],315:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\"]);e.exports={lineVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\"]),lineFrag:i,textVert:n([\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\"]),textFrag:i,gridVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\"]),gridFrag:i,boxVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\"]),tickVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"])}},{glslify:317}],316:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,s.textVert,s.textFrag);return new l(t,r,a)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"text-cache\"),o=t(\"binary-search-bounds\"),s=t(\"./shaders\");function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var c,u,f,h,p,d,m=l.prototype;m.drawTicks=(c=[0,0],u=[0,0],f=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],i=this.tickOffset[t],a=e.gl,s=e.viewBox,l=e.dataBox,h=e.screenBox,p=e.pixelRatio,d=e.tickEnable,m=e.tickPad,g=e.tickColor,v=e.tickAngle,y=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],T=this.labelCount[t],k=o.lt(n,l[t]),M=o.le(n,l[t+2]);c[0]=c[1]=0,c[t]=1,u[t]=(s[2+t]+s[t])/(h[2+t]-h[t])-1;var A=2/h[2+(1^t)]-h[1^t];u[1^t]=A*s[1^t]-1,d[t]&&(u[1^t]-=A*p*m[t],k<M&&i[M]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=g[t],r.uniforms.angle=v[t],a.drawArrays(a.TRIANGLES,i[k],i[M]-i[k]))),y[t]&&T&&(u[1^t]-=A*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),u[1^t]=A*s[2+(1^t)]-1,d[t+2]&&(u[1^t]+=A*p*m[t+2],k<M&&i[M]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=g[t+2],r.uniforms.angle=v[t+2],a.drawArrays(a.TRIANGLES,i[k],i[M]-i[k]))),y[t+2]&&T&&(u[1^t]+=A*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),m.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,c=r.pixelRatio;if(this.titleCount){for(var u=0;u<2;++u)e[u]=2*(o[u]*c-a[u])/(a[2+u]-a[u])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),m.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,c=.5*(n[o+2]+n[o]),u=n[o+2]-n[o],f=a[o],m=a[o+2]-f,g=i[o],v=i[o+2]-g;p[o]=2*l/u*m/v,h[o]=2*(s-c)/u*m/v}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),m.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,c=t.bounds;for(o=0;o<2;++o){var u=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e<h.length;++e){var p=h[e],d=p.x,m=p.text,g=p.font||\"sans-serif\";i=p.fontSize||12;for(var v=1/(c[o+2]-c[o]),y=c[o],x=m.split(\"\\n\"),b=0;b<x.length;b++)for(n=a(g,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*i,-n[r+1]*i-b*i*1.2,(d-y)*v);u.push(Math.floor(s.length/3)),f.push(d)}this.tickOffset[o]=u,this.tickX[o]=f}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=a(t.labelFont[o],t.labels[o],{textAlign:\"center\"}).data,i=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=a(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},m.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":315,\"binary-search-bounds\":103,\"gl-buffer\":263,\"gl-shader\":335,\"text-cache\":592}],317:[function(t,e,r){arguments[4][261][0].apply(r,arguments)},{dup:261}],318:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[e.drawingBufferWidth,e.drawingBufferHeight]),c=new l(e,r);return c.grid=i(c),c.text=a(c),c.line=o(c),c.box=s(c),c.update(t),c};var n=t(\"gl-select-static\"),i=t(\"./lib/grid\"),a=t(\"./lib/text\"),o=t(\"./lib/line\"),s=t(\"./lib/box\");function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var c=l.prototype;function u(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function f(t,e){return t.x-e.x}c.setDirty=function(){this.dirty=this.pickDirty=!0},c.setOverlayDirty=function(){this.dirty=!0},c.nextDepthValue=function(){return this._depthCounter++/65536},c.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var c=this.borderColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var u=this.backgroundColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;d<2;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var m=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(m,e[1],m,e[3],p[d],h[d]):o.drawLine(e[0],m,e[2],m,p[d],h[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var g=this.borderLineEnable,v=this.borderLineWidth,y=this.borderLineColor;for(g[1]&&o.drawLine(r[0],r[1]-.5*v[1]*i,r[0],r[3]+.5*v[3]*i,v[1],y[1]),g[0]&&o.drawLine(r[0]-.5*v[0]*i,r[1],r[2]+.5*v[2]*i,r[1],v[0],y[0]),g[3]&&o.drawLine(r[2],r[1]-.5*v[1]*i,r[2],r[3]+.5*v[3]*i,v[3],y[3]),g[2]&&o.drawLine(r[0]-.5*v[0]*i,r[3],r[2]+.5*v[2]*i,r[3],v[2],y[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},c.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},c.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),c=this.objects,u=0;u<c.length;++u){var f=c[u].pick(a,o,l);if(f)return f}return null}},c.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},c.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},c.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},c.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,i=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/i,10,10/i]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=u(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=u(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=u(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t)||!!t.titleEnable,this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=u(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=u(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=u(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var a=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=a[s].slice(0);0!==l.length&&(l.sort(f),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:a}),this.text.update({bounds:o,ticks:a,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},c.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},c.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},c.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},c.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},c.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":312,\"./lib/grid\":313,\"./lib/line\":314,\"./lib/text\":316,\"gl-select-static\":334}],319:[function(t,e,r){\"use strict\";e.exports=function(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]);\"zoomMin\"in e&&(r[0]=e.zoomMin);\"zoomMax\"in e&&(r[1]=e.zoomMax);var c=i({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),u=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],f=0,h=t.clientWidth,p=t.clientHeight,d={keyBindingMode:\"rotate\",enableWheel:!0,view:c,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:c.modes,_ortho:e._ortho||e.projection&&\"orthographic\"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,i=e-2*r;c.idle(e-r),c.recalcMatrix(i),c.flush(e-(100+2*r));for(var a=!0,o=c.computedMatrix,s=0;s<16;++s)a=a&&u[s]===o[s],u[s]=o[s];var l=t.clientWidth===h&&t.clientHeight===p;return h=t.clientWidth,p=t.clientHeight,a?!l:(f=Math.exp(c.computedRadius[0]),!0)},lookAt:function(t,e,r){c.lookAt(c.lastT(),t,e,r)},rotate:function(t,e,r){c.rotate(c.lastT(),t,e,r)},pan:function(t,e,r){c.pan(c.lastT(),t,e,r)},translate:function(t,e,r){c.translate(c.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return c.computedMatrix},set:function(t){return c.setMatrix(c.lastT(),t),c.computedMatrix},enumerable:!0},mode:{get:function(){return c.getMode()},set:function(t){var e=c.computedUp.slice(),r=c.computedEye.slice(),i=c.computedCenter.slice();if(c.setMode(t),\"turntable\"===t){var a=n();c._active.lookAt(a,r,i,e),c._active.lookAt(a+500,r,i,[0,0,1]),c._active.flush(a)}return c.getMode()},enumerable:!0},center:{get:function(){return c.computedCenter},set:function(t){return c.lookAt(c.lastT(),null,t),c.computedCenter},enumerable:!0},eye:{get:function(){return c.computedEye},set:function(t){return c.lookAt(c.lastT(),t),c.computedEye},enumerable:!0},up:{get:function(){return c.computedUp},set:function(t){return c.lookAt(c.lastT(),null,null,t),c.computedUp},enumerable:!0},distance:{get:function(){return f},set:function(t){return c.setDistance(c.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return c.getDistanceLimits(r)},set:function(t){return c.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",(function(t){return t.preventDefault(),!1})),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,i,a){var o=d.keyBindingMode;if(!1!==o){var s=\"rotate\"===o,l=\"pan\"===o,u=\"zoom\"===o,h=!!a.control,p=!!a.alt,m=!!a.shift,g=!!(1&e),v=!!(2&e),y=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(i-d._lastY),w=d.flipX?1:-1,T=d.flipY?1:-1,k=Math.PI*d.rotateSpeed,M=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&g&&!h&&!p&&!m||g&&!h&&!p&&m)&&c.rotate(M,w*k*b,-T*k*_,0),(l&&g&&!h&&!p&&!m||v||g&&h&&!p&&!m)&&c.pan(M,-d.translateSpeed*b*f,d.translateSpeed*_*f,0),u&&g&&!h&&!p&&!m||y||g&&!h&&p&&!m)){var A=-d.zoomSpeed*_/window.innerHeight*(M-c.lastT())*100;c.pan(M,0,0,f*(Math.exp(A)-1))}return d._lastX=r,d._lastY=i,d._lastMods=a,!0}}d.mouseListener=a(t,e),t.addEventListener(\"touchstart\",(function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods)}),!!l&&{passive:!0}),t.addEventListener(\"touchmove\",(function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener(\"touchend\",(function(t){e(0,d._lastX,d._lastY,d._lastMods)}),!!l&&{passive:!0}),d.wheelListener=o(t,(function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,i=d.flipY?1:-1,a=n();if(Math.abs(t)>Math.abs(e))c.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-c.lastT())/20;c.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=t(\"right-now\"),i=t(\"3d-view\"),a=t(\"mouse-change\"),o=t(\"mouse-wheel\"),s=t(\"mouse-event-offset\"),l=t(\"has-passive-events\")},{\"3d-view\":55,\"has-passive-events\":440,\"mouse-change\":466,\"mouse-event-offset\":467,\"mouse-wheel\":469,\"right-now\":538}],320:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n  uv = position;\\n  gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n  gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},{\"gl-shader\":335,glslify:321}],321:[function(t,e,r){arguments[4][261][0].apply(r,arguments)},{dup:261}],322:[function(t,e,r){\"use strict\";var n=t(\"./camera.js\"),i=t(\"gl-axes3d\"),a=t(\"gl-axes3d/properties\"),o=t(\"gl-spikes3d\"),s=t(\"gl-select-static\"),l=t(\"gl-fbo\"),c=t(\"a-big-triangle\"),u=t(\"mouse-change\"),f=t(\"gl-mat4/perspective\"),h=t(\"gl-mat4/ortho\"),p=t(\"./lib/shader\"),d=t(\"is-mobile\")({tablet:!0,featureDetect:!0});function m(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function g(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function v(t){return\"boolean\"!=typeof t||t}e.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;if(!e){if(e=document.createElement(\"canvas\"),t.container)t.container.appendChild(e);else document.body.appendChild(e)}var r=t.gl;r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d}));if(!r)throw new Error(\"webgl not supported\");var y=t.bounds||[[-10,-10,-10],[10,10,10]],x=new m,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},M=i(r,k);M.enable=!k.disable;var A=t.spikes||{},S=o(r,A),E=[],L=[],C=[],P=[],I=!0,O=!0,z=new Array(16),D=new Array(16),R={view:null,projection:z,model:D,_ortho:!1},F=(O=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),B=t.cameraObject||n(e,T),N={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:B,axes:M,axesPixels:null,spikes:S,bounds:y,objects:E,shape:F,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:v(t.autoResize),autoBounds:v(t.autoBounds),autoScale:!!t.autoScale,autoCenter:v(t.autoCenter),clipToBounds:v(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:R,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,O=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},j=[r.drawingBufferWidth/N.pixelRatio|0,r.drawingBufferHeight/N.pixelRatio|0];function U(){if(!N._stopped&&N.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*N.pixelRatio),a=0|Math.ceil(n*N.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",I=!0}}}N.autoResize&&U();function V(){for(var t=E.length,e=P.length,n=0;n<e;++n)C[n]=0;t:for(n=0;n<t;++n){var i=E[n],a=i.pickSlots;if(a){for(var o=0;o<e;++o)if(C[o]+a<255){L[n]=o,i.setPickBase(C[o]+1),C[o]+=a;continue t}var l=s(r,F);L[n]=e,P.push(l),C.push(a),i.setPickBase(1),e+=1}else L[n]=-1}for(;e>0&&0===C[e-1];)C.pop(),P.pop().dispose()}function q(){if(N.contextLost)return!0;r.isContextLost()&&(N.contextLost=!0,N.mouseListener.enabled=!1,N.selection.object=null,N.oncontextloss&&N.oncontextloss())}window.addEventListener(\"resize\",U),N.update=function(t){N._stopped||(t=t||{},I=!0,O=!0)},N.add=function(t){N._stopped||(t.axes=M,E.push(t),L.push(-1),I=!0,O=!0,V())},N.remove=function(t){if(!N._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),L.pop(),I=!0,O=!0,V())}},N.dispose=function(){if(!N._stopped&&(N._stopped=!0,window.removeEventListener(\"resize\",U),e.removeEventListener(\"webglcontextlost\",q),N.mouseListener.enabled=!1,!N.contextLost)){M.dispose(),S.dispose();for(var t=0;t<E.length;++t)E[t].dispose();b.dispose();for(t=0;t<P.length;++t)P[t].dispose();_.dispose(),r=null,M=null,S=null,E=[]}},N._mouseRotating=!1,N._prevButtons=0,N.enableMouseListeners=function(){N.mouseListener=u(e,(function(t,e,r){if(!N._stopped){var n=P.length,i=E.length,a=x.object;x.distance=1/0,x.mouse[0]=e,x.mouse[1]=r,x.object=null,x.screen=null,x.dataCoordinate=x.dataPosition=null;var o=!1;if(t&&N._prevButtons)N._mouseRotating=!0;else{N._mouseRotating&&(O=!0),N._mouseRotating=!1;for(var s=0;s<n;++s){var l=P[s].query(e,j[1]-r-1,N.pickRadius);if(l){if(l.distance>x.distance)continue;for(var c=0;c<i;++c){var u=E[c];if(L[c]===s){var f=u.pick(l);f&&(x.buttons=t,x.screen=l.coord,x.distance=l.distance,x.object=u,x.index=f.distance,x.dataPosition=f.position,x.dataCoordinate=f.dataCoordinate,x.data=f,o=!0)}}}}}a&&a!==x.object&&(a.highlight&&a.highlight(null),I=!0),x.object&&(x.object.highlight&&x.object.highlight(x.data),I=!0),(o=o||x.object!==a)&&N.onselect&&N.onselect(x),1&t&&!(1&N._prevButtons)&&N.onclick&&N.onclick(x),N._prevButtons=t}}))},e.addEventListener(\"webglcontextlost\",q);var H=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],G=[H[0].slice(),H[1].slice()];function Y(){if(!q()){U();var t=N.camera.tick();R.view=N.camera.matrix,I=I||t,O=O||t,M.pixelRatio=N.pixelRatio,S.pixelRatio=N.pixelRatio;var e=E.length,n=H[0],i=H[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-1/0;for(var o=0;o<e;++o){(C=E[o]).pixelRatio=N.pixelRatio,C.axes=N.axes,I=I||!!C.dirty,O=O||!!C.dirty;var s=C.bounds;if(s)for(var l=s[0],u=s[1],p=0;p<3;++p)n[p]=Math.min(n[p],l[p]),i[p]=Math.max(i[p],u[p])}var d=N.bounds;if(N.autoBounds)for(p=0;p<3;++p){if(i[p]<n[p])n[p]=-1,i[p]=1;else{n[p]===i[p]&&(n[p]-=1,i[p]+=1);var m=.05*(i[p]-n[p]);n[p]=n[p]-m,i[p]=i[p]+m}d[0][p]=n[p],d[1][p]=i[p]}var v=!1;for(p=0;p<3;++p)v=v||G[0][p]!==d[0][p]||G[1][p]!==d[1][p],G[0][p]=d[0][p],G[1][p]=d[1][p];if(O=O||v,I=I||v){if(v){var y=[0,0,0];for(o=0;o<3;++o)y[o]=g((d[1][o]-d[0][o])/10);M.autoTicks?M.update({bounds:d,tickSpacing:y}):M.update({bounds:d})}var T=r.drawingBufferWidth,k=r.drawingBufferHeight;F[0]=T,F[1]=k,j[0]=0|Math.max(T/N.pixelRatio,1),j[1]=0|Math.max(k/N.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,i=n.projection,a=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,c=t.zFar,u=t.fovy,p=o/s;e?(h(i,-p,p,-1,1,l,c),n._ortho=!0):(f(i,u,p,l,c),n._ortho=!1);for(var d=0;d<16;++d)a[d]=0;a[15]=1;var m=0;for(d=0;d<3;++d)m=Math.max(m,r[1][d]-r[0][d]);for(d=0;d<3;++d)t.autoScale?a[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):a[5*d]=1/m,t.autoCenter&&(a[12+d]=.5*-a[5*d]*(r[0][d]+r[1][d]))}(N,w);for(o=0;o<e;++o){(C=E[o]).axesBounds=d,N.clipToBounds&&(C.clipBounds=d)}x.object&&(N.snapToData?S.position=x.dataCoordinate:S.position=x.dataPosition,S.bounds=d),O&&(O=!1,function(){if(!q()){r.colorMask(!0,!0,!0,!0),r.depthMask(!0),r.disable(r.BLEND),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL);for(var t=E.length,e=P.length,n=0;n<e;++n){var i=P[n];i.shape=j,i.begin();for(var a=0;a<t;++a)if(L[a]===n){var o=E[a];o.drawPick&&(o.pixelRatio=1,o.drawPick(R))}i.end()}}}()),N.axesPixels=a(N.axes,R,T,k),N.onrender&&N.onrender(),r.bindFramebuffer(r.FRAMEBUFFER,null),r.viewport(0,0,T,k),N.clearRGBA(),r.depthMask(!0),r.colorMask(!0,!0,!0,!0),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL),r.disable(r.BLEND),r.disable(r.CULL_FACE);var A=!1;M.enable&&(A=A||M.isTransparent(),M.draw(R)),S.axes=M,x.object&&S.draw(R),r.disable(r.CULL_FACE);for(o=0;o<e;++o){(C=E[o]).axes=M,C.pixelRatio=N.pixelRatio,C.isOpaque&&C.isOpaque()&&C.draw(R),C.isTransparent&&C.isTransparent()&&(A=!0)}if(A){b.shape=F,b.bind(),r.clear(r.DEPTH_BUFFER_BIT),r.colorMask(!1,!1,!1,!1),r.depthMask(!0),r.depthFunc(r.LESS),M.enable&&M.isTransparent()&&M.drawTransparent(R);for(o=0;o<e;++o){(C=E[o]).isOpaque&&C.isOpaque()&&C.draw(R)}r.enable(r.BLEND),r.blendEquation(r.FUNC_ADD),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.colorMask(!0,!0,!0,!0),r.depthMask(!1),r.clearColor(0,0,0,0),r.clear(r.COLOR_BUFFER_BIT),M.isTransparent()&&M.drawTransparent(R);for(o=0;o<e;++o){var C;(C=E[o]).isTransparent&&C.isTransparent()&&C.drawTransparent(R)}r.bindFramebuffer(r.FRAMEBUFFER,null),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.disable(r.DEPTH_TEST),_.bind(),b.color[0].bind(0),_.uniforms.accumBuffer=0,c(r),r.disable(r.BLEND)}I=!1;for(o=0;o<e;++o)E[o].dirty=!1}}}return N.enableMouseListeners(),function t(){if(N._stopped||N.contextLost)return;Y(),requestAnimationFrame(t)}(),N.redraw=function(){N._stopped||(I=!0,Y())},N},createCamera:n}},{\"./camera.js\":319,\"./lib/shader\":320,\"a-big-triangle\":70,\"gl-axes3d\":254,\"gl-axes3d/properties\":262,\"gl-fbo\":272,\"gl-mat4/ortho\":298,\"gl-mat4/perspective\":299,\"gl-select-static\":334,\"gl-spikes3d\":345,\"is-mobile\":451,\"mouse-change\":466}],323:[function(t,e,r){var n=t(\"glslify\");r.pointVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n  highp float a = 12.9898;\\n  highp float b = 78.233;\\n  highp float c = 43758.5453;\\n  highp float d = dot(co.xy, vec2(a, b));\\n  highp float e = mod(d, 3.14);\\n  return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n    // if we don't jitter the point size a bit, overall point cloud\\n    // saturation 'jumps' on zooming, which is disturbing and confusing\\n  gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    // get the same square surface as circle would be\\n    gl_PointSize *= 0.886;\\n  }\\n}\"]),r.pointFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n  float radius;\\n  vec4 baseColor;\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    if(centerFraction == 1.0) {\\n      gl_FragColor = color;\\n    } else {\\n      gl_FragColor = mix(borderColor, color, centerFraction);\\n    }\\n  } else {\\n    radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n    if(radius > 1.0) {\\n      discard;\\n    }\\n    baseColor = mix(borderColor, color, step(radius, centerFraction));\\n    gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n  }\\n}\\n\"]),r.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\"]),r.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"])},{glslify:438}],324:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"typedarray-pool\"),o=t(\"./lib/shader\");function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}e.exports=function(t,e){var r=t.gl,a=i(r),l=i(r),c=n(r,o.pointVertex,o.pointFragment),u=n(r,o.pickVertex,o.pickFragment),f=new s(t,a,l,c,u);return f.update(e),t.addObject(f),f};var l,c,u=s.prototype;u.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},u.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),c=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e<n;e++)c[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(c),i||a.free(l),o||a.free(c),this.pointCount=n,this.pickOffset=0},u.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],c=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,i=this.plot.dataBox;if(0===this.pointCount)return t;var a=i[2]-i[0],o=i[3]-i[1],s=function(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),u=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=u<5,r.uniforms.pointSize=u,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(c[0]=255&t,c[1]=t>>8&255,c[2]=t>>16&255,c[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=c,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),u.draw=u.unifiedDraw,u.drawPick=u.unifiedDraw,u.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":323,\"gl-buffer\":263,\"gl-shader\":335,\"typedarray-pool\":613}],325:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c=e[0],u=e[1],f=e[2],h=e[3],p=r[0],d=r[1],m=r[2],g=r[3];(a=c*p+u*d+f*m+h*g)<0&&(a=-a,p=-p,d=-d,m=-m,g=-g);1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n);return t[0]=s*c+l*p,t[1]=s*u+l*d,t[2]=s*f+l*m,t[3]=s*h+l*g,t}},{}],326:[function(t,e,r){\"use strict\";e.exports=function(t){return t||0===t?t.toString():\"\"}},{}],327:[function(t,e,r){\"use strict\";var n=t(\"vectorize-text\");e.exports=function(t,e,r){var a=i[e];a||(a=i[e]={});if(t in a)return a[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,c,u=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(c=0;c<s.positions[l].length;++c)s.positions[l][c]/=r;for(l=0;l<u.positions.length;++l)for(c=0;c<u.positions[l].length;++c)u.positions[l][c]/=r}var f=[[1/0,1/0],[-1/0,-1/0]],h=u.positions.length;for(l=0;l<h;++l){var p=u.positions[l];for(c=0;c<2;++c)f[0][c]=Math.min(f[0][c],p[c]),f[1][c]=Math.max(f[1][c],p[c])}return a[t]=[s,u,f]};var i={}},{\"vectorize-text\":619}],328:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n\\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (\\n    outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n    interpColor.a * opacity == 0.\\n  ) discard;\\n  gl_FragColor = interpColor * opacity;\\n}\\n\"]),c=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n  gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),u=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:u},h={vertex:o,fragment:l,attributes:u},p={vertex:s,fragment:l,attributes:u},d={vertex:a,fragment:c,attributes:u},m={vertex:o,fragment:c,attributes:u},g={vertex:s,fragment:c,attributes:u};function v(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}r.createPerspective=function(t){return v(t,f)},r.createOrtho=function(t){return v(t,h)},r.createProject=function(t){return v(t,p)},r.createPickPerspective=function(t){return v(t,d)},r.createPickOrtho=function(t){return v(t,m)},r.createPickProject=function(t){return v(t,g)}},{\"gl-shader\":335,glslify:329}],329:[function(t,e,r){arguments[4][261][0].apply(r,arguments)},{dup:261}],330:[function(t,e,r){\"use strict\";var n=t(\"is-string-blank\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"typedarray-pool\"),s=t(\"gl-mat4/multiply\"),l=t(\"./lib/shaders\"),c=t(\"./lib/glyphs\"),u=t(\"./lib/get-simple-string\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function m(t){return!0===t||t>1?1:t}function g(t,e,r,n,i,a,o,s,l,c,u,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=u,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}e.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),c=l.createPickOrtho(e),u=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),m=a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new g(e,r,n,o,f,h,p,d,m,s,c,u);return v.update(t),v};var v=g.prototype;v.pickSlots=1,v.setPickBase=function(t){this.pickId=t},v.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},v.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var y=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],M=[[0,0,0],[0,0,0]];function A(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function L(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,c=r.model||f,u=r.view||f,h=r.projection||f,d=e.axesBounds,m=function(t){for(var e=M,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],y[0]=2/o.drawingBufferWidth,y[1]=2/o.drawingBufferHeight,t.bind(),l.view=u,l.projection=h,l.screenSize=y,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=m,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var g=0;g<3;++g)if(a[g]){l.scale=e.projectScale[g],l.opacity=e.projectOpacity[g];for(var v=T,L=0;L<16;++L)v[L]=0;for(L=0;L<4;++L)v[5*L]=1;v[5*g]=0,i[g]<0?v[12+g]=d[0][g]:v[12+g]=d[1][g],s(v,c,v),l.model=v;var C=(g+1)%3,P=(g+2)%3,I=A(x),O=A(b);I[C]=1,O[P]=1;var z=p(0,0,0,S(_,I)),D=p(0,0,0,S(w,O));if(Math.abs(z[1])>Math.abs(D[1])){var R=z;z=D,D=R,R=I,I=O,O=R;var F=C;C=P,P=F}z[0]<0&&(I[C]=-1),D[1]>0&&(O[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(c[4*C+L],2),N+=Math.pow(c[4*P+L],2);I[C]/=Math.sqrt(B),O[P]/=Math.sqrt(N),l.axes[0]=I,l.axes[1]=O,l.fragClipBounds[0]=E(k,m[0],g,-1e8),l.fragClipBounds[1]=E(k,m[1],g,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}var C=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function P(t,e,r,n,i,a,o){var s=r.gl;if((a===r.projectHasAlpha||o)&&L(e,r,n,i),a===r.hasAlpha||o){t.bind();var l=t.uniforms;l.model=n.model||f,l.view=n.view||f,l.projection=n.projection||f,y[0]=2/s.drawingBufferWidth,y[1]=2/s.drawingBufferHeight,l.screenSize=y,l.highlightId=r.highlightId,l.highlightScale=r.highlightScale,l.fragClipBounds=C,l.clipBounds=r.axes.bounds,l.opacity=r.opacity,l.pickGroup=r.pickId/255,l.pixelRatio=i,r.vao.bind(),r.vao.draw(s.TRIANGLES,r.vertexCount),r.lineWidth>0&&(s.lineWidth(r.lineWidth*i),r.vao.draw(s.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function I(t,e,r,i){var a;a=Array.isArray(t)?e<t.length?t[e]:void 0:t,a=u(a);var o=!0;n(a)&&(a=\"\\u25bc\",o=!1);var s=c(a,r,i);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}v.draw=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},v.drawTransparent=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},v.drawPick=function(t){P(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},v.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},v.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},v.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{r=+t.projectOpacity;this.projectOpacity=[r,r,r]}for(var n=0;n<3;++n)this.projectOpacity[n]=m(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=m(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l=t.font||\"normal\",c=t.alignment||[0,0];if(2===c.length)i=c[0],a=c[1];else{i=[],a=[];for(n=0;n<c.length;++n)i[n]=c[n][0],a[n]=c[n][1]}var u=[1/0,1/0,1/0],f=[-1/0,-1/0,-1/0],h=t.glyph,p=t.color,d=t.size,g=t.angle,v=t.lineColor,y=-1,x=0,b=0,_=0;if(s.length){_=s.length;t:for(n=0;n<_;++n){for(var w=s[n],T=0;T<3;++T)if(isNaN(w[T])||!isFinite(w[T]))continue t;var k=(N=I(h,n,l,this.pixelRatio)).mesh,M=N.lines,A=N.bounds;x+=3*k.cells.length,b+=2*M.edges.length}}var S=x+b,E=o.mallocFloat(3*S),L=o.mallocFloat(4*S),C=o.mallocFloat(2*S),P=o.mallocUint32(S);if(S>0){var O=0,z=x,D=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(v)&&Array.isArray(v[0]);t:for(n=0;n<_;++n){y+=1;for(w=s[n],T=0;T<3;++T){if(isNaN(w[T])||!isFinite(w[T]))continue t;f[T]=Math.max(f[T],w[T]),u[T]=Math.min(u[T],w[T])}k=(N=I(h,n,l,this.pixelRatio)).mesh,M=N.lines,A=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(U=F?n<p.length?p[n]:[0,0,0,0]:p).length){for(T=0;T<3;++T)D[T]=U[T];D[3]=1}else if(4===U.length){for(T=0;T<4;++T)D[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else D[0]=D[1]=D[2]=0,D[3]=1;else D=[1,1,1,0];if(j)if(Array.isArray(v)){var U;if(3===(U=B?n<v.length?v[n]:[0,0,0,0]:v).length){for(T=0;T<3;++T)R[T]=U[T];R[T]=1}else if(4===U.length){for(T=0;T<4;++T)R[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else R[0]=R[1]=R[2]=0,R[3]=1;else R=[1,1,1,0];var V=.5;j?Array.isArray(d)?V=n<d.length?+d[n]:12:d?V=+d:this.useOrtho&&(V=12):V=0;var q=0;Array.isArray(g)?q=n<g.length?+g[n]:0:g&&(q=+g);var H=Math.cos(q),G=Math.sin(q);for(w=s[n],T=0;T<3;++T)f[T]=Math.max(f[T],w[T]),u[T]=Math.min(u[T],w[T]);var Y=i,W=a;Y=0;Array.isArray(i)?Y=n<i.length?i[n]:0:i&&(Y=i);W=0;Array.isArray(a)?W=n<a.length?a[n]:0:a&&(W=a);var X=[Y*=Y>0?1-A[0][0]:Y<0?1+A[1][0]:1,W*=W>0?1-A[0][1]:W<0?1+A[1][1]:1],Z=k.cells||[],J=k.positions||[];for(T=0;T<Z.length;++T)for(var K=Z[T],Q=0;Q<3;++Q){for(var $=0;$<3;++$)E[3*O+$]=w[$];for($=0;$<4;++$)L[4*O+$]=D[$];P[O]=y;var tt=J[K[Q]];C[2*O]=V*(H*tt[0]-G*tt[1]+X[0]),C[2*O+1]=V*(G*tt[0]+H*tt[1]+X[1]),O+=1}for(Z=M.edges,J=M.positions,T=0;T<Z.length;++T)for(K=Z[T],Q=0;Q<2;++Q){for($=0;$<3;++$)E[3*z+$]=w[$];for($=0;$<4;++$)L[4*z+$]=R[$];P[z]=y;tt=J[K[Q]];C[2*z]=V*(H*tt[0]-G*tt[1]+X[0]),C[2*z+1]=V*(G*tt[0]+H*tt[1]+X[1]),z+=1}}}this.bounds=[u,f],this.points=s,this.pointCount=s.length,this.vertexCount=x,this.lineVertexCount=b,this.pointBuffer.update(E),this.colorBuffer.update(L),this.glyphBuffer.update(C),this.idBuffer.update(P),o.free(E),o.free(L),o.free(C),o.free(P)},v.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/get-simple-string\":326,\"./lib/glyphs\":327,\"./lib/shaders\":328,\"gl-buffer\":263,\"gl-mat4/multiply\":297,\"gl-vao\":357,\"is-string-blank\":454,\"typedarray-pool\":613}],331:[function(t,e,r){\"use strict\";var n=t(\"glslify\");r.boxVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\"]),r.boxFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"])},{glslify:332}],332:[function(t,e,r){arguments[4][261][0].apply(r,arguments)},{dup:261}],333:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"./lib/shaders\");function o(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-1/0,-1/0],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}e.exports=function(t,e){var r=t.gl,s=i(r,[0,0,0,1,1,0,1,1]),l=n(r,a.boxVertex,a.boxFragment),c=new o(t,s,l);return c.update(e),t.addOverlay(c),c};var s=o.prototype;s.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,c=t.viewBox,u=t.pixelRatio,f=(e[0]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],h=(e[1]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1],p=(e[2]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],d=(e[3]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1];if(f=Math.max(f,c[0]),h=Math.max(h,c[1]),p=Math.min(p,c[2]),d=Math.min(d,c[3]),!(p<f||d<h)){o.bind();var m=s[2]-s[0],g=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,m,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,m,g,i),o.drawBox(p,h,m,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var v=r*u;o.drawBox(f-v,h-v,p+v,h+v,a),o.drawBox(f-v,d-v,p+v,d+v,a),o.drawBox(f-v,h-v,f+v,d+v,a),o.drawBox(p-v,h-v,p+v,d+v,a)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":331,\"gl-buffer\":263,\"gl-shader\":335}],334:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=e[0],a=e[1],o=n(t,r,a,{}),s=i.mallocUint8(r*a*4);return new l(t,o,s)};var n=t(\"gl-fbo\"),i=t(\"typedarray-pool\"),a=t(\"ndarray\"),o=t(\"bit-twiddle\").nextPow2;function s(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function 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a=[t.id,e.id,r.join(\":\"),i.join(\":\")].join(\"@\"),o=this.programs[a];return o&&this.gl.isProgram(o)||(this.programs[a]=o=function(t,e,r,i,a){var o=t.createProgram();t.attachShader(o,e),t.attachShader(o,r);for(var s=0;s<i.length;++s)t.bindAttribLocation(o,a[s],i[s]);if(t.linkProgram(o),!t.getProgramParameter(o,t.LINK_STATUS)){var l=t.getProgramInfoLog(o);throw new n(l,\"Error linking program: \"+l)}return o}(this.gl,t.shader,e.shader,r,i),t.programs.push(a),e.programs.push(a)),o}},{\"./GLError\":336,\"gl-format-compiler-error\":273,\"weakmap-shim\":624}],342:[function(t,e,r){\"use strict\";function n(t){this.plot=t,this.enable=[!0,!0,!1,!1],this.width=[1,1,1,1],this.color=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.center=[1/0,1/0]}e.exports=function(t,e){var r=new n(t);return r.update(e),t.addOverlay(r),r};var 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1\\n\\nattribute vec3 position, color;\\nattribute float weight;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 coordinates[3];\\nuniform vec4 colors[3];\\nuniform vec2 screenShape;\\nuniform float lineWidth;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vertexPosition = mix(coordinates[0],\\n    mix(coordinates[2], coordinates[1], 0.5 * (position + 1.0)), abs(position));\\n\\n  vec4 clipPos = projection * view * model * vec4(vertexPosition, 1.0);\\n  vec2 clipOffset = (projection * view * model * vec4(color, 0.0)).xy;\\n  vec2 delta = weight * clipOffset * screenShape;\\n  vec2 lineOffset = normalize(vec2(delta.y, -delta.x)) / screenShape;\\n\\n  gl_Position   = vec4(clipPos.xy + clipPos.w * 0.5 * lineWidth * lineOffset, clipPos.z, clipPos.w);\\n  fragColor     = color.x * colors[0] + color.y * colors[1] + color.z * colors[2];\\n}\\n\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec3\"},{name:\"weight\",type:\"float\"}])}},{\"gl-shader\":335,glslify:343}],345:[function(t,e,r){\"use strict\";var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders/index\");e.exports=function(t,e){var r=[];function o(t,e,n,i,a,o){var s=[t,e,n,0,0,0,1];s[i+3]=1,s[i]=a,r.push.apply(r,s),s[6]=-1,r.push.apply(r,s),s[i]=o,r.push.apply(r,s),r.push.apply(r,s),s[6]=1,r.push.apply(r,s),s[i]=a,r.push.apply(r,s)}o(0,0,0,0,0,1),o(0,0,0,1,0,1),o(0,0,0,2,0,1),o(1,0,0,1,-1,1),o(1,0,0,2,-1,1),o(0,1,0,0,-1,1),o(0,1,0,2,-1,1),o(0,0,1,0,-1,1),o(0,0,1,1,-1,1);var l=n(t,r),c=i(t,[{type:t.FLOAT,buffer:l,size:3,offset:0,stride:28},{type:t.FLOAT,buffer:l,size:3,offset:12,stride:28},{type:t.FLOAT,buffer:l,size:1,offset:24,stride:28}]),u=a(t);u.attributes.position.location=0,u.attributes.color.location=1,u.attributes.weight.location=2;var f=new s(t,l,c,u);return f.update(e),f};var o=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function s(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n,this.pixelRatio=1,this.bounds=[[-1e3,-1e3,-1e3],[1e3,1e3,1e3]],this.position=[0,0,0],this.lineWidth=[2,2,2],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.enabled=[!0,!0,!0],this.drawSides=[!0,!0,!0],this.axes=null}var l=s.prototype,c=[0,0,0],u=[0,0,0],f=[0,0];l.isTransparent=function(){return!1},l.drawTransparent=function(t){},l.draw=function(t){var e=this.gl,r=this.vao,n=this.shader;r.bind(),n.bind();var i,a=t.model||o,s=t.view||o,l=t.projection||o;this.axes&&(i=this.axes.lastCubeProps.axis);for(var h=c,p=u,d=0;d<3;++d)i&&i[d]<0?(h[d]=this.bounds[0][d],p[d]=this.bounds[1][d]):(h[d]=this.bounds[1][d],p[d]=this.bounds[0][d]);f[0]=e.drawingBufferWidth,f[1]=e.drawingBufferHeight,n.uniforms.model=a,n.uniforms.view=s,n.uniforms.projection=l,n.uniforms.coordinates=[this.position,h,p],n.uniforms.colors=this.colors,n.uniforms.screenShape=f;for(d=0;d<3;++d)n.uniforms.lineWidth=this.lineWidth[d]*this.pixelRatio,this.enabled[d]&&(r.draw(e.TRIANGLES,6,6*d),this.drawSides[d]&&r.draw(e.TRIANGLES,12,18+12*d));r.unbind()},l.update=function(t){t&&(\"bounds\"in t&&(this.bounds=t.bounds),\"position\"in t&&(this.position=t.position),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"colors\"in t&&(this.colors=t.colors),\"enabled\"in t&&(this.enabled=t.enabled),\"drawSides\"in t&&(this.drawSides=t.drawSides))},l.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders/index\":344,\"gl-buffer\":263,\"gl-vao\":357}],346:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * tubePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(tubePosition, 1.0);\\n  vec4 t_position  = view * tubePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = tubePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float tubeScale;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  gl_Position = projection * view * tubePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},{glslify:347}],347:[function(t,e,r){arguments[4][261][0].apply(r,arguments)},{dup:261}],348:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\"),i=t(\"gl-vec4\"),a=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],o=function(t,e,r,a){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,c=0;c<l.length;c++)o=Math.max(o,n.length(l[c]));var u=t.map((function(t){return function(t,e,r,a){for(var o=t.points,s=t.velocities,l=t.divergences,c=[],u=[],f=[],h=[],p=[],d=[],m=0,g=0,v=i.create(),y=i.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),g=n.length(_)/a,v=i.create(),n.copy(v,_),v[3]=w;for(var T=0;T<8;T++)p[T]=[b[0],b[1],b[2],T];if(h.length>0)for(T=0;T<8;T++){var k=(T+1)%8;c.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(y,v,v,v,y,y),d.push(m,g,g,g,m,m);var M=c.length;u.push([M-6,M-5,M-4],[M-3,M-2,M-1])}var A=h;h=p,p=A;var S=y;y=v,v=S;var E=m;m=g,g=E}return{positions:c,cells:u,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s<u.length;s++){var m=u[s],g=f.length;f=f.concat(m.positions),p=p.concat(m.vectors),d=d.concat(m.vertexIntensity);for(c=0;c<m.cells.length;c++){var v=m.cells[c],y=[];h.push(y);for(var x=0;x<v.length;x++)y.push(v[x]+g)}}return{positions:f,cells:h,vectors:p,vertexIntensity:d,colormap:e}},s=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var i=t[r];if(i===e)return r;if(i>e)return r-1}return r},l=function(t,e,r){return t<e?e:t>r?r:t},c=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;n<r;n++){var i=Math.abs(t[n]-t[n-1]);i<e&&(e=i)}return e};e.exports=function(t,e){var r=t.startingPositions,i=t.maxLength||1e3,u=t.tubeSize||1,f=t.absoluteTubeSize,h=t.gridFill||\"+x+y+z\",p={};-1!==h.indexOf(\"-x\")&&(p.reversedX=!0),-1!==h.indexOf(\"-y\")&&(p.reversedY=!0),-1!==h.indexOf(\"-z\")&&(p.reversedZ=!0),p.filled=a.indexOf(h.replace(/-/g,\"\").replace(/\\+/g,\"\"));var d=t.getVelocity||function(e){return function(t,e,r){var i=e.vectors,a=e.meshgrid,o=t[0],c=t[1],u=t[2],f=a[0].length,h=a[1].length,p=a[2].length,d=s(a[0],o),m=s(a[1],c),g=s(a[2],u),v=d+1,y=m+1,x=g+1;if(d=l(d,0,f-1),v=l(v,0,f-1),m=l(m,0,h-1),y=l(y,0,h-1),g=l(g,0,p-1),x=l(x,0,p-1),d<0||m<0||g<0||v>f-1||y>h-1||x>p-1)return n.create();var b,_,w,T,k,M,A=a[0][d],S=a[0][v],E=a[1][m],L=a[1][y],C=a[2][g],P=(o-A)/(S-A),I=(c-E)/(L-E),O=(u-C)/(a[2][x]-C);switch(isFinite(P)||(P=.5),isFinite(I)||(I=.5),isFinite(O)||(O=.5),r.reversedX&&(d=f-1-d,v=f-1-v),r.reversedY&&(m=h-1-m,y=h-1-y),r.reversedZ&&(g=p-1-g,x=p-1-x),r.filled){case 5:k=g,M=x,w=m*p,T=y*p,b=d*p*h,_=v*p*h;break;case 4:k=g,M=x,b=d*p,_=v*p,w=m*p*f,T=y*p*f;break;case 3:w=m,T=y,k=g*h,M=x*h,b=d*h*p,_=v*h*p;break;case 2:w=m,T=y,b=d*h,_=v*h,k=g*h*f,M=x*h*f;break;case 1:b=d,_=v,k=g*f,M=x*f,w=m*f*p,T=y*f*p;break;default:b=d,_=v,w=m*f,T=y*f,k=g*f*h,M=x*f*h}var z=i[b+w+k],D=i[b+w+M],R=i[b+T+k],F=i[b+T+M],B=i[_+w+k],N=i[_+w+M],j=i[_+T+k],U=i[_+T+M],V=n.create(),q=n.create(),H=n.create(),G=n.create();n.lerp(V,z,B,P),n.lerp(q,D,N,P),n.lerp(H,R,j,P),n.lerp(G,F,U,P);var Y=n.create(),W=n.create();n.lerp(Y,V,H,I),n.lerp(W,q,G,I);var X=n.create();return n.lerp(X,Y,W,O),X}(e,t,p)},m=t.getDivergence||function(t,e){var r=n.create(),i=1e-4;n.add(r,t,[i,0,0]);var a=d(r);n.subtract(a,a,e),n.scale(a,a,1/i),n.add(r,t,[0,i,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1/i),n.add(r,t,[0,0,i]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1/i),n.add(r,a,o),n.add(r,r,s),r},g=[],v=e[0][0],y=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],T=function(t){var e=t[0],r=t[1],n=t[2];return!(e<v||e>b||r<y||r>_||n<x||n>w)},k=10*n.distance(e[0],e[1])/i,M=k*k,A=1,S=0,E=r.length;E>1&&(A=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,l=0;l<s;l++){var u=t[l],f=u[0],h=u[1],p=u[2];i[f]||(e.push(f),i[f]=!0),a[h]||(r.push(h),a[h]=!0),o[p]||(n.push(p),o[p]=!0)}var d=c(e),m=c(r),g=c(n),v=Math.min(d,m,g);return isFinite(v)?v:1}(r));for(var L=0;L<E;L++){var C=n.create();n.copy(C,r[L]);var P=[C],I=[],O=d(C),z=C;I.push(O);var D=[],R=m(C,O),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F),g.push({points:P,velocities:I,divergences:D});for(var B=0;B<100*i&&P.length<i&&T(C);){B++;var N=n.clone(O),j=n.squaredLength(N);if(0===j)break;if(j>M&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,C),O=d(N),n.squaredDistance(z,N)-M>-1e-4*M){P.push(N),z=N,I.push(O);R=m(N,O),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F)}C=N}}var U=o(g,t.colormap,S,A);return f?U.tubeScale=f:(0===S&&(S=1),U.tubeScale=.5*u*A/S),U};var u=t(\"./lib/shaders\"),f=t(\"gl-cone3d\").createMesh;e.exports.createTubeMesh=function(t,e){return f(t,e,{shaders:u,traceType:\"streamtube\"})}},{\"./lib/shaders\":346,\"gl-cone3d\":264,\"gl-vec3\":376,\"gl-vec4\":412}],349:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform vec3 objectOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 localCoordinate = vec3(uv.zw, f.x);\\n  worldCoordinate = objectOffset + localCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  kill = f.y;\\n  value = f.z;\\n  planeCoordinate = uv.xy;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat beckmannSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  if (\\n    kill > 0.0 ||\\n    vColor.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\\n  ) discard;\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  //decide how to interpolate color \\u2014 in vertex or in fragment\\n  vec4 surfaceColor =\\n    step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\\n    step(.5, vertexColor) * vColor;\\n\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform vec3 objectOffset;\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  worldCoordinate = objectOffset + dataCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z += zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = f + objectOffset.z;\\n  kill = -1.0;\\n  planeCoordinate = uv.zw;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if ((kill > 0.0) ||\\n      (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);r.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},r.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{\"gl-shader\":335,glslify:438}],350:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=y(e),n=b(e),s=x(e),l=_(e),c=i(e),u=a(e,[{buffer:c,size:4,stride:40,offset:0},{buffer:c,size:3,stride:40,offset:16},{buffer:c,size:3,stride:40,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),m=o(e,1,256,e.RGBA,e.UNSIGNED_BYTE);m.minFilter=e.LINEAR,m.magFilter=e.LINEAR;var g=new A(e,[0,0],[[0,0,0],[0,0,0]],r,n,c,u,m,s,l,f,h,p,d,[0,0,0]),v={levels:[[],[],[]]};for(var w in t)v[w]=t[w];return v.colormap=v.colormap||\"jet\",g.update(v),g};var n=t(\"bit-twiddle\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"typedarray-pool\"),l=t(\"colormap\"),c=t(\"ndarray-ops\"),u=t(\"ndarray-pack\"),f=t(\"ndarray\"),h=t(\"surface-nets\"),p=t(\"gl-mat4/multiply\"),d=t(\"gl-mat4/invert\"),m=t(\"binary-search-bounds\"),g=t(\"ndarray-gradient\"),v=t(\"./lib/shaders\"),y=v.createShader,x=v.createContourShader,b=v.createPickShader,_=v.createPickContourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],T=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],k=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function M(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=k[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();function A(t,e,r,n,i,a,o,l,c,u,h,p,d,m,g){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=g,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=c,this._contourPickShader=u,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new M([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=m,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var S=A.prototype;S.genColormap=function(t,e){var r=!1,n=u([l({colormap:t,nshades:256,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return c.divseq(n,255),this.hasAlphaScale=r,n},S.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},S.isOpaque=function(){return!this.isTransparent()},S.pickSlots=1,S.setPickBase=function(t){this.pickId=t};var E=[0,0,0],L={showSurface:!1,showContour:!1,projections:[w.slice(),w.slice(),w.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function C(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||E,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=L.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var c=L.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)c[i][n]=t.clipBounds[i][n];c[0][r]=-1e8,c[1][r]=1e8}return L.showSurface=o,L.showContour=s,L}var P={model:w,view:w,projection:w,inverseModel:w.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},I=w.slice(),O=[1,0,0,0,1,0,0,0,1];function z(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=P;n.model=t.model||w,n.view=t.view||w,n.projection=t.projection||w,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=O,n.vertexColor=this.vertexColor;var s=I;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var c=s[12+i];for(o=0;o<3;++o)c+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=c/l}var u=C(n,this);if(u.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=u.projections[i],this._shader.uniforms.clipBounds=u.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(u.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=k[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o<this.contourLevels[i].length;++o)o===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==o&&o-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),this._contourCounts[i][o]&&(f.uniforms.height=this.contourLevels[i][o],h.draw(r.LINES,this._contourCounts[i][o],this._contourOffsets[i][o]));for(i=0;i<3;++i)for(f.uniforms.model=u.projections[i],f.uniforms.clipBounds=u.clipBounds[i],o=0;o<3;++o)if(this.contourProject[i][o]){f.uniforms.permutation=k[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var m=0;m<this.contourLevels[o].length;++m)m===this.highlightLevel[o]?(f.uniforms.contourColor=this.highlightColor[o],f.uniforms.contourTint=this.highlightTint[o]):0!==m&&m-1!==this.highlightLevel[o]||(f.uniforms.contourColor=this.contourColor[o],f.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][m]&&(f.uniforms.height=this.contourLevels[o][m],h.draw(r.LINES,this._contourCounts[o][m],this._contourOffsets[o][m]))}for(h.unbind(),(h=this._dynamicVAO).bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=k[i],r.lineWidth(this.dynamicWidth[i]*this.pixelRatio),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),o=0;o<3;++o)this.contourProject[o][i]&&(f.uniforms.model=u.projections[o],f.uniforms.clipBounds=u.clipBounds[o],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));h.unbind()}}S.draw=function(t){return z.call(this,t,!1)},S.drawTransparent=function(t){return z.call(this,t,!0)};var D={model:w,view:w,projection:w,inverseModel:w,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function R(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function F(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function B(t){if(Array.isArray(t)){if(Array.isArray(t))return[F(t[0]),F(t[1]),F(t[2])];var e=F(t);return[e.slice(),e.slice(),e.slice()]}}S.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=D;r.model=t.model||w,r.view=t.view||w,r.projection=t.projection||w,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=O;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var o=C(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]*this.pixelRatio),s.uniforms.permutation=k[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(s.uniforms.height=this.contourLevels[a][n],l.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){s.uniforms.permutation=k[a],e.lineWidth(this.contourWidth[a]*this.pixelRatio);for(var c=0;c<this.contourLevels[a].length;++c)this._contourCounts[a][c]&&(s.uniforms.height=this.contourLevels[a][c],l.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c]))}l.unbind()}},S.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var c=r.position;c[0]=c[1]=c[2]=0;for(var u=0;u<2;++u)for(var f=u?a:1-a,h=0;h<2;++h)for(var p=i+u,d=s+h,g=f*(h?l:1-l),v=0;v<3;++v)c[v]+=this._field[v].get(p,d)*g;for(var y=this._pickResult.level,x=0;x<3;++x)if(y[x]=m.le(this.contourLevels[x],c[x]),y[x]<0)this.contourLevels[x].length>0&&(y[x]=0);else if(y[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][y[x]],_=this.contourLevels[x][y[x]+1];Math.abs(b-c[x])>Math.abs(_-c[x])&&(y[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],v=0;v<3;++v)r.dataCoordinate[v]=this._field[v].get(r.index[0],r.index[1]);return r},S.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();c.assign(t.lo(1,1).hi(r[0],r[1]),e),c.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),c.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),c.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),c.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},S.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=R(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=R(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=R(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=B(t.contourColor)),\"contourProject\"in t&&(this.contourProject=R(t.contourProject,(function(t){return R(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=B(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=R(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=R(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var c=l[o];for(v=0;v<2;++v)if(c.shape[v]!==a[v])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],c)}}else if(t.ticks){var u=t.ticks;if(!Array.isArray(u)||2!==u.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=u[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var m=[0,0];m[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],m,0)}this._field[0].set(0,0,0);for(var v=0;v<a[0];++v)this._field[0].set(v+1,0,v);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),v=0;v<a[1];++v)this._field[1].set(0,v+1,v);this._field[1].set(0,a[1]+1,a[1]-1)}var y=this._field,x=f(s.mallocFloat(3*y[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)g(x.pick(o),y[o],\"mirror\");var b=f(s.mallocFloat(3*y[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(v=0;v<a[1]+2;++v){var _=x.get(0,o,v,0),w=x.get(0,o,v,1),k=x.get(1,o,v,0),M=x.get(1,o,v,1),A=x.get(2,o,v,0),S=x.get(2,o,v,1),E=k*S-M*A,L=A*w-S*_,C=_*M-w*k,P=Math.sqrt(E*E+L*L+C*C);P<1e-8?(P=Math.max(Math.abs(E),Math.abs(L),Math.abs(C)))<1e-8?(C=1,L=E=0,P=1):P=1/P:P=1/Math.sqrt(P),b.set(o,v,0,E*P),b.set(o,v,1,L*P),b.set(o,v,2,C*P)}s.free(x.data);var I=[1/0,1/0,1/0],O=[-1/0,-1/0,-1/0],z=1/0,D=-1/0,F=(a[0]-1)*(a[1]-1)*6,N=s.mallocFloat(n.nextPow2(10*F)),j=0,U=0;for(o=0;o<a[0]-1;++o)t:for(v=0;v<a[1]-1;++v){for(var V=0;V<2;++V)for(var q=0;q<2;++q)for(var H=0;H<3;++H){var G=this._field[H].get(1+o+V,1+v+q);if(isNaN(G)||!isFinite(G))continue t}for(H=0;H<6;++H){var Y=o+T[H][0],W=v+T[H][1],X=this._field[0].get(Y+1,W+1),Z=this._field[1].get(Y+1,W+1);G=this._field[2].get(Y+1,W+1),E=b.get(Y+1,W+1,0),L=b.get(Y+1,W+1,1),C=b.get(Y+1,W+1,2),t.intensity&&(J=t.intensity.get(Y,W));var J=t.intensity?t.intensity.get(Y,W):G+this.objectOffset[2];N[j++]=Y,N[j++]=W,N[j++]=X,N[j++]=Z,N[j++]=G,N[j++]=0,N[j++]=J,N[j++]=E,N[j++]=L,N[j++]=C,I[0]=Math.min(I[0],X+this.objectOffset[0]),I[1]=Math.min(I[1],Z+this.objectOffset[1]),I[2]=Math.min(I[2],G+this.objectOffset[2]),z=Math.min(z,J),O[0]=Math.max(O[0],X+this.objectOffset[0]),O[1]=Math.max(O[1],Z+this.objectOffset[1]),O[2]=Math.max(O[2],G+this.objectOffset[2]),D=Math.max(D,J),U+=1}}for(t.intensityBounds&&(z=+t.intensityBounds[0],D=+t.intensityBounds[1]),o=6;o<j;o+=10)N[o]=(N[o]-z)/(D-z);this._vertexCount=U,this._coordinateBuffer.update(N.subarray(0,j)),s.freeFloat(N),s.free(b.data),this.bounds=[I,O],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===z&&this.intensityBounds[1]===D||(r=!0),this.intensityBounds=[z,D]}if(\"levels\"in t){var K=t.levels;for(K=Array.isArray(K[0])?K.slice():[[],[],K],o=0;o<3;++o)K[o]=K[o].slice(),K[o].sort((function(t,e){return t-e}));for(o=0;o<3;++o)for(v=0;v<K[o].length;++v)K[o][v]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(K[o].length!==this.contourLevels[o].length){r=!0;break}for(v=0;v<K[o].length;++v)if(K[o][v]!==this.contourLevels[o][v]){r=!0;break t}}this.contourLevels=K}if(r){y=this._field,a=this.shape;for(var Q=[],$=0;$<3;++$){var tt=this.contourLevels[$],et=[],rt=[],nt=[0,0,0];for(o=0;o<tt.length;++o){var it=h(this._field[$],tt[o]);et.push(Q.length/5|0),U=0;t:for(v=0;v<it.cells.length;++v){var at=it.cells[v];for(H=0;H<2;++H){var ot=it.positions[at[H]],st=ot[0],lt=0|Math.floor(st),ct=st-lt,ut=ot[1],ft=0|Math.floor(ut),ht=ut-ft,pt=!1;e:for(var dt=0;dt<3;++dt){nt[dt]=0;var mt=($+dt+1)%3;for(V=0;V<2;++V){var gt=V?ct:1-ct;for(Y=0|Math.min(Math.max(lt+V,0),a[0]),q=0;q<2;++q){var vt=q?ht:1-ht;if(W=0|Math.min(Math.max(ft+q,0),a[1]),G=dt<2?this._field[mt].get(Y,W):(this.intensity.get(Y,W)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(G)||isNaN(G)){pt=!0;break e}var yt=gt*vt;nt[dt]+=yt*G}}}if(pt){if(H>0){for(var xt=0;xt<5;++xt)Q.pop();U-=1}continue t}Q.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[$]=et,this._contourCounts[$]=rt}var bt=s.mallocFloat(Q.length);for(o=0;o<Q.length;++o)bt[o]=Q[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},S.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},S.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,c=(o+2)%3,u=this._field[o],f=this._field[l],p=this._field[c],d=h(u,r[o]),m=d.cells,g=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<m.length;++e)for(var v=m[e],y=0;y<2;++y){var x=g[v[y]],b=+x[0],_=0|b,w=0|Math.min(_+1,i[0]),T=b-_,k=1-T,M=+x[1],A=0|M,S=0|Math.min(A+1,i[1]),E=M-A,L=1-E,C=k*L,P=k*E,I=T*L,O=T*E,z=C*f.get(_,A)+P*f.get(_,S)+I*f.get(w,A)+O*f.get(w,S),D=C*p.get(_,A)+P*p.get(_,S)+I*p.get(w,A)+O*p.get(w,S);if(isNaN(z)||isNaN(D)){y&&(n-=1);break}a[2*n+0]=z,a[2*n+1]=D,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),s.freeFloat(a)}}},{\"./lib/shaders\":349,\"binary-search-bounds\":103,\"bit-twiddle\":104,colormap:137,\"gl-buffer\":263,\"gl-mat4/invert\":295,\"gl-mat4/multiply\":297,\"gl-texture2d\":352,\"gl-vao\":357,ndarray:479,\"ndarray-gradient\":472,\"ndarray-ops\":474,\"ndarray-pack\":475,\"surface-nets\":587,\"typedarray-pool\":613}],351:[function(t,e,r){\"use strict\";var n=t(\"css-font\"),i=t(\"pick-by-alias\"),a=t(\"regl\"),o=t(\"gl-util/context\"),s=t(\"es6-weak-map\"),l=t(\"color-normalize\"),c=t(\"font-atlas\"),u=t(\"typedarray-pool\"),f=t(\"parse-rect\"),h=t(\"is-plain-obj\"),p=t(\"parse-unit\"),d=t(\"to-px\"),m=t(\"detect-kerning\"),g=t(\"object-assign\"),v=t(\"font-measure\"),y=t(\"flatten-vertex-data\"),x=t(\"bit-twiddle\").nextPow2,b=new s,_=!1;if(document.body){var w=document.body.appendChild(document.createElement(\"div\"));w.style.font=\"italic small-caps bold condensed 16px/2 cursive\",getComputedStyle(w).fontStretch&&(_=!0),document.body.removeChild(w)}var T=function(t){!function(t){return\"function\"==typeof t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||a({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(h(t)?t:{})};T.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},stencil:{enable:!1},depth:{enable:!1},count:t.prop(\"count\"),offset:t.prop(\"offset\"),attributes:{charOffset:{offset:4,stride:8,buffer:t.this(\"sizeBuffer\")},width:{offset:0,stride:8,buffer:t.this(\"sizeBuffer\")},char:t.this(\"charBuffer\"),position:t.this(\"position\")},uniforms:{atlasSize:function(t,e){return[e.atlas.width,e.atlas.height]},atlasDim:function(t,e){return[e.atlas.cols,e.atlas.rows]},atlas:function(t,e){return e.atlas.texture},charStep:function(t,e){return e.atlas.step},em:function(t,e){return e.atlas.em},color:t.prop(\"color\"),opacity:t.prop(\"opacity\"),viewport:t.this(\"viewportArray\"),scale:t.this(\"scale\"),align:t.prop(\"align\"),baseline:t.prop(\"baseline\"),translate:t.this(\"translate\"),positionOffset:t.prop(\"positionOffset\")},primitive:\"points\",viewport:t.this(\"viewport\"),vert:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tattribute float width, charOffset, char;\\n\\t\\t\\tattribute vec2 position;\\n\\t\\t\\tuniform float fontSize, charStep, em, align, baseline;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform vec4 color;\\n\\t\\t\\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\t\"+(T.normalViewport?\"\":\"vec2 positionOffset = vec2(positionOffset.x,- positionOffset.y);\")+\"\\n\\n\\t\\t\\t\\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\\n\\t\\t\\t\\t\\t+ positionOffset))\\n\\t\\t\\t\\t\\t/ (viewport.zw * scale.xy);\\n\\n\\t\\t\\t\\tvec2 position = (position + translate) * scale;\\n\\t\\t\\t\\tposition += offset * scale;\\n\\n\\t\\t\\t\\t\"+(T.normalViewport?\"position.y = 1. - position.y;\":\"\")+\"\\n\\n\\t\\t\\t\\tcharCoord = position * viewport.zw + viewport.xy;\\n\\n\\t\\t\\t\\tgl_Position = vec4(position * 2. - 1., 0, 1);\\n\\n\\t\\t\\t\\tgl_PointSize = charStep;\\n\\n\\t\\t\\t\\tcharId.x = mod(char, atlasDim.x);\\n\\t\\t\\t\\tcharId.y = floor(char / atlasDim.x);\\n\\n\\t\\t\\t\\tcharWidth = width * em;\\n\\n\\t\\t\\t\\tfontColor = color / 255.;\\n\\t\\t\\t}\",frag:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tuniform sampler2D atlas;\\n\\t\\t\\tuniform float fontSize, charStep, opacity;\\n\\t\\t\\tuniform vec2 atlasSize;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\n\\t\\t\\tfloat lightness(vec4 color) {\\n\\t\\t\\t\\treturn color.r * 0.299 + color.g * 0.587 + color.b * 0.114;\\n\\t\\t\\t}\\n\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 uv = gl_FragCoord.xy - charCoord + charStep * .5;\\n\\t\\t\\t\\tfloat halfCharStep = floor(charStep * .5 + .5);\\n\\n\\t\\t\\t\\t// invert y and shift by 1px (FF expecially needs that)\\n\\t\\t\\t\\tuv.y = charStep - uv.y;\\n\\n\\t\\t\\t\\t// ignore points outside of character bounding box\\n\\t\\t\\t\\tfloat halfCharWidth = ceil(charWidth * .5);\\n\\t\\t\\t\\tif (floor(uv.x) > halfCharStep + halfCharWidth ||\\n\\t\\t\\t\\t\\tfloor(uv.x) < halfCharStep - halfCharWidth) return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign textbaseline\",baseline:\"baseline textBaseline textbaseline\",direction:\"dir direction textDirection\",color:\"color colour fill fill-color fillColor textColor textcolor\",kerning:\"kerning kern\",range:\"range dataBox\",viewport:\"vp viewport viewBox viewbox viewPort\",opacity:\"opacity alpha transparency visible visibility opaque\",offset:\"offset positionOffset padding shift indent indentation\"},!0)).opacity&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map((function(t){return parseFloat(t)})):this.opacity=parseFloat(t.opacity)),null!=t.viewport&&(this.viewport=f(t.viewport),T.normalViewport&&(this.viewport.y=this.canvas.height-this.viewport.y-this.viewport.height),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null==this.viewport&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null!=t.kerning&&(this.kerning=t.kerning),null!=t.offset&&(\"number\"==typeof t.offset&&(t.offset=[t.offset,0]),this.positionOffset=y(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var i=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&i==e.font[r].baseString||(a=!0,e.font[r]=T.fonts[i],e.font[r]))){var c=t.family.join(\", \"),u=[t.style];t.style!=t.variant&&u.push(t.variant),t.variant!=t.weight&&u.push(t.weight),_&&t.weight!=t.stretch&&u.push(t.stretch),e.font[r]={baseString:i,family:c,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:v(c,{origin:\"top\",fontSize:T.baseFontSize,fontStyle:u.join(\" \")})},T.fonts[i]=e.font[r]}})),(a||o)&&this.font.forEach((function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),h=0;h<s.length;h++)s[h]=t.text;t.text=s}if(null!=t.text||a){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var b=1;b<t.text.length;b++)this.textOffsets[b]=this.textOffsets[b-1]+t.text[b-1].length,this.count+=t.text[b].length,this.counts.push(t.text[b].length);this.text=t.text.join(\"\")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];r=[],this.font.forEach((function(t,n){T.atlasContext.font=t.baseString;for(var i=e.fontAtlas[n],a=0;a<e.text.length;a++){var o=e.text.charAt(a);if(null==i.ids[o]&&(i.ids[o]=i.chars.length,i.chars.push(o),r.push(o)),null==t.width[o]&&(t.width[o]=T.atlasContext.measureText(o).width/T.baseFontSize,e.kerning)){var s=[];for(var l in t.width)s.push(l+o,o+l);g(t.kerning,m(t.family,{pairs:s}))}}}))}if(t.position)if(t.position.length>2){for(var w=!t.position[0].length,k=u.mallocFloat(2*this.count),M=0,A=0;M<this.counts.length;M++){var S=this.counts[M];if(w)for(var E=0;E<S;E++)k[A++]=t.position[2*M],k[A++]=t.position[2*M+1];else for(var L=0;L<S;L++)k[A++]=t.position[M][0],k[A++]=t.position[M][1]}this.position.call?this.position({type:\"float\",data:k}):this.position=this.regl.buffer({type:\"float\",data:k}),u.freeFloat(k)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||a){var C=u.mallocUint8(this.count),P=u.mallocFloat(2*this.count);this.textWidth=[];for(var I=0,O=0;I<this.counts.length;I++){for(var z=this.counts[I],D=this.font[I]||this.font[0],R=this.fontAtlas[I]||this.fontAtlas[0],F=0;F<z;F++){var B=this.text.charAt(O),N=this.text.charAt(O-1);if(C[O]=R.ids[B],P[2*O]=D.width[B],F){var j=P[2*O-2],U=P[2*O],V=P[2*O-1]+.5*j+.5*U;if(this.kerning){var q=D.kerning[N+B];q&&(V+=.001*q)}P[2*O+1]=V}else P[2*O+1]=.5*P[2*O];O++}this.textWidth.push(P.length?.5*P[2*O-2]+P[2*O-1]:0)}t.align||(t.align=this.align),this.charBuffer({data:C,type:\"uint8\",usage:\"stream\"}),this.sizeBuffer({data:P,type:\"float\",usage:\"stream\"}),u.freeUint8(C),u.freeFloat(P),r.length&&this.font.forEach((function(t,r){var n=e.fontAtlas[r],i=n.step,a=Math.floor(T.maxAtlasSize/i),o=Math.min(a,n.chars.length),s=Math.ceil(n.chars.length/o),l=x(o*i),u=x(s*i);n.width=l,n.height=u,n.rows=s,n.cols=o,n.em&&n.texture({data:c({canvas:T.atlasCanvas,font:n.fontString,chars:n.chars,shape:[l,u],step:[i,i]})})}))}if(t.align&&(this.align=t.align,this.alignOffset=this.textWidth.map((function(t,r){var n=Array.isArray(e.align)?e.align.length>1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0}))),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map((function(t,r){var n=(e.font[r]||e.font[0]).metrics,i=0;return i+=.5*n.bottom,i+=\"number\"==typeof t?t-n.baseline:-n[t],T.normalViewport||(i*=-1),i}))),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var H;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;H=u.mallocUint8(G);for(var Y=(t.color.subarray||t.color.slice).bind(t.color),W=0;W<G;W+=4)H.set(l(Y(W,W+4),\"uint8\"),W)}else{var X=t.color.length;H=u.mallocUint8(4*X);for(var Z=0;Z<X;Z++)H.set(l(t.color[Z]||0,\"uint8\"),4*Z)}this.color=H}else this.color=l(t.color,\"uint8\");if(t.position||t.text||t.color||t.baseline||t.align||t.font||t.offset||t.opacity)if(this.color.length>4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var J=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(J);for(var K=0;K<this.batch.length;K++)this.batch[K]={count:this.counts.length>1?this.counts[K]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[K]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*K,4*K+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[K]:this.opacity,baseline:null!=this.baselineOffset[K]?this.baselineOffset[K]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[K]?this.alignOffset[K]:this.alignOffset[0]:0,atlas:this.fontAtlas[K]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*K,2*K+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},T.prototype.destroy=function(){},T.prototype.kerning=!0,T.prototype.position={constant:new Float32Array(2)},T.prototype.translate=null,T.prototype.scale=null,T.prototype.font=null,T.prototype.text=\"\",T.prototype.positionOffset=[0,0],T.prototype.opacity=1,T.prototype.color=new Uint8Array([0,0,0,255]),T.prototype.alignOffset=[0,0],T.normalViewport=!1,T.maxAtlasSize=1024,T.atlasCanvas=document.createElement(\"canvas\"),T.atlasContext=T.atlasCanvas.getContext(\"2d\",{alpha:!1}),T.baseFontSize=64,T.fonts={},e.exports=T},{\"bit-twiddle\":104,\"color-normalize\":131,\"css-font\":150,\"detect-kerning\":177,\"es6-weak-map\":237,\"flatten-vertex-data\":248,\"font-atlas\":249,\"font-measure\":250,\"gl-util/context\":353,\"is-plain-obj\":453,\"object-assign\":483,\"parse-rect\":488,\"parse-unit\":490,\"pick-by-alias\":494,regl:536,\"to-px\":596,\"typedarray-pool\":613}],352:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"ndarray-ops\"),a=t(\"typedarray-pool\");e.exports=function(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");o||c(t);if(\"number\"==typeof arguments[1])return v(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return v(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1],r=u(e)?e:e.raw;if(r)return y(t,r,0|e.width,0|e.height,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return x(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function c(t){o=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],s=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],l=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var f=function(t,e){i.muls(t,e,255)};function h(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function p(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var d=p.prototype;function m(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function g(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function v(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=g(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new p(t,o,e,r,n,i)}function y(t,e,r,n,i,a){var o=g(t);return t.texImage2D(t.TEXTURE_2D,0,i,i,a,e),new p(t,o,r,n,i,a)}function x(t,e){var r=e.dtype,o=e.shape.slice(),s=t.getParameter(t.MAX_TEXTURE_SIZE);if(o[0]<0||o[0]>s||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=m(o,e.stride.slice()),c=0;\"float32\"===r?c=t.FLOAT:\"float64\"===r?(c=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?c=t.UNSIGNED_BYTE:(c=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var u,h,d=0;if(2===o.length)d=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])d=t.ALPHA;else if(2===o[2])d=t.LUMINANCE_ALPHA;else if(3===o[2])d=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");d=t.RGBA}}c!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(c=t.UNSIGNED_BYTE,l=!1);var v=e.size;if(l)u=0===e.offset&&e.data.length===v?e.data:e.data.subarray(e.offset,e.offset+v);else{var y=[o[2],o[2]*o[0],1];h=a.malloc(v,r);var 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f(this.rightPoints,t,e)}return h(this.leftPoints,e)},a.queryInterval=function(t,e,r){var n;if(t<this.mid&&this.left&&(n=this.left.queryInterval(t,e,r)))return n;if(e>this.mid&&this.right&&(n=this.right.queryInterval(t,e,r)))return n;return e<this.mid?u(this.leftPoints,e,r):t>this.mid?f(this.rightPoints,t,r):h(this.leftPoints,r)};var y=v.prototype;y.insert=function(t){this.root?this.root.insert(t):this.root=new i(t[0],null,null,[t],[t])},y.remove=function(t){if(this.root){var e=this.root.remove(t);return 2===e&&(this.root=null),0!==e}return!1},y.queryPoint=function(t,e){if(this.root)return this.root.queryPoint(t,e)},y.queryInterval=function(t,e,r){if(t<=e&&this.root)return this.root.queryInterval(t,e,r)},Object.defineProperty(y,\"count\",{get:function(){return this.root?this.root.count:0}}),Object.defineProperty(y,\"intervals\",{get:function(){return this.root?this.root.intervals([]):[]}})},{\"binary-search-bounds\":445}],445:[function(t,e,r){arguments[4][247][0].apply(r,arguments)},{dup:247}],446:[function(t,e,r){\"use strict\";e.exports=function(t,e){e=e||new Array(t.length);for(var r=0;r<t.length;++r)e[t[r]]=r;return e}},{}],447:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=new Array(t),r=0;r<t;++r)e[r]=r;return e}},{}],448:[function(t,e,r){e.exports=!0},{}],449:[function(t,e,r){function n(t){return!!t.constructor&&\"function\"==typeof t.constructor.isBuffer&&t.constructor.isBuffer(t)}\n",
+              "/*!\n",
+              " * Determine if an object is a Buffer\n",
+              " *\n",
+              " * @author   Feross Aboukhadijeh <https://feross.org>\n",
+              " * @license  MIT\n",
+              " */\n",
+              "e.exports=function(t){return null!=t&&(n(t)||function(t){return\"function\"==typeof t.readFloatLE&&\"function\"==typeof t.slice&&n(t.slice(0,0))}(t)||!!t._isBuffer)}},{}],450:[function(t,e,r){\"use strict\";e.exports=\"undefined\"!=typeof navigator&&(/MSIE/.test(navigator.userAgent)||/Trident\\//.test(navigator.appVersion))},{}],451:[function(t,e,r){\"use strict\";e.exports=a,e.exports.isMobile=a,e.exports.default=a;var n=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino/i,i=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino|android|ipad|playbook|silk/i;function a(t){t||(t={});var e=t.ua;if(e||\"undefined\"==typeof navigator||(e=navigator.userAgent),e&&e.headers&&\"string\"==typeof e.headers[\"user-agent\"]&&(e=e.headers[\"user-agent\"]),\"string\"!=typeof e)return!1;var r=t.tablet?i.test(e):n.test(e);return!r&&t.tablet&&t.featureDetect&&navigator&&navigator.maxTouchPoints>1&&-1!==e.indexOf(\"Macintosh\")&&-1!==e.indexOf(\"Safari\")&&(r=!0),r}},{}],452:[function(t,e,r){\"use strict\";e.exports=function(t){var e=typeof t;return null!==t&&(\"object\"===e||\"function\"===e)}},{}],453:[function(t,e,r){\"use strict\";var n=Object.prototype.toString;e.exports=function(t){var e;return\"[object Object]\"===n.call(t)&&(null===(e=Object.getPrototypeOf(t))||e===Object.getPrototypeOf({}))}},{}],454:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e,r=t.length,n=0;n<r;n++)if(((e=t.charCodeAt(n))<9||e>13)&&32!==e&&133!==e&&160!==e&&5760!==e&&6158!==e&&(e<8192||e>8205)&&8232!==e&&8233!==e&&8239!==e&&8287!==e&&8288!==e&&12288!==e&&65279!==e)return!1;return!0}},{}],455:[function(t,e,r){\"use strict\";e.exports=function(t){return\"string\"==typeof t&&(t=t.trim(),!!(/^[mzlhvcsqta]\\s*[-+.0-9][^mlhvzcsqta]+/i.test(t)&&/[\\dz]$/i.test(t)&&t.length>4))}},{}],456:[function(t,e,r){e.exports=function(t,e,r){return t*(1-r)+e*r}},{}],457:[function(t,e,r){!function(t,n){\"object\"==typeof r&&void 0!==e?e.exports=n():(t=t||self).mapboxgl=n()}(this,(function(){\"use strict\";var t,e,r;function n(n,i){if(t)if(e){var a=\"var sharedChunk = {}; (\"+t+\")(sharedChunk); (\"+e+\")(sharedChunk);\",o={};t(o),(r=i(o)).workerUrl=window.URL.createObjectURL(new Blob([a],{type:\"text/javascript\"}))}else e=i;else t=i}return n(0,(function(t){function e(t,e){return t(e={exports:{}},e.exports),e.exports}var r=n;function n(t,e,r,n){this.cx=3*t,this.bx=3*(r-t)-this.cx,this.ax=1-this.cx-this.bx,this.cy=3*e,this.by=3*(n-e)-this.cy,this.ay=1-this.cy-this.by,this.p1x=t,this.p1y=n,this.p2x=r,this.p2y=n}n.prototype.sampleCurveX=function(t){return((this.ax*t+this.bx)*t+this.cx)*t},n.prototype.sampleCurveY=function(t){return((this.ay*t+this.by)*t+this.cy)*t},n.prototype.sampleCurveDerivativeX=function(t){return(3*this.ax*t+2*this.bx)*t+this.cx},n.prototype.solveCurveX=function(t,e){var r,n,i,a,o;for(void 0===e&&(e=1e-6),i=t,o=0;o<8;o++){if(a=this.sampleCurveX(i)-t,Math.abs(a)<e)return i;var s=this.sampleCurveDerivativeX(i);if(Math.abs(s)<1e-6)break;i-=a/s}if((i=t)<(r=0))return r;if(i>(n=1))return n;for(;r<n;){if(a=this.sampleCurveX(i),Math.abs(a-t)<e)return i;t>a?r=i:n=i,i=.5*(n-r)+r}return i},n.prototype.solve=function(t,e){return this.sampleCurveY(this.solveCurveX(t,e))};var i=a;function a(t,e){this.x=t,this.y=e}function o(t,e,n,i){var a=new r(t,e,n,i);return function(t){return a.solve(t)}}a.prototype={clone:function(){return new a(this.x,this.y)},add:function(t){return this.clone()._add(t)},sub:function(t){return this.clone()._sub(t)},multByPoint:function(t){return this.clone()._multByPoint(t)},divByPoint:function(t){return this.clone()._divByPoint(t)},mult:function(t){return this.clone()._mult(t)},div:function(t){return this.clone()._div(t)},rotate:function(t){return this.clone()._rotate(t)},rotateAround:function(t,e){return this.clone()._rotateAround(t,e)},matMult:function(t){return this.clone()._matMult(t)},unit:function(){return this.clone()._unit()},perp:function(){return this.clone()._perp()},round:function(){return this.clone()._round()},mag:function(){return Math.sqrt(this.x*this.x+this.y*this.y)},equals:function(t){return this.x===t.x&&this.y===t.y},dist:function(t){return Math.sqrt(this.distSqr(t))},distSqr:function(t){var e=t.x-this.x,r=t.y-this.y;return e*e+r*r},angle:function(){return Math.atan2(this.y,this.x)},angleTo:function(t){return Math.atan2(this.y-t.y,this.x-t.x)},angleWith:function(t){return this.angleWithSep(t.x,t.y)},angleWithSep:function(t,e){return Math.atan2(this.x*e-this.y*t,this.x*t+this.y*e)},_matMult:function(t){var e=t[0]*this.x+t[1]*this.y,r=t[2]*this.x+t[3]*this.y;return this.x=e,this.y=r,this},_add:function(t){return this.x+=t.x,this.y+=t.y,this},_sub:function(t){return this.x-=t.x,this.y-=t.y,this},_mult:function(t){return this.x*=t,this.y*=t,this},_div:function(t){return this.x/=t,this.y/=t,this},_multByPoint:function(t){return this.x*=t.x,this.y*=t.y,this},_divByPoint:function(t){return this.x/=t.x,this.y/=t.y,this},_unit:function(){return this._div(this.mag()),this},_perp:function(){var t=this.y;return this.y=this.x,this.x=-t,this},_rotate:function(t){var e=Math.cos(t),r=Math.sin(t),n=e*this.x-r*this.y,i=r*this.x+e*this.y;return this.x=n,this.y=i,this},_rotateAround:function(t,e){var r=Math.cos(t),n=Math.sin(t),i=e.x+r*(this.x-e.x)-n*(this.y-e.y),a=e.y+n*(this.x-e.x)+r*(this.y-e.y);return this.x=i,this.y=a,this},_round:function(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this}},a.convert=function(t){return t instanceof a?t:Array.isArray(t)?new a(t[0],t[1]):t};var s=o(.25,.1,.25,1);function l(t,e,r){return Math.min(r,Math.max(e,t))}function c(t,e,r){var n=r-e,i=((t-e)%n+n)%n+e;return i===e?r:i}function u(t){for(var e=[],r=arguments.length-1;r-- >0;)e[r]=arguments[r+1];for(var n=0,i=e;n<i.length;n+=1){var a=i[n];for(var o in a)t[o]=a[o]}return t}var f=1;function h(){return f++}function p(){return function t(e){return e?(e^16*Math.random()>>e/4).toString(16):([1e7]+-[1e3]+-4e3+-8e3+-1e11).replace(/[018]/g,t)}()}function d(t){return!!t&&/^[0-9a-f]{8}-[0-9a-f]{4}-[4][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$/i.test(t)}function m(t,e){t.forEach((function(t){e[t]&&(e[t]=e[t].bind(e))}))}function g(t,e){return-1!==t.indexOf(e,t.length-e.length)}function v(t,e,r){var n={};for(var i in t)n[i]=e.call(r||this,t[i],i,t);return n}function y(t,e,r){var n={};for(var i 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r.width=t.width,r.height=t.height,n.drawImage(t,0,0,t.width,t.height),n.getImageData(-e,-e,t.width+2*e,t.height+2*e)},resolveURL:function(t){return L||(L=self.document.createElement(\"a\")),L.href=t,L.href},hardwareConcurrency:self.navigator.hardwareConcurrency||4,get devicePixelRatio(){return self.devicePixelRatio},get prefersReducedMotion(){return!!self.matchMedia&&(null==C&&(C=self.matchMedia(\"(prefers-reduced-motion: reduce)\")),C.matches)}},F={API_URL:\"https://api.mapbox.com\",get EVENTS_URL(){return this.API_URL?0===this.API_URL.indexOf(\"https://api.mapbox.cn\")?\"https://events.mapbox.cn/events/v2\":0===this.API_URL.indexOf(\"https://api.mapbox.com\")?\"https://events.mapbox.com/events/v2\":null:null},FEEDBACK_URL:\"https://apps.mapbox.com/feedback\",REQUIRE_ACCESS_TOKEN:!0,ACCESS_TOKEN:null,MAX_PARALLEL_IMAGE_REQUESTS:16},B={supported:!1,testSupport:function(t){if(N||!I)return;j?U(t):P=t}},N=!1,j=!1;function U(t){var 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Date.now()>this._skuTokenExpiresAt},q.prototype.transformRequest=function(t,e){return this._transformRequestFn&&this._transformRequestFn(t,e)||{url:t}},q.prototype.normalizeStyleURL=function(t,e){if(!H(t))return t;var r=X(t);return r.path=\"/styles/v1\"+r.path,this._makeAPIURL(r,this._customAccessToken||e)},q.prototype.normalizeGlyphsURL=function(t,e){if(!H(t))return t;var r=X(t);return r.path=\"/fonts/v1\"+r.path,this._makeAPIURL(r,this._customAccessToken||e)},q.prototype.normalizeSourceURL=function(t,e){if(!H(t))return t;var r=X(t);return r.path=\"/v4/\"+r.authority+\".json\",r.params.push(\"secure\"),this._makeAPIURL(r,this._customAccessToken||e)},q.prototype.normalizeSpriteURL=function(t,e,r,n){var i=X(t);return H(t)?(i.path=\"/styles/v1\"+i.path+\"/sprite\"+e+r,this._makeAPIURL(i,this._customAccessToken||n)):(i.path+=\"\"+e+r,Z(i))},q.prototype.normalizeTileURL=function(t,e){if(this._isSkuTokenExpired()&&this._createSkuToken(),t&&!H(t))return t;var r=X(t),n=R.devicePixelRatio>=2||512===e?\"@2x\":\"\",i=B.supported?\".webp\":\"$1\";r.path=r.path.replace(/(\\.(png|jpg)\\d*)(?=$)/,\"\"+n+i),r.path=r.path.replace(/^.+\\/v4\\//,\"/\"),r.path=\"/v4\"+r.path;var a=this._customAccessToken||function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e].match(/^access_token=(.*)$/);if(n)return n[1]}return null}(r.params)||F.ACCESS_TOKEN;return F.REQUIRE_ACCESS_TOKEN&&a&&this._skuToken&&r.params.push(\"sku=\"+this._skuToken),this._makeAPIURL(r,a)},q.prototype.canonicalizeTileURL=function(t,e){var r=X(t);if(!r.path.match(/(^\\/v4\\/)/)||!r.path.match(/\\.[\\w]+$/))return t;var n=\"mapbox://tiles/\";n+=r.path.replace(\"/v4/\",\"\");var i=r.params;return e&&(i=i.filter((function(t){return!t.match(/^access_token=/)}))),i.length&&(n+=\"?\"+i.join(\"&\")),n},q.prototype.canonicalizeTileset=function(t,e){for(var r=!!e&&H(e),n=[],i=0,a=t.tiles||[];i<a.length;i+=1){var o=a[i];Y(o)?n.push(this.canonicalizeTileURL(o,r)):n.push(o)}return 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r=e.parse(t[1],1,Bt);if(!r)return null;var n=[],i=null;e.expectedType&&\"value\"!==e.expectedType.kind&&(i=e.expectedType);for(var a=1;a<t.length;a+=2){var o=1===a?-1/0:t[a],s=t[a+1],l=a,c=a+1;if(\"number\"!=typeof o)return e.error('Input/output pairs for \"step\" expressions must be defined using literal numeric values (not computed expressions) for the input values.',l);if(n.length&&n[n.length-1][0]>=o)return e.error('Input/output pairs for \"step\" expressions must be arranged with input values in strictly ascending order.',l);var u=e.parse(s,c,i);if(!u)return null;i=i||u.type,n.push([o,u])}return new qe(i,r,n)},qe.prototype.evaluate=function(t){var e=this.labels,r=this.outputs;if(1===e.length)return r[0].evaluate(t);var n=this.input.evaluate(t);if(n<=e[0])return r[0].evaluate(t);var i=e.length;return n>=e[i-1]?r[i-1].evaluate(t):r[Ve(e,n)].evaluate(t)},qe.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1){t(r[e])}},qe.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},qe.prototype.serialize=function(){for(var t=[\"step\",this.input.serialize()],e=0;e<this.labels.length;e++)e>0&&t.push(this.labels[e]),t.push(this.outputs[e].serialize());return t};var Ge=Object.freeze({__proto__:null,number:He,color:function(t,e,r){return new te(He(t.r,e.r,r),He(t.g,e.g,r),He(t.b,e.b,r),He(t.a,e.a,r))},array:function(t,e,r){return t.map((function(t,n){return He(t,e[n],r)}))}}),Ye=6/29,We=3*Ye*Ye,Xe=Math.PI/180,Ze=180/Math.PI;function Je(t){return t>.008856451679035631?Math.pow(t,1/3):t/We+4/29}function Ke(t){return t>Ye?t*t*t:We*(t-4/29)}function Qe(t){return 255*(t<=.0031308?12.92*t:1.055*Math.pow(t,1/2.4)-.055)}function $e(t){return(t/=255)<=.04045?t/12.92:Math.pow((t+.055)/1.055,2.4)}function tr(t){var e=$e(t.r),r=$e(t.g),n=$e(t.b),i=Je((.4124564*e+.3575761*r+.1804375*n)/.95047),a=Je((.2126729*e+.7151522*r+.072175*n)/1);return{l:116*a-16,a:500*(i-a),b:200*(a-Je((.0193339*e+.119192*r+.9503041*n)/1.08883)),alpha:t.a}}function er(t){var e=(t.l+16)/116,r=isNaN(t.a)?e:e+t.a/500,n=isNaN(t.b)?e:e-t.b/200;return e=1*Ke(e),r=.95047*Ke(r),n=1.08883*Ke(n),new te(Qe(3.2404542*r-1.5371385*e-.4985314*n),Qe(-.969266*r+1.8760108*e+.041556*n),Qe(.0556434*r-.2040259*e+1.0572252*n),t.alpha)}function rr(t,e,r){var n=e-t;return t+r*(n>180||n<-180?n-360*Math.round(n/360):n)}var nr={forward:tr,reverse:er,interpolate:function(t,e,r){return{l:He(t.l,e.l,r),a:He(t.a,e.a,r),b:He(t.b,e.b,r),alpha:He(t.alpha,e.alpha,r)}}},ir={forward:function(t){var e=tr(t),r=e.l,n=e.a,i=e.b,a=Math.atan2(i,n)*Ze;return{h:a<0?a+360:a,c:Math.sqrt(n*n+i*i),l:r,alpha:t.a}},reverse:function(t){var e=t.h*Xe,r=t.c;return 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if(\"exponential\"===n[0]){var o=n[1];if(\"number\"!=typeof o)return e.error(\"Exponential interpolation requires a numeric base.\",1,1);n={name:\"exponential\",base:o}}else{if(\"cubic-bezier\"!==n[0])return e.error(\"Unknown interpolation type \"+String(n[0]),1,0);var s=n.slice(1);if(4!==s.length||s.some((function(t){return\"number\"!=typeof t||t<0||t>1})))return e.error(\"Cubic bezier interpolation requires four numeric arguments with values between 0 and 1.\",1);n={name:\"cubic-bezier\",controlPoints:s}}if(t.length-1<4)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if((t.length-1)%2!=0)return e.error(\"Expected an even number of arguments.\");if(!(i=e.parse(i,2,Bt)))return null;var l=[],c=null;\"interpolate-hcl\"===r||\"interpolate-lab\"===r?c=Ut:e.expectedType&&\"value\"!==e.expectedType.kind&&(c=e.expectedType);for(var u=0;u<a.length;u+=2){var f=a[u],h=a[u+1],p=u+3,d=u+4;if(\"number\"!=typeof f)return e.error('Input/output pairs for 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a=Ve(e,n),o=e[a],s=e[a+1],l=or.interpolationFactor(this.interpolation,n,o,s),c=r[a].evaluate(t),u=r[a+1].evaluate(t);return\"interpolate\"===this.operator?Ge[this.type.kind.toLowerCase()](c,u,l):\"interpolate-hcl\"===this.operator?ir.reverse(ir.interpolate(ir.forward(c),ir.forward(u),l)):nr.reverse(nr.interpolate(nr.forward(c),nr.forward(u),l))},or.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1){t(r[e])}},or.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},or.prototype.serialize=function(){var t;t=\"linear\"===this.interpolation.name?[\"linear\"]:\"exponential\"===this.interpolation.name?1===this.interpolation.base?[\"linear\"]:[\"exponential\",this.interpolation.base]:[\"cubic-bezier\"].concat(this.interpolation.controlPoints);for(var e=[this.operator,t,this.input.serialize()],r=0;r<this.labels.length;r++)e.push(this.labels[r],this.outputs[r].serialize());return e};var lr=function(t,e){this.type=t,this.args=e};lr.parse=function(t,e){if(t.length<2)return e.error(\"Expectected at least one argument.\");var r=null,n=e.expectedType;n&&\"value\"!==n.kind&&(r=n);for(var i=[],a=0,o=t.slice(1);a<o.length;a+=1){var s=o[a],l=e.parse(s,1+i.length,r,void 0,{typeAnnotation:\"omit\"});if(!l)return null;r=r||l.type,i.push(l)}var c=n&&i.some((function(t){return Jt(n,t.type)}));return new lr(c?qt:r,i)},lr.prototype.evaluate=function(t){for(var e,r=null,n=0,i=0,a=this.args;i<a.length;i+=1){if(n++,(r=a[i].evaluate(t))&&r instanceof ie&&!r.available&&(e||(e=r.name),r=null,n===this.args.length&&(r=e)),null!==r)break}return r},lr.prototype.eachChild=function(t){this.args.forEach(t)},lr.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},lr.prototype.serialize=function(){var t=[\"coalesce\"];return this.eachChild((function(e){t.push(e.serialize())})),t};var cr=function(t,e){this.type=e.type,this.bindings=[].concat(t),this.result=e};cr.prototype.evaluate=function(t){return this.result.evaluate(t)},cr.prototype.eachChild=function(t){for(var e=0,r=this.bindings;e<r.length;e+=1){t(r[e][1])}t(this.result)},cr.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found \"+(t.length-1)+\" instead.\");for(var r=[],n=1;n<t.length-1;n+=2){var i=t[n];if(\"string\"!=typeof i)return e.error(\"Expected string, but found \"+typeof i+\" instead.\",n);if(/[^a-zA-Z0-9_]/.test(i))return e.error(\"Variable names must contain only alphanumeric characters or '_'.\",n);var a=e.parse(t[n+1],n+1);if(!a)return null;r.push([i,a])}var o=e.parse(t[t.length-1],t.length-1,e.expectedType,r);return o?new cr(r,o):null},cr.prototype.outputDefined=function(){return this.result.outputDefined()},cr.prototype.serialize=function(){for(var t=[\"let\"],e=0,r=this.bindings;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];t.push(i,a.serialize())}return t.push(this.result.serialize()),t};var ur=function(t,e,r){this.type=t,this.index=e,this.input=r};ur.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Bt),n=e.parse(t[2],2,Wt(e.expectedType||qt));if(!r||!n)return null;var i=n.type;return new ur(i.itemType,r,n)},ur.prototype.evaluate=function(t){var e=this.index.evaluate(t),r=this.input.evaluate(t);if(e<0)throw new ue(\"Array index out of bounds: \"+e+\" < 0.\");if(e>=r.length)throw new ue(\"Array index out of bounds: \"+e+\" > \"+(r.length-1)+\".\");if(e!==Math.floor(e))throw new ue(\"Array index must be an integer, but found \"+e+\" instead.\");return r[e]},ur.prototype.eachChild=function(t){t(this.index),t(this.input)},ur.prototype.outputDefined=function(){return!1},ur.prototype.serialize=function(){return[\"at\",this.index.serialize(),this.input.serialize()]};var fr=function(t,e){this.type=jt,this.needle=t,this.haystack=e};fr.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,qt),n=e.parse(t[2],2,qt);return r&&n?Kt(r.type,[jt,Nt,Bt,Ft,qt])?new fr(r,n):e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(r.type)+\" instead\"):null},fr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!r)return!1;if(!Qt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new ue(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(se(e))+\" instead.\");if(!Qt(r,[\"string\",\"array\"]))throw new ue(\"Expected second argument to be of type array or string, but found \"+Xt(se(r))+\" instead.\");return r.indexOf(e)>=0},fr.prototype.eachChild=function(t){t(this.needle),t(this.haystack)},fr.prototype.outputDefined=function(){return!0},fr.prototype.serialize=function(){return[\"in\",this.needle.serialize(),this.haystack.serialize()]};var hr=function(t,e,r){this.type=Bt,this.needle=t,this.haystack=e,this.fromIndex=r};hr.parse=function(t,e){if(t.length<=2||t.length>=5)return e.error(\"Expected 3 or 4 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,qt),n=e.parse(t[2],2,qt);if(!r||!n)return null;if(!Kt(r.type,[jt,Nt,Bt,Ft,qt]))return e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(r.type)+\" instead\");if(4===t.length){var i=e.parse(t[3],3,Bt);return i?new hr(r,n,i):null}return new hr(r,n)},hr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!Qt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new ue(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(se(e))+\" instead.\");if(!Qt(r,[\"string\",\"array\"]))throw new ue(\"Expected second argument to be of type array or string, but found \"+Xt(se(r))+\" instead.\");if(this.fromIndex){var n=this.fromIndex.evaluate(t);return r.indexOf(e,n)}return r.indexOf(e)},hr.prototype.eachChild=function(t){t(this.needle),t(this.haystack),this.fromIndex&&t(this.fromIndex)},hr.prototype.outputDefined=function(){return!1},hr.prototype.serialize=function(){if(null!=this.fromIndex&&void 0!==this.fromIndex){var t=this.fromIndex.serialize();return[\"index-of\",this.needle.serialize(),this.haystack.serialize(),t]}return[\"index-of\",this.needle.serialize(),this.haystack.serialize()]};var pr=function(t,e,r,n,i,a){this.inputType=t,this.type=e,this.input=r,this.cases=n,this.outputs=i,this.otherwise=a};pr.parse=function(t,e){if(t.length<5)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=1)return e.error(\"Expected an even number of 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m?\"value\"!==d.type.kind&&e.concat(1).checkSubtype(r,d.type)?null:new pr(r,n,d,i,a,m):null},pr.prototype.evaluate=function(t){var e=this.input.evaluate(t);return(se(e)===this.inputType&&this.outputs[this.cases[e]]||this.otherwise).evaluate(t)},pr.prototype.eachChild=function(t){t(this.input),this.outputs.forEach(t),t(this.otherwise)},pr.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))&&this.otherwise.outputDefined()},pr.prototype.serialize=function(){for(var t=this,e=[\"match\",this.input.serialize()],r=[],n={},i=0,a=Object.keys(this.cases).sort();i<a.length;i+=1){var o=a[i];void 0===(f=n[this.cases[o]])?(n[this.cases[o]]=r.length,r.push([this.cases[o],[o]])):r[f][1].push(o)}for(var s=function(e){return\"number\"===t.inputType.kind?Number(e):e},l=0,c=r;l<c.length;l+=1){var u=c[l],f=u[0],h=u[1];1===h.length?e.push(s(h[0])):e.push(h.map(s)),e.push(this.outputs[outputIndex$1].serialize())}return e.push(this.otherwise.serialize()),e};var dr=function(t,e,r){this.type=t,this.branches=e,this.otherwise=r};dr.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=0)return e.error(\"Expected an odd number of arguments.\");var r;e.expectedType&&\"value\"!==e.expectedType.kind&&(r=e.expectedType);for(var n=[],i=1;i<t.length-1;i+=2){var a=e.parse(t[i],i,jt);if(!a)return null;var o=e.parse(t[i+1],i+1,r);if(!o)return null;n.push([a,o]),r=r||o.type}var s=e.parse(t[t.length-1],t.length-1,r);return s?new dr(r,n,s):null},dr.prototype.evaluate=function(t){for(var e=0,r=this.branches;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];if(i.evaluate(t))return a.evaluate(t)}return this.otherwise.evaluate(t)},dr.prototype.eachChild=function(t){for(var e=0,r=this.branches;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];t(i),t(a)}t(this.otherwise)},dr.prototype.outputDefined=function(){return this.branches.every((function(t){t[0];return 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or?a.interpolation:void 0;return Ir(new Zr(n?\"camera\":\"composite\",t.value,a.labels,o))}Zr.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)},Zr.prototype.evaluate=function(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)},Zr.prototype.interpolationFactor=function(t,e,r){return this.interpolationType?or.interpolationFactor(this.interpolationType,t,e,r):0};var Kr=function(t,e){this._parameters=t,this._specification=e,It(this,function t(e,r){var n,i,a,o=\"color\"===r.type,s=e.stops&&\"object\"==typeof e.stops[0][0],l=s||void 0!==e.property,c=s||!l,u=e.type||(Rr(r)?\"exponential\":\"interval\");if(o&&((e=It({},e)).stops&&(e.stops=e.stops.map((function(t){return[t[0],te.parse(t[1])]}))),e.default?e.default=te.parse(e.default):e.default=te.parse(r.default)),e.colorSpace&&\"rgb\"!==e.colorSpace&&!ar[e.colorSpace])throw new Error(\"Unknown color space: 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n&&r<n.minimum?[new Ct(e,r,r+\" is less than the minimum value \"+n.minimum)]:\"maximum\"in n&&r>n.maximum?[new Ct(e,r,r+\" is greater than the maximum value \"+n.maximum)]:[]}function en(t){var e,r,n,i=t.valueSpec,a=Ot(t.value.type),o={},s=\"categorical\"!==a&&void 0===t.value.property,l=!s,c=\"array\"===Fr(t.value.stops)&&\"array\"===Fr(t.value.stops[0])&&\"object\"===Fr(t.value.stops[0][0]),u=Qr({key:t.key,value:t.value,valueSpec:t.styleSpec.function,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{stops:function(t){if(\"identity\"===a)return[new Ct(t.key,t.value,'identity function may not have a \"stops\" property')];var e=[],r=t.value;e=e.concat($r({key:t.key,value:r,valueSpec:t.valueSpec,style:t.style,styleSpec:t.styleSpec,arrayElementValidator:f})),\"array\"===Fr(r)&&0===r.length&&e.push(new Ct(t.key,r,\"array must have at least one stop\"));return e},default:function(t){return kn({key:t.key,value:t.value,valueSpec:i,style:t.style,styleSpec:t.styleSpec})}}});return\"identity\"===a&&s&&u.push(new Ct(t.key,t.value,'missing required property \"property\"')),\"identity\"===a||t.value.stops||u.push(new Ct(t.key,t.value,'missing required property \"stops\"')),\"exponential\"===a&&t.valueSpec.expression&&!Rr(t.valueSpec)&&u.push(new Ct(t.key,t.value,\"exponential functions not supported\")),t.styleSpec.$version>=8&&(l&&!zr(t.valueSpec)?u.push(new Ct(t.key,t.value,\"property functions not supported\")):s&&!Dr(t.valueSpec)&&u.push(new Ct(t.key,t.value,\"zoom functions not supported\"))),\"categorical\"!==a&&!c||void 0!==t.value.property||u.push(new Ct(t.key,t.value,'\"property\" property is required')),u;function f(t){var e=[],a=t.value,s=t.key;if(\"array\"!==Fr(a))return[new Ct(s,a,\"array expected, \"+Fr(a)+\" found\")];if(2!==a.length)return[new Ct(s,a,\"array length 2 expected, length \"+a.length+\" found\")];if(c){if(\"object\"!==Fr(a[0]))return[new Ct(s,a,\"object expected, \"+Fr(a[0])+\" found\")];if(void 0===a[0].zoom)return[new Ct(s,a,\"object stop key must have zoom\")];if(void 0===a[0].value)return[new Ct(s,a,\"object stop key must have value\")];if(n&&n>Ot(a[0].zoom))return[new Ct(s,a[0].zoom,\"stop zoom values must appear in ascending order\")];Ot(a[0].zoom)!==n&&(n=Ot(a[0].zoom),r=void 0,o={}),e=e.concat(Qr({key:s+\"[0]\",value:a[0],valueSpec:{zoom:{}},style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:tn,value:h}}))}else e=e.concat(h({key:s+\"[0]\",value:a[0],valueSpec:{},style:t.style,styleSpec:t.styleSpec},a));return Yr(zt(a[1]))?e.concat([new Ct(s+\"[1]\",a[1],\"expressions are not allowed in function stops.\")]):e.concat(kn({key:s+\"[1]\",value:a[1],valueSpec:i,style:t.style,styleSpec:t.styleSpec}))}function h(t,n){var s=Fr(t.value),l=Ot(t.value),c=null!==t.value?t.value:n;if(e){if(s!==e)return[new Ct(t.key,c,s+\" stop domain type must match previous stop domain type \"+e)]}else e=s;if(\"number\"!==s&&\"string\"!==s&&\"boolean\"!==s)return[new Ct(t.key,c,\"stop domain value must be a number, string, or boolean\")];if(\"number\"!==s&&\"categorical\"!==a){var u=\"number expected, \"+s+\" found\";return zr(i)&&void 0===a&&(u+='\\nIf you intended to use a categorical function, specify `\"type\": \"categorical\"`.'),[new Ct(t.key,c,u)]}return\"categorical\"!==a||\"number\"!==s||isFinite(l)&&Math.floor(l)===l?\"categorical\"!==a&&\"number\"===s&&void 0!==r&&l<r?[new Ct(t.key,c,\"stop domain values must appear in ascending order\")]:(r=l,\"categorical\"===a&&l in o?[new Ct(t.key,c,\"stop domain values must be unique\")]:(o[l]=!0,[])):[new Ct(t.key,c,\"integer expected, found \"+l)]}}function rn(t){var e=(\"property\"===t.expressionContext?Jr:Wr)(zt(t.value),t.valueSpec);if(\"error\"===e.result)return e.value.map((function(e){return new Ct(\"\"+t.key+e.key,t.value,e.message)}));var r=e.value.expression||e.value._styleExpression.expression;if(\"property\"===t.expressionContext&&\"text-font\"===t.propertyKey&&!r.outputDefined())return[new Ct(t.key,t.value,'Invalid data expression for \"'+t.propertyKey+'\". Output values must be contained as literals within the expression.')];if(\"property\"===t.expressionContext&&\"layout\"===t.propertyType&&!Be(r))return[new Ct(t.key,t.value,'\"feature-state\" data expressions are not supported with layout properties.')];if(\"filter\"===t.expressionContext&&!Be(r))return[new Ct(t.key,t.value,'\"feature-state\" data expressions are not supported with filters.')];if(t.expressionContext&&0===t.expressionContext.indexOf(\"cluster\")){if(!Ne(r,[\"zoom\",\"feature-state\"]))return[new Ct(t.key,t.value,'\"zoom\" and \"feature-state\" expressions are not supported with cluster properties.')];if(\"cluster-initial\"===t.expressionContext&&!Fe(r))return[new Ct(t.key,t.value,\"Feature data expressions are not supported with initial expression part of cluster properties.\")]}return[]}function nn(t){var e=t.key,r=t.value,n=t.valueSpec,i=[];return Array.isArray(n.values)?-1===n.values.indexOf(Ot(r))&&i.push(new Ct(e,r,\"expected one of [\"+n.values.join(\", \")+\"], 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on={type:\"boolean\",default:!1,transition:!1,\"property-type\":\"data-driven\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]}};function sn(t){if(null==t)return{filter:function(){return!0},needGeometry:!1};an(t)||(t=cn(t));var e=Wr(t,on);if(\"error\"===e.result)throw new Error(e.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return{filter:function(t,r,n){return e.value.evaluate(t,r,{},n)},needGeometry:function t(e){if(!Array.isArray(e))return!1;if(\"within\"===e[0])return!0;for(var r=1;r<e.length;r++)if(t(e[r]))return!0;return!1}(t)}}function ln(t,e){return t<e?-1:t>e?1:0}function cn(t){if(!t)return!0;var e,r=t[0];return t.length<=1?\"any\"!==r:\"==\"===r?un(t[1],t[2],\"==\"):\"!=\"===r?pn(un(t[1],t[2],\"==\")):\"<\"===r||\">\"===r||\"<=\"===r||\">=\"===r?un(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(cn))):\"all\"===r?[\"all\"].concat(t.slice(1).map(cn)):\"none\"===r?[\"all\"].concat(t.slice(1).map(cn).map(pn)):\"in\"===r?fn(t[1],t.slice(2)):\"!in\"===r?pn(fn(t[1],t.slice(2))):\"has\"===r?hn(t[1]):\"!has\"===r?pn(hn(t[1])):\"within\"!==r||t}function un(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function fn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(ln)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function hn(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function pn(t){return[\"!\",t]}function dn(t){return an(zt(t.value))?rn(It({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):function t(e){var r=e.value,n=e.key;if(\"array\"!==Fr(r))return[new Ct(n,r,\"array expected, \"+Fr(r)+\" found\")];var i,a=e.styleSpec,o=[];if(r.length<1)return[new Ct(n,r,\"filter array must have at least 1 element\")];switch(o=o.concat(nn({key:n+\"[0]\",value:r[0],valueSpec:a.filter_operator,style:e.style,styleSpec:e.styleSpec})),Ot(r[0])){case\"<\":case\"<=\":case\">\":case\">=\":r.length>=2&&\"$type\"===Ot(r[1])&&o.push(new Ct(n,r,'\"$type\" cannot be use with operator \"'+r[0]+'\"'));case\"==\":case\"!=\":3!==r.length&&o.push(new Ct(n,r,'filter array for operator \"'+r[0]+'\" must have 3 elements'));case\"in\":case\"!in\":r.length>=2&&\"string\"!==(i=Fr(r[1]))&&o.push(new Ct(n+\"[1]\",r[1],\"string expected, \"+i+\" 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r=t.key,n=t.style,i=t.styleSpec,a=t.value,o=t.objectKey,s=i[e+\"_\"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if(\"paint\"===e&&l&&s[l[1]]&&s[l[1]].transition)return kn({key:r,value:a,valueSpec:i.transition,style:n,styleSpec:i});var c,u=t.valueSpec||s[o];if(!u)return[new Ct(r,a,'unknown property \"'+o+'\"')];if(\"string\"===Fr(a)&&zr(u)&&!u.tokens&&(c=/^{([^}]+)}$/.exec(a)))return[new Ct(r,a,'\"'+o+'\" does not support interpolation syntax\\nUse an identity property function instead: `{ \"type\": \"identity\", \"property\": '+JSON.stringify(c[1])+\" }`.\")];var f=[];return\"symbol\"===t.layerType&&(\"text-field\"===o&&n&&!n.glyphs&&f.push(new Ct(r,a,'use of \"text-field\" requires a style \"glyphs\" property')),\"text-font\"===o&&Br(zt(a))&&\"identity\"===Ot(a.type)&&f.push(new Ct(r,a,'\"text-font\" does not support identity 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Qn(t,e){return!(!e&&Kn(t))&&!(t>=2304&&t<=3583||t>=3840&&t<=4255||Yn.Khmer(t))}function $n(t){for(var e=0,r=t;e<r.length;e+=1){if(Kn(r[e].charCodeAt(0)))return!0}return!1}var ti=\"deferred\",ei=\"loading\",ri=\"loaded\",ni=\"error\",ii=null,ai=\"unavailable\",oi=null,si=function(t){t&&\"string\"==typeof t&&t.indexOf(\"NetworkError\")>-1&&(ai=ni),ii&&ii(t)};function li(){ci.fire(new At(\"pluginStateChange\",{pluginStatus:ai,pluginURL:oi}))}var ci=new Et,ui=function(){return ai},fi=function(){if(ai!==ti||!oi)throw new Error(\"rtl-text-plugin cannot be downloaded unless a pluginURL is specified\");ai=ei,li(),oi&&xt({url:oi},(function(t){t?si(t):(ai=ri,li())}))},hi={applyArabicShaping:null,processBidirectionalText:null,processStyledBidirectionalText:null,isLoaded:function(){return ai===ri||null!=hi.applyArabicShaping},isLoading:function(){return ai===ei},setState:function(t){ai=t.pluginStatus,oi=t.pluginURL},isParsed:function(){return null!=hi.applyArabicShaping&&null!=hi.processBidirectionalText&&null!=hi.processStyledBidirectionalText},getPluginURL:function(){return oi}},pi=function(t,e){this.zoom=t,e?(this.now=e.now,this.fadeDuration=e.fadeDuration,this.zoomHistory=e.zoomHistory,this.transition=e.transition):(this.now=0,this.fadeDuration=0,this.zoomHistory=new Gn,this.transition={})};pi.prototype.isSupportedScript=function(t){return function(t,e){for(var r=0,n=t;r<n.length;r+=1){if(!Qn(n[r].charCodeAt(0),e))return!1}return!0}(t,hi.isLoaded())},pi.prototype.crossFadingFactor=function(){return 0===this.fadeDuration?1:Math.min((this.now-this.zoomHistory.lastIntegerZoomTime)/this.fadeDuration,1)},pi.prototype.getCrossfadeParameters=function(){var t=this.zoom,e=t-Math.floor(t),r=this.crossFadingFactor();return t>this.zoomHistory.lastIntegerZoom?{fromScale:2,toScale:1,t:e+(1-e)*r}:{fromScale:.5,toScale:1,t:1-(1-r)*e}};var di=function(t,e){this.property=t,this.value=e,this.expression=function(t,e){if(Br(t))return new Kr(t,e);if(Yr(t)){var r=Jr(t,e);if(\"error\"===r.result)throw new Error(r.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return r.value}var n=t;return\"string\"==typeof t&&\"color\"===e.type&&(n=te.parse(t)),{kind:\"constant\",evaluate:function(){return n}}}(void 0===e?t.specification.default:e,t.specification)};di.prototype.isDataDriven=function(){return\"source\"===this.expression.kind||\"composite\"===this.expression.kind},di.prototype.possiblyEvaluate=function(t,e,r){return this.property.possiblyEvaluate(this,t,e,r)};var mi=function(t){this.property=t,this.value=new di(t,void 0)};mi.prototype.transitioned=function(t,e){return new vi(this.property,this.value,e,u({},t.transition,this.transition),t.now)},mi.prototype.untransitioned=function(){return new vi(this.property,this.value,null,{},0)};var gi=function(t){this._properties=t,this._values=Object.create(t.defaultTransitionablePropertyValues)};gi.prototype.getValue=function(t){return x(this._values[t].value.value)},gi.prototype.setValue=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new mi(this._values[t].property)),this._values[t].value=new di(this._values[t].property,null===e?void 0:x(e))},gi.prototype.getTransition=function(t){return x(this._values[t].transition)},gi.prototype.setTransition=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new mi(this._values[t].property)),this._values[t].transition=x(e)||void 0},gi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i);var a=this.getTransition(n);void 0!==a&&(t[n+\"-transition\"]=a)}return t},gi.prototype.transitioned=function(t,e){for(var r=new yi(this._properties),n=0,i=Object.keys(this._values);n<i.length;n+=1){var a=i[n];r._values[a]=this._values[a].transitioned(t,e._values[a])}return r},gi.prototype.untransitioned=function(){for(var t=new yi(this._properties),e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e];t._values[n]=this._values[n].untransitioned()}return t};var vi=function(t,e,r,n,i){this.property=t,this.value=e,this.begin=i+n.delay||0,this.end=this.begin+n.duration||0,t.specification.transition&&(n.delay||n.duration)&&(this.prior=r)};vi.prototype.possiblyEvaluate=function(t,e,r){var n=t.now||0,i=this.value.possiblyEvaluate(t,e,r),a=this.prior;if(a){if(n>this.end)return this.prior=null,i;if(this.value.isDataDriven())return this.prior=null,i;if(n<this.begin)return a.possiblyEvaluate(t,e,r);var o=(n-this.begin)/(this.end-this.begin);return this.property.interpolate(a.possiblyEvaluate(t,e,r),i,function(t){if(t<=0)return 0;if(t>=1)return 1;var e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}(o))}return i};var yi=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};yi.prototype.possiblyEvaluate=function(t,e,r){for(var n=new _i(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n},yi.prototype.hasTransition=function(){for(var t=0,e=Object.keys(this._values);t<e.length;t+=1){var r=e[t];if(this._values[r].prior)return!0}return!1};var xi=function(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)};xi.prototype.getValue=function(t){return x(this._values[t].value)},xi.prototype.setValue=function(t,e){this._values[t]=new di(this._values[t].property,null===e?void 0:x(e))},xi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i)}return t},xi.prototype.possiblyEvaluate=function(t,e,r){for(var n=new _i(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n};var bi=function(t,e,r){this.property=t,this.value=e,this.parameters=r};bi.prototype.isConstant=function(){return\"constant\"===this.value.kind},bi.prototype.constantOr=function(t){return\"constant\"===this.value.kind?this.value.value:t},bi.prototype.evaluate=function(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)};var _i=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};_i.prototype.get=function(t){return this._values[t]};var wi=function(t){this.specification=t};wi.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},wi.prototype.interpolate=function(t,e,r){var n=Ge[this.specification.type];return n?n(t,e,r):t};var Ti=function(t,e){this.specification=t,this.overrides=e};Ti.prototype.possiblyEvaluate=function(t,e,r,n){return\"constant\"===t.expression.kind||\"camera\"===t.expression.kind?new bi(this,{kind:\"constant\",value:t.expression.evaluate(e,null,{},r,n)},e):new bi(this,t.expression,e)},Ti.prototype.interpolate=function(t,e,r){if(\"constant\"!==t.value.kind||\"constant\"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new bi(this,{kind:\"constant\",value:void 0},t.parameters);var n=Ge[this.specification.type];return n?new bi(this,{kind:\"constant\",value:n(t.value.value,e.value.value,r)},t.parameters):t},Ti.prototype.evaluate=function(t,e,r,n,i,a){return\"constant\"===t.kind?t.value:t.evaluate(e,r,n,i,a)};var ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0===t.value)return new bi(this,{kind:\"constant\",value:void 0},e);if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n),a=\"resolvedImage\"===t.property.specification.type&&\"string\"!=typeof i?i.name:i,o=this._calculate(a,a,a,e);return new bi(this,{kind:\"constant\",value:o},e)}if(\"camera\"===t.expression.kind){var s=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new bi(this,{kind:\"constant\",value:s},e)}return new bi(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n,i,a){if(\"source\"===t.kind){var o=t.evaluate(e,r,n,i,a);return this._calculate(o,o,o,e)}return\"composite\"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(Ti),Mi=function(t){this.specification=t};Mi.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return this._calculate(i,i,i,e)}return this._calculate(t.expression.evaluate(new pi(Math.floor(e.zoom-1),e)),t.expression.evaluate(new pi(Math.floor(e.zoom),e)),t.expression.evaluate(new pi(Math.floor(e.zoom+1),e)),e)}},Mi.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},Mi.prototype.interpolate=function(t){return t};var Ai=function(t){this.specification=t};Ai.prototype.possiblyEvaluate=function(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)},Ai.prototype.interpolate=function(){return!1};var Si=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new di(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new mi(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};Nn(\"DataDrivenProperty\",Ti),Nn(\"DataConstantProperty\",wi),Nn(\"CrossFadedDataDrivenProperty\",ki),Nn(\"CrossFadedProperty\",Mi),Nn(\"ColorRampProperty\",Ai);var Ei=function(t){function e(e,r){if(t.call(this),this.id=e.id,this.type=e.type,this._featureFilter={filter:function(){return!0},needGeometry:!1},\"custom\"!==e.type&&(e=e,this.metadata=e.metadata,this.minzoom=e.minzoom,this.maxzoom=e.maxzoom,\"background\"!==e.type&&(this.source=e.source,this.sourceLayer=e[\"source-layer\"],this.filter=e.filter),r.layout&&(this._unevaluatedLayout=new xi(r.layout)),r.paint)){for(var n in this._transitionablePaint=new gi(r.paint),e.paint)this.setPaintProperty(n,e.paint[n],{validate:!1});for(var i in e.layout)this.setLayoutProperty(i,e.layout[i],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new _i(r.paint)}}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return\"visibility\"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".layout.\"+t;if(this._validate(In,n,t,e,r))return}\"visibility\"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e},e.prototype.getPaintProperty=function(t){return g(t,\"-transition\")?this._transitionablePaint.getTransition(t.slice(0,-\"-transition\".length)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".paint.\"+t;if(this._validate(Pn,n,t,e,r))return!1}if(g(t,\"-transition\"))return this._transitionablePaint.setTransition(t.slice(0,-\"-transition\".length),e||void 0),!1;var i=this._transitionablePaint._values[t],a=\"cross-faded-data-driven\"===i.property.specification[\"property-type\"],o=i.value.isDataDriven(),s=i.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var l=this._transitionablePaint._values[t].value;return l.isDataDriven()||o||a||this._handleOverridablePaintPropertyUpdate(t,s,l)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||(!!(this.maxzoom&&t>=this.maxzoom)||\"none\"===this.visibility)},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),y(t,(function(t,e){return!(void 0===t||\"layout\"===e&&!Object.keys(t).length||\"paint\"===e&&!Object.keys(t).length)}))},e.prototype._validate=function(t,e,r,n,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&On(this,t.call(Ln,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:Lt,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof bi&&zr(e.property.specification)&&((\"source\"===e.value.kind||\"composite\"===e.value.kind)&&e.value.isStateDependent))return!0}return!1},e}(Et),Li={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},Ci=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},Pi=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function Ii(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map((function(t){var i,a=(i=t.type,Li[i].BYTES_PER_ELEMENT),o=r=Oi(r,Math.max(e,a)),s=t.components||1;return n=Math.max(n,a),r+=a*s,{name:t.name,type:t.type,components:s,offset:o}})),size:Oi(r,Math.max(n,e)),alignment:e}}function Oi(t,e){return Math.ceil(t/e)*e}Pi.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},Pi.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},Pi.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},Pi.prototype.clear=function(){this.length=0},Pi.prototype.resize=function(t){this.reserve(t),this.length=t},Pi.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},Pi.prototype._refreshViews=function(){throw new Error(\"_refreshViews() must be implemented by each concrete StructArray layout\")};var zi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t},e}(Pi);zi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout2i4\",zi);var Di=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.int16[a+0]=e,this.int16[a+1]=r,this.int16[a+2]=n,this.int16[a+3]=i,t},e}(Pi);Di.prototype.bytesPerElement=8,Nn(\"StructArrayLayout4i8\",Di);var Ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Pi);Ri.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2i4i12\",Ri);var Fi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=i,this.uint8[l+6]=a,this.uint8[l+7]=o,t},e}(Pi);Fi.prototype.bytesPerElement=8,Nn(\"StructArrayLayout2i4ub8\",Fi);var Bi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c){var u=this.length;return this.resize(u+1),this.emplace(u,t,e,r,n,i,a,o,s,l,c)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u){var f=9*t,h=18*t;return this.uint16[f+0]=e,this.uint16[f+1]=r,this.uint16[f+2]=n,this.uint16[f+3]=i,this.uint16[f+4]=a,this.uint16[f+5]=o,this.uint16[f+6]=s,this.uint16[f+7]=l,this.uint8[h+16]=c,this.uint8[h+17]=u,t},e}(Pi);Bi.prototype.bytesPerElement=18,Nn(\"StructArrayLayout8ui2ub18\",Bi);var Ni=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f){var h=this.length;return this.resize(h+1),this.emplace(h,t,e,r,n,i,a,o,s,l,c,u,f)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h){var p=12*t;return this.int16[p+0]=e,this.int16[p+1]=r,this.int16[p+2]=n,this.int16[p+3]=i,this.uint16[p+4]=a,this.uint16[p+5]=o,this.uint16[p+6]=s,this.uint16[p+7]=l,this.int16[p+8]=c,this.int16[p+9]=u,this.int16[p+10]=f,this.int16[p+11]=h,t},e}(Pi);Ni.prototype.bytesPerElement=24,Nn(\"StructArrayLayout4i4ui4i24\",Ni);var ji=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.float32[i+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,t},e}(Pi);ji.prototype.bytesPerElement=12,Nn(\"StructArrayLayout3f12\",ji);var Ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint32[r+0]=e,t},e}(Pi);Ui.prototype.bytesPerElement=4,Nn(\"StructArrayLayout1ul4\",Ui);var Vi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l){var c=this.length;return this.resize(c+1),this.emplace(c,t,e,r,n,i,a,o,s,l)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c){var u=10*t,f=5*t;return this.int16[u+0]=e,this.int16[u+1]=r,this.int16[u+2]=n,this.int16[u+3]=i,this.int16[u+4]=a,this.int16[u+5]=o,this.uint32[f+3]=s,this.uint16[u+8]=l,this.uint16[u+9]=c,t},e}(Pi);Vi.prototype.bytesPerElement=20,Nn(\"StructArrayLayout6i1ul2ui20\",Vi);var qi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Pi);qi.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2i2i2i12\",qi);var Hi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n,i)},e.prototype.emplace=function(t,e,r,n,i,a){var o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=i,this.int16[s+7]=a,t},e}(Pi);Hi.prototype.bytesPerElement=16,Nn(\"StructArrayLayout2f1f2i16\",Hi);var Gi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=12*t,o=3*t;return this.uint8[a+0]=e,this.uint8[a+1]=r,this.float32[o+1]=n,this.float32[o+2]=i,t},e}(Pi);Gi.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2ub2f12\",Gi);var Yi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.uint16[i+0]=e,this.uint16[i+1]=r,this.uint16[i+2]=n,t},e}(Pi);Yi.prototype.bytesPerElement=6,Nn(\"StructArrayLayout3ui6\",Yi);var Wi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g){var v=this.length;return this.resize(v+1),this.emplace(v,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v){var y=24*t,x=12*t,b=48*t;return this.int16[y+0]=e,this.int16[y+1]=r,this.uint16[y+2]=n,this.uint16[y+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[y+10]=l,this.uint16[y+11]=c,this.uint16[y+12]=u,this.float32[x+7]=f,this.float32[x+8]=h,this.uint8[b+36]=p,this.uint8[b+37]=d,this.uint8[b+38]=m,this.uint32[x+10]=g,this.int16[y+22]=v,t},e}(Pi);Wi.prototype.bytesPerElement=48,Nn(\"StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48\",Wi);var Xi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,w,T,k,M,A,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,w,T,k,M,A,S)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,w,T,k,M,A,S,E){var L=34*t,C=17*t;return this.int16[L+0]=e,this.int16[L+1]=r,this.int16[L+2]=n,this.int16[L+3]=i,this.int16[L+4]=a,this.int16[L+5]=o,this.int16[L+6]=s,this.int16[L+7]=l,this.uint16[L+8]=c,this.uint16[L+9]=u,this.uint16[L+10]=f,this.uint16[L+11]=h,this.uint16[L+12]=p,this.uint16[L+13]=d,this.uint16[L+14]=m,this.uint16[L+15]=g,this.uint16[L+16]=v,this.uint16[L+17]=y,this.uint16[L+18]=x,this.uint16[L+19]=b,this.uint16[L+20]=_,this.uint16[L+21]=w,this.uint16[L+22]=T,this.uint32[C+12]=k,this.float32[C+13]=M,this.float32[C+14]=A,this.float32[C+15]=S,this.float32[C+16]=E,t},e}(Pi);Xi.prototype.bytesPerElement=68,Nn(\"StructArrayLayout8i15ui1ul4f68\",Xi);var Zi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.float32[r+0]=e,t},e}(Pi);Zi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout1f4\",Zi);var Ji=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,t},e}(Pi);Ji.prototype.bytesPerElement=6,Nn(\"StructArrayLayout3i6\",Ji);var Ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=2*t,a=4*t;return this.uint32[i+0]=e,this.uint16[a+2]=r,this.uint16[a+3]=n,t},e}(Pi);Ki.prototype.bytesPerElement=8,Nn(\"StructArrayLayout1ul2ui8\",Ki);var Qi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.uint16[n+0]=e,this.uint16[n+1]=r,t},e}(Pi);Qi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout2ui4\",Qi);var $i=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint16[r+0]=e,t},e}(Pi);$i.prototype.bytesPerElement=2,Nn(\"StructArrayLayout1ui2\",$i);var ta=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.float32[n+0]=e,this.float32[n+1]=r,t},e}(Pi);ta.prototype.bytesPerElement=8,Nn(\"StructArrayLayout2f8\",ta);var ea=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,this.float32[a+3]=i,t},e}(Pi);ea.prototype.bytesPerElement=16,Nn(\"StructArrayLayout4f16\",ea);var ra=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.y2.get=function(){return this._structArray.int16[this._pos2+5]},r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.anchorPoint.get=function(){return new i(this.anchorPointX,this.anchorPointY)},Object.defineProperties(e.prototype,r),e}(Ci);ra.prototype.size=20;var na=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new ra(this,t)},e}(Vi);Nn(\"CollisionBoxArray\",na);var ia=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},glyphStartIndex:{configurable:!0},numGlyphs:{configurable:!0},vertexStartIndex:{configurable:!0},lineStartIndex:{configurable:!0},lineLength:{configurable:!0},segment:{configurable:!0},lowerSize:{configurable:!0},upperSize:{configurable:!0},lineOffsetX:{configurable:!0},lineOffsetY:{configurable:!0},writingMode:{configurable:!0},placedOrientation:{configurable:!0},hidden:{configurable:!0},crossTileID:{configurable:!0},associatedIconIndex:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.glyphStartIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.numGlyphs.get=function(){return this._structArray.uint16[this._pos2+3]},r.vertexStartIndex.get=function(){return this._structArray.uint32[this._pos4+2]},r.lineStartIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.lineLength.get=function(){return this._structArray.uint32[this._pos4+4]},r.segment.get=function(){return this._structArray.uint16[this._pos2+10]},r.lowerSize.get=function(){return this._structArray.uint16[this._pos2+11]},r.upperSize.get=function(){return this._structArray.uint16[this._pos2+12]},r.lineOffsetX.get=function(){return this._structArray.float32[this._pos4+7]},r.lineOffsetY.get=function(){return this._structArray.float32[this._pos4+8]},r.writingMode.get=function(){return this._structArray.uint8[this._pos1+36]},r.placedOrientation.get=function(){return this._structArray.uint8[this._pos1+37]},r.placedOrientation.set=function(t){this._structArray.uint8[this._pos1+37]=t},r.hidden.get=function(){return this._structArray.uint8[this._pos1+38]},r.hidden.set=function(t){this._structArray.uint8[this._pos1+38]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},r.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(e.prototype,r),e}(Ci);ia.prototype.size=48;var aa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new ia(this,t)},e}(Wi);Nn(\"PlacedSymbolArray\",aa);var oa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},rightJustifiedTextSymbolIndex:{configurable:!0},centerJustifiedTextSymbolIndex:{configurable:!0},leftJustifiedTextSymbolIndex:{configurable:!0},verticalPlacedTextSymbolIndex:{configurable:!0},placedIconSymbolIndex:{configurable:!0},verticalPlacedIconSymbolIndex:{configurable:!0},key:{configurable:!0},textBoxStartIndex:{configurable:!0},textBoxEndIndex:{configurable:!0},verticalTextBoxStartIndex:{configurable:!0},verticalTextBoxEndIndex:{configurable:!0},iconBoxStartIndex:{configurable:!0},iconBoxEndIndex:{configurable:!0},verticalIconBoxStartIndex:{configurable:!0},verticalIconBoxEndIndex:{configurable:!0},featureIndex:{configurable:!0},numHorizontalGlyphVertices:{configurable:!0},numVerticalGlyphVertices:{configurable:!0},numIconVertices:{configurable:!0},numVerticalIconVertices:{configurable:!0},useRuntimeCollisionCircles:{configurable:!0},crossTileID:{configurable:!0},textBoxScale:{configurable:!0},textOffset0:{configurable:!0},textOffset1:{configurable:!0},collisionCircleDiameter:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},r.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},r.key.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+11]},r.verticalTextBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+12]},r.iconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+13]},r.iconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+14]},r.verticalIconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+15]},r.verticalIconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+16]},r.featureIndex.get=function(){return this._structArray.uint16[this._pos2+17]},r.numHorizontalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+18]},r.numVerticalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+19]},r.numIconVertices.get=function(){return this._structArray.uint16[this._pos2+20]},r.numVerticalIconVertices.get=function(){return this._structArray.uint16[this._pos2+21]},r.useRuntimeCollisionCircles.get=function(){return 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c=t.readVarint();n=7&c,a=c>>3}if(a--,1===n||2===n)o+=t.readSVarint(),s+=t.readSVarint(),1===n&&(e&&l.push(e),e=[]),e.push(new i(o,s));else{if(7!==n)throw new Error(\"unknown command \"+n);e&&e.push(e[0].clone())}}return e&&l.push(e),l},ws.prototype.bbox=function(){var t=this._pbf;t.pos=this._geometry;for(var e=t.readVarint()+t.pos,r=1,n=0,i=0,a=0,o=1/0,s=-1/0,l=1/0,c=-1/0;t.pos<e;){if(n<=0){var u=t.readVarint();r=7&u,n=u>>3}if(n--,1===r||2===r)(i+=t.readSVarint())<o&&(o=i),i>s&&(s=i),(a+=t.readSVarint())<l&&(l=a),a>c&&(c=a);else if(7!==r)throw new Error(\"unknown command \"+r)}return[o,l,s,c]},ws.prototype.toGeoJSON=function(t,e,r){var n,i,a=this.extent*Math.pow(2,r),o=this.extent*t,s=this.extent*e,l=this.loadGeometry(),c=ws.types[this.type];function u(t){for(var e=0;e<t.length;e++){var r=t[e],n=180-360*(r.y+s)/a;t[e]=[360*(r.x+o)/a-180,360/Math.PI*Math.atan(Math.exp(n*Math.PI/180))-90]}}switch(this.type){case 1:var f=[];for(n=0;n<l.length;n++)f[n]=l[n][0];u(l=f);break;case 2:for(n=0;n<l.length;n++)u(l[n]);break;case 3:for(l=function(t){var e=t.length;if(e<=1)return[t];for(var r,n,i=[],a=0;a<e;a++){var o=ks(t[a]);0!==o&&(void 0===n&&(n=o<0),n===o<0?(r&&i.push(r),r=[t[a]]):r.push(t[a]))}r&&i.push(r);return i}(l),n=0;n<l.length;n++)for(i=0;i<l[n].length;i++)u(l[n][i])}1===l.length?l=l[0]:c=\"Multi\"+c;var h={type:\"Feature\",geometry:{type:c,coordinates:l},properties:this.properties};return\"id\"in this&&(h.id=this.id),h};var Ms=As;function As(t,e){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=t,this._keys=[],this._values=[],this._features=[],t.readFields(Ss,this,e),this.length=this._features.length}function Ss(t,e,r){15===t?e.version=r.readVarint():1===t?e.name=r.readString():5===t?e.extent=r.readVarint():2===t?e._features.push(r.pos):3===t?e._keys.push(r.readString()):4===t&&e._values.push(function(t){var e=null,r=t.readVarint()+t.pos;for(;t.pos<r;){var n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function Es(t,e,r){if(3===t){var n=new Ms(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}As.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error(\"feature index out of bounds\");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new _s(this._pbf,e,this.extent,this._keys,this._values)};var Ls={VectorTile:function(t,e){this.layers=t.readFields(Es,{},e)},VectorTileFeature:_s,VectorTileLayer:Ms},Cs=Ls.VectorTileFeature.types,Ps=Math.pow(2,13);function Is(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,2*Math.floor(n*Ps)+o,i*Ps*2,a*Ps*2,Math.round(s))}var Os=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new Ri,this.indexArray=new Yi,this.programConfigurations=new Ua(bs,t.layers,t.zoom),this.segments=new pa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function zs(t,e){return t.x===e.x&&(t.x<0||t.x>8192)||t.y===e.y&&(t.y<0||t.y>8192)}function Ds(t){return t.every((function(t){return t.x<0}))||t.every((function(t){return t.x>8192}))||t.every((function(t){return t.y<0}))||t.every((function(t){return t.y>8192}))}Os.prototype.populate=function(t,e,r){this.features=[],this.hasPattern=ds(\"fill-extrusion\",this.layers,e);for(var n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.feature,s=a.id,l=a.index,c=a.sourceLayerIndex,u=this.layers[0]._featureFilter.needGeometry,f={type:o.type,id:s,properties:o.properties,geometry:u?Ya(o):[]};if(this.layers[0]._featureFilter.filter(new pi(this.zoom),f,r)){var h={id:s,sourceLayerIndex:c,index:l,geometry:u?f.geometry:Ya(o),properties:o.properties,type:o.type,patterns:{}};void 0!==o.id&&(h.id=o.id),this.hasPattern?this.features.push(ms(\"fill-extrusion\",this.layers,h,this.zoom,e)):this.addFeature(h,h.geometry,l,r,{}),e.featureIndex.insert(o,h.geometry,l,c,this.index,!0)}}},Os.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.features;n<i.length;n+=1){var a=i[n],o=a.geometry;this.addFeature(a,o,a.index,e,r)}},Os.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Os.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Os.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Os.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,bs),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Os.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Os.prototype.addFeature=function(t,e,r,n,i){for(var a=0,o=hs(e,500);a<o.length;a+=1){for(var s=o[a],l=0,c=0,u=s;c<u.length;c+=1){l+=u[c].length}for(var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),h=0,p=s;h<p.length;h+=1){var d=p[h];if(0!==d.length&&!Ds(d))for(var m=0,g=0;g<d.length;g++){var v=d[g];if(g>=1){var y=d[g-1];if(!zs(v,y)){f.vertexLength+4>pa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var x=v.sub(y)._perp()._unit(),b=y.dist(v);m+b>32768&&(m=0),Is(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,0,m),Is(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,1,m),m+=b,Is(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,0,m),Is(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,1,m);var _=f.vertexLength;this.indexArray.emplaceBack(_,_+2,_+1),this.indexArray.emplaceBack(_+1,_+2,_+3),f.vertexLength+=4,f.primitiveLength+=2}}}}if(f.vertexLength+l>pa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(l,this.layoutVertexArray,this.indexArray)),\"Polygon\"===Cs[t.type]){for(var w=[],T=[],k=f.vertexLength,M=0,A=s;M<A.length;M+=1){var S=A[M];if(0!==S.length){S!==s[0]&&T.push(w.length/2);for(var E=0;E<S.length;E++){var L=S[E];Is(this.layoutVertexArray,L.x,L.y,0,0,1,1,0),w.push(L.x),w.push(L.y)}}}for(var C=Do(w,T),P=0;P<C.length;P+=3)this.indexArray.emplaceBack(k+C[P],k+C[P+2],k+C[P+1]);f.primitiveLength+=C.length/3,f.vertexLength+=l}}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},Nn(\"FillExtrusionBucket\",Os,{omit:[\"layers\",\"features\"]});var Rs={paint:new Si({\"fill-extrusion-opacity\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-opacity\"]),\"fill-extrusion-color\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-color\"]),\"fill-extrusion-translate\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-translate\"]),\"fill-extrusion-translate-anchor\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-translate-anchor\"]),\"fill-extrusion-pattern\":new ki(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-pattern\"]),\"fill-extrusion-height\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-height\"]),\"fill-extrusion-base\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-base\"]),\"fill-extrusion-vertical-gradient\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-vertical-gradient\"])})},Fs=function(t){function e(e){t.call(this,e,Rs)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.createBucket=function(t){return new Os(t)},e.prototype.queryRadius=function(){return so(this.paint.get(\"fill-extrusion-translate\"))},e.prototype.is3D=function(){return!0},e.prototype.queryIntersectsFeature=function(t,e,r,n,a,o,s,l){var c=lo(t,this.paint.get(\"fill-extrusion-translate\"),this.paint.get(\"fill-extrusion-translate-anchor\"),o.angle,s),u=this.paint.get(\"fill-extrusion-height\").evaluate(e,r),f=this.paint.get(\"fill-extrusion-base\").evaluate(e,r),h=function(t,e,r,n){for(var a=[],o=0,s=t;o<s.length;o+=1){var l=s[o],c=[l.x,l.y,n,1];xo(c,c,e),a.push(new i(c[0]/c[3],c[1]/c[3]))}return a}(c,l,0,0),p=function(t,e,r,n){for(var a=[],o=[],s=n[8]*e,l=n[9]*e,c=n[10]*e,u=n[11]*e,f=n[8]*r,h=n[9]*r,p=n[10]*r,d=n[11]*r,m=0,g=t;m<g.length;m+=1){for(var v=g[m],y=[],x=[],b=0,_=v;b<_.length;b+=1){var w=_[b],T=w.x,k=w.y,M=n[0]*T+n[4]*k+n[12],A=n[1]*T+n[5]*k+n[13],S=n[2]*T+n[6]*k+n[14],E=n[3]*T+n[7]*k+n[15],L=S+c,C=E+u,P=M+f,I=A+h,O=S+p,z=E+d,D=new i((M+s)/C,(A+l)/C);D.z=L/C,y.push(D);var R=new i(P/z,I/z);R.z=O/z,x.push(R)}a.push(y),o.push(x)}return[a,o]}(n,f,u,l);return function(t,e,r){var n=1/0;Ka(r,e)&&(n=Ns(r,e[0]));for(var i=0;i<e.length;i++)for(var a=e[i],o=t[i],s=0;s<a.length-1;s++){var l=a[s],c=a[s+1],u=o[s],f=o[s+1],h=[l,c,f,u,l];Za(r,h)&&(n=Math.min(n,Ns(r,h)))}return n!==1/0&&n}(p[0],p[1],h)},e}(Ei);function Bs(t,e){return t.x*e.x+t.y*e.y}function Ns(t,e){if(1===t.length){for(var r,n=0,i=e[n++];!r||i.equals(r);)if(!(r=e[n++]))return 1/0;for(;n<e.length;n++){var a=e[n],o=t[0],s=r.sub(i),l=a.sub(i),c=o.sub(i),u=Bs(s,s),f=Bs(s,l),h=Bs(l,l),p=Bs(c,s),d=Bs(c,l),m=u*h-f*f,g=(h*p-f*d)/m,v=(u*d-f*p)/m,y=1-g-v,x=i.z*y+r.z*g+a.z*v;if(isFinite(x))return x}return 1/0}for(var b=1/0,_=0,w=e;_<w.length;_+=1){var T=w[_];b=Math.min(b,T.z)}return b}var js=Ii([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4).members,Us=Ls.VectorTileFeature.types,Vs=Math.cos(Math.PI/180*37.5),qs=Math.pow(2,14)/.5,Hs=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new Fi,this.indexArray=new Yi,this.programConfigurations=new Ua(js,t.layers,t.zoom),this.segments=new pa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};Hs.prototype.populate=function(t,e,r){this.hasPattern=ds(\"line\",this.layers,e);for(var n=this.layers[0].layout.get(\"line-sort-key\"),i=[],a=0,o=t;a<o.length;a+=1){var s=o[a],l=s.feature,c=s.id,u=s.index,f=s.sourceLayerIndex,h=this.layers[0]._featureFilter.needGeometry,p={type:l.type,id:c,properties:l.properties,geometry:h?Ya(l):[]};if(this.layers[0]._featureFilter.filter(new pi(this.zoom),p,r)){h||(p.geometry=Ya(l));var d=n?n.evaluate(p,{},r):void 0,m={id:c,properties:l.properties,type:l.type,sourceLayerIndex:f,index:u,geometry:p.geometry,patterns:{},sortKey:d};i.push(m)}}n&&i.sort((function(t,e){return t.sortKey-e.sortKey}));for(var g=0,v=i;g<v.length;g+=1){var y=v[g],x=y,b=x.geometry,_=x.index,w=x.sourceLayerIndex;if(this.hasPattern){var T=ms(\"line\",this.layers,y,this.zoom,e);this.patternFeatures.push(T)}else this.addFeature(y,b,_,r,{});var k=t[_].feature;e.featureIndex.insert(k,b,_,w,this.index)}},Hs.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Hs.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.patternFeatures;n<i.length;n+=1){var a=i[n];this.addFeature(a,a.geometry,a.index,e,r)}},Hs.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Hs.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Hs.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,js),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Hs.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Hs.prototype.addFeature=function(t,e,r,n,i){for(var a=this.layers[0].layout,o=a.get(\"line-join\").evaluate(t,{}),s=a.get(\"line-cap\"),l=a.get(\"line-miter-limit\"),c=a.get(\"line-round-limit\"),u=0,f=e;u<f.length;u+=1){var h=f[u];this.addLine(h,t,o,s,l,c)}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},Hs.prototype.addLine=function(t,e,r,n,i,a){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,e.properties&&e.properties.hasOwnProperty(\"mapbox_clip_start\")&&e.properties.hasOwnProperty(\"mapbox_clip_end\")){this.clipStart=+e.properties.mapbox_clip_start,this.clipEnd=+e.properties.mapbox_clip_end;for(var o=0;o<t.length-1;o++)this.totalDistance+=t[o].dist(t[o+1]);this.updateScaledDistance()}for(var s=\"Polygon\"===Us[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var c=0;c<l-1&&t[c].equals(t[c+1]);)c++;if(!(l<(s?3:2))){\"bevel\"===r&&(i=1.05);var u,f=this.overscaling<=16?122880/(512*this.overscaling):0,h=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray),p=void 0,d=void 0,m=void 0,g=void 0;this.e1=this.e2=-1,s&&(u=t[l-2],g=t[c].sub(u)._unit()._perp());for(var v=c;v<l;v++)if(!(d=v===l-1?s?t[c+1]:void 0:t[v+1])||!t[v].equals(d)){g&&(m=g),u&&(p=u),u=t[v],g=d?d.sub(u)._unit()._perp():m;var y=(m=m||g).add(g);0===y.x&&0===y.y||y._unit();var x=m.x*g.x+m.y*g.y,b=y.x*g.x+y.y*g.y,_=0!==b?1/b:1/0,w=2*Math.sqrt(2-2*b),T=b<Vs&&p&&d,k=m.x*g.y-m.y*g.x>0;if(T&&v>c){var M=u.dist(p);if(M>2*f){var A=u.sub(u.sub(p)._mult(f/M)._round());this.updateDistance(p,A),this.addCurrentVertex(A,m,0,0,h),p=A}}var S=p&&d,E=S?r:s?\"butt\":n;if(S&&\"round\"===E&&(_<a?E=\"miter\":_<=2&&(E=\"fakeround\")),\"miter\"===E&&_>i&&(E=\"bevel\"),\"bevel\"===E&&(_>2&&(E=\"flipbevel\"),_<i&&(E=\"miter\")),p&&this.updateDistance(p,u),\"miter\"===E)y._mult(_),this.addCurrentVertex(u,y,0,0,h);else if(\"flipbevel\"===E){if(_>100)y=g.mult(-1);else{var L=_*m.add(g).mag()/m.sub(g).mag();y._perp()._mult(L*(k?-1:1))}this.addCurrentVertex(u,y,0,0,h),this.addCurrentVertex(u,y.mult(-1),0,0,h)}else if(\"bevel\"===E||\"fakeround\"===E){var C=-Math.sqrt(_*_-1),P=k?C:0,I=k?0:C;if(p&&this.addCurrentVertex(u,m,P,I,h),\"fakeround\"===E)for(var O=Math.round(180*w/Math.PI/20),z=1;z<O;z++){var D=z/O;if(.5!==D){var R=D-.5;D+=D*R*(D-1)*((1.0904+x*(x*(3.55645-1.43519*x)-3.2452))*R*R+(.848013+x*(.215638*x-1.06021)))}var F=g.sub(m)._mult(D)._add(m)._unit()._mult(k?-1:1);this.addHalfVertex(u,F.x,F.y,!1,k,0,h)}d&&this.addCurrentVertex(u,g,-P,-I,h)}else if(\"butt\"===E)this.addCurrentVertex(u,y,0,0,h);else if(\"square\"===E){var B=p?1:-1;this.addCurrentVertex(u,y,B,B,h)}else\"round\"===E&&(p&&(this.addCurrentVertex(u,m,0,0,h),this.addCurrentVertex(u,m,1,1,h,!0)),d&&(this.addCurrentVertex(u,g,-1,-1,h,!0),this.addCurrentVertex(u,g,0,0,h)));if(T&&v<l-1){var N=u.dist(d);if(N>2*f){var j=u.add(d.sub(u)._mult(f/N)._round());this.updateDistance(u,j),this.addCurrentVertex(j,g,0,0,h),u=j}}}}},Hs.prototype.addCurrentVertex=function(t,e,r,n,i,a){void 0===a&&(a=!1);var o=e.x+e.y*r,s=e.y-e.x*r,l=-e.x+e.y*n,c=-e.y-e.x*n;this.addHalfVertex(t,o,s,a,!1,r,i),this.addHalfVertex(t,l,c,a,!0,-n,i),this.distance>qs/2&&0===this.totalDistance&&(this.distance=0,this.addCurrentVertex(t,e,r,n,i,a))},Hs.prototype.addHalfVertex=function(t,e,r,n,i,a,o){var s=t.x,l=t.y,c=.5*this.scaledDistance;this.layoutVertexArray.emplaceBack((s<<1)+(n?1:0),(l<<1)+(i?1:0),Math.round(63*e)+128,Math.round(63*r)+128,1+(0===a?0:a<0?-1:1)|(63&c)<<2,c>>6);var u=o.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,u),o.primitiveLength++),i?this.e2=u:this.e1=u},Hs.prototype.updateScaledDistance=function(){this.scaledDistance=this.totalDistance>0?(this.clipStart+(this.clipEnd-this.clipStart)*this.distance/this.totalDistance)*(qs-1):this.distance},Hs.prototype.updateDistance=function(t,e){this.distance+=t.dist(e),this.updateScaledDistance()},Nn(\"LineBucket\",Hs,{omit:[\"layers\",\"patternFeatures\"]});var Gs=new Si({\"line-cap\":new wi(Lt.layout_line[\"line-cap\"]),\"line-join\":new Ti(Lt.layout_line[\"line-join\"]),\"line-miter-limit\":new wi(Lt.layout_line[\"line-miter-limit\"]),\"line-round-limit\":new wi(Lt.layout_line[\"line-round-limit\"]),\"line-sort-key\":new Ti(Lt.layout_line[\"line-sort-key\"])}),Ys={paint:new Si({\"line-opacity\":new Ti(Lt.paint_line[\"line-opacity\"]),\"line-color\":new Ti(Lt.paint_line[\"line-color\"]),\"line-translate\":new wi(Lt.paint_line[\"line-translate\"]),\"line-translate-anchor\":new wi(Lt.paint_line[\"line-translate-anchor\"]),\"line-width\":new Ti(Lt.paint_line[\"line-width\"]),\"line-gap-width\":new Ti(Lt.paint_line[\"line-gap-width\"]),\"line-offset\":new Ti(Lt.paint_line[\"line-offset\"]),\"line-blur\":new Ti(Lt.paint_line[\"line-blur\"]),\"line-dasharray\":new Mi(Lt.paint_line[\"line-dasharray\"]),\"line-pattern\":new ki(Lt.paint_line[\"line-pattern\"]),\"line-gradient\":new Ai(Lt.paint_line[\"line-gradient\"])}),layout:Gs},Ws=new(function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(e,r){return r=new pi(Math.floor(r.zoom),{now:r.now,fadeDuration:r.fadeDuration,zoomHistory:r.zoomHistory,transition:r.transition}),t.prototype.possiblyEvaluate.call(this,e,r)},e.prototype.evaluate=function(e,r,n,i){return r=u({},r,{zoom:Math.floor(r.zoom)}),t.prototype.evaluate.call(this,e,r,n,i)},e}(Ti))(Ys.paint.properties[\"line-width\"].specification);Ws.useIntegerZoom=!0;var Xs=function(t){function e(e){t.call(this,e,Ys)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._handleSpecialPaintPropertyUpdate=function(t){\"line-gradient\"===t&&this._updateGradient()},e.prototype._updateGradient=function(){var t=this._transitionablePaint._values[\"line-gradient\"].value.expression;this.gradient=Co(t,\"lineProgress\"),this.gradientTexture=null},e.prototype.recalculate=function(e,r){t.prototype.recalculate.call(this,e,r),this.paint._values[\"line-floorwidth\"]=Ws.possiblyEvaluate(this._transitioningPaint._values[\"line-width\"].value,e)},e.prototype.createBucket=function(t){return new Hs(t)},e.prototype.queryRadius=function(t){var e=t,r=Zs(oo(\"line-width\",this,e),oo(\"line-gap-width\",this,e)),n=oo(\"line-offset\",this,e);return r/2+Math.abs(n)+so(this.paint.get(\"line-translate\"))},e.prototype.queryIntersectsFeature=function(t,e,r,n,a,o,s){var l=lo(t,this.paint.get(\"line-translate\"),this.paint.get(\"line-translate-anchor\"),o.angle,s),c=s/2*Zs(this.paint.get(\"line-width\").evaluate(e,r),this.paint.get(\"line-gap-width\").evaluate(e,r)),u=this.paint.get(\"line-offset\").evaluate(e,r);return u&&(n=function(t,e){for(var r=[],n=new i(0,0),a=0;a<t.length;a++){for(var o=t[a],s=[],l=0;l<o.length;l++){var c=o[l-1],u=o[l],f=o[l+1],h=0===l?n:u.sub(c)._unit()._perp(),p=l===o.length-1?n:f.sub(u)._unit()._perp(),d=h._add(p)._unit(),m=d.x*p.x+d.y*p.y;d._mult(1/m),s.push(d._mult(e)._add(u))}r.push(s)}return r}(n,u*s)),function(t,e,r){for(var n=0;n<e.length;n++){var i=e[n];if(t.length>=3)for(var a=0;a<i.length;a++)if(io(t,i[a]))return!0;if(Qa(t,i,r))return!0}return!1}(l,n,c)},e.prototype.isTileClipped=function(){return!0},e}(Ei);function Zs(t,e){return e>0?e+2*t:t}var 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el(t,e,r){return t.sections.forEach((function(t){t.text=function(t,e,r){var n=e.layout.get(\"text-transform\").evaluate(r,{});return\"uppercase\"===n?t=t.toLocaleUpperCase():\"lowercase\"===n&&(t=t.toLocaleLowerCase()),hi.applyArabicShaping&&(t=hi.applyArabicShaping(t)),t}(t.text,e,r)})),t}var 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nl=function(t,e,r,n,i){var a,o,s=8*i-n-1,l=(1<<s)-1,c=l>>1,u=-7,f=r?i-1:0,h=r?-1:1,p=t[e+f];for(f+=h,a=p&(1<<-u)-1,p>>=-u,u+=s;u>0;a=256*a+t[e+f],f+=h,u-=8);for(o=a&(1<<-u)-1,a>>=-u,u+=n;u>0;o=256*o+t[e+f],f+=h,u-=8);if(0===a)a=1-c;else{if(a===l)return o?NaN:1/0*(p?-1:1);o+=Math.pow(2,n),a-=c}return(p?-1:1)*o*Math.pow(2,a-n)},il=function(t,e,r,n,i,a){var o,s,l,c=8*a-i-1,u=(1<<c)-1,f=u>>1,h=23===i?Math.pow(2,-24)-Math.pow(2,-77):0,p=n?0:a-1,d=n?1:-1,m=e<0||0===e&&1/e<0?1:0;for(e=Math.abs(e),isNaN(e)||e===1/0?(s=isNaN(e)?1:0,o=u):(o=Math.floor(Math.log(e)/Math.LN2),e*(l=Math.pow(2,-o))<1&&(o--,l*=2),(e+=o+f>=1?h/l:h*Math.pow(2,1-f))*l>=2&&(o++,l/=2),o+f>=u?(s=0,o=u):o+f>=1?(s=(e*l-1)*Math.pow(2,i),o+=f):(s=e*Math.pow(2,f-1)*Math.pow(2,i),o=0));i>=8;t[r+p]=255&s,p+=d,s/=256,i-=8);for(o=o<<i|s,c+=i;c>0;t[r+p]=255&o,p+=d,o/=256,c-=8);t[r+p-d]|=128*m},al=ol;function ol(t){this.buf=ArrayBuffer.isView&&ArrayBuffer.isView(t)?t:new 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e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed32());return t},readPackedFixed64:function(t){if(this.type!==ol.Bytes)return t.push(this.readFixed64());var e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readFixed64());return t},readPackedSFixed64:function(t){if(this.type!==ol.Bytes)return t.push(this.readSFixed64());var e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed64());return t},skip:function(t){var e=7&t;if(e===ol.Varint)for(;this.buf[this.pos++]>127;);else if(e===ol.Bytes)this.pos=this.readVarint()+this.pos;else if(e===ol.Fixed32)this.pos+=4;else{if(e!==ol.Fixed64)throw new Error(\"Unimplemented type: \"+e);this.pos+=8}},writeTag:function(t,e){this.writeVarint(t<<3|e)},realloc:function(t){for(var e=this.length||16;e<this.pos+t;)e*=2;if(e!==this.length){var r=new Uint8Array(e);r.set(this.buf),this.buf=r,this.length=e}},finish:function(){return 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r=(7&t)<<4;if(e.buf[e.pos++]|=r|((t>>>=3)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;e.buf[e.pos++]=127&t}(n,e)}(t,this):(this.realloc(4),this.buf[this.pos++]=127&t|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=t>>>7&127))))},writeSVarint:function(t){this.writeVarint(t<0?2*-t-1:2*t)},writeBoolean:function(t){this.writeVarint(Boolean(t))},writeString:function(t){t=String(t),this.realloc(4*t.length),this.pos++;var e=this.pos;this.pos=function(t,e,r){for(var n,i,a=0;a<e.length;a++){if((n=e.charCodeAt(a))>55295&&n<57344){if(!i){n>56319||a+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):i=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,i=n;continue}n=i-55296<<10|n-56320|65536,i=null}else i&&(t[r++]=239,t[r++]=191,t[r++]=189,i=null);n<128?t[r++]=n:(n<2048?t[r++]=n>>6|192:(n<65536?t[r++]=n>>12|224:(t[r++]=n>>18|240,t[r++]=n>>12&63|128),t[r++]=n>>6&63|128),t[r++]=63&n|128)}return r}(this.buf,t,this.pos);var r=this.pos-e;r>=128&&ul(e,r,this),this.pos=e-1,this.writeVarint(r),this.pos+=r},writeFloat:function(t){this.realloc(4),il(this.buf,t,this.pos,!0,23,4),this.pos+=4},writeDouble:function(t){this.realloc(8),il(this.buf,t,this.pos,!0,52,8),this.pos+=8},writeBytes:function(t){var e=t.length;this.writeVarint(e),this.realloc(e);for(var r=0;r<e;r++)this.buf[this.pos++]=t[r]},writeRawMessage:function(t,e){this.pos++;var r=this.pos;t(e,this);var n=this.pos-r;n>=128&&ul(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,ol.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,fl,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,hl,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,ml,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,pl,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,dl,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,gl,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,vl,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,yl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,xl,e)},writeBytesField:function(t,e){this.writeTag(t,ol.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,ol.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,ol.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,ol.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,ol.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,ol.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,ol.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,ol.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,ol.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,ol.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};function Tl(t,e,r){1===t&&r.readMessage(kl,e)}function kl(t,e,r){if(3===t){var n=r.readMessage(Ml,{}),i=n.id,a=n.bitmap,o=n.width,s=n.height,l=n.left,c=n.top,u=n.advance;e.push({id:i,bitmap:new So({width:o+6,height:s+6},a),metrics:{width:o,height:s,left:l,top:c,advance:u}})}}function Ml(t,e,r){1===t?e.id=r.readVarint():2===t?e.bitmap=r.readBytes():3===t?e.width=r.readVarint():4===t?e.height=r.readVarint():5===t?e.left=r.readSVarint():6===t?e.top=r.readSVarint():7===t&&(e.advance=r.readVarint())}function Al(t){for(var e=0,r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];e+=a.w*a.h,r=Math.max(r,a.w)}t.sort((function(t,e){return e.h-t.h}));for(var o=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),r),h:1/0}],s=0,l=0,c=0,u=t;c<u.length;c+=1)for(var f=u[c],h=o.length-1;h>=0;h--){var p=o[h];if(!(f.w>p.w||f.h>p.h)){if(f.x=p.x,f.y=p.y,l=Math.max(l,f.y+f.h),s=Math.max(s,f.x+f.w),f.w===p.w&&f.h===p.h){var d=o.pop();h<o.length&&(o[h]=d)}else 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Eo({width:o||1,height:s||1});for(var c in t){var u=t[c],f=r[c].paddedRect;Eo.copy(u.data,l,{x:0,y:0},{x:f.x+1,y:f.y+1},u.data)}for(var h in e){var p=e[h],d=n[h].paddedRect,m=d.x+1,g=d.y+1,v=p.data.width,y=p.data.height;Eo.copy(p.data,l,{x:0,y:0},{x:m,y:g},p.data),Eo.copy(p.data,l,{x:0,y:y-1},{x:m,y:g-1},{width:v,height:1}),Eo.copy(p.data,l,{x:0,y:0},{x:m,y:g+y},{width:v,height:1}),Eo.copy(p.data,l,{x:v-1,y:0},{x:m-1,y:g},{width:1,height:y}),Eo.copy(p.data,l,{x:0,y:0},{x:m+v,y:g},{width:1,height:y})}this.image=l,this.iconPositions=r,this.patternPositions=n};Ll.prototype.addImages=function(t,e,r){for(var n in t){var i=t[n],a={x:0,y:0,w:i.data.width+2,h:i.data.height+2};r.push(a),e[n]=new Sl(a,i),i.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},Ll.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},Ll.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl,i=n[0],a=n[1];r.update(e.data,void 0,{x:i,y:a})}},Nn(\"ImagePosition\",Sl),Nn(\"ImageAtlas\",Ll);var Cl={horizontal:1,vertical:2,horizontalOnly:3};var Pl=function(){this.scale=1,this.fontStack=\"\",this.imageName=null};Pl.forText=function(t,e){var r=new Pl;return r.scale=t||1,r.fontStack=e,r},Pl.forImage=function(t){var e=new Pl;return e.imageName=t,e};var Il=function(){this.text=\"\",this.sectionIndex=[],this.sections=[],this.imageSectionID=null};function Ol(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m){var g,v=Il.fromFeature(t,i);f===Cl.vertical&&v.verticalizePunctuation();var y=hi.processBidirectionalText,x=hi.processStyledBidirectionalText;if(y&&1===v.sections.length){g=[];for(var b=0,_=y(v.toString(),jl(v,c,a,e,n,p,d));b<_.length;b+=1){var w=_[b],T=new Il;T.text=w,T.sections=v.sections;for(var k=0;k<w.length;k++)T.sectionIndex.push(0);g.push(T)}}else if(x){g=[];for(var M=0,A=x(v.text,v.sectionIndex,jl(v,c,a,e,n,p,d));M<A.length;M+=1){var S=A[M],E=new Il;E.text=S[0],E.sectionIndex=S[1],E.sections=v.sections,g.push(E)}}else g=function(t,e){for(var r=[],n=t.text,i=0,a=0,o=e;a<o.length;a+=1){var s=o[a];r.push(t.substring(i,s)),i=s}return i<n.length&&r.push(t.substring(i,n.length)),r}(v,jl(v,c,a,e,n,p,d));var L=[],C={positionedLines:L,text:v.toString(),top:u[1],bottom:u[1],left:u[0],right:u[0],writingMode:f,iconsInText:!1,verticalizable:!1};return function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=0,p=-17,d=0,m=0,g=\"right\"===s?1:\"left\"===s?0:.5,v=0,y=0,x=i;y<x.length;y+=1){var b=x[y];b.trim();var _=b.getMaxScale(),w=24*(_-1),T={positionedGlyphs:[],lineOffset:0};t.positionedLines[v]=T;var k=T.positionedGlyphs,M=0;if(b.length()){for(var A=0;A<b.length();A++){var S=b.getSection(A),E=b.getSectionIndex(A),L=b.getCharCode(A),C=0,P=null,I=null,O=null,z=24,D=!(l===Cl.horizontal||!u&&!Zn(L)||u&&(zl[L]||(Y=L,Yn.Arabic(Y)||Yn[\"Arabic Supplement\"](Y)||Yn[\"Arabic Extended-A\"](Y)||Yn[\"Arabic Presentation Forms-A\"](Y)||Yn[\"Arabic Presentation Forms-B\"](Y))));if(S.imageName){var R=n[S.imageName];if(!R)continue;O=S.imageName,t.iconsInText=t.iconsInText||!0,I=R.paddedRect;var F=R.displaySize;S.scale=24*S.scale/f,P={width:F[0],height:F[1],left:1,top:-3,advance:D?F[1]:F[0]};var B=24-F[1]*S.scale;C=w+B,z=P.advance;var N=D?F[0]*S.scale-24*_:F[1]*S.scale-24*_;N>0&&N>M&&(M=N)}else{var j=r[S.fontStack],U=j&&j[L];if(U&&U.rect)I=U.rect,P=U.metrics;else{var V=e[S.fontStack],q=V&&V[L];if(!q)continue;P=q.metrics}C=24*(_-S.scale)}D?(t.verticalizable=!0,k.push({glyph:L,imageName:O,x:h,y:p+C,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:I}),h+=z*S.scale+c):(k.push({glyph:L,imageName:O,x:h,y:p+C,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:I}),h+=P.advance*S.scale+c)}if(0!==k.length){var H=h-c;d=Math.max(H,d),Vl(k,0,k.length-1,g,M)}h=0;var G=a*_+M;T.lineOffset=Math.max(M,w),p+=G,m=Math.max(G,m),++v}else p+=a,++v}var Y;var W=p- -17,X=Ul(o),Z=X.horizontalAlign,J=X.verticalAlign;(function(t,e,r,n,i,a,o,s,l){var c=(e-r)*i,u=0;u=a!==o?-s*n- -17:(-n*l+.5)*o;for(var f=0,h=t;f<h.length;f+=1)for(var p=h[f],d=0,m=p.positionedGlyphs;d<m.length;d+=1){var g=m[d];g.x+=c,g.y+=u}})(t.positionedLines,g,Z,J,d,m,a,W,i.length),t.top+=-J*W,t.bottom=t.top+W,t.left+=-Z*d,t.right=t.left+d}(C,e,r,n,g,o,s,l,f,c,h,m),!function(t){for(var e=0,r=t;e<r.length;e+=1){if(0!==r[e].positionedGlyphs.length)return!1}return!0}(L)&&C}Il.fromFeature=function(t,e){for(var r=new Il,n=0;n<t.sections.length;n++){var i=t.sections[n];i.image?r.addImageSection(i):r.addTextSection(i,e)}return r},Il.prototype.length=function(){return this.text.length},Il.prototype.getSection=function(t){return this.sections[this.sectionIndex[t]]},Il.prototype.getSectionIndex=function(t){return this.sectionIndex[t]},Il.prototype.getCharCode=function(t){return this.text.charCodeAt(t)},Il.prototype.verticalizePunctuation=function(){this.text=function(t){for(var e=\"\",r=0;r<t.length;r++){var n=t.charCodeAt(r+1)||null,i=t.charCodeAt(r-1)||null;(!n||!Jn(n)||rl[t[r+1]])&&(!i||!Jn(i)||rl[t[r-1]])&&rl[t[r]]?e+=rl[t[r]]:e+=t[r]}return e}(this.text)},Il.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&zl[this.text.charCodeAt(e)];e++)t++;for(var 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e=this.data,r=this.compare,n=this.length>>1,i=e[t];t<n;){var a=1+(t<<1),o=e[a],s=a+1;if(s<this.length&&r(e[s],o)<0&&(a=s,o=e[s]),r(o,i)>=0)break;e[t]=o,t=a}e[t]=i};var pc=Number.POSITIVE_INFINITY;function dc(t,e){return e[1]!==pc?function(t,e,r){var n=0,i=0;switch(e=Math.abs(e),r=Math.abs(r),t){case\"top-right\":case\"top-left\":case\"top\":i=r-7;break;case\"bottom-right\":case\"bottom-left\":case\"bottom\":i=7-r}switch(t){case\"top-right\":case\"bottom-right\":case\"right\":n=-e;break;case\"top-left\":case\"bottom-left\":case\"left\":n=e}return[n,i]}(t,e[0],e[1]):function(t,e){var r=0,n=0;e<0&&(e=0);var i=e/Math.sqrt(2);switch(t){case\"top-right\":case\"top-left\":n=i-7;break;case\"bottom-right\":case\"bottom-left\":n=7-i;break;case\"bottom\":n=7-e;break;case\"top\":n=e-7}switch(t){case\"top-right\":case\"bottom-right\":r=-i;break;case\"top-left\":case\"bottom-left\":r=i;break;case\"left\":r=e;break;case\"right\":r=-e}return[r,n]}(t,e[0])}function mc(t){switch(t){case\"right\":case\"top-right\":case\"bottom-right\":return\"right\";case\"left\":case\"top-left\":case\"bottom-left\":return\"left\"}return\"center\"}function gc(t,e,r,n,a,o,s,l,c,u,f,h,p,d,m){var g=function(t,e,r,n,a,o,s,l){for(var c=n.layout.get(\"text-rotate\").evaluate(o,{})*Math.PI/180,u=[],f=0,h=e.positionedLines;f<h.length;f+=1)for(var p=h[f],d=0,m=p.positionedGlyphs;d<m.length;d+=1){var g=m[d];if(g.rect){var v=g.rect||{},y=4,x=!0,b=1,_=0,w=(a||l)&&g.vertical,T=g.metrics.advance*g.scale/2;if(l&&e.verticalizable){var k=24*(g.scale-1),M=(24-g.metrics.width*g.scale)/2;_=p.lineOffset/2-(g.imageName?-M:k)}if(g.imageName){var A=s[g.imageName];x=A.sdf,y=1/(b=A.pixelRatio)}var S=a?[g.x+T,g.y]:[0,0],E=a?[0,0]:[g.x+T+r[0],g.y+r[1]-_],L=[0,0];w&&(L=E,E=[0,0]);var C=(g.metrics.left-y)*g.scale-T+E[0],P=(-g.metrics.top-y)*g.scale+E[1],I=C+v.w*g.scale/b,O=P+v.h*g.scale/b,z=new i(C,P),D=new i(I,P),R=new i(C,O),F=new i(I,O);if(w){var B=new i(-T,T- -17),N=-Math.PI/2,j=12-T,U=g.imageName?j:0,V=new i(22-j,-U),q=new(Function.prototype.bind.apply(i,[null].concat(L)));z._rotateAround(N,B)._add(V)._add(q),D._rotateAround(N,B)._add(V)._add(q),R._rotateAround(N,B)._add(V)._add(q),F._rotateAround(N,B)._add(V)._add(q)}if(c){var H=Math.sin(c),G=Math.cos(c),Y=[G,-H,H,G];z._matMult(Y),D._matMult(Y),R._matMult(Y),F._matMult(Y)}var W=new i(0,0),X=new i(0,0);u.push({tl:z,tr:D,bl:R,br:F,tex:v,writingMode:e.writingMode,glyphOffset:S,sectionIndex:g.sectionIndex,isSDF:x,pixelOffsetTL:W,pixelOffsetBR:X,minFontScaleX:0,minFontScaleY:0})}}return u}(0,r,l,a,o,s,n,t.allowVerticalPlacement),v=t.textSizeData,y=null;\"source\"===v.kind?(y=[128*a.layout.get(\"text-size\").evaluate(s,{})])[0]>32640&&_(t.layerIds[0]+': Value for \"text-size\" is >= 255. Reduce your \"text-size\".'):\"composite\"===v.kind&&((y=[128*d.compositeTextSizes[0].evaluate(s,{},m),128*d.compositeTextSizes[1].evaluate(s,{},m)])[0]>32640||y[1]>32640)&&_(t.layerIds[0]+': Value for \"text-size\" is >= 255. Reduce your \"text-size\".'),t.addSymbols(t.text,g,y,l,o,s,u,e,c.lineStartIndex,c.lineLength,p,m);for(var x=0,b=f;x<b.length;x+=1){h[b[x]]=t.text.placedSymbolArray.length-1}return 4*g.length}function vc(t){for(var e in t)return t[e];return null}function yc(t,e,r,n){var i=t.compareText;if(e in i){for(var a=i[e],o=a.length-1;o>=0;o--)if(n.dist(a[o])<r)return!0}else i[e]=[];return i[e].push(n),!1}var xc=Ls.VectorTileFeature.types,bc=[{name:\"a_fade_opacity\",components:1,type:\"Uint8\",offset:0}];function _c(t,e,r,n,i,a,o,s,l,c,u,f,h){var p=s?Math.min(32640,Math.round(s[0])):0,d=s?Math.min(32640,Math.round(s[1])):0;t.emplaceBack(e,r,Math.round(32*n),Math.round(32*i),a,o,(p<<1)+(l?1:0),d,16*c,16*u,256*f,256*h)}function wc(t,e,r){t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r)}function Tc(t){for(var e=0,r=t.sections;e<r.length;e+=1){if($n(r[e].text))return!0}return!1}var kc=function(t){this.layoutVertexArray=new Ni,this.indexArray=new Yi,this.programConfigurations=t,this.segments=new pa,this.dynamicLayoutVertexArray=new ji,this.opacityVertexArray=new Ui,this.placedSymbolArray=new aa};kc.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length&&0===this.indexArray.length&&0===this.dynamicLayoutVertexArray.length&&0===this.opacityVertexArray.length},kc.prototype.upload=function(t,e,r,n){this.isEmpty()||(r&&(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Js.members),this.indexBuffer=t.createIndexBuffer(this.indexArray,e),this.dynamicLayoutVertexBuffer=t.createVertexBuffer(this.dynamicLayoutVertexArray,Ks.members,!0),this.opacityVertexBuffer=t.createVertexBuffer(this.opacityVertexArray,bc,!0),this.opacityVertexBuffer.itemSize=1),(r||n)&&this.programConfigurations.upload(t))},kc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())},Nn(\"SymbolBuffers\",kc);var Mc=function(t,e,r){this.layoutVertexArray=new t,this.layoutAttributes=e,this.indexArray=new r,this.segments=new pa,this.collisionVertexArray=new Gi};Mc.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,Qs.members,!0)},Mc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},Nn(\"CollisionBuffers\",Mc);var Ac=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=ho([]),this.placementViewportMatrix=ho([]);var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=Gl(this.zoom,e[\"text-size\"]),this.iconSizeData=Gl(this.zoom,e[\"icon-size\"]);var r=this.layers[0].layout,n=r.get(\"symbol-sort-key\"),i=r.get(\"symbol-z-order\");this.sortFeaturesByKey=\"viewport-y\"!==i&&void 0!==n.constantOr(1);var a=\"viewport-y\"===i||\"auto\"===i&&!this.sortFeaturesByKey;this.sortFeaturesByY=a&&(r.get(\"text-allow-overlap\")||r.get(\"icon-allow-overlap\")||r.get(\"text-ignore-placement\")||r.get(\"icon-ignore-placement\")),\"point\"===r.get(\"symbol-placement\")&&(this.writingModes=r.get(\"text-writing-mode\").map((function(t){return Cl[t]}))),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id})),this.sourceID=t.sourceID};Ac.prototype.createArrays=function(){this.text=new kc(new Ua(Js.members,this.layers,this.zoom,(function(t){return/^text/.test(t)}))),this.icon=new kc(new Ua(Js.members,this.layers,this.zoom,(function(t){return/^icon/.test(t)}))),this.glyphOffsetArray=new la,this.lineVertexArray=new ca,this.symbolInstances=new sa},Ac.prototype.calculateGlyphDependencies=function(t,e,r,n,i){for(var a=0;a<t.length;a++)if(e[t.charCodeAt(a)]=!0,(r||n)&&i){var o=rl[t.charAt(a)];o&&(e[o.charCodeAt(0)]=!0)}},Ac.prototype.populate=function(t,e,r){var n=this.layers[0],i=n.layout,a=i.get(\"text-font\"),o=i.get(\"text-field\"),s=i.get(\"icon-image\"),l=(\"constant\"!==o.value.kind||o.value.value instanceof ne&&!o.value.value.isEmpty()||o.value.value.toString().length>0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),c=\"constant\"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,u=i.get(\"symbol-sort-key\");if(this.features=[],l||c){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new pi(this.zoom),m=0,g=t;m<g.length;m+=1){var v=g[m],y=v.feature,x=v.id,b=v.index,_=v.sourceLayerIndex,w=n._featureFilter.needGeometry,T={type:y.type,id:x,properties:y.properties,geometry:w?Ya(y):[]};if(n._featureFilter.filter(d,T,r)){w||(T.geometry=Ya(y));var k=void 0;if(l){var M=n.getValueAndResolveTokens(\"text-field\",T,r,p),A=ne.factory(M);Tc(A)&&(this.hasRTLText=!0),(!this.hasRTLText||\"unavailable\"===ui()||this.hasRTLText&&hi.isParsed())&&(k=el(A,n,T))}var S=void 0;if(c){var E=n.getValueAndResolveTokens(\"icon-image\",T,r,p);S=E instanceof ie?E:ie.fromString(E)}if(k||S){var L=this.sortFeaturesByKey?u.evaluate(T,{},r):void 0,C={id:x,text:k,icon:S,index:b,sourceLayerIndex:_,geometry:Ya(y),properties:y.properties,type:xc[y.type],sortKey:L};if(this.features.push(C),S&&(f[S.name]=!0),k){var P=a.evaluate(T,{},r).join(\",\"),I=\"map\"===i.get(\"text-rotation-alignment\")&&\"point\"!==i.get(\"symbol-placement\");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(Cl.vertical)>=0;for(var O=0,z=k.sections;O<z.length;O+=1){var D=z[O];if(D.image)f[D.image.name]=!0;else{var R=Wn(k.toString()),F=D.fontStack||P,B=h[F]=h[F]||{};this.calculateGlyphDependencies(D.text,B,I,this.allowVerticalPlacement,R)}}}}}}\"line\"===i.get(\"symbol-placement\")&&(this.features=function(t){var e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){var a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){var a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}for(var c=0;c<t.length;c++){var u=t[c],f=u.geometry,h=u.text?u.text.toString():null;if(h){var p=l(h,f),d=l(h,f,!0);if(p in r&&d in e&&r[p]!==e[d]){var m=s(p,d,f),g=o(p,d,n[m].geometry);delete e[p],delete r[d],r[l(h,n[g].geometry,!0)]=g,n[m].geometry=null}else p in r?o(p,d,f):d in e?s(p,d,f):(a(c),e[p]=i-1,r[d]=i-1)}else a(c)}return n.filter((function(t){return t.geometry}))}(this.features)),this.sortFeaturesByKey&&this.features.sort((function(t,e){return t.sortKey-e.sortKey}))}},Ac.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},Ac.prototype.isEmpty=function(){return 0===this.symbolInstances.length&&!this.hasRTLText},Ac.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},Ac.prototype.upload=function(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},Ac.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},Ac.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},Ac.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),i=t.dist(e[t.segment]),a={},o=t.segment+1;o<e.length;o++)a[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var c=a[l];this.lineVertexArray.emplaceBack(c.x,c.y,c.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},Ac.prototype.addSymbols=function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=t.indexArray,p=t.layoutVertexArray,d=t.segments.prepareSegment(4*e.length,p,h,a.sortKey),m=this.glyphOffsetArray.length,g=d.vertexLength,v=this.allowVerticalPlacement&&o===Cl.vertical?Math.PI/2:0,y=a.text&&a.text.sections,x=0;x<e.length;x++){var b=e[x],_=b.tl,w=b.tr,T=b.bl,k=b.br,M=b.tex,A=b.pixelOffsetTL,S=b.pixelOffsetBR,E=b.minFontScaleX,L=b.minFontScaleY,C=b.glyphOffset,P=b.isSDF,I=b.sectionIndex,O=d.vertexLength,z=C[1];_c(p,s.x,s.y,_.x,z+_.y,M.x,M.y,r,P,A.x,A.y,E,L),_c(p,s.x,s.y,w.x,z+w.y,M.x+M.w,M.y,r,P,S.x,A.y,E,L),_c(p,s.x,s.y,T.x,z+T.y,M.x,M.y+M.h,r,P,A.x,S.y,E,L),_c(p,s.x,s.y,k.x,z+k.y,M.x+M.w,M.y+M.h,r,P,S.x,S.y,E,L),wc(t.dynamicLayoutVertexArray,s,v),h.emplaceBack(O,O+1,O+2),h.emplaceBack(O+1,O+2,O+3),d.vertexLength+=4,d.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(C[0]),x!==e.length-1&&I===e[x+1].sectionIndex||t.programConfigurations.populatePaintArrays(p.length,a,a.index,{},f,y&&y[I])}t.placedSymbolArray.emplaceBack(s.x,s.y,m,this.glyphOffsetArray.length-m,g,l,c,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0,u)},Ac.prototype._addCollisionDebugVertex=function(t,e,r,n,i,a){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,i,Math.round(a.x),Math.round(a.y))},Ac.prototype.addCollisionDebugVertices=function(t,e,r,n,a,o,s){var l=a.segments.prepareSegment(4,a.layoutVertexArray,a.indexArray),c=l.vertexLength,u=a.layoutVertexArray,f=a.collisionVertexArray,h=s.anchorX,p=s.anchorY;this._addCollisionDebugVertex(u,f,o,h,p,new i(t,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,n)),this._addCollisionDebugVertex(u,f,o,h,p,new i(t,n)),l.vertexLength+=4;var d=a.indexArray;d.emplaceBack(c,c+1),d.emplaceBack(c+1,c+2),d.emplaceBack(c+2,c+3),d.emplaceBack(c+3,c),l.primitiveLength+=4},Ac.prototype.addDebugCollisionBoxes=function(t,e,r,n){for(var i=t;i<e;i++){var a=this.collisionBoxArray.get(i),o=a.x1,s=a.y1,l=a.x2,c=a.y2;this.addCollisionDebugVertices(o,s,l,c,n?this.textCollisionBox:this.iconCollisionBox,a.anchorPoint,r)}},Ac.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new Mc(qi,$s.members,Qi),this.iconCollisionBox=new Mc(qi,$s.members,Qi);for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e,!1),this.addDebugCollisionBoxes(e.verticalIconBoxStartIndex,e.verticalIconBoxEndIndex,e,!1)}},Ac.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,i,a,o,s,l){for(var c={},u=e;u<r;u++){var f=t.get(u);c.textBox={x1:f.x1,y1:f.y1,x2:f.x2,y2:f.y2,anchorPointX:f.anchorPointX,anchorPointY:f.anchorPointY},c.textFeatureIndex=f.featureIndex;break}for(var h=n;h<i;h++){var p=t.get(h);c.verticalTextBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},c.verticalTextFeatureIndex=p.featureIndex;break}for(var d=a;d<o;d++){var m=t.get(d);c.iconBox={x1:m.x1,y1:m.y1,x2:m.x2,y2:m.y2,anchorPointX:m.anchorPointX,anchorPointY:m.anchorPointY},c.iconFeatureIndex=m.featureIndex;break}for(var g=s;g<l;g++){var v=t.get(g);c.verticalIconBox={x1:v.x1,y1:v.y1,x2:v.x2,y2:v.y2,anchorPointX:v.anchorPointX,anchorPointY:v.anchorPointY},c.verticalIconFeatureIndex=v.featureIndex;break}return c},Ac.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex,r.verticalIconBoxStartIndex,r.verticalIconBoxEndIndex))}},Ac.prototype.hasTextData=function(){return this.text.segments.get().length>0},Ac.prototype.hasIconData=function(){return this.icon.segments.get().length>0},Ac.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},Ac.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},Ac.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},Ac.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i<n;i+=4)t.indexArray.emplaceBack(i,i+1,i+2),t.indexArray.emplaceBack(i+1,i+2,i+3)},Ac.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],i=[],a=[],o=0;o<this.symbolInstances.length;++o){a.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),i.push(s.featureIndex)}return a.sort((function(t,e){return n[t]-n[e]||i[e]-i[t]})),a},Ac.prototype.addToSortKeyRanges=function(t,e){var r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})},Ac.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var i=n[r],a=this.symbolInstances.get(i);this.featureSortOrder.push(a.featureIndex),[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},Nn(\"SymbolBucket\",Ac,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),Ac.MAX_GLYPHS=65535,Ac.addDynamicAttributes=wc;var Sc=new Si({\"symbol-placement\":new wi(Lt.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new wi(Lt.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new wi(Lt.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new Ti(Lt.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new wi(Lt.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new wi(Lt.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new wi(Lt.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new wi(Lt.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new wi(Lt.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new Ti(Lt.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new wi(Lt.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new wi(Lt.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new Ti(Lt.layout_symbol[\"icon-image\"]),\"icon-rotate\":new Ti(Lt.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new wi(Lt.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new wi(Lt.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new Ti(Lt.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new Ti(Lt.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new wi(Lt.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new wi(Lt.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new wi(Lt.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new Ti(Lt.layout_symbol[\"text-field\"]),\"text-font\":new Ti(Lt.layout_symbol[\"text-font\"]),\"text-size\":new Ti(Lt.layout_symbol[\"text-size\"]),\"text-max-width\":new Ti(Lt.layout_symbol[\"text-max-width\"]),\"text-line-height\":new wi(Lt.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new Ti(Lt.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new Ti(Lt.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new Ti(Lt.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new wi(Lt.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new Ti(Lt.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new wi(Lt.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new wi(Lt.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new Ti(Lt.layout_symbol[\"text-rotate\"]),\"text-padding\":new wi(Lt.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new wi(Lt.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new Ti(Lt.layout_symbol[\"text-transform\"]),\"text-offset\":new Ti(Lt.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new wi(Lt.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new wi(Lt.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new wi(Lt.layout_symbol[\"text-optional\"])}),Ec={paint:new Si({\"icon-opacity\":new Ti(Lt.paint_symbol[\"icon-opacity\"]),\"icon-color\":new Ti(Lt.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new Ti(Lt.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new Ti(Lt.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new Ti(Lt.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new wi(Lt.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new wi(Lt.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new Ti(Lt.paint_symbol[\"text-opacity\"]),\"text-color\":new Ti(Lt.paint_symbol[\"text-color\"],{runtimeType:Ut,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new Ti(Lt.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new Ti(Lt.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new Ti(Lt.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new wi(Lt.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new wi(Lt.paint_symbol[\"text-translate-anchor\"])}),layout:Sc},Lc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Ft,this.defaultValue=t};Lc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},Lc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},Lc.prototype.outputDefined=function(){return!1},Lc.prototype.serialize=function(){return null},Nn(\"FormatSectionOverride\",Lc,{omit:[\"defaultValue\"]});var Cc=function(t){function e(e){t.call(this,e,Ec)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a<o.length;a+=1){var s=o[a];i.indexOf(s)<0&&i.push(s)}this.layout._values[\"text-writing-mode\"]=i}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e,r,n){var i=this.layout.get(t).evaluate(e,{},r,n),a=this._unevaluatedLayout._values[t];return a.isDataDriven()||Yr(a.value)||!i?i:function(t,e){return e.replace(/{([^{}]+)}/g,(function(e,r){return r in t?String(t[r]):\"\"}))}(e.properties,i)},e.prototype.createBucket=function(t){return new Ac(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=Ec.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var i=this.paint.get(n),a=new Lc(i),o=new Gr(a,i.property.specification),s=null;s=\"constant\"===i.value.kind||\"source\"===i.value.kind?new Xr(\"source\",o):new Zr(\"composite\",o,i.value.zoomStops,i.value._interpolationType),this.paint._values[n]=new bi(i.property,s,i.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get(\"text-field\"),n=Ec.paint.properties[e],i=!1,a=function(t){for(var e=0,r=t;e<r.length;e+=1){var a=r[e];if(n.overrides&&n.overrides.hasOverride(a))return void(i=!0)}};if(\"constant\"===r.value.kind&&r.value.value instanceof ne)a(r.value.value.sections);else if(\"source\"===r.value.kind){var o=function(t){if(!i)if(t instanceof ce&&se(t.value)===Gt){var e=t.value;a(e.sections)}else t instanceof pe?a(t.sections):t.eachChild(o)},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return i},e}(Ei),Pc={paint:new Si({\"background-color\":new wi(Lt.paint_background[\"background-color\"]),\"background-pattern\":new Mi(Lt.paint_background[\"background-pattern\"]),\"background-opacity\":new wi(Lt.paint_background[\"background-opacity\"])})},Ic=function(t){function e(e){t.call(this,e,Pc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ei),Oc={paint:new Si({\"raster-opacity\":new wi(Lt.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new wi(Lt.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new wi(Lt.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new wi(Lt.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new wi(Lt.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new wi(Lt.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new wi(Lt.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new wi(Lt.paint_raster[\"raster-fade-duration\"])})},zc=function(t){function e(e){t.call(this,e,Oc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ei);var Dc=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.is3D=function(){return\"3d\"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(Ei),Rc={circle:_o,heatmap:Po,hillshade:Oo,fill:xs,\"fill-extrusion\":Fs,line:Xs,symbol:Cc,background:Ic,raster:zc};var Fc=self.HTMLImageElement,Bc=self.HTMLCanvasElement,Nc=self.HTMLVideoElement,jc=self.ImageData,Uc=self.ImageBitmap,Vc=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Vc.prototype.update=function(t,e,r){var n=t.width,i=t.height,a=!(this.size&&this.size[0]===n&&this.size[1]===i||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),a)this.size=[n,i],t instanceof Fc||t instanceof Bc||t instanceof Nc||t instanceof jc||Uc&&t instanceof Uc?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,i,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},c=l.x,u=l.y;t instanceof Fc||t instanceof Bc||t instanceof Nc||t instanceof jc||Uc&&t instanceof Uc?s.texSubImage2D(s.TEXTURE_2D,0,c,u,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,c,u,n,i,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Vc.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Vc.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Vc.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var qc=function(t){var e=this;this._callback=t,this._triggered=!1,\"undefined\"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};qc.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((function(){t._triggered=!1,t._callback()}),0))},qc.prototype.remove=function(){delete this._channel,this._callback=function(){}};var Hc=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},m([\"receive\",\"process\"],this),this.invoker=new qc(this.process),this.target.addEventListener(\"message\",this.receive,!1),this.globalScope=k()?t:self};function Gc(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}Hc.prototype.send=function(t,e,r,n,i){var a=this;void 0===i&&(i=!1);var o=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[o]=r);var s=S(this.globalScope)?void 0:[];return this.target.postMessage({id:o,type:t,hasCallback:!!r,targetMapId:n,mustQueue:i,sourceMapId:this.mapId,data:qn(e,s)},s),{cancel:function(){r&&delete a.callbacks[o],a.target.postMessage({id:o,type:\"<cancel>\",targetMapId:n,sourceMapId:a.mapId})}}},Hc.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"<cancel>\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else k()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Hc.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Hc.prototype.processTask=function(t,e){var r=this;if(\"<response>\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(Hn(e.error)):n(null,Hn(e.data)))}else{var i=!1,a=S(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"<response>\",sourceMapId:r.mapId,error:e?qn(e):null,data:qn(n,a)},a)}:function(t){i=!0},s=null,l=Hn(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var c=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,c[0],l.source)[c[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Hc.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Yc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Yc.prototype.setNorthEast=function(t){return this._ne=t instanceof Wc?new Wc(t.lng,t.lat):Wc.convert(t),this},Yc.prototype.setSouthWest=function(t){return this._sw=t instanceof Wc?new Wc(t.lng,t.lat):Wc.convert(t),this},Yc.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Wc)e=t,r=t;else{if(!(t instanceof Yc)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Yc.convert(a))}var o=t;return this.extend(Wc.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Wc(e.lng,e.lat),this._ne=new Wc(r.lng,r.lat)),this},Yc.prototype.getCenter=function(){return new Wc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Yc.prototype.getSouthWest=function(){return this._sw},Yc.prototype.getNorthEast=function(){return this._ne},Yc.prototype.getNorthWest=function(){return new Wc(this.getWest(),this.getNorth())},Yc.prototype.getSouthEast=function(){return new Wc(this.getEast(),this.getSouth())},Yc.prototype.getWest=function(){return this._sw.lng},Yc.prototype.getSouth=function(){return this._sw.lat},Yc.prototype.getEast=function(){return this._ne.lng},Yc.prototype.getNorth=function(){return this._ne.lat},Yc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Yc.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Yc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Yc.prototype.contains=function(t){var e=Wc.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Yc.convert=function(t){return!t||t instanceof Yc?t:new Yc(t)};var Wc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Wc.prototype.wrap=function(){return new Wc(c(this.lng,-180,180),this.lat)},Wc.prototype.toArray=function(){return[this.lng,this.lat]},Wc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Wc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return 6371008.8*Math.acos(Math.min(i,1))},Wc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Yc(new Wc(this.lng-r,this.lat-e),new Wc(this.lng+r,this.lat+e))},Wc.convert=function(t){if(t instanceof Wc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Wc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new Wc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var Xc=2*Math.PI*6371008.8;function Zc(t){return Xc*Math.cos(t*Math.PI/180)}function Jc(t){return(180+t)/360}function Kc(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Qc(t,e){return t/Zc(e)}function $c(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var tu=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};tu.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Wc.convert(t);return new tu(Jc(r.lng),Kc(r.lat),Qc(e,r.lat))},tu.prototype.toLngLat=function(){return new Wc(360*this.x-180,$c(this.y))},tu.prototype.toAltitude=function(){return t=this.z,e=this.y,t*Zc($c(e));var t,e},tu.prototype.meterInMercatorCoordinateUnits=function(){return 1/Xc*(t=$c(this.y),1/Math.cos(t*Math.PI/180));var t};var eu=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=iu(0,t,t,e,r)};eu.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},eu.prototype.url=function(t,e){var r,n,i,a,o,s=(r=this.x,n=this.y,i=this.z,a=Gc(256*r,256*(n=Math.pow(2,i)-n-1),i),o=Gc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<<a-1)?1:0)+(r&n?2:0);return i}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",String(this.z)).replace(\"{x}\",String(this.x)).replace(\"{y}\",String(\"tms\"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace(\"{quadkey}\",l).replace(\"{bbox-epsg-3857}\",s)},eu.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new i(8192*(t.x*e-this.x),8192*(t.y*e-this.y))},eu.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y};var ru=function(t,e){this.wrap=t,this.canonical=e,this.key=iu(t,e.z,e.z,e.x,e.y)},nu=function(t,e,r,n,i){this.overscaledZ=t,this.wrap=e,this.canonical=new eu(r,+n,+i),this.key=iu(e,t,r,n,i)};function iu(t,e,r,n,i){(t*=2)<0&&(t=-1*t-1);var a=1<<r;return(a*a*t+a*i+n).toString(36)+r.toString(36)+e.toString(36)}nu.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},nu.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new nu(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new nu(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},nu.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?iu(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):iu(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},nu.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},nu.prototype.children=function(t){if(this.overscaledZ>=t)return[new nu(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new nu(e,this.wrap,e,r,n),new nu(e,this.wrap,e,r+1,n),new nu(e,this.wrap,e,r,n+1),new nu(e,this.wrap,e,r+1,n+1)]},nu.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},nu.prototype.wrapped=function(){return new nu(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},nu.prototype.unwrapTo=function(t){return new nu(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},nu.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},nu.prototype.toUnwrapped=function(){return new ru(this.wrap,this.canonical)},nu.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},nu.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new tu(t.x-this.wrap,t.y))},Nn(\"CanonicalTileID\",eu),Nn(\"OverscaledTileID\",nu,{omit:[\"posMatrix\"]});var au=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError(\"DEM tiles must be square\");if(r&&\"mapbox\"!==r&&\"terrarium\"!==r)return _('\"'+r+'\" is not a valid encoding type. Valid types include \"mapbox\" and \"terrarium\".');this.stride=e.height;var n=this.dim=e.height-2;this.data=new Uint32Array(e.data.buffer),this.encoding=r||\"mapbox\";for(var i=0;i<n;i++)this.data[this._idx(-1,i)]=this.data[this._idx(0,i)],this.data[this._idx(n,i)]=this.data[this._idx(n-1,i)],this.data[this._idx(i,-1)]=this.data[this._idx(i,0)],this.data[this._idx(i,n)]=this.data[this._idx(i,n-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(n,-1)]=this.data[this._idx(n-1,0)],this.data[this._idx(-1,n)]=this.data[this._idx(0,n-1)],this.data[this._idx(n,n)]=this.data[this._idx(n-1,n-1)]};au.prototype.get=function(t,e){var r=new Uint8Array(this.data.buffer),n=4*this._idx(t,e);return(\"terrarium\"===this.encoding?this._unpackTerrarium:this._unpackMapbox)(r[n],r[n+1],r[n+2])},au.prototype.getUnpackVector=function(){return\"terrarium\"===this.encoding?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},au.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},au.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},au.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},au.prototype.getPixels=function(){return new Eo({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},au.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,c=a;c<o;c++)for(var u=n;u<i;u++)this.data[this._idx(u,c)]=t.data[this._idx(u+s,c+l)]},Nn(\"DEMData\",au);var ou=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};ou.prototype.encode=function(t){return this._stringToNumber[t]},ou.prototype.decode=function(t){return this._numberToString[t]};var su=function(t,e,r,n,i){this.type=\"Feature\",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=i},lu={geometry:{configurable:!0}};lu.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},lu.geometry.set=function(t){this._geometry=t},su.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)\"_geometry\"!==e&&\"_vectorTileFeature\"!==e&&(t[e]=this[e]);return t},Object.defineProperties(su.prototype,lu);var cu=function(){this.state={},this.stateChanges={},this.deletedStates={}};cu.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},u(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var i in this.deletedStates[t]={},this.state[t])i!==n&&(this.deletedStates[t][i]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var a in this.deletedStates[t][n]={},this.state[t][n])r[a]||(this.deletedStates[t][n][a]=null);else for(var o in r){this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]}},cu.prototype.removeFeatureState=function(t,e,r){if(!(null===this.deletedStates[t])){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e){if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null}else this.deletedStates[t]=null}},cu.prototype.getState=function(t,e){var r=String(e),n=this.state[t]||{},i=this.stateChanges[t]||{},a=u({},n[r],i[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var o=this.deletedStates[t][e];if(null===o)return{};for(var s in o)delete a[s]}return a},cu.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},cu.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var i={};for(var a in this.stateChanges[n])this.state[n][a]||(this.state[n][a]={}),u(this.state[n][a],this.stateChanges[n][a]),i[a]=this.state[n][a];r[n]=i}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var c in this.deletedStates[o]){if(null===this.deletedStates[o][c])this.state[o][c]={};else for(var f=0,h=Object.keys(this.deletedStates[o][c]);f<h.length;f+=1){var p=h[f];delete this.state[o][c][p]}s[c]=this.state[o][c]}r[o]=r[o]||{},u(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var d in t){t[d].setFeatureState(r,e)}};var uu=function(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new zn(8192,16,0),this.grid3D=new zn(8192,16,0),this.featureIndexArray=new fa,this.promoteId=e};function fu(t,e,r,n,i){return v(t,(function(t,a){var o=e instanceof _i?e.get(a):null;return o&&o.evaluate?o.evaluate(r,n,i):o}))}function hu(t){for(var e=1/0,r=1/0,n=-1/0,i=-1/0,a=0,o=t;a<o.length;a+=1){var s=o[a];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),i=Math.max(i,s.y)}return{minX:e,minY:r,maxX:n,maxY:i}}function pu(t,e){return e-t}uu.prototype.insert=function(t,e,r,n,i,a){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);for(var s=a?this.grid3D:this.grid,l=0;l<e.length;l++){for(var c=e[l],u=[1/0,1/0,-1/0,-1/0],f=0;f<c.length;f++){var h=c[f];u[0]=Math.min(u[0],h.x),u[1]=Math.min(u[1],h.y),u[2]=Math.max(u[2],h.x),u[3]=Math.max(u[3],h.y)}u[0]<8192&&u[1]<8192&&u[2]>=0&&u[3]>=0&&s.insert(o,u[0],u[1],u[2],u[3])}},uu.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new Ls.VectorTile(new al(this.rawTileData)).layers,this.sourceLayerCoder=new ou(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},uu.prototype.query=function(t,e,r,n){var a=this;this.loadVTLayers();for(var o=t.params||{},s=8192/t.tileSize/t.scale,l=sn(o.filter),c=t.queryGeometry,u=t.queryPadding*s,f=hu(c),h=this.grid.query(f.minX-u,f.minY-u,f.maxX+u,f.maxY+u),p=hu(t.cameraQueryGeometry),d=this.grid3D.query(p.minX-u,p.minY-u,p.maxX+u,p.maxY+u,(function(e,r,n,a){return function(t,e,r,n,a){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&a>=l.y)return!0}var c=[new i(e,r),new i(e,a),new i(n,a),new i(n,r)];if(t.length>2)for(var u=0,f=c;u<f.length;u+=1){if(io(t,f[u]))return!0}for(var h=0;h<t.length-1;h++){if(ao(t[h],t[h+1],c))return!0}return!1}(t.cameraQueryGeometry,e-u,r-u,n+u,a+u)})),m=0,g=d;m<g.length;m+=1){var v=g[m];h.push(v)}h.sort(pu);for(var y,x={},b=function(i){var u=h[i];if(u!==y){y=u;var f=a.featureIndexArray.get(u),p=null;a.loadMatchingFeature(x,f.bucketIndex,f.sourceLayerIndex,f.featureIndex,l,o.layers,o.availableImages,e,r,n,(function(e,r,n){return p||(p=Ya(e)),r.queryIntersectsFeature(c,e,n,p,a.z,t.transform,s,t.pixelPosMatrix)}))}},_=0;_<h.length;_++)b(_);return x},uu.prototype.loadMatchingFeature=function(t,e,r,n,i,a,o,s,l,c,u){var f=this.bucketLayerIDs[e];if(!a||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),p=this.vtLayers[h].feature(n);if(i.filter(new pi(this.tileID.overscaledZ),p))for(var d=this.getId(p,h),m=0;m<f.length;m++){var g=f[m];if(!(a&&a.indexOf(g)<0)){var v=s[g];if(v){var y={};void 0!==d&&c&&(y=c.getState(v.sourceLayer||\"_geojsonTileLayer\",d));var x=l[g];x.paint=fu(x.paint,v.paint,p,y,o),x.layout=fu(x.layout,v.layout,p,y,o);var b=!u||u(p,v,y);if(b){var _=new su(p,this.z,this.x,this.y,d);_.layer=x;var w=t[g];void 0===w&&(w=t[g]=[]),w.push({featureIndex:n,feature:_,intersectionZ:b})}}}}}},uu.prototype.lookupSymbolFeatures=function(t,e,r,n,i,a,o,s){var l={};this.loadVTLayers();for(var c=sn(i),u=0,f=t;u<f.length;u+=1){var h=f[u];this.loadMatchingFeature(l,r,n,h,c,a,o,s,e)}return l},uu.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,i=r[e];n<i.length;n+=1){if(t===i[n])return!0}return!1},uu.prototype.getId=function(t,e){var r=t.id;if(this.promoteId){var n=\"string\"==typeof this.promoteId?this.promoteId:this.promoteId[e];\"boolean\"==typeof(r=t.properties[n])&&(r=Number(r))}return r},Nn(\"FeatureIndex\",uu,{omit:[\"rawTileData\",\"sourceLayerCoder\"]});var du=function(t,e){this.tileID=t,this.uid=h(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state=\"loading\"};du.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<R.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},du.prototype.wasRequested=function(){return\"errored\"===this.state||\"loaded\"===this.state||\"reloading\"===this.state},du.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=a[i],n=t.layerIds.map((function(t){return e.getLayer(t)})).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map((function(t){return n.filter((function(e){return e.id===t}))[0]})));for(var o=0,s=n;o<s.length;o+=1){var l=s[o];r[l.id]=t}}},i=0,a=t;i<a.length;i+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var i=this.buckets[n];if(i instanceof Ac){if(this.hasSymbolBuckets=!0,!r)break;i.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var a in this.buckets){var o=this.buckets[a];if(o instanceof Ac&&o.hasRTLText){this.hasRTLText=!0,hi.isLoading()||hi.isLoaded()||\"deferred\"!==ui()||fi();break}}for(var s in this.queryPadding=0,this.buckets){var l=this.buckets[s];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(s).queryRadius(l))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new na},du.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},du.prototype.getBucket=function(t){return this.buckets[t.id]},du.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Vc(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Vc(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},du.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},du.prototype.queryRenderedFeatures=function(t,e,r,n,i,a,o,s,l,c){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:i,scale:a,tileSize:this.tileSize,pixelPosMatrix:c,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}},du.prototype.querySourceFeatures=function(t,e){var r=this.latestFeatureIndex;if(r&&r.rawTileData){var n=r.loadVTLayers(),i=e?e.sourceLayer:\"\",a=n._geojsonTileLayer||n[i];if(a)for(var o=sn(e&&e.filter),s=this.tileID.canonical,l=s.z,c=s.x,u=s.y,f={z:l,x:c,y:u},h=0;h<a.length;h++){var p=a.feature(h);if(o.filter(new pi(this.tileID.overscaledZ),p)){var d=r.getId(p,i),m=new su(p,l,c,u,d);m.tile=f,t.push(m)}}}},du.prototype.hasData=function(){return\"loaded\"===this.state||\"reloading\"===this.state||\"expired\"===this.state},du.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},du.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=M(t.cacheControl);r[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*r[\"max-age\"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),i=!1;if(this.expirationTime>n)i=!1;else if(e)if(this.expirationTime<e)i=!0;else{var a=this.expirationTime-e;a?this.expirationTime=n+Math.max(a,3e4):i=!0}else i=!0;i?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},du.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},du.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets)if(e.style.hasLayer(n)){var i=this.buckets[n],a=i.layers[0].sourceLayer||\"_geojsonTileLayer\",o=r[a],s=t[a];if(o&&s&&0!==Object.keys(s).length){i.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{});var l=e&&e.style&&e.style.getLayer(n);l&&(this.queryPadding=Math.max(this.queryPadding,l.queryRadius(i)))}}}},du.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},du.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<R.now()},du.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},du.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=R.now()+t},du.prototype.setDependencies=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){r[i[n]]=!0}this.dependencies[t]=r},du.prototype.hasDependency=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var i=n[r],a=this.dependencies[i];if(a)for(var o=0,s=e;o<s.length;o+=1){if(a[s[o]])return!0}}return!1};var 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r},t.makeRequest=yt,t.mapObject=v,t.mercatorXfromLng=Jc,t.mercatorYfromLat=Kc,t.mercatorZfromAltitude=Qc,t.mul=mo,t.multiply=po,t.mvt=Ls,t.normalize=function(t,e){var r=e[0],n=e[1],i=e[2],a=r*r+n*n+i*i;return a>0&&(a=1/Math.sqrt(a)),t[0]=e[0]*a,t[1]=e[1]*a,t[2]=e[2]*a,t},t.number=He,t.offscreenCanvasSupported=pt,t.ortho=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t},t.parseGlyphPBF=function(t){return new al(t).readFields(Tl,[])},t.pbf=al,t.performSymbolLayout=function(t,e,r,n,i,a,o){t.createArrays();var s=512*t.overscaling;t.tilePixelRatio=8192/s,t.compareText={},t.iconsNeedLinear=!1;var l=t.layers[0].layout,c=t.layers[0]._unevaluatedLayout._values,u={};if(\"composite\"===t.textSizeData.kind){var f=t.textSizeData,h=f.minZoom,p=f.maxZoom;u.compositeTextSizes=[c[\"text-size\"].possiblyEvaluate(new 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g=(c+1)%2;(0===c?r-i<=d:n-i<=m)&&(o.push(f),o.push(p-1),o.push(g)),(0===c?r+i>=d:n+i>=m)&&(o.push(p+1),o.push(u),o.push(g))}}return s}(this.ids,this.coords,t,e,r,this.nodeSize)};var j={minZoom:0,maxZoom:16,radius:40,extent:512,nodeSize:64,log:!1,generateId:!1,reduce:null,map:function(t){return t}},U=function(t){this.options=X(Object.create(j),t),this.trees=new Array(this.options.maxZoom+1)};function V(t,e,r,n,i){return{x:t,y:e,zoom:1/0,id:r,parentId:-1,numPoints:n,properties:i}}function q(t,e){var r=t.geometry.coordinates,n=r[0],i=r[1];return{x:Y(n),y:W(i),zoom:1/0,index:e,parentId:-1}}function H(t){return{type:\"Feature\",id:t.id,properties:G(t),geometry:{type:\"Point\",coordinates:[(n=t.x,360*(n-.5)),(e=t.y,r=(180-360*e)*Math.PI/180,360*Math.atan(Math.exp(r))/Math.PI-90)]}};var e,r,n}function G(t){var e=t.numPoints,r=e>=1e4?Math.round(e/1e3)+\"k\":e>=1e3?Math.round(e/100)/10+\"k\":e;return 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r=0;r<e.length;r+=3)t.minX=Math.min(t.minX,e[r]),t.minY=Math.min(t.minY,e[r+1]),t.maxX=Math.max(t.maxX,e[r]),t.maxY=Math.max(t.maxY,e[r+1])}function tt(t,e,r,n){if(e.geometry){var i=e.geometry.coordinates,a=e.geometry.type,o=Math.pow(r.tolerance/((1<<r.maxZoom)*r.extent),2),s=[],l=e.id;if(r.promoteId?l=e.properties[r.promoteId]:r.generateId&&(l=n||0),\"Point\"===a)et(i,s);else if(\"MultiPoint\"===a)for(var c=0;c<i.length;c++)et(i[c],s);else if(\"LineString\"===a)rt(i,s,o,!1);else if(\"MultiLineString\"===a){if(r.lineMetrics){for(c=0;c<i.length;c++)s=[],rt(i[c],s,o,!1),t.push(Q(l,\"LineString\",s,e.properties));return}nt(i,s,o,!1)}else if(\"Polygon\"===a)nt(i,s,o,!0);else{if(\"MultiPolygon\"!==a){if(\"GeometryCollection\"===a){for(c=0;c<e.geometry.geometries.length;c++)tt(t,{id:l,geometry:e.geometry.geometries[c],properties:e.properties},r,n);return}throw new Error(\"Input data is not a valid GeoJSON object.\")}for(c=0;c<i.length;c++){var 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u=t[c],f=u.geometry,h=u.type,p=0===i?u.minX:u.minY,d=0===i?u.maxX:u.maxY;if(p>=r&&d<n)l.push(u);else if(!(d<r||p>=n)){var m=[];if(\"Point\"===h||\"MultiPoint\"===h)st(f,m,r,n,i);else if(\"LineString\"===h)lt(f,m,r,n,i,!1,s.lineMetrics);else if(\"MultiLineString\"===h)ut(f,m,r,n,i,!1);else if(\"Polygon\"===h)ut(f,m,r,n,i,!0);else if(\"MultiPolygon\"===h)for(var g=0;g<f.length;g++){var v=[];ut(f[g],v,r,n,i,!0),v.length&&m.push(v)}if(m.length){if(s.lineMetrics&&\"LineString\"===h){for(g=0;g<m.length;g++)l.push(Q(u.id,h,m[g],u.tags));continue}\"LineString\"!==h&&\"MultiLineString\"!==h||(1===m.length?(h=\"LineString\",m=m[0]):h=\"MultiLineString\"),\"Point\"!==h&&\"MultiPoint\"!==h||(h=3===m.length?\"Point\":\"MultiPoint\"),l.push(Q(u.id,h,m,u.tags))}}}return l.length?l:null}function st(t,e,r,n,i){for(var a=0;a<t.length;a+=3){var o=t[a+i];o>=r&&o<=n&&(e.push(t[a]),e.push(t[a+1]),e.push(t[a+2]))}}function lt(t,e,r,n,i,a,o){for(var 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r=[],n=0;n<t.length;n++){var i,a=t[n],o=a.type;if(\"Point\"===o||\"MultiPoint\"===o||\"LineString\"===o)i=mt(a.geometry,e);else if(\"MultiLineString\"===o||\"Polygon\"===o){i=[];for(var s=0;s<a.geometry.length;s++)i.push(mt(a.geometry[s],e))}else if(\"MultiPolygon\"===o)for(i=[],s=0;s<a.geometry.length;s++){for(var l=[],c=0;c<a.geometry[s].length;c++)l.push(mt(a.geometry[s][c],e));i.push(l)}r.push(Q(a.id,o,i,a.tags))}return r}function mt(t,e){var r=[];r.size=t.size,void 0!==t.start&&(r.start=t.start,r.end=t.end);for(var n=0;n<t.length;n+=3)r.push(t[n]+e,t[n+1],t[n+2]);return r}function gt(t,e){if(t.transformed)return t;var r,n,i,a=1<<t.z,o=t.x,s=t.y;for(r=0;r<t.features.length;r++){var l=t.features[r],c=l.geometry,u=l.type;if(l.geometry=[],1===u)for(n=0;n<c.length;n+=2)l.geometry.push(vt(c[n],c[n+1],e,a,o,s));else for(n=0;n<c.length;n++){var f=[];for(i=0;i<c[n].length;i+=2)f.push(vt(c[n][i],c[n][i+1],e,a,o,s));l.geometry.push(f)}}return t.transformed=!0,t}function 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u={},e.tags)u[f]=e.tags[f];u.mapbox_clip_start=i.start/i.size,u.mapbox_clip_end=i.end/i.size}var h={geometry:o,type:\"Polygon\"===a||\"MultiPolygon\"===a?3:\"LineString\"===a||\"MultiLineString\"===a?2:1,tags:u};null!==e.id&&(h.id=e.id),t.features.push(h)}}function bt(t,e,r,n,i,a){var o=n*n;if(n>0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;l<e.length;l+=3)(0===n||e[l+2]>o)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n<i;a=n,n+=2)r+=(t[n]-t[a])*(t[n+1]+t[a+1]);if(r>0===e)for(n=0,i=t.length;n<i/2;n+=2){var o=t[n],s=t[n+1];t[n]=t[i-2-n],t[n+1]=t[i-1-n],t[i-2-n]=o,t[i-1-n]=s}}(s,a),t.push(s)}}function _t(t,e){var r=(e=this.options=function(t,e){for(var r in e)t[r]=e[r];return t}(Object.create(this.options),e)).debug;if(r&&console.time(\"preprocess data\"),e.maxZoom<0||e.maxZoom>24)throw new Error(\"maxZoom should be in the 0-24 range\");if(e.promoteId&&e.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n<t.features.length;n++)tt(r,t.features[n],e,n);else\"Feature\"===t.type?tt(r,t,e):tt(r,{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",e.indexMaxZoom,e.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,i=ot(t,1,-1-r,r,0,-1,2,e),a=ot(t,1,1-r,2+r,0,-1,2,e);return(i||a)&&(n=ot(t,1,-r,1+r,0,-1,2,e)||[],i&&(n=dt(i,1).concat(n)),a&&(n=n.concat(dt(a,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}function wt(t,e,r){return 32*((1<<t)*r+e)+t}function Tt(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var i=new g(n.features),a=_(i);0===a.byteOffset&&a.byteLength===a.buffer.byteLength||(a=new Uint8Array(a)),e(null,{vectorTile:i,rawData:a.buffer})}U.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,i=e.maxZoom,a=e.nodeSize;r&&console.time(\"total time\");var o=\"prepare \"+t.length+\" points\";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(q(t[l],l));this.trees[i+1]=new N(s,Z,J,a,Float32Array),r&&console.timeEnd(o);for(var c=i;c>=n;c--){var u=+Date.now();s=this._cluster(s,c),this.trees[c]=new N(s,Z,J,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",c,s.length,+Date.now()-u)}return r&&console.timeEnd(\"total time\"),this},U.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],c=[],u=0,f=l.range(Y(r),W(a),Y(i),W(n));u<f.length;u+=1){var h=f[u],p=l.points[h];c.push(p.numPoints?H(p):this.points[p.index])}return c},U.prototype.getChildren=function(t){var e=this._getOriginId(t),r=this._getOriginZoom(t),n=\"No cluster with the specified id.\",i=this.trees[r];if(!i)throw new Error(n);var a=i.points[e];if(!a)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,c=i.within(a.x,a.y,o);l<c.length;l+=1){var u=c[l],f=i.points[u];f.parentId===t&&s.push(f.numPoints?H(f):this.points[f.index])}if(0===s.length)throw new Error(n);return s},U.prototype.getLeaves=function(t,e,r){e=e||10,r=r||0;var n=[];return this._appendLeaves(n,t,e,r,0),n},U.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],i=Math.pow(2,t),a=this.options,o=a.extent,s=a.radius/o,l=(r-s)/i,c=(r+1+s)/i,u={features:[]};return this._addTileFeatures(n.range((e-s)/i,l,(e+1+s)/i,c),n.points,e,r,i,u),0===e&&this._addTileFeatures(n.range(1-s/i,l,1,c),n.points,i,r,i,u),e===i-1&&this._addTileFeatures(n.range(0,l,s/i,c),n.points,-1,r,i,u),u.features.length?u:null},U.prototype.getClusterExpansionZoom=function(t){for(var e=this._getOriginZoom(t)-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},U.prototype._appendLeaves=function(t,e,r,n,i){for(var a=0,o=this.getChildren(e);a<o.length;a+=1){var s=o[a],l=s.properties;if(l&&l.cluster?i+l.point_count<=n?i+=l.point_count:i=this._appendLeaves(t,l.cluster_id,r,n,i):i<n?i++:t.push(s),t.length===r)break}return i},U.prototype._addTileFeatures=function(t,e,r,n,i,a){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],c=l.numPoints,u={type:1,geometry:[[Math.round(this.options.extent*(l.x*i-r)),Math.round(this.options.extent*(l.y*i-n))]],tags:c?G(l):this.points[l.index].properties},f=void 0;c?f=l.id:this.options.generateId?f=l.index:this.points[l.index].id&&(f=this.points[l.index].id),void 0!==f&&(u.id=f),a.features.push(u)}},U.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(t,this.options.maxZoom+1))},U.prototype._cluster=function(t,e){for(var r=[],n=this.options,i=n.radius,a=n.extent,o=n.reduce,s=i/(a*Math.pow(2,e)),l=0;l<t.length;l++){var c=t[l];if(!(c.zoom<=e)){c.zoom=e;for(var u=this.trees[e+1],f=u.within(c.x,c.y,s),h=c.numPoints||1,p=c.x*h,d=c.y*h,m=o&&h>1?this._map(c,!0):null,g=(l<<5)+(e+1)+this.points.length,v=0,y=f;v<y.length;v+=1){var x=y[v],b=u.points[x];if(!(b.zoom<=e)){b.zoom=e;var _=b.numPoints||1;p+=b.x*_,d+=b.y*_,h+=_,b.parentId=g,o&&(m||(m=this._map(c,!0)),o(m,this._map(b)))}}1===h?r.push(c):(c.parentId=g,r.push(V(p/h,d/h,g,h,m)))}}return r},U.prototype._getOriginId=function(t){return t-this.points.length>>5},U.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},U.prototype._map=function(t,e){if(t.numPoints)return e?X({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?X({},n):n},_t.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},_t.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,c=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var u=1<<e,f=wt(e,r,n),h=this.tiles[f];if(!h&&(c>1&&console.time(\"creation\"),h=this.tiles[f]=yt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),c)){c>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<<i-e;if(r!==Math.floor(a/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||h.numPoints<=l.indexMaxPoints)continue;if(h.source=null,0!==t.length){c>1&&console.time(\"clipping\");var m,g,v,y,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;m=g=v=y=null,x=ot(t,u,r-_,r+T,0,h.minX,h.maxX,l),b=ot(t,u,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(m=ot(x,u,n-_,n+T,1,h.minY,h.maxY,l),g=ot(x,u,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(v=ot(b,u,n-_,n+T,1,h.minY,h.maxY,l),y=ot(b,u,n+w,n+k,1,h.minY,h.maxY,l),b=null),c>1&&console.timeEnd(\"clipping\"),s.push(m||[],e+1,2*r,2*n),s.push(g||[],e+1,2*r,2*n+1),s.push(v||[],e+1,2*r+1,2*n),s.push(y||[],e+1,2*r+1,2*n+1)}}},_t.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<<t,s=wt(t,e=(e%o+o)%o,r);if(this.tiles[s])return gt(this.tiles[s],i);a>1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,c=t,u=e,f=r;!l&&c>0;)c--,u=Math.floor(u/2),f=Math.floor(f/2),l=this.tiles[wt(c,u,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",c,u,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,c,u,f,t,e,r),a>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?gt(this.tiles[s],i):null):null};var kt=function(e){function r(t,r,n,i){e.call(this,t,r,n,Tt),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if(\"object\"!=typeof o)return r(new Error(\"Input data given to '\"+n.source+\"' is not a valid GeoJSON object.\"));f(o,!0);try{e._geoJSONIndex=n.cluster?new U(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),c=0,u=l;c<u.length;c+=1){var f=u[c],h=n[f],p=h[0],d=h[1],m=t.createExpression(d),g=t.createExpression(\"string\"==typeof p?[p,[\"accumulated\"],[\"get\",f]]:p);i[f]=m.value,a[f]=g.value}return r.map=function(t){s.properties=t;for(var e={},r=0,n=l;r<n.length;r+=1){var a=n[r];e[a]=i[a].evaluate(o,s)}return e},r.reduce=function(t,e){s.properties=e;for(var r=0,n=l;r<n.length;r+=1){var i=n[r];o.accumulated=t[i],t[i]=a[i].evaluate(o,s)}},r}(n)).load(o.features):function(t,e){return new _t(t,e)}(o,n.geojsonVtOptions)}catch(a){return r(a)}e.loaded={};var s={};if(i){var l=i.finish();l&&(s.resourceTiming={},s.resourceTiming[n.source]=JSON.parse(JSON.stringify(l)))}r(null,s)}))}},r.prototype.coalesce=function(){\"Coalescing\"===this._state?this._state=\"Idle\":\"NeedsLoadData\"===this._state&&(this._state=\"Coalescing\",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded,i=t.uid;return n&&n[i]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if(\"string\"!=typeof e.data)return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON 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registered.\");t.plugin.applyArabicShaping=e.applyArabicShaping,t.plugin.processBidirectionalText=e.processBidirectionalText,t.plugin.processStyledBidirectionalText=e.processStyledBidirectionalText}};return Mt.prototype.setReferrer=function(t,e){this.referrer=e},Mt.prototype.setImages=function(t,e,r){for(var n in this.availableImages[t]=e,this.workerSources[t]){var i=this.workerSources[t][n];for(var a in 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t.Point(r.clientX-n.left-e.clientLeft,r.clientY-n.top-e.clientTop)},r.touchPos=function(e,r){for(var n=e.getBoundingClientRect(),i=[],a=0;a<r.length;a++)i.push(new t.Point(r[a].clientX-n.left-e.clientLeft,r[a].clientY-n.top-e.clientTop));return i},r.mouseButton=function(e){return void 0!==t.window.InstallTrigger&&2===e.button&&e.ctrlKey&&t.window.navigator.platform.toUpperCase().indexOf(\"MAC\")>=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var h=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e<r.length;e+=1){var n=r[e],i=n.ids,a=n.callback;this._notify(i,a)}this.requestors=[]}},r.prototype.getImage=function(t){return this.images[t]},r.prototype.addImage=function(t,e){this._validate(t,e)&&(this.images[t]=e)},r.prototype._validate=function(e,r){var n=!0;return this._validateStretch(r.stretchX,r.data&&r.data.width)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchX\" value'))),n=!1),this._validateStretch(r.stretchY,r.data&&r.data.height)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchY\" value'))),n=!1),this._validateContent(r.content,r)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"content\" value'))),n=!1),n},r.prototype._validateStretch=function(t,e){if(!t)return!0;for(var r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];if(a[0]<r||a[1]<a[0]||e<a[1])return!1;r=a[1]}return!0},r.prototype._validateContent=function(t,e){return!t||4===t.length&&(!(t[0]<0||e.data.width<t[0])&&(!(t[1]<0||e.data.height<t[1])&&(!(t[2]<0||e.data.width<t[2])&&(!(t[3]<0||e.data.height<t[3])&&(!(t[2]<t[0])&&!(t[3]<t[1]))))))},r.prototype.updateImage=function(t,e){var r=this.images[t];e.version=r.version+1,this.images[t]=e,this.updatedImages[t]=!0},r.prototype.removeImage=function(t){var e=this.images[t];delete this.images[t],delete this.patterns[t],e.userImage&&e.userImage.onRemove&&e.userImage.onRemove()},r.prototype.listImages=function(){return Object.keys(this.images)},r.prototype.getImages=function(t,e){var r=!0;if(!this.isLoaded())for(var n=0,i=t;n<i.length;n+=1){var a=i[n];this.images[a]||(r=!1)}this.isLoaded()||r?this._notify(t,e):this.requestors.push({ids:t,callback:e})},r.prototype._notify=function(e,r){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i];this.images[o]||this.fire(new t.Event(\"styleimagemissing\",{id:o}));var s=this.images[o];s?n[o]={data:s.data.clone(),pixelRatio:s.pixelRatio,sdf:s.sdf,version:s.version,stretchX:s.stretchX,stretchY:s.stretchY,content:s.content,hasRenderCallback:Boolean(s.userImage&&s.userImage.render)}:t.warnOnce('Image \"'+o+'\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. You can provide missing images by listening for the \"styleimagemissing\" map event.')}r(null,n)},r.prototype.getPixelSize=function(){var t=this.atlasImage;return{width:t.width,height:t.height}},r.prototype.getPattern=function(e){var r=this.patterns[e],n=this.getImage(e);if(!n)return null;if(r&&r.position.version===n.version)return r.position;if(r)r.position.version=n.version;else{var i={w:n.data.width+2,h:n.data.height+2,x:0,y:0},a=new t.ImagePosition(i,n);this.patterns[e]={bin:i,position:a}}return this._updatePatternAtlas(),this.patterns[e].position},r.prototype.bind=function(e){var r=e.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new t.Texture(e,this.atlasImage,r.RGBA),this.atlasTexture.bind(r.LINEAR,r.CLAMP_TO_EDGE)},r.prototype._updatePatternAtlas=function(){var e=[];for(var r in this.patterns)e.push(this.patterns[r].bin);var n=t.potpack(e),i=n.w,a=n.h,o=this.atlasImage;for(var s in o.resize({width:i||1,height:a||1}),this.patterns){var l=this.patterns[s].bin,c=l.x+1,u=l.y+1,f=this.images[s].data,h=f.width,p=f.height;t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u},{width:h,height:p}),t.RGBAImage.copy(f,o,{x:0,y:p-1},{x:c,y:u-1},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u+p},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:h-1,y:0},{x:c-1,y:u},{width:1,height:p}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c+h,y:u},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var i=this.images[n];f(i)&&this.updateImage(n,i)}}},r}(t.Evented);var p=g,d=g,m=1e20;function g(t,e,r,n,i,a){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=i||\"sans-serif\",this.fontWeight=a||\"normal\",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}function v(t,e,r,n,i,a,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(y(n,i,a,o,r),l=0;l<r;l++)t[l*e+s]=i[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(y(n,i,a,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(i[s])}}function y(t,e,r,n,i){r[0]=0,n[0]=-m,n[1]=+m;for(var a=1,o=0;a<i;a++){for(var s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);s<=n[o];)o--,s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);r[++o]=a,n[o]=s,n[o+1]=+m}for(a=0,o=0;a<i;a++){for(;n[o+1]<a;)o++;e[a]=(a-r[o])*(a-r[o])+t[r[o]]}}g.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var i=e.data[4*n+3]/255;this.gridOuter[n]=1===i?0:0===i?m:Math.pow(Math.max(0,.5-i),2),this.gridInner[n]=1===i?m:0===i?0:Math.pow(Math.max(0,i-.5),2)}for(v(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),v(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++){var a=this.gridOuter[n]-this.gridInner[n];r[n]=Math.max(0,Math.min(255,Math.round(255-255*(a/this.radius+this.cutoff))))}return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,i=[];for(var a in e)for(var o=0,s=e[a];o<s.length;o+=1){var l=s[o];i.push({stack:a,id:l})}t.asyncAll(i,(function(t,e){var r=t.stack,i=t.id,a=n.entries[r];a||(a=n.entries[r]={glyphs:{},requests:{},ranges:{}});var o=a.glyphs[i];if(void 0===o){if(o=n._tinySDF(a,r,i))return a.glyphs[i]=o,void e(null,{stack:r,id:i,glyph:o});var s=Math.floor(i/256);if(256*s>65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i<o.length;i+=1){(0,o[i])(t,e)}delete a.requests[s]}))),l.push((function(t,n){t?e(t):n&&e(null,{stack:r,id:i,glyph:n[i]||null})}))}}else e(null,{stack:r,id:i,glyph:o})}),(function(t,e){if(t)r(t);else if(e){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.stack,l=o.id,c=o.glyph;(n[s]||(n[s]={}))[l]=c&&{id:c.id,bitmap:c.bitmap.clone(),metrics:c.metrics}}r(null,n)}}))},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar[\"CJK Unified Ideographs\"](e)||t.isChar[\"Hangul Syllables\"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var i=this.localIdeographFontFamily;if(i&&this._doesCharSupportLocalGlyph(n)){var a=e.tinySDF;if(!a){var o=\"400\";/bold/i.test(r)?o=\"900\":/medium/i.test(r)?o=\"500\":/light/i.test(r)&&(o=\"200\"),a=e.tinySDF=new x.TinySDF(24,3,8,.25,i,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},a.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,i,a){var o=256*r,s=o+255,l=i.transformRequest(i.normalizeGlyphsURL(n).replace(\"{fontstack}\",e).replace(\"{range}\",o+\"-\"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,(function(e,r){if(e)a(e);else if(r){for(var n={},i=0,o=t.parseGlyphPBF(r);i<o.length;i+=1){var s=o[i];n[s.id]=s}a(null,n)}}))},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var i=e[n];t.endsWith(n,\"-transition\")?this._transitionable.setTransition(n.slice(0,-\"-transition\".length),i):this._transitionable.setValue(n,i)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),T=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};T.prototype.getDash=function(t,e){var r=t.join(\",\")+String(e);return this.dashEntry[r]||(this.dashEntry[r]=this.addDash(t,e)),this.dashEntry[r]},T.prototype.getDashRanges=function(t,e,r){var n=[],i=t.length%2==1?-t[t.length-1]*r:0,a=t[0]*r,o=!0;n.push({left:i,right:a,isDash:o,zeroLength:0===t[0]});for(var s=t[0],l=1;l<t.length;l++){o=!o;var c=t[l];i=s*r,a=(s+=c)*r,n.push({left:i,right:a,isDash:o,zeroLength:0===c})}return n},T.prototype.addRoundDash=function(t,e,r){for(var n=e/2,i=-r;i<=r;i++)for(var a=this.nextRow+r+i,o=this.width*a,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),f=Math.abs(c-l.right),h=Math.min(u,f),p=void 0,d=i/r*(n+1);if(l.isDash){var m=n-Math.abs(d);p=Math.sqrt(h*h+m*m)}else p=n-Math.sqrt(h*h+d*d);this.data[o+c]=Math.max(0,Math.min(255,p+128))}},T.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),f=Math.abs(c-l.right),h=Math.min(u,f),p=l.isDash?h:-h;this.data[o+c]=Math.max(0,Math.min(255,p+128))}},T.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o<e.length;o++)a+=e[o];if(0!==a){var s=this.width/a,l=this.getDashRanges(e,this.width,s);r?this.addRoundDash(l,s,n):this.addRegularDash(l)}var c={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:a};return this.nextRow+=i,this.dirty=!0,c},T.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.ALPHA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.ALPHA,this.width,this.height,0,e.ALPHA,e.UNSIGNED_BYTE,this.data))};var k=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var i=this.workerPool.acquire(this.id),a=0;a<i.length;a++){var o=i[a],s=new e.Actor(o,n,this.id);s.name=\"Worker \"+a,this.actors.push(s)}};function M(e,r,n){var i=function(i,a){if(i)return n(i);if(a){var o=t.pick(t.extend(a,e),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);a.vector_layers&&(o.vectorLayers=a.vector_layers,o.vectorLayerIds=o.vectorLayers.map((function(t){return t.id}))),o.tiles=r.canonicalizeTileset(o,e.url),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),i):t.browser.frame((function(){return i(null,e)}))}k.prototype.broadcast=function(e,r,n){n=n||function(){},t.asyncAll(this.actors,(function(t,n){t.send(e,r,n)}),n)},k.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},k.prototype.remove=function(){this.actors.forEach((function(t){t.remove()})),this.actors=[],this.workerPool.release(this.id)},k.Actor=t.Actor;var A=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};A.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},A.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),i=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),a=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<a&&e.y>=i&&e.y<o};var S=function(e){function r(r,n,i,a){if(e.call(this),this.id=r,this.dispatcher=i,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\",\"promoteId\"])),this._options=t.extend({type:\"vector\"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(a)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new A(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme)),i={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};function a(n,i){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(i&&i.resourceTiming&&(e.resourceTiming=i.resourceTiming),this.map._refreshExpiredTiles&&i&&e.setExpiryData(i),e.loadVectorData(i,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}i.request.collectResourceTiming=this._collectResourceTiming,e.actor&&\"expired\"!==e.state?\"loading\"===e.state?e.reloadCallback=r:e.request=e.actor.send(\"reloadTile\",i,a.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send(\"loadTile\",i,a.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send(\"abortTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),E=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.dispatcher=i,this.setEventedParent(a),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:\"raster\"},n),t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"]))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new A(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,i=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(i,t.ResourceType.Tile),(function(i,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(i)e.state=\"errored\",r(i);else if(a){n.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(a.width),e.texture?e.texture.update(a,{useMipmap:!0}):(e.texture=new t.Texture(o,a,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state=\"loaded\",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}}))},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),L=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),this.type=\"raster-dem\",this.maxzoom=22,this._options=t.extend({type:\"raster-dem\"},n),this.encoding=n.encoding||\"mapbox\"}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);function i(t,n){t&&(e.state=\"errored\",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state=\"loaded\",r(null))}e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(n)e.state=\"errored\",r(n);else if(a){this.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=t.window.ImageBitmap&&a instanceof t.window.ImageBitmap&&t.offscreenCanvasSupported()?a:t.browser.getImageData(a,1),s={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:o,encoding:this.encoding};e.actor&&\"expired\"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send(\"loadDEMTile\",s,i.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state=\"unloaded\",t.actor&&t.actor.send(\"removeDEMTile\",{uid:t.uid,source:this.id})},r}(E),C=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=i.getActor(),this.setEventedParent(a),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution),this.promoteId=n.promoteId;var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1,generateId:n.generateId||!1},clusterProperties:n.clusterProperties},n.workerOptions)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:\"source\",sourceDataType:\"metadata\"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),P=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),I=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.x),a=Math.max(a,l.y)}var c=i-r,u=a-n,f=Math.max(c,u),h=Math.max(0,Math.floor(-Math.log(f)/Math.LN2)),p=Math.pow(2,h);return new t.CanonicalTileID(h,Math.floor((r+i)/2*p),Math.floor((n+a)/2*p))}(n),this.minzoom=this.maxzoom=this.tileID.z;var i=n.map((function(t){return r.tileID.getTilePoint(t)._round()}));return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(i[0].x,i[0].y,0,0),this._boundsArray.emplaceBack(i[1].x,i[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(i[3].x,i[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(i[2].x,i[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state=\"errored\",e(null))},r.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented);var O=function(e){function r(t,r,n,i){e.call(this,t,r,n,i),this.roundZoom=!0,this.type=\"video\",this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,i=r.urls;n<i.length;n+=1){var a=i[n];this.urls.push(this.map._requestManager.transformRequest(a,t.ResourceType.Source).url)}t.getVideo(this.urls,(function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener(\"playing\",(function(){e.map.triggerRepaint()})),e.map&&e.video.play(),e._finishLoading())}))},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),z=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var 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e=this.gl;e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0),this.current=t,this.dirty=!1}},e}(_t),Tt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){if(t!==this.current||this.dirty){this.context.bindFramebuffer.set(this.parent);var e=this.gl;e.framebufferRenderbuffer(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(_t),kt=function(t,e,r,n){this.context=t,this.width=e,this.height=r;var i=t.gl,a=this.framebuffer=i.createFramebuffer();this.colorAttachment=new wt(t,a),n&&(this.depthAttachment=new Tt(t,a))};kt.prototype.destroy=function(){var t=this.context.gl,e=this.colorAttachment.get();if(e&&t.deleteTexture(e),this.depthAttachment){var r=this.depthAttachment.get();r&&t.deleteRenderbuffer(r)}t.deleteFramebuffer(this.framebuffer)};var Mt=function(t,e,r){this.func=t,this.mask=e,this.range=r};Mt.ReadOnly=!1,Mt.ReadWrite=!0,Mt.disabled=new Mt(519,Mt.ReadOnly,[0,1]);var At=function(t,e,r,n,i,a){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=i,this.pass=a};At.disabled=new At({func:519,mask:0},0,0,7680,7680,7680);var St=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};St.disabled=new St(St.Replace=[1,0],t.Color.transparent,[!1,!1,!1,!1]),St.unblended=new St(St.Replace,t.Color.transparent,[!0,!0,!0,!0]),St.alphaBlended=new St([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Et=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Et.disabled=new Et(!1,1029,2305),Et.backCCW=new Et(!0,1029,2305);var Lt=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension(\"OES_vertex_array_object\"),this.clearColor=new H(this),this.clearDepth=new G(this),this.clearStencil=new Y(this),this.colorMask=new W(this),this.depthMask=new X(this),this.stencilMask=new Z(this),this.stencilFunc=new J(this),this.stencilOp=new K(this),this.stencilTest=new Q(this),this.depthRange=new $(this),this.depthTest=new tt(this),this.depthFunc=new et(this),this.blend=new rt(this),this.blendFunc=new nt(this),this.blendColor=new it(this),this.blendEquation=new at(this),this.cullFace=new ot(this),this.cullFaceSide=new st(this),this.frontFace=new lt(this),this.program=new ct(this),this.activeTexture=new ut(this),this.viewport=new ft(this),this.bindFramebuffer=new ht(this),this.bindRenderbuffer=new pt(this),this.bindTexture=new dt(this),this.bindVertexBuffer=new mt(this),this.bindElementBuffer=new gt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new vt(this),this.pixelStoreUnpack=new yt(this),this.pixelStoreUnpackPremultiplyAlpha=new xt(this),this.pixelStoreUnpackFlipY=new bt(this),this.extTextureFilterAnisotropic=t.getExtension(\"EXT_texture_filter_anisotropic\")||t.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||t.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&(t.getExtension(\"OES_texture_half_float_linear\"),this.extRenderToTextureHalfFloat=t.getExtension(\"EXT_color_buffer_half_float\")),this.extTimerQuery=t.getExtension(\"EXT_disjoint_timer_query\")};Lt.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Lt.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Lt.prototype.createIndexBuffer=function(t,e){return new j(this,t,e)},Lt.prototype.createVertexBuffer=function(t,e,r){return new V(this,t,e,r)},Lt.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,i=n.createRenderbuffer();return this.bindRenderbuffer.set(i),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),i},Lt.prototype.createFramebuffer=function(t,e,r){return new kt(this,t,e,r)},Lt.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,i=0;e&&(i|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(i|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(i)},Lt.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Lt.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Lt.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Lt.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,St.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Lt.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Ct=function(e){function r(r,n,i){var a=this;e.call(this),this.id=r,this.dispatcher=i,this.on(\"data\",(function(t){\"source\"===t.dataType&&\"metadata\"===t.sourceDataType&&(a._sourceLoaded=!0),a._sourceLoaded&&!a._paused&&\"source\"===t.dataType&&\"content\"===t.sourceDataType&&(a.reload(),a.transform&&a.update(a.transform))})),this.on(\"error\",(function(){a._sourceErrored=!0})),this._source=function(e,r,n,i){var a=new D[r.type](e,r,n,i);if(a.id!==e)throw new Error(\"Expected Source id to be \"+e+\" instead of \"+a.id);return t.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],a),a}(r,n,i,this),this._tiles={},this._cache=new N(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,(function(){}))},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,(function(){}))},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return t.values(this._tiles).map((function(t){return t.tileID})).sort(Pt).map((function(t){return t.key}))},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var i in this._tiles)this._isIdRenderable(i,e)&&n.push(this._tiles[i]);return e?n.sort((function(e,n){var i=e.tileID,a=n.tileID,o=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle),s=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle);return i.overscaledZ-a.overscaledZ||s.y-o.y||s.x-o.x})).map((function(t){return t.tileID.key})):n.map((function(t){return t.tileID})).sort(Pt).map((function(t){return t.key}))},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)\"errored\"!==this._tiles[t].state&&this._reloadTile(t,\"reloading\")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&(\"loading\"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,i){if(i)return e.state=\"errored\",void(404!==i.status?this._source.fire(new t.ErrorEvent(i,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),\"expired\"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),\"raster-dem\"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event(\"data\",{dataType:\"source\",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var i=this.getTileByID(n);a(t,i),a(i,t)}}function a(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,i=Math.pow(2,t.tileID.canonical.z),a=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(It(this._source.type)){for(var c={},u={},f=0,h=Object.keys(l);f<h.length;f+=1){var p=h[f],d=l[p],m=this._tiles[p];if(m&&!(m.fadeEndTime&&m.fadeEndTime<=t.browser.now())){var g=this.findLoadedParent(d,o);g&&(this._addTile(g.tileID),c[g.tileID.key]=g.tileID),u[p]=d}}for(var v in this._retainLoadedChildren(u,a,s,l),c)l[v]||(this._coveredTiles[v]=!0,l[v]=c[v])}for(var y in l)this._tiles[y].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}this._updateLoadedParentTileCache()}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},i={},a=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,c=t;l<c.length;l+=1){var u=c[l],f=this._addTile(u);n[u.key]=u,f.hasData()||e<this._source.maxzoom&&(s[u.key]=u)}this._retainLoadedChildren(s,e,o,n);for(var h=0,p=t;h<p.length;h+=1){var d=p[h],m=this._tiles[d.key];if(!m.hasData()){if(e+1>this._source.maxzoom){var g=d.children(this._source.maxzoom)[0],v=this.getTile(g);if(v&&v.hasData()){n[g.key]=g;continue}}else{var y=d.children(this._source.maxzoom);if(n[y[0].key]&&n[y[1].key]&&n[y[2].key]&&n[y[3].key])continue}for(var x=m.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(m=this.getTile(_))&&x&&(m=this._addTile(_)),m&&(n[_.key]=_,x=m.wasRequested(),m.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a<o.length;a+=1){var s=o[a];this._loadedParentTiles[s]=r}}},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event(\"dataloading\",{tile:r,coord:r.tileID,dataType:\"source\"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout((function(){r._reloadTile(t,\"expired\"),delete r._timers[t]}),n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),c=s.map((function(t){return o.pointCoordinate(t)})),u=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,m=0,g=c;m<g.length;m+=1){var v=g[m];f=Math.min(f,v.x),h=Math.min(h,v.y),p=Math.max(p,v.x),d=Math.max(d,v.y)}for(var y=function(e){var n=i._tiles[u[e]];if(!n.holdingForFade()){var s=n.tileID,m=Math.pow(2,o.zoom-n.tileID.overscaledZ),g=r*n.queryPadding*t.EXTENT/n.tileSize/m,v=[s.getTilePoint(new t.MercatorCoordinate(f,h)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(v[0].x-g<t.EXTENT&&v[0].y-g<t.EXTENT&&v[1].x+g>=0&&v[1].y+g>=0){var y=l.map((function(t){return s.getTilePoint(t)})),x=c.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:y,cameraQueryGeometry:x,scale:m})}}},x=0;x<u.length;x++)y(x);return a},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map((function(t){return e._tiles[t].tileID})),n=0,i=r;n<i.length;n+=1){var a=i[n];a.posMatrix=this.transform.calculatePosMatrix(a.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(It(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||\"_geojsonTileLayer\",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles){this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\")}this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function Pt(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function It(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function Ot(){return new t.window.Worker(Zi.workerUrl)}Ct.maxOverzooming=10,Ct.maxUnderzooming=3;var zt=\"mapboxgl_preloaded_worker_pool\",Dt=function(){this.active={}};Dt.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<Dt.workerCount;)this.workers.push(new Ot);return this.active[t]=!0,this.workers.slice()},Dt.prototype.release=function(t){delete this.active[t],0===this.numActive()&&(this.workers.forEach((function(t){t.terminate()})),this.workers=null)},Dt.prototype.isPreloaded=function(){return!!this.active[zt]},Dt.prototype.numActive=function(){return Object.keys(this.active).length};var Rt,Ft=Math.floor(t.browser.hardwareConcurrency/2);function Bt(){return Rt||(Rt=new Dt),Rt}function Nt(e,r){var n={};for(var i in e)\"ref\"!==i&&(n[i]=e[i]);return t.refProperties.forEach((function(t){t in r&&(n[t]=r[t])})),n}function jt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)\"ref\"in t[n]&&(t[n]=Nt(t[n],e[t[n].ref]));return t}Dt.workerCount=Math.max(Math.min(Ft,6),1);var Ut={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function Vt(t,e,r){r.push({command:Ut.addSource,args:[t,e[t]]})}function qt(t,e,r){e.push({command:Ut.removeSource,args:[t]}),r[t]=!0}function Ht(t,e,r,n){qt(t,r,n),Vt(t,e,r)}function Gt(e,r,n){var i;for(i in e[n])if(e[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;for(i in r[n])if(r[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;return!0}function Yt(e,r,n,i,a,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}))}function Wt(t){return t.id}function Xt(t,e){return t[e.id]=e,t}function Zt(e,r){if(!e)return[{command:Ut.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:Ut.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:Ut.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:Ut.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:Ut.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:Ut.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:Ut.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:Ut.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:Ut.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:Ut.setLight,args:[r.light]});var i={},a=[];!function(e,r,n,i){var a;for(a in r=r||{},e=e||{})e.hasOwnProperty(a)&&(r.hasOwnProperty(a)||qt(a,n,i));for(a in r)r.hasOwnProperty(a)&&(e.hasOwnProperty(a)?t.deepEqual(e[a],r[a])||(\"geojson\"===e[a].type&&\"geojson\"===r[a].type&&Gt(e,r,a)?n.push({command:Ut.setGeoJSONSourceData,args:[a,r[a].data]}):Ht(a,r,n,i)):Vt(a,r,n))}(e.sources,r.sources,a,i);var o=[];e.layers&&e.layers.forEach((function(t){i[t.source]?n.push({command:Ut.removeLayer,args:[t.id]}):o.push(t)})),n=n.concat(a),function(e,r,n){r=r||[];var i,a,o,s,l,c,u,f=(e=e||[]).map(Wt),h=r.map(Wt),p=e.reduce(Xt,{}),d=r.reduce(Xt,{}),m=f.slice(),g=Object.create(null);for(i=0,a=0;i<f.length;i++)o=f[i],d.hasOwnProperty(o)?a++:(n.push({command:Ut.removeLayer,args:[o]}),m.splice(m.indexOf(o,a),1));for(i=0,a=0;i<h.length;i++)o=h[h.length-1-i],m[m.length-1-i]!==o&&(p.hasOwnProperty(o)?(n.push({command:Ut.removeLayer,args:[o]}),m.splice(m.lastIndexOf(o,m.length-a),1)):a++,c=m[m.length-i],n.push({command:Ut.addLayer,args:[d[o],c]}),m.splice(m.length-i,0,o),g[o]=!0);for(i=0;i<h.length;i++)if(s=p[o=h[i]],l=d[o],!g[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s[\"source-layer\"],l[\"source-layer\"])&&t.deepEqual(s.type,l.type)){for(u in Yt(s.layout,l.layout,n,o,null,Ut.setLayoutProperty),Yt(s.paint,l.paint,n,o,null,Ut.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:Ut.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:Ut.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}));for(u in l)l.hasOwnProperty(u)&&!s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}))}else n.push({command:Ut.removeLayer,args:[o]}),c=m[m.lastIndexOf(o)+1],n.push({command:Ut.addLayer,args:[l,c]})}(o,r.layers,n)}catch(t){console.warn(\"Unable to compute style diff:\",t),n=[{command:Ut.setStyle,args:[r]}]}return n}var Jt=function(t,e){this.reset(t,e)};Jt.prototype.reset=function(t,e){this.points=t||[],this._distances=[0];for(var r=1;r<this.points.length;r++)this._distances[r]=this._distances[r-1]+this.points[r].dist(this.points[r-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(e||0,.5*this.length),this.paddedLength=this.length-2*this.padding},Jt.prototype.lerp=function(e){if(1===this.points.length)return this.points[0];e=t.clamp(e,0,1);for(var r=1,n=this._distances[r],i=e*this.paddedLength+this.padding;n<i&&r<this._distances.length;)n=this._distances[++r];var a=r-1,o=this._distances[a],s=n-o,l=s>0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Kt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a<this.xCellCount*this.yCellCount;a++)n.push([]),i.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function Qt(e,r,n,i,a){var o=t.create();return r?(t.scale(o,o,[1/a,1/a,1]),n||t.rotateZ(o,o,i.angle)):t.multiply(o,i.labelPlaneMatrix,e),o}function $t(e,r,n,i,a){if(r){var o=t.clone(e);return t.scale(o,o,[a,a,1]),n||t.rotateZ(o,o,-i.angle),o}return i.glCoordMatrix}function te(e,r){var n=[e.x,e.y,0,1];fe(n,n,r);var i=n[3];return{point:new t.Point(n[0]/i,n[1]/i),signedDistanceFromCamera:i}}function ee(t,e){return.5+t/e*.5}function re(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ne(e,r,n,i,a,o,s,l){var c=i?e.textSizeData:e.iconSizeData,u=t.evaluateSizeForZoom(c,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,m=n.transform.width/n.transform.height,g=!1,v=0;v<d.length;v++){var y=d.get(v);if(y.hidden||y.writingMode===t.WritingMode.vertical&&!g)ue(y.numGlyphs,h);else{g=!1;var x=[y.anchorX,y.anchorY,0,1];if(t.transformMat4(x,x,r),re(x,f)){var b=x[3],_=ee(n.transform.cameraToCenterDistance,b),w=t.evaluateSizeForFeature(c,u,y),T=s?w/_:w*_,k=new t.Point(y.anchorX,y.anchorY),M=te(k,a).point,A={},S=oe(y,T,!1,l,r,a,o,e.glyphOffsetArray,p,h,M,k,A,m);g=S.useVertical,(S.notEnoughRoom||g||S.needsFlipping&&oe(y,T,!0,l,r,a,o,e.glyphOffsetArray,p,h,M,k,A,m).notEnoughRoom)&&ue(y.numGlyphs,h)}else ue(y.numGlyphs,h)}}i?e.text.dynamicLayoutVertexBuffer.updateData(h):e.icon.dynamicLayoutVertexBuffer.updateData(h)}function ie(t,e,r,n,i,a,o,s,l,c,u){var f=s.glyphStartIndex+s.numGlyphs,h=s.lineStartIndex,p=s.lineStartIndex+s.lineLength,d=e.getoffsetX(s.glyphStartIndex),m=e.getoffsetX(f-1),g=le(t*d,r,n,i,a,o,s.segment,h,p,l,c,u);if(!g)return null;var v=le(t*m,r,n,i,a,o,s.segment,h,p,l,c,u);return v?{first:g,last:v}:null}function ae(e,r,n,i){if(e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*i)return{useVertical:!0};return(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function oe(e,r,n,i,a,o,s,l,c,u,f,h,p,d){var m,g=r/24,v=e.lineOffsetX*g,y=e.lineOffsetY*g;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=ie(g,l,v,y,n,f,h,e,c,o,p);if(!w)return{notEnoughRoom:!0};var T=te(w.first.point,s).point,k=te(w.last.point,s).point;if(i&&!n){var M=ae(e.writingMode,T,k,d);if(M)return M}m=[w.first];for(var A=e.glyphStartIndex+1;A<x-1;A++)m.push(le(g*l.getoffsetX(A),v,y,n,f,h,e.segment,b,_,c,o,p));m.push(w.last)}else{if(i&&!n){var S=te(h,a).point,E=e.lineStartIndex+e.segment+1,L=new t.Point(c.getx(E),c.gety(E)),C=te(L,a),P=C.signedDistanceFromCamera>0?C.point:se(h,L,S,1,a),I=ae(e.writingMode,S,P,d);if(I)return I}var O=le(g*l.getoffsetX(e.glyphStartIndex),v,y,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,c,o,p);if(!O)return{notEnoughRoom:!0};m=[O]}for(var z=0,D=m;z<D.length;z+=1){var R=D[z];t.addDynamicAttributes(u,R.point,R.angle)}return{}}function se(t,e,r,n,i){var a=te(t.add(t.sub(e)._unit()),i).point,o=r.sub(a);return r.add(o._mult(n/o.mag()))}function le(e,r,n,i,a,o,s,l,c,u,f,h){var p=i?e-r:e+r,d=p>0?1:-1,m=0;i&&(d*=-1,m=Math.PI),d<0&&(m+=Math.PI);for(var g=d>0?l+s:l+s+1,v=a,y=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((g+=d)<l||g>=c)return null;if(y=v,w.push(v),void 0===(v=h[g])){var T=new t.Point(u.getx(g),u.gety(g)),k=te(T,f);if(k.signedDistanceFromCamera>0)v=h[g]=k.point;else{var M=g-d;v=se(0===x?o:new t.Point(u.getx(M),u.gety(M)),T,y,_-x+1,f)}}x+=b,b=y.dist(v)}var A=(_-x)/b,S=v.sub(y),E=S.mult(A)._add(y);E._add(S._unit()._perp()._mult(n*d));var L=m+Math.atan2(v.y-y.y,v.x-y.x);return w.push(E),{point:E,angle:L,path:w}}Kt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Kt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Kt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Kt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Kt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Kt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var c=this.circles[3*l],u=this.circles[3*l+1],f=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:c-f,y1:u-f,x2:c+f,y2:u+f})}return a?o.filter(a):o}var h={hitTest:i,seenUids:{box:{},circle:{}}};return this._forEachCell(t,e,r,n,this._queryCell,o,h,a),i?o.length>0:o},Kt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var c=[],u={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,c,u,i),n?c.length>0:c},Kt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Kt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Kt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Kt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,c=this.boxCells[i];if(null!==c)for(var u=this.bboxes,f=0,h=c;f<h.length;f+=1){var p=h[f];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=u[d+2]&&e<=u[d+3]&&r>=u[d+0]&&n>=u[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:u[d],y1:u[d+1],x2:u[d+2],y2:u[d+3]})}}}var m=this.circleCells[i];if(null!==m)for(var g=this.circles,v=0,y=m;v<y.length;v+=1){var x=y[v];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(g[b],g[b+1],g[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return a.push(!0),!0;var _=g[b],w=g[b+1],T=g[b+2];a.push({key:this.circleKeys[x],x1:_-T,y1:w-T,x2:_+T,y2:w+T})}}}},Kt.prototype._queryCellCircle=function(t,e,r,n,i,a,o,s){var l=o.circle,c=o.seenUids,u=this.boxCells[i];if(null!==u)for(var f=this.bboxes,h=0,p=u;h<p.length;h+=1){var d=p[h];if(!c.box[d]){c.box[d]=!0;var m=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,f[m+0],f[m+1],f[m+2],f[m+3])&&(!s||s(this.boxKeys[d])))return a.push(!0),!0}}var g=this.circleCells[i];if(null!==g)for(var v=this.circles,y=0,x=g;y<x.length;y+=1){var b=x[y];if(!c.circle[b]){c.circle[b]=!0;var _=3*b;if(this._circlesCollide(v[_],v[_+1],v[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return a.push(!0),!0}}},Kt.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToXCellCoord(t),c=this._convertToYCellCoord(e),u=this._convertToXCellCoord(r),f=this._convertToYCellCoord(n),h=l;h<=u;h++)for(var p=c;p<=f;p++){var d=this.xCellCount*p+h;if(i.call(this,t,e,r,n,d,a,o,s))return}},Kt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Kt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Kt.prototype._circlesCollide=function(t,e,r,n,i,a){var o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s},Kt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var c=(o-i)/2,u=Math.abs(e-(i+c));if(u>c+r)return!1;if(l<=s||u<=c)return!0;var f=l-s,h=u-c;return f*f+h*h<=r*r};var ce=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ue(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(ce,3*n)}}function fe(t,e,r){var n=e[0],i=e[1];return t[0]=r[0]*n+r[4]*i+r[12],t[1]=r[1]*n+r[5]*i+r[13],t[3]=r[3]*n+r[7]*i+r[15],t}var he=function(t,e,r){void 0===e&&(e=new Kt(t.width+200,t.height+200,25)),void 0===r&&(r=new Kt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+100,this.screenBottomBoundary=t.height+100,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function pe(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}he.prototype.placeCollisionBox=function(t,e,r,n,i){var a=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*a.perspectiveRatio,s=t.x1*o+a.point.x,l=t.y1*o+a.point.y,c=t.x2*o+a.point.x,u=t.y2*o+a.point.y;return!this.isInsideGrid(s,l,c,u)||!e&&this.grid.hitTest(s,l,c,u,i)?{box:[],offscreen:!1}:{box:[s,l,c,u],offscreen:this.isOffscreen(s,l,c,u)}},he.prototype.placeCollisionCircles=function(e,r,n,i,a,o,s,l,c,u,f,h,p){var d=[],m=new t.Point(r.anchorX,r.anchorY),g=te(m,o),v=ee(this.transform.cameraToCenterDistance,g.signedDistanceFromCamera),y=(u?a/v:a*v)/t.ONE_EM,x=te(m,s).point,b=ie(y,i,r.lineOffsetX*y,r.lineOffsetY*y,!1,x,m,r,n,s,{}),_=!1,w=!1,T=!0;if(b){for(var k=.5*h*v+p,M=new t.Point(-100,-100),A=new t.Point(this.screenRightBoundary,this.screenBottomBoundary),S=new Jt,E=b.first,L=b.last,C=[],P=E.path.length-1;P>=1;P--)C.push(E.path[P]);for(var I=1;I<L.path.length;I++)C.push(L.path[I]);var O=2.5*k;if(l){var z=C.map((function(t){return te(t,l)}));C=z.some((function(t){return t.signedDistanceFromCamera<=0}))?[]:z.map((function(t){return t.point}))}var D=[];if(C.length>0){for(var R=C[0].clone(),F=C[0].clone(),B=1;B<C.length;B++)R.x=Math.min(R.x,C[B].x),R.y=Math.min(R.y,C[B].y),F.x=Math.max(F.x,C[B].x),F.y=Math.max(F.y,C[B].y);D=R.x>=M.x&&F.x<=A.x&&R.y>=M.y&&F.y<=A.y?[C]:F.x<M.x||R.x>A.x||F.y<M.y||R.y>A.y?[]:t.clipLine([C],M.x,M.y,A.x,A.y)}for(var N=0,j=D;N<j.length;N+=1){var U=j[N];S.reset(U,.25*k);var V=0;V=S.length<=.5*k?1:Math.ceil(S.paddedLength/O)+1;for(var q=0;q<V;q++){var H=q/Math.max(V-1,1),G=S.lerp(H),Y=G.x+100,W=G.y+100;d.push(Y,W,k,0);var X=Y-k,Z=W-k,J=Y+k,K=W+k;if(T=T&&this.isOffscreen(X,Z,J,K),w=w||this.isInsideGrid(X,Z,J,K),!e&&this.grid.hitTestCircle(Y,W,k,f)&&(_=!0,!c))return{circles:[],offscreen:!1,collisionDetected:_}}}}return{circles:!c&&_||!w?[]:d,offscreen:T,collisionDetected:_}},he.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,i=1/0,a=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var c=l[s],u=new t.Point(c.x+100,c.y+100);n=Math.min(n,u.x),i=Math.min(i,u.y),a=Math.max(a,u.x),o=Math.max(o,u.y),r.push(u)}for(var f={},h={},p=0,d=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o));p<d.length;p+=1){var m=d[p],g=m.key;if(void 0===f[g.bucketInstanceId]&&(f[g.bucketInstanceId]={}),!f[g.bucketInstanceId][g.featureIndex]){var v=[new t.Point(m.x1,m.y1),new t.Point(m.x2,m.y1),new t.Point(m.x2,m.y2),new t.Point(m.x1,m.y2)];t.polygonIntersectsPolygon(r,v)&&(f[g.bucketInstanceId][g.featureIndex]=!0,void 0===h[g.bucketInstanceId]&&(h[g.bucketInstanceId]=[]),h[g.bucketInstanceId].push(g.featureIndex))}}return h},he.prototype.insertCollisionBox=function(t,e,r,n,i){var a={bucketInstanceId:r,featureIndex:n,collisionGroupID:i};(e?this.ignoredGrid:this.grid).insert(a,t[0],t[1],t[2],t[3])},he.prototype.insertCollisionCircles=function(t,e,r,n,i){for(var a=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:i},s=0;s<t.length;s+=4)a.insertCircle(o,t[s],t[s+1],t[s+2])},he.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var i=[r,n,0,1];return fe(i,i,e),{point:new t.Point((i[0]/i[3]+1)/2*this.transform.width+100,(-i[1]/i[3]+1)/2*this.transform.height+100),perspectiveRatio:.5+this.transform.cameraToCenterDistance/i[3]*.5}},he.prototype.isOffscreen=function(t,e,r,n){return r<100||t>=this.screenRightBoundary||n<100||e>this.screenBottomBoundary},he.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary},he.prototype.getViewportMatrix=function(){var e=t.identity([]);return t.translate(e,e,[-100,-100,0]),e};var de=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};de.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var me=function(t,e,r,n,i){this.text=new de(t?t.text:null,e,r,i),this.icon=new de(t?t.icon:null,e,n,i)};me.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var ge=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},ve=function(){this.invProjMatrix=t.create(),this.viewportMatrix=t.create(),this.circles=[]},ye=function(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i},xe=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function be(e,r,n,i,a){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,c=t.evaluateVariableOffset(e,i);return new t.Point(s+c[0]*a,l+c[1]*a)}function _e(e,r,n,i,a,o){var s=e.x1,l=e.x2,c=e.y1,u=e.y2,f=e.anchorPointX,h=e.anchorPointY,p=new t.Point(r,n);return i&&p._rotate(a?o:-o),{x1:s+p.x,y1:c+p.y,x2:l+p.x,y2:u+p.y,anchorPointX:f,anchorPointY:h}}xe.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var we=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new he(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new xe(r),this.collisionCircleArrays={},this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function Te(t,e,r,n,i){t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0)}we.prototype.getBucketParts=function(e,r,n,i){var a=n.getBucket(r),o=n.latestFeatureIndex;if(a&&o&&r.id===a.layerIds[0]){var s=n.collisionBoxArray,l=a.layers[0].layout,c=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),u=n.tileSize/t.EXTENT,f=this.transform.calculatePosMatrix(n.tileID.toUnwrapped()),h=\"map\"===l.get(\"text-pitch-alignment\"),p=\"map\"===l.get(\"text-rotation-alignment\"),d=pe(n,1,this.transform.zoom),m=Qt(f,h,p,this.transform,d),g=null;if(h){var v=$t(f,h,p,this.transform,d);g=t.multiply([],this.transform.labelPlaneMatrix,v)}this.retainedQueryData[a.bucketInstanceId]=new ye(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,n.tileID);var y={bucket:a,layout:l,posMatrix:f,textLabelPlaneMatrix:m,labelToScreenMatrix:g,scale:c,textPixelRatio:u,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:t.evaluateSizeForZoom(a.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(a.sourceID)};if(i)for(var x=0,b=a.sortKeyRanges;x<b.length;x+=1){var _=b[x],w=_.sortKey,T=_.symbolInstanceStart,k=_.symbolInstanceEnd;e.push({sortKey:w,symbolInstanceStart:T,symbolInstanceEnd:k,parameters:y})}else e.push({symbolInstanceStart:0,symbolInstanceEnd:a.symbolInstances.length,parameters:y})}},we.prototype.attemptAnchorPlacement=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d){var m,g=[f.textOffset0,f.textOffset1],v=be(t,r,n,g,i),y=this.collisionIndex.placeCollisionBox(_e(e,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate);if(d&&0===this.collisionIndex.placeCollisionBox(_e(d,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate).box.length)return;if(y.box.length>0)return this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(m=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:g,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:m},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:v,placedGlyphBoxes:y}},we.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,c=a.textLabelPlaneMatrix,u=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,m=a.collisionGroup,g=s.get(\"text-optional\"),v=s.get(\"icon-optional\"),y=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=y&&(x||!o.hasIconData()||v),M=x&&(y||!o.hasTextData()||g);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var A=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new ge(!1,!1,!1);else{var p,T=!1,A=!1,S=!0,E=null,L={box:null,offscreen:null},C={box:null,offscreen:null},P=null,I=null,O=0,z=0,D=0;a.textFeatureIndex?O=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(O=e.featureIndex),a.verticalTextFeatureIndex&&(z=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i<s.length;i+=1){if(s[i]===t.WritingMode.vertical?(L=n(),C=L):L=r(),L&&L.box&&L.box.length)break}else L=r()};if(s.get(\"text-variable-anchor\")){var N=s.get(\"text-variable-anchor\");if(i.prevPlacement&&i.prevPlacement.variableOffsets[e.crossTileID]){var j=i.prevPlacement.variableOffsets[e.crossTileID];N.indexOf(j.anchor)>0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,c=e.textBoxScale,u=w&&!x?r:null,h={box:[],offscreen:!1},p=y?2*N.length:N.length,d=0;d<p;++d){var g=N[d%N.length],v=d>=N.length,k=i.attemptAnchorPlacement(g,t,a,s,c,b,_,f,l,m,v,e,o,n,u);if(k&&(h=k.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=k.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=L&&L.box&&L.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),L&&(T=L.box,S=L.offscreen);var V=F(L&&L.box);if(!T&&i.prevPlacement){var q=i.prevPlacement.variableOffsets[e.crossTileID];q&&(i.variableOffsets[e.crossTileID]=q,i.markUsedJustification(o,q.anchor,e,V))}}else{var H=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,y,f,l,m.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return H(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?H(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(L&&L.box&&L.box.length)}}if(T=(p=L)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),Y=t.evaluateSizeForFeature(o.textSizeData,d,G),W=s.get(\"text-padding\"),X=e.collisionCircleDiameter;P=i.collisionIndex.placeCollisionCircles(y,G,o.lineVertexArray,o.glyphOffsetArray,Y,l,c,u,n,_,m.predicate,X,W),T=y||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(a.iconFeatureIndex&&(D=a.iconFeatureIndex),a.iconBox){var Z=function(t){var e=w&&E?_e(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,m.predicate)};A=C&&C.box&&C.box.length&&a.verticalIconBox?(I=Z(a.verticalIconBox)).box.length>0:(I=Z(a.iconBox)).box.length>0,S=S&&I.offscreen}var J=g||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,K=v||0===e.numIconVertices;if(J||K?K?J||(A=A&&T):T=A&&T:A=T=A&&T,T&&p&&p.box&&(C&&C.box&&z?i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,z,m.ID):i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,O,m.ID)),A&&I&&i.collisionIndex.insertCollisionBox(I.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,D,m.ID),P&&(T&&i.collisionIndex.insertCollisionCircles(P.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,O,m.ID),n)){var Q=o.bucketInstanceId,$=i.collisionCircleArrays[Q];void 0===$&&($=i.collisionCircleArrays[Q]=new ve);for(var tt=0;tt<P.circles.length;tt+=4)$.circles.push(P.circles[tt+0]),$.circles.push(P.circles[tt+1]),$.circles.push(P.circles[tt+2]),$.circles.push(P.collisionDetected?1:0)}i.placements[e.crossTileID]=new ge(T||k,A||M,S||o.justReloaded),r[e.crossTileID]=!0}};if(T)for(var S=o.getSortedSymbolIndexes(this.transform.angle),E=S.length-1;E>=0;--E){var L=S[E];A(o.symbolInstances.get(L),o.collisionArrays[L])}else for(var C=e.symbolInstanceStart;C<e.symbolInstanceEnd;C++)A(o.symbolInstances.get(C),o.collisionArrays[C]);if(n&&o.bucketInstanceId in this.collisionCircleArrays){var P=this.collisionCircleArrays[o.bucketInstanceId];t.invert(P.invProjMatrix,l),P.viewportMatrix=this.collisionIndex.getViewportMatrix()}o.justReloaded=!1},we.prototype.markUsedJustification=function(e,r,n,i){var a,o={left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex};a=i===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:o[t.getAnchorJustification(r)];for(var s=0,l=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];s<l.length;s+=1){var c=l[s];c>=0&&(e.text.placedSymbolArray.get(c).crossTileID=a>=0&&c!==a?0:n.crossTileID)}},we.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1){var l=s[o];e.text.placedSymbolArray.get(l).placedOrientation=i}n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=a)},we.prototype.commit=function(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;var e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;var n=e?e.symbolFadeChange(t):1,i=e?e.opacities:{},a=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],c=i[s];c?(this.opacities[s]=new me(c,n,l.text,l.icon),r=r||l.text!==c.text.placed||l.icon!==c.icon.placed):(this.opacities[s]=new me(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var u in i){var f=i[u];if(!this.opacities[u]){var h=new me(f,n,!1,!1);h.isHidden()||(this.opacities[u]=h,r=r||f.text.placed||f.icon.placed)}}for(var p in a)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=a[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:\"number\"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},we.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.getBucket(t);o&&a.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,a.collisionBoxArray)}},we.prototype.updateBucketOpacities=function(e,r,n){var i=this;e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexArray.clear(),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexArray.clear();var a=e.layers[0].layout,o=new me(null,0,!1,!1,!0),s=a.get(\"text-allow-overlap\"),l=a.get(\"icon-allow-overlap\"),c=a.get(\"text-variable-anchor\"),u=\"map\"===a.get(\"text-rotation-alignment\"),f=\"map\"===a.get(\"text-pitch-alignment\"),h=\"none\"!==a.get(\"icon-text-fit\"),p=new me(null,0,s&&(l||!e.hasIconData()||a.get(\"icon-optional\")),l&&(s||!e.hasTextData()||a.get(\"text-optional\")),!0);!e.collisionArrays&&n&&(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData())&&e.deserializeCollisionBoxes(n);for(var d=function(t,e,r){for(var n=0;n<e/4;n++)t.opacityVertexArray.emplaceBack(r)},m=function(n){var a=e.symbolInstances.get(n),s=a.numHorizontalGlyphVertices,l=a.numVerticalGlyphVertices,m=a.crossTileID,g=r[m],v=i.opacities[m];g?v=o:v||(v=p,i.opacities[m]=v),r[m]=!0;var y=s>0||l>0,x=a.numIconVertices>0,b=i.placedOrientations[a.crossTileID],_=b===t.WritingMode.vertical,w=b===t.WritingMode.horizontal||b===t.WritingMode.horizontalOnly;if(y){var T=Pe(v.text),k=_?Ie:T;d(e.text,s,k);var M=w?Ie:T;d(e.text,l,M);var A=v.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=A||_?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=A||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,b);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,\"left\",a,E),i.markUsedOrientation(e,E,a))}if(x){var L=Pe(v.icon),C=!(h&&a.verticalPlacedIconSymbolIndex&&_);if(a.placedIconSymbolIndex>=0){var P=C?L:Ie;d(e.icon,a.numIconVertices,P),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=v.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var I=C?Ie:L;d(e.icon,a.numVerticalIconVertices,I),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=v.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var O=e.collisionArrays[n];if(O){var z=new t.Point(0,0);if(O.textBox||O.verticalTextBox){var D=!0;if(c){var R=i.variableOffsets[m];R?(z=be(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),u&&z._rotate(f?i.transform.angle:-i.transform.angle)):D=!1}O.textBox&&Te(e.textCollisionBox.collisionVertexArray,v.text.placed,!D||_,z.x,z.y),O.verticalTextBox&&Te(e.textCollisionBox.collisionVertexArray,v.text.placed,!D||w,z.x,z.y)}var F=Boolean(!w&&O.verticalIconBox);O.iconBox&&Te(e.iconCollisionBox.collisionVertexArray,v.icon.placed,F,h?z.x:0,h?z.y:0),O.verticalIconBox&&Te(e.iconCollisionBox.collisionVertexArray,v.icon.placed,!F,h?z.x:0,h?z.y:0)}}},g=0;g<e.symbolInstances.length;g++)m(g);if(e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexBuffer&&e.iconCollisionBox.collisionVertexBuffer.updateData(e.iconCollisionBox.collisionVertexArray),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexBuffer&&e.textCollisionBox.collisionVertexBuffer.updateData(e.textCollisionBox.collisionVertexArray),e.bucketInstanceId in this.collisionCircleArrays){var v=this.collisionCircleArrays[e.bucketInstanceId];e.placementInvProjMatrix=v.invProjMatrix,e.placementViewportMatrix=v.viewportMatrix,e.collisionCircleArray=v.circles,delete this.collisionCircleArrays[e.bucketInstanceId]}},we.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},we.prototype.zoomAdjustment=function(t){return Math.max(0,(this.transform.zoom-t)/1.5)},we.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},we.prototype.stillRecent=function(t,e){var r=this.zoomAtLastRecencyCheck===e?1-this.zoomAdjustment(e):1;return this.zoomAtLastRecencyCheck=e,this.commitTime+this.fadeDuration*r>t},we.prototype.setStale=function(){this.stale=!0};var ke=Math.pow(2,25),Me=Math.pow(2,24),Ae=Math.pow(2,17),Se=Math.pow(2,16),Ee=Math.pow(2,9),Le=Math.pow(2,8),Ce=Math.pow(2,1);function Pe(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*ke+e*Me+r*Ae+e*Se+r*Ee+e*Le+r*Ce+e}var Ie=0,Oe=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Oe.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex<t.length;){var o=t[this._currentTileIndex];if(e.getBucketParts(a,n,o,this._sortAcrossTiles),this._currentTileIndex++,i())return!0}for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,a.sort((function(t,e){return t.sortKey-e.sortKey})));this._currentPartIndex<a.length;){var s=a[this._currentPartIndex];if(e.placeLayerBucketPart(s,this._seenCrossTileIDs,r),this._currentPartIndex++,i())return!0}return!1};var ze=function(t,e,r,n,i,a,o){this.placement=new we(t,i,a,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};ze.prototype.isDone=function(){return this._done},ze.prototype.continuePlacement=function(e,r,n){for(var i=this,a=t.browser.now(),o=function(){var e=t.browser.now()-a;return!i._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Oe(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},ze.prototype.commit=function(t){return this.placement.commit(t),this.placement};var De=512/t.EXTENT/2,Re=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var i=e.get(n),a=i.key;this.indexedSymbolInstances[a]||(this.indexedSymbolInstances[a]=[]),this.indexedSymbolInstances[a].push({crossTileID:i.crossTileID,coord:this.getScaledCoordinates(i,t)})}};Re.prototype.getScaledCoordinates=function(e,r){var n=r.canonical.z-this.tileID.canonical.z,i=De/Math.pow(2,n);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*i),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*i)}},Re.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),i=0;i<t.length;i++){var a=t.get(i);if(!a.crossTileID){var o=this.indexedSymbolInstances[a.key];if(o)for(var s=this.getScaledCoordinates(a,e),l=0,c=o;l<c.length;l+=1){var u=c[l];if(Math.abs(u.coord.x-s.x)<=n&&Math.abs(u.coord.y-s.y)<=n&&!r[u.crossTileID]){r[u.crossTileID]=!0,a.crossTileID=u.crossTileID;break}}}}};var Fe=function(){this.maxCrossTileID=0};Fe.prototype.generate=function(){return++this.maxCrossTileID};var Be=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Be.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],i={};for(var a in n){var o=n[a];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),i[o.tileID.key]=o}this.indexes[r]=i}this.lng=t},Be.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++){e.symbolInstances.get(n).crossTileID=0}this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var i=this.usedCrossTileIDs[t.overscaledZ];for(var a in this.indexes){var o=this.indexes[a];if(Number(a)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var c=o[t.scaledTo(Number(a)).key];c&&c.findMatches(e.symbolInstances,t,i)}}for(var u=0;u<e.symbolInstances.length;u++){var f=e.symbolInstances.get(u);f.crossTileID||(f.crossTileID=r.generate(),i[f.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new Re(t,e.symbolInstances,e.bucketInstanceId),!0},Be.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,i=e.indexedSymbolInstances[r];n<i.length;n+=1){var a=i[n];delete this.usedCrossTileIDs[t][a.crossTileID]}},Be.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var i in n)t[n[i].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[i]),delete n[i],e=!0)}return e};var Ne=function(){this.layerIndexes={},this.crossTileIDs=new Fe,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Ne.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Be);var i=!1,a={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],c=l.getBucket(t);c&&t.id===c.layerIds[0]&&(c.bucketInstanceId||(c.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,c,this.crossTileIDs)&&(i=!0),a[c.bucketInstanceId]=!0)}return n.removeStaleBuckets(a)&&(i=!0),i},Ne.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach((function(t){e[t]=!0})),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var je=function(e,r){return t.emitValidationErrors(e,r&&r.filter((function(t){return\"source.canvas\"!==t.identifier})))},Ue=t.pick(Ut,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),Ve=t.pick(Ut,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),qe=function(){var e={},r=t.styleSpec.$version;for(var n in t.styleSpec.$root){var i=t.styleSpec.$root[n];if(i.required){var a=null;null!=(a=\"version\"===n?r:\"array\"===i.type?[]:{})&&(e[n]=a)}}return e}(),He=function(e){function r(n,i){var a=this;void 0===i&&(i={}),e.call(this),this.map=n,this.dispatcher=new k(Bt(),this),this.imageManager=new h,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,i.localIdeographFontFamily),this.lineAtlas=new T(256,512),this.crossTileSymbolIndex=new Ne,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast(\"setReferrer\",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginStateChange((function(e){var r={pluginStatus:e.pluginStatus,pluginURL:e.pluginURL};o.dispatcher.broadcast(\"syncRTLPluginState\",r,(function(e,r){if((t.triggerPluginCompletionEvent(e),r)&&r.every((function(t){return t})))for(var n in o.sourceCaches)o.sourceCaches[n].reload()}))})),this.on(\"data\",(function(t){if(\"source\"===t.dataType&&\"metadata\"===t.sourceDataType){var e=a.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in a._layers){var i=a._layers[n];i.source===r.id&&a._validateLayer(i)}}}}))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"}));var i=\"boolean\"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var a=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(a,(function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,i)}))},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._request=t.browser.frame((function(){n._request=null,n._load(e,!1!==r.validate)}))},r.prototype.loadEmpty=function(){this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._load(qe,!1)},r.prototype._load=function(e,r){if(!r||!je(this,t.validateStyle(e))){for(var n in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(n,e.sources[n],{validate:!1});e.sprite?this._loadSprite(e.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var i=jt(this.stylesheet.layers);this._order=i.map((function(t){return t.id})),this._layers={},this._serializedLayers={};for(var a=0,o=i;a<o.length;a+=1){var s=o[a];(s=t.createStyleLayer(s)).setEventedParent(this,{layer:{id:s.id}}),this._layers[s.id]=s,this._serializedLayers[s.id]=s.serialize()}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new w(this.stylesheet.light),this.fire(new t.Event(\"data\",{dataType:\"style\"})),this.fire(new t.Event(\"style.load\"))}},r.prototype._loadSprite=function(e){var r=this;this._spriteRequest=function(e,r,n){var i,a,o,s=t.browser.devicePixelRatio>1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,u())})),c=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){c=null,o||(o=t,a=e,u())}));function u(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],c=l.width,u=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,m=l.stretchX,g=l.stretchY,v=l.content,y=new t.RGBAImage({width:c,height:u});t.RGBAImage.copy(e,y,{x:f,y:h},{x:0,y:0},{width:c,height:u}),r[s]={data:y,pixelRatio:d,sdf:p,stretchX:m,stretchY:g,content:v}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),c&&(c.cancel(),c=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=this._layers[i];\"custom\"!==a.type&&e.push(a.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),i=Object.keys(this._removedLayers);for(var a in(n.length||i.length)&&this._updateWorkerLayers(n,i),this._updatedSources){var o=this._updatedSources[a];\"reload\"===o?this._reloadSource(a):\"clear\"===o&&this._clearSource(a)}for(var s in this._updateTilesForChangedImages(),this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}for(var l in this.sourceCaches)this.sourceCaches[l].used=!1;for(var c=0,u=this._order;c<u.length;c+=1){var f=u[c],h=this._layers[f];h.recalculate(e,this._availableImages),!h.isHidden(e.zoom)&&h.source&&(this.sourceCaches[h.source].used=!0)}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event(\"data\",{dataType:\"style\"}))}},r.prototype._updateTilesForChangedImages=function(){var t=Object.keys(this._changedImages);if(t.length){for(var e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies([\"icons\",\"patterns\"],t);this._changedImages={}}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),je(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=jt(e.layers);var n=Zt(this.serialize(),e).filter((function(t){return!(t.command in Ve)}));if(0===n.length)return!1;var i=n.filter((function(t){return!(t.command in Ue)}));if(i.length>0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0)||!this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n)){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Ct(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(je(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is requred to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s<l.length;s+=1){var c=l[s][o];if(c)for(var u=0,f=c;u<f.length;u+=1){var h=f[u];i.push(h)}}}}i.sort((function(t,e){return e.intersectionZ-t.intersectionZ}));for(var p=[],d=this._order.length-1;d>=0;d--){var m=this._order[d];if(r(m))for(var g=i.length-1;g>=0;g--){var v=i[g].feature;if(n[v.layer.id]<d)break;p.push(v),i.pop()}else for(var y=0,x=t;y<x.length;y+=1){var b=x[y][m];if(b)for(var _=0,w=b;_<w.length;_+=1){var T=w[_];p.push(T.feature)}}}return p},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,\"queryRenderedFeatures.filter\",r.filter,null,r);var i={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var a=0,o=r.layers;a<o.length;a+=1){var s=o[a],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error(\"The layer '\"+s+\"' does not exist in the map's style and cannot be queried for features.\"))),[];i[l.source]=!0}}var c=[];for(var u in r.availableImages=this._availableImages,this.sourceCaches)r.layers&&!i[u]||c.push(F(this.sourceCaches[u],this._layers,this._serializedLayers,e,r,n));return this.placement&&c.push(function(t,e,r,n,i,a,o){for(var s={},l=a.queryRenderedSymbols(n),c=[],u=0,f=Object.keys(l).map(Number);u<f.length;u+=1){var h=f[u];c.push(o[h])}c.sort(B);for(var p=function(){var r=m[d],n=r.featureIndex.lookupSymbolFeatures(l[r.bucketInstanceId],e,r.bucketIndex,r.sourceLayerIndex,i.filter,i.layers,i.availableImages,t);for(var a in n){var o=s[a]=s[a]||[],c=n[a];c.sort((function(t,e){var n=r.featureSortOrder;if(n){var i=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-i}return e.featureIndex-t.featureIndex}));for(var u=0,f=c;u<f.length;u+=1){var h=f[u];o.push(h)}}},d=0,m=c;d<m.length;d+=1)p();var g=function(e){s[e].forEach((function(n){var i=n.feature,a=t[e],o=r[a.source].getFeatureState(i.layer[\"source-layer\"],i.id);i.source=i.layer.source,i.layer[\"source-layer\"]&&(i.sourceLayer=i.layer[\"source-layer\"]),i.state=o}))};for(var v in s)g(v);return s}(this._layers,this._serializedLayers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(c)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,\"querySourceFeatures.filter\",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map((function(e){return t.getTileByID(e)})),n=[],i={},a=0;a<r.length;a++){var o=r[a],s=o.tileID.canonical.key;i[s]||(i[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called \"'+t+'\" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"loadWorkerSource\",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),i=!1;for(var a in e)if(!t.deepEqual(e[a],n[a])){i=!0;break}if(i){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,i,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&je(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},i)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off(\"pluginStateChange\",this._rtlTextPluginCallback),this._layers){this._layers[e].setEventedParent(null)}for(var r in this.sourceCaches)this.sourceCaches[r].clearTiles(),this.sourceCaches[r].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,i,a){void 0===a&&(a=!1);for(var o=!1,s=!1,l={},c=0,u=this._order;c<u.length;c+=1){var f=u[c],h=this._layers[f];if(\"symbol\"===h.type){if(!l[h.source]){var p=this.sourceCaches[h.source];l[h.source]=p.getRenderableIds(!0).map((function(t){return p.getTileByID(t)})).sort((function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)}))}var d=this.crossTileSymbolIndex.addLayer(h,l[h.source],e.center.lng);o=o||d}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((a=a||this._layerOrderChanged||0===n)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now(),e.zoom))&&(this.pauseablePlacement=new ze(e,this._order,a,r,n,i,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(var m=0,g=this._order;m<g.length;m+=1){var v=g[m],y=this._layers[v];\"symbol\"===y.type&&this.placement.updateLayerOpacities(y,l[y.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r),this._updateTilesForChangedImages();var n=this.sourceCaches[e.source];n&&n.setDependencies(e.tileID.key,e.type,e.icons)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);He.getSourceType=function(t){return D[t]},He.setSourceType=function(t,e){D[t]=e},He.registerForPluginStateChange=t.registerForPluginStateChange;var Ge=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Ye=yr(\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\",\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\"),We=yr(\"uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Xe=yr(\"uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\"),Ze=yr(\"varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main(void) {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}\"),Je=yr(\"void main() {gl_FragColor=vec4(1.0);}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Ke=yr(\"uniform highp float u_intensity;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main() {\\n#pragma mapbox: initialize highp float weight\\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#pragma mapbox: define mediump float radius\\nconst highp float ZERO=1.0/255.0/16.0;\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main(void) {\\n#pragma mapbox: initialize highp float weight\\n#pragma mapbox: initialize mediump float radius\\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}\"),Qe=yr(\"uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(0.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\"),$e=yr(\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),tr=yr(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd  =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz  /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),er=yr(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),rr=yr(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),nr=yr(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),ir=yr(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),ar=yr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),or=yr(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),sr=yr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),lr=yr(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),cr=yr(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),ur=yr(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),fr=yr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define MAX_LINE_DISTANCE 32767.0\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),hr=yr(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),pr=yr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),dr=yr(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),mr=yr(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),gr=yr(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),vr=yr(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function yr(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n={};return{fragmentSource:t=t.replace(r,(function(t,e,r,i,a){return n[a]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,i,a){var o=\"float\"===i?\"vec2\":\"vec4\",s=a.match(/color/)?\"color\":o;return n[a]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+a+\" = a_\"+a+\";\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = a_\"+a+\";\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"}))}}var xr=Object.freeze({__proto__:null,prelude:Ye,background:We,backgroundPattern:Xe,circle:Ze,clippingMask:Je,heatmap:Ke,heatmapTexture:Qe,collisionBox:$e,collisionCircle:tr,debug:er,fill:rr,fillOutline:nr,fillOutlinePattern:ir,fillPattern:ar,fillExtrusion:or,fillExtrusionPattern:sr,hillshadePrepare:lr,hillshade:cr,line:ur,lineGradient:fr,linePattern:hr,lineSDF:pr,raster:dr,symbolIcon:mr,symbolSDF:gr,symbolTextAndIcon:vr}),br=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};br.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,c=0;!l&&c<n.length;c++)this.boundPaintVertexBuffers[c]!==n[c]&&(l=!0);var u=!this.vao||this.boundProgram!==e||this.boundLayoutVertexBuffer!==r||l||this.boundIndexBuffer!==i||this.boundVertexOffset!==a||this.boundDynamicVertexBuffer!==o||this.boundDynamicVertexBuffer2!==s;!t.extVertexArrayObject||u?this.freshBind(e,r,n,i,a,o,s):(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),i&&i.dynamicDraw&&i.bind(),s&&s.bind())},br.prototype.freshBind=function(t,e,r,n,i,a,o){var s,l=t.numAttributes,c=this.context,u=c.gl;if(c.extVertexArrayObject)this.vao&&this.destroy(),this.vao=c.extVertexArrayObject.createVertexArrayOES(),c.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=i,this.boundDynamicVertexBuffer=a,this.boundDynamicVertexBuffer2=o;else{s=c.currentNumAttributes||0;for(var f=l;f<s;f++)u.disableVertexAttribArray(f)}e.enableAttributes(u,t);for(var h=0,p=r;h<p.length;h+=1){p[h].enableAttributes(u,t)}a&&a.enableAttributes(u,t),o&&o.enableAttributes(u,t),e.bind(),e.setVertexAttribPointers(u,t,i);for(var d=0,m=r;d<m.length;d+=1){var g=m[d];g.bind(),g.setVertexAttribPointers(u,t,i)}a&&(a.bind(),a.setVertexAttribPointers(u,t,i)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(u,t,i)),c.currentNumAttributes=l},br.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var _r=function(t,e,r,n,i){var a=t.gl;this.program=a.createProgram();var o=r?r.defines():[];i&&o.push(\"#define OVERDRAW_INSPECTOR;\");var s=o.concat(Ye.fragmentSource,e.fragmentSource).join(\"\\n\"),l=o.concat(Ye.vertexSource,e.vertexSource).join(\"\\n\"),c=a.createShader(a.FRAGMENT_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(c,s),a.compileShader(c),a.attachShader(this.program,c);var u=a.createShader(a.VERTEX_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(u,l),a.compileShader(u),a.attachShader(this.program,u);for(var f=r?r.layoutAttributes:[],h=0;h<f.length;h++)a.bindAttribLocation(this.program,h,f[h].name);a.linkProgram(this.program),a.deleteShader(u),a.deleteShader(c),this.numAttributes=a.getProgramParameter(this.program,a.ACTIVE_ATTRIBUTES),this.attributes={};for(var p={},d=0;d<this.numAttributes;d++){var m=a.getActiveAttrib(this.program,d);m&&(this.attributes[m.name]=a.getAttribLocation(this.program,m.name))}for(var g=a.getProgramParameter(this.program,a.ACTIVE_UNIFORMS),v=0;v<g;v++){var y=a.getActiveUniform(this.program,v);y&&(p[y.name]=a.getUniformLocation(this.program,y.name))}this.fixedUniforms=n(t,p),this.binderUniforms=r?r.getUniforms(t,p):[]}}};function wr(t,e,r){var n=1/pe(r,1,e.transform.tileZoom),i=Math.pow(2,r.tileID.overscaledZ),a=r.tileSize*Math.pow(2,e.transform.tileZoom)/i,o=a*(r.tileID.canonical.x+r.tileID.wrap*i),s=a*r.tileID.canonical.y;return{u_image:0,u_texsize:r.imageAtlasTexture.size,u_scale:[n,t.fromScale,t.toScale],u_fade:t.t,u_pixel_coord_upper:[o>>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}_r.prototype.draw=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m){var g,v=t.gl;if(!this.failedToCreate){for(var y in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[y].set(o[y]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(g={},g[v.LINES]=2,g[v.TRIANGLES]=3,g[v.LINE_STRIP]=1,g)[e],b=0,_=u.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new br)).bind(t,this,l,p?p.getPaintVertexBuffers():[],c,w.vertexOffset,d,m),v.drawElements(e,w.primitiveLength*x,v.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var Tr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var c=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[c.r,c.g,c.b],u_vertical_gradient:+n,u_opacity:i}},kr=function(e,r,n,i,a,o,s){return t.extend(Tr(e,r,n,i),wr(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},Mr=function(t){return{u_matrix:t}},Ar=function(e,r,n,i){return t.extend(Mr(e),wr(n,r,i))},Sr=function(t,e){return{u_matrix:t,u_world:e}},Er=function(e,r,n,i,a){return t.extend(Ar(e,r,n,i),{u_world:a})},Lr=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=pe(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Cr=function(t,e,r){var n=pe(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Pr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},Ir=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Or=function(t){return{u_matrix:t}},zr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:pe(e,1,r),u_intensity:n}};function Dr(e,r){var n=Math.pow(2,r.canonical.z),i=r.canonical.y;return[new t.MercatorCoordinate(0,i/n).toLngLat().lat,new t.MercatorCoordinate(0,(i+1)/n).toLngLat().lat]}var Rr=function(e,r,n){var i=e.transform;return{u_matrix:Ur(e,r,n),u_ratio:1/pe(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Fr=function(e,r,n){return t.extend(Rr(e,r,n),{u_image:0})},Br=function(e,r,n,i){var a=e.transform,o=jr(r,a);return{u_matrix:Ur(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/pe(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},Nr=function(e,r,n,i,a){var o=e.transform,s=e.lineAtlas,l=jr(r,o),c=\"round\"===n.layout.get(\"line-cap\"),u=s.getDash(i.from,c),f=s.getDash(i.to,c),h=u.width*a.fromScale,p=f.width*a.toScale;return t.extend(Rr(e,r,n),{u_patternscale_a:[l/h,-u.height/2],u_patternscale_b:[l/p,-f.height/2],u_sdfgamma:s.width/(256*Math.min(h,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:u.y,u_tex_y_b:f.y,u_mix:a.t})};function jr(t,e){return 1/pe(t,1,e.tileZoom)}function Ur(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var Vr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:qr(i.paint.get(\"raster-hue-rotate\"))};var a,o};function qr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Hr,Gr=function(t,e,r,n,i,a,o,s,l,c){var u=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:u.cameraToCenterDistance,u_pitch:u.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:u.width/u.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:c,u_texture:0}},Yr=function(e,r,n,i,a,o,s,l,c,u,f){var h=a.transform;return t.extend(Gr(e,r,n,i,a,o,s,l,c,u),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},Wr=function(e,r,n,i,a,o,s,l,c,u){return t.extend(Yr(e,r,n,i,a,o,s,l,!0,c,!0),{u_texsize_icon:u,u_texture_icon:1})},Xr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},Zr=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,c=Math.pow(2,n.tileID.overscaledZ),u=n.tileSize*Math.pow(2,r.transform.tileZoom)/c,f=u*(n.tileID.canonical.x+n.tileID.wrap*c),h=u*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/pe(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},Jr={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function Kr(e,r,n,i,a,o,s){for(var l=e.context,c=l.gl,u=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d<i.length;d++){var m=i[d],g=r.getTile(m),v=g.getBucket(n);if(v){var y=m.posMatrix;0===a[0]&&0===a[1]||(y=e.translatePosMatrix(m.posMatrix,g,a,o));var x=s?v.textCollisionBox:v.iconCollisionBox,b=v.collisionCircleArray;if(b.length>0){var _=t.create(),w=y;t.mul(_,v.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,v.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&u.draw(l,c.LINES,Mt.disabled,At.disabled,e.colorModeForRenderPass(),Et.disabled,Cr(y,e.transform,g),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var M=0,A=0,S=f;A<S.length;A+=1)for(var E=S[A],L=0;L<E.circleArray.length/4;L++){var C=4*L,P=E.circleArray[C+0],I=E.circleArray[C+1],O=E.circleArray[C+2],z=E.circleArray[C+3];k.emplace(M++,P,I,O,z,0),k.emplace(M++,P,I,O,z,1),k.emplace(M++,P,I,O,z,2),k.emplace(M++,P,I,O,z,3)}(!Hr||Hr.length<2*h)&&(Hr=function(e){var r=2*e,n=new t.StructArrayLayout3ui6;n.resize(r),n._trim();for(var i=0;i<r;i++){var a=6*i;n.uint16[a+0]=4*i+0,n.uint16[a+1]=4*i+1,n.uint16[a+2]=4*i+2,n.uint16[a+3]=4*i+2,n.uint16[a+4]=4*i+3,n.uint16[a+5]=4*i+0}return n}(h));for(var D=l.createIndexBuffer(Hr,!0),R=l.createVertexBuffer(k,t.collisionCircleLayout.members,!0),F=0,B=f;F<B.length;F+=1){var N=B[F],j=Pr(N.transform,N.invTransform,e.transform);T.draw(l,c.TRIANGLES,Mt.disabled,At.disabled,e.colorModeForRenderPass(),Et.disabled,j,n.id,R,D,t.SegmentVector.simpleSegment(0,2*N.circleOffset,N.circleArray.length,N.circleArray.length/2),null,e.transform.zoom,null,null,null)}R.destroy(),D.destroy()}}var Qr=t.identity(new Float32Array(16));function $r(e,r,n,i,a,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,c=-(s.verticalAlign-.5)*n,u=t.evaluateVariableOffset(e,i);return new t.Point((l/a+u[0])*o,(c/a+u[1])*o)}function tn(e,r,n,i,a,o,s,l,c,u,f){var h=e.text.placedSymbolArray,p=e.text.dynamicLayoutVertexArray,d=e.icon.dynamicLayoutVertexArray,m={};p.clear();for(var g=0;g<h.length;g++){var v=h.get(g),y=e.allowVerticalPlacement&&!v.placedOrientation,x=v.hidden||!v.crossTileID||y?null:i[v.crossTileID];if(x){var b=new t.Point(v.anchorX,v.anchorY),_=te(b,n?l:s),w=ee(o.cameraToCenterDistance,_.signedDistanceFromCamera),T=a.evaluateSizeForFeature(e.textSizeData,u,v)*w/t.ONE_EM;n&&(T*=e.tilePixelRatio/c);for(var k=x.width,M=x.height,A=$r(x.anchor,k,M,x.textOffset,x.textBoxScale,T),S=n?te(b.add(A),s).point:_.point.add(r?A.rotate(-o.angle):A),E=e.allowVerticalPlacement&&v.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,L=0;L<v.numGlyphs;L++)t.addDynamicAttributes(p,S,E);f&&v.associatedIconIndex>=0&&(m[v.associatedIconIndex]={shiftedAnchor:S,angle:E})}else ue(v.numGlyphs,p)}if(f){d.clear();for(var C=e.icon.placedSymbolArray,P=0;P<C.length;P++){var I=C.get(P);if(I.hidden)ue(I.numGlyphs,d);else{var O=m[P];if(O)for(var z=0;z<I.numGlyphs;z++)t.addDynamicAttributes(d,O.shiftedAnchor,O.angle);else ue(I.numGlyphs,d)}}e.icon.dynamicLayoutVertexBuffer.updateData(d)}e.text.dynamicLayoutVertexBuffer.updateData(p)}function en(t,e,r){return r.iconsInText&&e?\"symbolTextAndIcon\":t?\"symbolSDF\":\"symbolIcon\"}function rn(e,r,n,i,a,o,s,l,c,u,f,h){for(var p=e.context,d=p.gl,m=e.transform,g=\"map\"===l,v=\"map\"===c,y=g&&\"point\"!==n.layout.get(\"symbol-placement\"),x=g&&!v&&!y,b=void 0!==n.layout.get(\"symbol-sort-key\").constantOr(1),_=e.depthModeForSublayer(0,Mt.ReadOnly),w=n.layout.get(\"text-variable-anchor\"),T=[],k=0,M=i;k<M.length;k+=1){var A=M[k],S=r.getTile(A),E=S.getBucket(n);if(E){var L=a?E.text:E.icon;if(L&&L.segments.get().length){var C=L.programConfigurations.get(n.id),P=a||E.sdfIcons,I=a?E.textSizeData:E.iconSizeData,O=v||0!==m.pitch,z=e.useProgram(en(P,a,E),C),D=t.evaluateSizeForZoom(I,m.zoom),R=void 0,F=[0,0],B=void 0,N=void 0,j=null,U=void 0;if(a){if(B=S.glyphAtlasTexture,N=d.LINEAR,R=S.glyphAtlasTexture.size,E.iconsInText){F=S.imageAtlasTexture.size,j=S.imageAtlasTexture;var V=\"composite\"===I.kind||\"camera\"===I.kind;U=O||e.options.rotating||e.options.zooming||V?d.LINEAR:d.NEAREST}}else{var q=1!==n.layout.get(\"icon-size\").constantOr(0)||E.iconsNeedLinear;B=S.imageAtlasTexture,N=P||e.options.rotating||e.options.zooming||q||O?d.LINEAR:d.NEAREST,R=S.imageAtlasTexture.size}var H=pe(S,1,e.transform.zoom),G=Qt(A.posMatrix,v,g,e.transform,H),Y=$t(A.posMatrix,v,g,e.transform,H),W=w&&E.hasTextData(),X=\"none\"!==n.layout.get(\"icon-text-fit\")&&W&&E.hasIconData();y&&ne(E,A.posMatrix,e,a,G,Y,v,u);var Z=e.translatePosMatrix(A.posMatrix,S,o,s),J=y||a&&w||X?Qr:G,K=e.translatePosMatrix(Y,S,o,s,!0),Q=P&&0!==n.paint.get(a?\"text-halo-width\":\"icon-halo-width\").constantOr(1),$={program:z,buffers:L,uniformValues:P?E.iconsInText?Wr(I.kind,D,x,v,e,Z,J,K,R,F):Yr(I.kind,D,x,v,e,Z,J,K,a,R,!0):Gr(I.kind,D,x,v,e,Z,J,K,a,R),atlasTexture:B,atlasTextureIcon:j,atlasInterpolation:N,atlasInterpolationIcon:U,isSDF:P,hasHalo:Q};if(b)for(var tt=0,et=L.segments.get();tt<et.length;tt+=1){var rt=et[tt];T.push({segments:new t.SegmentVector([rt]),sortKey:rt.sortKey,state:$})}else T.push({segments:L.segments,sortKey:0,state:$})}}}b&&T.sort((function(t,e){return t.sortKey-e.sortKey}));for(var nt=0,it=T;nt<it.length;nt+=1){var at=it[nt],ot=at.state;if(p.activeTexture.set(d.TEXTURE0),ot.atlasTexture.bind(ot.atlasInterpolation,d.CLAMP_TO_EDGE),ot.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),ot.atlasTextureIcon&&ot.atlasTextureIcon.bind(ot.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),ot.isSDF){var st=ot.uniformValues;ot.hasHalo&&(st.u_is_halo=1,nn(ot.buffers,at.segments,n,e,ot.program,_,f,h,st)),st.u_is_halo=0}nn(ot.buffers,at.segments,n,e,ot.program,_,f,h,ot.uniformValues)}}function nn(t,e,r,n,i,a,o,s,l){var c=n.context,u=c.gl;i.draw(c,u.TRIANGLES,a,o,s,Et.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function an(t,e,r,n,i,a,o){var s,l,c,u,f,h=t.context.gl,p=r.paint.get(\"fill-pattern\"),d=p&&p.constantOr(1),m=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",s=h.LINES):(l=d?\"fillPattern\":\"fill\",s=h.TRIANGLES);for(var g=0,v=n;g<v.length;g+=1){var y=v[g],x=e.getTile(y);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(h.TEXTURE0),x.imageAtlasTexture.bind(h.LINEAR,h.CLAMP_TO_EDGE),_.updatePaintBuffers(m));var T=p.constantOr(null);if(T&&x.imageAtlas){var k=x.imageAtlas,M=k.patternPositions[T.to.toString()],A=k.patternPositions[T.from.toString()];M&&A&&_.setConstantPatternPositions(M,A)}var S=t.translatePosMatrix(y.posMatrix,x,r.paint.get(\"fill-translate\"),r.paint.get(\"fill-translate-anchor\"));if(o){u=b.indexBuffer2,f=b.segments2;var E=[h.drawingBufferWidth,h.drawingBufferHeight];c=\"fillOutlinePattern\"===l&&d?Er(S,t,m,x,E):Sr(S,E)}else u=b.indexBuffer,f=b.segments,c=d?Ar(S,t,m,x):Mr(S);w.draw(t.context,s,i,t.stencilModeForClipping(y),a,Et.disabled,c,r.id,b.layoutVertexBuffer,u,f,r.paint,t.transform.zoom,_)}}}}function on(t,e,r,n,i,a,o){for(var s=t.context,l=s.gl,c=r.paint.get(\"fill-extrusion-pattern\"),u=c.constantOr(1),f=r.getCrossfadeParameters(),h=r.paint.get(\"fill-extrusion-opacity\"),p=0,d=n;p<d.length;p+=1){var m=d[p],g=e.getTile(m),v=g.getBucket(r);if(v){var y=v.programConfigurations.get(r.id),x=t.useProgram(u?\"fillExtrusionPattern\":\"fillExtrusion\",y);u&&(t.context.activeTexture.set(l.TEXTURE0),g.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),y.updatePaintBuffers(f));var b=c.constantOr(null);if(b&&g.imageAtlas){var _=g.imageAtlas,w=_.patternPositions[b.to.toString()],T=_.patternPositions[b.from.toString()];w&&T&&y.setConstantPatternPositions(w,T)}var k=t.translatePosMatrix(m.posMatrix,g,r.paint.get(\"fill-extrusion-translate\"),r.paint.get(\"fill-extrusion-translate-anchor\")),M=r.paint.get(\"fill-extrusion-vertical-gradient\"),A=u?kr(k,t,M,h,m,f,g):Tr(k,t,M,h);x.draw(s,s.gl.TRIANGLES,i,a,o,Et.backCCW,A,r.id,v.layoutVertexBuffer,v.indexBuffer,v.segments,r.paint,t.transform.zoom,y)}}}function sn(t,e,r,n,i,a){var o=t.context,s=o.gl,l=e.fbo;if(l){var c=t.useProgram(\"hillshade\");o.activeTexture.set(s.TEXTURE0),s.bindTexture(s.TEXTURE_2D,l.colorAttachment.get());var u=function(t,e,r){var n=r.paint.get(\"hillshade-shadow-color\"),i=r.paint.get(\"hillshade-highlight-color\"),a=r.paint.get(\"hillshade-accent-color\"),o=r.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===r.paint.get(\"hillshade-illumination-anchor\")&&(o-=t.transform.angle);var s=!t.options.moving;return{u_matrix:t.transform.calculatePosMatrix(e.tileID.toUnwrapped(),s),u_image:0,u_latrange:Dr(t,e.tileID),u_light:[r.paint.get(\"hillshade-exaggeration\"),o],u_shadow:n,u_highlight:i,u_accent:a}}(t,e,r);c.draw(o,s.TRIANGLES,n,i,a,Et.disabled,u,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}}function ln(e,r,n,i,a,o,s){var l=e.context,c=l.gl,u=r.dem;if(u&&u.data){var f=u.dim,h=u.stride,p=u.getPixels();if(l.activeTexture.set(c.TEXTURE1),l.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(h),r.demTexture){var d=r.demTexture;d.update(p,{premultiply:!1}),d.bind(c.NEAREST,c.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(l,p,c.RGBA,{premultiply:!1}),r.demTexture.bind(c.NEAREST,c.CLAMP_TO_EDGE);l.activeTexture.set(c.TEXTURE0);var m=r.fbo;if(!m){var g=new t.Texture(l,{width:f,height:f,data:null},c.RGBA);g.bind(c.LINEAR,c.CLAMP_TO_EDGE),(m=r.fbo=l.createFramebuffer(f,f,!0)).colorAttachment.set(g.texture)}l.bindFramebuffer.set(m.framebuffer),l.viewport.set([0,0,f,f]),e.useProgram(\"hillshadePrepare\").draw(l,c.TRIANGLES,a,o,s,Et.disabled,function(e,r,n){var i=r.stride,a=t.create();return t.ortho(a,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(a,a,[0,-t.EXTENT,0]),{u_matrix:a,u_image:1,u_dimension:[i,i],u_zoom:e.overscaledZ,u_maxzoom:n,u_unpack:r.getUnpackVector()}}(r.tileID,u,i),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function cn(e,r,n,i,a){var o=i.paint.get(\"raster-fade-duration\");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,c=r?(s-r.timeAdded)/o:-1,u=n.getSource(),f=a.coveringZoomLevel({tileSize:u.tileSize,roundZoom:u.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-c,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var un=new t.Color(1,0,0,1),fn=new t.Color(0,1,0,1),hn=new t.Color(0,0,1,1),pn=new t.Color(1,0,1,1),dn=new t.Color(0,1,1,1);function mn(t){var e=t.transform.padding;gn(t,t.transform.height-(e.top||0),3,un),gn(t,e.bottom||0,3,fn),vn(t,e.left||0,3,hn),vn(t,t.transform.width-(e.right||0),3,pn);var r=t.transform.centerPoint;!function(t,e,r,n){yn(t,e-1,r-10,2,20,n),yn(t,e-10,r-1,20,2,n)}(t,r.x,t.transform.height-r.y,dn)}function gn(t,e,r,n){yn(t,0,e+r/2,t.transform.width,r,n)}function vn(t,e,r,n){yn(t,e-r/2,0,r,t.transform.height,n)}function yn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function xn(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=Mt.disabled,c=At.disabled,u=e.colorModeForRenderPass();i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,c,u,Et.disabled,Ir(o,t.Color.red),\"$debug\",e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var f=r.getTileByID(n.key).latestRawTileData,h=f&&f.byteLength||0,p=Math.floor(h/1024),d=r.getTile(n).tileSize,m=512/Math.min(d,512)*(n.overscaledZ/e.transform.zoom)*.5,g=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(g+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,g+\" \"+p+\"kb\"),s.draw(i,a.TRIANGLES,l,c,St.alphaBlended,Et.disabled,Ir(o,t.Color.transparent,m),\"$debug\",e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var bn={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=At.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,c=\"map\"===a,u=\"map\"===o,f=0,h=e;f<h.length;f+=1){var p=h[f],d=i.getTile(p),m=d.getBucket(n);if(m&&m.text&&m.text.segments.get().length){var g=m.textSizeData,v=t.evaluateSizeForZoom(g,l.zoom),y=pe(d,1,r.transform.zoom),x=Qt(p.posMatrix,u,c,r.transform,y),b=\"none\"!==n.layout.get(\"icon-text-fit\")&&m.hasIconData();if(v){var _=Math.pow(2,l.zoom-d.tileID.overscaledZ);tn(m,c,u,s,t.symbolSize,l,x,p.posMatrix,_,v,b)}}}}(i,e,n,r,n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),a),0!==n.paint.get(\"icon-opacity\").constantOr(1)&&rn(e,r,n,i,!1,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),n.layout.get(\"icon-rotation-alignment\"),n.layout.get(\"icon-pitch-alignment\"),n.layout.get(\"icon-keep-upright\"),o,s),0!==n.paint.get(\"text-opacity\").constantOr(1)&&rn(e,r,n,i,!0,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),n.layout.get(\"text-keep-upright\"),o,s),r.map.showCollisionBoxes&&(Kr(e,r,n,i,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),!0),Kr(e,r,n,i,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),!1))}},circle:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"circle-opacity\"),o=n.paint.get(\"circle-stroke-width\"),s=n.paint.get(\"circle-stroke-opacity\"),l=void 0!==n.layout.get(\"circle-sort-key\").constantOr(1);if(0!==a.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var c=e.context,u=c.gl,f=e.depthModeForSublayer(0,Mt.ReadOnly),h=At.disabled,p=e.colorModeForRenderPass(),d=[],m=0;m<i.length;m++){var g=i[m],v=r.getTile(g),y=v.getBucket(n);if(y){var x=y.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram(\"circle\",x),layoutVertexBuffer:y.layoutVertexBuffer,indexBuffer:y.indexBuffer,uniformValues:Lr(e,g,v,n)};if(l)for(var _=0,w=y.segments.get();_<w.length;_+=1){var T=w[_];d.push({segments:new t.SegmentVector([T]),sortKey:T.sortKey,state:b})}else d.push({segments:y.segments,sortKey:0,state:b})}}l&&d.sort((function(t,e){return t.sortKey-e.sortKey}));for(var k=0,M=d;k<M.length;k+=1){var A=M[k],S=A.state,E=S.programConfiguration,L=S.program,C=S.layoutVertexBuffer,P=S.indexBuffer,I=S.uniformValues,O=A.segments;L.draw(c,u.TRIANGLES,f,h,p,Et.disabled,I,n.id,C,P,O,n.paint,e.transform.zoom,E)}}}},heatmap:function(e,r,n,i){if(0!==n.paint.get(\"heatmap-opacity\"))if(\"offscreen\"===e.renderPass){var a=e.context,o=a.gl,s=At.disabled,l=new St([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);!function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var i=r.heatmapFbo;if(i)n.bindTexture(n.TEXTURE_2D,i.colorAttachment.get()),t.bindFramebuffer.set(i.framebuffer);else{var a=n.createTexture();n.bindTexture(n.TEXTURE_2D,a),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),i=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4,!1),function(t,e,r,n){var i=t.gl,a=t.extRenderToTextureHalfFloat?t.extTextureHalfFloat.HALF_FLOAT_OES:i.UNSIGNED_BYTE;i.texImage2D(i.TEXTURE_2D,0,i.RGBA,e.width/4,e.height/4,0,i.RGBA,a,null),n.colorAttachment.set(r)}(t,e,a,i)}}(a,e,n),a.clear({color:t.Color.transparent});for(var c=0;c<i.length;c++){var u=i[c];if(!r.hasRenderableParent(u)){var f=r.getTile(u),h=f.getBucket(n);if(h){var p=h.programConfigurations.get(n.id),d=e.useProgram(\"heatmap\",p),m=e.transform.zoom;d.draw(a,o.TRIANGLES,Mt.disabled,s,l,Et.disabled,zr(u.posMatrix,f,m,n.paint.get(\"heatmap-intensity\")),n.id,h.layoutVertexBuffer,h.indexBuffer,h.segments,n.paint,e.transform.zoom,p)}}}a.viewport.set([0,0,e.width,e.height])}else\"translucent\"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,i=n.gl,a=r.heatmapFbo;if(!a)return;n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,i.RGBA));o.bind(i.LINEAR,i.CLAMP_TO_EDGE),e.useProgram(\"heatmapTexture\").draw(n,i.TRIANGLES,Mt.disabled,At.disabled,e.colorModeForRenderPass(),Et.disabled,function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:i,u_opacity:r.paint.get(\"heatmap-opacity\")}}(e,r,0,1),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}(e,n))},line:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"line-opacity\"),o=n.paint.get(\"line-width\");if(0!==a.constantOr(1)&&0!==o.constantOr(1)){var s=e.depthModeForSublayer(0,Mt.ReadOnly),l=e.colorModeForRenderPass(),c=n.paint.get(\"line-dasharray\"),u=n.paint.get(\"line-pattern\"),f=u.constantOr(1),h=n.paint.get(\"line-gradient\"),p=n.getCrossfadeParameters(),d=f?\"linePattern\":c?\"lineSDF\":h?\"lineGradient\":\"line\",m=e.context,g=m.gl,v=!0;if(h){m.activeTexture.set(g.TEXTURE0);var y=n.gradientTexture;if(!n.gradient)return;y||(y=n.gradientTexture=new t.Texture(m,n.gradient,g.RGBA)),y.bind(g.LINEAR,g.CLAMP_TO_EDGE)}for(var x=0,b=i;x<b.length;x+=1){var _=b[x],w=r.getTile(_);if(!f||w.patternsLoaded()){var T=w.getBucket(n);if(T){var k=T.programConfigurations.get(n.id),M=e.context.program.get(),A=e.useProgram(d,k),S=v||A.program!==M,E=u.constantOr(null);if(E&&w.imageAtlas){var L=w.imageAtlas,C=L.patternPositions[E.to.toString()],P=L.patternPositions[E.from.toString()];C&&P&&k.setConstantPatternPositions(C,P)}var I=f?Br(e,w,n,p):c?Nr(e,w,n,c,p):h?Fr(e,w,n):Rr(e,w,n);f?(m.activeTexture.set(g.TEXTURE0),w.imageAtlasTexture.bind(g.LINEAR,g.CLAMP_TO_EDGE),k.updatePaintBuffers(p)):c&&(S||e.lineAtlas.dirty)&&(m.activeTexture.set(g.TEXTURE0),e.lineAtlas.bind(m)),A.draw(m,g.TRIANGLES,s,e.stencilModeForClipping(_),l,Et.disabled,I,n.id,T.layoutVertexBuffer,T.indexBuffer,T.segments,n.paint,e.transform.zoom,k),v=!1}}}}}},fill:function(e,r,n,i){var a=n.paint.get(\"fill-color\"),o=n.paint.get(\"fill-opacity\");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get(\"fill-pattern\"),c=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===a.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?\"opaque\":\"translucent\";if(e.renderPass===c){var u=e.depthModeForSublayer(1,\"opaque\"===e.renderPass?Mt.ReadWrite:Mt.ReadOnly);an(e,r,n,i,u,s,!1)}if(\"translucent\"===e.renderPass&&n.paint.get(\"fill-antialias\")){var f=e.depthModeForSublayer(n.getPaintProperty(\"fill-outline-color\")?2:0,Mt.ReadOnly);an(e,r,n,i,f,s,!0)}}},\"fill-extrusion\":function(t,e,r,n){var i=r.paint.get(\"fill-extrusion-opacity\");if(0!==i&&\"translucent\"===t.renderPass){var a=new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D);if(1!==i||r.paint.get(\"fill-extrusion-pattern\").constantOr(1))on(t,e,r,n,a,At.disabled,St.disabled),on(t,e,r,n,a,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();on(t,e,r,n,a,At.disabled,o)}}},hillshade:function(t,e,r,n){if(\"offscreen\"===t.renderPass||\"translucent\"===t.renderPass){for(var i=t.context,a=e.getSource().maxzoom,o=t.depthModeForSublayer(0,Mt.ReadOnly),s=t.colorModeForRenderPass(),l=\"translucent\"===t.renderPass?t.stencilConfigForOverlap(n):[{},n],c=l[0],u=0,f=l[1];u<f.length;u+=1){var h=f[u],p=e.getTile(h);p.needsHillshadePrepare&&\"offscreen\"===t.renderPass?ln(t,p,r,a,o,At.disabled,s):\"translucent\"===t.renderPass&&sn(t,p,r,o,c[h.overscaledZ],s)}i.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"raster-opacity\")&&n.length)for(var i=t.context,a=i.gl,o=e.getSource(),s=t.useProgram(\"raster\"),l=t.colorModeForRenderPass(),c=o instanceof I?[{},n]:t.stencilConfigForOverlap(n),u=c[0],f=c[1],h=f[f.length-1].overscaledZ,p=!t.options.moving,d=0,m=f;d<m.length;d+=1){var g=m[d],v=t.depthModeForSublayer(g.overscaledZ-h,1===r.paint.get(\"raster-opacity\")?Mt.ReadWrite:Mt.ReadOnly,a.LESS),y=e.getTile(g),x=t.transform.calculatePosMatrix(g.toUnwrapped(),p);y.registerFadeDuration(r.paint.get(\"raster-fade-duration\"));var b=e.findLoadedParent(g,0),_=cn(y,b,e,r,t.transform),w=void 0,T=void 0,k=\"nearest\"===r.paint.get(\"raster-resampling\")?a.NEAREST:a.LINEAR;i.activeTexture.set(a.TEXTURE0),y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),i.activeTexture.set(a.TEXTURE1),b?(b.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),w=Math.pow(2,b.tileID.overscaledZ-y.tileID.overscaledZ),T=[y.tileID.canonical.x*w%1,y.tileID.canonical.y*w%1]):y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST);var M=Vr(x,T||[0,0],w||1,_,r);o instanceof I?s.draw(i,a.TRIANGLES,v,At.disabled,l,Et.disabled,M,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(i,a.TRIANGLES,v,u[g.overscaledZ],l,Et.disabled,M,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get(\"background-color\"),i=r.paint.get(\"background-opacity\");if(0!==i){var a=t.context,o=a.gl,s=t.transform,l=s.tileSize,c=r.paint.get(\"background-pattern\");if(!t.isPatternMissing(c)){var u=!c&&1===n.a&&1===i&&t.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(t.renderPass===u){var f=At.disabled,h=t.depthModeForSublayer(0,\"opaque\"===u?Mt.ReadWrite:Mt.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(c?\"backgroundPattern\":\"background\"),m=s.coveringTiles({tileSize:l});c&&(a.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var g=r.getCrossfadeParameters(),v=0,y=m;v<y.length;v+=1){var x=y[v],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=c?Zr(b,i,t,c,{tileID:x,tileSize:l},g):Xr(b,i,n);d.draw(a,o.TRIANGLES,h,f,p,Et.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)xn(t,e,r[n])},custom:function(t,e,r){var n=t.context,i=r.implementation;if(\"offscreen\"===t.renderPass){var a=i.prerender;a&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),a.call(i,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if(\"translucent\"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(At.disabled);var o=\"3d\"===i.renderingMode?new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,Mt.ReadOnly);n.setDepthMode(o),i.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},_n=function(t,e){this.context=new Lt(t),this.transform=e,this._tileTextures={},this.setup(),this.numSublayers=Ct.maxUnderzooming+Ct.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Ne,this.gpuTimers={}};_n.prototype.resize=function(e,r){if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,i=this.style._order;n<i.length;n+=1){var a=i[n];this.style._layers[a].resize()}},_n.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,Ge.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,Ge.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var i=new t.StructArrayLayout4i8;i.emplaceBack(0,0,0,0),i.emplaceBack(t.EXTENT,0,t.EXTENT,0),i.emplaceBack(0,t.EXTENT,0,t.EXTENT),i.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(i,P.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var a=new t.StructArrayLayout2i4;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(a,Ge.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s),this.emptyTexture=new t.Texture(e,{width:1,height:1,data:new Uint8Array([0,0,0,0])},e.gl.RGBA);var l=this.context.gl;this.stencilClearMode=new At({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},_n.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(e,r.TRIANGLES,Mt.disabled,this.stencilClearMode,St.disabled,Et.disabled,Or(n),\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},_n.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(St.disabled),r.setDepthMode(Mt.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a<o.length;a+=1){var s=o[a],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;i.draw(r,n.TRIANGLES,Mt.disabled,new At({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),St.disabled,Et.disabled,Or(s.posMatrix),\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},_n.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new At({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},_n.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new At({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},_n.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s<a;s++)o[s+i]=new At({func:r.GEQUAL,mask:255},s+this.nextStencilID,255,r.KEEP,r.KEEP,r.REPLACE);return this.nextStencilID+=a,[o,n]}return[(e={},e[i]=At.disabled,e),n]},_n.prototype.colorModeForRenderPass=function(){var e=this.context.gl;if(this._showOverdrawInspector){return new St([e.CONSTANT_COLOR,e.ONE],new t.Color(1/8,1/8,1/8,0),[!0,!0,!0,!0])}return\"opaque\"===this.renderPass?St.unblended:St.alphaBlended},_n.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return Mt.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new Mt(r||this.context.gl.LEQUAL,e,[n,n])},_n.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},_n.prototype.render=function(e,r){var n=this;this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var i=this.style._order,a=this.style.sourceCaches;for(var o in a){var s=a[o];s.used&&s.prepare(this.context)}var l,c,u={},f={},h={};for(var p in a){var d=a[p];u[p]=d.getVisibleCoordinates(),f[p]=u[p].slice().reverse(),h[p]=d.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var m=0;m<i.length;m++){var g=i[m];if(this.style._layers[g].is3D()){this.opaquePassCutoff=m;break}}this.renderPass=\"offscreen\";for(var v=0,y=i;v<y.length;v+=1){var x=y[v],b=this.style._layers[x];if(b.hasOffscreenPass()&&!b.isHidden(this.transform.zoom)){var _=f[b.source];(\"custom\"===b.type||_.length)&&this.renderLayer(this,a[b.source],b,_)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass=\"opaque\",this.currentLayer=i.length-1;this.currentLayer>=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=u[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<i.length;this.currentLayer++){var M=this.style._layers[i[this.currentLayer]],A=a[M.source],S=(\"symbol\"===M.type?h:f)[M.source];this._renderTileClippingMasks(M,u[M.source]),this.renderLayer(this,A,M,S)}this.options.showTileBoundaries&&(t.values(this.style._layers).forEach((function(t){t.source&&!t.isHidden(n.transform.zoom)&&(t.source!==(c&&c.id)&&(c=n.style.sourceCaches[t.source]),(!l||l.getSource().maxzoom<c.getSource().maxzoom)&&(l=c))})),l&&bn.debug(this,l,l.getVisibleCoordinates()));this.options.showPadding&&mn(this),this.context.setDefault()},_n.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||\"custom\"===r.type||n.length)&&(this.id=r.id,this.gpuTimingStart(r),bn[r.type](t,e,r,n,this.style.placement.variableOffsets),this.gpuTimingEnd())},_n.prototype.gpuTimingStart=function(t){if(this.options.gpuTiming){var e=this.context.extTimerQuery,r=this.gpuTimers[t.id];r||(r=this.gpuTimers[t.id]={calls:0,cpuTime:0,query:e.createQueryEXT()}),r.calls++,e.beginQueryEXT(e.TIME_ELAPSED_EXT,r.query)}},_n.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var t=this.context.extTimerQuery;t.endQueryEXT(t.TIME_ELAPSED_EXT)}},_n.prototype.collectGpuTimers=function(){var t=this.gpuTimers;return this.gpuTimers={},t},_n.prototype.queryGpuTimers=function(t){var e={};for(var r in t){var n=t[r],i=this.context.extTimerQuery,a=i.getQueryObjectEXT(n.query,i.QUERY_RESULT_EXT)/1e6;i.deleteQueryEXT(n.query),e[r]=a}return e},_n.prototype.translatePosMatrix=function(e,r,n,i,a){if(!n[0]&&!n[1])return e;var o=a?\"map\"===i?this.transform.angle:0:\"viewport\"===i?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var c=[a?n[0]:pe(r,n[0],this.transform.zoom),a?n[1]:pe(r,n[1],this.transform.zoom),0],u=new Float32Array(16);return t.translate(u,e,c),u},_n.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},_n.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},_n.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},_n.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new _r(this.context,xr[t],e,Jr[t],this._showOverdrawInspector)),this.cache[r]},_n.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},_n.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},_n.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},_n.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var wn=function(t,e){this.points=t,this.planes=e};wn.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new wn(a,o)};var Tn=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};Tn.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a<r.length;a++)n[a]=r[a]?this.min[a]:this.center[a],i[a]=r[a]?this.center[a]:this.max[a];return i[2]=this.max[2],new Tn(n,i)},Tn.prototype.distanceX=function(t){return Math.max(Math.min(this.max[0],t[0]),this.min[0])-t[0]},Tn.prototype.distanceY=function(t){return Math.max(Math.min(this.max[1],t[1]),this.min[1])-t[1]},Tn.prototype.intersects=function(e){for(var r=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],n=!0,i=0;i<e.planes.length;i++){for(var a=e.planes[i],o=0,s=0;s<r.length;s++)o+=t.dot$1(a,r[s])>=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var c=Number.MAX_VALUE,u=-Number.MAX_VALUE,f=0;f<e.points.length;f++){var h=e.points[f][l]-this.min[l];c=Math.min(c,h),u=Math.max(u,h)}if(u<0||c>this.max[l]-this.min[l])return 0}return 1};var kn=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};kn.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},kn.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},kn.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},kn.prototype.clone=function(){return new kn(this.top,this.bottom,this.left,this.right)},kn.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var Mn=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new kn,this._posMatrixCache={},this._alignedPosMatrixCache={}},An={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};Mn.prototype.clone=function(){var t=new Mn(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},An.minZoom.get=function(){return this._minZoom},An.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},An.maxZoom.get=function(){return this._maxZoom},An.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},An.minPitch.get=function(){return this._minPitch},An.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},An.maxPitch.get=function(){return this._maxPitch},An.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},An.renderWorldCopies.get=function(){return this._renderWorldCopies},An.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},An.worldSize.get=function(){return this.tileSize*this.scale},An.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},An.size.get=function(){return new t.Point(this.width,this.height)},An.bearing.get=function(){return-this.angle/Math.PI*180},An.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},An.pitch.get=function(){return this._pitch/Math.PI*180},An.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},An.fov.get=function(){return this._fov/Math.PI*180},An.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},An.zoom.get=function(){return this._zoom},An.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},An.center.get=function(){return this._center},An.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},An.padding.get=function(){return this._edgeInsets.toJSON()},An.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},An.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},Mn.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},Mn.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},Mn.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},Mn.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),c=s-1;c<=l+1;c++)0!==c&&r.push(new t.UnwrappedTileID(c,e));return r},Mn.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=wn.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var c=function(t){return{aabb:new Tn([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},u=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)u.push(c(-d)),u.push(c(d));for(u.push(c(0));u.length>0;){var m=u.pop(),g=m.x,v=m.y,y=m.fullyVisible;if(!y){var x=m.aabb.intersects(s);if(0===x)continue;y=2===x}var b=m.aabb.distanceX(o),_=m.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_)),T=3+(1<<h-m.zoom)-2;if(m.zoom===h||w>T&&m.zoom>=l)f.push({tileID:new t.OverscaledTileID(m.zoom===h?p:m.zoom,m.wrap,m.zoom,g,v),distanceSq:t.sqrLen([o[0]-.5-g,o[1]-.5-v])});else for(var k=0;k<4;k++){var M=(g<<1)+k%2,A=(v<<1)+(k>>1);u.push({aabb:m.aabb.quadrant(k),zoom:m.zoom+1,x:M,y:A,wrap:m.wrap,fullyVisible:y})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},Mn.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},An.unmodified.get=function(){return this._unmodified},Mn.prototype.zoomScale=function(t){return Math.pow(2,t)},Mn.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},Mn.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},Mn.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},An.point.get=function(){return this.project(this.center)},Mn.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},Mn.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},Mn.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},Mn.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},Mn.prototype.coordinateLocation=function(t){return t.toLngLat()},Mn.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,c=n[1]/a,u=r[2]/i,f=n[2]/a,h=u===f?0:(0-u)/(f-u);return new t.MercatorCoordinate(t.number(o,s,h)/this.worldSize,t.number(l,c,h)/this.worldSize)},Mn.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},Mn.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},Mn.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},Mn.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},Mn.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},Mn.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},Mn.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,c=this.size,u=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-a<c.y?c.y/(o-a):0}if(this.lngRange){var h=this.lngRange;s=t.mercatorXfromLng(h[0])*this.worldSize,r=(l=t.mercatorXfromLng(h[1])*this.worldSize)-s<c.x?c.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+a)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=u,void(this._constraining=!1);if(this.latRange){var m=p.y,g=c.y/2;m-g<a&&(i=a+g),m+g>o&&(i=o-g)}if(this.lngRange){var v=p.x,y=c.x/2;v-y<s&&(n=s+y),v+y>l&&(n=l-y)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=u,this._constraining=!1}},Mn.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,c=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),u=this.height/50,f=new Float64Array(16);t.perspective(f,this._fov,this.width/this.height,u,c),f[8]=2*-r.x/this.width,f[9]=2*r.y/this.height,t.scale(f,f,[1,-1,1]),t.translate(f,f,[0,0,-this.cameraToCenterDistance]),t.rotateX(f,f,this._pitch),t.rotateZ(f,f,this.angle),t.translate(f,f,[-s,-l,0]),this.mercatorMatrix=t.scale([],f,[this.worldSize,this.worldSize,this.worldSize]),t.scale(f,f,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=f,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),m=Math.sin(this.angle),g=s-Math.round(s)+d*h+m*p,v=l-Math.round(l)+d*p+m*h,y=new Float64Array(f);if(t.translate(y,y,[g>.5?g-1:g,v>.5?v-1:v,0]),this.alignedProjMatrix=y,f=t.create(),t.scale(f,f,[this.width/2,-this.height/2,1]),t.translate(f,f,[1,-1,0]),this.labelPlaneMatrix=f,f=t.create(),t.scale(f,f,[1,-1,1]),t.translate(f,f,[-1,-1,0]),t.scale(f,f,[2/this.width,2/this.height,1]),this.glCoordMatrix=f,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(f=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=f,this._posMatrixCache={},this._alignedPosMatrixCache={}}},Mn.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},Mn.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},Mn.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var c=l[s];n=Math.min(n,c.x),i=Math.min(i,c.y),a=Math.max(a,c.x),o=Math.max(o,c.y)}return[new t.Point(n,i),new t.Point(a,i),new t.Point(a,o),new t.Point(n,o),new t.Point(n,i)]},Object.defineProperties(Mn.prototype,An);var Sn=function(e){var r,n,i,a,o;this._hashName=e&&encodeURIComponent(e),t.bindAll([\"_getCurrentHash\",\"_onHashChange\",\"_updateHash\"],this),this._updateHash=(r=this._updateHashUnthrottled.bind(this),n=300,i=!1,a=null,o=function(){a=null,i&&(r(),a=setTimeout(o,n),i=!1)},function(){return i=!0,a||o(),a})};Sn.prototype.addTo=function(e){return this._map=e,t.window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},Sn.prototype.remove=function(){return t.window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},Sn.prototype.getHashString=function(e){var r=this._map.getCenter(),n=Math.round(100*this._map.getZoom())/100,i=Math.ceil((n*Math.LN2+Math.log(512/360/.5))/Math.LN10),a=Math.pow(10,i),o=Math.round(r.lng*a)/a,s=Math.round(r.lat*a)/a,l=this._map.getBearing(),c=this._map.getPitch(),u=\"\";if(u+=e?\"/\"+o+\"/\"+s+\"/\"+n:n+\"/\"+s+\"/\"+o,(l||c)&&(u+=\"/\"+Math.round(10*l)/10),c&&(u+=\"/\"+Math.round(c)),this._hashName){var f=this._hashName,h=!1,p=t.window.location.hash.slice(1).split(\"&\").map((function(t){var e=t.split(\"=\")[0];return e===f?(h=!0,e+\"=\"+u):t})).filter((function(t){return t}));return h||p.push(f+\"=\"+u),\"#\"+p.join(\"&\")}return\"#\"+u},Sn.prototype._getCurrentHash=function(){var e,r=this,n=t.window.location.hash.replace(\"#\",\"\");return this._hashName?(n.split(\"&\").map((function(t){return t.split(\"=\")})).forEach((function(t){t[0]===r._hashName&&(e=t)})),(e&&e[1]||\"\").split(\"/\")):n.split(\"/\")},Sn.prototype._onHashChange=function(){var t=this._getCurrentHash();if(t.length>=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},Sn.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,\"\",e)}catch(t){}};var En={linearity:.3,easing:t.bezier(0,0,.3,1)},Ln=t.extend({deceleration:2500,maxSpeed:1400},En),Cn=t.extend({deceleration:20,maxSpeed:1400},En),Pn=t.extend({deceleration:1e3,maxSpeed:360},En),In=t.extend({deceleration:1e3,maxSpeed:90},En),On=function(t){this._map=t,this.clear()};function zn(t,e){(!t.duration||t.duration<e.duration)&&(t.duration=e.duration,t.easing=e.easing)}function Dn(e,r,n){var i=n.maxSpeed,a=n.linearity,o=n.deceleration,s=t.clamp(e*a/(r/1e3),-i,i),l=Math.abs(s)/(o*a);return{easing:n.easing,duration:1e3*l,amount:s*(l/2)}}On.prototype.clear=function(){this._inertiaBuffer=[]},On.prototype.record=function(e){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:t.browser.now(),settings:e})},On.prototype._drainInertiaBuffer=function(){for(var e=this._inertiaBuffer,r=t.browser.now();e.length>0&&r-e[0].time>160;)e.shift()},On.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n<i.length;n+=1){var a=i[n].settings;r.zoom+=a.zoomDelta||0,r.bearing+=a.bearingDelta||0,r.pitch+=a.pitchDelta||0,a.panDelta&&r.pan._add(a.panDelta),a.around&&(r.around=a.around),a.pinchAround&&(r.pinchAround=a.pinchAround)}var o=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,s={};if(r.pan.mag()){var l=Dn(r.pan.mag(),o,t.extend({},Ln,e||{}));s.offset=r.pan.mult(l.amount/r.pan.mag()),s.center=this._map.transform.center,zn(s,l)}if(r.zoom){var c=Dn(r.zoom,o,Cn);s.zoom=this._map.transform.zoom+c.amount,zn(s,c)}if(r.bearing){var u=Dn(r.bearing,o,Pn);s.bearing=this._map.transform.bearing+t.clamp(u.amount,-179,179),zn(s,u)}if(r.pitch){var f=Dn(r.pitch,o,In);s.pitch=this._map.transform.pitch+f.amount,zn(s,f)}if(s.zoom||s.bearing){var h=void 0===r.pinchAround?r.around:r.pinchAround;s.around=h?this._map.unproject(h):this._map.getCenter()}return this.clear(),t.extend(s,{noMoveStart:!0})}};var Rn=function(e){function n(n,i,a,o){void 0===o&&(o={});var s=r.mousePos(i.getCanvasContainer(),a),l=i.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:a},o)),this._defaultPrevented=!1,this.target=i}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Fn=function(e){function n(n,i,a){var o=\"touchend\"===n?a.changedTouches:a.touches,s=r.touchPos(i.getCanvasContainer(),o),l=s.map((function(t){return i.unproject(t)})),c=s.reduce((function(t,e,r,n){return t.add(e.div(n.length))}),new t.Point(0,0)),u=i.unproject(c);e.call(this,n,{points:s,point:c,lngLats:l,lngLat:u,originalEvent:a}),this._defaultPrevented=!1}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Bn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),Nn=function(t,e){this._map=t,this._clickTolerance=e.clickTolerance};Nn.prototype.reset=function(){delete this._mousedownPos},Nn.prototype.wheel=function(t){return this._firePreventable(new Bn(t.type,this._map,t))},Nn.prototype.mousedown=function(t,e){return this._mousedownPos=e,this._firePreventable(new Rn(t.type,this._map,t))},Nn.prototype.mouseup=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.click=function(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.dblclick=function(t){return this._firePreventable(new Rn(t.type,this._map,t))},Nn.prototype.mouseover=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.mouseout=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.touchstart=function(t){return this._firePreventable(new Fn(t.type,this._map,t))},Nn.prototype.touchmove=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype.touchend=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype.touchcancel=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},Nn.prototype.isEnabled=function(){return!0},Nn.prototype.isActive=function(){return!1},Nn.prototype.enable=function(){},Nn.prototype.disable=function(){};var jn=function(t){this._map=t};jn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},jn.prototype.mousemove=function(t){this._map.fire(new Rn(t.type,this._map,t))},jn.prototype.mousedown=function(){this._delayContextMenu=!0},jn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Rn(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},jn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new Rn(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},jn.prototype.isEnabled=function(){return!0},jn.prototype.isActive=function(){return!1},jn.prototype.enable=function(){},jn.prototype.disable=function(){};var Un=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Vn(t,e){for(var r={},n=0;n<t.length;n++)r[t[n].identifier]=e[n];return r}Un.prototype.isEnabled=function(){return!!this._enabled},Un.prototype.isActive=function(){return!!this._active},Un.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Un.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Un.prototype.mousedown=function(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(r.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)},Un.prototype.mousemoveWindow=function(t,e){if(this._active){var n=e;if(!(this._lastPos.equals(n)||!this._box&&n.dist(this._startPos)<this._clickTolerance)){var i=this._startPos;this._lastPos=n,this._box||(this._box=r.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var a=Math.min(i.x,n.x),o=Math.max(i.x,n.x),s=Math.min(i.y,n.y),l=Math.max(i.y,n.y);r.setTransform(this._box,\"translate(\"+a+\"px,\"+s+\"px)\"),this._box.style.width=o-a+\"px\",this._box.style.height=l-s+\"px\"}}},Un.prototype.mouseupWindow=function(e,n){var i=this;if(this._active&&0===e.button){var a=this._startPos,o=n;if(this.reset(),r.suppressClick(),a.x!==o.x||a.y!==o.y)return this._map.fire(new t.Event(\"boxzoomend\",{originalEvent:e})),{cameraAnimation:function(t){return t.fitScreenCoordinates(a,o,i._map.getBearing(),{linear:!0})}};this._fireEvent(\"boxzoomcancel\",e)}},Un.prototype.keydown=function(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent(\"boxzoomcancel\",t))},Un.prototype.reset=function(){this._active=!1,this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},Un.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var qn=function(t){this.reset(),this.numTouches=t.numTouches};qn.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},qn.prototype.touchstart=function(e,r,n){(this.centroid||n.length>this.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n<i.length;n+=1){var a=i[n];r._add(a)}return r.div(e.length)}(r),this.touches=Vn(n,r)))},qn.prototype.touchmove=function(t,e,r){if(!this.aborted&&this.centroid){var n=Vn(r,e);for(var i in this.touches){var a=this.touches[i],o=n[i];(!o||o.dist(a)>30)&&(this.aborted=!0)}}},qn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Hn=function(t){this.singleTap=new qn(t),this.numTaps=t.numTaps,this.reset()};Hn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Hn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Hn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Hn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Gn=function(){this._zoomIn=new Hn({numTouches:1,numTaps:2}),this._zoomOut=new Hn({numTouches:2,numTaps:1}),this.reset()};Gn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Gn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Gn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Gn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Gn.prototype.touchcancel=function(){this.reset()},Gn.prototype.enable=function(){this._enabled=!0},Gn.prototype.disable=function(){this._enabled=!1,this.reset()},Gn.prototype.isEnabled=function(){return this._enabled},Gn.prototype.isActive=function(){return this._active};var Yn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};Yn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Yn.prototype._correctButton=function(t,e){return!1},Yn.prototype._move=function(t,e){return{}},Yn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},Yn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r&&(t.preventDefault(),this._moved||!(e.dist(r)<this._clickTolerance)))return this._moved=!0,this._lastPoint=e,this._move(r,e)},Yn.prototype.mouseupWindow=function(t){r.mouseButton(t)===this._eventButton&&(this._moved&&r.suppressClick(),this.reset())},Yn.prototype.enable=function(){this._enabled=!0},Yn.prototype.disable=function(){this._enabled=!1,this.reset()},Yn.prototype.isEnabled=function(){return this._enabled},Yn.prototype.isActive=function(){return this._active};var Wn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.mousedown=function(e,r){t.prototype.mousedown.call(this,e,r),this._lastPoint&&(this._active=!0)},e.prototype._correctButton=function(t,e){return 0===e&&!t.ctrlKey},e.prototype._move=function(t,e){return{around:e,panDelta:e.sub(t)}},e}(Yn),Xn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=.8*(e.x-t.x);if(r)return this._active=!0,{bearingDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Yn),Zn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=-.5*(e.y-t.y);if(r)return this._active=!0,{pitchDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Yn),Jn=function(t){this._minTouches=1,this._clickTolerance=t.clickTolerance||1,this.reset()};Jn.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new t.Point(0,0)},Jn.prototype.touchstart=function(t,e,r){return this._calculateTransform(t,e,r)},Jn.prototype.touchmove=function(t,e,r){if(this._active)return t.preventDefault(),this._calculateTransform(t,e,r)},Jn.prototype.touchend=function(t,e,r){this._calculateTransform(t,e,r),this._active&&r.length<this._minTouches&&this.reset()},Jn.prototype.touchcancel=function(){this.reset()},Jn.prototype._calculateTransform=function(e,r,n){n.length>0&&(this._active=!0);var i=Vn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var c=i[l],u=this._touches[l];u&&(a._add(c),o._add(c.sub(u)),s++,i[l]=c)}if(this._touches=i,!(s<this._minTouches)&&o.mag()){var f=o.div(s);if(this._sum._add(f),!(this._sum.mag()<this._clickTolerance))return{around:a.div(s),panDelta:f}}},Jn.prototype.enable=function(){this._enabled=!0},Jn.prototype.disable=function(){this._enabled=!1,this.reset()},Jn.prototype.isEnabled=function(){return this._enabled},Jn.prototype.isActive=function(){return this._active};var Kn=function(){this.reset()};function Qn(t,e,r){for(var n=0;n<t.length;n++)if(t[n].identifier===r)return e[n]}Kn.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},Kn.prototype._start=function(t){},Kn.prototype._move=function(t,e,r){return{}},Kn.prototype.touchstart=function(t,e,r){this._firstTwoTouches||r.length<2||(this._firstTwoTouches=[r[0].identifier,r[1].identifier],this._start([e[0],e[1]]))},Kn.prototype.touchmove=function(t,e,r){if(this._firstTwoTouches){t.preventDefault();var n=this._firstTwoTouches,i=n[0],a=n[1],o=Qn(r,e,i),s=Qn(r,e,a);if(o&&s){var l=this._aroundCenter?null:o.add(s).div(2);return this._move([o,s],l,t)}}},Kn.prototype.touchend=function(t,e,n){if(this._firstTwoTouches){var i=this._firstTwoTouches,a=i[0],o=i[1],s=Qn(n,e,a),l=Qn(n,e,o);s&&l||(this._active&&r.suppressClick(),this.reset())}},Kn.prototype.touchcancel=function(){this.reset()},Kn.prototype.enable=function(t){this._enabled=!0,this._aroundCenter=!!t&&\"center\"===t.around},Kn.prototype.disable=function(){this._enabled=!1,this.reset()},Kn.prototype.isEnabled=function(){return this._enabled},Kn.prototype.isActive=function(){return this._active};function $n(t,e){return Math.log(t/e)/Math.LN2}var ti=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._distance,delete this._startDistance},e.prototype._start=function(t){this._startDistance=this._distance=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._distance;if(this._distance=t[0].dist(t[1]),this._active||!(Math.abs($n(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:$n(this._distance,r),pinchAround:e}},e}(Kn);function ei(t,e){return 180*t.angleWith(e)/Math.PI}var ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},e.prototype._start=function(t){this._startVector=this._vector=t[0].sub(t[1]),this._minDiameter=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._vector;if(this._vector=t[0].sub(t[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:ei(this._vector,r),pinchAround:e}},e.prototype._isBelowThreshold=function(t){this._minDiameter=Math.min(this._minDiameter,t.mag());var e=25/(Math.PI*this._minDiameter)*360,r=ei(t,this._startVector);return Math.abs(r)<e},e}(Kn);function ni(t){return Math.abs(t.y)>Math.abs(t.x)}var ii=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,ni(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid){this._lastPoints=t,this._active=!0;return{pitchDelta:-.5*((n.y+i.y)/2)}}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return ni(t)&&ni(e)&&a}},e}(Kn),ai={panStep:100,bearingStep:15,pitchStep:10},oi=function(){var t=ai;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep};function si(t){return t*(2-t)}oi.prototype.reset=function(){this._active=!1},oi.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:si,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},oi.prototype.enable=function(){this._enabled=!0},oi.prototype.disable=function(){this._enabled=!1,this.reset()},oi.prototype.isEnabled=function(){return this._enabled},oi.prototype.isActive=function(){return this._active};var li=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=1/450,t.bindAll([\"_onWheel\",\"_onTimeout\",\"_onScrollFrame\",\"_onScrollFinished\"],this)};li.prototype.setZoomRate=function(t){this._defaultZoomRate=t},li.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},li.prototype.isEnabled=function(){return!!this._enabled},li.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},li.prototype.isZooming=function(){return!!this._zooming},li.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},li.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},li.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%4.000244140625==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},li.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},li.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},li.prototype.renderFrame=function(){return this._onScrollFrame()},li.prototype._onScrollFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>4.000244140625?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,c=this._easing,u=!1;if(\"wheel\"===this._type&&l&&c){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=c(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):u=!0}else o=s,u=!0;return this._active=!0,u&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!u,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},li.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},li.prototype.reset=function(){this._active=!1};var ci=function(t,e){this._clickZoom=t,this._tapZoom=e};ci.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},ci.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},ci.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},ci.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var ui=function(){this.reset()};ui.prototype.reset=function(){this._active=!1},ui.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},ui.prototype.enable=function(){this._enabled=!0},ui.prototype.disable=function(){this._enabled=!1,this.reset()},ui.prototype.isEnabled=function(){return this._enabled},ui.prototype.isActive=function(){return this._active};var fi=function(){this._tap=new Hn({numTouches:1,numTaps:1}),this.reset()};fi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},fi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},fi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},fi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},fi.prototype.touchcancel=function(){this.reset()},fi.prototype.enable=function(){this._enabled=!0},fi.prototype.disable=function(){this._enabled=!1,this.reset()},fi.prototype.isEnabled=function(){return this._enabled},fi.prototype.isActive=function(){return this._active};var hi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};hi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},hi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},hi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},hi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var pi=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};pi.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},pi.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},pi.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},pi.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var di=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};di.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},di.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},di.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},di.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},di.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},di.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var mi=function(t){return t.zoom||t.drag||t.pitch||t.rotate},gi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function vi(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var yi=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new On(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!1}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;a<o.length;a+=1){var s=o[a],l=s[0],c=s[1],u=s[2];r.addEventListener(l,c,l===t.window.document?this.handleWindowEvent:this.handleEvent,u)}};yi.prototype.destroy=function(){for(var e=0,n=this._listeners;e<n.length;e+=1){var i=n[e],a=i[0],o=i[1],s=i[2];r.removeEventListener(a,o,a===t.window.document?this.handleWindowEvent:this.handleEvent,s)}},yi.prototype._addDefaultHandlers=function(t){var e=this._map,r=e.getCanvasContainer();this._add(\"mapEvent\",new Nn(e,t));var n=e.boxZoom=new Un(e,t);this._add(\"boxZoom\",n);var i=new Gn,a=new ui;e.doubleClickZoom=new ci(a,i),this._add(\"tapZoom\",i),this._add(\"clickZoom\",a);var o=new fi;this._add(\"tapDragZoom\",o);var s=e.touchPitch=new ii;this._add(\"touchPitch\",s);var l=new Xn(t),c=new Zn(t);e.dragRotate=new pi(t,l,c),this._add(\"mouseRotate\",l,[\"mousePitch\"]),this._add(\"mousePitch\",c,[\"mouseRotate\"]);var u=new Wn(t),f=new Jn(t);e.dragPan=new hi(r,u,f),this._add(\"mousePan\",u),this._add(\"touchPan\",f,[\"touchZoom\",\"touchRotate\"]);var h=new ri,p=new ti;e.touchZoomRotate=new di(r,p,h,o),this._add(\"touchRotate\",h,[\"touchPan\",\"touchZoom\"]),this._add(\"touchZoom\",p,[\"touchPan\",\"touchRotate\"]);var d=e.scrollZoom=new li(e,this);this._add(\"scrollZoom\",d,[\"mousePan\"]);var m=e.keyboard=new oi;this._add(\"keyboard\",m),this._add(\"blockableMapEvent\",new jn(e));for(var g=0,v=[\"boxZoom\",\"doubleClickZoom\",\"tapDragZoom\",\"touchPitch\",\"dragRotate\",\"dragPan\",\"touchZoomRotate\",\"scrollZoom\",\"keyboard\"];g<v.length;g+=1){var y=v[g];t.interactive&&t[y]&&e[y].enable(t[y])}},yi.prototype._add=function(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e},yi.prototype.stop=function(){if(!this._updatingCamera){for(var t=0,e=this._handlers;t<e.length;t+=1){e[t].handler.reset()}this._inertia.clear(),this._fireEvents({},{}),this._changes=[]}},yi.prototype.isActive=function(){for(var t=0,e=this._handlers;t<e.length;t+=1){if(e[t].handler.isActive())return!0}return!1},yi.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},yi.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},yi.prototype.isMoving=function(){return Boolean(mi(this._eventsInProgress))||this.isZooming()},yi.prototype._blockedByActive=function(t,e,r){for(var n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1},yi.prototype.handleWindowEvent=function(t){this.handleEvent(t,t.type+\"Window\")},yi.prototype._getMapTouches=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=i.target;this._el.contains(a)&&e.push(i)}return e},yi.prototype.handleEvent=function(t,e){if(\"blur\"!==t.type){this._updatingCamera=!0;for(var n=\"renderFrame\"===t.type?void 0:t,i={needsRenderFrame:!1},a={},o={},s=t.touches?this._getMapTouches(t.touches):void 0,l=s?r.touchPos(this._el,s):r.mousePos(this._el,t),c=0,u=this._handlers;c<u.length;c+=1){var f=u[c],h=f.handlerName,p=f.handler,d=f.allowed;if(p.isEnabled()){var m=void 0;this._blockedByActive(o,d,h)?p.reset():p[e||t.type]&&(m=p[e||t.type](t,l,s),this.mergeHandlerResult(i,a,m,h,n),m&&m.needsRenderFrame&&this._triggerRenderFrame()),(m||p.isActive())&&(o[h]=p)}}var g={};for(var v in this._previousActiveHandlers)o[v]||(g[v]=n);this._previousActiveHandlers=o,(Object.keys(g).length||vi(i))&&(this._changes.push([i,a,g]),this._triggerRenderFrame()),(Object.keys(o).length||vi(i))&&this._map._stop(!0),this._updatingCamera=!1;var y=i.cameraAnimation;y&&(this._inertia.clear(),this._fireEvents({},{}),this._changes=[],y(this._map))}else this.stop()},yi.prototype.mergeHandlerResult=function(e,r,n,i,a){if(n){t.extend(e,n);var o={handlerName:i,originalEvent:n.originalEvent||a};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}},yi.prototype._applyChanges=function(){for(var e={},r={},n={},i=0,a=this._changes;i<a.length;i+=1){var o=a[i],s=o[0],l=o[1],c=o[2];s.panDelta&&(e.panDelta=(e.panDelta||new t.Point(0,0))._add(s.panDelta)),s.zoomDelta&&(e.zoomDelta=(e.zoomDelta||0)+s.zoomDelta),s.bearingDelta&&(e.bearingDelta=(e.bearingDelta||0)+s.bearingDelta),s.pitchDelta&&(e.pitchDelta=(e.pitchDelta||0)+s.pitchDelta),void 0!==s.around&&(e.around=s.around),void 0!==s.pinchAround&&(e.pinchAround=s.pinchAround),s.noInertia&&(e.noInertia=s.noInertia),t.extend(r,l),t.extend(n,c)}this._updateMapTransform(e,r,n),this._changes=[]},yi.prototype._updateMapTransform=function(t,e,r){var n=this._map,i=n.transform;if(!vi(t))return this._fireEvents(e,r);var a=t.panDelta,o=t.zoomDelta,s=t.bearingDelta,l=t.pitchDelta,c=t.around,u=t.pinchAround;void 0!==u&&(c=u),n._stop(!0),c=c||n.transform.centerPoint;var f=i.pointLocation(a?c.sub(a):c);s&&(i.bearing+=s),l&&(i.pitch+=l),o&&(i.zoom+=o),i.setLocationAtPoint(f,c),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r)},yi.prototype._fireEvents=function(e,r){var n=this,i=mi(this._eventsInProgress),a=mi(e),o={};for(var s in e){var l=e[s].originalEvent;this._eventsInProgress[s]||(o[s+\"start\"]=l),this._eventsInProgress[s]=e[s]}for(var c in!i&&a&&this._fireEvent(\"movestart\",a.originalEvent),o)this._fireEvent(c,o[c]);for(var u in e.rotate&&(this._bearingChanged=!0),a&&this._fireEvent(\"move\",a.originalEvent),e){var f=e[u].originalEvent;this._fireEvent(u,f)}var h,p={};for(var d in this._eventsInProgress){var m=this._eventsInProgress[d],g=m.handlerName,v=m.originalEvent;this._handlersById[g].isActive()||(delete this._eventsInProgress[d],h=r[g]||v,p[d+\"end\"]=h)}for(var y in p)this._fireEvent(y,p[y]);var x=mi(this._eventsInProgress);if((i||a)&&!x){this._updatingCamera=!0;var b=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),_=function(t){return 0!==t&&-n._bearingSnap<t&&t<n._bearingSnap};b?(_(b.bearing||this._map.getBearing())&&(b.bearing=0),this._map.easeTo(b,{originalEvent:h})):(this._map.fire(new t.Event(\"moveend\",{originalEvent:h})),_(this._map.getBearing())&&this._map.resetNorth()),this._bearingChanged=!1,this._updatingCamera=!1}},yi.prototype._fireEvent=function(e,r){this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},yi.prototype._triggerRenderFrame=function(){var t=this;void 0===this._frameId&&(this._frameId=this._map._requestRenderFrame((function(e){delete t._frameId,t.handleEvent(new gi(\"renderFrame\",{timeStamp:e})),t._applyChanges()})))};var xi=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll([\"_renderFrameCallback\"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.getPadding=function(){return this.transform.padding},r.prototype.setPadding=function(t,e){return this.jumpTo({padding:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){return e=t.LngLatBounds.convert(e),this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),0,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,i){var a={top:0,bottom:0,right:0,left:0};if(\"number\"==typeof(i=t.extend({padding:a,offset:[0,0],maxZoom:this.transform.maxZoom},i)).padding){var o=i.padding;i.padding={top:o,bottom:o,right:o,left:o}}i.padding=t.extend(a,i.padding);var s=this.transform,l=s.padding,c=s.project(t.LngLat.convert(e)),u=s.project(t.LngLat.convert(r)),f=c.rotate(-n*Math.PI/180),h=u.rotate(-n*Math.PI/180),p=new t.Point(Math.max(f.x,h.x),Math.max(f.y,h.y)),d=new t.Point(Math.min(f.x,h.x),Math.min(f.y,h.y)),m=p.sub(d),g=(s.width-(l.left+l.right+i.padding.left+i.padding.right))/m.x,v=(s.height-(l.top+l.bottom+i.padding.top+i.padding.bottom))/m.y;if(!(v<0||g<0)){var y=Math.min(s.scaleZoom(s.scale*Math.min(g,v)),i.maxZoom),x=t.Point.convert(i.offset),b=(i.padding.left-i.padding.right)/2,_=(i.padding.top-i.padding.bottom)/2,w=new t.Point(x.x+b,x.y+_).mult(s.scale/s.zoomScale(y));return{center:s.unproject(c.add(u).div(2).sub(w)),zoom:y,bearing:n}}t.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,i,a){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,i),i,a)},r.prototype._fitInternal=function(e,r,n){return e?(delete(r=t.extend(e,r)).padding,r.linear?this.easeTo(r,n):this.flyTo(r,n)):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,i=!1,a=!1,o=!1;return\"zoom\"in e&&n.zoom!==+e.zoom&&(i=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),\"bearing\"in e&&n.bearing!==+e.bearing&&(a=!0,n.bearing=+e.bearing),\"pitch\"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),null==e.padding||n.isPaddingEqual(e.padding)||(n.padding=e.padding),this.fire(new t.Event(\"movestart\",r)).fire(new t.Event(\"move\",r)),i&&this.fire(new t.Event(\"zoomstart\",r)).fire(new t.Event(\"zoom\",r)).fire(new t.Event(\"zoomend\",r)),a&&this.fire(new t.Event(\"rotatestart\",r)).fire(new t.Event(\"rotate\",r)).fire(new t.Event(\"rotateend\",r)),o&&this.fire(new t.Event(\"pitchstart\",r)).fire(new t.Event(\"pitch\",r)).fire(new t.Event(\"pitchend\",r)),this.fire(new t.Event(\"moveend\",r))},r.prototype.easeTo=function(e,r){var n=this;this._stop(!1,e.easeId),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||!e.essential&&t.browser.prefersReducedMotion)&&(e.duration=0);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=this.getPadding(),c=\"zoom\"in e?+e.zoom:a,u=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,f=\"pitch\"in e?+e.pitch:s,h=\"padding\"in e?e.padding:i.padding,p=t.Point.convert(e.offset),d=i.centerPoint.add(p),m=i.pointLocation(d),g=t.LngLat.convert(e.center||m);this._normalizeCenter(g);var v,y,x=i.project(m),b=i.project(g).sub(x),_=i.zoomScale(c-a);e.around&&(v=t.LngLat.convert(e.around),y=i.locationPoint(v));var w={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||c!==a,this._rotating=this._rotating||o!==u,this._pitching=this._pitching||f!==s,this._padding=!i.isPaddingEqual(h),this._easeId=e.easeId,this._prepareEase(r,e.noMoveStart,w),clearTimeout(this._easeEndTimeoutID),this._ease((function(e){if(n._zooming&&(i.zoom=t.number(a,c,e)),n._rotating&&(i.bearing=t.number(o,u,e)),n._pitching&&(i.pitch=t.number(s,f,e)),n._padding&&(i.interpolatePadding(l,h,e),d=i.centerPoint.add(p)),v)i.setLocationAtPoint(v,y);else{var m=i.zoomScale(i.zoom-a),g=c>a?Math.min(2,_):Math.max(.5,_),w=Math.pow(g,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(m));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),c=this.getPadding(),u=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(u-o),m=t.Point.convert(e.offset),g=a.centerPoint.add(m),v=a.pointLocation(g),y=t.LngLat.convert(e.center||v);this._normalizeCenter(y);var x=a.project(v),b=a.project(y).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var M=t.clamp(Math.min(e.minZoom,o,u),a.minZoom,a.maxZoom),A=w/a.zoomScale(M-o);_=Math.sqrt(A/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function L(t){return(Math.exp(t)-Math.exp(-t))/2}function C(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),I=function(t){return C(P)/C(P+_*t)},O=function(t){return w*((C(P)*(L(e=P+_*t)/C(e))-L(P))/S)/k;var e},z=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(z)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var D=T<w?-1:1;z=Math.abs(Math.log(T/w))/_,O=function(){return 0},I=function(t){return Math.exp(D*_*t)}}if(\"duration\"in e)e.duration=+e.duration;else{var R=\"screenSpeed\"in e?+e.screenSpeed/_:+e.speed;e.duration=1e3*z/R}return e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*z,d=1/I(i);a.zoom=1===e?u:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(c,p,e),g=a.centerPoint.add(m));var v=1===e?y:a.unproject(x.add(b.mult(O(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?v.wrap():v,g),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop()}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),bi=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};bi.prototype.getDefaultPosition=function(){return\"bottom-right\"},bi.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},bi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},bi.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n<r.length-1?\"&\":\"\")),t}),\"?\");e.href=t.config.FEEDBACK_URL+\"/\"+n+(this._map._hash?this._map._hash.getHashString(!0):\"\"),e.rel=\"noopener nofollow\"}},bi.prototype._updateData=function(t){!t||\"metadata\"!==t.sourceDataType&&\"style\"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},bi.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((function(t){return\"string\"!=typeof t?\"\":t}))):\"string\"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var i=r[n];if(i.used){var a=i.getSource();a.attribution&&t.indexOf(a.attribution)<0&&t.push(a.attribution)}}t.sort((function(t,e){return t.length-e.length}));var o=(t=t.filter((function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},bi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\")};var _i=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};_i.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},_i.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},_i.prototype.getDefaultPosition=function(){return\"bottom-left\"},_i.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},_i.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t){if(t[e].getSource().mapbox_logo)return!0}return!1}},_i.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var wi=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};wi.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},wi.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var i=n[r];if(i.id===t)return void(i.cancelled=!0)}},wi.prototype.run=function(t){void 0===t&&(t=0);var e=this._currentlyRunning=this._queue;this._queue=[];for(var r=0,n=e;r<n.length;r+=1){var i=n[r];if(!i.cancelled&&(i.callback(t),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},wi.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var Ti={\"FullscreenControl.Enter\":\"Enter fullscreen\",\"FullscreenControl.Exit\":\"Exit fullscreen\",\"GeolocateControl.FindMyLocation\":\"Find my location\",\"GeolocateControl.LocationNotAvailable\":\"Location not available\",\"LogoControl.Title\":\"Mapbox logo\",\"NavigationControl.ResetBearing\":\"Reset bearing to north\",\"NavigationControl.ZoomIn\":\"Zoom in\",\"NavigationControl.ZoomOut\":\"Zoom out\",\"ScaleControl.Feet\":\"ft\",\"ScaleControl.Meters\":\"m\",\"ScaleControl.Kilometers\":\"km\",\"ScaleControl.Miles\":\"mi\",\"ScaleControl.NauticalMiles\":\"nm\"},ki=t.window.HTMLImageElement,Mi=t.window.HTMLElement,Ai=t.window.ImageBitmap,Si={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:60,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:\"sans-serif\",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},Ei=function(n){function i(e){var r=this;if(null!=(e=t.extend({},Si,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>60)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new Mn(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new wi,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Ti,e.locale),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof Mi))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1)),this.handlers=new yi(this,e);var a=\"string\"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new Sn(a).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new bi({customAttribution:e.customAttribution})),this.addControl(new _i,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r=\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between -2 and the current maxZoom, inclusive\")},i.prototype.getMinZoom=function(){return this.transform.minZoom},i.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()<t&&this.setPitch(t),this;throw new Error(\"minPitch must be between 0 and the current maxPitch, inclusive\")},i.prototype.getMinPitch=function(){return this.transform.minPitch},i.prototype.setMaxPitch=function(t){if((t=null==t?60:t)>60)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new Rn(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new Rn(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new Rn(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;if(void 0===r)return n.prototype.off.call(this,t,e);return this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o<a.length;o++){var s=a[o];if(s.layer===e&&s.listener===r){for(var l in s.delegates)i.off(l,s.delegates[l]);return a.splice(o,1),i}}}(this._delegatedListeners),this},i.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||\"number\"==typeof e[0])n=[t.Point.convert(e)];else{var i=t.Point.convert(e[0]),a=t.Point.convert(e[1]);n=[i,new t.Point(a.x,i.y),a,new t.Point(i.x,a.y),i]}return this.style.queryRenderedFeatures(n,r,this.transform)},i.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},i.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},i.prototype._getUIString=function(t){var e=this._locale[t];if(null==e)throw new Error(\"Missing UI string '\"+t+\"'\");return e},i.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new He(this,e||{}),this.style.setEventedParent(this,{style:this.style}),\"string\"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},i.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new He(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},i.prototype._diffStyle=function(e,r){var n=this;if(\"string\"==typeof e){var i=this._requestManager.normalizeStyleURL(e),a=this._requestManager.transformRequest(i,t.ResourceType.Style);t.getJSON(a,(function(e,i){e?n.fire(new t.ErrorEvent(e)):i&&n._updateDiff(i,r)}))}else\"object\"==typeof e&&this._updateDiff(e,r)},i.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce(\"Unable to perform style diff: \"+(n.message||n.error||n)+\".  Rebuilding the style from scratch.\"),this._updateStyle(e,r)}},i.prototype.getStyle=function(){if(this.style)return this.style.serialize()},i.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce(\"There is no style added to the map.\")},i.prototype.addSource=function(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)},i.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error(\"There is no source with ID '\"+e+\"'\")))},i.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var i=r[n];if(\"loaded\"!==i.state&&\"errored\"!==i.state)return!1}}return!0},i.prototype.addSourceType=function(t,e,r){return this._lazyInitEmptyStyle(),this.style.addSourceType(t,e,r)},i.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},i.prototype.getSource=function(t){return this.style.getSource(t)},i.prototype.addImage=function(e,r,n){void 0===n&&(n={});var i=n.pixelRatio;void 0===i&&(i=1);var a=n.sdf;void 0===a&&(a=!1);var o=n.stretchX,s=n.stretchY,l=n.content;this._lazyInitEmptyStyle();if(r instanceof ki||Ai&&r instanceof Ai){var c=t.browser.getImageData(r),u=c.width,f=c.height,h=c.data;this.style.addImage(e,{data:new t.RGBAImage({width:u,height:f},h),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var p=r.width,d=r.height,m=r.data,g=r;this.style.addImage(e,{data:new t.RGBAImage({width:p,height:d},new Uint8Array(m)),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0,userImage:g}),g.onAdd&&g.onAdd(this,e)}},i.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));var i=r instanceof ki||Ai&&r instanceof Ai?t.browser.getImageData(r):r,a=i.width,o=i.height,s=i.data;if(void 0===a||void 0===o)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));if(a!==n.data.width||o!==n.data.height)return this.fire(new t.ErrorEvent(new Error(\"The width and height of the updated image must be that same as the previous version of the image\")));var l=!(r instanceof ki||Ai&&r instanceof Ai);n.data.replace(s,l),this.style.updateImage(e,n)},i.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error(\"Missing required image id\"))),!1)},i.prototype.removeImage=function(t){this.style.removeImage(t)},i.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},i.prototype.listImages=function(){return this.style.listImages()},i.prototype.addLayer=function(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)},i.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},i.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},i.prototype.getLayer=function(t){return this.style.getLayer(t)},i.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},i.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},i.prototype.getFilter=function(t){return this.style.getFilter(t)},i.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},i.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},i.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},i.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},i.prototype.setLight=function(t,e){return void 0===e&&(e={}),this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)},i.prototype.getLight=function(){return this.style.getLight()},i.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},i.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},i.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},i.prototype.getContainer=function(){return this._container},i.prototype.getCanvasContainer=function(){return this._canvasContainer},i.prototype.getCanvas=function(){return this._canvas},i.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},i.prototype._detectMissingCSS=function(){\"rgb(250, 128, 114)\"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue(\"background-color\")&&t.warnOnce(\"This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.\")},i.prototype._setupContainer=function(){var t=this._container;t.classList.add(\"mapboxgl-map\"),(this._missingCSSCanary=r.create(\"div\",\"mapboxgl-canary\",t)).style.visibility=\"hidden\",this._detectMissingCSS();var e=this._canvasContainer=r.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=r.create(\"canvas\",\"mapboxgl-canvas\",e),this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var i=this._controlContainer=r.create(\"div\",\"mapboxgl-control-container\",t),a=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach((function(t){a[t]=r.create(\"div\",\"mapboxgl-ctrl-\"+t,i)}))},i.prototype._resizeCanvas=function(e,r){var n=t.browser.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+\"px\",this._canvas.style.height=r+\"px\"},i.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext(\"webgl\",r)||this._canvas.getContext(\"experimental-webgl\",r);n?(this.painter=new _n(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error(\"Failed to initialize WebGL\")))},i.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event(\"webglcontextlost\",{originalEvent:e}))},i.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event(\"webglcontextrestored\",{originalEvent:e}))},i.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},i.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},i.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},i.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},i.prototype._render=function(e){var r,n=this,i=0,a=this.painter.context.extTimerQuery;if(this.listens(\"gpu-timing-frame\")&&(r=a.createQueryEXT(),a.beginQueryEXT(a.TIME_ELAPSED_EXT,r),i=t.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(e),!this._removed){var o=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var s=this.transform.zoom,l=t.browser.now();this.style.zoomHistory.update(s,l);var c=new t.EvaluationParameters(s,{now:l,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),u=c.crossFadingFactor();1===u&&u===this._crossFadingFactor||(o=!0,this._crossFadingFactor=u),this.style.update(c)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens(\"gpu-timing-layer\")}),this.fire(new t.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event(\"load\"))),this.style&&(this.style.hasTransitions()||o)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens(\"gpu-timing-frame\")){var f=t.browser.now()-i;a.endQueryEXT(a.TIME_ELAPSED_EXT,r),setTimeout((function(){var e=a.getQueryObjectEXT(r,a.QUERY_RESULT_EXT)/1e6;a.deleteQueryEXT(r),n.fire(new t.Event(\"gpu-timing-frame\",{cpuTime:f,gpuTime:e}))}),50)}if(this.listens(\"gpu-timing-layer\")){var h=this.painter.collectGpuTimers();setTimeout((function(){var e=n.painter.queryGpuTimers(h);n.fire(new t.Event(\"gpu-timing-layer\",{layerTimes:e}))}),50)}return this._sourcesDirty||this._styleDirty||this._placementDirty||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&(this._fullyLoaded||(this._fullyLoaded=!0),this.fire(new t.Event(\"idle\"))),this}},i.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1){r[e].onRemove(this)}this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener(\"resize\",this._onWindowResize,!1),t.window.removeEventListener(\"online\",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");n&&n.loseContext(),Li(this._canvasContainer),Li(this._controlContainer),Li(this._missingCSSCanary),this._container.classList.remove(\"mapboxgl-map\"),this._removed=!0,this.fire(new t.Event(\"remove\"))},i.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame((function(t){e._frame=null,e._render(t)})))},i.prototype._onWindowOnline=function(){this._update()},i.prototype._onWindowResize=function(t){this._trackResize&&this.resize({originalEvent:t})._update()},a.showTileBoundaries.get=function(){return!!this._showTileBoundaries},a.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},a.showPadding.get=function(){return!!this._showPadding},a.showPadding.set=function(t){this._showPadding!==t&&(this._showPadding=t,this._update())},a.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},a.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},a.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},a.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},a.repaint.get=function(){return!!this._repaint},a.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},a.vertices.get=function(){return!!this._vertices},a.vertices.set=function(t){this._vertices=t,this._update()},i.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},a.version.get=function(){return t.version},Object.defineProperties(i.prototype,a),i}(xi);function Li(t){t.parentNode&&t.parentNode.removeChild(t)}var Ci={showCompass:!0,showZoom:!0,visualizePitch:!1},Pi=function(e){var n=this;this.options=t.extend({},Ci,e),this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this.options.showZoom&&(t.bindAll([\"_setButtonTitle\",\"_updateZoomButtons\"],this),this._zoomInButton=this._createButton(\"mapboxgl-ctrl-zoom-in\",(function(t){return n._map.zoomIn({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomInButton).setAttribute(\"aria-hidden\",!0),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-zoom-out\",(function(t){return n._map.zoomOut({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomOutButton).setAttribute(\"aria-hidden\",!0)),this.options.showCompass&&(t.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-compass\",(function(t){n.options.visualizePitch?n._map.resetNorthPitch({},{originalEvent:t}):n._map.resetNorth({},{originalEvent:t})})),this._compassIcon=r.create(\"span\",\"mapboxgl-ctrl-icon\",this._compass),this._compassIcon.setAttribute(\"aria-hidden\",!0))};Pi.prototype._updateZoomButtons=function(){var t=this._map.getZoom();this._zoomInButton.disabled=t===this._map.getMaxZoom(),this._zoomOutButton.disabled=t===this._map.getMinZoom()},Pi.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?\"scale(\"+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+\") rotateX(\"+this._map.transform.pitch+\"deg) rotateZ(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\":\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassIcon.style.transform=t},Pi.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,\"ZoomIn\"),this._setButtonTitle(this._zoomOutButton,\"ZoomOut\"),this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,\"ResetBearing\"),this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ii(this._map,this._compass,this.options.visualizePitch)),this._container},Pi.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},Pi.prototype._createButton=function(t,e){var n=r.create(\"button\",t,this._container);return n.type=\"button\",n.addEventListener(\"click\",e),n},Pi.prototype._setButtonTitle=function(t,e){var r=this._map._getUIString(\"NavigationControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)};var Ii=function(e,n,i){void 0===i&&(i=!1),this._clickTolerance=10,this.element=n,this.mouseRotate=new Xn({clickTolerance:e.dragRotate._mouseRotate._clickTolerance}),this.map=e,i&&(this.mousePitch=new Zn({clickTolerance:e.dragRotate._mousePitch._clickTolerance})),t.bindAll([\"mousedown\",\"mousemove\",\"mouseup\",\"touchstart\",\"touchmove\",\"touchend\",\"reset\"],this),r.addEventListener(n,\"mousedown\",this.mousedown),r.addEventListener(n,\"touchstart\",this.touchstart,{passive:!1}),r.addEventListener(n,\"touchmove\",this.touchmove),r.addEventListener(n,\"touchend\",this.touchend),r.addEventListener(n,\"touchcancel\",this.reset)};function Oi(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var i=new t.LngLat(e.lng-360,e.lat),a=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(i).distSqr(r)<o?e=i:n.locationPoint(a).distSqr(r)<o&&(e=a)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ii.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ii.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ii.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ii.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ii.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ii.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ii.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ii.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ii.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ii.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ii.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};var zi={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function Di(t,e,r){var n=t.classList;for(var i in zi)n.remove(\"mapboxgl-\"+r+\"-anchor-\"+i);n.add(\"mapboxgl-\"+r+\"-anchor-\"+e)}var Ri,Fi=function(e){function n(n,i){var a=this;if(e.call(this),(n instanceof t.window.HTMLElement||i)&&(n=t.extend({element:n},i)),t.bindAll([\"_update\",\"_onMove\",\"_onUp\",\"_addDragHandler\",\"_onMapClick\",\"_onKeyPress\"],this),this._anchor=n&&n.anchor||\"center\",this._color=n&&n.color||\"#3FB1CE\",this._draggable=n&&n.draggable||!1,this._state=\"inactive\",this._rotation=n&&n.rotation||0,this._rotationAlignment=n&&n.rotationAlignment||\"auto\",this._pitchAlignment=n&&n.pitchAlignment&&\"auto\"!==n.pitchAlignment?n.pitchAlignment:this._rotationAlignment,n&&n.element)this._element=n.element,this._offset=t.Point.convert(n&&n.offset||[0,0]);else{this._defaultMarker=!0,this._element=r.create(\"div\"),this._element.setAttribute(\"aria-label\",\"Map marker\");var o=r.createNS(\"http://www.w3.org/2000/svg\",\"svg\");o.setAttributeNS(null,\"display\",\"block\"),o.setAttributeNS(null,\"height\",\"41px\"),o.setAttributeNS(null,\"width\",\"27px\"),o.setAttributeNS(null,\"viewBox\",\"0 0 27 41\");var s=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");s.setAttributeNS(null,\"stroke\",\"none\"),s.setAttributeNS(null,\"stroke-width\",\"1\"),s.setAttributeNS(null,\"fill\",\"none\"),s.setAttributeNS(null,\"fill-rule\",\"evenodd\");var l=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");l.setAttributeNS(null,\"fill-rule\",\"nonzero\");var c=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");c.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),c.setAttributeNS(null,\"fill\",\"#000000\");for(var u=0,f=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];u<f.length;u+=1){var h=f[u],p=r.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");p.setAttributeNS(null,\"opacity\",\"0.04\"),p.setAttributeNS(null,\"cx\",\"10.5\"),p.setAttributeNS(null,\"cy\",\"5.80029008\"),p.setAttributeNS(null,\"rx\",h.rx),p.setAttributeNS(null,\"ry\",h.ry),c.appendChild(p)}var d=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");d.setAttributeNS(null,\"fill\",this._color);var m=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");m.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),d.appendChild(m);var g=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");g.setAttributeNS(null,\"opacity\",\"0.25\"),g.setAttributeNS(null,\"fill\",\"#000000\");var v=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");v.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),g.appendChild(v);var y=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");y.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),y.setAttributeNS(null,\"fill\",\"#FFFFFF\");var x=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");x.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var b=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");b.setAttributeNS(null,\"fill\",\"#000000\"),b.setAttributeNS(null,\"opacity\",\"0.25\"),b.setAttributeNS(null,\"cx\",\"5.5\"),b.setAttributeNS(null,\"cy\",\"5.5\"),b.setAttributeNS(null,\"r\",\"5.4999962\");var _=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");_.setAttributeNS(null,\"fill\",\"#FFFFFF\"),_.setAttributeNS(null,\"cx\",\"5.5\"),_.setAttributeNS(null,\"cy\",\"5.5\"),_.setAttributeNS(null,\"r\",\"5.4999962\"),x.appendChild(b),x.appendChild(_),l.appendChild(c),l.appendChild(d),l.appendChild(g),l.appendChild(y),l.appendChild(x),o.appendChild(l),this._element.appendChild(o),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add(\"mapboxgl-marker\"),this._element.addEventListener(\"dragstart\",(function(t){t.preventDefault()})),this._element.addEventListener(\"mousedown\",(function(t){t.preventDefault()})),this._element.addEventListener(\"focus\",(function(){var t=a._map.getContainer();t.scrollTop=0,t.scrollLeft=0})),Di(this._element,this._anchor,\"marker\"),this._popup=null}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on(\"move\",this._update),t.on(\"moveend\",this._update),this.setDraggable(this._draggable),this._update(),this._map.on(\"click\",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler),this._map.off(\"mouseup\",this._onUp),this._map.off(\"touchend\",this._onUp),this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener(\"keypress\",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute(\"tabindex\")),t){if(!(\"offset\"in t.options)){var e=Math.sqrt(Math.pow(13.5,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[e,-1*(24.6+e)],\"bottom-right\":[-e,-1*(24.6+e)],left:[13.5,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute(\"tabindex\"),this._originalTabIndex||this._element.setAttribute(\"tabindex\",\"0\"),this._element.addEventListener(\"keypress\",this._onKeyPress)}return this},n.prototype._onKeyPress=function(t){var e=t.code,r=t.charCode||t.keyCode;\"Space\"!==e&&\"Enter\"!==e&&32!==r&&13!==r||this.togglePopup()},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=Oi(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var e=\"\";\"viewport\"===this._rotationAlignment||\"auto\"===this._rotationAlignment?e=\"rotateZ(\"+this._rotation+\"deg)\":\"map\"===this._rotationAlignment&&(e=\"rotateZ(\"+(this._rotation-this._map.getBearing())+\"deg)\");var n=\"\";\"viewport\"===this._pitchAlignment||\"auto\"===this._pitchAlignment?n=\"rotateX(0deg)\":\"map\"===this._pitchAlignment&&(n=\"rotateX(\"+this._map.getPitch()+\"deg)\"),t&&\"moveend\"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,zi[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px) \"+n+\" \"+e)}},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",\"pending\"===this._state&&(this._state=\"active\",this.fire(new t.Event(\"dragstart\"))),this.fire(new t.Event(\"drag\"))},n.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),\"active\"===this._state&&this.fire(new t.Event(\"dragend\")),this._state=\"inactive\"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||\"auto\",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&\"auto\"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Bi={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0};var Ni=0,ji=!1,Ui=function(e){function n(r){e.call(this),this.options=t.extend({},Bi,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_onZoom\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.onAdd=function(e){var n;return this._map=e,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),n=this._setupUI,void 0!==Ri?n(Ri):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:\"geolocation\"}).then((function(t){Ri=\"denied\"!==t.state,n(Ri)})):(Ri=!!t.window.navigator.geolocation,n(Ri)),this._container},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,Ni=0,ji=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitude<e.getWest()||r.longitude>e.getEast()||r.latitude<e.getSouth()||r.latitude>e.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&ji)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new Fi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new Fi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){var r=e.originalEvent&&\"resize\"===e.originalEvent.type;e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||r||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Ni--,ji=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Ni>1?(e={maximumAge:6e5,timeout:0},ji=!0):(e=this.options.positionOptions,ji=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Vi={maxWidth:100,unit:\"metric\"},qi=function(e){this.options=t.extend({},Vi,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function Hi(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;if(l>5280)Gi(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\"));else Gi(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else if(r&&\"nautical\"===r.unit){Gi(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\"))}else s>=1e3?Gi(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):Gi(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function Gi(t,e,r,n){var i,a,o,s=(i=r,a=Math.pow(10,(\"\"+Math.floor(i)).length-1),o=(o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o),a*o),l=s/r;t.style.width=e*l+\"px\",t.innerHTML=s+\"&nbsp;\"+n}qi.prototype.getDefaultPosition=function(){return\"bottom-left\"},qi.prototype._onMove=function(){Hi(this._map,this._container,this.options)},qi.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},qi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},qi.prototype.setUnit=function(t){this.options.unit=t,Hi(this._map,this._container,this.options)};var Yi=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce(\"Full screen control 'container' must be a DOM element.\")),t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.window.document&&(this._fullscreenchange=\"MSFullscreenChange\")};Yi.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},Yi.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},Yi.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},Yi.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},Yi.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},Yi.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},Yi.prototype._isFullscreen=function(){return this._fullscreen},Yi.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},Yi.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var Wi={closeButton:!0,closeOnClick:!0,className:\"\",maxWidth:\"240px\"},Xi=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(Wi),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(e){var n=this,i=this._lngLat||this._trackPointer;if(this._map&&i&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return n._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=Oi(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||e)){var a=this._pos=this._trackPointer&&e?e:this._map.project(this._lngLat),o=this.options.anchor,s=function e(r){if(r){if(\"number\"==typeof r){var n=Math.round(Math.sqrt(.5*Math.pow(r,2)));return{center:new t.Point(0,0),top:new t.Point(0,r),\"top-left\":new t.Point(n,n),\"top-right\":new t.Point(-n,n),bottom:new t.Point(0,-r),\"bottom-left\":new t.Point(n,-n),\"bottom-right\":new t.Point(-n,-n),left:new t.Point(r,0),right:new t.Point(-r,0)}}if(r instanceof t.Point||Array.isArray(r)){var i=t.Point.convert(r);return{center:i,top:i,\"top-left\":i,\"top-right\":i,bottom:i,\"bottom-left\":i,\"bottom-right\":i,left:i,right:i}}return{center:t.Point.convert(r.center||[0,0]),top:t.Point.convert(r.top||[0,0]),\"top-left\":t.Point.convert(r[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(r[\"top-right\"]||[0,0]),bottom:t.Point.convert(r.bottom||[0,0]),\"bottom-left\":t.Point.convert(r[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(r[\"bottom-right\"]||[0,0]),left:t.Point.convert(r.left||[0,0]),right:t.Point.convert(r.right||[0,0])}}return e(new t.Point(0,0))}(this.options.offset);if(!o){var l,c=this._container.offsetWidth,u=this._container.offsetHeight;l=a.y+s.bottom.y<u?[\"top\"]:a.y>this._map.transform.height-u?[\"bottom\"]:[],a.x<c/2?l.push(\"left\"):a.x>this._map.transform.width-c/2&&l.push(\"right\"),o=0===l.length?\"bottom\":l.join(\"-\")}var f=a.add(s[o]).round();r.setTransform(this._container,zi[o]+\" translate(\"+f.x+\"px,\"+f.y+\"px)\"),Di(this._container,o,\"popup\")}},n.prototype._onClose=function(){this.remove()},n}(t.Evented);var Zi={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:Ei,NavigationControl:Pi,GeolocateControl:Ui,AttributionControl:bi,ScaleControl:qi,FullscreenControl:Yi,Popup:Xi,Marker:Fi,Style:He,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){Bt().acquire(zt)},clearPrewarmedResources:function(){var t=Rt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(zt),Rt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()\"))},get accessToken(){return t.config.ACCESS_TOKEN},set accessToken(e){t.config.ACCESS_TOKEN=e},get baseApiUrl(){return t.config.API_URL},set baseApiUrl(e){t.config.API_URL=e},get workerCount(){return Dt.workerCount},set workerCount(t){Dt.workerCount=t},get maxParallelImageRequests(){return t.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(e){t.config.MAX_PARALLEL_IMAGE_REQUESTS=e},clearStorage:function(e){t.clearTileCache(e)},workerUrl:\"\"};return Zi})),r}))},{}],458:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=1<<t+1,r=new Array(e),n=0;n<e;++n)r[n]=a(t,n);return r};var n=t(\"convex-hull\");function i(t,e,r){for(var n=new Array(t),i=0;i<t;++i)n[i]=0,i===e&&(n[i]+=.5),i===r&&(n[i]+=.5);return n}function a(t,e){if(0===e||e===(1<<t+1)-1)return[];for(var r=[],a=[],o=0;o<=t;++o)if(e&1<<o){r.push(i(t,o-1,o-1)),a.push(null);for(var s=0;s<=t;++s)~e&1<<s&&(r.push(i(t,o-1,s-1)),a.push([o,s]))}var l=n(r),c=[];t:for(o=0;o<l.length;++o){var u=l[o],f=[];for(s=0;s<u.length;++s){if(!a[u[s]])continue t;f.push(a[u[s]].slice())}c.push(f)}return c}},{\"convex-hull\":141}],459:[function(t,e,r){var n=t(\"./normalize\"),i=t(\"gl-mat4/create\"),a=t(\"gl-mat4/clone\"),o=t(\"gl-mat4/determinant\"),s=t(\"gl-mat4/invert\"),l=t(\"gl-mat4/transpose\"),c={length:t(\"gl-vec3/length\"),normalize:t(\"gl-vec3/normalize\"),dot:t(\"gl-vec3/dot\"),cross:t(\"gl-vec3/cross\")},u=i(),f=i(),h=[0,0,0,0],p=[[0,0,0],[0,0,0],[0,0,0]],d=[0,0,0];function m(t,e,r,n,i){t[0]=e[0]*n+r[0]*i,t[1]=e[1]*n+r[1]*i,t[2]=e[2]*n+r[2]*i}e.exports=function(t,e,r,i,g,v){if(e||(e=[0,0,0]),r||(r=[0,0,0]),i||(i=[0,0,0]),g||(g=[0,0,0,1]),v||(v=[0,0,0,1]),!n(u,t))return!1;if(a(f,u),f[3]=0,f[7]=0,f[11]=0,f[15]=1,Math.abs(o(f)<1e-8))return!1;var y,x,b,_,w,T,k,M=u[3],A=u[7],S=u[11],E=u[12],L=u[13],C=u[14],P=u[15];if(0!==M||0!==A||0!==S){if(h[0]=M,h[1]=A,h[2]=S,h[3]=P,!s(f,f))return!1;l(f,f),y=g,b=f,_=(x=h)[0],w=x[1],T=x[2],k=x[3],y[0]=b[0]*_+b[4]*w+b[8]*T+b[12]*k,y[1]=b[1]*_+b[5]*w+b[9]*T+b[13]*k,y[2]=b[2]*_+b[6]*w+b[10]*T+b[14]*k,y[3]=b[3]*_+b[7]*w+b[11]*T+b[15]*k}else g[0]=g[1]=g[2]=0,g[3]=1;if(e[0]=E,e[1]=L,e[2]=C,function(t,e){t[0][0]=e[0],t[0][1]=e[1],t[0][2]=e[2],t[1][0]=e[4],t[1][1]=e[5],t[1][2]=e[6],t[2][0]=e[8],t[2][1]=e[9],t[2][2]=e[10]}(p,u),r[0]=c.length(p[0]),c.normalize(p[0],p[0]),i[0]=c.dot(p[0],p[1]),m(p[1],p[1],p[0],1,-i[0]),r[1]=c.length(p[1]),c.normalize(p[1],p[1]),i[0]/=r[1],i[1]=c.dot(p[0],p[2]),m(p[2],p[2],p[0],1,-i[1]),i[2]=c.dot(p[1],p[2]),m(p[2],p[2],p[1],1,-i[2]),r[2]=c.length(p[2]),c.normalize(p[2],p[2]),i[1]/=r[2],i[2]/=r[2],c.cross(d,p[1],p[2]),c.dot(p[0],d)<0)for(var I=0;I<3;I++)r[I]*=-1,p[I][0]*=-1,p[I][1]*=-1,p[I][2]*=-1;return v[0]=.5*Math.sqrt(Math.max(1+p[0][0]-p[1][1]-p[2][2],0)),v[1]=.5*Math.sqrt(Math.max(1-p[0][0]+p[1][1]-p[2][2],0)),v[2]=.5*Math.sqrt(Math.max(1-p[0][0]-p[1][1]+p[2][2],0)),v[3]=.5*Math.sqrt(Math.max(1+p[0][0]+p[1][1]+p[2][2],0)),p[2][1]>p[1][2]&&(v[0]=-v[0]),p[0][2]>p[2][0]&&(v[1]=-v[1]),p[1][0]>p[0][1]&&(v[2]=-v[2]),!0}},{\"./normalize\":460,\"gl-mat4/clone\":280,\"gl-mat4/create\":282,\"gl-mat4/determinant\":283,\"gl-mat4/invert\":295,\"gl-mat4/transpose\":308,\"gl-vec3/cross\":364,\"gl-vec3/dot\":369,\"gl-vec3/length\":379,\"gl-vec3/normalize\":386}],460:[function(t,e,r){e.exports=function(t,e){var r=e[15];if(0===r)return!1;for(var n=1/r,i=0;i<16;i++)t[i]=e[i]*n;return!0}},{}],461:[function(t,e,r){var n=t(\"gl-vec3/lerp\"),i=t(\"mat4-recompose\"),a=t(\"mat4-decompose\"),o=t(\"gl-mat4/determinant\"),s=t(\"quat-slerp\"),l=f(),c=f(),u=f();function f(){return{translate:h(),scale:h(1),skew:h(),perspective:[0,0,0,1],quaternion:[0,0,0,1]}}function h(t){return[t||0,t||0,t||0]}e.exports=function(t,e,r,f){if(0===o(e)||0===o(r))return!1;var h=a(e,l.translate,l.scale,l.skew,l.perspective,l.quaternion),p=a(r,c.translate,c.scale,c.skew,c.perspective,c.quaternion);return!(!h||!p)&&(n(u.translate,l.translate,c.translate,f),n(u.skew,l.skew,c.skew,f),n(u.scale,l.scale,c.scale,f),n(u.perspective,l.perspective,c.perspective,f),s(u.quaternion,l.quaternion,c.quaternion,f),i(t,u.translate,u.scale,u.skew,u.perspective,u.quaternion),!0)}},{\"gl-mat4/determinant\":283,\"gl-vec3/lerp\":380,\"mat4-decompose\":459,\"mat4-recompose\":462,\"quat-slerp\":525}],462:[function(t,e,r){var n={identity:t(\"gl-mat4/identity\"),translate:t(\"gl-mat4/translate\"),multiply:t(\"gl-mat4/multiply\"),create:t(\"gl-mat4/create\"),scale:t(\"gl-mat4/scale\"),fromRotationTranslation:t(\"gl-mat4/fromRotationTranslation\")},i=(n.create(),n.create());e.exports=function(t,e,r,a,o,s){return n.identity(t),n.fromRotationTranslation(t,s,e),t[3]=o[0],t[7]=o[1],t[11]=o[2],t[15]=o[3],n.identity(i),0!==a[2]&&(i[9]=a[2],n.multiply(t,t,i)),0!==a[1]&&(i[9]=0,i[8]=a[1],n.multiply(t,t,i)),0!==a[0]&&(i[8]=0,i[4]=a[0],n.multiply(t,t,i)),n.scale(t,t,r),t}},{\"gl-mat4/create\":282,\"gl-mat4/fromRotationTranslation\":286,\"gl-mat4/identity\":293,\"gl-mat4/multiply\":297,\"gl-mat4/scale\":305,\"gl-mat4/translate\":307}],463:[function(t,e,r){\"use strict\";e.exports=Math.log2||function(t){return Math.log(t)*Math.LOG2E}},{}],464:[function(t,e,r){\"use strict\";var n=t(\"binary-search-bounds\"),i=t(\"mat4-interpolate\"),a=t(\"gl-mat4/invert\"),o=t(\"gl-mat4/rotateX\"),s=t(\"gl-mat4/rotateY\"),l=t(\"gl-mat4/rotateZ\"),c=t(\"gl-mat4/lookAt\"),u=t(\"gl-mat4/translate\"),f=(t(\"gl-mat4/scale\"),t(\"gl-vec3/normalize\")),h=[0,0,0];function 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+              "*/\n",
+              "\"use strict\";var n=Object.getOwnPropertySymbols,i=Object.prototype.hasOwnProperty,a=Object.prototype.propertyIsEnumerable;function o(t){if(null==t)throw new TypeError(\"Object.assign cannot be called with null or undefined\");return Object(t)}e.exports=function(){try{if(!Object.assign)return!1;var t=new String(\"abc\");if(t[5]=\"de\",\"5\"===Object.getOwnPropertyNames(t)[0])return!1;for(var e={},r=0;r<10;r++)e[\"_\"+String.fromCharCode(r)]=r;if(\"0123456789\"!==Object.getOwnPropertyNames(e).map((function(t){return e[t]})).join(\"\"))return!1;var n={};return\"abcdefghijklmnopqrst\".split(\"\").forEach((function(t){n[t]=t})),\"abcdefghijklmnopqrst\"===Object.keys(Object.assign({},n)).join(\"\")}catch(t){return!1}}()?Object.assign:function(t,e){for(var r,s,l=o(t),c=1;c<arguments.length;c++){for(var u in r=Object(arguments[c]))i.call(r,u)&&(l[u]=r[u]);if(n){s=n(r);for(var f=0;f<s.length;f++)a.call(r,s[f])&&(l[s[f]]=r[s[f]])}}return l}},{}],484:[function(t,e,r){\"use 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i=this.computedMatrix,a=i[0],o=i[4],s=i[8],u=i[1],f=i[5],h=i[9],p=i[2],d=i[6],m=i[10],g=e*a+r*u,v=e*o+r*f,y=e*s+r*h,x=-(d*y-m*v),b=-(m*g-p*y),_=-(p*v-d*g),w=Math.sqrt(Math.max(0,1-Math.pow(x,2)-Math.pow(b,2)-Math.pow(_,2))),T=c(x,b,_,w);T>1e-6?(x/=T,b/=T,_/=T,w/=T):(x=b=_=0,w=1);var k=this.computedRotation,M=k[0],A=k[1],S=k[2],E=k[3],L=M*w+E*x+A*_-S*b,C=A*w+E*b+S*x-M*_,P=S*w+E*_+M*b-A*x,I=E*w-M*x-A*b-S*_;if(n){x=p,b=d,_=m;var O=Math.sin(n)/l(x,b,_);x*=O,b*=O,_*=O,I=I*(w=Math.cos(e))-(L=L*w+I*x+C*_-P*b)*x-(C=C*w+I*b+P*x-L*_)*b-(P=P*w+I*_+L*b-C*x)*_}var z=c(L,C,P,I);z>1e-6?(L/=z,C/=z,P/=z,I/=z):(L=C=P=0,I=1),this.rotation.set(t,L,C,P,I)},h.lookAt=function(t,e,r,n){this.recalcMatrix(t),r=r||this.computedCenter,e=e||this.computedEye,n=n||this.computedUp;var a=this.computedMatrix;i(a,e,r,n);var o=this.computedRotation;s(o,a[0],a[1],a[2],a[4],a[5],a[6],a[8],a[9],a[10]),u(o,o),this.rotation.set(t,o[0],o[1],o[2],o[3]);for(var l=0,c=0;c<3;++c)l+=Math.pow(r[c]-e[c],2);this.radius.set(t,.5*Math.log(Math.max(l,1e-6))),this.center.set(t,r[0],r[1],r[2])},h.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},h.setMatrix=function(t,e){var r=this.computedRotation;s(r,e[0],e[1],e[2],e[4],e[5],e[6],e[8],e[9],e[10]),u(r,r),this.rotation.set(t,r[0],r[1],r[2],r[3]);var n=this.computedMatrix;o(n,e);var i=n[15];if(Math.abs(i)>1e-6){var a=n[12]/i,l=n[13]/i,c=n[14]/i;this.recalcMatrix(t);var f=Math.exp(this.computedRadius[0]);this.center.set(t,a-n[2]*f,l-n[6]*f,c-n[10]*f),this.radius.idle(t)}else this.center.idle(t),this.radius.idle(t)},h.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},h.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-1/0,e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},h.getDistanceLimits=function(t){var e=this.radius.bounds;return 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+              "/*!\n",
+              " * pad-left <https://github.com/jonschlinkert/pad-left>\n",
+              " *\n",
+              " * Copyright (c) 2014-2015, Jon Schlinkert.\n",
+              " * Licensed under the MIT license.\n",
+              " */\n",
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+              "/*\n",
+              " * @copyright 2016 Sean Connelly (@voidqk), http://syntheti.cc\n",
+              " * @license MIT\n",
+              " * @preserve Project Home: https://github.com/voidqk/polybooljs\n",
+              " */\n",
+              "var n,i=t(\"./lib/build-log\"),a=t(\"./lib/epsilon\"),o=t(\"./lib/intersecter\"),s=t(\"./lib/segment-chainer\"),l=t(\"./lib/segment-selector\"),c=t(\"./lib/geojson\"),u=!1,f=a();function h(t,e,r){var i=n.segments(t),a=n.segments(e),o=r(n.combine(i,a));return n.polygon(o)}n={buildLog:function(t){return!0===t?u=i():!1===t&&(u=!1),!1!==u&&u.list},epsilon:function(t){return f.epsilon(t)},segments:function(t){var e=o(!0,f,u);return 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f=e.linesIntersect(o,s,c,u);if(!1===f){if(!e.pointsCollinear(o,s,c))return!1;if(e.pointsSame(o,u)||e.pointsSame(s,c))return!1;var h=e.pointsSame(o,c),p=e.pointsSame(s,u);if(h&&p)return n;var d=!h&&e.pointBetween(o,c,u),m=!p&&e.pointBetween(s,c,u);if(h)return m?l(n,s):l(t,u),n;d&&(p||(m?l(n,s):l(t,u)),l(n,o))}else 0===f.alongA&&(-1===f.alongB?l(t,c):0===f.alongB?l(t,f.pt):1===f.alongB&&l(t,u)),0===f.alongB&&(-1===f.alongA?l(n,o):0===f.alongA?l(n,f.pt):1===f.alongA&&l(n,s));return!1}for(var f=[];!a.isEmpty();){var h=a.getHead();if(r&&r.vert(h.pt[0]),h.isStart){r&&r.segmentNew(h.seg,h.primary);var p=c(h),d=p.before?p.before.ev:null,m=p.after?p.after.ev:null;function g(){if(d){var t=u(h,d);if(t)return t}return!!m&&u(h,m)}r&&r.tempStatus(h.seg,!!d&&d.seg,!!m&&m.seg);var v,y=g();if(y){var x;if(t)(x=null===h.seg.myFill.below||h.seg.myFill.above!==h.seg.myFill.below)&&(y.seg.myFill.above=!y.seg.myFill.above);else 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p=s.index,d=s.matches_pt1?o:a,m=s.matches_head,g=n[p],v=m?g[0]:g[g.length-1],y=m?g[1]:g[g.length-2],x=m?g[g.length-1]:g[0],b=m?g[g.length-2]:g[1];return e.pointsCollinear(y,v,d)&&(m?(r&&r.chainRemoveHead(s.index,d),g.shift()):(r&&r.chainRemoveTail(s.index,d),g.pop()),v=y),e.pointsSame(x,d)?(n.splice(p,1),e.pointsCollinear(b,x,v)&&(m?(r&&r.chainRemoveTail(s.index,v),g.pop()):(r&&r.chainRemoveHead(s.index,v),g.shift())),r&&r.chainClose(s.index),void i.push(g)):void(m?(r&&r.chainAddHead(s.index,d),g.unshift(d)):(r&&r.chainAddTail(s.index,d),g.push(d)))}var _=s.index,w=l.index;r&&r.chainConnect(_,w);var T=n[_].length<n[w].length;s.matches_head?l.matches_head?T?(M(_),A(_,w)):(M(w),A(w,_)):A(w,_):l.matches_head?A(_,w):T?(M(_),A(w,_)):(M(w),A(_,w))}function k(t,e,r){return c.index=t,c.matches_head=e,c.matches_pt1=r,c===s?(c=l,!1):(c=null,!0)}function M(t){r&&r.chainReverse(t),n[t].reverse()}function A(t,i){var a=n[t],o=n[i],s=a[a.length-1],l=a[a.length-2],c=o[0],u=o[1];e.pointsCollinear(l,s,c)&&(r&&r.chainRemoveTail(t,s),a.pop(),s=l),e.pointsCollinear(s,c,u)&&(r&&r.chainRemoveHead(i,c),o.shift()),r&&r.chainJoin(t,i),n[t]=a.concat(o),n.splice(i,1)}})),i}},{}],507:[function(t,e,r){function n(t,e,r){var n=[];return t.forEach((function(t){var i=(t.myFill.above?8:0)+(t.myFill.below?4:0)+(t.otherFill&&t.otherFill.above?2:0)+(t.otherFill&&t.otherFill.below?1:0);0!==e[i]&&n.push({id:r?r.segmentId():-1,start:t.start,end:t.end,myFill:{above:1===e[i],below:2===e[i]},otherFill:null})})),r&&r.selected(n),n}var i={union:function(t,e){return n(t,[0,2,1,0,2,2,0,0,1,0,1,0,0,0,0,0],e)},intersect:function(t,e){return n(t,[0,0,0,0,0,2,0,2,0,0,1,1,0,2,1,0],e)},difference:function(t,e){return n(t,[0,0,0,0,2,0,2,0,1,1,0,0,0,1,2,0],e)},differenceRev:function(t,e){return n(t,[0,2,1,0,0,0,1,1,0,2,0,2,0,0,0,0],e)},xor:function(t,e){return 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n=e,i=0;i<r.length;)if(t[n++]!==r[i++])return!1;return!0},r.str2arr=function(t,e){var r=[],n=0;if(e&&\"hex\"===e)for(;n<t.length;)r.push(parseInt(t.slice(n,n+2),16)),n+=2;else for(;n<t.length;n++)r.push(255&t.charCodeAt(n));return r},r.readUInt16LE=function(t,e){return t[e]|t[e+1]<<8},r.readUInt16BE=function(t,e){return t[e+1]|t[e]<<8},r.readUInt32LE=function(t,e){return t[e]|t[e+1]<<8|t[e+2]<<16|16777216*t[e+3]},r.readUInt32BE=function(t,e){return t[e+3]|t[e+2]<<8|t[e+1]<<16|16777216*t[e]},o.prototype=Object.create(Error.prototype),o.prototype.constructor=o,r.ProbeError=o},{stream:565,\"stream-parser\":581}],510:[function(t,e,r){\"use strict\";function n(t,e){var r=new Error(t);return r.code=e,r}function i(t){try{return decodeURIComponent(escape(t))}catch(e){return t}}function a(t,e,r){this.input=t.subarray(e,r),this.start=e;var i=String.fromCharCode.apply(null,this.input.subarray(0,4));if(\"II*\\0\"!==i&&\"MM\\0*\"!==i)throw n(\"invalid TIFF signature\",\"EBADDATA\");this.big_endian=\"M\"===i[0]}a.prototype.each=function(t){this.aborted=!1;var e=this.read_uint32(4);for(this.ifds_to_read=[{id:0,offset:e}];this.ifds_to_read.length>0&&!this.aborted;){var r=this.ifds_to_read.shift();r.offset&&this.scan_ifd(r.id,r.offset,t)}},a.prototype.read_uint16=function(t){var e=this.input;if(t+2>e.length)throw n(\"unexpected EOF\",\"EBADDATA\");return this.big_endian?256*e[t]+e[t+1]:e[t]+256*e[t+1]},a.prototype.read_uint32=function(t){var e=this.input;if(t+4>e.length)throw n(\"unexpected EOF\",\"EBADDATA\");return this.big_endian?16777216*e[t]+65536*e[t+1]+256*e[t+2]+e[t+3]:e[t]+256*e[t+1]+65536*e[t+2]+16777216*e[t+3]},a.prototype.is_subifd_link=function(t,e){return 0===t&&34665===e||0===t&&34853===e||34665===t&&40965===e},a.prototype.exif_format_length=function(t){switch(t){case 1:case 2:case 6:case 7:return 1;case 3:case 8:return 2;case 4:case 9:case 11:return 4;case 5:case 10:case 12:return 8;default:return 0}},a.prototype.exif_format_read=function(t,e){var r;switch(t){case 1:case 2:return r=this.input[e];case 6:return(r=this.input[e])|33554430*(128&r);case 3:return r=this.read_uint16(e);case 8:return(r=this.read_uint16(e))|131070*(32768&r);case 4:return r=this.read_uint32(e);case 9:return 0|(r=this.read_uint32(e));case 5:case 10:case 11:case 12:case 7:default:return null}},a.prototype.scan_ifd=function(t,e,r){var a=this.read_uint16(e);e+=2;for(var o=0;o<a;o++){var s=this.read_uint16(e),l=this.read_uint16(e+2),c=this.read_uint32(e+4),u=this.exif_format_length(l),f=c*u,h=f<=4?e+8:this.read_uint32(e+8),p=!1;if(h+f>this.input.length)throw n(\"unexpected EOF\",\"EBADDATA\");for(var d=[],m=h,g=0;g<c;g++,m+=u){var v=this.exif_format_read(l,m);if(null===v){d=null;break}d.push(v)}if(Array.isArray(d)&&2===l&&(d=i(String.fromCharCode.apply(null,d)))&&\"\\0\"===d[d.length-1]&&(d=d.slice(0,-1)),this.is_subifd_link(t,s)&&Array.isArray(d)&&Number.isInteger(d[0])&&d[0]>0&&(this.ifds_to_read.push({id:s,offset:d[0]}),p=!0),!1===r({is_big_endian:this.big_endian,ifd:t,tag:s,format:l,count:c,entry_offset:e+this.start,data_length:f,data_offset:h+this.start,value:d,is_subifd_link:p}))return void(this.aborted=!0);e+=12}0===t&&this.ifds_to_read.push({id:1,offset:this.read_uint32(e)})},e.exports.ExifParser=a,e.exports.get_orientation=function(t){var e=0;try{return new a(t,0,t.length).each((function(t){if(0===t.ifd&&274===t.tag&&Array.isArray(t.value))return e=t.value[0],!1})),e}catch(t){return-1}}},{}],511:[function(t,e,r){\"use strict\";var n=t(\"./common\").readUInt16BE,i=t(\"./common\").readUInt32BE;function a(t,e){if(t.length<4+e)return null;var r=i(t,e);return t.length<r+e||r<8?null:{boxtype:String.fromCharCode.apply(null,t.slice(e+4,e+8)),data:t.slice(e+8,e+r),end:e+r}}function o(t,e){for(var r=0;;){var n=a(t,r);if(!n)break;switch(n.boxtype){case\"ispe\":e.sizes.push({width:i(n.data,4),height:i(n.data,8)});break;case\"irot\":e.transforms.push({type:\"irot\",value:3&n.data[0]});break;case\"imir\":e.transforms.push({type:\"imir\",value:1&n.data[0]})}r=n.end}}function s(t,e,r){for(var n=0,i=0;i<r;i++)n=256*n+(t[e+i]||0);return n}function l(t,e){for(var r=t[4]>>4&15,i=15&t[4],a=t[5]>>4&15,o=n(t,6),l=8,c=0;c<o;c++){var u=n(t,l),f=n(t,l+=2),h=s(t,l+=2,a),p=n(t,l+=a);if(l+=2,0===f&&1===p){var d=s(t,l,r),m=s(t,l+r,i);e.item_loc[u]={length:m,offset:d+h}}l+=p*(r+i)}}function c(t,e){for(var r=n(t,4),i=6,o=0;o<r;o++){var s=a(t,i);if(!s)break;if(\"infe\"===s.boxtype){for(var l=n(s.data,4),c=\"\",u=8;u<s.data.length&&s.data[u];u++)c+=String.fromCharCode(s.data[u]);e.item_inf[c]=l}i=s.end}}function u(t,e){for(var r=0;;){var n=a(t,r);if(!n)break;\"ipco\"===n.boxtype&&o(n.data,e),r=n.end}}e.exports.unbox=a,e.exports.readSizeFromMeta=function(t){var e={sizes:[],transforms:[],item_inf:{},item_loc:{}};if(function(t,e){for(var r=4;;){var n=a(t,r);if(!n)break;\"iprp\"===n.boxtype&&u(n.data,e),\"iloc\"===n.boxtype&&l(n.data,e),\"iinf\"===n.boxtype&&c(n.data,e),r=n.end}}(t,e),e.sizes.length){var r,n,i,o=(r=e.sizes,n=r.reduce((function(t,e){return t.width>e.width||t.width===e.width&&t.height>e.height?t:e})),i=r.reduce((function(t,e){return t.height>e.height||t.height===e.height&&t.width>e.width?t:e})),n.width>i.height||n.width===i.height&&n.height>i.width?n:i),s=1;e.transforms.forEach((function(t){var e={1:6,2:5,3:8,4:7,5:4,6:3,7:2,8:1},r={1:4,2:3,3:2,4:1,5:6,6:5,7:8,8:7};if(\"imir\"===t.type&&(s=0===t.value?r[s]:e[s=e[s=r[s]]]),\"irot\"===t.type)for(var n=0;n<t.value;n++)s=e[s]}));var f=null;return e.item_inf.Exif&&(f=e.item_loc[e.item_inf.Exif]),{width:o.width,height:o.height,orientation:e.transforms.length?s:null,variants:e.sizes,exif_location:f}}},e.exports.getMimeType=function(t){var e=String.fromCharCode.apply(null,t.slice(0,4)),r={};r[e]=!0;for(var n=8;n<t.length;n+=4)r[String.fromCharCode.apply(null,t.slice(n,n+4))]=!0;if(r.mif1||r.msf1||r.miaf)return\"avif\"===e||\"avis\"===e||\"avio\"===e?{type:\"avif\",mime:\"image/avif\"}:\"heic\"===e||\"heix\"===e?{type:\"heic\",mime:\"image/heic\"}:\"hevc\"===e||\"hevx\"===e?{type:\"heic\",mime:\"image/heic-sequence\"}:r.avif||r.avis?{type:\"avif\",mime:\"image/avif\"}:r.heic||r.heix||r.hevc||r.hevx||r.heis?r.msf1?{type:\"heif\",mime:\"image/heif-sequence\"}:{type:\"heif\",mime:\"image/heif\"}:{type:\"avif\",mime:\"image/avif\"}}},{\"./common\":509}],512:[function(t,e,r){\"use strict\";var n=t(\"../common\").str2arr,i=t(\"../common\").sliceEq,a=t(\"../common\").readUInt32BE,o=t(\"../miaf_utils\"),s=t(\"../exif_utils\"),l=n(\"ftyp\");e.exports=function(t){if(i(t,4,l)){var e=o.unbox(t,0);if(e){var r=o.getMimeType(e.data);if(r){for(var n,c=e.end;;){var u=o.unbox(t,c);if(!u)break;if(c=u.end,\"mdat\"===u.boxtype)return;if(\"meta\"===u.boxtype){n=u.data;break}}if(n){var f=o.readSizeFromMeta(n);if(f){var h={width:f.width,height:f.height,type:r.type,mime:r.mime,wUnits:\"px\",hUnits:\"px\"};if(f.variants.length>1&&(h.variants=f.variants),f.orientation&&(h.orientation=f.orientation),f.exif_location&&f.exif_location.offset+f.exif_location.length<=t.length){var p=a(t,f.exif_location.offset),d=t.slice(f.exif_location.offset+p+4,f.exif_location.offset+f.exif_location.length),m=s.get_orientation(d);m>0&&(h.orientation=m)}return h}}}}}}},{\"../common\":509,\"../exif_utils\":510,\"../miaf_utils\":511}],513:[function(t,e,r){\"use strict\";var n=t(\"../common\").str2arr,i=t(\"../common\").sliceEq,a=t(\"../common\").readUInt16LE,o=n(\"BM\");e.exports=function(t){if(!(t.length<26)&&i(t,0,o))return{width:a(t,18),height:a(t,22),type:\"bmp\",mime:\"image/bmp\",wUnits:\"px\",hUnits:\"px\"}}},{\"../common\":509}],514:[function(t,e,r){\"use strict\";var n=t(\"../common\").str2arr,i=t(\"../common\").sliceEq,a=t(\"../common\").readUInt16LE,o=n(\"GIF87a\"),s=n(\"GIF89a\");e.exports=function(t){if(!(t.length<10)&&(i(t,0,o)||i(t,0,s)))return{width:a(t,6),height:a(t,8),type:\"gif\",mime:\"image/gif\",wUnits:\"px\",hUnits:\"px\"}}},{\"../common\":509}],515:[function(t,e,r){\"use strict\";var n=t(\"../common\").readUInt16LE;e.exports=function(t){var e=n(t,0),r=n(t,2),i=n(t,4);if(0===e&&1===r&&i){for(var a=[],o={width:0,height:0},s=0;s<i;s++){var 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n=t(\"color-normalize\"),i=t(\"array-bounds\"),a=t(\"object-assign\"),o=t(\"glslify\"),s=t(\"pick-by-alias\"),l=t(\"flatten-vertex-data\"),c=t(\"earcut\"),u=t(\"array-normalize\"),f=t(\"to-float32\"),h=f.float32,p=f.fract32,d=t(\"es6-weak-map\"),m=t(\"parse-rect\"),g=t(\"array-find-index\");function v(t,e){if(!(this instanceof v))return new v(t,e);if(\"function\"==typeof t?(e||(e={}),e.regl=t):e=t,e.length&&(e.positions=e),!(t=e.regl).hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=v.shaders.has(t)?v.shaders.get(t):v.shaders.set(t,v.createShaders(t)).get(t),this.update(e)}e.exports=v,v.dashMult=2,v.maxPatternLength=256,v.precisionThreshold=3e6,v.maxPoints=1e4,v.maxLines=2048,v.shaders=new d,v.createShaders=function(t){var e,r=t.buffer({usage:\"static\",type:\"float\",data:[0,1,0,0,1,1,1,0]}),n={primitive:\"triangle strip\",instances:t.prop(\"count\"),count:4,offset:0,uniforms:{miterMode:function(t,e){return\"round\"===e.join?2:1},miterLimit:t.prop(\"miterLimit\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),thickness:t.prop(\"thickness\"),dashPattern:t.prop(\"dashTexture\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),dashSize:t.prop(\"dashLength\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop(\"depth\")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\")},i=t(a({vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\\nattribute vec4 color;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\\n\\t// the order is important\\n\\treturn position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n}\\n\\nvoid main() {\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineOffset = lineTop * 2. - 1.;\\n\\n\\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\\n\\ttangent = normalize(diff * scale * viewport.zw);\\n\\tvec2 normal = vec2(-tangent.y, tangent.x);\\n\\n\\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\\n\\t\\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\\n\\n\\t\\t+ thickness * normal * .5 * lineOffset / viewport.zw;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\n\\nuniform float dashSize, pixelRatio, thickness, opacity, id;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvoid main() {\\n\\tfloat alpha = 1.;\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:16,divisor:1},color:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1}}},n));try{e=t(a({cull:{enable:!0,face:\"back\"},vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\\nattribute vec4 aColor, bColor;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, translate;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\nuniform float miterLimit, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 tangent;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nconst float REVERSE_THRESHOLD = -.875;\\nconst float MIN_DIFF = 1e-6;\\n\\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\\n// TODO: precalculate dot products, normalize things beforehead etc.\\n// TODO: refactor to rectangular algorithm\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nbool isNaN( float val ){\\n  return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\\n}\\n\\nvoid main() {\\n\\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\\n\\n  vec2 adjustedScale;\\n  adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\\n  adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\\n\\n  vec2 scaleRatio = adjustedScale * viewport.zw;\\n\\tvec2 normalWidth = thickness / scaleRatio;\\n\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineBot = 1. - lineTop;\\n\\n\\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\\n\\n\\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\\n\\n\\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\\n\\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\\n\\n\\tvec2 prevDiff = aCoord - prevCoord;\\n\\tvec2 currDiff = bCoord - aCoord;\\n\\tvec2 nextDiff = nextCoord - bCoord;\\n\\n\\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\\n\\tvec2 currTangent = normalize(currDiff * scaleRatio);\\n\\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\\n\\n\\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\\n\\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\\n\\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\\n\\n\\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\\n\\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\\n\\n\\t// collapsed/unidirectional segment cases\\n\\t// FIXME: there should be more elegant solution\\n\\tvec2 prevTanDiff = abs(prevTangent - currTangent);\\n\\tvec2 nextTanDiff = abs(nextTangent - currTangent);\\n\\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\\n\\t\\tstartJoinDirection = currNormal;\\n\\t}\\n\\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\\n\\t\\tendJoinDirection = currNormal;\\n\\t}\\n\\tif (aCoord == bCoord) {\\n\\t\\tendJoinDirection = startJoinDirection;\\n\\t\\tcurrNormal = prevNormal;\\n\\t\\tcurrTangent = prevTangent;\\n\\t}\\n\\n\\ttangent = currTangent;\\n\\n\\t//calculate join shifts relative to normals\\n\\tfloat startJoinShift = dot(currNormal, startJoinDirection);\\n\\tfloat endJoinShift = dot(currNormal, endJoinDirection);\\n\\n\\tfloat startMiterRatio = abs(1. / startJoinShift);\\n\\tfloat endMiterRatio = abs(1. / endJoinShift);\\n\\n\\tvec2 startJoin = startJoinDirection * startMiterRatio;\\n\\tvec2 endJoin = endJoinDirection * endMiterRatio;\\n\\n\\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\\n\\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\\n\\tstartBotJoin = -startTopJoin;\\n\\n\\tendTopJoin = sign(endJoinShift) * endJoin * .5;\\n\\tendBotJoin = -endTopJoin;\\n\\n\\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\\n\\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\\n\\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\\n\\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\\n\\n\\t//miter anti-clipping\\n\\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\\n\\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\\n\\n\\t//prevent close to reverse direction switch\\n\\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\n\\tif (prevReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\\n\\t\\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\tbTopCoord -= normalWidth * endTopJoin;\\n\\t\\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\\n\\t}\\n\\n\\tif (nextReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\\n\\t\\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position  * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\nuniform float dashSize, pixelRatio, thickness, opacity, id, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1},bColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:4,divisor:1},prevCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:0,divisor:1},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},nextCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:24,divisor:1}}},n))}catch(t){e=i}return{fill:t({primitive:\"triangle\",elements:function(t,e){return e.triangles},offset:0,vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position, positionFract;\\n\\nuniform vec4 color;\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio, id;\\nuniform vec4 viewport;\\nuniform float opacity;\\n\\nvarying vec4 fragColor;\\n\\nconst float MAX_LINES = 256.;\\n\\nvoid main() {\\n\\tfloat depth = (MAX_LINES - 4. - id) / (MAX_LINES);\\n\\n\\tvec2 position = position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n\\tfragColor.a *= opacity;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n\\tgl_FragColor = fragColor;\\n}\\n\"]),uniforms:{scale:t.prop(\"scale\"),color:t.prop(\"fill\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]}},attributes:{position:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8},positionFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8}},blend:n.blend,depth:{enable:!1},scissor:n.scissor,stencil:n.stencil,viewport:n.viewport}),rect:i,miter:e}},v.defaults={dashes:null,join:\"miter\",miterLimit:1,thickness:10,cap:\"square\",color:\"black\",opacity:1,overlay:!1,viewport:null,range:null,close:!1,fill:null},v.prototype.render=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];e.length&&(t=this).update.apply(t,e),this.draw()},v.prototype.draw=function(){for(var t=this,e=[],r=arguments.length;r--;)e[r]=arguments[r];return(e.length?e:this.passes).forEach((function(e,r){var n;if(e&&Array.isArray(e))return(n=t).draw.apply(n,e);\"number\"==typeof e&&(e=t.passes[e]),e&&e.count>1&&e.opacity&&(t.regl._refresh(),e.fill&&e.triangles&&e.triangles.length>2&&t.shaders.fill(e),e.thickness&&(e.scale[0]*e.viewport.width>v.precisionThreshold||e.scale[1]*e.viewport.height>v.precisionThreshold||\"rect\"===e.join||!e.join&&(e.thickness<=2||e.count>=v.maxPoints)?t.shaders.rect(e):t.shaders.miter(e)))})),this},v.prototype.update=function(t){var e=this;if(t){null!=t.length?\"number\"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var r=this.regl,o=this.gl;if(t.forEach((function(t,f){var d=e.passes[f];if(void 0!==t)if(null!==t){if(\"number\"==typeof t[0]&&(t={positions:t}),t=s(t,{positions:\"positions points data coords\",thickness:\"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth\",join:\"lineJoin linejoin 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fragColor, colorAmt);\\n    color.a *= opacity;\\n\\n    gl_FragColor = color;\\n  }\\n\\n}\\n\"]),s.vert=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract, paletteSize;\\nuniform float pixelRatio;\\nuniform bool constPointSize;\\nuniform sampler2D palette;\\n\\nconst float maxSize = 100.;\\nconst float borderLevel = .5;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragPointSize, fragBorderRadius, fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n  return isDirect ? id / 255. : texture2D(palette,\\n    vec2(\\n      (id.x + .5) / paletteSize.x,\\n      (id.y + .5) / paletteSize.y\\n    )\\n  );\\n}\\n\\nvoid main() {\\n  // ignore inactive points\\n  if (isActive == 0.) return;\\n\\n  vec2 position = vec2(x, y);\\n  vec2 positionFract = vec2(xFract, yFract);\\n\\n  vec4 color = getColor(colorId);\\n  vec4 borderColor = getColor(borderColorId);\\n\\n  float size = size * maxSize / 255.;\\n  float borderSize = borderSize * maxSize / 255.;\\n\\n  gl_PointSize = 2. * size * pointSizeScale;\\n  fragPointSize = size * pixelRatio;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragColor = color;\\n  fragBorderColor = borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n\\n  fragBorderColorLevel = clamp(borderLevel - borderLevel * borderSize / size, 0., 1.);\\n  fragColorLevel = clamp(borderLevel + (1. - borderLevel) * borderSize / size, 0., 1.);\\n}\"]),this.drawMarker=t(s);var l=f({},o);l.frag=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\n\\nuniform float opacity;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat smoothStep(float edge0, float edge1, float x) {\\n\\tfloat t;\\n\\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\\n\\treturn t * t * (3.0 - 2.0 * t);\\n}\\n\\nvoid main() {\\n\\tfloat radius, alpha = 1.0, delta = fragWidth;\\n\\n\\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\\n\\n\\tif (radius > 1.0 + delta) {\\n\\t\\tdiscard;\\n\\t}\\n\\n\\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\\n\\n\\tfloat borderRadius = fragBorderRadius;\\n\\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\\n\\tvec4 color = mix(fragColor, fragBorderColor, ratio);\\n\\tcolor.a *= alpha * opacity;\\n\\tgl_FragColor = color;\\n}\\n\"]),l.vert=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio;\\nuniform bool constPointSize;\\nuniform sampler2D palette;\\nuniform vec2 paletteSize;\\n\\nconst float maxSize = 100.;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n  return isDirect ? id / 255. : texture2D(palette,\\n    vec2(\\n      (id.x + .5) / paletteSize.x,\\n      (id.y + .5) / paletteSize.y\\n    )\\n  );\\n}\\n\\nvoid main() {\\n  // ignore inactive points\\n  if (isActive == 0.) return;\\n\\n  vec2 position = vec2(x, y);\\n  vec2 positionFract = vec2(xFract, yFract);\\n\\n  vec4 color = getColor(colorId);\\n  vec4 borderColor = getColor(borderColorId);\\n\\n  float size = size * maxSize / 255.;\\n  float borderSize = borderSize * maxSize / 255.;\\n\\n  gl_PointSize = (size + borderSize) * pointSizeScale;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\\n  fragColor = color;\\n  fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n}\\n\"]),g&&(l.frag=l.frag.replace(\"smoothstep\",\"smoothStep\"),s.frag=s.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=t(l)}b.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},b.prototype.render=function(){return arguments.length&&this.update.apply(this,arguments),this.draw(),this},b.prototype.draw=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];var i=this.groups;if(1===r.length&&Array.isArray(r[0])&&(null===r[0][0]||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var a=0;a<r.length;a++)this.drawItem(a,r[a]);else i.forEach((function(e,r){t.drawItem(r)}));return this},b.prototype.drawItem=function(t,e){var r=this.groups,n=r[t];if(\"number\"==typeof e&&(t=e,n=r[e],e=null),n&&n.count&&n.opacity){n.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,n,e));for(var a=[],o=1;o<n.activation.length;o++)n.activation[o]&&(!0===n.activation[o]||n.activation[o].data.length)&&a.push.apply(a,i(this.getMarkerDrawOptions(o,n,e)));a.length&&this.drawMarker(a)}},b.prototype.getMarkerDrawOptions=function(t,e,r){var i=e.range,a=e.tree,o=e.viewport,s=e.activation,l=e.selectionBuffer,c=e.count;this.regl;if(!a)return r?[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var u=[],h=a.range(i,{lod:!0,px:[(i[2]-i[0])/o.width,(i[3]-i[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(c),m=0;m<r.length;m++){var g=r[m];d[g]=p?p[g]:1}l.subdata(d)}for(var v=h.length;v--;){var y=n(h[v],2),x=y[0],b=y[1];u.push(f({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return u},b.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,o=this.regl,s=this.maxSize,c=this.maxColors,h=this.palette;this.groups=i=r.map((function(e,r){var n=i[r];if(void 0===e)return n;null===e?e={positions:null}:\"function\"==typeof e?e={ondraw:e}:\"number\"==typeof e[0]&&(e={positions:e}),null===(e=p(e,{positions:\"positions data 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t.x.length?e.xAttr={buffer:o.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:o.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=m(t,\"float64\");var c=e.count=Math.floor(t.length/2),f=e.bounds=c?l(t,2):null;if(r.range||e.range||(delete e.range,r.range=f),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||c>n)?e.tree=u(t,{bounds:f}):n&&n.length&&(e.tree=n),e.tree){var h={primitive:\"points\",usage:\"static\",data:e.tree,type:\"uint32\"};e.elements?e.elements(h):e.elements=o.elements(h)}return i({data:v.float(t),usage:\"dynamic\"}),a({data:v.fract(t),usage:\"dynamic\"}),s({data:new Uint8Array(c),type:\"uint8\",usage:\"stream\"}),t}},{marker:function(e,r,n){var i=r.activation;if(i.forEach((function(t){return t&&t.destroy&&t.destroy()})),i.length=0,e&&\"number\"!=typeof e[0]){for(var a=[],s=0,l=Math.min(e.length,r.count);s<l;s++){var c=t.addMarker(e[s]);a[c]||(a[c]=new Uint8Array(r.count)),a[c][s]=1}for(var u=0;u<a.length;u++)if(a[u]){var f={data:a[u],type:\"uint8\",usage:\"static\"};i[u]?i[u](f):i[u]=o.buffer(f),i[u].data=a[u]}}else{i[t.addMarker(e)]=!0}return e},range:function(t,e,r){var n=e.bounds;if(n)return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=v.fract(e.scale),e.translateFract=v.fract(e.translate),t},viewport:function(t){return y(t||[a.drawingBufferWidth,a.drawingBufferHeight])}}]),g){var _=n,w=_.count,T=_.size,k=_.borderSize,M=_.sizeBuffer,A=new Uint8Array(2*w);if(T.length||k.length)for(var S=0;S<w;S++)A[2*S]=Math.round(255*(null==T[S]?T:T[S])/s),A[2*S+1]=Math.round(255*(null==k[S]?k:k[S])/s);M({data:A,usage:\"dynamic\"})}if(x){var E,L=n,C=L.count,P=L.color,I=L.borderColor,O=L.colorBuffer;if(t.tooManyColors){if(P.length||I.length){E=new Uint8Array(8*C);for(var z=0;z<C;z++){var D=P[z];E[8*z]=h[4*D],E[8*z+1]=h[4*D+1],E[8*z+2]=h[4*D+2],E[8*z+3]=h[4*D+3];var R=I[z];E[8*z+4]=h[4*R],E[8*z+5]=h[4*R+1],E[8*z+6]=h[4*R+2],E[8*z+7]=h[4*R+3]}}}else if(P.length||I.length){E=new Uint8Array(4*C+2);for(var F=0;F<C;F++)null!=P[F]&&(E[4*F]=P[F]%c,E[4*F+1]=Math.floor(P[F]/c)),null!=I[F]&&(E[4*F+2]=I[F]%c,E[4*F+3]=Math.floor(I[F]/c))}O({data:E||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return n}))}},b.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,i=this.markerCache,a=null==t?0:i.indexOf(t);if(a>=0)return a;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return a=r.length,i.push(t),r.push(n.texture({channels:1,data:e,radius:l,mag:\"linear\",min:\"linear\"})),a},b.prototype.updateColor=function(t){var e=this.paletteIds,r=this.palette,n=this.maxColors;Array.isArray(t)||(t=[t]);var i=[];if(\"number\"==typeof t[0]){var a=[];if(Array.isArray(t))for(var o=0;o<t.length;o+=4)a.push(t.slice(o,o+4));else for(var l=0;l<t.length;l+=4)a.push(t.subarray(l,l+4));t=a}for(var u=0;u<t.length;u++){var f=t[u];f=s(f,\"uint8\");var h=c(f,!1);if(null==e[h]){var p=r.length;e[h]=Math.floor(p/4),r[p]=f[0],r[p+1]=f[1],r[p+2]=f[2],r[p+3]=f[3]}i[u]=e[h]}return!this.tooManyColors&&r.length>4*n&&(this.tooManyColors=!0),this.updatePalette(r),1===i.length?i[0]:i},b.prototype.updatePalette=function(t){if(!this.tooManyColors){var e=this.maxColors,r=this.paletteTexture,n=Math.ceil(.25*t.length/e);if(n>1)for(var i=.25*(t=t.slice()).length%e;i<n*e;i++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},b.prototype.destroy=function(){return this.groups.forEach((function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach((function(t){return t&&t.destroy&&t.destroy()})),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()})),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach((function(t){return t&&t.destroy&&t.destroy()})),this};var _=t(\"object-assign\");e.exports=function(t,e){var r=new x(t,e),n=r.render.bind(r);return _(n,{render:n,update:r.update.bind(r),draw:r.draw.bind(r),destroy:r.destroy.bind(r),regl:r.regl,gl:r.gl,canvas:r.gl.canvas,groups:r.groups,markers:r.markerCache,palette:r.palette}),n}},{\"@plotly/point-cluster\":59,\"array-bounds\":76,\"color-id\":129,\"color-normalize\":131,\"flatten-vertex-data\":248,glslify:438,\"is-iexplorer\":450,\"object-assign\":483,\"parse-rect\":488,\"pick-by-alias\":494,\"to-float32\":595,\"update-diff\":617}],535:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),i=t(\"pick-by-alias\"),a=t(\"array-bounds\"),o=t(\"raf\"),s=t(\"array-range\"),l=t(\"parse-rect\"),c=t(\"flatten-vertex-data\");function u(t,e){if(!(this instanceof u))return new u(t,e);this.traces=[],this.passes={},this.regl=t,this.scatter=n(t),this.canvas=this.scatter.canvas}function f(t,e,r){return(null!=t.id?t.id:t)<<16|(255&e)<<8|255&r}function h(t,e,r){var n,i,a,o,s=t[e],l=t[r];return s.length>2?(s[0],s[2],n=s[1],i=s[3]):s.length?(n=s[0],i=s[1]):(s.x,n=s.y,s.x+s.width,i=s.y+s.height),l.length>2?(a=l[0],o=l[2],l[1],l[3]):l.length?(a=l[0],o=l[1]):(a=l.x,l.y,o=l.x+l.width,l.y+l.height),[a,n,o,i]}function p(t){if(\"number\"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}e.exports=u,u.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o((function(){e.draw(),e.dirty=!0,e.planned=null}))):(this.draw(),this.dirty=!0,o((function(){e.dirty=!1}))),this)},u.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var i=[],a=0,o=0;o<this.traces.length;o++){for(var s=this.traces[o],l=this.traces[o].passes,c=0;c<l.length;c++)i.push(this.passes[l[c]]);s.passOffset=a,a+=s.passes.length}return(t=this.scatter).update.apply(t,i),this}},u.prototype.updateItem=function(t,e){var r=this.regl;if(null===e)return this.traces[t]=null,this;if(!e)return this;var n,o=i(e,{data:\"data items columns rows values dimensions samples x\",snap:\"snap cluster\",size:\"sizes size radius\",color:\"colors color fill fill-color fillColor\",opacity:\"opacity alpha transparency 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A.viewport=[x+k*_+_*S[0],b+T*w+w*S[1],x+(k+1)*_-_*S[2],b+(T+1)*w-w*S[3]]}o.color&&(A.color=s.color),o.size&&(A.size=s.size),o.marker&&(A.marker=s.marker),o.borderSize&&(A.borderSize=s.borderSize),o.borderColor&&(A.borderColor=s.borderColor),o.opacity&&(A.opacity=s.opacity),o.range&&(A.range=n?h(s.range,T,k):s.range||A.bounds),s.passes.push(M)}return this},u.prototype.draw=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=[],i=0;i<e.length;i++)if(\"number\"==typeof e[i]){var a=this.traces[e[i]],o=a.passes,l=a.passOffset;n.push.apply(n,s(l,l+o.length))}else if(e[i].length){var c=e[i],u=this.traces[i],f=u.passes,h=u.passOffset;f=f.map((function(t,e){n[h+e]=c}))}(t=this.scatter).draw.apply(t,n)}else this.scatter.draw();return this},u.prototype.destroy=function(){return this.traces.forEach((function(t){t.buffer&&t.buffer.destroy&&t.buffer.destroy()})),this.traces=null,this.passes=null,this.scatter.destroy(),this}},{\"array-bounds\":76,\"array-range\":79,\"flatten-vertex-data\":248,\"parse-rect\":488,\"pick-by-alias\":494,raf:526,\"regl-scatter2d\":534}],536:[function(t,e,r){!function(t,n){\"object\"==typeof r&&void 0!==e?e.exports=n():t.createREGL=n()}(this,(function(){function t(t,e){this.id=V++,this.type=t,this.data=e}function e(t){return\"[\"+function t(e){if(0===e.length)return[];var r=e.charAt(0),n=e.charAt(e.length-1);if(1<e.length&&r===n&&('\"'===r||\"'\"===r))return['\"'+e.substr(1,e.length-2).replace(/\\\\/g,\"\\\\\\\\\").replace(/\"/g,'\\\\\"')+'\"'];if(r=/\\[(false|true|null|\\d+|'[^']*'|\"[^\"]*\")\\]/.exec(e))return 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+              " * repeat-string <https://github.com/jonschlinkert/repeat-string>\n",
+              " *\n",
+              " * Copyright (c) 2014-2015, Jon Schlinkert.\n",
+              " * Licensed under the MIT License.\n",
+              " */\n",
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n.baseCalendar,i(a.prototype,{name:\"Ethiopian\",jdEpoch:1724220.5,daysPerMonth:[30,30,30,30,30,30,30,30,30,30,30,30,5],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Ethiopian\",epochs:[\"BEE\",\"EE\"],monthNames:[\"Meskerem\",\"Tikemet\",\"Hidar\",\"Tahesas\",\"Tir\",\"Yekatit\",\"Megabit\",\"Miazia\",\"Genbot\",\"Sene\",\"Hamle\",\"Nehase\",\"Pagume\"],monthNamesShort:[\"Mes\",\"Tik\",\"Hid\",\"Tah\",\"Tir\",\"Yek\",\"Meg\",\"Mia\",\"Gen\",\"Sen\",\"Ham\",\"Neh\",\"Pag\"],dayNames:[\"Ehud\",\"Segno\",\"Maksegno\",\"Irob\",\"Hamus\",\"Arb\",\"Kidame\"],dayNamesShort:[\"Ehu\",\"Seg\",\"Mak\",\"Iro\",\"Ham\",\"Arb\",\"Kid\"],dayNamesMin:[\"Eh\",\"Se\",\"Ma\",\"Ir\",\"Ha\",\"Ar\",\"Ki\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()+(e.year()<0?1:0))%4==3||t%4==-1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return(t=i.year())<0&&t++,i.day()+30*(i.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,i=e-30*(n-1)+1;return this.newDate(r,n,i)}}),n.calendars.ethiopian=a},{\"../main\":640,\"object-assign\":483}],630:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Hebrew\",jdEpoch:347995.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29,29],hasYearZero:!1,minMonth:1,firstMonth:7,minDay:1,regionalOptions:{\"\":{name:\"Hebrew\",epochs:[\"BAM\",\"AM\"],monthNames:[\"Nisan\",\"Iyar\",\"Sivan\",\"Tammuz\",\"Av\",\"Elul\",\"Tishrei\",\"Cheshvan\",\"Kislev\",\"Tevet\",\"Shevat\",\"Adar\",\"Adar II\"],monthNamesShort:[\"Nis\",\"Iya\",\"Siv\",\"Tam\",\"Av\",\"Elu\",\"Tis\",\"Che\",\"Kis\",\"Tev\",\"She\",\"Ada\",\"Ad2\"],dayNames:[\"Yom Rishon\",\"Yom Sheni\",\"Yom Shlishi\",\"Yom Revi'i\",\"Yom Chamishi\",\"Yom Shishi\",\"Yom Shabbat\"],dayNamesShort:[\"Ris\",\"She\",\"Shl\",\"Rev\",\"Cha\",\"Shi\",\"Sha\"],dayNamesMin:[\"Ri\",\"She\",\"Shl\",\"Re\",\"Ch\",\"Shi\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return this._leapYear(e.year())},_leapYear:function(t){return o(7*(t=t<0?t+1:t)+1,19)<7},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),this._leapYear(t.year?t.year():t)?13:12},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),this.toJD(-1===t?1:t+1,7,1)-this.toJD(t,7,1)},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),12===e&&this.leapYear(t)||8===e&&5===o(this.daysInYear(t),10)?30:9===e&&3===o(this.daysInYear(t),10)?29:this.daysPerMonth[e-1]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return{yearType:(this.leapYear(i)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(i)%10-3]}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t<=0?t+1:t,o=this.jdEpoch+this._delay1(a)+this._delay2(a)+r+1;if(e<7){for(var s=7;s<=this.monthsInYear(t);s++)o+=this.daysInMonth(t,s);for(s=1;s<e;s++)o+=this.daysInMonth(t,s)}else for(s=7;s<e;s++)o+=this.daysInMonth(t,s);return o},_delay1:function(t){var e=Math.floor((235*t-234)/19),r=12084+13753*e,n=29*e+Math.floor(r/25920);return o(3*(n+1),7)<3&&n++,n},_delay2:function(t){var e=this._delay1(t-1),r=this._delay1(t);return this._delay1(t+1)-r==356?2:r-e==382?1:0},fromJD:function(t){t=Math.floor(t)+.5;for(var e=Math.floor(98496*(t-this.jdEpoch)/35975351)-1;t>=this.toJD(-1===e?1:e+1,7,1);)e++;for(var r=t<this.toJD(e,1,1)?7:1;t>this.toJD(e,r,this.daysInMonth(e,r));)r++;var n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.hebrew=a},{\"../main\":640,\"object-assign\":483}],631:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Islamic\",jdEpoch:1948439.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Islamic\",epochs:[\"BH\",\"AH\"],monthNames:[\"Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' al-thani\",\"Jumada al-awwal\",\"Jumada al-thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-ahad\",\"Yawm al-ithnayn\",\"Yawm ath-thulaathaa'\",\"Yawm al-arbi'aa'\",\"Yawm al-kham\\u012bs\",\"Yawm al-jum'a\",\"Yawm as-sabt\"],dayNamesShort:[\"Aha\",\"Ith\",\"Thu\",\"Arb\",\"Kha\",\"Jum\",\"Sab\"],dayNamesMin:[\"Ah\",\"It\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!1}},leapYear:function(t){return(11*this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year()+14)%30<11},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return this.leapYear(t)?355:354},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),t=t<=0?t+1:t,(r=i.day())+Math.ceil(29.5*(e-1))+354*(t-1)+Math.floor((3+11*t)/30)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t)+.5;var e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.islamic=a},{\"../main\":640,\"object-assign\":483}],632:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Julian\",jdEpoch:1721423.5,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Julian\",epochs:[\"BC\",\"AD\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"mm/dd/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()<0?e.year()+1:e.year())%4==0},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),r=i.day(),t<0&&t++,e<=2&&(t--,e+=12),Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r-1524.5},fromJD:function(t){var e=Math.floor(t+.5)+1524,r=Math.floor((e-122.1)/365.25),n=Math.floor(365.25*r),i=Math.floor((e-n)/30.6001),a=i-Math.floor(i<14?1:13),o=r-Math.floor(a>2?4716:4715),s=e-n-Math.floor(30.6001*i);return o<=0&&o--,this.newDate(o,a,s)}}),n.calendars.julian=a},{\"../main\":640,\"object-assign\":483}],633:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}function s(t,e){return o(t-1,e)+1}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Mayan\",jdEpoch:584282.5,hasYearZero:!0,minMonth:0,firstMonth:0,minDay:0,regionalOptions:{\"\":{name:\"Mayan\",epochs:[\"\",\"\"],monthNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],monthNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],dayNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesMin:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],digits:null,dateFormat:\"YYYY.m.d\",firstDay:0,isRTL:!1,haabMonths:[\"Pop\",\"Uo\",\"Zip\",\"Zotz\",\"Tzec\",\"Xul\",\"Yaxkin\",\"Mol\",\"Chen\",\"Yax\",\"Zac\",\"Ceh\",\"Mac\",\"Kankin\",\"Muan\",\"Pax\",\"Kayab\",\"Cumku\",\"Uayeb\"],tzolkinMonths:[\"Imix\",\"Ik\",\"Akbal\",\"Kan\",\"Chicchan\",\"Cimi\",\"Manik\",\"Lamat\",\"Muluc\",\"Oc\",\"Chuen\",\"Eb\",\"Ben\",\"Ix\",\"Men\",\"Cib\",\"Caban\",\"Etznab\",\"Cauac\",\"Ahau\"]}},leapYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r<t.length;r++){var n=parseInt(t[r],10);if(Math.abs(n)>19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),!0},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate).toJD(),a=this._toHaab(i),o=this._toTzolkin(i);return{haabMonthName:this.local.haabMonths[a[0]-1],haabMonth:a[0],haabDay:a[1],tzolkinDayName:this.local.tzolkinMonths[o[0]-1],tzolkinDay:o[0],tzolkinTrecena:o[1]}},_toHaab:function(t){var e=o((t-=this.jdEpoch)+8+340,365);return[Math.floor(e/20)+1,o(e,20)]},_toTzolkin:function(t){return[s((t-=this.jdEpoch)+20,20),s(t+4,13)]},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return i.day()+20*i.month()+360*i.year()+this.jdEpoch},fromJD:function(t){t=Math.floor(t)+.5-this.jdEpoch;var e=Math.floor(t/360);t%=360,t+=t<0?360:0;var r=Math.floor(t/20),n=t%20;return this.newDate(e,r,n)}}),n.calendars.mayan=a},{\"../main\":640,\"object-assign\":483}],634:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar;var o=n.instance(\"gregorian\");i(a.prototype,{name:\"Nanakshahi\",jdEpoch:2257673.5,daysPerMonth:[31,31,31,31,31,30,30,30,30,30,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Nanakshahi\",epochs:[\"BN\",\"AN\"],monthNames:[\"Chet\",\"Vaisakh\",\"Jeth\",\"Harh\",\"Sawan\",\"Bhadon\",\"Assu\",\"Katak\",\"Maghar\",\"Poh\",\"Magh\",\"Phagun\"],monthNamesShort:[\"Che\",\"Vai\",\"Jet\",\"Har\",\"Saw\",\"Bha\",\"Ass\",\"Kat\",\"Mgr\",\"Poh\",\"Mgh\",\"Pha\"],dayNames:[\"Somvaar\",\"Mangalvar\",\"Budhvaar\",\"Veervaar\",\"Shukarvaar\",\"Sanicharvaar\",\"Etvaar\"],dayNamesShort:[\"Som\",\"Mangal\",\"Budh\",\"Veer\",\"Shukar\",\"Sanichar\",\"Et\"],dayNamesMin:[\"So\",\"Ma\",\"Bu\",\"Ve\",\"Sh\",\"Sa\",\"Et\"],digits:null,dateFormat:\"dd-mm-yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear);return o.leapYear(e.year()+(e.year()<1?1:0)+1469)},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(1-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidMonth);(t=i.year())<0&&t++;for(var a=i.day(),s=1;s<i.month();s++)a+=this.daysPerMonth[s-1];return a+o.toJD(t+1468,3,13)},fromJD:function(t){t=Math.floor(t+.5);for(var e=Math.floor((t-(this.jdEpoch-1))/366);t>=this.toJD(e+1,1,1);)e++;for(var r=t-Math.floor(this.toJD(e,1,1)+.5)+1,n=1;r>this.daysInMonth(e,n);)r-=this.daysInMonth(e,n),n++;return this.newDate(e,n,r)}}),n.calendars.nanakshahi=a},{\"../main\":640,\"object-assign\":483}],635:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Nepali\",jdEpoch:1700709.5,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{\"\":{name:\"Nepali\",epochs:[\"BBS\",\"ABS\"],monthNames:[\"Baisakh\",\"Jestha\",\"Ashadh\",\"Shrawan\",\"Bhadra\",\"Ashwin\",\"Kartik\",\"Mangsir\",\"Paush\",\"Mangh\",\"Falgun\",\"Chaitra\"],monthNamesShort:[\"Bai\",\"Je\",\"As\",\"Shra\",\"Bha\",\"Ash\",\"Kar\",\"Mang\",\"Pau\",\"Ma\",\"Fal\",\"Chai\"],dayNames:[\"Aaitabaar\",\"Sombaar\",\"Manglbaar\",\"Budhabaar\",\"Bihibaar\",\"Shukrabaar\",\"Shanibaar\"],dayNamesShort:[\"Aaita\",\"Som\",\"Mangl\",\"Budha\",\"Bihi\",\"Shukra\",\"Shani\"],dayNamesMin:[\"Aai\",\"So\",\"Man\",\"Bu\",\"Bi\",\"Shu\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:1,isRTL:!1}},leapYear:function(t){return 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9===e?(o+=r-this.NEPALI_CALENDAR_DATA[l][0])<0&&(o+=a.daysInYear(c)):o+=this.NEPALI_CALENDAR_DATA[l][9]-this.NEPALI_CALENDAR_DATA[l][0],a.newDate(c,1,1).add(o,\"d\").toJD()},fromJD:function(t){var e=n.instance().fromJD(t),r=e.year(),i=e.dayOfYear(),a=r+56;this._createMissingCalendarData(a);for(var o=9,s=this.NEPALI_CALENDAR_DATA[a][0],l=this.NEPALI_CALENDAR_DATA[a][o]-s+1;i>l;)++o>12&&(o=1,a++),l+=this.NEPALI_CALENDAR_DATA[a][o];var c=this.NEPALI_CALENDAR_DATA[a][o]-(l-i);return this.newDate(a,o,c)},_createMissingCalendarData:function(t){var e=this.daysPerMonth.slice(0);e.unshift(17);for(var r=t-1;r<t+2;r++)void 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 682*((e.year()-(e.year()>0?474:473))%2820+474+38)%2816<682},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-(n.dayOfWeek()+1)%7,\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t-(t>=0?474:473),s=474+o(a,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(a/2820)+this.jdEpoch-1},fromJD:function(t){var e=(t=Math.floor(t)+.5)-this.toJD(475,1,1),r=Math.floor(e/1029983),n=o(e,1029983),i=2820;if(1029982!==n){var a=Math.floor(n/366),s=o(n,366);i=Math.floor((2134*a+2816*s+2815)/1028522)+a+1}var l=i+2820*r+474;l=l<=0?l-1:l;var 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i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(i.year());return a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(i.year());return a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)},_g2tYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)}}),n.calendars.taiwan=o},{\"../main\":640,\"object-assign\":483}],638:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\"),a=n.instance();function 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n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thal\\u0101th\\u0101\\u2019\",\"Yawm al-Arba\\u2018\\u0101\\u2019\",\"Yawm al-Kham\\u012bs\",\"Yawm al-Jum\\u2018a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,i=0,a=0;a<o.length;a++){if(o[a]>r)return o[i]-o[i-1];i++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate),a=12*(i.year()-1)+i.month()-15292;return i.day()+o[a-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;n<o.length&&!(o[n]>e);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),s=a+1,l=i-12*a,c=e-o[r-1]+1;return this.newDate(s,l,c)},isValid:function(t,e,r){var i=n.baseCalendar.prototype.isValid.apply(this,arguments);return i&&(i=(t=null!=t.year?t.year:t)>=1276&&t<=1500),i},_validate:function(t,e,r,i){var a=n.baseCalendar.prototype._validate.apply(this,arguments);if(a.year<1276||a.year>1500)throw i.replace(/\\{0\\}/,this.local.name);return a}}),n.calendars.ummalqura=a;var 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n=t(\"object-assign\");function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(c.local.differentCalendars||c.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);i=t.day();\"y\"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):\"m\"===r&&(!function(t){for(;o<t.minMonth;)a--,o+=t.monthsInYear(a);for(var e=t.monthsInYear(a);o>e-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw 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r,s,l=o(t,e),c=l.on,u=l.off.concat(l.explicitOff),f={},h=t._fullLayout.annotations;if(!c.length&&!u.length)return;for(r=0;r<c.length;r++)(s=a(t.layout,\"annotations\",h[c[r]])).modifyItem(\"visible\",!0),n.extendFlat(f,s.getUpdateObj());for(r=0;r<u.length;r++)(s=a(t.layout,\"annotations\",h[u[r]])).modifyItem(\"visible\",!1),n.extendFlat(f,s.getUpdateObj());return i.call(\"update\",t,{},f)}}},{\"../../lib\":799,\"../../plot_api/plot_template\":838,\"../../registry\":927}],648:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../color\");e.exports=function(t,e,r,a){a(\"opacity\");var o=a(\"bgcolor\"),s=a(\"bordercolor\"),l=i.opacity(s);a(\"borderpad\");var c=a(\"borderwidth\"),u=a(\"showarrow\");if(a(\"text\",u?\" \":r._dfltTitle.annotation),a(\"textangle\"),n.coerceFont(a,\"font\",r.font),a(\"width\"),a(\"align\"),a(\"height\")&&a(\"valign\"),u){var f,h,p=a(\"arrowside\");-1!==p.indexOf(\"end\")&&(f=a(\"arrowhead\"),h=a(\"arrowsize\")),-1!==p.indexOf(\"start\")&&(a(\"startarrowhead\",f),a(\"startarrowsize\",h)),a(\"arrowcolor\",l?e.bordercolor:i.defaultLine),a(\"arrowwidth\",2*(l&&c||1)),a(\"standoff\"),a(\"startstandoff\")}var d=a(\"hovertext\"),m=r.hoverlabel||{};if(d){var g=a(\"hoverlabel.bgcolor\",m.bgcolor||(i.opacity(o)?i.rgb(o):i.defaultLine)),v=a(\"hoverlabel.bordercolor\",m.bordercolor||i.contrast(g));n.coerceFont(a,\"hoverlabel.font\",{family:m.font.family,size:m.font.size,color:m.font.color||v})}a(\"captureevents\",!!d)}},{\"../../lib\":799,\"../color\":662}],649:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib/to_log_range\");e.exports=function(t,e,r,a){e=e||{};var o=\"log\"===r&&\"linear\"===e.type,s=\"linear\"===r&&\"log\"===e.type;if(o||s)for(var l,c,u=t._fullLayout.annotations,f=e._id.charAt(0),h=0;h<u.length;h++)l=u[h],c=\"annotations[\"+h+\"].\",l[f+\"ref\"]===e._id&&p(f),l[\"a\"+f+\"ref\"]===e._id&&p(\"a\"+f);function p(t){var r=l[t],s=null;s=o?i(r,e.range):Math.pow(10,r),n(s)||(s=null),a(c+t,s)}}},{\"../../lib/to_log_range\":826,\"fast-isnumeric\":245}],650:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../plots/cartesian/axes\"),a=t(\"../../plots/array_container_defaults\"),o=t(\"./common_defaults\"),s=t(\"./attributes\");function l(t,e,r){function a(r,i){return n.coerce(t,e,s,r,i)}var l=a(\"visible\"),c=a(\"clicktoshow\");if(l||c){o(t,e,r,a);for(var u=e.showarrow,f=[\"x\",\"y\"],h=[-10,-30],p={_fullLayout:r},d=0;d<2;d++){var m=f[d],g=i.coerceRef(t,e,p,m,\"\",\"paper\");if(\"paper\"!==g)i.getFromId(p,g)._annIndices.push(e._index);if(i.coercePosition(e,p,a,g,m,.5),u){var v=\"a\"+m,y=i.coerceRef(t,e,p,v,\"pixel\",[\"pixel\",\"paper\"]);\"pixel\"!==y&&y!==g&&(y=e[v]=\"pixel\");var x=\"pixel\"===y?h[d]:.4;i.coercePosition(e,p,a,y,v,x)}a(m+\"anchor\"),a(m+\"shift\")}if(n.noneOrAll(t,e,[\"x\",\"y\"]),u&&n.noneOrAll(t,e,[\"ax\",\"ay\"]),c){var b=a(\"xclick\"),_=a(\"yclick\");e._xclick=void 0===b?e.x:i.cleanPosition(b,p,e.xref),e._yclick=void 0===_?e.y:i.cleanPosition(_,p,e.yref)}}}e.exports=function(t,e){a(t,e,{name:\"annotations\",handleItemDefaults:l})}},{\"../../lib\":799,\"../../plots/array_container_defaults\":844,\"../../plots/cartesian/axes\":849,\"./attributes\":645,\"./common_defaults\":648}],651:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../registry\"),a=t(\"../../plots/plots\"),o=t(\"../../lib\"),s=o.strTranslate,l=t(\"../../plots/cartesian/axes\"),c=t(\"../color\"),u=t(\"../drawing\"),f=t(\"../fx\"),h=t(\"../../lib/svg_text_utils\"),p=t(\"../../lib/setcursor\"),d=t(\"../dragelement\"),m=t(\"../../plot_api/plot_template\").arrayEditor,g=t(\"./draw_arrow_head\");function v(t,e){var r=t._fullLayout.annotations[e]||{},n=l.getFromId(t,r.xref),i=l.getFromId(t,r.yref);n&&n.setScale(),i&&i.setScale(),x(t,r,e,!1,n,i)}function y(t,e,r,n,i){var a=i[r],o=i[r+\"ref\"],s=-1!==r.indexOf(\"y\"),c=\"domain\"===l.getRefType(o),u=s?n.h:n.w;return t?c?a+(s?-e:e)/t._length:t.p2r(t.r2p(a)+e):a+(s?-e:e)/u}function x(t,e,r,a,v,x){var b,_,w=t._fullLayout,T=t._fullLayout._size,k=t._context.edits;a?(b=\"annotation-\"+a,_=a+\".annotations\"):(b=\"annotation\",_=\"annotations\");var M=m(t.layout,_,e),A=M.modifyBase,S=M.modifyItem,E=M.getUpdateObj;w._infolayer.selectAll(\".\"+b+'[data-index=\"'+r+'\"]').remove();var L=\"clip\"+w._uid+\"_ann\"+r;if(e._input&&!1!==e.visible){var C={x:{},y:{}},P=+e.textangle||0,I=w._infolayer.append(\"g\").classed(b,!0).attr(\"data-index\",String(r)).style(\"opacity\",e.opacity),O=I.append(\"g\").classed(\"annotation-text-g\",!0),z=k[e.showarrow?\"annotationTail\":\"annotationPosition\"],D=e.captureevents||k.annotationText||z,R=O.append(\"g\").style(\"pointer-events\",D?\"all\":null).call(p,\"pointer\").on(\"click\",(function(){t._dragging=!1,t.emit(\"plotly_clickannotation\",Y(n.event))}));e.hovertext&&R.on(\"mouseover\",(function(){var r=e.hoverlabel,n=r.font,i=this.getBoundingClientRect(),a=t.getBoundingClientRect();f.loneHover({x0:i.left-a.left,x1:i.right-a.left,y:(i.top+i.bottom)/2-a.top,text:e.hovertext,color:r.bgcolor,borderColor:r.bordercolor,fontFamily:n.family,fontSize:n.size,fontColor:n.color},{container:w._hoverlayer.node(),outerContainer:w._paper.node(),gd:t})})).on(\"mouseout\",(function(){f.loneUnhover(w._hoverlayer.node())}));var F=e.borderwidth,B=e.borderpad,N=F+B,j=R.append(\"rect\").attr(\"class\",\"bg\").style(\"stroke-width\",F+\"px\").call(c.stroke,e.bordercolor).call(c.fill,e.bgcolor),U=e.width||e.height,V=w._topclips.selectAll(\"#\"+L).data(U?[0]:[]);V.enter().append(\"clipPath\").classed(\"annclip\",!0).attr(\"id\",L).append(\"rect\"),V.exit().remove();var q=e.font,H=w._meta?o.templateString(e.text,w._meta):e.text,G=R.append(\"text\").classed(\"annotation-text\",!0).text(H);k.annotationText?G.call(h.makeEditable,{delegate:R,gd:t}).call(W).on(\"edit\",(function(r){e.text=r,this.call(W),S(\"text\",r),v&&v.autorange&&A(v._name+\".autorange\",!0),x&&x.autorange&&A(x._name+\".autorange\",!0),i.call(\"_guiRelayout\",t,E())})):G.call(W)}else n.selectAll(\"#\"+L).remove();function Y(t){var n={index:r,annotation:e._input,fullAnnotation:e,event:t};return a&&(n.subplotId=a),n}function W(r){return r.call(u.font,q).attr({\"text-anchor\":{left:\"start\",right:\"end\"}[e.align]||\"middle\"}),h.convertToTspans(r,t,X),r}function X(){var r=G.selectAll(\"a\");1===r.size()&&r.text()===G.text()&&R.insert(\"a\",\":first-child\").attr({\"xlink:xlink:href\":r.attr(\"xlink:href\"),\"xlink:xlink:show\":r.attr(\"xlink:show\")}).style({cursor:\"pointer\"}).node().appendChild(j.node());var n=R.select(\".annotation-text-math-group\"),f=!n.empty(),m=u.bBox((f?n:G).node()),b=m.width,_=m.height,M=e.width||b,D=e.height||_,B=Math.round(M+2*N),q=Math.round(D+2*N);function H(t,e){return\"auto\"===e&&(e=t<1/3?\"left\":t>2/3?\"right\":\"center\"),{center:0,middle:0,left:.5,bottom:-.5,right:-.5,top:.5}[e]}for(var W=!1,X=[\"x\",\"y\"],Z=0;Z<X.length;Z++){var J,K,Q,$,tt,et=X[Z],rt=e[et+\"ref\"]||et,nt=e[\"a\"+et+\"ref\"],it={x:v,y:x}[et],at=(P+(\"x\"===et?0:-90))*Math.PI/180,ot=B*Math.cos(at),st=q*Math.sin(at),lt=Math.abs(ot)+Math.abs(st),ct=e[et+\"anchor\"],ut=e[et+\"shift\"]*(\"x\"===et?1:-1),ft=C[et],ht=l.getRefType(rt);if(it&&\"domain\"!==ht){var pt=it.r2fraction(e[et]);(pt<0||pt>1)&&(nt===rt?((pt=it.r2fraction(e[\"a\"+et]))<0||pt>1)&&(W=!0):W=!0),J=it._offset+it.r2p(e[et]),$=.5}else{var dt=\"domain\"===ht;\"x\"===et?(Q=e[et],J=dt?it._offset+it._length*Q:J=T.l+T.w*Q):(Q=1-e[et],J=dt?it._offset+it._length*Q:J=T.t+T.h*Q),$=e.showarrow?.5:Q}if(e.showarrow){ft.head=J;var mt=e[\"a\"+et];if(tt=ot*H(.5,e.xanchor)-st*H(.5,e.yanchor),nt===rt){var gt=l.getRefType(nt);\"domain\"===gt?(\"y\"===et&&(mt=1-mt),ft.tail=it._offset+it._length*mt):\"paper\"===gt?\"y\"===et?(mt=1-mt,ft.tail=T.t+T.h*mt):ft.tail=T.l+T.w*mt:ft.tail=it._offset+it.r2p(mt),K=tt}else ft.tail=J+mt,K=tt+mt;ft.text=ft.tail+tt;var vt=w[\"x\"===et?\"width\":\"height\"];if(\"paper\"===rt&&(ft.head=o.constrain(ft.head,1,vt-1)),\"pixel\"===nt){var yt=-Math.max(ft.tail-3,ft.text),xt=Math.min(ft.tail+3,ft.text)-vt;yt>0?(ft.tail+=yt,ft.text+=yt):xt>0&&(ft.tail-=xt,ft.text-=xt)}ft.tail+=ut,ft.head+=ut}else K=tt=lt*H($,ct),ft.text=J+tt;ft.text+=ut,tt+=ut,K+=ut,e[\"_\"+et+\"padplus\"]=lt/2+K,e[\"_\"+et+\"padminus\"]=lt/2-K,e[\"_\"+et+\"size\"]=lt,e[\"_\"+et+\"shift\"]=tt}if(W)R.remove();else{var bt=0,_t=0;if(\"left\"!==e.align&&(bt=(M-b)*(\"center\"===e.align?.5:1)),\"top\"!==e.valign&&(_t=(D-_)*(\"middle\"===e.valign?.5:1)),f)n.select(\"svg\").attr({x:N+bt-1,y:N+_t}).call(u.setClipUrl,U?L:null,t);else{var wt=N+_t-m.top,Tt=N+bt-m.left;G.call(h.positionText,Tt,wt).call(u.setClipUrl,U?L:null,t)}V.select(\"rect\").call(u.setRect,N,N,M,D),j.call(u.setRect,F/2,F/2,B-F,q-F),R.call(u.setTranslate,Math.round(C.x.text-B/2),Math.round(C.y.text-q/2)),O.attr({transform:\"rotate(\"+P+\",\"+C.x.text+\",\"+C.y.text+\")\"});var kt,Mt=function(r,n){I.selectAll(\".annotation-arrow-g\").remove();var l=C.x.head,f=C.y.head,h=C.x.tail+r,p=C.y.tail+n,m=C.x.text+r,b=C.y.text+n,_=o.rotationXYMatrix(P,m,b),w=o.apply2DTransform(_),M=o.apply2DTransform2(_),L=+j.attr(\"width\"),z=+j.attr(\"height\"),D=m-.5*L,F=D+L,B=b-.5*z,N=B+z,U=[[D,B,D,N],[D,N,F,N],[F,N,F,B],[F,B,D,B]].map(M);if(!U.reduce((function(t,e){return t^!!o.segmentsIntersect(l,f,l+1e6,f+1e6,e[0],e[1],e[2],e[3])}),!1)){U.forEach((function(t){var e=o.segmentsIntersect(h,p,l,f,t[0],t[1],t[2],t[3]);e&&(h=e.x,p=e.y)}));var V=e.arrowwidth,q=e.arrowcolor,H=e.arrowside,G=I.append(\"g\").style({opacity:c.opacity(q)}).classed(\"annotation-arrow-g\",!0),Y=G.append(\"path\").attr(\"d\",\"M\"+h+\",\"+p+\"L\"+l+\",\"+f).style(\"stroke-width\",V+\"px\").call(c.stroke,c.rgb(q));if(g(Y,H,e),k.annotationPosition&&Y.node().parentNode&&!a){var W=l,X=f;if(e.standoff){var Z=Math.sqrt(Math.pow(l-h,2)+Math.pow(f-p,2));W+=e.standoff*(h-l)/Z,X+=e.standoff*(p-f)/Z}var 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n=t(\"../annotations/attributes\"),i=t(\"../../plot_api/edit_types\").overrideAll,a=t(\"../../plot_api/plot_template\").templatedArray;e.exports=i(a(\"annotation\",{visible:n.visible,x:{valType:\"any\"},y:{valType:\"any\"},z:{valType:\"any\"},ax:{valType:\"number\"},ay:{valType:\"number\"},xanchor:n.xanchor,xshift:n.xshift,yanchor:n.yanchor,yshift:n.yshift,text:n.text,textangle:n.textangle,font:n.font,width:n.width,height:n.height,opacity:n.opacity,align:n.align,valign:n.valign,bgcolor:n.bgcolor,bordercolor:n.bordercolor,borderpad:n.borderpad,borderwidth:n.borderwidth,showarrow:n.showarrow,arrowcolor:n.arrowcolor,arrowhead:n.arrowhead,startarrowhead:n.startarrowhead,arrowside:n.arrowside,arrowsize:n.arrowsize,startarrowsize:n.startarrowsize,arrowwidth:n.arrowwidth,standoff:n.standoff,startstandoff:n.startstandoff,hovertext:n.hovertext,hoverlabel:n.hoverlabel,captureevents:n.captureevents}),\"calc\",\"from-root\")},{\"../../plot_api/edit_types\":831,\"../../plot_api/plot_template\":838,\"../annotations/attributes\":645}],655:[function(t,e,r){\"use 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n.coerce(t,e,s,r,i)}function c(t){var n=t+\"axis\",a={_fullLayout:{}};return a._fullLayout[n]=r[n],i.coercePosition(e,a,l,t,t,.5)}l(\"visible\")&&(o(t,e,a.fullLayout,l),c(\"x\"),c(\"y\"),c(\"z\"),n.noneOrAll(t,e,[\"x\",\"y\",\"z\"]),e.xref=\"x\",e.yref=\"y\",e.zref=\"z\",l(\"xanchor\"),l(\"yanchor\"),l(\"xshift\"),l(\"yshift\"),e.showarrow&&(e.axref=\"pixel\",e.ayref=\"pixel\",l(\"ax\",-10),l(\"ay\",-30),n.noneOrAll(t,e,[\"ax\",\"ay\"])))}e.exports=function(t,e,r){a(t,e,{name:\"annotations\",handleItemDefaults:l,fullLayout:r.fullLayout})}},{\"../../lib\":799,\"../../plots/array_container_defaults\":844,\"../../plots/cartesian/axes\":849,\"../annotations/common_defaults\":648,\"./attributes\":654}],657:[function(t,e,r){\"use strict\";var n=t(\"../annotations/draw\").drawRaw,i=t(\"../../plots/gl3d/project\"),a=[\"x\",\"y\",\"z\"];e.exports=function(t){for(var e=t.fullSceneLayout,r=t.dataScale,o=e.annotations,s=0;s<o.length;s++){for(var l=o[s],c=!1,u=0;u<3;u++){var 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This does not set the calendar for\",\"interpreting data on this axis, that's specified in the trace\",\"or via the global `layout.calendar`\"].join(\" \"));e.exports={moduleType:\"component\",name:\"calendars\",schema:{traces:{scatter:g,bar:g,box:g,heatmap:g,contour:g,histogram:g,histogram2d:g,histogram2dcontour:g,scatter3d:v,surface:v,mesh3d:v,scattergl:g,ohlc:m,candlestick:m},layout:{calendar:p([\"Sets the default calendar system to use for interpreting and\",\"displaying dates throughout the plot.\"].join(\" \"))},subplots:{xaxis:{calendar:y},yaxis:{calendar:y},scene:{xaxis:{calendar:y},yaxis:{calendar:y},zaxis:{calendar:y}},polar:{radialaxis:{calendar:y}}},transforms:{filter:{valuecalendar:p([\"WARNING: All transforms are deprecated and may be removed from the API in next major version.\",\"Sets the calendar system to use for `value`, if it is a date.\"].join(\" \")),targetcalendar:p([\"WARNING: All transforms are deprecated and may be removed from the API in next major version.\",\"Sets the calendar system to use for `target`, if it is an\",\"array of dates. If `target` is a string (eg *x*) we use the\",\"corresponding trace attribute (eg `xcalendar`) if it exists,\",\"even if `targetcalendar` is provided.\"].join(\" \"))}}},layoutAttributes:l,handleDefaults:c,handleTraceDefaults:function(t,e,r,n){for(var i=0;i<r.length;i++)c(t,e,r[i]+\"calendar\",n.calendar)},CANONICAL_SUNDAY:{chinese:\"2000-01-02\",coptic:\"2000-01-03\",discworld:\"2000-01-03\",ethiopian:\"2000-01-05\",hebrew:\"5000-01-01\",islamic:\"1000-01-02\",julian:\"2000-01-03\",mayan:\"5000-01-01\",nanakshahi:\"1000-01-05\",nepali:\"2000-01-05\",persian:\"1000-01-01\",jalali:\"1000-01-01\",taiwan:\"1000-01-04\",thai:\"2000-01-04\",ummalqura:\"1400-01-06\"},CANONICAL_TICK:{chinese:\"2000-01-01\",coptic:\"2000-01-01\",discworld:\"2000-01-01\",ethiopian:\"2000-01-01\",hebrew:\"5000-01-01\",islamic:\"1000-01-01\",julian:\"2000-01-01\",mayan:\"5000-01-01\",nanakshahi:\"1000-01-01\",nepali:\"2000-01-01\",persian:\"1000-01-01\",jalali:\"1000-01-01\",taiwan:\"1000-01-01\",thai:\"2000-01-01\",ummalqura:\"1400-01-01\"},DFLTRANGE:{chinese:[\"2000-01-01\",\"2001-01-01\"],coptic:[\"1700-01-01\",\"1701-01-01\"],discworld:[\"1800-01-01\",\"1801-01-01\"],ethiopian:[\"2000-01-01\",\"2001-01-01\"],hebrew:[\"5700-01-01\",\"5701-01-01\"],islamic:[\"1400-01-01\",\"1401-01-01\"],julian:[\"2000-01-01\",\"2001-01-01\"],mayan:[\"5200-01-01\",\"5201-01-01\"],nanakshahi:[\"0500-01-01\",\"0501-01-01\"],nepali:[\"2000-01-01\",\"2001-01-01\"],persian:[\"1400-01-01\",\"1401-01-01\"],jalali:[\"1400-01-01\",\"1401-01-01\"],taiwan:[\"0100-01-01\",\"0101-01-01\"],thai:[\"2500-01-01\",\"2501-01-01\"],ummalqura:[\"1400-01-01\",\"1401-01-01\"]},getCal:h,worldCalFmt:function(t,e,r){for(var 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F,N,j,U,V,q,H,G,Y,W,X,Z,J,K=[],Q=[],$={hLinePoint:null,vLinePoint:null},tt=!1;if(Array.isArray(e))for(S=\"array\",j=0;j<e.length;j++)(V=t.calcdata[e[j].curveNumber||0])&&(q=V[0].trace,\"skip\"!==V[0].trace.hoverinfo&&(Q.push(V),\"h\"===q.orientation&&(tt=!0)));else{for(U=0;U<t.calcdata.length;U++)V=t.calcdata[U],\"skip\"!==(q=V[0].trace).hoverinfo&&v.isTraceInSubplots(q,s)&&(Q.push(V),\"h\"===q.orientation&&(tt=!0));var et,rt;if(!e.target)et=\"xpx\"in e?e.xpx:b[0]._length/2,rt=\"ypx\"in e?e.ypx:_[0]._length/2;else{if(!1===c.triggerHandler(t,\"plotly_beforehover\",e))return;var nt=e.composedPath&&e.composedPath()[0];nt||(nt=e.target);var it=nt.getBoundingClientRect();et=e.clientX-it.left,rt=e.clientY-it.top,l._calcInverseTransform(t);var at=o.apply3DTransform(l._invTransform)(et,rt);if(et=at[0],rt=at[1],et<0||et>b[0]._length||rt<0||rt>_[0]._length)return d.unhoverRaw(t,e)}if(e.pointerX=et+b[0]._offset,e.pointerY=rt+_[0]._offset,F=\"xval\"in e?v.flat(s,e.xval):v.p2c(b,et),N=\"yval\"in e?v.flat(s,e.yval):v.p2c(_,rt),!i(F[0])||!i(N[0]))return o.warn(\"Fx.hover failed\",e,t),d.unhoverRaw(t,e)}var ot=1/0;function st(t,r){for(U=0;U<Q.length;U++)if((V=Q[U])&&V[0]&&V[0].trace&&!0===(q=V[0].trace).visible&&0!==q._length&&-1===[\"carpet\",\"contourcarpet\"].indexOf(q._module.name)){if(\"splom\"===q.type?H=s[G=0]:(H=v.getSubplot(q),G=s.indexOf(H)),Y=S,v.isUnifiedHover(Y)&&(Y=Y.charAt(0)),Z={cd:V,trace:q,xa:b[G],ya:_[G],maxHoverDistance:C,maxSpikeDistance:I,index:!1,distance:Math.min(ot,C),spikeDistance:1/0,xSpike:void 0,ySpike:void 0,color:p.defaultLine,name:q.name,x0:void 0,x1:void 0,y0:void 0,y1:void 0,xLabelVal:void 0,yLabelVal:void 0,zLabelVal:void 0,text:void 0},l[H]&&(Z.subplot=l[H]._subplot),l._splomScenes&&l._splomScenes[q.uid]&&(Z.scene=l._splomScenes[q.uid]),J=K.length,\"array\"===Y){var n=e[U];\"pointNumber\"in n?(Z.index=n.pointNumber,Y=\"closest\"):(Y=\"\",\"xval\"in n&&(W=n.xval,Y=\"x\"),\"yval\"in n&&(X=n.yval,Y=Y?\"closest\":\"y\"))}else void 0!==t&&void 0!==r?(W=t,X=r):(W=F[G],X=N[G]);if(0!==C)if(q._module&&q._module.hoverPoints){var a=q._module.hoverPoints(Z,W,X,Y,{finiteRange:!0,hoverLayer:l._hoverlayer});if(a)for(var c,u=0;u<a.length;u++)c=a[u],i(c.x0)&&i(c.y0)&&K.push(z(c,S))}else o.log(\"Unrecognized trace type in hover:\",q);if(\"closest\"===S&&K.length>J&&(K.splice(0,J),ot=K[0].distance),m&&0!==I&&0===K.length){Z.distance=I,Z.index=!1;var f=q._module.hoverPoints(Z,W,X,\"closest\",{hoverLayer:l._hoverlayer});if(f&&(f=f.filter((function(t){return t.spikeDistance<=I}))),f&&f.length){var h,d=f.filter((function(t){return t.xa.showspikes&&\"hovered data\"!==t.xa.spikesnap}));if(d.length){var g=d[0];i(g.x0)&&i(g.y0)&&(h=ct(g),(!$.vLinePoint||$.vLinePoint.spikeDistance>h.spikeDistance)&&($.vLinePoint=h))}var y=f.filter((function(t){return t.ya.showspikes&&\"hovered data\"!==t.ya.spikesnap}));if(y.length){var x=y[0];i(x.x0)&&i(x.y0)&&(h=ct(x),(!$.hLinePoint||$.hLinePoint.spikeDistance>h.spikeDistance)&&($.hLinePoint=h))}}}}}function lt(t,e){for(var r,n=null,i=1/0,a=0;a<t.length;a++)(r=t[a].spikeDistance)<=i&&r<=e&&(n=t[a],i=r);return n}function ct(t){return t?{xa:t.xa,ya:t.ya,x:void 0!==t.xSpike?t.xSpike:(t.x0+t.x1)/2,y:void 0!==t.ySpike?t.ySpike:(t.y0+t.y1)/2,distance:t.distance,spikeDistance:t.spikeDistance,curveNumber:t.trace.index,color:t.color,pointNumber:t.index}:null}st();var ut={fullLayout:l,container:l._hoverlayer,outerContainer:l._paperdiv,event:e},ft=t._spikepoints,ht={vLinePoint:$.vLinePoint,hLinePoint:$.hLinePoint};if(t._spikepoints=ht,m&&0!==I&&0!==K.length){var pt=lt(K.filter((function(t){return t.ya.showspikes})),I);$.hLinePoint=ct(pt);var dt=lt(K.filter((function(t){return t.xa.showspikes})),I);$.vLinePoint=ct(dt)}if(0===K.length){var mt=d.unhoverRaw(t,e);return!m||null===$.hLinePoint&&null===$.vLinePoint||R(ft)&&D(t,$,ut),mt}m&&R(ft)&&D(t,$,ut);var gt=function(){K.sort((function(t,e){return t.distance-e.distance})),K=function(t,e){for(var r=e.charAt(0),n=[],i=[],a=[],o=0;o<t.length;o++){var s=t[o];g.traceIs(s.trace,\"bar-like\")||g.traceIs(s.trace,\"box-violin\")?a.push(s):s.trace[r+\"period\"]?i.push(s):n.push(s)}return n.concat(i).concat(a)}(K,S)};if(gt(),v.isXYhover(Y)&&0!==K[0].length&&\"splom\"!==K[0].trace.type){var vt=K[0],yt=(K=E[vt.trace.type]?K.filter((function(t){return t.trace.index===vt.trace.index})):[vt]).length,xt=B(\"x\",vt,l),bt=B(\"y\",vt,l);st(xt,bt);var _t,wt=[],Tt={},kt=0,Mt=function(t){var e=E[t.trace.type]?L(t):t.trace.index;if(Tt[e]){var r=Tt[e]-1,n=wt[r];r>0&&Math.abs(t.distance)<Math.abs(n.distance)&&(wt[r]=t)}else kt++,Tt[e]=kt,wt.push(t)};for(_t=0;_t<yt;_t++)Mt(K[_t]);for(_t=K.length-1;_t>yt-1;_t--)Mt(K[_t]);K=wt,gt()}var At=t._hoverdata,St=[];for(j=0;j<K.length;j++){var Et=K[j],Lt=v.makeEventData(Et,Et.trace,Et.cd);if(!1!==Et.hovertemplate){var Ct=!1;Et.cd[Et.index]&&Et.cd[Et.index].ht&&(Ct=Et.cd[Et.index].ht),Et.hovertemplate=Ct||Et.trace.hovertemplate||!1}Et.eventData=[Lt],St.push(Lt)}t._hoverdata=St;var Pt=\"y\"===S&&(Q.length>1||K.length>1)||\"closest\"===S&&tt&&K.length>1,It=p.combine(l.plot_bgcolor||p.background,l.paper_bgcolor),Ot={hovermode:S,rotateLabels:Pt,bgColor:It,container:l._hoverlayer,outerContainer:l._paperdiv,commonLabelOpts:l.hoverlabel,hoverdistance:l.hoverdistance},zt=P(K,Ot,t);v.isUnifiedHover(S)||(!function(t,e,r){var n,i,a,o,s,l,c,u=0,f=1,h=t.size(),p=new Array(h),d=0;function m(t){var e=t[0],r=t[t.length-1];if(i=e.pmin-e.pos-e.dp+e.size,a=r.pos+r.dp+r.size-e.pmax,i>.01){for(s=t.length-1;s>=0;s--)t[s].dp+=i;n=!1}if(!(a<.01)){if(i<-.01){for(s=t.length-1;s>=0;s--)t[s].dp-=a;n=!1}if(n){var c=0;for(o=0;o<t.length;o++)(l=t[o]).pos+l.dp+l.size>e.pmax&&c++;for(o=t.length-1;o>=0&&!(c<=0);o--)(l=t[o]).pos>e.pmax-1&&(l.del=!0,c--);for(o=0;o<t.length&&!(c<=0);o++)if((l=t[o]).pos<e.pmin+1)for(l.del=!0,c--,a=2*l.size,s=t.length-1;s>=0;s--)t[s].dp-=a;for(o=t.length-1;o>=0&&!(c<=0);o--)(l=t[o]).pos+l.dp+l.size>e.pmax&&(l.del=!0,c--)}}}t.each((function(t){var n=t[e],i=\"x\"===n._id.charAt(0),a=n.range;0===d&&a&&a[0]>a[1]!==i&&(f=-1),p[d++]=[{datum:t,traceIndex:t.trace.index,dp:0,pos:t.pos,posref:t.posref,size:t.by*(i?T:1)/2,pmin:0,pmax:i?r.width:r.height}]})),p.sort((function(t,e){return t[0].posref-e[0].posref||f*(e[0].traceIndex-t[0].traceIndex)}));for(;!n&&u<=h;){for(u++,n=!0,o=0;o<p.length-1;){var g=p[o],v=p[o+1],y=g[g.length-1],x=v[0];if((i=y.pos+y.dp+y.size-x.pos-x.dp+x.size)>.01&&y.pmin===x.pmin&&y.pmax===x.pmax){for(s=v.length-1;s>=0;s--)v[s].dp+=i;for(g.push.apply(g,v),p.splice(o+1,1),c=0,s=g.length-1;s>=0;s--)c+=g[s].dp;for(a=c/g.length,s=g.length-1;s>=0;s--)g[s].dp-=a;n=!1}else o++}p.forEach(m)}for(o=p.length-1;o>=0;o--){var b=p[o];for(s=b.length-1;s>=0;s--){var _=b[s],w=_.datum;w.offset=_.dp,w.del=_.del}}}(zt,Pt?\"xa\":\"ya\",l),O(zt,Pt,l._invScaleX,l._invScaleY));if(e.target&&e.target.tagName){var Dt=g.getComponentMethod(\"annotations\",\"hasClickToShow\")(t,St);f(n.select(e.target),Dt?\"pointer\":\"\")}if(!e.target||a||!function(t,e,r){if(!r||r.length!==t._hoverdata.length)return!0;for(var n=r.length-1;n>=0;n--){var i=r[n],a=t._hoverdata[n];if(i.curveNumber!==a.curveNumber||String(i.pointNumber)!==String(a.pointNumber)||String(i.pointNumbers)!==String(a.pointNumbers))return!0}return!1}(t,0,At))return;At&&t.emit(\"plotly_unhover\",{event:e,points:At});t.emit(\"plotly_hover\",{event:e,points:t._hoverdata,xaxes:b,yaxes:_,xvals:F,yvals:N})}(t,e,r,a)}))},r.loneHover=function(t,e){var r=!0;Array.isArray(t)||(r=!1,t=[t]);var i=t.map((function(t){return{color:t.color||p.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,nameLength:t.nameLength,textAlign:t.textAlign,trace:t.trace||{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:t.hovertemplate||!1,eventData:t.eventData||!1,hovertemplateLabels:t.hovertemplateLabels||!1}})),a=n.select(e.container),o=e.outerContainer?n.select(e.outerContainer):a,s={hovermode:\"closest\",rotateLabels:!1,bgColor:e.bgColor||p.background,container:a,outerContainer:o},l=P(i,s,e.gd),c=0,u=0;l.sort((function(t,e){return t.y0-e.y0})).each((function(t,r){var n=t.y0-t.by/2;t.offset=n-5<c?c-n+5:0,c=n+t.by+t.offset,r===e.anchorIndex&&(u=t.offset)})).each((function(t){t.offset-=u}));var f=e.gd._fullLayout._invScaleX,h=e.gd._fullLayout._invScaleY;return O(l,s.rotateLabels,f,h),r?l:l.node()};var C=/<extra>([\\s\\S]*)<\\/extra>/;function P(t,e,r){var i=r._fullLayout,a=e.hovermode,c=e.rotateLabels,f=e.bgColor,d=e.container,m=e.outerContainer,g=e.commonLabelOpts||{},w=e.fontFamily||y.HOVERFONT,T=e.fontSize||y.HOVERFONTSIZE,k=t[0],M=k.xa,E=k.ya,C=a.charAt(0),P=k[C+\"Label\"],O=m.node().getBoundingClientRect(),z=O.top,D=O.width,R=O.height,F=void 0!==P&&k.distance<=e.hoverdistance&&(\"x\"===a||\"y\"===a);if(F){var B,N,j=!0;for(B=0;B<t.length;B++)if(j&&void 0===t[B].zLabel&&(j=!1),N=t[B].hoverinfo||t[B].trace.hoverinfo){var U=Array.isArray(N)?N:N.split(\"+\");if(-1===U.indexOf(\"all\")&&-1===U.indexOf(a)){F=!1;break}}j&&(F=!1)}var V=d.selectAll(\"g.axistext\").data(F?[0]:[]);if(V.enter().append(\"g\").classed(\"axistext\",!0),V.exit().remove(),V.each((function(){var t=n.select(this),e=o.ensureSingle(t,\"path\",\"\",(function(t){t.style({\"stroke-width\":\"1px\"})})),l=o.ensureSingle(t,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),c=g.bgcolor||p.defaultLine,f=g.bordercolor||p.contrast(c),d=p.contrast(c),m={family:g.font.family||w,size:g.font.size||T,color:g.font.color||d};e.style({fill:c,stroke:f}),l.text(P).call(h.font,m).call(u.positionText,0,0).call(u.convertToTspans,r),t.attr(\"transform\",\"\");var v,y,x=l.node().getBoundingClientRect();if(\"x\"===a){var b=\"top\"===M.side?\"-\":\"\";l.attr(\"text-anchor\",\"middle\").call(u.positionText,0,\"top\"===M.side?z-x.bottom-A-S:z-x.top+A+S),v=M._offset+(k.x0+k.x1)/2,y=E._offset+(\"top\"===M.side?0:E._length);var _=x.width/2+S;v<_?(v=_,e.attr(\"d\",\"M-\"+(_-A)+\",0L-\"+(_-2*A)+\",\"+b+A+\"H\"+(S+x.width/2)+\"v\"+b+(2*S+x.height)+\"H-\"+_+\"V\"+b+A+\"Z\")):v>i.width-_?(v=i.width-_,e.attr(\"d\",\"M\"+(_-A)+\",0L\"+_+\",\"+b+A+\"v\"+b+(2*S+x.height)+\"H-\"+_+\"V\"+b+A+\"H\"+(_-2*A)+\"Z\")):e.attr(\"d\",\"M0,0L\"+A+\",\"+b+A+\"H\"+(S+x.width/2)+\"v\"+b+(2*S+x.height)+\"H-\"+(S+x.width/2)+\"V\"+b+A+\"H-\"+A+\"Z\")}else{var L,C,I;\"right\"===E.side?(L=\"start\",C=1,I=\"\",v=M._offset+M._length):(L=\"end\",C=-1,I=\"-\",v=M._offset),y=E._offset+(k.y0+k.y1)/2,l.attr(\"text-anchor\",L),e.attr(\"d\",\"M0,0L\"+I+A+\",\"+A+\"V\"+(S+x.height/2)+\"h\"+I+(2*S+x.width)+\"V-\"+(S+x.height/2)+\"H\"+I+A+\"V-\"+A+\"Z\");var O,D=x.height/2,R=z-x.top-D,F=\"clip\"+i._uid+\"commonlabel\"+E._id;if(v<x.width+2*S+A){O=\"M-\"+(A+S)+\"-\"+D+\"h-\"+(x.width-S)+\"V\"+D+\"h\"+(x.width-S)+\"Z\";var B=x.width-v+S;u.positionText(l,B,R),\"end\"===L&&l.selectAll(\"tspan\").each((function(){var t=n.select(this),e=h.tester.append(\"text\").text(t.text()).call(h.font,m),r=e.node().getBoundingClientRect();Math.round(r.width)<Math.round(x.width)&&t.attr(\"x\",B-r.width),e.remove()}))}else u.positionText(l,C*(S+A),R),O=null;var N=i._topclips.selectAll(\"#\"+F).data(O?[0]:[]);N.enter().append(\"clipPath\").attr(\"id\",F).append(\"path\"),N.exit().remove(),N.select(\"path\").attr(\"d\",O),h.setClipUrl(l,O?F:null,r)}t.attr(\"transform\",s(v,y))})),v.isUnifiedHover(a)){if(d.selectAll(\"g.hovertext\").remove(),0===t.length)return;var q={showlegend:!0,legend:{title:{text:P,font:i.hoverlabel.font},font:i.hoverlabel.font,bgcolor:i.hoverlabel.bgcolor,bordercolor:i.hoverlabel.bordercolor,borderwidth:1,tracegroupgap:7,traceorder:i.legend?i.legend.traceorder:void 0,orientation:\"v\"}},H={};x(q,H,r._fullData);var G=H.legend;G.entries=[];for(var Y=0;Y<t.length;Y++){var W=I(t[Y],!0,a,i,P),X=W[0],Z=W[1],J=t[Y];J.name=Z,J.text=\"\"!==Z?Z+\" : \"+X:X;var 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t=n.select(this);t.append(\"rect\").call(p.fill,p.addOpacity(f,.8)),t.append(\"text\").classed(\"name\",!0),t.append(\"path\").style(\"stroke-width\",\"1px\"),t.append(\"text\").classed(\"nums\",!0).call(h.font,w,T)})),ot.exit().remove(),ot.each((function(t){var e=n.select(this).attr(\"transform\",\"\"),o=t.color;Array.isArray(o)&&(o=o[t.eventData[0].pointNumber]);var d=t.bgcolor||o,m=p.combine(p.opacity(d)?d:p.defaultLine,f),g=p.combine(p.opacity(o)?o:p.defaultLine,f),v=t.borderColor||p.contrast(m),y=I(t,F,a,i,P,e),x=y[0],b=y[1],k=e.select(\"text.nums\").call(h.font,t.fontFamily||w,t.fontSize||T,t.fontColor||v).text(x).attr(\"data-notex\",1).call(u.positionText,0,0).call(u.convertToTspans,r),M=e.select(\"text.name\"),E=0,L=0;if(b&&b!==x){M.call(h.font,t.fontFamily||w,t.fontSize||T,g).text(b).attr(\"data-notex\",1).call(u.positionText,0,0).call(u.convertToTspans,r);var C=M.node().getBoundingClientRect();E=C.width+2*S,L=C.height+2*S}else 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n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=t(\"../dragelement\"),o=t(\"./helpers\"),s=t(\"./layout_attributes\"),l=t(\"./hover\");e.exports={moduleType:\"component\",name:\"fx\",constants:t(\"./constants\"),schema:{layout:s},attributes:t(\"./attributes\"),layoutAttributes:s,supplyLayoutGlobalDefaults:t(\"./layout_global_defaults\"),supplyDefaults:t(\"./defaults\"),supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\"),getDistanceFunction:o.getDistanceFunction,getClosest:o.getClosest,inbox:o.inbox,quadrature:o.quadrature,appendArrayPointValue:o.appendArrayPointValue,castHoverOption:function(t,e,r){return i.castOption(t,e,\"hoverlabel.\"+r)},castHoverinfo:function(t,e,r){return i.castOption(t,r,\"hoverinfo\",(function(r){return i.coerceHoverinfo({hoverinfo:r},{_module:t._module},e)}))},hover:l.hover,unhover:a.unhover,loneHover:l.loneHover,loneUnhover:function(t){var 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n=t(\"@plotly/d3\"),i=t(\"../../registry\"),a=t(\"../../lib\"),o=a.strTranslate,s=t(\"../drawing\"),l=t(\"../color\"),c=t(\"../colorscale/helpers\").extractOpts,u=t(\"../../traces/scatter/subtypes\"),f=t(\"../../traces/pie/style_one\"),h=t(\"../../traces/pie/helpers\").castOption,p=t(\"./constants\");function d(t,e){return(e?\"radial\":\"horizontal\")+(t?\"\":\"reversed\")}function m(t){var e=t[0].trace,r=e.contours,n=u.hasLines(e),i=u.hasMarkers(e),a=e.visible&&e.fill&&\"none\"!==e.fill,o=!1,s=!1;if(r){var l=r.coloring;\"lines\"===l?o=!0:n=\"none\"===l||\"heatmap\"===l||r.showlines,\"constraint\"===r.type?a=\"=\"!==r._operation:\"fill\"!==l&&\"heatmap\"!==l||(s=!0)}return{showMarker:i,showLine:n,showFill:a,showGradientLine:o,showGradientFill:s,anyLine:n||o,anyFill:a||s}}function g(t,e,r){return t&&a.isArrayOrTypedArray(t)?e:t>r?r:t}e.exports=function(t,e,r){var v=e._fullLayout;r||(r=v.legend);var 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r=e.currentTarget;r.setAttribute(\"data-attr\",\"zoom\"),r.setAttribute(\"data-val\",\"reset\"),f(t,e),r.setAttribute(\"data-attr\",\"resetLastSave\"),p(t,e),x(t,\"geo\"),x(t,\"mapbox\")}},u.toggleSpikelines={name:\"toggleSpikelines\",title:function(t){return c(t,\"Toggle Spike Lines\")},icon:o.spikeline,attr:\"_cartesianSpikesEnabled\",val:\"on\",click:function(t){var e=t._fullLayout,r=e._cartesianSpikesEnabled;e._cartesianSpikesEnabled=\"on\"===r?\"off\":\"on\",n.call(\"_guiRelayout\",t,function(t){for(var e=\"on\"===t._fullLayout._cartesianSpikesEnabled,r=a.list(t,null,!0),n={},i=0;i<r.length;i++){var o=r[i];n[o._name+\".showspikes\"]=!!e||o._showSpikeInitial}return n}(t))}},u.resetViewMapbox={name:\"resetViewMapbox\",_cat:\"resetView\",title:function(t){return c(t,\"Reset view\")},attr:\"reset\",icon:o.home,click:function(t){x(t,\"mapbox\")}},u.zoomInMapbox={name:\"zoomInMapbox\",_cat:\"zoomin\",title:function(t){return c(t,\"Zoom 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n=t(\"../../lib\"),i=t(\"../color\"),a=t(\"../../plot_api/plot_template\"),o=t(\"./attributes\");e.exports=function(t,e){var r=t.modebar||{},s=a.newContainer(e,\"modebar\");function l(t,e){return n.coerce(r,s,o,t,e)}l(\"orientation\"),l(\"bgcolor\",i.addOpacity(e.paper_bgcolor,.5));var c=i.contrast(i.rgb(e.modebar.bgcolor));l(\"color\",i.addOpacity(c,.3)),l(\"activecolor\",i.addOpacity(c,.7)),l(\"uirevision\",e.uirevision),l(\"add\"),l(\"remove\")}},{\"../../lib\":799,\"../../plot_api/plot_template\":838,\"../color\":662,\"./attributes\":721}],725:[function(t,e,r){\"use strict\";e.exports={moduleType:\"component\",name:\"modebar\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),manage:t(\"./manage\")}},{\"./attributes\":721,\"./defaults\":724,\"./manage\":726}],726:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axis_ids\"),i=t(\"../../traces/scatter/subtypes\"),a=t(\"../../registry\"),o=t(\"../fx/helpers\").isUnifiedHover,s=t(\"./modebar\"),l=t(\"./buttons\"),c=t(\"./constants\").DRAW_MODES;e.exports=function(t){var e=t._fullLayout,r=t._context,u=e._modeBar;if(r.displayModeBar||r.watermark){if(!Array.isArray(r.modeBarButtonsToRemove))throw new Error([\"*modeBarButtonsToRemove* configuration options\",\"must be an array.\"].join(\" \"));if(!Array.isArray(r.modeBarButtonsToAdd))throw new Error([\"*modeBarButtonsToAdd* configuration options\",\"must be an array.\"].join(\" \"));var f,h=r.modeBarButtons;f=Array.isArray(h)&&h.length?function(t){for(var e=0;e<t.length;e++)for(var r=t[e],n=0;n<r.length;n++){var i=r[n];if(\"string\"==typeof i){if(void 0===l[i])throw new Error([\"*modeBarButtons* configuration options\",\"invalid button name\"].join(\" \"));t[e][n]=l[i]}}return t}(h):!r.displayModeBar&&r.watermark?[]:function(t){var e=t._fullLayout,r=t._fullData,s=t._context;function u(t,e){if(\"string\"==typeof e){if(e.toLowerCase()===t.toLowerCase())return!0}else{var r=e.name,n=e._cat||e.name;if(r===t||n===t.toLowerCase())return!0}return!1}var f=e.modebar.add;\"string\"==typeof f&&(f=[f]);var h=e.modebar.remove;\"string\"==typeof h&&(h=[h]);var p=s.modeBarButtonsToAdd.concat(f.filter((function(t){for(var e=0;e<s.modeBarButtonsToRemove.length;e++)if(u(t,s.modeBarButtonsToRemove[e]))return!1;return!0}))),d=s.modeBarButtonsToRemove.concat(h.filter((function(t){for(var e=0;e<s.modeBarButtonsToAdd.length;e++)if(u(t,s.modeBarButtonsToAdd[e]))return!1;return!0}))),m=e._has(\"cartesian\"),g=e._has(\"gl3d\"),v=e._has(\"geo\"),y=e._has(\"pie\"),x=e._has(\"funnelarea\"),b=e._has(\"gl2d\"),_=e._has(\"ternary\"),w=e._has(\"mapbox\"),T=e._has(\"polar\"),k=e._has(\"sankey\"),M=function(t){for(var e=n.list({_fullLayout:t},null,!0),r=0;r<e.length;r++)if(!e[r].fixedrange)return!1;return!0}(e),A=o(e.hovermode),S=[];function 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e=0;e<t.length;e++)if(!a.traceIs(t[e],\"noHover\"))return!1;return!0}(r)||A)&&(P=[]);!m&&!b||M||(C=[\"zoomIn2d\",\"zoomOut2d\",\"autoScale2d\"],\"resetViews\"!==I[0]&&(I=[\"resetScale2d\"]));g?O=[\"zoom3d\",\"pan3d\",\"orbitRotation\",\"tableRotation\"]:(m||b)&&!M||_?O=[\"zoom2d\",\"pan2d\"]:w||v?O=[\"pan2d\"]:T&&(O=[\"zoom2d\"]);(function(t){for(var e=!1,r=0;r<t.length&&!e;r++){var n=t[r];n._module&&n._module.selectPoints&&(a.traceIs(n,\"scatter-like\")?(i.hasMarkers(n)||i.hasText(n))&&(e=!0):a.traceIs(n,\"box-violin\")&&\"all\"!==n.boxpoints&&\"all\"!==n.points||(e=!0))}return e})(r)&&O.push(\"select2d\",\"lasso2d\");var z=[],D=function(t){-1===z.indexOf(t)&&-1!==P.indexOf(t)&&z.push(t)};if(Array.isArray(p)){for(var R=[],F=0;F<p.length;F++){var B=p[F];\"string\"==typeof B?(B=B.toLowerCase(),-1!==c.indexOf(B)?(e._has(\"mapbox\")||e._has(\"cartesian\"))&&O.push(B):\"togglespikelines\"===B?D(\"toggleSpikelines\"):\"togglehover\"===B?D(\"toggleHover\"):\"hovercompare\"===B?D(\"hoverCompareCartesian\"):\"hoverclosest\"===B?(D(\"hoverClosestCartesian\"),D(\"hoverClosestGeo\"),D(\"hoverClosest3d\"),D(\"hoverClosestGl2d\"),D(\"hoverClosestPie\")):\"v1hovermode\"===B&&(D(\"toggleHover\"),D(\"hoverClosestCartesian\"),D(\"hoverCompareCartesian\"),D(\"hoverClosestGeo\"),D(\"hoverClosest3d\"),D(\"hoverClosestGl2d\"),D(\"hoverClosestPie\"))):R.push(B)}p=R}return E(O),E(C.concat(I)),E(z),function(t,e){if(e.length)if(Array.isArray(e[0]))for(var r=0;r<e.length;r++)t.push(e[r]);else t.push(e);return t}(S,p)}(t),u?u.update(t,f):e._modeBar=s(t,f)}else u&&(u.destroy(),delete 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t.match(n.segmentRE).forEach((function(t){var a=e[t.charAt(0)].drawn;if(void 0!==a){var o=t.substr(1).match(n.paramRE);!o||o.length<a||r.push(i.cleanNumber(o[a]))}})),r},r.getDataToPixel=function(t,e,n,i){var a,o=t._fullLayout._size;if(e)if(\"domain\"===i)a=function(t){return e._length*(n?1-t:t)+e._offset};else{var s=r.shapePositionToRange(e);a=function(t){return e._offset+e.r2p(s(t,!0))},\"date\"===e.type&&(a=r.decodeDate(a))}else a=n?function(t){return o.t+o.h*(1-t)}:function(t){return o.l+o.w*t};return a},r.getPixelToData=function(t,e,n,i){var a,o=t._fullLayout._size;if(e)if(\"domain\"===i)a=function(t){var r=(t-e._offset)/e._length;return n?1-r:r};else{var s=r.rangeToShapePosition(e);a=function(t){return s(e.p2r(t-e._offset))}}else a=n?function(t){return 1-(t-o.t)/o.h}:function(t){return(t-o.l)/o.w};return a},r.roundPositionForSharpStrokeRendering=function(t,e){var r=1===Math.round(e%2),n=Math.round(t);return r?n+.5:n},r.makeOptionsAndPlotinfo=function(t,e){var r=t._fullLayout.shapes[e]||{},n=t._fullLayout._plots[r.xref+r.yref];return!!n?n._hadPlotinfo=!0:(n={},r.xref&&\"paper\"!==r.xref&&(n.xaxis=t._fullLayout[r.xref+\"axis\"]),r.yref&&\"paper\"!==r.yref&&(n.yaxis=t._fullLayout[r.yref+\"axis\"])),n.xsizemode=r.xsizemode,n.ysizemode=r.ysizemode,n.xanchor=r.xanchor,n.yanchor=r.yanchor,{options:r,plotinfo:n}}},{\"../../lib\":799,\"./constants\":744}],754:[function(t,e,r){\"use strict\";var n=t(\"./draw\");e.exports={moduleType:\"component\",name:\"shapes\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),supplyDrawNewShapeDefaults:t(\"./draw_newshape/defaults\"),includeBasePlot:t(\"../../plots/cartesian/include_components\")(\"shapes\"),calcAutorange:t(\"./calc_autorange\"),draw:n.draw,drawOne:n.drawOne}},{\"../../plots/cartesian/include_components\":862,\"./attributes\":742,\"./calc_autorange\":743,\"./defaults\":745,\"./draw\":746,\"./draw_newshape/defaults\":749}],755:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),i=t(\"../../plots/pad_attributes\"),a=t(\"../../lib/extend\").extendDeepAll,o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../plots/animation_attributes\"),l=t(\"../../plot_api/plot_template\").templatedArray,c=t(\"./constants\"),u=l(\"step\",{visible:{valType:\"boolean\",dflt:!0},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\"},value:{valType:\"string\"},execute:{valType:\"boolean\",dflt:!0}});e.exports=o(l(\"slider\",{visible:{valType:\"boolean\",dflt:!0},active:{valType:\"number\",min:0,dflt:0},steps:u,lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",min:-2,max:3,dflt:0},pad:a(i({editType:\"arraydraw\"}),{},{t:{dflt:20}}),xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\"},y:{valType:\"number\",min:-2,max:3,dflt:0},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},transition:{duration:{valType:\"number\",min:0,dflt:150},easing:{valType:\"enumerated\",values:s.transition.easing.values,dflt:\"cubic-in-out\"}},currentvalue:{visible:{valType:\"boolean\",dflt:!0},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},offset:{valType:\"number\",dflt:10},prefix:{valType:\"string\"},suffix:{valType:\"string\"},font:n({})},font:n({}),activebgcolor:{valType:\"color\",dflt:c.gripBgActiveColor},bgcolor:{valType:\"color\",dflt:c.railBgColor},bordercolor:{valType:\"color\",dflt:c.railBorderColor},borderwidth:{valType:\"number\",min:0,dflt:c.railBorderWidth},ticklen:{valType:\"number\",min:0,dflt:c.tickLength},tickcolor:{valType:\"color\",dflt:c.tickColor},tickwidth:{valType:\"number\",min:0,dflt:1},minorticklen:{valType:\"number\",min:0,dflt:c.minorTickLength}}),\"arraydraw\",\"from-root\")},{\"../../lib/extend\":789,\"../../plot_api/edit_types\":831,\"../../plot_api/plot_template\":838,\"../../plots/animation_attributes\":843,\"../../plots/font_attributes\":878,\"../../plots/pad_attributes\":912,\"./constants\":756}],756:[function(t,e,r){\"use 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a=Math.round(n*(r._stepCount-1)),o=r._visibleSteps[a]._index;o!==r.active&&k(t,e,r,o,!0,i)}function k(t,e,r,n,a,o){var s=r.active;r.active=n,u(t.layout,f.name,r).applyUpdate(\"active\",n);var l=r.steps[r.active];e.call(S,r,o),e.call(x,r),t.emit(\"plotly_sliderchange\",{slider:r,step:r.steps[r.active],interaction:a,previousActive:s}),l&&l.method&&a&&(e._nextMethod?(e._nextMethod.step=l,e._nextMethod.doCallback=a,e._nextMethod.doTransition=o):(e._nextMethod={step:l,doCallback:a,doTransition:o},e._nextMethodRaf=window.requestAnimationFrame((function(){var r=e._nextMethod.step;r.method&&(r.execute&&i.executeAPICommand(t,r.method,r.args),e._nextMethod=null,e._nextMethodRaf=null)}))))}function M(t,e,r){var i=r.node(),o=n.select(e);function s(){return r.data()[0]}t.on(\"mousedown\",(function(){var t=s();e.emit(\"plotly_sliderstart\",{slider:t});var l=r.select(\".\"+f.gripRectClass);n.event.stopPropagation(),n.event.preventDefault(),l.call(a.fill,t.activebgcolor);var c=L(t,n.mouse(i)[0]);T(e,r,t,c,!0),t._dragging=!0,o.on(\"mousemove\",(function(){var t=s(),a=L(t,n.mouse(i)[0]);T(e,r,t,a,!1)})),o.on(\"mouseup\",(function(){var t=s();t._dragging=!1,l.call(a.fill,t.bgcolor),o.on(\"mouseup\",null),o.on(\"mousemove\",null),e.emit(\"plotly_sliderend\",{slider:t,step:t.steps[t.active]})}))}))}function A(t,e){var r=t.selectAll(\"rect.\"+f.tickRectClass).data(e._visibleSteps),i=e._dims;r.enter().append(\"rect\").classed(f.tickRectClass,!0),r.exit().remove(),r.attr({width:e.tickwidth+\"px\",\"shape-rendering\":\"crispEdges\"}),r.each((function(t,r){var s=r%i.labelStride==0,l=n.select(this);l.attr({height:s?e.ticklen:e.minorticklen}).call(a.fill,e.tickcolor),o.setTranslate(l,E(e,r/(e._stepCount-1))-.5*e.tickwidth,(s?f.tickOffset:f.minorTickOffset)+i.currentValueTotalHeight)}))}function S(t,e,r){for(var n=t.select(\"rect.\"+f.gripRectClass),i=0,a=0;a<e._stepCount;a++)if(e._visibleSteps[a]._index===e.active){i=a;break}var o=E(e,i/(e._stepCount-1));if(!e._invokingCommand){var s=n;r&&e.transition.duration>0&&(s=s.transition().duration(e.transition.duration).ease(e.transition.easing)),s.attr(\"transform\",l(o-.5*f.gripWidth,e._dims.currentValueTotalHeight))}}function E(t,e){var r=t._dims;return r.inputAreaStart+f.stepInset+(r.inputAreaLength-2*f.stepInset)*Math.min(1,Math.max(0,e))}function L(t,e){var r=t._dims;return Math.min(1,Math.max(0,(e-f.stepInset-r.inputAreaStart)/(r.inputAreaLength-2*f.stepInset-2*r.inputAreaStart)))}function C(t,e,r){var n=r._dims,i=s.ensureSingle(t,\"rect\",f.railTouchRectClass,(function(n){n.call(M,e,t,r).style(\"pointer-events\",\"all\")}));i.attr({width:n.inputAreaLength,height:Math.max(n.inputAreaWidth,f.tickOffset+r.ticklen+n.labelHeight)}).call(a.fill,r.bgcolor).attr(\"opacity\",0),o.setTranslate(i,0,n.currentValueTotalHeight)}function P(t,e){var 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o=e.length===r.length;if(!i&&!o)return{fullReplot:!0,calc:!0};var s,l,c=T.traceFlags();c.arrays={},c.nChanges=0,c.nChangesAnim=0;var u={getValObject:function(t){var e=f.getTraceValObject(l,t);return!l._module.animatable&&e.anim&&(e.anim=!1),e},flags:c,immutable:n,transition:i,newDataRevision:a,gd:t},p={};for(s=0;s<e.length;s++)if(r[s]){if(l=r[s]._fullInput,h.hasMakesDataTransform(l)&&(l=r[s]),p[l.uid])continue;p[l.uid]=1,it(e[s]._fullInput,l,[],u)}(c.calc||c.plot)&&(c.fullReplot=!0);i&&c.nChanges&&c.nChangesAnim&&(c.anim=c.nChanges===c.nChangesAnim&&o?\"all\":\"some\");return c}(t,c,v,x,b,M);if(X(t)&&(k.layoutReplot=!0),S.calc||k.calc){t.calcdata=void 0;for(var E=Object.getOwnPropertyNames(y),C=0;C<E.length;C++){var P=E[C],I=P.substring(0,5);if(\"xaxis\"===I||\"yaxis\"===I){var O=y[P]._emptyCategories;O&&O()}}}else h.supplyDefaultsUpdateCalc(t.calcdata,v);var z=[];if(a&&(t._transitionData={},h.createTransitionData(t),z.push((function(){return 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t.dtick=e>.3?\"D2\":\"D1\"}else\"category\"===t.type||\"multicategory\"===t.type?(t.tick0=0,t.dtick=Math.ceil(Math.max(e,1))):Mt(t)?(t.tick0=0,r=1,t.dtick=ot(e,r,at)):(t.tick0=0,r=n(10),t.dtick=ot(e,r,$));if(0===t.dtick&&(t.dtick=1),!i(t.dtick)&&\"string\"!=typeof t.dtick){var f=t.dtick;throw t.dtick=1,\"ax.dtick error: \"+String(f)}},V.tickIncrement=function(t,e,r,a){var o=r?-1:1;if(i(e))return s.increment(t,o*e);var l=e.charAt(0),c=o*Number(e.substr(1));if(\"M\"===l)return s.incrementMonth(t,c,a);if(\"L\"===l)return Math.log(Math.pow(10,t)+c)/Math.LN10;if(\"D\"===l){var u=\"D2\"===e?it:nt,f=t+.01*o,h=s.roundUp(s.mod(f,1),u,r);return Math.floor(f)+Math.log(n.round(Math.pow(10,h),1))/Math.LN10}throw\"unrecognized dtick \"+String(e)},V.tickFirst=function(t,e){var r=t.r2l||Number,a=s.simpleMap(t.range,r,void 0,void 0,e),o=a[1]<a[0],l=o?Math.floor:Math.ceil,c=X(a)[0],u=t.dtick,f=r(t.tick0);if(i(u)){var 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h=s.simpleMap(t.range,t.r2l),p=(Math.abs(h[1]-h[0])-(t._lBreaks||0))/1e4;for(a=0;a<t.ticktext.length&&!(Math.abs(e-f(t.tickvals[a]))<p);a++);if(a<t.ticktext.length)return o.text=String(t.ticktext[a]),o}function d(n){if(void 0===n)return!0;if(r)return\"none\"===n;var i={first:t._tmin,last:t._tmax}[n];return\"all\"!==n&&e!==i}var m=r?\"never\":\"none\"!==t.exponentformat&&d(t.showexponent)?\"hide\":\"\";if(\"date\"===u?function(t,e,r,n){var a=t._tickround,o=r&&t.hoverformat||V.getTickFormat(t);n&&(a=i(a)?4:{y:\"m\",m:\"d\",d:\"M\",M:\"S\",S:4}[a]);var l,c=s.formatDate(e.x,o,a,t._dateFormat,t.calendar,t._extraFormat),u=c.indexOf(\"\\n\");-1!==u&&(l=c.substr(u+1),c=c.substr(0,u));n&&(\"00:00:00\"===c||\"00:00\"===c?(c=l,l=\"\"):8===c.length&&(c=c.replace(/:00$/,\"\")));if(l)if(r)\"d\"===a?c+=\", \"+l:c=l+(c?\", \"+c:\"\");else if(t._inCalcTicks&&t._prevDateHead===l){var f=St(t),h=t._realSide||t.side;(!f&&\"top\"===h||f&&\"bottom\"===h)&&(c+=\"<br> \")}else t._prevDateHead=l,c+=\"<br>\"+l;e.text=c}(t,o,r,c):\"log\"===u?function(t,e,r,n,a){var o=t.dtick,l=e.x,c=t.tickformat,u=\"string\"==typeof o&&o.charAt(0);\"never\"===a&&(a=\"\");n&&\"L\"!==u&&(o=\"L3\",u=\"L\");if(c||\"L\"===u)e.text=ht(Math.pow(10,l),t,a,n);else if(i(o)||\"D\"===u&&s.mod(l+.01,1)<.1){var f=Math.round(l),h=Math.abs(f),p=t.exponentformat;\"power\"===p||ut(p)&&ft(f)?(e.text=0===f?1:1===f?\"10\":\"10<sup>\"+(f>1?\"\":P)+h+\"</sup>\",e.fontSize*=1.25):(\"e\"===p||\"E\"===p)&&h>2?e.text=\"1\"+p+(f>0?\"+\":P)+h:(e.text=ht(Math.pow(10,l),t,\"\",\"fakehover\"),\"D1\"===o&&\"y\"===t._id.charAt(0)&&(e.dy-=e.fontSize/6))}else{if(\"D\"!==u)throw\"unrecognized dtick \"+String(o);e.text=String(Math.round(Math.pow(10,s.mod(l,1)))),e.fontSize*=.75}if(\"D1\"===t.dtick){var 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a=r[i],o=a._id,s=rt.xLinks[o]||rt.yLinks[o],l=n[0]||U[s]||X[s];l&&(e?(e[a._name+\".range[0]\"]=e[l._name+\".range[0]\"],e[a._name+\".range[1]\"]=e[l._name+\".range[1]\"]):a.range=l.range.slice())}}function Vt(){var e,r=[];function n(t){for(e=0;e<t.length;e++)t[e].fixedrange||r.push(t[e]._id)}for(ot&&(n(Z),n(et.xaxes),n(rt.xaxes)),st&&(n(J),n(et.yaxes),n(rt.yaxes)),ft={},e=0;e<r.length;e++){var i=r[e],a=T(t,i);p.drawOne(t,a,{skipTitle:!0}),ft[a._name+\".range[0]\"]=a.range[0],ft[a._name+\".range[1]\"]=a.range[1]}p.redrawComponents(t,r)}function qt(){if(!t._transitioningWithDuration){var e=t._context.doubleClick,r=[];nt&&(r=r.concat(Z)),it&&(r=r.concat(J)),rt.xaxes&&(r=r.concat(rt.xaxes)),rt.yaxes&&(r=r.concat(rt.yaxes));var n,i,a,s={};if(\"reset+autosize\"===e)for(e=\"autosize\",i=0;i<r.length;i++)if((n=r[i])._rangeInitial&&(n.range[0]!==n._rangeInitial[0]||n.range[1]!==n._rangeInitial[1])||!n._rangeInitial&&!n.autorange){e=\"reset\";break}if(\"autosize\"===e)for(i=0;i<r.length;i++)(n=r[i]).fixedrange||(s[n._name+\".autorange\"]=!0);else if(\"reset\"===e)for((nt||et.isSubplotConstrained)&&(r=r.concat(et.xaxes)),it&&!et.isSubplotConstrained&&(r=r.concat(et.yaxes)),et.isSubplotConstrained&&(nt?it||(r=r.concat(J)):r=r.concat(Z)),i=0;i<r.length;i++)(n=r[i]).fixedrange||(n._rangeInitial?(a=n._rangeInitial,s[n._name+\".range[0]\"]=a[0],s[n._name+\".range[1]\"]=a[1]):s[n._name+\".autorange\"]=!0);t.emit(\"plotly_doubleclick\",null),o.call(\"_guiRelayout\",t,s)}}function Ht(){Gt([0,0,$,tt]),s.syncOrAsync([w.previousPromises,function(){t._fullLayout._replotting=!1,o.call(\"_guiRelayout\",t,ft)}],t)}function Gt(e){var r,n,i,a,l=t._fullLayout,c=l._plots,u=l._subplots.cartesian;if(ct&&o.subplotsRegistry.splom.drag(t),lt)for(r=0;r<u.length;r++)if(i=(n=c[u[r]]).xaxis,a=n.yaxis,n._scene){var h=s.simpleMap(i.range,i.r2l),p=s.simpleMap(a.range,a.r2l);n._scene.update({range:[h[0],p[0],h[1],p[1]]})}if((ct||lt)&&(b(t),_(t)),ut){var m=e[2]/P._length,v=e[3]/I._length;for(r=0;r<u.length;r++){i=(n=c[u[r]]).xaxis,a=n.yaxis;var y,x,w,T,k=(ot||rt.isSubplotConstrained)&&!i.fixedrange&&U[i._id],M=(st||rt.isSubplotConstrained)&&!a.fixedrange&&X[a._id];if(k?(y=m,w=g||rt.isSubplotConstrained?e[0]:Xt(i,y)):rt.xaHash[i._id]?(y=m,w=e[0]*i._length/P._length):rt.yaHash[i._id]?(y=v,w=\"ns\"===it?-e[1]*i._length/I._length:Xt(i,y,{n:\"top\",s:\"bottom\"}[it])):w=Wt(i,y=Yt(i,m,v)),M?(x=v,T=d||rt.isSubplotConstrained?e[1]:Xt(a,x)):rt.yaHash[a._id]?(x=v,T=e[1]*a._length/I._length):rt.xaHash[a._id]?(x=m,T=\"ew\"===nt?-e[0]*a._length/P._length:Xt(a,x,{e:\"right\",w:\"left\"}[nt])):T=Wt(a,x=Yt(a,m,v)),y||x){y||(y=1),x||(x=1);var A=i._offset-w/y,S=a._offset-T/x;n.clipRect.call(f.setTranslate,w,T).call(f.setScale,y,x),n.plot.call(f.setTranslate,A,S).call(f.setScale,1/y,1/x),y===n.xScaleFactor&&x===n.yScaleFactor||(f.setPointGroupScale(n.zoomScalePts,y,x),f.setTextPointsScale(n.zoomScaleTxt,y,x)),f.hideOutsideRangePoints(n.clipOnAxisFalseTraces,n),n.xScaleFactor=y,n.yScaleFactor=x}}}}function Yt(t,e,r){return t.fixedrange?0:ot&&et.xaHash[t._id]?e:st&&(et.isSubplotConstrained?et.xaHash:et.yaHash)[t._id]?r:0}function Wt(t,e){return e?(t.range=t._r.slice(),S(t,e),Xt(t,e)):0}function Xt(t,e,r){return t._length*(1-e)*x[r||t.constraintoward||\"middle\"]}return d.length*g.length!=1&&Y(xt,(function(e){if(t._context._scrollZoom.cartesian||t._fullLayout._enablescrollzoom){if(Pt(),t._transitioningWithDuration)return e.preventDefault(),void e.stopPropagation();vt(),clearTimeout(Ft);var r=-e.deltaY;if(isFinite(r)||(r=e.wheelDelta/10),isFinite(r)){var 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c&&(Z.addPt([it,at]),Q=Z.filtered);i.selectionDefs&&i.selectionDefs.length?(K=function(t,e,r){if(r)return n.difference({regions:t,inverted:!1},{regions:[e],inverted:!1}).regions;return n.union({regions:t,inverted:!1},{regions:[e],inverted:!1}).regions}(i.mergedPolygons,Q,ut),Q.subtract=ut,J=R(i.selectionDefs.concat([Q]))):(K=[Q],J=S(Q)),m(q(K,x),ft,i),w&&b.throttle(mt,k.SELECTDELAY,(function(){var t;gt=[];var e,r=[];for($=0;$<vt.length;$++)if(e=(tt=vt[$])._module.selectPoints(tt,J),r.push(e),t=V(e,tt),gt.length)for(var n=0;n<t.length;n++)gt.push(t[n]);else gt=t;U(L,vt,et={points:gt}),pt(et,Q,Z),i.gd.emit(\"plotly_selecting\",et)}))},i.clickFn=function(t,e){if(dt.remove(),L._fullLayout._activeShapeIndex>=0)L._fullLayout._deactivateShape(L);else if(!_){var r=z.clickmode;b.done(mt).then((function(){if(b.clear(mt),2===t){for(ft.remove(),$=0;$<vt.length;$++)(tt=vt[$])._module.selectPoints(tt,!1);U(L,vt),B(i),L.emit(\"plotly_deselect\",null)}else 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e=this.scene,r=e.fullLayout._subplots.gl2d;return 0!==n.findSubplotsWithAxis(r,t).indexOf(e.id)},o.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},o.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},o.getLabelPad=function(t,e){var r=e.title.font.size,n=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?r*(1.5+(n?1:0))-10:r*(1.5+(n?.5:0))-10:\"yaxis\"===t?\"right\"===e.side?10+r*(1.5+(n?1:.5)):10+r*(1.5+(n?.5:0)):void 0},o.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},o.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},e.exports=function(t){return new a(t)}},{\"../../lib/str2rgbarray\":823,\"../cartesian/axes\":849}],890:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"./scene2d\"),a=t(\"../layout_attributes\"),o=t(\"../../constants/xmlns_namespaces\"),s=t(\"../cartesian/constants\"),l=t(\"../cartesian\"),c=t(\"../../components/fx/layout_attributes\"),u=t(\"../get_data\").getSubplotData;r.name=\"gl2d\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex=s.idRegex,r.attrRegex=s.attrRegex,r.attributes=t(\"../cartesian/attributes\"),r.supplyLayoutDefaults=function(t,e,r){e._has(\"cartesian\")||l.supplyLayoutDefaults(t,e,r)},r.layoutAttrOverrides=n(l.layoutAttributes,\"plot\",\"from-root\"),r.baseLayoutAttrOverrides=n({plot_bgcolor:a.plot_bgcolor,hoverlabel:c.hoverlabel},\"plot\",\"nested\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,a=0;a<n.length;a++){var o=n[a],s=e._plots[o],l=u(r,\"gl2d\",o),c=s._scene2d;void 0===c&&(c=new i({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=c),c.plot(l,t.calcdata,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl2d||[],a=0;a<i.length;a++){var o=i[a],s=n._plots[o];if(s._scene2d){var c=u(t,\"gl2d\",o);0===c.length&&(s._scene2d.destroy(),delete n._plots[o])}}l.clean.apply(this,arguments)},r.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var i=e._plots[r[n]]._scene2d,a=i.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":a,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),i.destroy()}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){e._plots[r[n]]._scene2d.updateFx(e.dragmode)}}},{\"../../components/fx/layout_attributes\":703,\"../../constants/xmlns_namespaces\":776,\"../../plot_api/edit_types\":831,\"../cartesian\":863,\"../cartesian/attributes\":847,\"../cartesian/constants\":856,\"../get_data\":887,\"../layout_attributes\":904,\"./scene2d\":891}],891:[function(t,e,r){\"use strict\";var n,i,a=t(\"../../registry\"),o=t(\"../../plots/cartesian/axes\"),s=t(\"../../components/fx\"),l=t(\"gl-plot2d\"),c=t(\"gl-spikes2d\"),u=t(\"gl-select-box\"),f=t(\"webgl-context\"),h=t(\"./convert\"),p=t(\"./camera\"),d=t(\"../../lib/show_no_webgl_msg\"),m=t(\"../cartesian/constraints\"),g=m.enforce,v=m.clean,y=t(\"../cartesian/autorange\").doAutoRange,x=t(\"../../components/dragelement/helpers\"),b=x.drawMode,_=x.selectMode,w=[\"xaxis\",\"yaxis\"],T=t(\"../cartesian/constants\").SUBPLOT_PATTERN;function k(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=h(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=c(this.glplot),this.selectBox=u(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}e.exports=k;var M=k.prototype;M.makeFramework=function(){if(this.staticPlot){if(!(i||(n=document.createElement(\"canvas\"),i=f({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=n,this.gl=i}else{var t=this.container.querySelector(\".gl-canvas-focus\"),e=f({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r);var a=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\";var o=this.mouseContainer=document.createElement(\"div\");o.style.position=\"absolute\",o.style[\"pointer-events\"]=\"auto\",this.pickCanvas=this.container.querySelector(\".gl-canvas-pick\");var s=this.container;s.appendChild(a),s.appendChild(o);var l=this;o.addEventListener(\"mouseout\",(function(){l.isMouseOver=!1,l.unhover()})),o.addEventListener(\"mouseover\",(function(){l.isMouseOver=!0}))},M.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a);for(var o=0,s=i-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var c=0;c<4;++c){var u=a[4*(r*o+l)+c];a[4*(r*o+l)+c]=a[4*(r*s+l)+c],a[4*(r*s+l)+c]=u}var f=document.createElement(\"canvas\");f.width=r,f.height=i;var h,p=f.getContext(\"2d\"),d=p.createImageData(r,i);switch(d.data.set(a),p.putImageData(d,0,0),t){case\"jpeg\":h=f.toDataURL(\"image/jpeg\");break;case\"webp\":h=f.toDataURL(\"image/webp\");break;default:h=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(n),h},M.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},M.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+\"\";return t},M.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(T),r=\"xaxis\"+e[1],n=\"yaxis\"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},M.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,i={},o=i[e._name+\".range\"]=e.range.slice(),s=i[r._name+\".range\"]=r.range.slice();i[e._name+\".autorange\"]=e.autorange,i[r._name+\".autorange\"]=r.autorange,a.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,i);var l=n[e._name];l.range=o,l.autorange=e.autorange;var c=n[r._name];c.range=s,c.autorange=r.autorange,i.lastInputTime=this.camera.lastInputTime,t.emit(\"plotly_relayout\",i)},M.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},M.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&a.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},M.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map((function(e){t[e].dispose(),delete t[e]})),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null}},M.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var s={_fullLayout:{_axisConstraintGroups:r._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis,_size:r._size}};v(s,this.xaxis),v(s,this.yaxis);var l,c,u=r._size,f=this.xaxis.domain,h=this.yaxis.domain;for(o.viewBox=[u.l+f[0]*u.w,u.b+h[0]*u.h,i-u.r-(1-f[1])*u.w,a-u.t-(1-h[1])*u.h],this.mouseContainer.style.width=u.w*(f[1]-f[0])+\"px\",this.mouseContainer.style.height=u.h*(h[1]-h[0])+\"px\",this.mouseContainer.height=u.h*(h[1]-h[0]),this.mouseContainer.style.left=u.l+f[0]*u.w+\"px\",this.mouseContainer.style.top=u.t+(1-h[1])*u.h+\"px\",c=0;c<2;++c)(l=this[w[c]])._length=o.viewBox[c+2]-o.viewBox[c],y(this.graphDiv,l),l.setScale();g(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},M.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,i=t.r2l,a=e.r2l;return[i(r[0]),a(n[0]),i(r[1]),a(n[1])]},M.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,i=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[i(t[1]),i(t[3])]},M.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if((i=t[n]).uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r];var l=e[r],c=this.traces[i.uid];c?c.update(i,l):(c=i._module.plot(this,i,l),this.traces[i.uid]=c)}this.glplot.objects.sort((function(t,e){return t._trace.index-e._trace.index}))},M.updateFx=function(t){_(t)||b(t)?(this.pickCanvas.style[\"pointer-events\"]=\"none\",this.mouseContainer.style[\"pointer-events\"]=\"none\"):(this.pickCanvas.style[\"pointer-events\"]=\"auto\",this.mouseContainer.style[\"pointer-events\"]=\"auto\"),this.mouseContainer.style.cursor=\"pan\"===t?\"move\":\"zoom\"===t?\"crosshair\":null},M.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=t.pointIndex,a=0;a<this.fullData.length;a++)this.fullData[a].uid===n&&(r=this.fullData[a]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:i,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,i),this.graphDiv.emit(e,{points:[o]})},M.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode){this.selectBox.enabled=!0;for(var c=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],u=0;u<2;u++)e.boxStart[u]===e.boxEnd[u]&&(c[u]=t.dataBox[u],c[u+2]=t.dataBox[u+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var f=i._size,h=this.xaxis.domain,p=this.yaxis.domain,d=(a=t.pick(o/t.pixelRatio+f.l+h[0]*f.w,l/t.pixelRatio-(f.t+(1-p[1])*f.h)))&&a.object._trace.handlePick(a);if(d&&n&&this.emitPointAction(d,\"plotly_click\"),a&&\"skip\"!==a.object._trace.hoverinfo&&i.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var m=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),m.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(a.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(a.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,\"plotly_hover\");var g=this.fullData[m.trace.index]||{},v=m.pointIndex,y=s.castHoverinfo(g,i,v);if(y&&\"all\"!==y){var x=y.split(\"+\");-1===x.indexOf(\"x\")&&(m.traceCoord[0]=void 0),-1===x.indexOf(\"y\")&&(m.traceCoord[1]=void 0),-1===x.indexOf(\"z\")&&(m.traceCoord[2]=void 0),-1===x.indexOf(\"text\")&&(m.textLabel=void 0),-1===x.indexOf(\"name\")&&(m.name=void 0)}s.loneHover({x:m.screenCoord[0],y:m.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",m.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",m.traceCoord[1]),zLabel:m.traceCoord[2],text:m.textLabel,name:m.name,color:s.castHoverOption(g,v,\"bgcolor\")||m.color,borderColor:s.castHoverOption(g,v,\"bordercolor\"),fontFamily:s.castHoverOption(g,v,\"font.family\"),fontSize:s.castHoverOption(g,v,\"font.size\"),fontColor:s.castHoverOption(g,v,\"font.color\"),nameLength:s.castHoverOption(g,v,\"namelength\"),textAlign:s.castHoverOption(g,v,\"align\")},{container:this.svgContainer,gd:this.graphDiv})}}a||this.unhover(),t.draw()}},M.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),s.loneUnhover(this.svgContainer))},M.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../components/dragelement/helpers\":680,\"../../components/fx\":702,\"../../lib/show_no_webgl_msg\":821,\"../../plots/cartesian/axes\":849,\"../../registry\":927,\"../cartesian/autorange\":848,\"../cartesian/constants\":856,\"../cartesian/constraints\":857,\"./camera\":888,\"./convert\":889,\"gl-plot2d\":318,\"gl-select-box\":333,\"gl-spikes2d\":342,\"webgl-context\":625}],892:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"../../components/fx/layout_attributes\"),a=t(\"./scene\"),o=t(\"../get_data\").getSubplotData,s=t(\"../../lib\"),l=t(\"../../constants/xmlns_namespaces\");r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=r.attrRegex=s.counterRegex(\"scene\"),r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.baseLayoutAttrOverrides=n({hoverlabel:i.hoverlabel},\"plot\",\"nested\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl3d,i=0;i<n.length;i++){var s=n[i],l=o(r,\"gl3d\",s),c=e[s],u=c.camera,f=c._scene;f||(f=new a({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:u},e),c._scene=f),f.viewInitial||(f.viewInitial={up:{x:u.up.x,y:u.up.y,z:u.up.z},eye:{x:u.eye.x,y:u.eye.y,z:u.eye.z},center:{x:u.center.x,y:u.center.y,z:u.center.z}}),f.plot(l,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl3d||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=e._size,i=0;i<r.length;i++){var a=e[r[i]],o=a.domain,s=a._scene,c=s.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=0;n<r.length;n++){e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}}},{\"../../components/fx/layout_attributes\":703,\"../../constants/xmlns_namespaces\":776,\"../../lib\":799,\"../../plot_api/edit_types\":831,\"../get_data\":887,\"./layout/attributes\":893,\"./layout/defaults\":897,\"./layout/layout_attributes\":898,\"./scene\":902}],893:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}},{}],894:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color\"),i=t(\"../../cartesian/layout_attributes\"),a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../plot_api/edit_types\").overrideAll;e.exports=o({visible:i.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:{text:i.title.text,font:i.title.font},type:a({},i.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autotypenumbers:i.autotypenumbers,autorange:i.autorange,rangemode:i.rangemode,range:a({},i.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:i.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,minexponent:i.minexponent,separatethousands:i.separatethousands,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth,_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},\"plot\",\"from-root\")},{\"../../../components/color\":662,\"../../../lib/extend\":789,\"../../../plot_api/edit_types\":831,\"../../cartesian/layout_attributes\":864}],895:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"../../../plot_api/plot_template\"),o=t(\"./axis_attributes\"),s=t(\"../../cartesian/type_defaults\"),l=t(\"../../cartesian/axis_defaults\"),c=[\"xaxis\",\"yaxis\",\"zaxis\"];e.exports=function(t,e,r){var u,f;function h(t,e){return i.coerce(u,f,o,t,e)}for(var p=0;p<c.length;p++){var d=c[p];u=t[d]||{},(f=a.newContainer(e,d))._id=d[0]+r.scene,f._name=d,s(u,f,h,r),l(u,f,h,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noTickson:!0,noTicklabelmode:!0,noTicklabelposition:!0,noTicklabeloverflow:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),h(\"gridcolor\",n(f.color,r.bgColor,13600/187).toRgbString()),h(\"title.text\",d[0]),f.setScale=i.noop,h(\"showspikes\")&&(h(\"spikesides\"),h(\"spikethickness\"),h(\"spikecolor\",f.color)),h(\"showaxeslabels\"),h(\"showbackground\")&&h(\"backgroundcolor\")}}},{\"../../../lib\":799,\"../../../plot_api/plot_template\":838,\"../../cartesian/axis_defaults\":851,\"../../cartesian/type_defaults\":875,\"./axis_attributes\":894,tinycolor2:594}],896:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=0;r<3;++r){var o=e[a[r]];o.visible?(this.labels[r]=t._meta?i.templateString(o.title.text,t._meta):o.title.text,\"font\"in o.title&&(o.title.font.color&&(this.labelColor[r]=n(o.title.font.color)),o.title.font.family&&(this.labelFont[r]=o.title.font.family),o.title.font.size&&(this.labelSize[r]=o.title.font.size)),\"showline\"in o&&(this.lineEnable[r]=o.showline),\"linecolor\"in o&&(this.lineColor[r]=n(o.linecolor)),\"linewidth\"in o&&(this.lineWidth[r]=o.linewidth),\"showgrid\"in o&&(this.gridEnable[r]=o.showgrid),\"gridcolor\"in o&&(this.gridColor[r]=n(o.gridcolor)),\"gridwidth\"in o&&(this.gridWidth[r]=o.gridwidth),\"log\"===o.type?this.zeroEnable[r]=!1:\"zeroline\"in o&&(this.zeroEnable[r]=o.zeroline),\"zerolinecolor\"in o&&(this.zeroLineColor[r]=n(o.zerolinecolor)),\"zerolinewidth\"in o&&(this.zeroLineWidth[r]=o.zerolinewidth),\"ticks\"in o&&o.ticks?this.lineTickEnable[r]=!0:this.lineTickEnable[r]=!1,\"ticklen\"in o&&(this.lineTickLength[r]=this._defaultLineTickLength[r]=o.ticklen),\"tickcolor\"in o&&(this.lineTickColor[r]=n(o.tickcolor)),\"tickwidth\"in o&&(this.lineTickWidth[r]=o.tickwidth),\"tickangle\"in o&&(this.tickAngle[r]=\"auto\"===o.tickangle?-3600:Math.PI*-o.tickangle/180),\"showticklabels\"in o&&(this.tickEnable[r]=o.showticklabels),\"tickfont\"in o&&(o.tickfont.color&&(this.tickColor[r]=n(o.tickfont.color)),o.tickfont.family&&(this.tickFont[r]=o.tickfont.family),o.tickfont.size&&(this.tickSize[r]=o.tickfont.size)),\"mirror\"in o?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(o.mirror)?(this.lineTickMirror[r]=!0,this.lineMirror[r]=!0):!0===o.mirror?(this.lineTickMirror[r]=!1,this.lineMirror[r]=!0):(this.lineTickMirror[r]=!1,this.lineMirror[r]=!1):this.lineMirror[r]=!1,\"showbackground\"in o&&!1!==o.showbackground?(this.backgroundEnable[r]=!0,this.backgroundColor[r]=n(o.backgroundcolor)):this.backgroundEnable[r]=!1):(this.tickEnable[r]=!1,this.labelEnable[r]=!1,this.lineEnable[r]=!1,this.lineTickEnable[r]=!1,this.gridEnable[r]=!1,this.zeroEnable[r]=!1,this.backgroundEnable[r]=!1)}},e.exports=function(t,e){var r=new o;return r.merge(t,e),r}},{\"../../../lib\":799,\"../../../lib/str2rgbarray\":823}],897:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"../../../components/color\"),a=t(\"../../../registry\"),o=t(\"../../subplot_defaults\"),s=t(\"./axis_defaults\"),l=t(\"./layout_attributes\"),c=t(\"../../get_data\").getSubplotData;function u(t,e,r,n){for(var o=r(\"bgcolor\"),l=i.combine(o,n.paper_bgcolor),u=[\"up\",\"center\",\"eye\"],f=0;f<u.length;f++)r(\"camera.\"+u[f]+\".x\"),r(\"camera.\"+u[f]+\".y\"),r(\"camera.\"+u[f]+\".z\");r(\"camera.projection.type\");var h=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),p=r(\"aspectmode\",h?\"manual\":\"auto\");h||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===p&&(e.aspectmode=\"auto\"),t.aspectmode=e.aspectmode);var d=c(n.fullData,\"gl3d\",n.id);s(t,e,{font:n.font,scene:n.id,data:d,bgColor:l,calendar:n.calendar,autotypenumbersDflt:n.autotypenumbersDflt,fullLayout:n.fullLayout}),a.getComponentMethod(\"annotations3d\",\"handleDefaults\")(t,e,n);var m=n.getDfltFromLayout(\"dragmode\");if(!1!==m&&!m)if(m=\"orbit\",t.camera&&t.camera.up){var g=t.camera.up.x,v=t.camera.up.y,y=t.camera.up.z;0!==y&&(g&&v&&y?y/Math.sqrt(g*g+v*v+y*y)>.999&&(m=\"turntable\"):m=\"turntable\")}else m=\"turntable\";r(\"dragmode\",m),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}e.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:\"gl3d\",attributes:l,handleDefaults:u,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},{\"../../../components/color\":662,\"../../../lib\":799,\"../../../registry\":927,\"../../get_data\":887,\"../../subplot_defaults\":921,\"./axis_defaults\":895,\"./layout_attributes\":898}],898:[function(t,e,r){\"use strict\";var n=t(\"./axis_attributes\"),i=t(\"../../domain\").attributes,a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../lib\").counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}e.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},{\"../../../lib\":799,\"../../../lib/extend\":789,\"../../domain\":877,\"./axis_attributes\":894}],899:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},e.exports=function(t){var e=new a;return e.merge(t),e}},{\"../../../lib/str2rgbarray\":823}],900:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],c=0;c<3;++c){var u=s[a[c]];if(u._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(u._length)===1/0||isNaN(u._length))l[c]=[];else{u._input_range=u.range.slice(),u.range[0]=r[c].lo/t.dataScale[c],u.range[1]=r[c].hi/t.dataScale[c],u._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),u.range[0]===u.range[1]&&(u.range[0]-=1,u.range[1]+=1);var f=u.tickmode;if(\"auto\"===u.tickmode){u.tickmode=\"linear\";var h=u.nticks||i.constrain(u._length/40,4,9);n.autoTicks(u,Math.abs(u.range[1]-u.range[0])/h)}for(var p=n.calcTicks(u,{msUTC:!0}),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[c],\"date\"===u.type&&(p[d].text=p[d].text.replace(/\\<br\\>/g,\" \"));l[c]=p,u.tickmode=f}}e.ticks=l;for(c=0;c<3;++c){o[c]=.5*(t.glplot.bounds[0][c]+t.glplot.bounds[1][c]);for(d=0;d<2;++d)e.bounds[d][c]=t.glplot.bounds[d][c]}t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}(l)};var n=t(\"../../cartesian/axes\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"],o=[0,0,0]},{\"../../../lib\":799,\"../../cartesian/axes\":849}],901:[function(t,e,r){\"use strict\";function n(t,e){var r,n,i=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)i[n]+=t[4*r+n]*e[r];return i}e.exports=function(t,e){return n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])))}},{}],902:[function(t,e,r){\"use strict\";var n,i,a=t(\"gl-plot3d\"),o=a.createCamera,s=a.createScene,l=t(\"webgl-context\"),c=t(\"has-passive-events\"),u=t(\"../../registry\"),f=t(\"../../lib\"),h=f.preserveDrawingBuffer(),p=t(\"../../plots/cartesian/axes\"),d=t(\"../../components/fx\"),m=t(\"../../lib/str2rgbarray\"),g=t(\"../../lib/show_no_webgl_msg\"),v=t(\"./project\"),y=t(\"./layout/convert\"),x=t(\"./layout/spikes\"),b=t(\"./layout/tick_marks\");function _(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\",r.appendChild(i),this.svgContainer=i,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=y(e,e[this.id]),this.spikeOptions=x(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=u.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=u.getComponentMethod(\"annotations3d\",\"draw\"),this.initializeGLPlot()}var w=_.prototype;w.prepareOptions=function(){var t={canvas:this.canvas,gl:this.gl,glOptions:{preserveDrawingBuffer:h,premultipliedAlpha:!0,antialias:!0},container:this.container,axes:this.axesOptions,spikes:this.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:this.camera,pixelRatio:this.pixelRatio};if(this.staticMode){if(!(i||(n=document.createElement(\"canvas\"),i=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");t.gl=i,t.canvas=n}return t};var T=!0;w.tryCreatePlot=function(){var t=this.prepareOptions(),e=!0;try{this.glplot=s(t)}catch(r){if(this.staticMode||!T||h)e=!1;else{f.warn([\"webgl setup failed possibly due to\",\"false preserveDrawingBuffer config.\",\"The mobile/tablet device may not be detected by is-mobile module.\",\"Enabling preserveDrawingBuffer in second attempt to create webgl scene...\"].join(\" \"));try{h=t.glOptions.preserveDrawingBuffer=!0,this.glplot=s(t)}catch(r){h=t.glOptions.preserveDrawingBuffer=!1,e=!1}}}return T=!1,e},w.initializeGLCamera=function(){var t=this.fullSceneLayout.camera,e=\"orthographic\"===t.projection.type;this.camera=o(this.container,{center:[t.center.x,t.center.y,t.center.z],eye:[t.eye.x,t.eye.y,t.eye.z],up:[t.up.x,t.up.y,t.up.z],_ortho:e,zoomMin:.01,zoomMax:100,mode:\"orbit\"})},w.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return g(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+\".camera\"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+\".aspectratio\"]=t.glplot.getAspectratio(),\"manual\"!==r[t.id].aspectmode&&(t.fullSceneLayout.aspectmode=r[t.id].aspectmode=e[t.id+\".aspectmode\"]=\"manual\")),e},i=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit(\"plotly_relayout\",e)}};return t.glplot.canvas&&(t.glplot.canvas.addEventListener(\"mouseup\",(function(){i(t)})),t.glplot.canvas.addEventListener(\"wheel\",(function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,a=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*a.x,y:n*a.y,z:n*a.z})}i(t)}}),!!c&&{passive:!1}),t.glplot.canvas.addEventListener(\"mousemove\",(function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit(\"plotly_relayouting\",e)}})),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",(function(r){e&&e.emit&&e.emit(\"plotly_webglcontextlost\",{event:r,layer:t.id})}),!1)),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},w.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,i=e.container.getBoundingClientRect();r._fullLayout._calcInverseTransform(r);var a=r._fullLayout._invScaleX,o=r._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),b(e),e.glplot.axes.update(e.axesOptions);for(var c,u=Object.keys(e.traces),h=null,m=e.glplot.selection,g=0;g<u.length;++g)\"skip\"!==(t=e.traces[u[g]]).data.hoverinfo&&t.handlePick(m)&&(h=t),t.setContourLevels&&t.setContourLevels();function y(t,r,n){var i=e.fullSceneLayout[t+\"axis\"];return\"log\"!==i.type&&(r=i.d2l(r)),p.hoverLabelText(i,r,n)}if(null!==h){var x=v(e.glplot.cameraParams,m.dataCoordinate);t=h.data;var _,w=r._fullData[t.index],T=m.index,k={xLabel:y(\"x\",m.traceCoordinate[0],t.xhoverformat),yLabel:y(\"y\",m.traceCoordinate[1],t.yhoverformat),zLabel:y(\"z\",m.traceCoordinate[2],t.zhoverformat)},M=d.castHoverinfo(w,e.fullLayout,T),A=(M||\"\").split(\"+\"),S=M&&\"all\"===M;w.hovertemplate||S||(-1===A.indexOf(\"x\")&&(k.xLabel=void 0),-1===A.indexOf(\"y\")&&(k.yLabel=void 0),-1===A.indexOf(\"z\")&&(k.zLabel=void 0),-1===A.indexOf(\"text\")&&(m.textLabel=void 0),-1===A.indexOf(\"name\")&&(h.name=void 0));var E=[];\"cone\"===t.type||\"streamtube\"===t.type?(k.uLabel=y(\"x\",m.traceCoordinate[3],t.uhoverformat),(S||-1!==A.indexOf(\"u\"))&&E.push(\"u: \"+k.uLabel),k.vLabel=y(\"y\",m.traceCoordinate[4],t.vhoverformat),(S||-1!==A.indexOf(\"v\"))&&E.push(\"v: \"+k.vLabel),k.wLabel=y(\"z\",m.traceCoordinate[5],t.whoverformat),(S||-1!==A.indexOf(\"w\"))&&E.push(\"w: \"+k.wLabel),k.normLabel=m.traceCoordinate[6].toPrecision(3),(S||-1!==A.indexOf(\"norm\"))&&E.push(\"norm: \"+k.normLabel),\"streamtube\"===t.type&&(k.divergenceLabel=m.traceCoordinate[7].toPrecision(3),(S||-1!==A.indexOf(\"divergence\"))&&E.push(\"divergence: \"+k.divergenceLabel)),m.textLabel&&E.push(m.textLabel),_=E.join(\"<br>\")):\"isosurface\"===t.type||\"volume\"===t.type?(k.valueLabel=p.hoverLabelText(e._mockAxis,e._mockAxis.d2l(m.traceCoordinate[3]),t.valuehoverformat),E.push(\"value: \"+k.valueLabel),m.textLabel&&E.push(m.textLabel),_=E.join(\"<br>\")):_=m.textLabel;var L={x:m.traceCoordinate[0],y:m.traceCoordinate[1],z:m.traceCoordinate[2],data:w._input,fullData:w,curveNumber:w.index,pointNumber:T};d.appendArrayPointValue(L,w,T),t._module.eventData&&(L=w._module.eventData(L,m,w,{},T));var C={points:[L]};e.fullSceneLayout.hovermode&&d.loneHover({trace:w,x:(.5+.5*x[0]/x[3])*s,y:(.5-.5*x[1]/x[3])*l,xLabel:k.xLabel,yLabel:k.yLabel,zLabel:k.zLabel,text:_,name:h.name,color:d.castHoverOption(w,T,\"bgcolor\")||h.color,borderColor:d.castHoverOption(w,T,\"bordercolor\"),fontFamily:d.castHoverOption(w,T,\"font.family\"),fontSize:d.castHoverOption(w,T,\"font.size\"),fontColor:d.castHoverOption(w,T,\"font.color\"),nameLength:d.castHoverOption(w,T,\"namelength\"),textAlign:d.castHoverOption(w,T,\"align\"),hovertemplate:f.castOption(w,T,\"hovertemplate\"),hovertemplateLabels:f.extendFlat({},L,k),eventData:[L]},{container:n,gd:r}),m.buttons&&m.distance<5?r.emit(\"plotly_click\",C):r.emit(\"plotly_hover\",C),c=C}else d.loneUnhover(n),r.emit(\"plotly_unhover\",c);e.drawAnnotations(e)},w.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):f.error(\"Catastrophic and 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e,r=t.camera;this.camera.lookAt.apply(this,[[(e=r).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),this.glplot.setAspectratio(t.aspectratio),\"orthographic\"===r.projection.type!==this.camera._ortho&&(this.glplot.redraw(),this.glplot.clearRGBA(),this.glplot.dispose(),this.initializeGLPlot())},w.isCameraChanged=function(t){var e=this.getCamera(),r=f.nestedProperty(t,this.id+\".camera\").get();function n(t,e,r,n){var i=[\"up\",\"center\",\"eye\"],a=[\"x\",\"y\",\"z\"];return e[i[r]]&&t[i[r]][a[n]]===e[i[r]][a[n]]}var i=!1;if(void 0===r)i=!0;else{for(var a=0;a<3;a++)for(var o=0;o<3;o++)if(!n(e,r,a,o)){i=!0;break}(!r.projection||e.projection&&e.projection.type!==r.projection.type)&&(i=!0)}return i},w.isAspectChanged=function(t){var e=this.glplot.getAspectratio(),r=f.nestedProperty(t,this.id+\".aspectratio\").get();return void 0===r||r.x!==e.x||r.y!==e.y||r.z!==e.z},w.saveLayout=function(t){var e,r,n,i,a,o,s=this.fullLayout,l=this.isCameraChanged(t),c=this.isAspectChanged(t),h=l||c;if(h){var p={};if(l&&(e=this.getCamera(),n=(r=f.nestedProperty(t,this.id+\".camera\")).get(),p[this.id+\".camera\"]=n),c&&(i=this.glplot.getAspectratio(),o=(a=f.nestedProperty(t,this.id+\".aspectratio\")).get(),p[this.id+\".aspectratio\"]=o),u.call(\"_storeDirectGUIEdit\",t,s._preGUI,p),l)r.set(e),f.nestedProperty(s,this.id+\".camera\").set(e);if(c)a.set(i),f.nestedProperty(s,this.id+\".aspectratio\").set(i),this.glplot.redraw()}return h},w.updateFx=function(t,e){var r=this.camera;if(r)if(\"orbit\"===t)r.mode=\"orbit\",r.keyBindingMode=\"rotate\";else if(\"turntable\"===t){r.up=[0,0,1],r.mode=\"turntable\",r.keyBindingMode=\"rotate\";var n=this.graphDiv,i=n._fullLayout,a=this.fullSceneLayout.camera,o=a.up.x,s=a.up.y,l=a.up.z;if(l/Math.sqrt(o*o+s*s+l*l)<.999){var c=this.id+\".camera.up\",h={x:0,y:0,z:1},p={};p[c]=h;var 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s,l=o.getContext(\"2d\"),c=l.createImageData(r,i);switch(c.data.set(a),l.putImageData(c,0,0),t){case\"jpeg\":s=o.toDataURL(\"image/jpeg\");break;case\"webp\":s=o.toDataURL(\"image/webp\");break;default:s=o.toDataURL(\"image/png\")}return this.staticMode&&this.container.removeChild(n),s},w.setConvert=function(){for(var t=0;t<3;t++){var e=this.fullSceneLayout[k[t]];p.setConvert(e,this.fullLayout),e.setScale=f.noop}},w.make4thDimension=function(){var t=this.graphDiv._fullLayout;this._mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},p.setConvert(this._mockAxis,t)},e.exports=_},{\"../../components/fx\":702,\"../../lib\":799,\"../../lib/show_no_webgl_msg\":821,\"../../lib/str2rgbarray\":823,\"../../plots/cartesian/axes\":849,\"../../registry\":927,\"./layout/convert\":896,\"./layout/spikes\":899,\"./layout/tick_marks\":900,\"./project\":901,\"gl-plot3d\":322,\"has-passive-events\":440,\"webgl-context\":625}],903:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){n=n||t.length;for(var i=new Array(n),a=0;a<n;a++)i[a]=[t[a],e[a],r[a]];return i}},{}],904:[function(t,e,r){\"use strict\";var n=t(\"./font_attributes\"),i=t(\"./animation_attributes\"),a=t(\"../components/color/attributes\"),o=t(\"../components/shapes/draw_newshape/attributes\"),s=t(\"./pad_attributes\"),l=t(\"../lib/extend\").extendFlat,c=n({editType:\"calc\"});c.family.dflt='\"Open Sans\", verdana, arial, sans-serif',c.size.dflt=12,c.color.dflt=a.defaultLine,e.exports={font:c,title:{text:{valType:\"string\",editType:\"layoutstyle\"},font:n({editType:\"layoutstyle\"}),xref:{valType:\"enumerated\",dflt:\"container\",values:[\"container\",\"paper\"],editType:\"layoutstyle\"},yref:{valType:\"enumerated\",dflt:\"container\",values:[\"container\",\"paper\"],editType:\"layoutstyle\"},x:{valType:\"number\",min:0,max:1,dflt:.5,editType:\"layoutstyle\"},y:{valType:\"number\",min:0,max:1,dflt:\"auto\",editType:\"layoutstyle\"},xanchor:{valType:\"enumerated\",dflt:\"auto\",values:[\"auto\",\"left\",\"center\",\"right\"],editType:\"layoutstyle\"},yanchor:{valType:\"enumerated\",dflt:\"auto\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],editType:\"layoutstyle\"},pad:l(s({editType:\"layoutstyle\"}),{}),editType:\"layoutstyle\"},uniformtext:{mode:{valType:\"enumerated\",values:[!1,\"hide\",\"show\"],dflt:!1,editType:\"plot\"},minsize:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},editType:\"plot\"},autosize:{valType:\"boolean\",dflt:!1,editType:\"none\"},width:{valType:\"number\",min:10,dflt:700,editType:\"plot\"},height:{valType:\"number\",min:10,dflt:450,editType:\"plot\"},margin:{l:{valType:\"number\",min:0,dflt:80,editType:\"plot\"},r:{valType:\"number\",min:0,dflt:80,editType:\"plot\"},t:{valType:\"number\",min:0,dflt:100,editType:\"plot\"},b:{valType:\"number\",min:0,dflt:80,editType:\"plot\"},pad:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},autoexpand:{valType:\"boolean\",dflt:!0,editType:\"plot\"},editType:\"plot\"},computed:{valType:\"any\",editType:\"none\"},paper_bgcolor:{valType:\"color\",dflt:a.background,editType:\"plot\"},plot_bgcolor:{valType:\"color\",dflt:a.background,editType:\"layoutstyle\"},autotypenumbers:{valType:\"enumerated\",values:[\"convert 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n='\\xa9 <a target=\"_blank\" href=\"https://www.openstreetmap.org/copyright\">OpenStreetMap</a> contributors',i=['\\xa9 <a target=\"_blank\" href=\"https://carto.com/\">Carto</a>',n].join(\" \"),a=['Map tiles by <a target=\"_blank\" href=\"https://stamen.com\">Stamen Design</a>','under <a target=\"_blank\" href=\"https://creativecommons.org/licenses/by/3.0\">CC BY 3.0</a>',\"|\",'Data by <a target=\"_blank\" href=\"https://openstreetmap.org\">OpenStreetMap</a> contributors','under <a target=\"_blank\" href=\"https://www.openstreetmap.org/copyright\">ODbL</a>'].join(\" \"),o={\"open-street-map\":{id:\"osm\",version:8,sources:{\"plotly-osm-tiles\":{type:\"raster\",attribution:n,tiles:[\"https://a.tile.openstreetmap.org/{z}/{x}/{y}.png\",\"https://b.tile.openstreetmap.org/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-osm-tiles\",type:\"raster\",source:\"plotly-osm-tiles\",minzoom:0,maxzoom:22}]},\"white-bg\":{id:\"white-bg\",version:8,sources:{},layers:[{id:\"white-bg\",type:\"background\",paint:{\"background-color\":\"#FFFFFF\"},minzoom:0,maxzoom:22}]},\"carto-positron\":{id:\"carto-positron\",version:8,sources:{\"plotly-carto-positron\":{type:\"raster\",attribution:i,tiles:[\"https://cartodb-basemaps-c.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-carto-positron\",type:\"raster\",source:\"plotly-carto-positron\",minzoom:0,maxzoom:22}]},\"carto-darkmatter\":{id:\"carto-darkmatter\",version:8,sources:{\"plotly-carto-darkmatter\":{type:\"raster\",attribution:i,tiles:[\"https://cartodb-basemaps-c.global.ssl.fastly.net/dark_all/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-carto-darkmatter\",type:\"raster\",source:\"plotly-carto-darkmatter\",minzoom:0,maxzoom:22}]},\"stamen-terrain\":{id:\"stamen-terrain\",version:8,sources:{\"plotly-stamen-terrain\":{type:\"raster\",attribution:a,tiles:[\"https://stamen-tiles.a.ssl.fastly.net/terrain/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-stamen-terrain\",type:\"raster\",source:\"plotly-stamen-terrain\",minzoom:0,maxzoom:22}]},\"stamen-toner\":{id:\"stamen-toner\",version:8,sources:{\"plotly-stamen-toner\":{type:\"raster\",attribution:a,tiles:[\"https://stamen-tiles.a.ssl.fastly.net/toner/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-stamen-toner\",type:\"raster\",source:\"plotly-stamen-toner\",minzoom:0,maxzoom:22}]},\"stamen-watercolor\":{id:\"stamen-watercolor\",version:8,sources:{\"plotly-stamen-watercolor\":{type:\"raster\",attribution:['Map tiles by <a target=\"_blank\" href=\"https://stamen.com\">Stamen Design</a>','under <a target=\"_blank\" href=\"https://creativecommons.org/licenses/by/3.0\">CC BY 3.0</a>',\"|\",'Data by <a target=\"_blank\" href=\"https://openstreetmap.org\">OpenStreetMap</a> contributors','under <a target=\"_blank\" href=\"https://creativecommons.org/licenses/by-sa/3.0\">CC BY SA</a>'].join(\" \"),tiles:[\"https://stamen-tiles.a.ssl.fastly.net/watercolor/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-stamen-watercolor\",type:\"raster\",source:\"plotly-stamen-watercolor\",minzoom:0,maxzoom:22}]}},s=Object.keys(o);e.exports={requiredVersion:\"1.10.1\",styleUrlPrefix:\"mapbox://styles/mapbox/\",styleUrlSuffix:\"v9\",styleValuesMapbox:[\"basic\",\"streets\",\"outdoors\",\"light\",\"dark\",\"satellite\",\"satellite-streets\"],styleValueDflt:\"basic\",stylesNonMapbox:o,styleValuesNonMapbox:s,traceLayerPrefix:\"plotly-trace-layer-\",layoutLayerPrefix:\"plotly-layout-layer-\",wrongVersionErrorMsg:[\"Your custom plotly.js bundle is not using the correct mapbox-gl version\",\"Please install mapbox-gl@1.10.1.\"].join(\"\\n\"),noAccessTokenErrorMsg:[\"Missing Mapbox access token.\",\"Mapbox trace type require a Mapbox access token to be registered.\",\"For example:\",\"  Plotly.newPlot(gd, data, layout, { mapboxAccessToken: 'my-access-token' });\",\"More info here: 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n=t(\"mapbox-gl/dist/mapbox-gl-unminified\"),i=t(\"../../lib\"),a=i.strTranslate,o=i.strScale,s=t(\"../../plots/get_data\").getSubplotCalcData,l=t(\"../../constants/xmlns_namespaces\"),c=t(\"@plotly/d3\"),u=t(\"../../components/drawing\"),f=t(\"../../lib/svg_text_utils\"),h=t(\"./mapbox\"),p=r.constants=t(\"./constants\");function d(t){return\"string\"==typeof t&&(-1!==p.styleValuesMapbox.indexOf(t)||0===t.indexOf(\"mapbox://\"))}r.name=\"mapbox\",r.attr=\"subplot\",r.idRoot=\"mapbox\",r.idRegex=r.attrRegex=i.counterRegex(\"mapbox\"),r.attributes={subplot:{valType:\"subplotid\",dflt:\"mapbox\",editType:\"calc\"}},r.layoutAttributes=t(\"./layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout_defaults\"),r.plot=function(t){var e=t._fullLayout,r=t.calcdata,a=e._subplots.mapbox;if(n.version!==p.requiredVersion)throw new Error(p.wrongVersionErrorMsg);var o=function(t,e){var r=t._fullLayout;if(\"\"===t._context.mapboxAccessToken)return\"\";for(var n=[],a=[],o=!1,s=!1,l=0;l<e.length;l++){var c=r[e[l]],u=c.accesstoken;d(c.style)&&(u?i.pushUnique(n,u):(d(c._input.style)&&(i.error(\"Uses Mapbox map style, but did not set an access token.\"),o=!0),s=!0)),u&&i.pushUnique(a,u)}if(s){var f=o?p.noAccessTokenErrorMsg:p.missingStyleErrorMsg;throw i.error(f),new Error(f)}return n.length?(n.length>1&&i.warn(p.multipleTokensErrorMsg),n[0]):(a.length&&i.log([\"Listed mapbox access token(s)\",a.join(\",\"),\"but did not use a Mapbox map style, ignoring token(s).\"].join(\" \")),\"\")}(t,a);n.accessToken=o;for(var l=0;l<a.length;l++){var c=a[l],u=s(r,\"mapbox\",c),f=e[c],m=f._subplot;m||(m=new h(t,c),e[c]._subplot=m),m.viewInitial||(m.viewInitial={center:i.extendFlat({},f.center),zoom:f.zoom,bearing:f.bearing,pitch:f.pitch}),m.plot(u,e,t._promises)}},r.clean=function(t,e,r,n){for(var i=n._subplots.mapbox||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._subplot&&n[o]._subplot.destroy()}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.mapbox,n=e._size,i=0;i<r.length;i++){var s=e[r[i]],h=s.domain,d=s._subplot.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":d,x:n.l+n.w*h.x[0],y:n.t+n.h*(1-h.y[1]),width:n.w*(h.x[1]-h.x[0]),height:n.h*(h.y[1]-h.y[0]),preserveAspectRatio:\"none\"});var m=c.select(s._subplot.div);if(!(null===m.select(\".mapboxgl-ctrl-logo\").node().offsetParent)){var g=e._glimages.append(\"g\");g.attr(\"transform\",a(n.l+n.w*h.x[0]+10,n.t+n.h*(1-h.y[0])-31)),g.append(\"path\").attr(\"d\",p.mapboxLogo.path0).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"}),g.append(\"path\").attr(\"d\",p.mapboxLogo.path1).style(\"opacity\",.35).style(\"enable-background\",\"new\"),g.append(\"path\").attr(\"d\",p.mapboxLogo.path2).style(\"opacity\",.35).style(\"enable-background\",\"new\"),g.append(\"polygon\").attr(\"points\",p.mapboxLogo.polygon).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"})}var v=m.select(\".mapboxgl-ctrl-attrib\").text().replace(\"Improve this map\",\"\"),y=e._glimages.append(\"g\"),x=y.append(\"text\");x.text(v).classed(\"static-attribution\",!0).attr({\"font-size\":12,\"font-family\":\"Arial\",color:\"rgba(0, 0, 0, 0.75)\",\"text-anchor\":\"end\",\"data-unformatted\":v});var b=u.bBox(x.node()),_=n.w*(h.x[1]-h.x[0]);if(b.width>_/2){var w=v.split(\"|\").join(\"<br>\");x.text(w).attr(\"data-unformatted\",w).call(f.convertToTspans,t),b=u.bBox(x.node())}x.attr(\"transform\",a(-3,8-b.height)),y.insert(\"rect\",\".static-attribution\").attr({x:-b.width-6,y:-b.height-3,width:b.width+6,height:b.height+3,fill:\"rgba(255, 255, 255, 0.75)\"});var T=1;b.width+6>_&&(T=_/(b.width+6));var k=[n.l+n.w*h.x[1],n.t+n.h*(1-h.y[0])];y.attr(\"transform\",a(k[0],k[1])+o(T))}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.mapbox,n=0;n<r.length;n++){e[r[n]]._subplot.updateFx(e)}}},{\"../../components/drawing\":684,\"../../constants/xmlns_namespaces\":776,\"../../lib\":799,\"../../lib/svg_text_utils\":824,\"../../plots/get_data\":887,\"./constants\":905,\"./layout_attributes\":909,\"./layout_defaults\":910,\"./mapbox\":911,\"@plotly/d3\":58,\"mapbox-gl/dist/mapbox-gl-unminified\":457}],908:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../lib/svg_text_utils\").sanitizeHTML,a=t(\"./convert_text_opts\"),o=t(\"./constants\");function s(t,e){this.subplot=t,this.uid=t.uid+\"-\"+e,this.index=e,this.idSource=\"source-\"+this.uid,this.idLayer=o.layoutLayerPrefix+this.uid,this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var l=s.prototype;function c(t){if(!t.visible)return!1;var e=t.source;if(Array.isArray(e)&&e.length>0){for(var r=0;r<e.length;r++)if(\"string\"!=typeof e[r]||0===e[r].length)return!1;return!0}return n.isPlainObject(e)||\"string\"==typeof e&&e.length>0}function u(t){var e={},r={};switch(t.type){case\"circle\":n.extendFlat(r,{\"circle-radius\":t.circle.radius,\"circle-color\":t.color,\"circle-opacity\":t.opacity});break;case\"line\":n.extendFlat(r,{\"line-width\":t.line.width,\"line-color\":t.color,\"line-opacity\":t.opacity,\"line-dasharray\":t.line.dash});break;case\"fill\":n.extendFlat(r,{\"fill-color\":t.color,\"fill-outline-color\":t.fill.outlinecolor,\"fill-opacity\":t.opacity});break;case\"symbol\":var i=t.symbol,o=a(i.textposition,i.iconsize);n.extendFlat(e,{\"icon-image\":i.icon+\"-15\",\"icon-size\":i.iconsize/10,\"text-field\":i.text,\"text-size\":i.textfont.size,\"text-anchor\":o.anchor,\"text-offset\":o.offset,\"symbol-placement\":i.placement}),n.extendFlat(r,{\"icon-color\":t.color,\"text-color\":i.textfont.color,\"text-opacity\":t.opacity});break;case\"raster\":n.extendFlat(r,{\"raster-fade-duration\":0,\"raster-opacity\":t.opacity})}return{layout:e,paint:r}}l.update=function(t){this.visible?this.needsNewImage(t)?this.updateImage(t):this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=c(t)},l.needsNewImage=function(t){return this.subplot.map.getSource(this.idSource)&&\"image\"===this.sourceType&&\"image\"===t.sourcetype&&(this.source!==t.source||JSON.stringify(this.coordinates)!==JSON.stringify(t.coordinates))},l.needsNewSource=function(t){return this.sourceType!==t.sourcetype||JSON.stringify(this.source)!==JSON.stringify(t.source)||this.layerType!==t.type},l.needsNewLayer=function(t){return this.layerType!==t.type||this.below!==this.subplot.belowLookup[\"layout-\"+this.index]},l.lookupBelow=function(){return this.subplot.belowLookup[\"layout-\"+this.index]},l.updateImage=function(t){this.subplot.map.getSource(this.idSource).updateImage({url:t.source,coordinates:t.coordinates});var e=this.findFollowingMapboxLayerId(this.lookupBelow());null!==e&&this.subplot.map.moveLayer(this.idLayer,e)},l.updateSource=function(t){var e=this.subplot.map;if(e.getSource(this.idSource)&&e.removeSource(this.idSource),this.sourceType=t.sourcetype,this.source=t.source,c(t)){var r=function(t){var e,r=t.sourcetype,n=t.source,a={type:r};\"geojson\"===r?e=\"data\":\"vector\"===r?e=\"string\"==typeof n?\"url\":\"tiles\":\"raster\"===r?(e=\"tiles\",a.tileSize=256):\"image\"===r&&(e=\"url\",a.coordinates=t.coordinates);a[e]=n,t.sourceattribution&&(a.attribution=i(t.sourceattribution));return a}(t);e.addSource(this.idSource,r)}},l.findFollowingMapboxLayerId=function(t){if(\"traces\"===t)for(var e=this.subplot.getMapLayers(),r=0;r<e.length;r++){var n=e[r].id;if(\"string\"==typeof n&&0===n.indexOf(o.traceLayerPrefix)){t=n;break}}return t},l.updateLayer=function(t){var e=this.subplot,r=u(t),n=this.lookupBelow(),i=this.findFollowingMapboxLayerId(n);this.removeLayer(),c(t)&&e.addLayer({id:this.idLayer,source:this.idSource,\"source-layer\":t.sourcelayer||\"\",type:t.type,minzoom:t.minzoom,maxzoom:t.maxzoom,layout:r.layout,paint:r.paint},i),this.layerType=t.type,this.below=n},l.updateStyle=function(t){if(c(t)){var e=u(t);this.subplot.setOptions(this.idLayer,\"setLayoutProperty\",e.layout),this.subplot.setOptions(this.idLayer,\"setPaintProperty\",e.paint)}},l.removeLayer=function(){var t=this.subplot.map;t.getLayer(this.idLayer)&&t.removeLayer(this.idLayer)},l.dispose=function(){var t=this.subplot.map;t.getLayer(this.idLayer)&&t.removeLayer(this.idLayer),t.getSource(this.idSource)&&t.removeSource(this.idSource)},e.exports=function(t,e,r){var n=new s(t,e);return n.update(r),n}},{\"../../lib\":799,\"../../lib/svg_text_utils\":824,\"./constants\":905,\"./convert_text_opts\":906}],909:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\").defaultLine,a=t(\"../domain\").attributes,o=t(\"../font_attributes\"),s=t(\"../../traces/scatter/attributes\").textposition,l=t(\"../../plot_api/edit_types\").overrideAll,c=t(\"../../plot_api/plot_template\").templatedArray,u=t(\"./constants\"),f=o({});f.family.dflt=\"Open Sans Regular, Arial Unicode MS 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t=c._fullLayout[s.id];q=i(t.bgcolor).getLuminance(),(H=g.makeZoombox(f,q,x,T,U)).attr(\"fill-rule\",\"evenodd\"),G=g.makeCorners(f,x,T),w(c)}();break;case\"select\":case\"lasso\":b(t,n,a,Y,l)}},R.onmousemove=function(t){y.hover(c,t,s.id),c._fullLayout._lasthover=R,c._fullLayout._hoversubplot=s.id},R.onmouseout=function(t){c._dragging||v.unhover(c,t)},v.init(Y)},z.updateRadialDrag=function(t,e,r){var i=this,c=i.gd,u=i.layers,f=i.radius,h=i.innerRadius,p=i.cx,d=i.cy,m=i.radialAxis,y=S.radialDragBoxSize,x=y/2;if(m.visible){var b,_,T,A=P(i.radialAxisAngle),E=m._rl,L=E[0],C=E[1],O=E[r],z=.75*(E[1]-E[0])/(1-e.hole)/f;r?(b=p+(f+x)*Math.cos(A),_=d-(f+x)*Math.sin(A),T=\"radialdrag\"):(b=p+(h-x)*Math.cos(A),_=d-(h-x)*Math.sin(A),T=\"radialdrag-inner\");var D,B,N,j=g.makeRectDragger(u,T,\"crosshair\",-x,-x,y,y),U={element:j,gd:c};F(n.select(j),m.visible&&h<f,{transform:l(b,_)}),U.prepFn=function(){D=null,B=null,N=null,U.moveFn=V,U.doneFn=q,w(c)},U.clampFn=function(t,e){return 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n=t(\"../../components/color/attributes\"),i=t(\"../domain\").attributes,a=t(\"../cartesian/layout_attributes\"),o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../lib/extend\").extendFlat,l={title:{text:a.title.text,font:a.title.font},color:a.color,tickmode:a.tickmode,nticks:s({},a.nticks,{dflt:6,min:1}),tick0:a.tick0,dtick:a.dtick,tickvals:a.tickvals,ticktext:a.ticktext,ticks:a.ticks,ticklen:a.ticklen,tickwidth:a.tickwidth,tickcolor:a.tickcolor,showticklabels:a.showticklabels,showtickprefix:a.showtickprefix,tickprefix:a.tickprefix,showticksuffix:a.showticksuffix,ticksuffix:a.ticksuffix,showexponent:a.showexponent,exponentformat:a.exponentformat,minexponent:a.minexponent,separatethousands:a.separatethousands,tickfont:a.tickfont,tickangle:a.tickangle,tickformat:a.tickformat,tickformatstops:a.tickformatstops,hoverformat:a.hoverformat,showline:s({},a.showline,{dflt:!0}),linecolor:a.linecolor,linewidth:a.linewidth,showgrid:s({},a.showgrid,{dflt:!0}),gridcolor:a.gridcolor,gridwidth:a.gridwidth,layer:a.layer,min:{valType:\"number\",dflt:0,min:0},_deprecated:{title:a._deprecated.title,titlefont:a._deprecated.titlefont}},c=e.exports=o({domain:i({name:\"ternary\"}),bgcolor:{valType:\"color\",dflt:n.background},sum:{valType:\"number\",dflt:1,min:0},aaxis:l,baxis:l,caxis:l},\"plot\",\"from-root\");c.uirevision={valType:\"any\",editType:\"none\"},c.aaxis.uirevision=c.baxis.uirevision=c.caxis.uirevision={valType:\"any\",editType:\"none\"}},{\"../../components/color/attributes\":661,\"../../lib/extend\":789,\"../../plot_api/edit_types\":831,\"../cartesian/layout_attributes\":864,\"../domain\":877}],925:[function(t,e,r){\"use 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n=t(\"@plotly/d3\"),i=t(\"tinycolor2\"),a=t(\"../../registry\"),o=t(\"../../lib\"),s=o.strTranslate,l=o._,c=t(\"../../components/color\"),u=t(\"../../components/drawing\"),f=t(\"../cartesian/set_convert\"),h=t(\"../../lib/extend\").extendFlat,p=t(\"../plots\"),d=t(\"../cartesian/axes\"),m=t(\"../../components/dragelement\"),g=t(\"../../components/fx\"),v=t(\"../../components/dragelement/helpers\"),y=v.freeMode,x=v.rectMode,b=t(\"../../components/titles\"),_=t(\"../cartesian/select\").prepSelect,w=t(\"../cartesian/select\").selectOnClick,T=t(\"../cartesian/select\").clearSelect,k=t(\"../cartesian/select\").clearSelectionsCache,M=t(\"../cartesian/constants\");function A(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework(e),this.aTickLayout=null,this.bTickLayout=null,this.cTickLayout=null}e.exports=A;var S=A.prototype;S.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={},this.layers={}},S.plot=function(t,e){var 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E=Math.sqrt(4/3);S.adjustLayout=function(t,e){var r,n,i,a,o,l,p=this,d=t.domain,m=(d.x[0]+d.x[1])/2,g=(d.y[0]+d.y[1])/2,v=d.x[1]-d.x[0],y=d.y[1]-d.y[0],x=v*e.w,b=y*e.h,_=t.sum,w=t.aaxis.min,T=t.baxis.min,k=t.caxis.min;x>E*b?i=(a=b)*E:a=(i=x)/E,o=v*i/x,l=y*a/b,r=e.l+e.w*m-i/2,n=e.t+e.h*(1-g)-a/2,p.x0=r,p.y0=n,p.w=i,p.h=a,p.sum=_,p.xaxis={type:\"linear\",range:[w+2*k-_,_-w-2*T],domain:[m-o/2,m+o/2],_id:\"x\"},f(p.xaxis,p.graphDiv._fullLayout),p.xaxis.setScale(),p.xaxis.isPtWithinRange=function(t){return t.a>=p.aaxis.range[0]&&t.a<=p.aaxis.range[1]&&t.b>=p.baxis.range[1]&&t.b<=p.baxis.range[0]&&t.c>=p.caxis.range[1]&&t.c<=p.caxis.range[0]},p.yaxis={type:\"linear\",range:[w,_-T-k],domain:[g-l/2,g+l/2],_id:\"y\"},f(p.yaxis,p.graphDiv._fullLayout),p.yaxis.setScale(),p.yaxis.isPtWithinRange=function(){return!0};var 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n=t(\"../../components/fx\"),i=t(\"../../registry\"),a=t(\"../../components/color\"),o=t(\"../../lib\").fillText,s=t(\"./helpers\").getLineWidth,l=t(\"../../plots/cartesian/axes\").hoverLabelText,c=t(\"../../constants/numerical\").BADNUM;function u(t,e,r,i,a){var s,u,f,h,p,d,m,g=t.cd,v=g[0].trace,y=g[0].t,x=\"closest\"===i,b=\"waterfall\"===v.type,_=t.maxHoverDistance,w=t.maxSpikeDistance;\"h\"===v.orientation?(s=r,u=e,f=\"y\",h=\"x\",p=I,d=C):(s=e,u=r,f=\"x\",h=\"y\",d=I,p=C);var T=v[f+\"period\"];function k(t){return A(t,-1)}function M(t){return A(t,1)}function A(t,e){return T?t.p+e*Math.abs(t.p-t.orig_p):t[f]+e*t.w/2}var S=x||T?k:function(t){return Math.min(k(t),t.p-y.bardelta/2)},E=x||T?M:function(t){return Math.max(M(t),t.p+y.bardelta/2)};function L(t,e,r){return a.finiteRange&&(r=0),n.inbox(t-s,e-s,r+Math.min(1,Math.abs(e-t)/m)-1)}function C(t){return L(S(t),E(t),_)}function P(t){var e=t[h];if(b){var r=Math.abs(t.rawS)||0;u>0?e+=r:u<0&&(e-=r)}return e}function I(t){var 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n=t(\"../../components/fx\"),i=t(\"../../lib\"),a=t(\"../bar/hover\").getTraceColor,o=i.fillText,s=t(\"../scatterpolar/hover\").makeHoverPointText,l=t(\"../../plots/polar/helpers\").isPtInsidePolygon;e.exports=function(t,e,r){var c=t.cd,u=c[0].trace,f=t.subplot,h=f.radialAxis,p=f.angularAxis,d=f.vangles,m=d?l:i.isPtInsideSector,g=t.maxHoverDistance,v=p._period||2*Math.PI,y=Math.abs(h.g2p(Math.sqrt(e*e+r*r))),x=Math.atan2(r,e);h.range[0]>h.range[1]&&(x+=Math.PI);if(n.getClosest(c,(function(t){return m(y,x,[t.rp0,t.rp1],[t.thetag0,t.thetag1],d)?g+Math.min(1,Math.abs(t.thetag1-t.thetag0)/v)-1+(t.rp1-y)/(t.rp1-t.rp0)-1:1/0}),t),!1!==t.index){var b=c[t.index];t.x0=t.x1=b.ct[0],t.y0=t.y1=b.ct[1];var _=i.extendFlat({},b,{r:b.s,theta:b.p});return o(b,u,t),s(_,u,f,t),t.hovertemplate=u.hovertemplate,t.color=a(u,b),t.xLabelVal=t.yLabelVal=void 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n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../mesh3d/attributes\"),s=t(\"../../plots/attributes\"),l=t(\"../../lib/extend\").extendFlat,c={x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},u:{valType:\"data_array\",editType:\"calc\"},v:{valType:\"data_array\",editType:\"calc\"},w:{valType:\"data_array\",editType:\"calc\"},sizemode:{valType:\"enumerated\",values:[\"scaled\",\"absolute\"],editType:\"calc\",dflt:\"scaled\"},sizeref:{valType:\"number\",editType:\"calc\",min:0},anchor:{valType:\"enumerated\",editType:\"calc\",values:[\"tip\",\"tail\",\"cm\",\"center\"],dflt:\"cm\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"},{keys:[\"norm\"]}),uhoverformat:i(\"u\",1),vhoverformat:i(\"v\",1),whoverformat:i(\"w\",1),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),showlegend:l({},s.showlegend,{dflt:!1})};l(c,n(\"\",{colorAttr:\"u/v/w 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n=t(\"../heatmap/attributes\"),i=t(\"../scatter/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\"),o=a.axisHoverFormat,s=a.descriptionOnlyNumbers,l=t(\"../../components/colorscale/attributes\"),c=t(\"../../components/drawing/attributes\").dash,u=t(\"../../plots/font_attributes\"),f=t(\"../../lib/extend\").extendFlat,h=t(\"../../constants/filter_ops\"),p=h.COMPARISON_OPS2,d=h.INTERVAL_OPS,m=i.line;e.exports=f({z:n.z,x:n.x,x0:n.x0,dx:n.dx,y:n.y,y0:n.y0,dy:n.dy,xperiod:n.xperiod,yperiod:n.yperiod,xperiod0:i.xperiod0,yperiod0:i.yperiod0,xperiodalignment:n.xperiodalignment,yperiodalignment:n.yperiodalignment,text:n.text,hovertext:n.hovertext,transpose:n.transpose,xtype:n.xtype,ytype:n.ytype,xhoverformat:o(\"x\"),yhoverformat:o(\"y\"),zhoverformat:o(\"z\",1),hovertemplate:n.hovertemplate,hoverongaps:n.hoverongaps,connectgaps:f({},n.connectgaps,{}),fillcolor:{valType:\"color\",editType:\"calc\"},autocontour:{valType:\"boolean\",dflt:!0,editType:\"calc\",impliedEdits:{\"contours.start\":void 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n=t(\"../pie/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../plots/domain\").attributes,o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../plots/template_attributes\").texttemplateAttrs,l=t(\"../../lib/extend\").extendFlat;e.exports={labels:n.labels,label0:n.label0,dlabel:n.dlabel,values:n.values,marker:{colors:n.marker.colors,line:{color:l({},n.marker.line.color,{dflt:null}),width:l({},n.marker.line.width,{dflt:1}),editType:\"calc\"},editType:\"calc\"},text:n.text,hovertext:n.hovertext,scalegroup:l({},n.scalegroup,{}),textinfo:l({},n.textinfo,{flags:[\"label\",\"text\",\"value\",\"percent\"]}),texttemplate:s({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"text\",\"percent\"]}),hoverinfo:l({},i.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:o({},{keys:[\"label\",\"color\",\"value\",\"text\",\"percent\"]}),textposition:l({},n.textposition,{values:[\"inside\",\"none\"],dflt:\"inside\"}),textfont:n.textfont,insidetextfont:n.insidetextfont,title:{text:n.title.text,font:n.title.font,position:l({},n.title.position,{values:[\"top 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n=t(\"../../lib\"),i=t(\"./attributes\"),a=t(\"../../plots/domain\").defaults,o=t(\"../bar/defaults\").handleText,s=t(\"../pie/defaults\").handleLabelsAndValues;e.exports=function(t,e,r,l){function c(r,a){return n.coerce(t,e,i,r,a)}var u=c(\"labels\"),f=c(\"values\"),h=s(u,f),p=h.len;if(e._hasLabels=h.hasLabels,e._hasValues=h.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),p){e._length=p,c(\"marker.line.width\")&&c(\"marker.line.color\",l.paper_bgcolor),c(\"marker.colors\"),c(\"scalegroup\");var d,m=c(\"text\"),g=c(\"texttemplate\");if(g||(d=c(\"textinfo\",Array.isArray(m)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),g||d&&\"none\"!==d){var v=c(\"textposition\");o(t,e,l,c,v,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1})}a(e,l,c),c(\"title.text\")&&(c(\"title.position\"),n.coerceFont(c,\"title.font\",l.font)),c(\"aspectratio\"),c(\"baseratio\")}else e.visible=!1}},{\"../../lib\":799,\"../../plots/domain\":877,\"../bar/defaults\":941,\"../pie/defaults\":1191,\"./attributes\":1072}],1076:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"funnelarea\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"funnelarea\",\"showLegend\"],attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\"),supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\"),style:t(\"./style\"),styleOne:t(\"../pie/style_one\"),meta:{}}},{\"../pie/style_one\":1199,\"./attributes\":1072,\"./base_plot\":1073,\"./calc\":1074,\"./defaults\":1075,\"./layout_attributes\":1077,\"./layout_defaults\":1078,\"./plot\":1079,\"./style\":1080}],1077:[function(t,e,r){\"use strict\";var n=t(\"../pie/layout_attributes\").hiddenlabels;e.exports={hiddenlabels:n,funnelareacolorway:{valType:\"colorlist\",editType:\"calc\"},extendfunnelareacolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{\"../pie/layout_attributes\":1195}],1078:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"funnelareacolorway\",e.colorway),r(\"extendfunnelareacolors\")}},{\"../../lib\":799,\"./layout_attributes\":1077}],1079:[function(t,e,r){\"use strict\";var 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n=t(\"../../lib\"),i=t(\"./attributes\"),a=t(\"../../plots/domain\").defaults,o=t(\"../../plot_api/plot_template\"),s=t(\"../../plots/array_container_defaults\"),l=t(\"./constants.js\"),c=t(\"../../plots/cartesian/tick_value_defaults\"),u=t(\"../../plots/cartesian/tick_mark_defaults\"),f=t(\"../../plots/cartesian/tick_label_defaults\");function h(t,e){function r(r,a){return n.coerce(t,e,i.gauge.steps,r,a)}r(\"color\"),r(\"line.color\"),r(\"line.width\"),r(\"range\"),r(\"thickness\")}e.exports={supplyDefaults:function(t,e,r,p){function d(r,a){return n.coerce(t,e,i,r,a)}a(e,p,d),d(\"mode\"),e._hasNumber=-1!==e.mode.indexOf(\"number\"),e._hasDelta=-1!==e.mode.indexOf(\"delta\"),e._hasGauge=-1!==e.mode.indexOf(\"gauge\");var m=d(\"value\");e._range=[0,\"number\"==typeof m?1.5*m:1];var g,v,y,x,b,_,w=new Array(2);function T(t,e){return n.coerce(y,x,i.gauge,t,e)}function k(t,e){return n.coerce(b,_,i.gauge.axis,t,e)}if(e._hasNumber&&(d(\"number.valueformat\"),d(\"number.font.color\",p.font.color),d(\"number.font.family\",p.font.family),d(\"number.font.size\"),void 0===e.number.font.size&&(e.number.font.size=l.defaultNumberFontSize,w[0]=!0),d(\"number.prefix\"),d(\"number.suffix\"),g=e.number.font.size),e._hasDelta&&(d(\"delta.font.color\",p.font.color),d(\"delta.font.family\",p.font.family),d(\"delta.font.size\"),void 0===e.delta.font.size&&(e.delta.font.size=(e._hasNumber?.5:1)*(g||l.defaultNumberFontSize),w[1]=!0),d(\"delta.reference\",e.value),d(\"delta.relative\"),d(\"delta.valueformat\",e.delta.relative?\"2%\":\"\"),d(\"delta.increasing.symbol\"),d(\"delta.increasing.color\"),d(\"delta.decreasing.symbol\"),d(\"delta.decreasing.color\"),d(\"delta.position\"),v=e.delta.font.size),e._scaleNumbers=(!e._hasNumber||w[0])&&(!e._hasDelta||w[1])||!1,d(\"title.font.color\",p.font.color),d(\"title.font.family\",p.font.family),d(\"title.font.size\",.25*(g||v||l.defaultNumberFontSize)),d(\"title.text\"),e._hasGauge){(y=t.gauge)||(y={}),x=o.newContainer(e,\"gauge\"),T(\"shape\"),(e._isBullet=\"bullet\"===e.gauge.shape)||d(\"title.align\",\"center\"),(e._isAngular=\"angular\"===e.gauge.shape)||d(\"align\",\"center\"),T(\"bgcolor\",p.paper_bgcolor),T(\"borderwidth\"),T(\"bordercolor\"),T(\"bar.color\"),T(\"bar.line.color\"),T(\"bar.line.width\"),T(\"bar.thickness\",l.valueThickness*(\"bullet\"===e.gauge.shape?.5:1)),s(y,x,{name:\"steps\",handleItemDefaults:h}),T(\"threshold.value\"),T(\"threshold.thickness\"),T(\"threshold.line.width\"),T(\"threshold.line.color\"),b={},y&&(b=y.axis||{}),_=o.newContainer(x,\"axis\"),k(\"visible\"),e._range=k(\"range\",e._range);var M={outerTicks:!0};c(b,_,k,\"linear\"),f(b,_,k,\"linear\",M),u(b,_,k,M)}else d(\"title.align\",\"center\"),d(\"align\",\"center\"),e._isAngular=e._isBullet=!1;e._length=null}}},{\"../../lib\":799,\"../../plot_api/plot_template\":838,\"../../plots/array_container_defaults\":844,\"../../plots/cartesian/tick_label_defaults\":871,\"../../plots/cartesian/tick_mark_defaults\":872,\"../../plots/cartesian/tick_value_defaults\":873,\"../../plots/domain\":877,\"./attributes\":1143,\"./constants.js\":1146}],1148:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"indicator\",basePlotModule:t(\"./base_plot\"),categories:[\"svg\",\"noOpacity\",\"noHover\"],animatable:!0,attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,calc:t(\"./calc\").calc,plot:t(\"./plot\"),meta:{}}},{\"./attributes\":1143,\"./base_plot\":1144,\"./calc\":1145,\"./defaults\":1147,\"./plot\":1149}],1149:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=i.strScale,o=i.strTranslate,s=i.rad2deg,l=t(\"../../constants/alignment\").MID_SHIFT,c=t(\"../../components/drawing\"),u=t(\"./constants\"),f=t(\"../../lib/svg_text_utils\"),h=t(\"../../plots/cartesian/axes\"),p=t(\"../../plots/cartesian/axis_defaults\"),d=t(\"../../plots/cartesian/position_defaults\"),m=t(\"../../plots/cartesian/layout_attributes\"),g=t(\"../../components/color\"),v={left:\"start\",center:\"middle\",right:\"end\"},y={left:0,center:.5,right:1},x=/[yzafpn\\xb5mkMGTPEZY]/;function b(t){return t&&t.duration>0}function _(t){t.each((function(t){g.stroke(n.select(this),t.line.color)})).each((function(t){g.fill(n.select(this),t.color)})).style(\"stroke-width\",(function(t){return t.line.width}))}function w(t,e,r){var n=t._fullLayout,a=i.extendFlat({type:\"linear\",ticks:\"outside\",range:r,showline:!0},e),o={type:\"linear\",_id:\"x\"+e._id},s={letter:\"x\",font:n.font,noHover:!0,noTickson:!0};function l(t,e){return i.coerce(a,o,m,t,e)}return p(a,o,l,s,n),d(a,o,l,s),o}function T(t,e,r){return[Math.min(e/t.width,r/t.height),t,e+\"x\"+r]}function k(t,e,r,i){var a=document.createElementNS(\"http://www.w3.org/2000/svg\",\"text\"),o=n.select(a);return o.text(t).attr(\"x\",0).attr(\"y\",0).attr(\"text-anchor\",r).attr(\"data-unformatted\",t).call(f.convertToTspans,i).call(c.font,e),c.bBox(o.node())}function M(t,e,r,n,a,o){var s=\"_cache\"+e;t[s]&&t[s].key===a||(t[s]={key:a,value:r});var l=i.aggNums(o,null,[t[s].value,n],2);return t[s].value=l,l}e.exports=function(t,e,r,p){var d,m=t._fullLayout;b(r)&&p&&(d=p()),i.makeTraceGroups(m._indicatorlayer,e,\"trace\").each((function(e){var p,A,S,E,L,C=e[0].trace,P=n.select(this),I=C._hasGauge,O=C._isAngular,z=C._isBullet,D=C.domain,R={w:m._size.w*(D.x[1]-D.x[0]),h:m._size.h*(D.y[1]-D.y[0]),l:m._size.l+m._size.w*D.x[0],r:m._size.r+m._size.w*(1-D.x[1]),t:m._size.t+m._size.h*(1-D.y[1]),b:m._size.b+m._size.h*D.y[0]},F=R.l+R.w/2,B=R.t+R.h/2,N=Math.min(R.w/2,R.h),j=u.innerRadius*N,U=C.align||\"center\";if(A=B,I){if(O&&(p=F,A=B+N/2,S=function(t){return function(t,e){var r=Math.sqrt(t.width/2*(t.width/2)+t.height*t.height);return[e/r,t,e]}(t,.9*j)}),z){var V=u.bulletPadding,q=1-u.bulletNumberDomainSize+V;p=R.l+(q+(1-q)*y[U])*R.w,S=function(t){return T(t,(u.bulletNumberDomainSize-V)*R.w,R.h)}}}else p=R.l+y[U]*R.w,S=function(t){return T(t,R.w,R.h)};!function(t,e,r,s){var l,u,p,d=r[0].trace,m=s.numbersX,_=s.numbersY,T=d.align||\"center\",A=v[T],S=s.transitionOpts,E=s.onComplete,L=i.ensureSingle(e,\"g\",\"numbers\"),C=[];d._hasNumber&&C.push(\"number\");d._hasDelta&&(C.push(\"delta\"),\"left\"===d.delta.position&&C.reverse());var P=L.selectAll(\"text\").data(C);function I(e,r,n,i){if(!e.match(\"s\")||n>=0==i>=0||r(n).slice(-1).match(x)||r(i).slice(-1).match(x))return r;var a=e.slice().replace(\"s\",\"f\").replace(/\\d+/,(function(t){return parseInt(t)-1})),o=w(t,{tickformat:a});return function(t){return Math.abs(t)<1?h.tickText(o,t).text:r(t)}}P.enter().append(\"text\"),P.attr(\"text-anchor\",(function(){return A})).attr(\"class\",(function(t){return t})).attr(\"x\",null).attr(\"y\",null).attr(\"dx\",null).attr(\"dy\",null),P.exit().remove();var O,z=d.mode+d.align;d._hasDelta&&(O=function(){var e=w(t,{tickformat:d.delta.valueformat},d._range);e.setScale(),h.prepTicks(e);var i=function(t){return h.tickText(e,t).text},a=function(t){return d.delta.relative?t.relativeDelta:t.delta},o=function(t,e){return 0===t||\"number\"!=typeof t||isNaN(t)?\"-\":(t>0?d.delta.increasing.symbol:d.delta.decreasing.symbol)+e(t)},s=function(t){return t.delta>=0?d.delta.increasing.color:d.delta.decreasing.color};void 0===d._deltaLastValue&&(d._deltaLastValue=a(r[0]));var l=L.select(\"text.delta\");function p(){l.text(o(a(r[0]),i)).call(g.fill,s(r[0])).call(f.convertToTspans,t)}return l.call(c.font,d.delta.font).call(g.fill,s({delta:d._deltaLastValue})),b(S)?l.transition().duration(S.duration).ease(S.easing).tween(\"text\",(function(){var t=n.select(this),e=a(r[0]),l=d._deltaLastValue,c=I(d.delta.valueformat,i,l,e),u=n.interpolateNumber(l,e);return d._deltaLastValue=e,function(e){t.text(o(u(e),c)),t.call(g.fill,s({delta:u(e)}))}})).each(\"end\",(function(){p(),E&&E()})).each(\"interrupt\",(function(){p(),E&&E()})):p(),u=k(o(a(r[0]),i),d.delta.font,A,t),l}(),z+=d.delta.position+d.delta.font.size+d.delta.font.family+d.delta.valueformat,z+=d.delta.increasing.symbol+d.delta.decreasing.symbol,p=u);d._hasNumber&&(!function(){var e=w(t,{tickformat:d.number.valueformat},d._range);e.setScale(),h.prepTicks(e);var i=function(t){return h.tickText(e,t).text},a=d.number.suffix,o=d.number.prefix,s=L.select(\"text.number\");function u(){var e=\"number\"==typeof r[0].y?o+i(r[0].y)+a:\"-\";s.text(e).call(c.font,d.number.font).call(f.convertToTspans,t)}b(S)?s.transition().duration(S.duration).ease(S.easing).each(\"end\",(function(){u(),E&&E()})).each(\"interrupt\",(function(){u(),E&&E()})).attrTween(\"text\",(function(){var t=n.select(this),e=n.interpolateNumber(r[0].lastY,r[0].y);d._lastValue=r[0].y;var s=I(d.number.valueformat,i,r[0].lastY,r[0].y);return function(r){t.text(o+s(e(r))+a)}})):u(),l=k(o+i(r[0].y)+a,d.number.font,A,t)}(),z+=d.number.font.size+d.number.font.family+d.number.valueformat+d.number.suffix+d.number.prefix,p=l);if(d._hasDelta&&d._hasNumber){var D,R,F=[(l.left+l.right)/2,(l.top+l.bottom)/2],B=[(u.left+u.right)/2,(u.top+u.bottom)/2],N=.75*d.delta.font.size;\"left\"===d.delta.position&&(D=M(d,\"deltaPos\",0,-1*(l.width*y[d.align]+u.width*(1-y[d.align])+N),z,Math.min),R=F[1]-B[1],p={width:l.width+u.width+N,height:Math.max(l.height,u.height),left:u.left+D,right:l.right,top:Math.min(l.top,u.top+R),bottom:Math.max(l.bottom,u.bottom+R)}),\"right\"===d.delta.position&&(D=M(d,\"deltaPos\",0,l.width*(1-y[d.align])+u.width*y[d.align]+N,z,Math.max),R=F[1]-B[1],p={width:l.width+u.width+N,height:Math.max(l.height,u.height),left:l.left,right:u.right+D,top:Math.min(l.top,u.top+R),bottom:Math.max(l.bottom,u.bottom+R)}),\"bottom\"===d.delta.position&&(D=null,R=u.height,p={width:Math.max(l.width,u.width),height:l.height+u.height,left:Math.min(l.left,u.left),right:Math.max(l.right,u.right),top:l.bottom-l.height,bottom:l.bottom+u.height}),\"top\"===d.delta.position&&(D=null,R=l.top,p={width:Math.max(l.width,u.width),height:l.height+u.height,left:Math.min(l.left,u.left),right:Math.max(l.right,u.right),top:l.bottom-l.height-u.height,bottom:l.bottom}),O.attr({dx:D,dy:R})}(d._hasNumber||d._hasDelta)&&L.attr(\"transform\",(function(){var t=s.numbersScaler(p);z+=t[2];var e,r=M(d,\"numbersScale\",1,t[0],z,Math.min);d._scaleNumbers||(r=1),e=d._isAngular?_-r*p.bottom:_-r*(p.top+p.bottom)/2,d._numbersTop=r*p.top+e;var n=p[T];\"center\"===T&&(n=(p.left+p.right)/2);var i=m-r*n;return i=M(d,\"numbersTranslate\",0,i,z,Math.max),o(i,e)+a(r)}))}(t,P,e,{numbersX:p,numbersY:A,numbersScaler:S,transitionOpts:r,onComplete:d}),I&&(E={range:C.gauge.axis.range,color:C.gauge.bgcolor,line:{color:C.gauge.bordercolor,width:0},thickness:1},L={range:C.gauge.axis.range,color:\"rgba(0, 0, 0, 0)\",line:{color:C.gauge.bordercolor,width:C.gauge.borderwidth},thickness:1});var H=P.selectAll(\"g.angular\").data(O?e:[]);H.exit().remove();var G=P.selectAll(\"g.angularaxis\").data(O?e:[]);G.exit().remove(),O&&function(t,e,r,i){var a,c,u,f,p=r[0].trace,d=i.size,m=i.radius,g=i.innerRadius,v=i.gaugeBg,y=i.gaugeOutline,x=[d.l+d.w/2,d.t+d.h/2+m/2],T=i.gauge,k=i.layer,M=i.transitionOpts,A=i.onComplete,S=Math.PI/2;function E(t){var e=p.gauge.axis.range[0],r=(t-e)/(p.gauge.axis.range[1]-e)*Math.PI-S;return r<-S?-S:r>S?S:r}function L(t){return n.svg.arc().innerRadius((g+m)/2-t/2*(m-g)).outerRadius((g+m)/2+t/2*(m-g)).startAngle(-S)}function C(t){t.attr(\"d\",(function(t){return L(t.thickness).startAngle(E(t.range[0])).endAngle(E(t.range[1]))()}))}T.enter().append(\"g\").classed(\"angular\",!0),T.attr(\"transform\",o(x[0],x[1])),k.enter().append(\"g\").classed(\"angularaxis\",!0).classed(\"crisp\",!0),k.selectAll(\"g.xangularaxistick,path,text\").remove(),(a=w(t,p.gauge.axis)).type=\"linear\",a.range=p.gauge.axis.range,a._id=\"xangularaxis\",a.ticklabeloverflow=\"allow\",a.setScale();var P=function(t){return(a.range[0]-t.x)/(a.range[1]-a.range[0])*Math.PI+Math.PI},I={},O=h.makeLabelFns(a,0).labelStandoff;I.xFn=function(t){var e=P(t);return Math.cos(e)*O},I.yFn=function(t){var e=P(t),r=Math.sin(e)>0?.2:1;return-Math.sin(e)*(O+t.fontSize*r)+Math.abs(Math.cos(e))*(t.fontSize*l)},I.anchorFn=function(t){var e=P(t),r=Math.cos(e);return Math.abs(r)<.1?\"middle\":r>0?\"start\":\"end\"},I.heightFn=function(t,e,r){var n=P(t);return-.5*(1+Math.sin(n))*r};var z=function(t){return o(x[0]+m*Math.cos(t),x[1]-m*Math.sin(t))};u=function(t){return z(P(t))};if(c=h.calcTicks(a),f=h.getTickSigns(a)[2],a.visible){f=\"inside\"===a.ticks?-1:1;var D=(a.linewidth||1)/2;h.drawTicks(t,a,{vals:c,layer:k,path:\"M\"+f*D+\",0h\"+f*a.ticklen,transFn:function(t){var e=P(t);return z(e)+\"rotate(\"+-s(e)+\")\"}}),h.drawLabels(t,a,{vals:c,layer:k,transFn:u,labelFns:I})}var R=[v].concat(p.gauge.steps),F=T.selectAll(\"g.bg-arc\").data(R);F.enter().append(\"g\").classed(\"bg-arc\",!0).append(\"path\"),F.select(\"path\").call(C).call(_),F.exit().remove();var B=L(p.gauge.bar.thickness),N=T.selectAll(\"g.value-arc\").data([p.gauge.bar]);N.enter().append(\"g\").classed(\"value-arc\",!0).append(\"path\");var j=N.select(\"path\");b(M)?(j.transition().duration(M.duration).ease(M.easing).each(\"end\",(function(){A&&A()})).each(\"interrupt\",(function(){A&&A()})).attrTween(\"d\",(U=B,V=E(r[0].lastY),q=E(r[0].y),function(){var t=n.interpolate(V,q);return function(e){return U.endAngle(t(e))()}})),p._lastValue=r[0].y):j.attr(\"d\",\"number\"==typeof r[0].y?B.endAngle(E(r[0].y)):\"M0,0Z\");var U,V,q;j.call(_),N.exit().remove(),R=[];var H=p.gauge.threshold.value;(H||0===H)&&R.push({range:[H,H],color:p.gauge.threshold.color,line:{color:p.gauge.threshold.line.color,width:p.gauge.threshold.line.width},thickness:p.gauge.threshold.thickness});var G=T.selectAll(\"g.threshold-arc\").data(R);G.enter().append(\"g\").classed(\"threshold-arc\",!0).append(\"path\"),G.select(\"path\").call(C).call(_),G.exit().remove();var Y=T.selectAll(\"g.gauge-outline\").data([y]);Y.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"path\"),Y.select(\"path\").call(C).call(_),Y.exit().remove()}(t,0,e,{radius:N,innerRadius:j,gauge:H,layer:G,size:R,gaugeBg:E,gaugeOutline:L,transitionOpts:r,onComplete:d});var Y=P.selectAll(\"g.bullet\").data(z?e:[]);Y.exit().remove();var W=P.selectAll(\"g.bulletaxis\").data(z?e:[]);W.exit().remove(),z&&function(t,e,r,n){var i,a,s,l,c,f=r[0].trace,p=n.gauge,d=n.layer,m=n.gaugeBg,v=n.gaugeOutline,y=n.size,x=f.domain,T=n.transitionOpts,k=n.onComplete;p.enter().append(\"g\").classed(\"bullet\",!0),p.attr(\"transform\",o(y.l,y.t)),d.enter().append(\"g\").classed(\"bulletaxis\",!0).classed(\"crisp\",!0),d.selectAll(\"g.xbulletaxistick,path,text\").remove();var M=y.h,A=f.gauge.bar.thickness*M,S=x.x[0],E=x.x[0]+(x.x[1]-x.x[0])*(f._hasNumber||f._hasDelta?1-u.bulletNumberDomainSize:1);(i=w(t,f.gauge.axis))._id=\"xbulletaxis\",i.domain=[S,E],i.setScale(),a=h.calcTicks(i),s=h.makeTransTickFn(i),l=h.getTickSigns(i)[2],c=y.t+y.h,i.visible&&(h.drawTicks(t,i,{vals:\"inside\"===i.ticks?h.clipEnds(i,a):a,layer:d,path:h.makeTickPath(i,c,l),transFn:s}),h.drawLabels(t,i,{vals:a,layer:d,transFn:s,labelFns:h.makeLabelFns(i,c)}));function L(t){t.attr(\"width\",(function(t){return Math.max(0,i.c2p(t.range[1])-i.c2p(t.range[0]))})).attr(\"x\",(function(t){return i.c2p(t.range[0])})).attr(\"y\",(function(t){return.5*(1-t.thickness)*M})).attr(\"height\",(function(t){return t.thickness*M}))}var C=[m].concat(f.gauge.steps),P=p.selectAll(\"g.bg-bullet\").data(C);P.enter().append(\"g\").classed(\"bg-bullet\",!0).append(\"rect\"),P.select(\"rect\").call(L).call(_),P.exit().remove();var I=p.selectAll(\"g.value-bullet\").data([f.gauge.bar]);I.enter().append(\"g\").classed(\"value-bullet\",!0).append(\"rect\"),I.select(\"rect\").attr(\"height\",A).attr(\"y\",(M-A)/2).call(_),b(T)?I.select(\"rect\").transition().duration(T.duration).ease(T.easing).each(\"end\",(function(){k&&k()})).each(\"interrupt\",(function(){k&&k()})).attr(\"width\",Math.max(0,i.c2p(Math.min(f.gauge.axis.range[1],r[0].y)))):I.select(\"rect\").attr(\"width\",\"number\"==typeof r[0].y?Math.max(0,i.c2p(Math.min(f.gauge.axis.range[1],r[0].y))):0);I.exit().remove();var O=r.filter((function(){return f.gauge.threshold.value||0===f.gauge.threshold.value})),z=p.selectAll(\"g.threshold-bullet\").data(O);z.enter().append(\"g\").classed(\"threshold-bullet\",!0).append(\"line\"),z.select(\"line\").attr(\"x1\",i.c2p(f.gauge.threshold.value)).attr(\"x2\",i.c2p(f.gauge.threshold.value)).attr(\"y1\",(1-f.gauge.threshold.thickness)/2*M).attr(\"y2\",(1-(1-f.gauge.threshold.thickness)/2)*M).call(g.stroke,f.gauge.threshold.line.color).style(\"stroke-width\",f.gauge.threshold.line.width),z.exit().remove();var D=p.selectAll(\"g.gauge-outline\").data([v]);D.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"rect\"),D.select(\"rect\").call(L).call(_),D.exit().remove()}(t,0,e,{gauge:Y,layer:W,size:R,gaugeBg:E,gaugeOutline:L,transitionOpts:r,onComplete:d});var X=P.selectAll(\"text.title\").data(e);X.exit().remove(),X.enter().append(\"text\").classed(\"title\",!0),X.attr(\"text-anchor\",(function(){return z?v.right:v[C.title.align]})).text(C.title.text).call(c.font,C.title.font).call(f.convertToTspans,t),X.attr(\"transform\",(function(){var t,e=R.l+R.w*y[C.title.align],r=u.titlePadding,n=c.bBox(X.node());if(I){if(O)if(C.gauge.axis.visible)t=c.bBox(G.node()).top-r-n.bottom;else t=R.t+R.h/2-N/2-n.bottom-r;z&&(t=A-(n.top+n.bottom)/2,e=R.l-u.bulletPadding*R.w)}else t=C._numbersTop-r-n.bottom;return o(e,t)}))}))}},{\"../../components/color\":662,\"../../components/drawing\":684,\"../../constants/alignment\":767,\"../../lib\":799,\"../../lib/svg_text_utils\":824,\"../../plots/cartesian/axes\":849,\"../../plots/cartesian/axis_defaults\":851,\"../../plots/cartesian/layout_attributes\":864,\"../../plots/cartesian/position_defaults\":867,\"./constants\":1146,\"@plotly/d3\":58}],1150:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../mesh3d/attributes\"),s=t(\"../../plots/attributes\"),l=t(\"../../lib/extend\").extendFlat,c=t(\"../../plot_api/edit_types\").overrideAll;var u=e.exports=c(l({x:{valType:\"data_array\"},y:{valType:\"data_array\"},z:{valType:\"data_array\"},value:{valType:\"data_array\"},isomin:{valType:\"number\"},isomax:{valType:\"number\"},surface:{show:{valType:\"boolean\",dflt:!0},count:{valType:\"integer\",dflt:2,min:1},fill:{valType:\"number\",min:0,max:1,dflt:1},pattern:{valType:\"flaglist\",flags:[\"A\",\"B\",\"C\",\"D\",\"E\"],extras:[\"all\",\"odd\",\"even\"],dflt:\"all\"}},spaceframe:{show:{valType:\"boolean\",dflt:!1},fill:{valType:\"number\",min:0,max:1,dflt:.15}},slices:{x:{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}},y:{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}},z:{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}}},caps:{x:{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}},y:{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}},z:{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}}},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:a(),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),valuehoverformat:i(\"value\",1),showlegend:l({},s.showlegend,{dflt:!1})},n(\"\",{colorAttr:\"`value`\",showScaleDflt:!0,editTypeOverride:\"calc\"}),{opacity:o.opacity,lightposition:o.lightposition,lighting:o.lighting,flatshading:o.flatshading,contour:o.contour,hoverinfo:l({},s.hoverinfo)}),\"calc\",\"nested\");u.flatshading.dflt=!0,u.lighting.facenormalsepsilon.dflt=0,u.x.editType=u.y.editType=u.z.editType=u.value.editType=\"calc+clearAxisTypes\",u.transforms=void 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0===e.isomax||null===e.isomin?s:e.isomax,n(t,e,{vals:[e._vMin,e._vMax],containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":670,\"../streamtube/calc\":1322}],1152:[function(t,e,r){\"use strict\";var n=t(\"gl-mesh3d\"),i=t(\"../../lib/gl_format_color\").parseColorScale,a=t(\"../../lib/str2rgbarray\"),o=t(\"../../components/colorscale\").extractOpts,s=t(\"../../plots/gl3d/zip3\"),l=function(t,e){for(var r=e.length-1;r>0;r--){var n=Math.min(e[r],e[r-1]),i=Math.max(e[r],e[r-1]);if(i>n&&n<t&&t<=i)return{id:r,distRatio:(i-t)/(i-n)}}return{id:0,distRatio:0}};function c(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.data=null,this.showContour=!1}var u=c.prototype;u.handlePick=function(t){if(t.object===this.mesh){var e=t.data.index,r=this.data._meshX[e],n=this.data._meshY[e],i=this.data._meshZ[e],a=this.data._Ys.length,o=this.data._Zs.length,s=l(r,this.data._Xs).id,c=l(n,this.data._Ys).id,u=l(i,this.data._Zs).id,f=t.index=u+o*c+o*a*s;t.traceCoordinate=[this.data._meshX[f],this.data._meshY[f],this.data._meshZ[f],this.data._value[f]];var h=this.data.hovertext||this.data.text;return Array.isArray(h)&&void 0!==h[f]?t.textLabel=h[f]:h&&(t.textLabel=h),!0}},u.update=function(t){var e=this.scene,r=e.fullSceneLayout;function n(t,e,r,n){return e.map((function(e){return t.d2l(e,0,n)*r}))}this.data=h(t);var l={positions:s(n(r.xaxis,t._meshX,e.dataScale[0],t.xcalendar),n(r.yaxis,t._meshY,e.dataScale[1],t.ycalendar),n(r.zaxis,t._meshZ,e.dataScale[2],t.zcalendar)),cells:s(t._meshI,t._meshJ,t._meshK),lightPosition:[t.lightposition.x,t.lightposition.y,t.lightposition.z],ambient:t.lighting.ambient,diffuse:t.lighting.diffuse,specular:t.lighting.specular,roughness:t.lighting.roughness,fresnel:t.lighting.fresnel,vertexNormalsEpsilon:t.lighting.vertexnormalsepsilon,faceNormalsEpsilon:t.lighting.facenormalsepsilon,opacity:t.opacity,contourEnable:t.contour.show,contourColor:a(t.contour.color).slice(0,3),contourWidth:t.contour.width,useFacetNormals:t.flatshading},c=o(t);l.vertexIntensity=t._meshIntensity,l.vertexIntensityBounds=[c.min,c.max],l.colormap=i(t),this.mesh.update(l)},u.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()};var f=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"];function h(t){t._meshI=[],t._meshJ=[],t._meshK=[];var 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v={positions:h,cells:n,lightPosition:[t.lightposition.x,t.lightposition.y,t.lightposition.z],ambient:t.lighting.ambient,diffuse:t.lighting.diffuse,specular:t.lighting.specular,roughness:t.lighting.roughness,fresnel:t.lighting.fresnel,vertexNormalsEpsilon:t.lighting.vertexnormalsepsilon,faceNormalsEpsilon:t.lighting.facenormalsepsilon,opacity:t.opacity,contourEnable:t.contour.show,contourColor:l(t.contour.color).slice(0,3),contourWidth:t.contour.width,useFacetNormals:t.flatshading};if(t.intensity){var y=c(t);this.color=\"#fff\";var x=t.intensitymode;v[x+\"Intensity\"]=t.intensity,v[x+\"IntensityBounds\"]=[y.min,y.max],v.colormap=s(t)}else t.vertexcolor?(this.color=t.vertexcolor[0],v.vertexColors=p(t.vertexcolor)):t.facecolor?(this.color=t.facecolor[0],v.cellColors=p(t.facecolor)):(this.color=t.color,v.meshColor=l(t.color));this.mesh.update(v)},h.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},e.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new 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i=r(\"values\"),a=r(\"visible\");if(i&&i.length||(a=e.visible=!1),a){r(\"label\"),r(\"displayindex\",e._index);var o,s=t.categoryarray,c=Array.isArray(s)&&s.length>0;c&&(o=\"array\");var u=r(\"categoryorder\",o);\"array\"===u?(r(\"categoryarray\"),r(\"ticktext\")):(delete t.categoryarray,delete t.ticktext),c||\"array\"!==u||(e.categoryorder=\"trace\")}}e.exports=function(t,e,r,f){function h(r,i){return n.coerce(t,e,l,r,i)}var p=s(t,e,{name:\"dimensions\",handleItemDefaults:u}),d=function(t,e,r,o,s){s(\"line.shape\"),s(\"line.hovertemplate\");var l=s(\"line.color\",o.colorway[0]);if(i(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),a(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,f,h);o(e,f,h),Array.isArray(p)&&p.length||(e.visible=!1),c(e,p,\"values\",d),h(\"hoveron\"),h(\"hovertemplate\"),h(\"arrangement\"),h(\"bundlecolors\"),h(\"sortpaths\"),h(\"counts\");var 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n=t(\"@plotly/d3\"),i=t(\"../../plot_api/plot_api\"),a=t(\"../../components/fx\"),o=t(\"../../lib\"),s=o.strTranslate,l=t(\"../../components/drawing\"),c=t(\"tinycolor2\"),u=t(\"../../lib/svg_text_utils\");function f(t,e,r,i){var a=t.map(R.bind(0,e,r)),c=i.selectAll(\"g.parcatslayer\").data([null]);c.enter().append(\"g\").attr(\"class\",\"parcatslayer\").style(\"pointer-events\",\"all\");var f=c.selectAll(\"g.trace.parcats\").data(a,h),v=f.enter().append(\"g\").attr(\"class\",\"trace parcats\");f.attr(\"transform\",(function(t){return s(t.x,t.y)})),v.append(\"g\").attr(\"class\",\"paths\");var y=f.select(\"g.paths\").selectAll(\"path.path\").data((function(t){return t.paths}),h);y.attr(\"fill\",(function(t){return t.model.color}));var _=y.enter().append(\"path\").attr(\"class\",\"path\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",0);b(_),y.attr(\"d\",(function(t){return t.svgD})),_.empty()||y.sort(d),y.exit().remove(),y.on(\"mouseover\",m).on(\"mouseout\",g).on(\"click\",x),v.append(\"g\").attr(\"class\",\"dimensions\");var k=f.select(\"g.dimensions\").selectAll(\"g.dimension\").data((function(t){return t.dimensions}),h);k.enter().append(\"g\").attr(\"class\",\"dimension\"),k.attr(\"transform\",(function(t){return s(t.x,0)})),k.exit().remove();var M=k.selectAll(\"g.category\").data((function(t){return t.categories}),h),A=M.enter().append(\"g\").attr(\"class\",\"category\");M.attr(\"transform\",(function(t){return s(0,t.y)})),A.append(\"rect\").attr(\"class\",\"catrect\").attr(\"pointer-events\",\"none\"),M.select(\"rect.catrect\").attr(\"fill\",\"none\").attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})),w(A);var S=M.selectAll(\"rect.bandrect\").data((function(t){return t.bands}),h);S.each((function(){o.raiseToTop(this)})),S.attr(\"fill\",(function(t){return t.color}));var O=S.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);S.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})).attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"})),T(O),S.exit().remove(),A.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var z=e._fullLayout.paper_bgcolor;M.select(\"text.catlabel\").attr(\"text-anchor\",(function(t){return p(t)?\"start\":\"end\"})).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",u.makeTextShadow(z)).style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",(function(t){return p(t)?t.width+5:-5})).attr(\"y\",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){l.font(n.select(this),t.parcatsViewModel.categorylabelfont),u.convertToTspans(n.select(this),e)})),A.append(\"text\").attr(\"class\",\"dimlabel\"),M.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"})).attr(\"x\",(function(t){return t.width/2})).attr(\"y\",-5).text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){l.font(n.select(this),t.parcatsViewModel.labelfont)})),M.selectAll(\"rect.bandrect\").on(\"mouseover\",E).on(\"mouseout\",L),M.exit().remove(),k.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on(\"dragstart\",C).on(\"drag\",P).on(\"dragend\",I)),f.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")})),f.exit().remove()}function h(t){return t.key}function p(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function d(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function m(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){o.raiseToTop(this),_(n.select(this));var e=v(t),r=y(t);if(t.parcatsViewModel.graphDiv.emit(\"plotly_hover\",{points:e,event:n.event,constraints:r}),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\")){var i,s,l,u=n.mouse(this)[0],f=t.parcatsViewModel.graphDiv,h=t.parcatsViewModel.trace,p=f._fullLayout,d=p._paperdiv.node().getBoundingClientRect(),m=t.parcatsViewModel.graphDiv.getBoundingClientRect();for(l=0;l<t.leftXs.length-1;l++)if(t.leftXs[l]+t.dimWidths[l]-2<=u&&u<=t.leftXs[l+1]+2){var g=t.parcatsViewModel.dimensions[l],x=t.parcatsViewModel.dimensions[l+1];i=(g.x+g.width+x.x)/2,s=(t.topYs[l]+t.topYs[l+1]+t.height)/2;break}var b=t.parcatsViewModel.x+i,w=t.parcatsViewModel.y+s,T=c.mostReadable(t.model.color,[\"black\",\"white\"]),k=t.model.count,M=k/t.parcatsViewModel.model.count,A={countLabel:k,probabilityLabel:M.toFixed(3)},S=[];-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&S.push([\"Count:\",A.countLabel].join(\" \")),-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&S.push([\"P:\",A.probabilityLabel].join(\" \"));var E=S.join(\"<br>\"),L=n.mouse(f)[0];a.loneHover({trace:h,x:b-d.left+m.left,y:w-d.top+m.top,text:E,color:t.model.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:10,fontColor:T,idealAlign:L<b?\"right\":\"left\",hovertemplate:(h.line||{}).hovertemplate,hovertemplateLabels:A,eventData:[{data:h._input,fullData:h,count:k,probability:M}]},{container:p._hoverlayer.node(),outerContainer:p._paper.node(),gd:f})}}}function g(t){if(!t.parcatsViewModel.dragDimension&&(b(n.select(this)),a.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(d),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\"))){var e=v(t),r=y(t);t.parcatsViewModel.graphDiv.emit(\"plotly_unhover\",{points:e,event:n.event,constraints:r})}}function v(t){for(var e=[],r=O(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var i=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:i})}return e}function y(t){for(var e={},r=t.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var i=r[n],a=i.categories[t.model.categoryInds[n]];e[i.containerInd]=a.categoryValue}return void 0!==t.model.rawColor&&(e.color=t.model.rawColor),e}function x(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){var e=v(t),r=y(t);t.parcatsViewModel.graphDiv.emit(\"plotly_click\",{points:e,event:n.event,constraints:r})}}function b(t){t.attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",.6).attr(\"stroke\",\"lightgray\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1)}function _(t){t.attr(\"fill-opacity\",.8).attr(\"stroke\",(function(t){return c.mostReadable(t.model.color,[\"black\",\"white\"])})).attr(\"stroke-width\",.3)}function w(t){t.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",1).attr(\"stroke-opacity\",1)}function T(t){t.attr(\"stroke\",\"black\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1).attr(\"fill-opacity\",1)}function k(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter((function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color}))}function M(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=n.select(t.parentNode).selectAll(\"rect.bandrect\"),l=[];s.each((function(t){k(t).each((function(t){Array.prototype.push.apply(l,v(t))}))}));var c={};c[a.dimensionInd]=a.categoryValue,o.emit(e,{points:l,event:r,constraints:c})}function A(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=k(i),l=[];s.each((function(t){Array.prototype.push.apply(l,v(t))}));var c={};c[a.dimensionInd]=a.categoryValue,void 0!==i.rawColor&&(c.color=i.rawColor),o.emit(e,{points:l,event:r,constraints:c})}function S(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=n.select(r.parentNode).select(\"rect.catrect\"),c=l.node().getBoundingClientRect(),u=l.datum(),f=u.parcatsViewModel,h=f.model.dimensions[u.model.dimensionInd],p=f.trace,d=c.top+c.height/2;f.dimensions.length>1&&h.displayInd===f.dimensions.length-1?(i=c.left,a=\"left\"):(i=c.left+c.width,a=\"right\");var m=u.model.count,g=u.model.categoryLabel,v=m/u.parcatsViewModel.model.count,y={countLabel:m,categoryLabel:g,probabilityLabel:v.toFixed(3)},x=[];-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&x.push([\"Count:\",y.countLabel].join(\" \")),-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&x.push([\"P(\"+y.categoryLabel+\"):\",y.probabilityLabel].join(\" \"));var b=x.join(\"<br>\");return{trace:p,x:o*(i-e.left),y:s*(d-e.top),text:b,color:\"lightgray\",borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:12,fontColor:\"black\",idealAlign:a,hovertemplate:p.hovertemplate,hovertemplateLabels:y,eventData:[{data:p._input,fullData:p,count:m,category:g,probability:v}]}}function E(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){if(n.mouse(this)[1]<-1)return;var e,r=t.parcatsViewModel.graphDiv,i=r._fullLayout,s=i._paperdiv.node().getBoundingClientRect(),l=t.parcatsViewModel.hoveron;if(\"color\"===l?(!function(t){var e=n.select(t).datum(),r=k(e);_(r),r.each((function(){o.raiseToTop(this)})),n.select(t.parentNode).selectAll(\"rect.bandrect\").filter((function(t){return t.color===e.color})).each((function(){o.raiseToTop(this),n.select(this).attr(\"stroke\",\"black\").attr(\"stroke-width\",1.5)}))}(this),A(this,\"plotly_hover\",n.event)):(!function(t){n.select(t.parentNode).selectAll(\"rect.bandrect\").each((function(t){var e=k(t);_(e),e.each((function(){o.raiseToTop(this)}))})),n.select(t.parentNode).select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",2.5)}(this),M(this,\"plotly_hover\",n.event)),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\"))\"category\"===l?e=S(r,s,this):\"color\"===l?e=function(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=r.getBoundingClientRect(),u=n.select(r).datum(),f=u.categoryViewModel,h=f.parcatsViewModel,p=h.model.dimensions[f.model.dimensionInd],d=h.trace,m=l.y+l.height/2;h.dimensions.length>1&&p.displayInd===h.dimensions.length-1?(i=l.left,a=\"left\"):(i=l.left+l.width,a=\"right\");var g=f.model.categoryLabel,v=u.parcatsViewModel.model.count,y=0;u.categoryViewModel.bands.forEach((function(t){t.color===u.color&&(y+=t.count)}));var x=f.model.count,b=0;h.pathSelection.each((function(t){t.model.color===u.color&&(b+=t.model.count)}));var _=y/v,w=y/b,T=y/x,k={countLabel:v,categoryLabel:g,probabilityLabel:_.toFixed(3)},M=[];-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&M.push([\"Count:\",k.countLabel].join(\" \")),-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&(M.push(\"P(color \\u2229 \"+g+\"): \"+k.probabilityLabel),M.push(\"P(\"+g+\" | color): \"+w.toFixed(3)),M.push(\"P(color | \"+g+\"): \"+T.toFixed(3)));var A=M.join(\"<br>\"),S=c.mostReadable(u.color,[\"black\",\"white\"]);return{trace:d,x:o*(i-e.left),y:s*(m-e.top),text:A,color:u.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontColor:S,fontSize:10,idealAlign:a,hovertemplate:d.hovertemplate,hovertemplateLabels:k,eventData:[{data:d._input,fullData:d,category:g,count:v,probability:_,categorycount:x,colorcount:b,bandcolorcount:y}]}}(r,s,this):\"dimension\"===l&&(e=function(t,e,r){var i=[];return n.select(r.parentNode.parentNode).selectAll(\"g.category\").select(\"rect.catrect\").each((function(){i.push(S(t,e,this))})),i}(r,s,this)),e&&a.loneHover(e,{container:i._hoverlayer.node(),outerContainer:i._paper.node(),gd:r})}}function L(t){var e=t.parcatsViewModel;if(!e.dragDimension&&(b(e.pathSelection),w(e.dimensionSelection.selectAll(\"g.category\")),T(e.dimensionSelection.selectAll(\"g.category\").selectAll(\"rect.bandrect\")),a.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(d),-1===e.hoverinfoItems.indexOf(\"skip\"))){\"color\"===t.parcatsViewModel.hoveron?A(this,\"plotly_unhover\",n.event):M(this,\"plotly_unhover\",n.event)}}function C(t){\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll(\"g.category\").select(\"rect.catrect\").each((function(e){var r=n.mouse(this)[0],i=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=i&&i<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map((function(t){return t.displayInd})),e.model.dragY=e.y,o.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll(\"rect.bandrect\").each((function(e){e.y<i&&i<=e.y+e.height&&(t.potentialClickBand=this)})))})),t.parcatsViewModel.dragDimension=t,a.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function P(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragHasMoved=!0,null!==t.dragDimensionDisplayInd)){var e=t.dragDimensionDisplayInd,r=e-1,i=e+1,a=t.parcatsViewModel.dimensions[e];if(null!==t.dragCategoryDisplayInd){var o=a.categories[t.dragCategoryDisplayInd];o.model.dragY+=n.event.dy;var s=o.model.dragY,l=o.model.displayInd,c=a.categories,u=c[l-1],f=c[l+1];void 0!==u&&s<u.y+u.height/2&&(o.model.displayInd=u.model.displayInd,u.model.displayInd=l),void 0!==f&&s+o.height>f.y+f.height/2&&(o.model.displayInd=f.model.displayInd,f.model.displayInd=l),t.dragCategoryDisplayInd=o.model.displayInd}if(null===t.dragCategoryDisplayInd||\"freeform\"===t.parcatsViewModel.arrangement){a.model.dragX=n.event.x;var h=t.parcatsViewModel.dimensions[r],p=t.parcatsViewModel.dimensions[i];void 0!==h&&a.model.dragX<h.x+h.width&&(a.model.displayInd=h.model.displayInd,h.model.displayInd=e),void 0!==p&&a.model.dragX+a.width>p.x&&(a.model.displayInd=p.model.displayInd,p.model.displayInd=t.dragDimensionDisplayInd),t.dragDimensionDisplayInd=a.model.displayInd}N(t.parcatsViewModel),B(t.parcatsViewModel),D(t.parcatsViewModel),z(t.parcatsViewModel)}}function I(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&null!==t.dragDimensionDisplayInd){n.select(this).selectAll(\"text\").attr(\"font-weight\",\"normal\");var e={},r=O(t.parcatsViewModel),a=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),o=t.initialDragDimensionDisplayInds.some((function(t,e){return t!==a[e]}));o&&a.forEach((function(r,n){var i=t.parcatsViewModel.model.dimensions[n].containerInd;e[\"dimensions[\"+i+\"].displayindex\"]=r}));var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map((function(t){return t.displayInd}));if(s=t.initialDragCategoryDisplayInds.some((function(t,e){return t!==l[e]}))){var c=t.model.categories.slice().sort((function(t,e){return t.displayInd-e.displayInd})),u=c.map((function(t){return t.categoryValue})),f=c.map((function(t){return t.categoryLabel}));e[\"dimensions[\"+t.model.containerInd+\"].categoryarray\"]=[u],e[\"dimensions[\"+t.model.containerInd+\"].ticktext\"]=[f],e[\"dimensions[\"+t.model.containerInd+\"].categoryorder\"]=\"array\"}}if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")&&!t.dragHasMoved&&t.potentialClickBand&&(\"color\"===t.parcatsViewModel.hoveron?A(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent):M(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd)t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null;t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,N(t.parcatsViewModel),B(t.parcatsViewModel),n.transition().duration(300).ease(\"cubic-in-out\").each((function(){D(t.parcatsViewModel,!0),z(t.parcatsViewModel,!0)})).each(\"end\",(function(){(o||s)&&i.restyle(t.parcatsViewModel.graphDiv,e,[r])}))}}function O(t){for(var e,r=t.graphDiv._fullData,n=0;n<r.length;n++)if(t.key===r[n].uid){e=n;break}return e}function z(t,e){var r;void 0===e&&(e=!1),t.pathSelection.data((function(t){return t.paths}),h),(r=t.pathSelection,e?r.transition():r).attr(\"d\",(function(t){return t.svgD}))}function D(t,e){function r(t){return e?t.transition():t}void 0===e&&(e=!1),t.dimensionSelection.data((function(t){return t.dimensions}),h);var i=t.dimensionSelection.selectAll(\"g.category\").data((function(t){return t.categories}),h);r(t.dimensionSelection).attr(\"transform\",(function(t){return s(t.x,0)})),r(i).attr(\"transform\",(function(t){return s(0,t.y)})),i.select(\".dimlabel\").text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})),i.select(\".catlabel\").attr(\"text-anchor\",(function(t){return p(t)?\"start\":\"end\"})).attr(\"x\",(function(t){return p(t)?t.width+5:-5})).each((function(t){var e,r;p(t)?(e=t.width+5,r=\"start\"):(e=-5,r=\"end\"),n.select(this).selectAll(\"tspan\").attr(\"x\",e).attr(\"text-anchor\",r)}));var a=i.selectAll(\"rect.bandrect\").data((function(t){return t.bands}),h),l=a.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"cursor\",\"move\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);a.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})),T(l),a.each((function(){o.raiseToTop(this)})),a.exit().remove()}function R(t,e,r){var n,i=r[0],a=e.margin||{l:80,r:80,t:100,b:80},o=i.trace,s=o.domain,l=e.width,c=e.height,u=Math.floor(l*(s.x[1]-s.x[0])),f=Math.floor(c*(s.y[1]-s.y[0])),h=s.x[0]*l+a.l,p=e.height-s.y[1]*e.height+a.t,d=o.line.shape;n=\"all\"===o.hoverinfo?[\"count\",\"probability\"]:(o.hoverinfo||\"\").split(\"+\");var 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n=t(\"./parcats\");e.exports=function(t,e,r,i){var a=t._fullLayout,o=a._paper,s=a._size;n(t,o,e,{width:s.w,height:s.h,margin:{t:s.t,r:s.r,b:s.b,l:s.l}},r,i)}},{\"./parcats\":1174}],1176:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/layout_attributes\"),a=t(\"../../plots/font_attributes\"),o=t(\"../../plots/domain\").attributes,s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/plot_template\").templatedArray;e.exports={domain:o({name:\"parcoords\",trace:!0,editType:\"plot\"}),labelangle:{valType:\"angle\",dflt:0,editType:\"plot\"},labelside:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},labelfont:a({editType:\"plot\"}),tickfont:a({editType:\"plot\"}),rangefont:a({editType:\"plot\"}),dimensions:l(\"dimension\",{label:{valType:\"string\",editType:\"plot\"},tickvals:s({},i.tickvals,{editType:\"plot\"}),ticktext:s({},i.ticktext,{editType:\"plot\"}),tickformat:s({},i.tickformat,{editType:\"plot\"}),visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},range:{valType:\"info_array\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},constraintrange:{valType:\"info_array\",freeLength:!0,dimensions:\"1-2\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},multiselect:{valType:\"boolean\",dflt:!0,editType:\"plot\"},values:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"}),line:s({editType:\"calc\"},n(\"line\",{colorscaleDflt:\"Viridis\",autoColorDflt:!1,editTypeOverride:\"calc\"}))}},{\"../../components/colorscale/attributes\":669,\"../../lib/extend\":789,\"../../plot_api/plot_template\":838,\"../../plots/cartesian/layout_attributes\":864,\"../../plots/domain\":877,\"../../plots/font_attributes\":878}],1177:[function(t,e,r){\"use 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r=e.brush,n=r.filter,a=r.svgBrush;a._dragging||(T(t,e),w(t,e),e.brush.svgBrush.wasDragged=!1),a._dragging=!1,i.event.sourceEvent.stopPropagation();var o=a.grabbingBar;if(a.grabbingBar=!1,a.grabLocation=void 0,e.parent.inBrushDrag=!1,y(),!a.wasDragged)return a.wasDragged=void 0,a.clickableOrdinalRange?r.filterSpecified&&e.multiselect?a.extent.push(a.clickableOrdinalRange):(a.extent=[a.clickableOrdinalRange],r.filterSpecified=!0):o?(a.extent=a.stayingIntervals,0===a.extent.length&&A(r)):A(r),a.brushCallback(e),b(t.parentNode),void a.brushEndCallback(r.filterSpecified?n.getConsolidated():[]);var s=function(){n.set(n.getConsolidated())};if(e.ordinal){var l=e.unitTickvals;l[l.length-1]<l[0]&&l.reverse(),a.newExtent=[p(0,l,a.newExtent[0],a.stayingIntervals),p(1,l,a.newExtent[1],a.stayingIntervals)];var c=a.newExtent[1]>a.newExtent[0];a.extent=a.stayingIntervals.concat(c?[a.newExtent]:[]),a.extent.length||A(r),a.brushCallback(e),c?b(t.parentNode,s):(s(),b(t.parentNode))}else 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a=t.selectAll(\".highlight\").data(o);a.enter().append(\"line\").classed(\"highlight\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width-n.bar.strokeWidth).attr(\"stroke\",n.bar.fillColor).attr(\"opacity\",n.bar.fillOpacity).attr(\"stroke-linecap\",\"butt\"),a.attr(\"y1\",(function(t){return t.height})).call(x)}(r,e)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map((function(t){return t.sort(s)})),t=e.multiselect?S(t.sort(M)):[t[0]]):t=[t.sort(s)],e.tickvals){var r=e.tickvals.slice().sort(s);if(!(t=t.map((function(t){var e=[p(0,r,t[0],[]),p(1,r,t[1],[])];if(e[1]>e[0])return e})).filter((function(t){return t}))).length)return}return t.length>1?t:t[0]}}},{\"../../lib\":799,\"../../lib/gup\":796,\"./constants\":1180,\"@plotly/d3\":58}],1178:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../plots/get_data\").getModuleCalcData,a=t(\"./plot\"),o=t(\"../../constants/xmlns_namespaces\");r.name=\"parcoords\",r.plot=function(t){var e=i(t.calcdata,\"parcoords\")[0];e.length&&a(t,e)},r.clean=function(t,e,r,n){var i=n._has&&n._has(\"parcoords\"),a=e._has&&e._has(\"parcoords\");i&&!a&&(n._paperdiv.selectAll(\".parcoords\").remove(),n._glimages.selectAll(\"*\").remove())},r.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(\".svg-container\");r.filter((function(t,e){return e===r.size()-1})).selectAll(\".gl-canvas-context, .gl-canvas-focus\").each((function(){var t=this.toDataURL(\"image/png\");e.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":t,preserveAspectRatio:\"none\",x:0,y:0,width:this.width,height:this.height})})),window.setTimeout((function(){n.selectAll(\"#filterBarPattern\").attr(\"id\",\"filterBarPattern\")}),60)}},{\"../../constants/xmlns_namespaces\":776,\"../../plots/get_data\":887,\"./plot\":1187,\"@plotly/d3\":58}],1179:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isArrayOrTypedArray,i=t(\"../../components/colorscale\"),a=t(\"../../lib/gup\").wrap;e.exports=function(t,e){var r,o;return i.hasColorscale(e,\"line\")&&n(e.line.color)?(r=e.line.color,o=i.extractOpts(e.line).colorscale,i.calc(t,e,{vals:r,containerStr:\"line\",cLetter:\"c\"})):(r=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=.5;return e}(e._length),o=[[0,e.line.color],[1,e.line.color]]),a({lineColor:r,cscale:o})}},{\"../../components/colorscale\":674,\"../../lib\":799,\"../../lib/gup\":796}],1180:[function(t,e,r){\"use 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n=t(\"../../lib\").isTypedArray;r.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},r.isOrdinal=function(t){return!!t.tickvals},r.isVisible=function(t){return t.visible||!(\"visible\"in t)}},{\"../../lib\":799}],1183:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcoords\",basePlotModule:t(\"./base_plot\"),categories:[\"gl\",\"regl\",\"noOpacity\",\"noHover\"],meta:{}}},{\"./attributes\":1176,\"./base_plot\":1178,\"./calc\":1179,\"./defaults\":1181,\"./plot\":1187}],1184:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nattribute vec4 p01_04, p05_08, p09_12, p13_16,\\n               p17_20, p21_24, p25_28, p29_32,\\n               p33_36, p37_40, p41_44, p45_48,\\n               p49_52, p53_56, 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hi) {\\n    return (lo < hi) && (lo > p || p > hi);\\n}\\n\\nbool vOutside(vec4 p, vec4 lo, vec4 hi) {\\n    return (\\n        fOutside(p[0], lo[0], hi[0]) ||\\n        fOutside(p[1], lo[1], hi[1]) ||\\n        fOutside(p[2], lo[2], hi[2]) ||\\n        fOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\\n    return (\\n        vOutside(p[0], lo[0], hi[0]) ||\\n        vOutside(p[1], lo[1], hi[1]) ||\\n        vOutside(p[2], lo[2], hi[2]) ||\\n        vOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    return mOutside(A, loA, hiA) ||\\n           mOutside(B, loB, hiB) ||\\n           mOutside(C, loC, hiC) ||\\n           mOutside(D, loD, hiD);\\n}\\n\\nbool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    mat4 pnts[4];\\n    pnts[0] = A;\\n    pnts[1] = B;\\n    pnts[2] = C;\\n    pnts[3] = D;\\n\\n    for(int i = 0; i < 4; ++i) {\\n        for(int j = 0; j < 4; ++j) {\\n            for(int k = 0; k < 4; ++k) {\\n                if(0 == iMod(\\n                    int(255.0 * texture2D(mask,\\n                        vec2(\\n                            (float(i * 2 + j / 2) + 0.5) / 8.0,\\n                            (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\\n                        ))[3]\\n                    ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\\n                    2\\n                )) return true;\\n            }\\n        }\\n    }\\n    return false;\\n}\\n\\nvec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float x = 0.5 * sign(v) + 0.5;\\n    float y = axisY(x, A, B, C, D);\\n    float z = 1.0 - abs(v);\\n\\n    z += isContext ? 0.0 : 2.0 * float(\\n        outsideBoundingBox(A, B, C, D) ||\\n        outsideRasterMask(A, B, C, D)\\n    );\\n\\n    return vec4(\\n        2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\\n        z,\\n        1.0\\n    );\\n}\\n\\nvoid main() {\\n    mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\\n    mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\\n    mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\\n    mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\\n\\n    float v = colors[3];\\n\\n    gl_Position = position(isContext, v, A, B, C, D);\\n\\n    fragColor =\\n        isContext ? vec4(contextColor) :\\n        isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\\n}\\n\"]),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n    gl_FragColor = fragColor;\\n}\\n\"]),o=t(\"./constants\").maxDimensionCount,s=t(\"../../lib\"),l=new Uint8Array(4),c=new Uint8Array(4),u={shape:[256,1],format:\"rgba\",type:\"uint8\",mag:\"nearest\",min:\"nearest\"};function f(t,e,r,n,i){var a=t._gl;a.enable(a.SCISSOR_TEST),a.scissor(e,r,n,i),t.clear({color:[0,0,0,0],depth:1})}function h(t,e,r,n,i,a){var o=a.key;r.drawCompleted||(!function(t){t.read({x:0,y:0,width:1,height:1,data:l})}(t),r.drawCompleted=!0),function s(l){var c=Math.min(n,i-l*n);0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete r.currentRafs[o],f(t,a.scissorX,a.scissorY,a.scissorWidth,a.viewBoxSize[1])),r.clearOnly||(a.count=2*c,a.offset=2*l*n,e(a),l*n+c<i&&(r.currentRafs[o]=window.requestAnimationFrame((function(){s(l+1)}))),r.drawCompleted=!1)}(0)}function p(t,e){for(var r=new Array(256),n=0;n<256;n++)r[n]=t(n/255).concat(e);return r}function d(t,e){return(t>>>8*e)%256/255}function m(t,e,r){for(var n=new Array(8*e),i=0,a=0;a<e;a++)for(var o=0;o<2;o++)for(var s=0;s<4;s++){var l=4*t+s,c=r[64*a+l];63===l&&0===o&&(c*=-1),n[i++]=c}return n}function g(t){var e=\"0\"+t;return e.substr(e.length-2)}function v(t){return t<o?\"p\"+g(t+1)+\"_\"+g(t+4):\"colors\"}function y(t,e,r,n,i,a,o,l,c,u,f,h,p){for(var d=[[],[]],m=0;m<64;m++)d[0][m]=m===i?1:0,d[1][m]=m===a?1:0;var 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r,n,l,g,b,_=e.context,w=e.pick,T=e.regl,k={currentRafs:{},drawCompleted:!0,clearOnly:!1},M=function(t){for(var e={},r=0;r<=o;r+=4)e[v(r)]=t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)});return e}(T),A=T.texture(u),S=[];L(e);var E=T({profile:!1,blend:{enable:_,func:{srcRGB:\"src alpha\",dstRGB:\"one minus src 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L(t){r=t.model,n=t.viewModel,l=n.dimensions.slice(),g=l[0]?l[0].values.length:0;var e=r.lines,i=w?e.color.map((function(t,r){return r/e.color.length})):e.color,a=function(t,e,r){for(var n,i=new Array(t*(o+4)),a=0,s=0;s<t;s++){for(var l=0;l<o;l++)i[a++]=l<e.length?e[l].paddedUnitValues[s]:.5;i[a++]=d(s,2),i[a++]=d(s,1),i[a++]=d(s,0),i[a++]=(n=r[s],Math.max(1e-6,Math.min(.999999,n)))}return i}(g,l,i);!function(t,e,r){for(var n=0;n<=o;n+=4)t[v(n)](m(n/4,e,r))}(M,g,a),_||w||(A=T.texture(s.extendFlat({data:p(r.unitToColor,255)},u)))}return{render:function(t,e,n){var i,a,o,s=t.length,c=1/0,u=-1/0;for(i=0;i<s;i++)t[i].dim0.canvasX<c&&(c=t[i].dim0.canvasX,a=i),t[i].dim1.canvasX>u&&(u=t[i].dim1.canvasX,o=i);0===s&&f(T,0,0,r.canvasWidth,r.canvasHeight);var p=function(t){var e,r,n,i=[[],[]];for(n=0;n<64;n++){var a=!t&&n<l.length?l[n].brush.filter.getBounds():[-1/0,1/0];i[0][n]=a[0],i[1][n]=a[1]}var o=new Array(16384);for(e=0;e<16384;e++)o[e]=255;if(!t)for(e=0;e<l.length;e++){var s=e%8,c=(e-s)/8,u=Math.pow(2,s),f=l[e].brush.filter.get();if(!(f.length<2)){var h=x(f[0])[1];for(r=1;r<f.length;r++){var p=x(f[r]);for(n=h+1;n<p[0];n++)o[8*n+c]&=~u;h=Math.max(h,p[1])}}}var d={shape:[8,2048],format:\"alpha\",type:\"uint8\",mag:\"nearest\",min:\"nearest\",data:o};return b?b(d):b=T.texture(d),{maskTexture:b,maskHeight:2048,loA:i[0].slice(0,16),loB:i[0].slice(16,32),loC:i[0].slice(32,48),loD:i[0].slice(48,64),hiA:i[1].slice(0,16),hiB:i[1].slice(16,32),hiC:i[1].slice(32,48),hiD:i[1].slice(48,64)}}(_);for(i=0;i<s;i++){var d=t[i],m=d.dim0.crossfilterDimensionIndex,v=d.dim1.crossfilterDimensionIndex,M=d.canvasX,A=d.canvasY,L=M+d.panelSizeX;if(e||!S[m]||S[m][0]!==M||S[m][1]!==L){S[m]=[M,L];var C=y(r,a,o,i,m,v,M,A,d.panelSizeX,d.panelSizeY,d.dim0.crossfilterDimensionIndex,_?0:w?2:1,p);k.clearOnly=n;var P=e?r.lines.blockLineCount:g;h(T,E,k,P,g,C)}}},readPixel:function(t,e){return T.read({x:t,y:e,width:1,height:1,data:c}),c},readPixels:function(t,e,r,n){var i=new Uint8Array(4*r*n);return T.read({x:t,y:e,width:r,height:n,data:i}),i},destroy:function(){for(var e in t.style[\"pointer-events\"]=\"none\",A.destroy(),b&&b.destroy(),M)M[e].destroy()},update:L}}},{\"../../lib\":799,\"./constants\":1180,glslify:438}],1185:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){var i,a;for(n||(n=1/0),i=0;i<e.length;i++)(a=e[i]).visible&&(n=Math.min(n,a[r].length));for(n===1/0&&(n=0),t._length=n,i=0;i<e.length;i++)(a=e[i]).visible&&(a._length=n);return n}},{}],1186:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"color-rgba\"),a=t(\"../../plots/cartesian/axes\"),o=t(\"../../lib\"),s=o.strRotate,l=o.strTranslate,c=t(\"../../lib/svg_text_utils\"),u=t(\"../../components/drawing\"),f=t(\"../../components/colorscale\"),h=t(\"../../lib/gup\"),p=h.keyFun,d=h.repeat,m=h.unwrap,g=t(\"./helpers\"),v=t(\"./constants\"),y=t(\"./axisbrush\"),x=t(\"./lines\");function b(t,e,r){return o.aggNums(t,null,e,r)}function _(t,e){return T(b(Math.min,t,e),b(Math.max,t,e))}function w(t){var e=t.range;return e?T(e[0],e[1]):_(t.values,t._length)}function T(t,e){return!isNaN(t)&&isFinite(t)||(t=0),!isNaN(e)&&isFinite(e)||(e=0),t===e&&(0===t?(t-=1,e+=1):(t*=.9,e*=1.1)),[t,e]}function k(t,e,r,i,a){var o,s,l=w(r);return i?n.scale.ordinal().domain(i.map((o=n.format(r.tickformat),s=a,s?function(t,e){var r=s[e];return null==r?o(t):r}:o))).range(i.map((function(r){var n=(r-l[0])/(l[1]-l[0]);return t-e+n*(2*e-t)}))):n.scale.linear().domain(l).range([t-e,e])}function M(t){if(t.tickvals){var e=w(t);return n.scale.ordinal().domain(t.tickvals).range(t.tickvals.map((function(t){return(t-e[0])/(e[1]-e[0])})))}}function A(t){var e=t.map((function(t){return t[0]})),r=t.map((function(t){var e=i(t[1]);return n.rgb(\"rgb(\"+e[0]+\",\"+e[1]+\",\"+e[2]+\")\")})),a=\"rgb\".split(\"\").map((function(t){return n.scale.linear().clamp(!0).domain(e).range(r.map((i=t,function(t){return t[i]})));var i}));return function(t){return a.map((function(e){return e(t)}))}}function S(t){return t.dimensions.some((function(t){return t.brush.filterSpecified}))}function E(t,e,r){var 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L(t,e,r){var i=r.width,a=r.height,s=r.dimensions,l=r.canvasPixelRatio,c=function(t){return i*t/Math.max(1,r.colCount-1)},u=v.verticalPadding/a,f=function(t,e){return n.scale.linear().range([e,t-e])}(a,v.verticalPadding),h={key:r.key,xScale:c,model:r,inBrushDrag:!1},p={};return h.dimensions=s.filter(g.isVisible).map((function(i,s){var d=function(t,e){return n.scale.linear().domain(w(t)).range([e,1-e])}(i,u),m=p[i.label];p[i.label]=(m||0)+1;var x=i.label+(m?\"__\"+m:\"\"),b=i.constraintrange,_=b&&b.length;_&&!Array.isArray(b[0])&&(b=[b]);var T=_?b.map((function(t){return t.map(d)})):[[-1/0,1/0]],A=i.values;A.length>i._length&&(A=A.slice(0,i._length));var E,L=i.tickvals;function C(t,e){return{val:t,text:E[e]}}function P(t,e){return t.val-e.val}if(Array.isArray(L)&&L.length){E=i.ticktext,Array.isArray(E)&&E.length?E.length>L.length?E=E.slice(0,L.length):L.length>E.length&&(L=L.slice(0,E.length)):E=L.map(n.format(i.tickformat));for(var I=1;I<L.length;I++)if(L[I]<L[I-1]){for(var 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X=G.selectAll(\".\"+v.cn.axisExtentBottom).data(d,p);X.enter().append(\"g\").classed(v.cn.axisExtentBottom,!0),X.attr(\"transform\",(function(t){return l(0,t.model.height+v.axisExtentOffset)}));var Z=X.selectAll(\".\"+v.cn.axisExtentBottomText).data(d,p);Z.enter().append(\"text\").classed(v.cn.axisExtentBottomText,!0).attr(\"dy\",\"0.75em\").call(C),Z.text((function(t){return z(t,!1)})).each((function(t){u.font(n.select(this),t.model.rangeFont)})),y.ensureAxisBrush(U,w)}},{\"../../components/colorscale\":674,\"../../components/drawing\":684,\"../../lib\":799,\"../../lib/gup\":796,\"../../lib/svg_text_utils\":824,\"../../plots/cartesian/axes\":849,\"./axisbrush\":1177,\"./constants\":1180,\"./helpers\":1182,\"./lines\":1184,\"@plotly/d3\":58,\"color-rgba\":133}],1187:[function(t,e,r){\"use strict\";var n=t(\"./parcoords\"),i=t(\"../../lib/prepare_regl\"),a=t(\"./helpers\").isVisible;function o(t,e,r){var n=e.indexOf(r),i=t.indexOf(n);return-1===i&&(i+=e.length),i}e.exports=function(t,e){var r=t._fullLayout;if(i(t)){var s={},l={},c={},u={},f=r._size;e.forEach((function(e,r){var n=e[0].trace;c[r]=n.index;var i=u[r]=n._fullInput.index;s[r]=t.data[i].dimensions,l[r]=t.data[i].dimensions.slice()}));n(t,e,{width:f.w,height:f.h,margin:{t:f.t,r:f.r,b:f.b,l:f.l}},{filterChanged:function(e,n,i){var a=l[e][n],o=i.map((function(t){return t.slice()})),s=\"dimensions[\"+n+\"].constraintrange\",f=r._tracePreGUI[t._fullData[c[e]]._fullInput.uid];if(void 0===f[s]){var h=a.constraintrange;f[s]=h||null}var p=t._fullData[c[e]].dimensions[n];o.length?(1===o.length&&(o=o[0]),a.constraintrange=o,p.constraintrange=o.slice(),o=[o]):(delete a.constraintrange,delete p.constraintrange,o=null);var d={};d[s]=o,t.emit(\"plotly_restyle\",[d,[u[e]]])},hover:function(e){t.emit(\"plotly_hover\",e)},unhover:function(e){t.emit(\"plotly_unhover\",e)},axesMoved:function(e,r){var n=function(t,e){return function(r,n){return o(t,e,r)-o(t,e,n)}}(r,l[e].filter(a));s[e].sort(n),l[e].filter((function(t){return!a(t)})).sort((function(t){return l[e].indexOf(t)})).forEach((function(t){s[e].splice(s[e].indexOf(t),1),s[e].splice(l[e].indexOf(t),0,t)})),t.emit(\"plotly_restyle\",[{dimensions:[s[e]]},[u[e]]])}})}}},{\"../../lib/prepare_regl\":812,\"./helpers\":1182,\"./parcoords\":1186}],1188:[function(t,e,r){\"use strict\";var n=t(\"../../plots/attributes\"),i=t(\"../../plots/domain\").attributes,a=t(\"../../plots/font_attributes\"),o=t(\"../../components/color/attributes\"),s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../plots/template_attributes\").texttemplateAttrs,c=t(\"../../lib/extend\").extendFlat,u=a({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});e.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:c({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplate:l({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:c({},u,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:c({},u,{}),outsidetextfont:c({},u,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:c({},u,{}),position:{valType:\"enumerated\",values:[\"top 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right\"],editType:\"calc\"}}}},{\"../../components/color/attributes\":661,\"../../lib/extend\":789,\"../../plots/attributes\":845,\"../../plots/domain\":877,\"../../plots/font_attributes\":878,\"../../plots/template_attributes\":922}],1189:[function(t,e,r){\"use strict\";var n=t(\"../../plots/plots\");r.name=\"pie\",r.plot=function(t,e,i,a){n.plotBasePlot(r.name,t,e,i,a)},r.clean=function(t,e,i,a){n.cleanBasePlot(r.name,t,e,i,a)}},{\"../../plots/plots\":913}],1190:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"tinycolor2\"),a=t(\"../../components/color\"),o={};function s(t){return function(e,r){return!!e&&(!!(e=i(e)).isValid()&&(e=a.addOpacity(e,e.getAlpha()),t[r]||(t[r]=e),e))}}function l(t,e){var r,n=JSON.stringify(t),a=e[n];if(!a){for(a=t.slice(),r=0;r<t.length;r++)a.push(i(t[r]).lighten(20).toHexString());for(r=0;r<t.length;r++)a.push(i(t[r]).darken(20).toHexString());e[n]=a}return a}e.exports={calc:function(t,e){var r,i,a=[],o=t._fullLayout,l=o.hiddenlabels||[],c=e.labels,u=e.marker.colors||[],f=e.values,h=e._length,p=e._hasValues&&h;if(e.dlabel)for(c=new Array(h),r=0;r<h;r++)c[r]=String(e.label0+r*e.dlabel);var d={},m=s(o[\"_\"+e.type+\"colormap\"]),g=0,v=!1;for(r=0;r<h;r++){var y,x,b;if(p){if(y=f[r],!n(y))continue;if((y=+y)<0)continue}else y=1;void 0!==(x=c[r])&&\"\"!==x||(x=r);var _=d[x=String(x)];void 0===_?(d[x]=a.length,(b=-1!==l.indexOf(x))||(g+=y),a.push({v:y,label:x,color:m(u[r],x),i:r,pts:[r],hidden:b})):(v=!0,(i=a[_]).v+=y,i.pts.push(r),i.hidden||(g+=y),!1===i.color&&u[r]&&(i.color=m(u[r],x)))}return(\"funnelarea\"===e.type?v:e.sort)&&a.sort((function(t,e){return e.v-t.v})),a[0]&&(a[0].vTotal=g),a},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,i=t.calcdata,a=n[r+\"colorway\"],s=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=l(a,o));for(var c=0,u=0;u<i.length;u++){var f=i[u];if(f[0].trace.type===r)for(var h=0;h<f.length;h++){var p=f[h];!1===p.color&&(s[p.label]?p.color=s[p.label]:(s[p.label]=p.color=a[c%a.length],c++))}}},makePullColorFn:s,generateExtendedColors:l}},{\"../../components/color\":662,\"fast-isnumeric\":245,tinycolor2:594}],1191:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"./attributes\"),o=t(\"../../plots/domain\").defaults,s=t(\"../bar/defaults\").handleText;function l(t,e){var r=Array.isArray(t),a=i.isArrayOrTypedArray(e),o=Math.min(r?t.length:1/0,a?e.length:1/0);if(isFinite(o)||(o=0),o&&a){for(var s,l=0;l<o;l++){var c=e[l];if(n(c)&&c>0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:a,len:o}}e.exports={handleLabelsAndValues:l,supplyDefaults:function(t,e,r,n){function c(r,n){return i.coerce(t,e,a,r,n)}var u=l(c(\"labels\"),c(\"values\")),f=u.len;if(e._hasLabels=u.hasLabels,e._hasValues=u.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),f){e._length=f,c(\"marker.line.width\")&&c(\"marker.line.color\"),c(\"marker.colors\"),c(\"scalegroup\");var h,p=c(\"text\"),d=c(\"texttemplate\");if(d||(h=c(\"textinfo\",Array.isArray(p)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),d||h&&\"none\"!==h){var m=c(\"textposition\");s(t,e,n,c,m,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(m)||\"auto\"===m||\"outside\"===m)&&c(\"automargin\"),(\"inside\"===m||\"auto\"===m||Array.isArray(m))&&c(\"insidetextorientation\")}o(e,n,c);var g=c(\"hole\");if(c(\"title.text\")){var v=c(\"title.position\",g?\"middle center\":\"top center\");g||\"middle center\"!==v||(e.title.position=\"top center\"),i.coerceFont(c,\"title.font\",n.font)}c(\"sort\"),c(\"direction\"),c(\"rotation\"),c(\"pull\")}else e.visible=!1}}},{\"../../lib\":799,\"../../plots/domain\":877,\"../bar/defaults\":941,\"./attributes\":1188,\"fast-isnumeric\":245}],1192:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx/helpers\").appendArrayMultiPointValues;e.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},{\"../../components/fx/helpers\":698}],1193:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");function i(t){return-1!==t.indexOf(\"e\")?t.replace(/[.]?0+e/,\"e\"):-1!==t.indexOf(\".\")?t.replace(/[.]?0+$/,\"\"):t}r.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+\"%\"},r.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},r.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r<e.length;r++){var n=t[e[r]];if(n||0===n||\"\"===n)return n}},r.castOption=function(t,e){return Array.isArray(t)?r.getFirstFilled(t,e):t||void 0},r.getRotationAngle=function(t){return(\"auto\"===t?0:t)*Math.PI/180}},{\"../../lib\":799}],1194:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),layoutAttributes:t(\"./layout_attributes\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\"),styleOne:t(\"./style_one\"),moduleType:\"trace\",name:\"pie\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"pie\",\"showLegend\"],meta:{}}},{\"./attributes\":1188,\"./base_plot\":1189,\"./calc\":1190,\"./defaults\":1191,\"./layout_attributes\":1195,\"./layout_defaults\":1196,\"./plot\":1197,\"./style\":1198,\"./style_one\":1199}],1195:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{}],1196:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"piecolorway\",e.colorway),r(\"extendpiecolors\")}},{\"../../lib\":799,\"./layout_attributes\":1195}],1197:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../plots/plots\"),a=t(\"../../components/fx\"),o=t(\"../../components/color\"),s=t(\"../../components/drawing\"),l=t(\"../../lib\"),c=l.strScale,u=l.strTranslate,f=t(\"../../lib/svg_text_utils\"),h=t(\"../bar/uniform_text\"),p=h.recordMinTextSize,d=h.clearMinTextSize,m=t(\"../bar/constants\").TEXTPAD,g=t(\"./helpers\"),v=t(\"./event_data\"),y=t(\"../../lib\").isValidTextValue;function x(t,e,r){var i=r[0],o=i.trace,s=i.cx,c=i.cy;\"_hasHoverLabel\"in o||(o._hasHoverLabel=!1),\"_hasHoverEvent\"in o||(o._hasHoverEvent=!1),t.on(\"mouseover\",(function(t){var r=e._fullLayout,u=e._fullData[o.index];if(!e._dragging&&!1!==r.hovermode){var f=u.hoverinfo;if(Array.isArray(f)&&(f=a.castHoverinfo({hoverinfo:[g.castOption(f,t.pts)],_module:o._module},r,0)),\"all\"===f&&(f=\"label+text+value+percent+name\"),u.hovertemplate||\"none\"!==f&&\"skip\"!==f&&f){var h=t.rInscribed||0,p=s+t.pxmid[0]*(1-h),d=c+t.pxmid[1]*(1-h),m=r.separators,y=[];if(f&&-1!==f.indexOf(\"label\")&&y.push(t.label),t.text=g.castOption(u.hovertext||u.text,t.pts),f&&-1!==f.indexOf(\"text\")){var x=t.text;l.isValidTextValue(x)&&y.push(x)}t.value=t.v,t.valueLabel=g.formatPieValue(t.v,m),f&&-1!==f.indexOf(\"value\")&&y.push(t.valueLabel),t.percent=t.v/i.vTotal,t.percentLabel=g.formatPiePercent(t.percent,m),f&&-1!==f.indexOf(\"percent\")&&y.push(t.percentLabel);var b=u.hoverlabel,_=b.font;a.loneHover({trace:o,x0:p-h*i.r,x1:p+h*i.r,y:d,text:y.join(\"<br>\"),name:u.hovertemplate||-1!==f.indexOf(\"name\")?u.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:g.castOption(b.bgcolor,t.pts)||t.color,borderColor:g.castOption(b.bordercolor,t.pts),fontFamily:g.castOption(_.family,t.pts),fontSize:g.castOption(_.size,t.pts),fontColor:g.castOption(_.color,t.pts),nameLength:g.castOption(b.namelength,t.pts),textAlign:g.castOption(b.align,t.pts),hovertemplate:g.castOption(u.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[v(t,u)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e}),o._hasHoverLabel=!0}o._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[v(t,u)],event:n.event})}})),t.on(\"mouseout\",(function(t){var r=e._fullLayout,i=e._fullData[o.index],s=n.select(this).datum();o._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[v(s,i)],event:n.event}),o._hasHoverEvent=!1),o._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),o._hasHoverLabel=!1)})),t.on(\"click\",(function(t){var r=e._fullLayout,i=e._fullData[o.index];e._dragging||!1===r.hovermode||(e._hoverdata=[v(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=g.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=g.castOption(t._input.textfont.color,e.pts));var i=g.castOption(t.insidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,a=g.castOption(t.insidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:i,size:a}}function _(t,e){for(var r,n,i=0;i<t.length;i++)if((n=(r=t[i][0]).trace).title.text){var a=n.title.text;n._meta&&(a=l.templateString(a,n._meta));var o=s.tester.append(\"text\").attr(\"data-notex\",1).text(a).call(s.font,n.title.font).call(f.convertToTspans,e),c=s.bBox(o.node(),!0);r.titleBox={width:c.width,height:c.height},o.remove()}}function w(t,e,r){var n=r.r||e.rpx1,i=e.rInscribed;if(e.startangle===e.stopangle)return{rCenter:1-i,scale:0,rotate:0,textPosAngle:0};var a,o=e.ring,s=1===o&&Math.abs(e.startangle-e.stopangle)===2*Math.PI,l=e.halfangle,c=e.midangle,u=r.trace.insidetextorientation,f=\"horizontal\"===u,h=\"tangential\"===u,p=\"radial\"===u,d=\"auto\"===u,m=[];if(!d){var g,v=function(r,i){if(function(t,e){var r=t.startangle,n=t.stopangle;return r>e&&e>n||r<e&&e<n}(e,r)){var s=Math.abs(r-e.startangle),l=Math.abs(r-e.stopangle),c=s<l?s:l;(a=\"tan\"===i?k(t,n,o,c,0):T(t,n,o,c,Math.PI/2)).textPosAngle=r,m.push(a)}};if(f||h){for(g=4;g>=-4;g-=2)v(Math.PI*g,\"tan\");for(g=4;g>=-4;g-=2)v(Math.PI*(g+1),\"tan\")}if(f||p){for(g=4;g>=-4;g-=2)v(Math.PI*(g+1.5),\"rad\");for(g=4;g>=-4;g-=2)v(Math.PI*(g+.5),\"rad\")}}if(s||d||f){var y=Math.sqrt(t.width*t.width+t.height*t.height);if((a={scale:i*n*2/y,rCenter:1-i,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,a.scale>=1)return a;m.push(a)}(d||p)&&((a=T(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,m.push(a)),(d||h)&&((a=k(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,m.push(a));for(var x=0,b=0,_=0;_<m.length;_++){var w=m[_].scale;if(b<w&&(b=w,x=_),!d&&b>=1)break}return m[x]}function T(t,e,r,n,i){e=Math.max(0,e-2*m);var a=t.width/t.height,o=S(a,n,e,r);return{scale:2*o/t.height,rCenter:M(a,o/e),rotate:A(i)}}function k(t,e,r,n,i){e=Math.max(0,e-2*m);var a=t.height/t.width,o=S(a,n,e,r);return{scale:2*o/t.width,rCenter:M(a,o/e),rotate:A(i+Math.PI/2)}}function M(t,e){return Math.cos(e)-t*e}function A(t){return(180/Math.PI*t+720)%180-90}function S(t,e,r,n){var i=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(i*i+.5)+i),n/(Math.sqrt(t*t+n/2)+t))}function E(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function L(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function C(t,e){var r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=I(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,c,u=(l=t.r,c=t.trace.aspectratio,l/(void 0===c?1:c)),f=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf(\"left\")?(f+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf(\"center\")?f*=2:-1!==a.title.position.indexOf(\"right\")&&(f+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=f/t.titleBox.width,n=P(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function P(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function I(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function O(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=a.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);a.title.text&&\"middle center\"!==a.title.position&&(l-=P(i,e));var c=s/2,u=l/2;\"funnelarea\"!==a.type||a.scalegroup||(u/=a.aspectratio),i.r=Math.min(c,u)/(1+I(a)),i.cx=e.l+e.w*(a.domain.x[1]+a.domain.x[0])/2,i.cy=e.t+e.h*(1-a.domain.y[0])-l/2,a.title.text&&-1!==a.title.position.indexOf(\"bottom\")&&(i.cy-=P(i,e)),a.scalegroup&&-1===r.indexOf(a.scalegroup)&&r.push(a.scalegroup)}!function(t,e){for(var r,n,i,a=0;a<e.length;a++){var o=1/0,s=e[a];for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var l;if(\"pie\"===i.type)l=r.r*r.r;else if(\"funnelarea\"===i.type){var c,u;i.aspectratio>1?(c=r.r,u=c/i.aspectratio):(u=r.r,c=u*i.aspectratio),c*=(1+i.baseratio)/2,l=c*u}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var f=o*r.vTotal;\"funnelarea\"===i.type&&(f/=(1+i.baseratio)/2,f/=i.aspectratio),r.r=Math.sqrt(f)}}}(t,r)}function z(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function D(t,e,r){var n=t._fullLayout,i=r.trace,a=i.texttemplate,o=i.textinfo;if(!a&&o&&\"none\"!==o){var s,c=o.split(\"+\"),u=function(t){return-1!==c.indexOf(t)},f=u(\"label\"),h=u(\"text\"),p=u(\"value\"),d=u(\"percent\"),m=n.separators;if(s=f?[e.label]:[],h){var v=g.getFirstFilled(i.text,e.pts);y(v)&&s.push(v)}p&&s.push(g.formatPieValue(e.v,m)),d&&s.push(g.formatPiePercent(e.v/r.vTotal,m)),e.text=s.join(\"<br>\")}if(a){var x=l.castOption(i,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:g.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:g.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=g.getFirstFilled(i.text,e.pts);(y(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}e.exports={plot:function(t,e){var r=t._fullLayout,a=r._size;d(\"pie\",r),_(e,t),O(e,a);var h=l.makeTraceGroups(r._pielayer,e,\"trace\").each((function(e){var h=n.select(this),d=e[0],m=d.trace;!function(t){var e,r,n,i=t[0],a=i.r,o=i.trace,s=g.getRotationAngle(o.rotation),l=2*Math.PI/i.vTotal,c=\"px0\",u=\"px1\";if(\"counterclockwise\"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,c=\"px1\",u=\"px0\"}for(n=z(a,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[c]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=z(a,s),r.midangle=s,s+=l*r.v/2,n=z(a,s),r.stopangle=s,r[u]=n,r.largeArc=r.v>i.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-o.hole,r.rInscribed=E(r,i))}(e),h.attr(\"stroke-linejoin\",\"round\"),h.each((function(){var v=n.select(this).selectAll(\"g.slice\").data(e);v.enter().append(\"g\").classed(\"slice\",!0),v.exit().remove();var y=[[[],[]],[[],[]]],_=!1;v.each((function(i,a){if(i.hidden)n.select(this).selectAll(\"path,g\").remove();else{i.pointNumber=i.i,i.curveNumber=m.index,y[i.pxmid[1]<0?0:1][i.pxmid[0]<0?0:1].push(i);var o=d.cx,c=d.cy,u=n.select(this),h=u.selectAll(\"path.surface\").data([i]);if(h.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),u.call(x,t,e),m.pull){var v=+g.castOption(m.pull,i.pts)||0;v>0&&(o+=v*i.pxmid[0],c+=v*i.pxmid[1])}i.cxFinal=o,i.cyFinal=c;var T=m.hole;if(i.v===d.vTotal){var k=\"M\"+(o+i.px0[0])+\",\"+(c+i.px0[1])+C(i.px0,i.pxmid,!0,1)+C(i.pxmid,i.px0,!0,1)+\"Z\";T?h.attr(\"d\",\"M\"+(o+T*i.px0[0])+\",\"+(c+T*i.px0[1])+C(i.px0,i.pxmid,!1,T)+C(i.pxmid,i.px0,!1,T)+\"Z\"+k):h.attr(\"d\",k)}else{var M=C(i.px0,i.px1,!0,1);if(T){var A=1-T;h.attr(\"d\",\"M\"+(o+T*i.px1[0])+\",\"+(c+T*i.px1[1])+C(i.px1,i.px0,!1,T)+\"l\"+A*i.px0[0]+\",\"+A*i.px0[1]+M+\"Z\")}else h.attr(\"d\",\"M\"+o+\",\"+c+\"l\"+i.px0[0]+\",\"+i.px0[1]+M+\"Z\")}D(t,i,d);var S=g.castOption(m.textposition,i.pts),E=u.selectAll(\"g.slicetext\").data(i.text&&\"none\"!==S?[0]:[]);E.enter().append(\"g\").classed(\"slicetext\",!0),E.exit().remove(),E.each((function(){var u=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),h=l.ensureUniformFontSize(t,\"outside\"===S?function(t,e,r){var n=g.castOption(t.outsidetextfont.color,e.pts)||g.castOption(t.textfont.color,e.pts)||r.color,i=g.castOption(t.outsidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,a=g.castOption(t.outsidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size;return{color:n,family:i,size:a}}(m,i,r.font):b(m,i,r.font));u.text(i.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,h).call(f.convertToTspans,t);var v,y=s.bBox(u.node());if(\"outside\"===S)v=L(y,i);else if(v=w(y,i,d),\"auto\"===S&&v.scale<1){var x=l.ensureUniformFontSize(t,m.outsidetextfont);u.call(s.font,x),v=L(y=s.bBox(u.node()),i)}var T=v.textPosAngle,k=void 0===T?i.pxmid:z(d.r,T);if(v.targetX=o+k[0]*v.rCenter+(v.x||0),v.targetY=c+k[1]*v.rCenter+(v.y||0),R(v,y),v.outside){var M=v.targetY;i.yLabelMin=M-y.height/2,i.yLabelMid=M,i.yLabelMax=M+y.height/2,i.labelExtraX=0,i.labelExtraY=0,_=!0}v.fontSize=h.size,p(m.type,v,r),e[a].transform=v,u.attr(\"transform\",l.getTextTransform(v))}))}function C(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*d.r+\",\"+n*d.r+\" 0 \"+i.largeArc+(r?\" 1 \":\" 0 \")+a+\",\"+o}}));var T=n.select(this).selectAll(\"g.titletext\").data(m.title.text?[0]:[]);if(T.enter().append(\"g\").classed(\"titletext\",!0),T.exit().remove(),T.each((function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),i=m.title.text;m._meta&&(i=l.templateString(i,m._meta)),r.text(i).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,m.title.font).call(f.convertToTspans,t),e=\"middle center\"===m.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(d):C(d,a),r.attr(\"transform\",u(e.x,e.y)+c(Math.min(1,e.scale))+u(e.tx,e.ty))})),_&&function(t,e){var r,n,i,a,o,s,l,c,u,f,h,p,d;function m(t,e){return t.pxmid[1]-e.pxmid[1]}function v(t,e){return e.pxmid[1]-t.pxmid[1]}function y(t,r){r||(r={});var 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n=t(\"../scatter/attributes\");e.exports={x:n.x,y:n.y,xy:{valType:\"data_array\",editType:\"calc\"},indices:{valType:\"data_array\",editType:\"calc\"},xbounds:{valType:\"data_array\",editType:\"calc\"},ybounds:{valType:\"data_array\",editType:\"calc\"},text:n.text,marker:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,arrayOk:!1,editType:\"calc\"},blend:{valType:\"boolean\",dflt:null,editType:\"calc\"},sizemin:{valType:\"number\",min:.1,max:2,dflt:.5,editType:\"calc\"},sizemax:{valType:\"number\",min:.1,dflt:20,editType:\"calc\"},border:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},arearatio:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"},editType:\"calc\"},editType:\"calc\"},transforms:void 0}},{\"../scatter/attributes\":1214}],1201:[function(t,e,r){\"use strict\";var n=t(\"gl-pointcloud2d\"),i=t(\"../../lib/str2rgbarray\"),a=t(\"../../plots/cartesian/autorange\").findExtremes,o=t(\"../scatter/get_trace_color\");function s(t,e){this.scene=t,this.uid=e,this.type=\"pointcloud\",this.pickXData=[],this.pickYData=[],this.xData=[],this.yData=[],this.textLabels=[],this.color=\"rgb(0, 0, 0)\",this.name=\"\",this.hoverinfo=\"all\",this.idToIndex=new Int32Array(0),this.bounds=[0,0,0,0],this.pointcloudOptions={positions:new Float32Array(0),idToIndex:this.idToIndex,sizemin:.5,sizemax:12,color:[0,0,0,1],areaRatio:1,borderColor:[0,0,0,1]},this.pointcloud=n(t.glplot,this.pointcloudOptions),this.pointcloud._trace=this}var l=s.prototype;l.handlePick=function(t){var e=this.idToIndex[t.pointId];return{trace:this,dataCoord:t.dataCoord,traceCoord:this.pickXYData?[this.pickXYData[2*e],this.pickXYData[2*e+1]]:[this.pickXData[e],this.pickYData[e]],textLabel:Array.isArray(this.textLabels)?this.textLabels[e]:this.textLabels,color:this.color,name:this.name,pointIndex:e,hoverinfo:this.hoverinfo}},l.update=function(t){this.index=t.index,this.textLabels=t.text,this.name=t.name,this.hoverinfo=t.hoverinfo,this.bounds=[1/0,1/0,-1/0,-1/0],this.updateFast(t),this.color=o(t,{})},l.updateFast=function(t){var e,r,n,o,s,l,c=this.xData=this.pickXData=t.x,u=this.yData=this.pickYData=t.y,f=this.pickXYData=t.xy,h=t.xbounds&&t.ybounds,p=t.indices,d=this.bounds;if(f){if(n=f,e=f.length>>>1,h)d[0]=t.xbounds[0],d[2]=t.xbounds[1],d[1]=t.ybounds[0],d[3]=t.ybounds[1];else for(l=0;l<e;l++)o=n[2*l],s=n[2*l+1],o<d[0]&&(d[0]=o),o>d[2]&&(d[2]=o),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);if(p)r=p;else for(r=new Int32Array(e),l=0;l<e;l++)r[l]=l}else for(e=c.length,n=new Float32Array(2*e),r=new 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r.update(e),r}},{\"../../lib/str2rgbarray\":823,\"../../plots/cartesian/autorange\":848,\"../scatter/get_trace_color\":1224,\"gl-pointcloud2d\":324}],1202:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./attributes\");e.exports=function(t,e,r){function a(r,a){return n.coerce(t,e,i,r,a)}a(\"x\"),a(\"y\"),a(\"xbounds\"),a(\"ybounds\"),t.xy&&t.xy instanceof Float32Array&&(e.xy=t.xy),t.indices&&t.indices instanceof Int32Array&&(e.indices=t.indices),a(\"text\"),a(\"marker.color\",r),a(\"marker.opacity\"),a(\"marker.blend\"),a(\"marker.sizemin\"),a(\"marker.sizemax\"),a(\"marker.border.color\",r),a(\"marker.border.arearatio\"),e._length=null}},{\"../../lib\":799,\"./attributes\":1200}],1203:[function(t,e,r){\"use strict\";[\"*pointcloud* trace is deprecated!\",\"Please consider switching to the *scattergl* trace type.\"].join(\" 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n=t(\"../../plots/font_attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../components/color/attributes\"),o=t(\"../../components/fx/attributes\"),s=t(\"../../plots/domain\").attributes,l=t(\"../../plots/template_attributes\").hovertemplateAttrs,c=t(\"../../components/colorscale/attributes\"),u=t(\"../../plot_api/plot_template\").templatedArray,f=t(\"../../plots/cartesian/axis_format_attributes\").descriptionOnlyNumbers,h=t(\"../../lib/extend\").extendFlat,p=t(\"../../plot_api/edit_types\").overrideAll;(e.exports=p({hoverinfo:h({},i.hoverinfo,{flags:[],arrayOk:!1}),hoverlabel:o.hoverlabel,domain:s({name:\"sankey\",trace:!0}),orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],dflt:\"h\"},valueformat:{valType:\"string\",dflt:\".3s\",description:f(\"value\")},valuesuffix:{valType:\"string\",dflt:\"\"},arrangement:{valType:\"enumerated\",values:[\"snap\",\"perpendicular\",\"freeform\",\"fixed\"],dflt:\"snap\"},textfont:n({}),customdata:void 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h={_id:\"x\",c2p:u.identity,_offset:r._sankey.translateX,_length:r._sankey.width},p={_id:\"y\",c2p:u.identity,_offset:r._sankey.translateY,_length:r._sankey.height},d={gd:t,element:o.node(),plotinfo:{id:e,xaxis:h,yaxis:p,fillRangeItems:u.noop},subplot:e,xaxes:[h],yaxes:[p],doneFnCompleted:function(r){var n,i=t._fullData[e],a=i.node.groups.slice(),o=[];function s(t){for(var e=i._sankey.graph.nodes,r=0;r<e.length;r++)if(e[r].pointNumber===t)return e[r]}for(var l=0;l<r.length;l++){var c=s(r[l].pointNumber);if(c)if(c.group){for(var u=0;u<c.childrenNodes.length;u++)o.push(c.childrenNodes[u].pointNumber);a[c.pointNumber-i.node._count]=!1}else o.push(c.pointNumber)}n=a.filter(Boolean).concat([o]),f.call(\"_guiRestyle\",t,{\"node.groups\":[n]},e)},prepFn:function(t,e,r){c(t,e,r,d,i)}};l.init(d)}}r.name=\"sankey\",r.baseLayoutAttrOverrides=n({hoverlabel:o.hoverlabel},\"plot\",\"nested\"),r.plot=function(t){var e=i(t.calcdata,\"sankey\")[0];a(t,e),r.updateFx(t)},r.clean=function(t,e,r,n){var 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m=t._fullData[d].node;t._fullData[d]._viewInitial={node:{groups:m.groups.slice(),x:m.x.slice(),y:m.y.slice()}}}var _=c(t,\"source:\")+\" \",w=c(t,\"target:\")+\" \",T=c(t,\"concentration:\")+\" \",k=c(t,\"incoming flow count:\")+\" \",M=c(t,\"outgoing flow count:\")+\" \";i(t,s,e,{width:f.w,height:f.h,margin:{t:f.t,r:f.r,b:f.b,l:f.l}},{linkEvents:{hover:function(e,r,i){!1!==t._fullLayout.hovermode&&(n.select(e).call(y.bind(0,r,i,!0)),\"skip\"!==r.link.trace.link.hoverinfo&&(r.link.fullData=r.link.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.link]})))},follow:function(e,i){if(!1!==t._fullLayout.hovermode){var s=i.link.trace.link;if(\"none\"!==s.hoverinfo&&\"skip\"!==s.hoverinfo){for(var l=[],c=0,f=0;f<i.flow.links.length;f++){var d=i.flow.links[f];if(\"closest\"!==t._fullLayout.hovermode||i.link.pointNumber===d.pointNumber){i.link.pointNumber===d.pointNumber&&(c=f),d.fullData=d.trace,s=i.link.trace.link;var m=v(d),g={valueLabel:n.format(i.valueFormat)(d.value)+i.valueSuffix};l.push({x:m[0],y:m[1],name:g.valueLabel,text:[d.label||\"\",_+d.source.label,w+d.target.label,d.concentrationscale?T+n.format(\"%0.2f\")(d.flow.labelConcentration):\"\"].filter(u).join(\"<br>\"),color:b(s,\"bgcolor\")||o.addOpacity(d.color,1),borderColor:b(s,\"bordercolor\"),fontFamily:b(s,\"font.family\"),fontSize:b(s,\"font.size\"),fontColor:b(s,\"font.color\"),nameLength:b(s,\"namelength\"),textAlign:b(s,\"align\"),idealAlign:n.event.x<m[0]?\"right\":\"left\",hovertemplate:s.hovertemplate,hovertemplateLabels:g,eventData:[d]})}}a.loneHover(l,{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t,anchorIndex:c}).each((function(){i.link.concentrationscale||h(this,.65),p(this)}))}}function v(t){var e,r;t.circular?(e=(t.circularPathData.leftInnerExtent+t.circularPathData.rightInnerExtent)/2,r=t.circularPathData.verticalFullExtent):(e=(t.source.x1+t.target.x0)/2,r=(t.y0+t.y1)/2);var n=[e,r];return\"v\"===t.trace.orientation&&n.reverse(),n[0]+=i.parent.translateX,n[1]+=i.parent.translateY,n}},unhover:function(e,i,o){!1!==t._fullLayout.hovermode&&(n.select(e).call(x.bind(0,i,o,!0)),\"skip\"!==i.link.trace.link.hoverinfo&&(i.link.fullData=i.link.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[i.link]})),a.loneUnhover(r._hoverlayer.node()))},select:function(e,r){var i=r.link;i.originalEvent=n.event,t._hoverdata=[i],a.click(t,{target:!0})}},nodeEvents:{hover:function(e,r,i){!1!==t._fullLayout.hovermode&&(n.select(e).call(g,r,i),\"skip\"!==r.node.trace.node.hoverinfo&&(r.node.fullData=r.node.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.node]})))},follow:function(e,i){if(!1!==t._fullLayout.hovermode){var o=i.node.trace.node;if(\"none\"!==o.hoverinfo&&\"skip\"!==o.hoverinfo){var s=n.select(e).select(\".\"+l.nodeRect),c=t._fullLayout._paperdiv.node().getBoundingClientRect(),f=s.node().getBoundingClientRect(),d=f.left-2-c.left,m=f.right+2-c.left,g=f.top+f.height/4-c.top,v={valueLabel:n.format(i.valueFormat)(i.node.value)+i.valueSuffix};i.node.fullData=i.node.trace,t._fullLayout._calcInverseTransform(t);var y=t._fullLayout._invScaleX,x=t._fullLayout._invScaleY,_=a.loneHover({x0:y*d,x1:y*m,y:x*g,name:n.format(i.valueFormat)(i.node.value)+i.valueSuffix,text:[i.node.label,k+i.node.targetLinks.length,M+i.node.sourceLinks.length].filter(u).join(\"<br>\"),color:b(o,\"bgcolor\")||i.tinyColorHue,borderColor:b(o,\"bordercolor\"),fontFamily:b(o,\"font.family\"),fontSize:b(o,\"font.size\"),fontColor:b(o,\"font.color\"),nameLength:b(o,\"namelength\"),textAlign:b(o,\"align\"),idealAlign:\"left\",hovertemplate:o.hovertemplate,hovertemplateLabels:v,eventData:[i.node]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t});h(_,.85),p(_)}}},unhover:function(e,i,o){!1!==t._fullLayout.hovermode&&(n.select(e).call(v,i,o),\"skip\"!==i.node.trace.node.hoverinfo&&(i.node.fullData=i.node.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[i.node]})),a.loneUnhover(r._hoverlayer.node()))},select:function(e,r,i){var 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n,i=y(e),a=i.trace,u=a.domain,f=\"h\"===a.orientation,p=a.node.pad,d=a.node.thickness,m=t.width*(u.x[1]-u.x[0]),g=t.height*(u.y[1]-u.y[0]),v=i._nodes,x=i._links,b=i.circular;(n=b?s.sankeyCircular().circularLinkGap(0):o.sankey()).iterations(l.sankeyIterations).size(f?[m,g]:[g,m]).nodeWidth(d).nodePadding(p).nodeId((function(t){return t.pointNumber})).nodes(v).links(x);var _,w,T,k=n();for(var M in n.nodePadding()<p&&h.warn(\"node.pad was reduced to \",n.nodePadding(),\" to fit within the figure.\"),i._groupLookup){var A,S=parseInt(i._groupLookup[M]);for(_=0;_<k.nodes.length;_++)if(k.nodes[_].pointNumber===S){A=k.nodes[_];break}if(A){var E={pointNumber:parseInt(M),x0:A.x0,x1:A.x1,y0:A.y0,y1:A.y1,partOfGroup:!0,sourceLinks:[],targetLinks:[]};k.nodes.unshift(E),A.childrenNodes.unshift(E)}}if(function(){for(_=0;_<k.nodes.length;_++){var t,e,r=k.nodes[_],n={};for(w=0;w<r.targetLinks.length;w++)t=(e=r.targetLinks[w]).source.pointNumber+\":\"+e.target.pointNumber,n.hasOwnProperty(t)||(n[t]=[]),n[t].push(e);var i=Object.keys(n);for(w=0;w<i.length;w++){var a=n[t=i[w]],o=0,s={};for(T=0;T<a.length;T++)s[(e=a[T]).label]||(s[e.label]=0),s[e.label]+=e.value,o+=e.value;for(T=0;T<a.length;T++)(e=a[T]).flow={value:o,labelConcentration:s[e.label]/o,concentration:e.value/o,links:a},e.concentrationscale&&(e.color=c(e.concentrationscale(e.flow.labelConcentration)))}var l=0;for(w=0;w<r.sourceLinks.length;w++)l+=r.sourceLinks[w].value;for(w=0;w<r.sourceLinks.length;w++)(e=r.sourceLinks[w]).concentrationOut=e.value/l;var u=0;for(w=0;w<r.targetLinks.length;w++)u+=r.targetLinks[w].value;for(w=0;w<r.targetLinks.length;w++)(e=r.targetLinks[w]).concenrationIn=e.value/u}}(),a.node.x.length&&a.node.y.length){for(_=0;_<Math.min(a.node.x.length,a.node.y.length,k.nodes.length);_++)if(a.node.x[_]&&a.node.y[_]){var L=[a.node.x[_]*m,a.node.y[_]*g];k.nodes[_].x0=L[0]-d/2,k.nodes[_].x1=L[0]+d/2;var C=k.nodes[_].y1-k.nodes[_].y0;k.nodes[_].y0=L[1]-C/2,k.nodes[_].y1=L[1]+C/2}if(\"snap\"===a.arrangement)!function(t){t.forEach((function(t){var e,r,n,i=0,a=t.length;for(t.sort((function(t,e){return t.y0-e.y0})),n=0;n<a;++n)(e=t[n]).y0>=i||(r=i-e.y0)>1e-6&&(e.y0+=r,e.y1+=r),i=e.y1+p}))}(function(t){var e,r,n=t.map((function(t,e){return{x0:t.x0,index:e}})).sort((function(t,e){return t.x0-e.x0})),i=[],a=-1,o=-1/0;for(_=0;_<n.length;_++){var s=t[n[_].index];s.x0>o+d&&(a+=1,e=s.x0),o=s.x0,i[a]||(i[a]=[]),i[a].push(s),r=e-s.x0,s.x0+=r,s.x1+=r}return 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n=t(\"@plotly/d3\"),i=t(\"../../components/drawing\"),a=t(\"../../registry\");function o(t,e,r){i.pointStyle(t.selectAll(\"path.point\"),e,r)}function s(t,e,r){i.textPointStyle(t.selectAll(\"text\"),e,r)}e.exports={style:function(t){var e=n.select(t).selectAll(\"g.trace.scatter\");e.style(\"opacity\",(function(t){return t[0].trace.opacity})),e.selectAll(\"g.points\").each((function(e){o(n.select(this),e.trace||e[0].trace,t)})),e.selectAll(\"g.text\").each((function(e){s(n.select(this),e.trace||e[0].trace,t)})),e.selectAll(\"g.trace path.js-line\").call(i.lineGroupStyle),e.selectAll(\"g.trace path.js-fill\").call(i.fillGroupStyle),a.getComponentMethod(\"errorbars\",\"style\")(e)},stylePoints:o,styleText:s,styleOnSelect:function(t,e,r){var 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n=t(\"../../lib\"),i=t(\"../../registry\");e.exports=function(t,e,r,a){var o,s=a(\"x\"),l=a(\"y\");if(i.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\"],r),s){var c=n.minRowLength(s);l?o=Math.min(c,n.minRowLength(l)):(o=c,a(\"y0\"),a(\"dy\"))}else{if(!l)return 0;o=n.minRowLength(l),a(\"x0\"),a(\"dx\")}return e._length=o,o}},{\"../../lib\":799,\"../../registry\":927}],1242:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../components/colorscale/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../plots/template_attributes\").texttemplateAttrs,l=t(\"../../plots/attributes\"),c=t(\"../../constants/gl3d_dashes\"),u=t(\"../../constants/gl3d_markers\"),f=t(\"../../lib/extend\").extendFlat,h=t(\"../../plot_api/edit_types\").overrideAll,p=n.line,d=n.marker,m=d.line,g=f({width:p.width,dash:{valType:\"enumerated\",values:Object.keys(c),dflt:\"solid\"}},i(\"line\"));var 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a=n.getComponentMethod(\"errorbars\",\"makeComputeError\")(e),o=new Array(t.length),s=0;s<t.length;s++){var l=a(+t[s],s);if(\"log\"===i.type){var c=i.c2l(t[s]),u=t[s]-l[0],f=t[s]+l[1];if(o[s]=[(i.c2l(u,!0)-c)*r,(i.c2l(f,!0)-c)*r],u>0){var h=i.c2l(u);i._lowerLogErrorBound||(i._lowerLogErrorBound=h),i._lowerErrorBound=Math.min(i._lowerLogErrorBound,h)}}else o[s]=[-l[0]*r,l[1]*r]}return o}e.exports=function(t,e,r){var n=[i(t.x,t.error_x,e[0],r.xaxis),i(t.y,t.error_y,e[1],r.yaxis),i(t.z,t.error_z,e[2],r.zaxis)],a=function(t){for(var e=0;e<t.length;e++)if(t[e])return t[e].length;return 0}(n);if(0===a)return null;for(var o=new Array(a),s=0;s<a;s++){for(var l=[[0,0,0],[0,0,0]],c=0;c<3;c++)if(n[c])for(var u=0;u<2;u++)l[u][c]=n[c][s][u];o[s]=l}return o}},{\"../../registry\":927}],1245:[function(t,e,r){\"use strict\";var n=t(\"gl-line3d\"),i=t(\"gl-scatter3d\"),a=t(\"gl-error3d\"),o=t(\"gl-mesh3d\"),s=t(\"delaunay-triangulate\"),l=t(\"../../lib\"),c=t(\"../../lib/str2rgbarray\"),u=t(\"../../lib/gl_format_color\").formatColor,f=t(\"../scatter/make_bubble_size_func\"),h=t(\"../../constants/gl3d_dashes\"),p=t(\"../../constants/gl3d_markers\"),d=t(\"../../plots/cartesian/axes\"),m=t(\"../../components/fx/helpers\").appendArrayPointValue,g=t(\"./calc_errors\");function v(t,e){this.scene=t,this.uid=e,this.linePlot=null,this.scatterPlot=null,this.errorBars=null,this.textMarkers=null,this.delaunayMesh=null,this.color=null,this.mode=\"\",this.dataPoints=[],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.textLabels=null,this.data=null}var y=v.prototype;function x(t){return null==t?0:t.indexOf(\"left\")>-1?-1:t.indexOf(\"right\")>-1?1:0}function b(t){return null==t?0:t.indexOf(\"top\")>-1?-1:t.indexOf(\"bottom\")>-1?1:0}function _(t,e){return e(4*t)}function w(t){return p[t]}function T(t,e,r,n,i){var 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e=[0,0,0],r=[[0,0,0],[0,0,0],[0,0,0]],n=[1,1,1],i=0;i<3;i++){var a=t[i];a&&!1!==a.copy_zstyle&&!1!==t[2].visible&&(a=t[2]),a&&a.visible&&(e[i]=a.width/2,r[i]=c(a.color),n[i]=a.thickness)}return{capSize:e,color:r,lineWidth:n}}([e.error_x,e.error_y,e.error_z]);return a.errorColor=X.color,a.errorLineWidth=X.lineWidth,a.errorCapSize=X.capSize,a.delaunayAxis=e.surfaceaxis,a.delaunayColor=c(e.surfacecolor),a}function M(t){if(l.isArrayOrTypedArray(t)){var e=t[0];return l.isArrayOrTypedArray(e)&&(t=e),\"rgb(\"+t.slice(0,3).map((function(t){return Math.round(255*t)}))+\")\"}return null}function A(t){return l.isArrayOrTypedArray(t)?4===t.length&&\"number\"==typeof t[0]?M(t):t.map(M):null}y.handlePick=function(t){if(t.object&&(t.object===this.linePlot||t.object===this.delaunayMesh||t.object===this.textMarkers||t.object===this.scatterPlot)){var e=t.index=t.data.index;return t.object.highlight&&t.object.highlight(null),this.scatterPlot&&(t.object=this.scatterPlot,this.scatterPlot.highlight(t.data)),t.textLabel=\"\",this.textLabels&&(Array.isArray(this.textLabels)?(this.textLabels[e]||0===this.textLabels[e])&&(t.textLabel=this.textLabels[e]):t.textLabel=this.textLabels),t.traceCoordinate=[this.data.x[e],this.data.y[e],this.data.z[e]],!0}},y.update=function(t){var e,r,l,c,u=this.scene.glplot.gl,f=h.solid;this.data=t;var p=k(this.scene,t);\"mode\"in p&&(this.mode=p.mode),\"lineDashes\"in p&&p.lineDashes in 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d=t.opacity;if(t.marker&&t.marker.opacity&&(d*=t.marker.opacity),r={gl:this.scene.glplot.gl,position:p.position,color:p.scatterColor,size:p.scatterSize,glyph:p.scatterMarker,opacity:d,orthographic:!0,lineWidth:p.scatterLineWidth,lineColor:p.scatterLineColor,project:p.project,projectScale:p.projectScale,projectOpacity:p.projectOpacity},-1!==this.mode.indexOf(\"markers\")?this.scatterPlot?this.scatterPlot.update(r):(this.scatterPlot=i(r),this.scatterPlot._trace=this,this.scatterPlot.highlightScale=1,this.scene.glplot.add(this.scatterPlot)):this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose(),this.scatterPlot=null),c={gl:this.scene.glplot.gl,position:p.position,glyph:p.text,color:p.textColor,size:p.textSize,angle:p.textAngle,alignment:p.textOffset,font:p.textFont,orthographic:!0,lineWidth:0,project:!1,opacity:t.opacity},this.textLabels=t.hovertext||t.text,-1!==this.mode.indexOf(\"text\")?this.textMarkers?this.textMarkers.update(c):(this.textMarkers=i(c),this.textMarkers._trace=this,this.textMarkers.highlightScale=1,this.scene.glplot.add(this.textMarkers)):this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose(),this.textMarkers=null),l={gl:this.scene.glplot.gl,position:p.position,color:p.errorColor,error:p.errorBounds,lineWidth:p.errorLineWidth,capSize:p.errorCapSize,opacity:t.opacity},this.errorBars?p.errorBounds?this.errorBars.update(l):(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose(),this.errorBars=null):p.errorBounds&&(this.errorBars=a(l),this.errorBars._trace=this,this.scene.glplot.add(this.errorBars)),p.delaunayAxis>=0){var m=function(t,e,r){var n,i=(r+1)%3,a=(r+2)%3,o=[],l=[];for(n=0;n<t.length;++n){var c=t[n];!isNaN(c[i])&&isFinite(c[i])&&!isNaN(c[a])&&isFinite(c[a])&&(o.push([c[i],c[a]]),l.push(n))}var u=s(o);for(n=0;n<u.length;++n)for(var f=u[n],h=0;h<f.length;++h)f[h]=l[f[h]];return{positions:t,cells:u,meshColor:e}}(p.position,p.delaunayColor,p.delaunayAxis);m.opacity=t.opacity,this.delaunayMesh?this.delaunayMesh.update(m):(m.gl=u,this.delaunayMesh=o(m),this.delaunayMesh._trace=this,this.scene.glplot.add(this.delaunayMesh))}else this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose(),this.delaunayMesh=null)},y.dispose=function(){this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose()),this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose()),this.errorBars&&(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose()),this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose()),this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose())},e.exports=function(t,e){var r=new v(t,e.uid);return r.update(e),r}},{\"../../components/fx/helpers\":698,\"../../constants/gl3d_dashes\":772,\"../../constants/gl3d_markers\":773,\"../../lib\":799,\"../../lib/gl_format_color\":795,\"../../lib/str2rgbarray\":823,\"../../plots/cartesian/axes\":849,\"../scatter/make_bubble_size_func\":1231,\"./calc_errors\":1244,\"delaunay-triangulate\":176,\"gl-error3d\":269,\"gl-line3d\":277,\"gl-mesh3d\":311,\"gl-scatter3d\":330}],1246:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function f(r,n){return i.coerce(t,e,c,r,n)}if(function(t,e,r,i){var a=0,o=r(\"x\"),s=r(\"y\"),l=r(\"z\");n.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\",\"z\"],i),o&&s&&l&&(a=Math.min(o.length,s.length,l.length),e._length=e._xlength=e._ylength=e._zlength=a);return 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n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/line_shape_defaults\"),c=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}p(\"carpet\"),e.xaxis=\"x\",e.yaxis=\"y\";var d=p(\"a\"),m=p(\"b\"),g=Math.min(d.length,m.length);if(g){e._length=g,p(\"text\"),p(\"texttemplate\"),p(\"hovertext\"),p(\"mode\",g<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&(s(t,e,r,h,p),l(t,e,p),p(\"connectgaps\")),a.hasMarkers(e)&&o(t,e,r,h,p,{gradient:!0}),a.hasText(e)&&c(t,e,h,p);var v=[];(a.hasMarkers(e)||a.hasText(e))&&(p(\"marker.maxdisplayed\"),v.push(\"points\")),p(\"fill\"),\"none\"!==e.fill&&(u(t,e,r,p),a.hasLines(e)||l(t,e,p)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||v.push(\"fills\"),\"fills\"!==p(\"hoveron\",v.join(\"+\")||\"points\")&&p(\"hovertemplate\"),n.coerceSelectionMarkerOpacity(e,p)}else e.visible=!1}},{\"../../lib\":799,\"../scatter/constants\":1218,\"../scatter/fillcolor_defaults\":1222,\"../scatter/line_defaults\":1227,\"../scatter/line_shape_defaults\":1229,\"../scatter/marker_defaults\":1233,\"../scatter/subtypes\":1239,\"../scatter/text_defaults\":1240,\"./attributes\":1248}],1251:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,i){var a=n[i];return t.a=a.a,t.b=a.b,t.y=a.y,t}},{}],1252:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r={},n=e._carpet,i=n.ab2ij([t.a,t.b]),a=Math.floor(i[0]),o=i[0]-a,s=Math.floor(i[1]),l=i[1]-s,c=n.evalxy([],a,s,o,l);return r.yLabel=c[1].toFixed(3),r}},{}],1253:[function(t,e,r){\"use 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n=t(\"../scatter/plot\"),i=t(\"../../plots/cartesian/axes\"),a=t(\"../../components/drawing\");e.exports=function(t,e,r,o){var s,l,c,u=r[0][0].carpet,f={xaxis:i.getFromId(t,u.xaxis||\"x\"),yaxis:i.getFromId(t,u.yaxis||\"y\"),plot:e.plot};for(n(t,f,r,o),s=0;s<r.length;s++)l=r[s][0].trace,c=o.selectAll(\"g.trace\"+l.uid+\" .js-line\"),a.setClipUrl(c,r[s][0].carpet._clipPathId,t)}},{\"../../components/drawing\":684,\"../../plots/cartesian/axes\":849,\"../scatter/plot\":1235}],1256:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../scatter/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../components/colorscale/attributes\"),l=t(\"../../components/drawing/attributes\").dash,c=t(\"../../lib/extend\").extendFlat,u=t(\"../../plot_api/edit_types\").overrideAll,f=a.marker,h=a.line,p=f.line;e.exports=u({lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country 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n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/text_defaults\"),l=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function f(r,i){return n.coerce(t,e,c,r,i)}var h,p=f(\"locations\");if(p&&p.length){var d,m=f(\"geojson\");(\"string\"==typeof m&&\"\"!==m||n.isPlainObject(m))&&(d=\"geojson-id\"),\"geojson-id\"===f(\"locationmode\",d)&&f(\"featureidkey\"),h=p.length}else{var g=f(\"lon\")||[],v=f(\"lat\")||[];h=Math.min(g.length,v.length)}h?(e._length=h,f(\"text\"),f(\"hovertext\"),f(\"hovertemplate\"),f(\"mode\"),i.hasLines(e)&&(o(t,e,r,u,f),f(\"connectgaps\")),i.hasMarkers(e)&&a(t,e,r,u,f,{gradient:!0}),i.hasText(e)&&(f(\"texttemplate\"),s(t,e,u,f)),f(\"fill\"),\"none\"!==e.fill&&l(t,e,r,f),n.coerceSelectionMarkerOpacity(e,f)):e.visible=!1}},{\"../../lib\":799,\"../scatter/fillcolor_defaults\":1222,\"../scatter/line_defaults\":1227,\"../scatter/marker_defaults\":1233,\"../scatter/subtypes\":1239,\"../scatter/text_defaults\":1240,\"./attributes\":1256}],1259:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,i){t.lon=e.lon,t.lat=e.lat,t.location=e.loc?e.loc:null;var a=n[i];return a.fIn&&a.fIn.properties&&(t.properties=a.fIn.properties),t}},{}],1260:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\");e.exports=function(t,e,r){var i={},a=r[e.geo]._subplot.mockAxis,o=t.lonlat;return i.lonLabel=n.tickText(a,a.c2l(o[0]),!0).text,i.latLabel=n.tickText(a,a.c2l(o[1]),!0).text,i}},{\"../../plots/cartesian/axes\":849}],1261:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx\"),i=t(\"../../constants/numerical\").BADNUM,a=t(\"../scatter/get_trace_color\"),o=t(\"../../lib\").fillText,s=t(\"./attributes\");e.exports=function(t,e,r){var l=t.cd,c=l[0].trace,u=t.xa,f=t.ya,h=t.subplot,p=h.projection.isLonLatOverEdges,d=h.project;if(n.getClosest(l,(function(t){var n=t.lonlat;if(n[0]===i)return 1/0;if(p(n))return 1/0;var a=d(n),o=d([e,r]),s=Math.abs(a[0]-o[0]),l=Math.abs(a[1]-o[1]),c=Math.max(3,t.mrc||0);return Math.max(Math.sqrt(s*s+l*l)-c,1-3/c)}),t),!1!==t.index){var m=l[t.index],g=m.lonlat,v=[u.c2p(g),f.c2p(g)],y=m.mrc||1;t.x0=v[0]-y,t.x1=v[0]+y,t.y0=v[1]-y,t.y1=v[1]+y,t.loc=m.loc,t.lon=g[0],t.lat=g[1];var x={};x[c.geo]={_subplot:h};var b=c._module.formatLabels(m,c,x);return t.lonLabel=b.lonLabel,t.latLabel=b.latLabel,t.color=a(c,m),t.extraText=function(t,e,r,n){if(t.hovertemplate)return;var i=e.hi||t.hoverinfo,a=\"all\"===i?s.hoverinfo.flags:i.split(\"+\"),l=-1!==a.indexOf(\"location\")&&Array.isArray(t.locations),c=-1!==a.indexOf(\"lon\"),u=-1!==a.indexOf(\"lat\"),f=-1!==a.indexOf(\"text\"),h=[];function p(t){return t+\"\\xb0\"}l?h.push(e.loc):c&&u?h.push(\"(\"+p(r.latLabel)+\", \"+p(r.lonLabel)+\")\"):c?h.push(n.lon+p(r.lonLabel)):u&&h.push(n.lat+p(r.latLabel));f&&o(e,t,h);return h.join(\"<br>\")}(c,m,t,l[0].t.labels),t.hovertemplate=c.hovertemplate,[t]}}},{\"../../components/fx\":702,\"../../constants/numerical\":775,\"../../lib\":799,\"../scatter/get_trace_color\":1224,\"./attributes\":1256}],1262:[function(t,e,r){\"use 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n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=t(\"../../lib/topojson_utils\").getTopojsonFeatures,o=t(\"../../lib/geojson_utils\"),s=t(\"../../lib/geo_location_utils\"),l=t(\"../../plots/cartesian/autorange\").findExtremes,c=t(\"../../constants/numerical\").BADNUM,u=t(\"../scatter/calc\").calcMarkerSize,f=t(\"../scatter/subtypes\"),h=t(\"./style\");e.exports={calcGeoJSON:function(t,e){var r,n,i=t[0].trace,o=e[i.geo],f=o._subplot,h=i._length;if(Array.isArray(i.locations)){var p=i.locationmode,d=\"geojson-id\"===p?s.extractTraceFeature(t):a(i,f.topojson);for(r=0;r<h;r++){n=t[r];var m=\"geojson-id\"===p?n.fOut:s.locationToFeature(p,n.loc,d);n.lonlat=m?m.properties.ct:[c,c]}}var g,v,y={padded:!0};if(\"geojson\"===o.fitbounds&&\"geojson-id\"===i.locationmode){var x=s.computeBbox(s.getTraceGeojson(i));g=[x[0],x[2]],v=[x[1],x[3]]}else{for(g=new Array(h),v=new Array(h),r=0;r<h;r++)n=t[r],g[r]=n.lonlat[0],v[r]=n.lonlat[1];y.ppad=u(i,h)}i._extremes.lon=l(o.lonaxis._ax,g,y),i._extremes.lat=l(o.lataxis._ax,v,y)},plot:function(t,e,r){var a=e.layers.frontplot.select(\".scatterlayer\"),s=i.makeTraceGroups(a,r,\"trace scattergeo\");function l(t,e){t.lonlat[0]===c&&n.select(e).remove()}s.selectAll(\"*\").remove(),s.each((function(e){var r=n.select(this),a=e[0].trace;if(f.hasLines(a)||\"none\"!==a.fill){var s=o.calcTraceToLineCoords(e),c=\"none\"!==a.fill?o.makePolygon(s):o.makeLine(s);r.selectAll(\"path.js-line\").data([{geojson:c,trace:a}]).enter().append(\"path\").classed(\"js-line\",!0).style(\"stroke-miterlimit\",2)}f.hasMarkers(a)&&r.selectAll(\"path.point\").data(i.identity).enter().append(\"path\").classed(\"point\",!0).each((function(t){l(t,this)})),f.hasText(a)&&r.selectAll(\"g\").data(i.identity).enter().append(\"g\").append(\"text\").each((function(t){l(t,this)})),h(t,e)}))}}},{\"../../constants/numerical\":775,\"../../lib\":799,\"../../lib/geo_location_utils\":792,\"../../lib/geojson_utils\":793,\"../../lib/topojson_utils\":827,\"../../plots/cartesian/autorange\":848,\"../scatter/calc\":1215,\"../scatter/subtypes\":1239,\"./style\":1265,\"@plotly/d3\":58}],1264:[function(t,e,r){\"use strict\";var n=t(\"../scatter/subtypes\"),i=t(\"../../constants/numerical\").BADNUM;e.exports=function(t,e){var 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n=t(\"../../lib\"),i=t(\"../../registry\"),a=t(\"./helpers\"),o=t(\"./attributes\"),s=t(\"../scatter/constants\"),l=t(\"../scatter/subtypes\"),c=t(\"../scatter/xy_defaults\"),u=t(\"../scatter/period_defaults\"),f=t(\"../scatter/marker_defaults\"),h=t(\"../scatter/line_defaults\"),p=t(\"../scatter/fillcolor_defaults\"),d=t(\"../scatter/text_defaults\");e.exports=function(t,e,r,m){function g(r,i){return n.coerce(t,e,o,r,i)}var v=!!t.marker&&a.isOpenSymbol(t.marker.symbol),y=l.isBubble(t),x=c(t,e,m,g);if(x){u(t,e,m,g),g(\"xhoverformat\"),g(\"yhoverformat\");var b=x<s.PTS_LINESONLY?\"lines+markers\":\"lines\";g(\"text\"),g(\"hovertext\"),g(\"hovertemplate\"),g(\"mode\",b),l.hasLines(e)&&(g(\"connectgaps\"),h(t,e,r,m,g),g(\"line.shape\")),l.hasMarkers(e)&&(f(t,e,r,m,g),g(\"marker.line.width\",v||y?1:0)),l.hasText(e)&&(g(\"texttemplate\"),d(t,e,m,g));var _=(e.line||{}).color,w=(e.marker||{}).color;g(\"fill\"),\"none\"!==e.fill&&p(t,e,r,g);var T=i.getComponentMethod(\"errorbars\",\"supplyDefaults\");T(t,e,_||w||r,{axis:\"y\"}),T(t,e,_||w||r,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,g)}else e.visible=!1}},{\"../../lib\":799,\"../../registry\":927,\"../scatter/constants\":1218,\"../scatter/fillcolor_defaults\":1222,\"../scatter/line_defaults\":1227,\"../scatter/marker_defaults\":1233,\"../scatter/period_defaults\":1234,\"../scatter/subtypes\":1239,\"../scatter/text_defaults\":1240,\"../scatter/xy_defaults\":1241,\"./attributes\":1266,\"./helpers\":1273}],1271:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\"),a=t(\"../../constants/interactions\").DESELECTDIM;e.exports={styleTextSelection:function(t){var e,r,o=t[0],s=o.trace,l=o.t,c=l._scene,u=l.index,f=c.selectBatch[u],h=c.unselectBatch[u],p=c.textOptions[u],d=c.textSelectedOptions[u]||{},m=c.textUnselectedOptions[u]||{},g=n.extendFlat({},p);if(f.length||h.length){var v=d.color,y=m.color,x=p.color,b=Array.isArray(x);for(g.color=new Array(s._length),e=0;e<f.length;e++)r=f[e],g.color[r]=v||(b?x[r]:x);for(e=0;e<h.length;e++){r=h[e];var _=b?x[r]:x;g.color[r]=y||(v?_:i.addOpacity(_,a))}}c.glText[u].update(g)}}},{\"../../components/color\":662,\"../../constants/interactions\":774,\"../../lib\":799}],1272:[function(t,e,r){\"use strict\";var n=t(\"../scatter/format_labels\");e.exports=function(t,e,r){var i=t.i;return\"x\"in t||(t.x=e._x[i]),\"y\"in t||(t.y=e._y[i]),n(t,e,r)}},{\"../scatter/format_labels\":1223}],1273:[function(t,e,r){\"use strict\";var n=t(\"./constants\");r.isOpenSymbol=function(t){return\"string\"==typeof t?n.OPEN_RE.test(t):t%200>100},r.isDotSymbol=function(t){return\"string\"==typeof t?n.DOT_RE.test(t):t>200}},{\"./constants\":1268}],1274:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../scatter/get_trace_color\");function o(t,e,r,o){var s=t.xa,l=t.ya,c=t.distance,u=t.dxy,f=t.index,h={pointNumber:f,x:e[f],y:r[f]};h.tx=Array.isArray(o.text)?o.text[f]:o.text,h.htx=Array.isArray(o.hovertext)?o.hovertext[f]:o.hovertext,h.data=Array.isArray(o.customdata)?o.customdata[f]:o.customdata,h.tp=Array.isArray(o.textposition)?o.textposition[f]:o.textposition;var p=o.textfont;p&&(h.ts=i.isArrayOrTypedArray(p.size)?p.size[f]:p.size,h.tc=Array.isArray(p.color)?p.color[f]:p.color,h.tf=Array.isArray(p.family)?p.family[f]:p.family);var d=o.marker;d&&(h.ms=i.isArrayOrTypedArray(d.size)?d.size[f]:d.size,h.mo=i.isArrayOrTypedArray(d.opacity)?d.opacity[f]:d.opacity,h.mx=i.isArrayOrTypedArray(d.symbol)?d.symbol[f]:d.symbol,h.mc=i.isArrayOrTypedArray(d.color)?d.color[f]:d.color);var m=d&&d.line;m&&(h.mlc=Array.isArray(m.color)?m.color[f]:m.color,h.mlw=i.isArrayOrTypedArray(m.width)?m.width[f]:m.width);var g=d&&d.gradient;g&&\"none\"!==g.type&&(h.mgt=Array.isArray(g.type)?g.type[f]:g.type,h.mgc=Array.isArray(g.color)?g.color[f]:g.color);var v=s.c2p(h.x,!0),y=l.c2p(h.y,!0),x=h.mrc||1,b=o.hoverlabel;b&&(h.hbg=Array.isArray(b.bgcolor)?b.bgcolor[f]:b.bgcolor,h.hbc=Array.isArray(b.bordercolor)?b.bordercolor[f]:b.bordercolor,h.hts=i.isArrayOrTypedArray(b.font.size)?b.font.size[f]:b.font.size,h.htc=Array.isArray(b.font.color)?b.font.color[f]:b.font.color,h.htf=Array.isArray(b.font.family)?b.font.family[f]:b.font.family,h.hnl=i.isArrayOrTypedArray(b.namelength)?b.namelength[f]:b.namelength);var _=o.hoverinfo;_&&(h.hi=Array.isArray(_)?_[f]:_);var w=o.hovertemplate;w&&(h.ht=Array.isArray(w)?w[f]:w);var T={};T[t.index]=h;var k=o._origX,M=o._origY,A=i.extendFlat({},t,{color:a(o,h),x0:v-x,x1:v+x,xLabelVal:k?k[f]:h.x,y0:y-x,y1:y+x,yLabelVal:M?M[f]:h.y,cd:T,distance:c,spikeDistance:u,hovertemplate:h.ht});return h.htx?A.text=h.htx:h.tx?A.text=h.tx:o.text&&(A.text=o.text),i.fillText(h,o,A),n.getComponentMethod(\"errorbars\",\"hoverInfo\")(h,o,A),A}e.exports={hoverPoints:function(t,e,r,n){var i,a,s,l,c,u,f,h,p,d=t.cd,m=d[0].t,g=d[0].trace,v=t.xa,y=t.ya,x=m.x,b=m.y,_=v.c2p(e),w=y.c2p(r),T=t.distance;if(m.tree){var k=v.p2c(_-T),M=v.p2c(_+T),A=y.p2c(w-T),S=y.p2c(w+T);i=\"x\"===n?m.tree.range(Math.min(k,M),Math.min(y._rl[0],y._rl[1]),Math.max(k,M),Math.max(y._rl[0],y._rl[1])):m.tree.range(Math.min(k,M),Math.min(A,S),Math.max(k,M),Math.max(A,S))}else i=m.ids;var E=T;if(\"x\"===n)for(c=0;c<i.length;c++)s=x[i[c]],u=Math.abs(v.c2p(s)-_),g._origX&&void 0!==g._origX[c]&&(u+=v.c2p(g._origX[c])-v.c2p(s)),u<E&&(E=u,f=y.c2p(b[i[c]])-w,g._origY&&void 0!==g._origY[c]&&(f+=y.c2p(g._origY[c])-y.c2p(l)),p=Math.sqrt(u*u+f*f),a=i[c]);else for(c=i.length-1;c>-1;c--)s=x[i[c]],l=b[i[c]],u=v.c2p(s)-_,f=y.c2p(l)-w,(h=Math.sqrt(u*u+f*f))<E&&(E=p=h,a=i[c]);return t.index=a,t.distance=E,t.dxy=p,void 0===a?[t]:[o(t,x,b,g)]},calcHover:o}},{\"../../lib\":799,\"../../registry\":927,\"../scatter/get_trace_color\":1224}],1275:[function(t,e,r){\"use strict\";var n=t(\"./hover\");e.exports={moduleType:\"trace\",name:\"scattergl\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"gl\",\"regl\",\"cartesian\",\"symbols\",\"errorBarsOK\",\"showLegend\",\"scatter-like\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"../scatter/cross_trace_defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"./format_labels\"),calc:t(\"./calc\"),plot:t(\"./plot\"),hoverPoints:n.hoverPoints,selectPoints:t(\"./select\"),meta:{}}},{\"../../plots/cartesian\":863,\"../scatter/cross_trace_defaults\":1220,\"../scatter/marker_colorbar\":1232,\"./attributes\":1266,\"./calc\":1267,\"./defaults\":1270,\"./format_labels\":1272,\"./hover\":1274,\"./plot\":1276,\"./select\":1278}],1276:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),i=t(\"regl-line2d\"),a=t(\"regl-error2d\"),o=t(\"gl-text\"),s=t(\"../../lib\"),l=t(\"../../components/dragelement/helpers\").selectMode,c=t(\"../../lib/prepare_regl\"),u=t(\"../scatter/subtypes\"),f=t(\"../scatter/link_traces\"),h=t(\"./edit_style\").styleTextSelection;function p(t,e,r){var n=t._size,i=t.width,a=t.height;return[n.l+e.domain[0]*n.w,n.b+r.domain[0]*n.h,i-n.r-(1-e.domain[1])*n.w,a-n.t-(1-r.domain[1])*n.h]}e.exports=function(t,e,r){if(r.length){var d,m,g=t._fullLayout,v=e._scene,y=e.xaxis,x=e.yaxis;if(v)if(c(t,[\"ANGLE_instanced_arrays\",\"OES_element_index_uint\"])){var b=v.count,_=g._glcanvas.data()[0].regl;if(f(t,e,r),v.dirty){if(!0===v.error2d&&(v.error2d=a(_)),!0===v.line2d&&(v.line2d=i(_)),!0===v.scatter2d&&(v.scatter2d=n(_,{constPointSize:!0})),!0===v.fill2d&&(v.fill2d=i(_)),!0===v.glText)for(v.glText=new Array(b),d=0;d<b;d++)v.glText[d]=new o(_);if(v.glText){if(b>v.glText.length){var w=b-v.glText.length;for(d=0;d<w;d++)v.glText.push(new o(_))}else if(b<v.glText.length){var T=v.glText.length-b;v.glText.splice(b,T).forEach((function(t){t.destroy()}))}for(d=0;d<b;d++)v.glText[d].update(v.textOptions[d])}if(v.line2d&&(v.line2d.update(v.lineOptions),v.lineOptions=v.lineOptions.map((function(t){if(t&&t.positions){for(var e=t.positions,r=0;r<e.length&&(isNaN(e[r])||isNaN(e[r+1]));)r+=2;for(var n=e.length-2;n>r&&(isNaN(e[n])||isNaN(e[n+1]));)n-=2;t.positions=e.slice(r,n+2)}return t})),v.line2d.update(v.lineOptions)),v.error2d){var k=(v.errorXOptions||[]).concat(v.errorYOptions||[]);v.error2d.update(k)}v.scatter2d&&v.scatter2d.update(v.markerOptions),v.fillOrder=s.repeat(null,b),v.fill2d&&(v.fillOptions=v.fillOptions.map((function(t,e){var n=r[e];if(t&&n&&n[0]&&n[0].trace){var i,a,o=n[0],s=o.trace,l=o.t,c=v.lineOptions[e],u=[];s._ownfill&&u.push(e),s._nexttrace&&u.push(e+1),u.length&&(v.fillOrder[e]=u);var f,h,p=[],d=c&&c.positions||l.positions;if(\"tozeroy\"===s.fill){for(f=0;f<d.length&&isNaN(d[f+1]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h+1]);)h-=2;0!==d[f+1]&&(p=[d[f],0]),p=p.concat(d.slice(f,h+2)),0!==d[h+1]&&(p=p.concat([d[h],0]))}else if(\"tozerox\"===s.fill){for(f=0;f<d.length&&isNaN(d[f]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h]);)h-=2;0!==d[f]&&(p=[0,d[f+1]]),p=p.concat(d.slice(f,h+2)),0!==d[h]&&(p=p.concat([0,d[h+1]]))}else if(\"toself\"===s.fill||\"tonext\"===s.fill){for(p=[],i=0,t.splitNull=!0,a=0;a<d.length;a+=2)(isNaN(d[a])||isNaN(d[a+1]))&&((p=p.concat(d.slice(i,a))).push(d[i],d[i+1]),p.push(null,null),i=a+2);p=p.concat(d.slice(i)),i&&p.push(d[i],d[i+1])}else{var m=s._nexttrace;if(m){var g=v.lineOptions[e+1];if(g){var y=g.positions;if(\"tonexty\"===s.fill){for(p=d.slice(),e=Math.floor(y.length/2);e--;){var x=y[2*e],b=y[2*e+1];isNaN(x)||isNaN(b)||p.push(x,b)}t.fill=m.fillcolor}}}}if(s._prevtrace&&\"tonext\"===s._prevtrace.fill){var _=v.lineOptions[e-1].positions,w=p.length/2,T=[i=w];for(a=0;a<_.length;a+=2)(isNaN(_[a])||isNaN(_[a+1]))&&(T.push(a/2+w+1),i=a+2);p=p.concat(_),t.hole=T}return t.fillmode=s.fill,t.opacity=s.opacity,t.positions=p,t}})),v.fill2d.update(v.fillOptions))}var M=g.dragmode,A=l(M),S=g.clickmode.indexOf(\"select\")>-1;for(d=0;d<b;d++){var E=r[d][0],L=E.trace,C=E.t,P=C.index,I=L._length,O=C.x,z=C.y;if(L.selectedpoints||A||S){if(A||(A=!0),L.selectedpoints){var D=v.selectBatch[P]=s.selIndices2selPoints(L),R={};for(m=0;m<D.length;m++)R[D[m]]=1;var F=[];for(m=0;m<I;m++)R[m]||F.push(m);v.unselectBatch[P]=F}var B=C.xpx=new Array(I),N=C.ypx=new Array(I);for(m=0;m<I;m++)B[m]=y.c2p(O[m]),N[m]=x.c2p(z[m])}else C.xpx=C.ypx=null}if(A){if(v.select2d||(v.select2d=n(g._glcanvas.data()[1].regl)),v.scatter2d){var j=new Array(b);for(d=0;d<b;d++)j[d]=v.selectBatch[d].length||v.unselectBatch[d].length?v.markerUnselectedOptions[d]:{};v.scatter2d.update(j)}v.select2d&&(v.select2d.update(v.markerOptions),v.select2d.update(v.markerSelectedOptions)),v.glText&&r.forEach((function(t){var e=((t||[])[0]||{}).trace||{};u.hasText(e)&&h(t)}))}else v.scatter2d&&v.scatter2d.update(v.markerOptions);var U={viewport:p(g,y,x),range:[(y._rl||y.range)[0],(x._rl||x.range)[0],(y._rl||y.range)[1],(x._rl||x.range)[1]]},V=s.repeat(U,v.count);v.fill2d&&v.fill2d.update(V),v.line2d&&v.line2d.update(V),v.error2d&&v.error2d.update(V.concat(V)),v.scatter2d&&v.scatter2d.update(V),v.select2d&&v.select2d.update(V),v.glText&&v.glText.forEach((function(t){t.update(U)}))}else v.init()}}},{\"../../components/dragelement/helpers\":680,\"../../lib\":799,\"../../lib/prepare_regl\":812,\"../scatter/link_traces\":1230,\"../scatter/subtypes\":1239,\"./edit_style\":1271,\"gl-text\":351,\"regl-error2d\":532,\"regl-line2d\":533,\"regl-scatter2d\":534}],1277:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){var r=e._scene,i={count:0,dirty:!0,lineOptions:[],fillOptions:[],markerOptions:[],markerSelectedOptions:[],markerUnselectedOptions:[],errorXOptions:[],errorYOptions:[],textOptions:[],textSelectedOptions:[],textUnselectedOptions:[],selectBatch:[],unselectBatch:[]},a={fill2d:!1,scatter2d:!1,error2d:!1,line2d:!1,glText:!1,select2d:!1};return e._scene||((r=e._scene={}).init=function(){n.extendFlat(r,a,i)},r.init(),r.update=function(t){var e=n.repeat(t,r.count);if(r.fill2d&&r.fill2d.update(e),r.scatter2d&&r.scatter2d.update(e),r.line2d&&r.line2d.update(e),r.error2d&&r.error2d.update(e.concat(e)),r.select2d&&r.select2d.update(e),r.glText)for(var i=0;i<r.count;i++)r.glText[i].update(t)},r.draw=function(){for(var t=r.count,e=r.fill2d,i=r.error2d,a=r.line2d,o=r.scatter2d,s=r.glText,l=r.select2d,c=r.selectBatch,u=r.unselectBatch,f=0;f<t;f++){if(e&&r.fillOrder[f]&&e.draw(r.fillOrder[f]),a&&r.lineOptions[f]&&a.draw(f),i&&(r.errorXOptions[f]&&i.draw(f),r.errorYOptions[f]&&i.draw(f+t)),o&&r.markerOptions[f])if(u[f].length){var h=n.repeat([],r.count);h[f]=u[f],o.draw(h)}else c[f].length||o.draw(f);s[f]&&r.textOptions[f]&&s[f].render()}l&&l.draw(c),r.dirty=!1},r.destroy=function(){r.fill2d&&r.fill2d.destroy&&r.fill2d.destroy(),r.scatter2d&&r.scatter2d.destroy&&r.scatter2d.destroy(),r.error2d&&r.error2d.destroy&&r.error2d.destroy(),r.line2d&&r.line2d.destroy&&r.line2d.destroy(),r.select2d&&r.select2d.destroy&&r.select2d.destroy(),r.glText&&r.glText.forEach((function(t){t.destroy&&t.destroy()})),r.lineOptions=null,r.fillOptions=null,r.markerOptions=null,r.markerSelectedOptions=null,r.markerUnselectedOptions=null,r.errorXOptions=null,r.errorYOptions=null,r.textOptions=null,r.textSelectedOptions=null,r.textUnselectedOptions=null,r.selectBatch=null,r.unselectBatch=null,e._scene=null}),r.dirty||n.extendFlat(r,i),r}},{\"../../lib\":799}],1278:[function(t,e,r){\"use strict\";var n=t(\"../scatter/subtypes\"),i=t(\"./edit_style\").styleTextSelection;e.exports=function(t,e){var r=t.cd,a=t.xaxis,o=t.yaxis,s=[],l=r[0].trace,c=r[0].t,u=l._length,f=c.x,h=c.y,p=c._scene,d=c.index;if(!p)return s;var m=n.hasText(l),g=n.hasMarkers(l),v=!g&&!m;if(!0!==l.visible||v)return s;var y=[],x=[];if(!1!==e&&!e.degenerate)for(var b=0;b<u;b++)e.contains([c.xpx[b],c.ypx[b]],!1,b,t)?(y.push(b),s.push({pointNumber:b,x:a.c2d(f[b]),y:o.c2d(h[b])})):x.push(b);if(g){var _=p.scatter2d;if(y.length||x.length){if(!p.selectBatch[d].length&&!p.unselectBatch[d].length){var w=new Array(p.count);w[d]=p.markerUnselectedOptions[d],_.update.apply(_,w)}}else{var T=new Array(p.count);T[d]=p.markerOptions[d],_.update.apply(_,T)}}return p.selectBatch[d]=y,p.unselectBatch[d]=x,m&&i(r),s}},{\"../scatter/subtypes\":1239,\"./edit_style\":1271}],1279:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../scattergeo/attributes\"),o=t(\"../scatter/attributes\"),s=t(\"../../plots/mapbox/layout_attributes\"),l=t(\"../../plots/attributes\"),c=t(\"../../components/colorscale/attributes\"),u=t(\"../../lib/extend\").extendFlat,f=t(\"../../plot_api/edit_types\").overrideAll,h=a.line,p=a.marker;e.exports=f({lon:a.lon,lat:a.lat,mode:u({},o.mode,{dflt:\"markers\"}),text:u({},o.text,{}),texttemplate:i({editType:\"plot\"},{keys:[\"lat\",\"lon\",\"text\"]}),hovertext:u({},o.hovertext,{}),line:{color:h.color,width:h.width},connectgaps:o.connectgaps,marker:u({symbol:{valType:\"string\",dflt:\"circle\",arrayOk:!0},angle:{valType:\"number\",dflt:\"auto\",arrayOk:!0},allowoverlap:{valType:\"boolean\",dflt:!1},opacity:p.opacity,size:p.size,sizeref:p.sizeref,sizemin:p.sizemin,sizemode:p.sizemode},c(\"marker\")),fill:a.fill,fillcolor:o.fillcolor,textfont:s.layers.symbol.textfont,textposition:s.layers.symbol.textposition,below:{valType:\"string\"},selected:{marker:o.selected.marker},unselected:{marker:o.unselected.marker},hoverinfo:u({},l.hoverinfo,{flags:[\"lon\",\"lat\",\"text\",\"name\"]}),hovertemplate:n()},\"calc\",\"nested\")},{\"../../components/colorscale/attributes\":669,\"../../lib/extend\":789,\"../../plot_api/edit_types\":831,\"../../plots/attributes\":845,\"../../plots/mapbox/layout_attributes\":909,\"../../plots/template_attributes\":922,\"../scatter/attributes\":1214,\"../scattergeo/attributes\":1256}],1280:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"../../constants/numerical\").BADNUM,o=t(\"../../lib/geojson_utils\"),s=t(\"../../components/colorscale\"),l=t(\"../../components/drawing\"),c=t(\"../scatter/make_bubble_size_func\"),u=t(\"../scatter/subtypes\"),f=t(\"../../plots/mapbox/convert_text_opts\"),h=t(\"../../components/fx/helpers\").appendArrayPointValue,p=t(\"../../lib/svg_text_utils\").NEWLINES,d=t(\"../../lib/svg_text_utils\").BR_TAG_ALL;function m(){return{geojson:o.makeBlank(),layout:{visibility:\"none\"},paint:{}}}function g(t,e){return i.isArrayOrTypedArray(t)?e?function(e){return n(t[e])?+t[e]:0}:function(e){return t[e]}:t?function(){return t}:v}function v(){return\"\"}function y(t){return t[0]===a}e.exports=function(t,e){var 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n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/line_shape_defaults\"),l=t(\"../scatter/text_defaults\"),c=t(\"../scatter/fillcolor_defaults\"),u=t(\"../scatter/constants\").PTS_LINESONLY,f=t(\"./attributes\");function h(t,e,r,n){var i,a=n(\"r\"),o=n(\"theta\");if(a)o?i=Math.min(a.length,o.length):(i=a.length,n(\"theta0\"),n(\"dtheta\"));else{if(!o)return 0;i=e.theta.length,n(\"r0\"),n(\"dr\")}return e._length=i,i}e.exports={handleRThetaDefaults:h,supplyDefaults:function(t,e,r,p){function d(r,i){return n.coerce(t,e,f,r,i)}var m=h(t,e,p,d);if(m){d(\"thetaunit\"),d(\"mode\",m<u?\"lines+markers\":\"lines\"),d(\"text\"),d(\"hovertext\"),\"fills\"!==e.hoveron&&d(\"hovertemplate\"),i.hasLines(e)&&(o(t,e,r,p,d),s(t,e,d),d(\"connectgaps\")),i.hasMarkers(e)&&a(t,e,r,p,d,{gradient:!0}),i.hasText(e)&&(d(\"texttemplate\"),l(t,e,p,d));var g=[];(i.hasMarkers(e)||i.hasText(e))&&(d(\"cliponaxis\"),d(\"marker.maxdisplayed\"),g.push(\"points\")),d(\"fill\"),\"none\"!==e.fill&&(c(t,e,r,d),i.hasLines(e)||s(t,e,d)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||g.push(\"fills\"),d(\"hoveron\",g.join(\"+\")||\"points\"),n.coerceSelectionMarkerOpacity(e,d)}else e.visible=!1}}},{\"../../lib\":799,\"../scatter/constants\":1218,\"../scatter/fillcolor_defaults\":1222,\"../scatter/line_defaults\":1227,\"../scatter/line_shape_defaults\":1229,\"../scatter/marker_defaults\":1233,\"../scatter/subtypes\":1239,\"../scatter/text_defaults\":1240,\"./attributes\":1288}],1291:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../plots/cartesian/axes\");e.exports=function(t,e,r){var a,o,s={},l=r[e.subplot]._subplot;l?(a=l.radialAxis,o=l.angularAxis):(a=(l=r[e.subplot]).radialaxis,o=l.angularaxis);var c=a.c2l(t.r);s.rLabel=i.tickText(a,c,!0).text;var u=\"degrees\"===o.thetaunit?n.rad2deg(t.theta):t.theta;return 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i=r._fullLayout,a=r._fullData[d.index],s=n.select(this).datum();if(d._hasHoverEvent&&(e.originalEvent=n.event,r.emit(\"plotly_unhover\",{points:[f(s,a,h.eventDataKeys)],event:n.event}),d._hasHoverEvent=!1),d._hasHoverLabel&&(o.loneUnhover(i._hoverlayer.node()),d._hasHoverLabel=!1),v){var l=t.select(\"path.surface\");h.styleOne(l,s,a,{hovered:!1})}})),t.on(\"click\",(function(t){var e=r._fullLayout,a=r._fullData[d.index],s=g&&(c.isHierarchyRoot(t)||c.isLeaf(t)),u=c.getPtId(t),p=c.isEntry(t)?c.findEntryWithChild(m,u):c.findEntryWithLevel(m,u),v=c.getPtId(p),y={points:[f(t,a,h.eventDataKeys)],event:n.event};s||(y.nextLevel=v);var x=l.triggerHandler(r,\"plotly_\"+d.type+\"click\",y);if(!1!==x&&e.hovermode&&(r._hoverdata=[f(t,a,h.eventDataKeys)],o.click(r,n.event)),!s&&!1!==x&&!r._dragging&&!r._transitioning){i.call(\"_storeDirectGUIEdit\",a,e._tracePreGUI[a.uid],{level:a.level});var b={data:[{level:v}],traces:[d.index]},_={frame:{redraw:!1,duration:h.transitionTime},transition:{duration:h.transitionTime,easing:h.transitionEasing},mode:\"immediate\",fromcurrent:!0};o.loneUnhover(e._hoverlayer.node()),i.call(\"animate\",r,b,_)}}))}},{\"../../components/fx\":702,\"../../components/fx/helpers\":698,\"../../lib\":799,\"../../lib/events\":788,\"../../registry\":927,\"../pie/helpers\":1193,\"./helpers\":1332,\"@plotly/d3\":58}],1332:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\"),a=t(\"../../lib/setcursor\"),o=t(\"../pie/helpers\");function s(t){return t.data.data.pid}r.findEntryWithLevel=function(t,e){var n;return e&&t.eachAfter((function(t){if(r.getPtId(t)===e)return n=t.copy()})),n||t},r.findEntryWithChild=function(t,e){var n;return t.eachAfter((function(t){for(var i=t.children||[],a=0;a<i.length;a++){var o=i[a];if(r.getPtId(o)===e)return 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r.isOutsideText(t,e)?function(t,e,n){return{color:r.getOutsideTextFontKey(\"color\",t,e,n),family:r.getOutsideTextFontKey(\"family\",t,e,n),size:r.getOutsideTextFontKey(\"size\",t,e,n)}}(t,e,a):function(t,e,a,o){var s=(o||{}).onPathbar,l=e.data.data,c=l.i,u=n.castOption(t,c,(s?\"pathbar.textfont\":\"insidetextfont\")+\".color\");return!u&&t._input.textfont&&(u=n.castOption(t._input,c,\"textfont.color\")),{color:u||i.contrast(l.color),family:r.getInsideTextFontKey(\"family\",t,e,a,o),size:r.getInsideTextFontKey(\"size\",t,e,a,o)}}(t,e,a,o)},r.hasTransition=function(t){return!!(t&&t.duration>0)},r.getMaxDepth=function(t){return t.maxdepth>=0?t.maxdepth:1/0},r.isHeader=function(t,e){return!(r.isLeaf(t)||t.depth===e._maxDepth-1)},r.getParent=function(t,e){return r.findEntryWithLevel(t,s(e))},r.listPath=function(t,e){var n=t.parent;if(!n)return[];var i=e?[n.data[e]]:[n];return r.listPath(n,e).concat(i)},r.getPath=function(t){return r.listPath(t,\"label\").join(\"/\")+\"/\"},r.formatValue=o.formatPieValue,r.formatPercent=function(t,e){var r=n.formatPercent(t,0);return\"0%\"===r&&(r=o.formatPiePercent(t,e)),r}},{\"../../components/color\":662,\"../../lib\":799,\"../../lib/setcursor\":820,\"../pie/helpers\":1193}],1333:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"sunburst\",basePlotModule:t(\"./base_plot\"),categories:[],animatable:!0,attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\"),supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\").style,colorbar:t(\"../scatter/marker_colorbar\"),meta:{}}},{\"../scatter/marker_colorbar\":1232,\"./attributes\":1326,\"./base_plot\":1327,\"./calc\":1328,\"./defaults\":1330,\"./layout_attributes\":1334,\"./layout_defaults\":1335,\"./plot\":1336,\"./style\":1337}],1334:[function(t,e,r){\"use 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M={};u.label&&(M.label=u.label),u.hasOwnProperty(\"v\")&&(M.value=u.v,M.valueLabel=x.formatValue(u.v,l)),M.currentPath=x.getPath(t.data),h||(M.percentParent=d/x.getValue(p),M.percentParentLabel=x.formatPercent(M.percentParent,l),M.parent=x.getPtLabel(p)),M.percentEntry=d/x.getValue(e),M.percentEntryLabel=x.formatPercent(M.percentEntry,l),M.entry=x.getPtLabel(e),M.percentRoot=d/x.getValue(f),M.percentRootLabel=x.formatPercent(M.percentRoot,l),M.root=x.getPtLabel(f),u.hasOwnProperty(\"color\")&&(M.color=u.color);var A=o.castOption(r,u.i,\"text\");return(o.isValidTextValue(A)||\"\"===A)&&(M.text=A),M.customdata=o.castOption(r,u.i,\"customdata\"),o.texttemplateString(k,M,i._d3locale,M,r._meta||{})}},{\"../../components/drawing\":684,\"../../lib\":799,\"../../lib/svg_text_utils\":824,\"../bar/style\":951,\"../bar/uniform_text\":953,\"../pie/helpers\":1193,\"../pie/plot\":1197,\"./constants\":1329,\"./fx\":1331,\"./helpers\":1332,\"./style\":1337,\"@plotly/d3\":58,\"d3-hierarchy\":167}],1337:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../components/color\"),a=t(\"../../lib\"),o=t(\"../bar/uniform_text\").resizeText;function s(t,e,r){var n=e.data.data,o=!e.children,s=n.i,l=a.castOption(r,s,\"marker.line.color\")||i.defaultLine,c=a.castOption(r,s,\"marker.line.width\")||0;t.style(\"stroke-width\",c).call(i.fill,n.color).call(i.stroke,l).style(\"opacity\",o?r.leaf.opacity:null)}e.exports={style:function(t){var e=t._fullLayout._sunburstlayer.selectAll(\".trace\");o(t,e,\"sunburst\"),e.each((function(t){var e=n.select(this),r=t[0].trace;e.style(\"opacity\",r.opacity),e.selectAll(\"path.surface\").each((function(t){n.select(this).call(s,t,r)}))}))},styleOne:s}},{\"../../components/color\":662,\"../../lib\":799,\"../bar/uniform_text\":953,\"@plotly/d3\":58}],1338:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),i=t(\"../../components/colorscale/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../plots/attributes\"),l=t(\"../../lib/extend\").extendFlat,c=t(\"../../plot_api/edit_types\").overrideAll;function u(t){return{show:{valType:\"boolean\",dflt:!1},start:{valType:\"number\",dflt:null,editType:\"plot\"},end:{valType:\"number\",dflt:null,editType:\"plot\"},size:{valType:\"number\",dflt:null,min:0,editType:\"plot\"},project:{x:{valType:\"boolean\",dflt:!1},y:{valType:\"boolean\",dflt:!1},z:{valType:\"boolean\",dflt:!1}},color:{valType:\"color\",dflt:n.defaultLine},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!0},highlightcolor:{valType:\"color\",dflt:n.defaultLine},highlightwidth:{valType:\"number\",min:1,max:16,dflt:2}}}var f=e.exports=c(l({z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:o(),xhoverformat:a(\"x\"),yhoverformat:a(\"y\"),zhoverformat:a(\"z\"),connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},surfacecolor:{valType:\"data_array\"}},i(\"\",{colorAttr:\"z or surfacecolor\",showScaleDflt:!0,autoColorDflt:!1,editTypeOverride:\"calc\"}),{contours:{x:u(),y:u(),z:u()},hidesurface:{valType:\"boolean\",dflt:!1},lightposition:{x:{valType:\"number\",min:-1e5,max:1e5,dflt:10},y:{valType:\"number\",min:-1e5,max:1e5,dflt:1e4},z:{valType:\"number\",min:-1e5,max:1e5,dflt:0}},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05},roughness:{valType:\"number\",min:0,max:1,dflt:.5},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},opacityscale:{valType:\"any\",editType:\"calc\"},_deprecated:{zauto:l({},i.zauto,{}),zmin:l({},i.zmin,{}),zmax:l({},i.zmax,{})},hoverinfo:l({},s.hoverinfo),showlegend:l({},s.showlegend,{dflt:!1})}),\"calc\",\"nested\");f.x.editType=f.y.editType=f.z.editType=\"calc+clearAxisTypes\",f.transforms=void 0},{\"../../components/color\":662,\"../../components/colorscale/attributes\":669,\"../../lib/extend\":789,\"../../plot_api/edit_types\":831,\"../../plots/attributes\":845,\"../../plots/cartesian/axis_format_attributes\":852,\"../../plots/template_attributes\":922}],1339:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":670}],1340:[function(t,e,r){\"use strict\";var n=t(\"gl-surface3d\"),i=t(\"ndarray\"),a=t(\"ndarray-linear-interpolate\").d2,o=t(\"../heatmap/interp2d\"),s=t(\"../heatmap/find_empties\"),l=t(\"../../lib\").isArrayOrTypedArray,c=t(\"../../lib/gl_format_color\").parseColorScale,u=t(\"../../lib/str2rgbarray\"),f=t(\"../../components/colorscale\").extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?i:n.d2l(i,0,r)},p.getZat=function(t,e,r,n){var i=this.data.z[e][t];return null===i&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[e][t]),void 0===r?i:n.d2l(i,0,r)},p.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,i],t.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],t.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){var o=t.dataCoordinate[a];null!=o&&(t.dataCoordinate[a]*=this.scene.dataScale[a])}var s=this.data.hovertext||this.data.text;return Array.isArray(s)&&s[i]&&void 0!==s[i][n]?t.textLabel=s[i][n]:t.textLabel=s||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var d=[2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97,101,103,107,109,113,127,131,137,139,149,151,157,163,167,173,179,181,191,193,197,199,211,223,227,229,233,239,241,251,257,263,269,271,277,281,283,293,307,311,313,317,331,337,347,349,353,359,367,373,379,383,389,397,401,409,419,421,431,433,439,443,449,457,461,463,467,479,487,491,499,503,509,521,523,541,547,557,563,569,571,577,587,593,599,601,607,613,617,619,631,641,643,647,653,659,661,673,677,683,691,701,709,719,727,733,739,743,751,757,761,769,773,787,797,809,811,821,823,827,829,839,853,857,859,863,877,881,883,887,907,911,919,929,937,941,947,953,967,971,977,983,991,997,1009,1013,1019,1021,1031,1033,1039,1049,1051,1061,1063,1069,1087,1091,1093,1097,1103,1109,1117,1123,1129,1151,1153,1163,1171,1181,1187,1193,1201,1213,1217,1223,1229,1231,1237,1249,1259,1277,1279,1283,1289,1291,1297,1301,1303,1307,1319,1321,1327,1361,1367,1373,1381,1399,1409,1423,1427,1429,1433,1439,1447,1451,1453,1459,1471,1481,1483,1487,1489,1493,1499,1511,1523,1531,1543,1549,1553,1559,1567,1571,1579,1583,1597,1601,1607,1609,1613,1619,1621,1627,1637,1657,1663,1667,1669,1693,1697,1699,1709,1721,1723,1733,1741,1747,1753,1759,1777,1783,1787,1789,1801,1811,1823,1831,1847,1861,1867,1871,1873,1877,1879,1889,1901,1907,1913,1931,1933,1949,1951,1973,1979,1987,1993,1997,1999,2003,2011,2017,2027,2029,2039,2053,2063,2069,2081,2083,2087,2089,2099,2111,2113,2129,2131,2137,2141,2143,2153,2161,2179,2203,2207,2213,2221,2237,2239,2243,2251,2267,2269,2273,2281,2287,2293,2297,2309,2311,2333,2339,2341,2347,2351,2357,2371,2377,2381,2383,2389,2393,2399,2411,2417,2423,2437,2441,2447,2459,2467,2473,2477,2503,2521,2531,2539,2543,2549,2551,2557,2579,2591,2593,2609,2617,2621,2633,2647,2657,2659,2663,2671,2677,2683,2687,2689,2693,2699,2707,2711,2713,2719,2729,2731,2741,2749,2753,2767,2777,2789,2791,2797,2801,2803,2819,2833,2837,2843,2851,2857,2861,2879,2887,2897,2903,2909,2917,2927,2939,2953,2957,2963,2969,2971,2999];function m(t,e){if(t<e)return 0;for(var r=0;0===Math.floor(t%e);)t/=e,r++;return r}function g(t){for(var e=[],r=0;r<d.length;r++){var n=d[r];e.push(m(t,n))}return e}function v(t){for(var e=g(t),r=t,n=0;n<d.length;n++)if(e[n]>0){r=d[n];break}return r}function y(t,e){if(!(t<1||e<1)){for(var r=g(t),n=g(e),i=1,a=0;a<d.length;a++)i*=Math.pow(d[a],Math.max(r[a],n[a]));return i}}p.calcXnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getXat(e-1,0),i=this.getXat(e,0);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r},p.calcYnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getYat(0,e-1),i=this.getYat(0,e);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r};var x=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],b=x[9],_=x[13];function w(t,e,r){var n=r[8]+r[2]*e[0]+r[5]*e[1];return t[0]=(r[6]+r[0]*e[0]+r[3]*e[1])/n,t[1]=(r[7]+r[1]*e[0]+r[4]*e[1])/n,t}function T(t,e,r){return function(t,e,r,n){for(var i=[0,0],o=t.shape[0],s=t.shape[1],l=0;l<o;l++)for(var c=0;c<s;c++)r(i,[l,c],n),t.set(l,c,a(e,i[0],i[1]))}(t,e,w,r),t}function k(t,e){for(var r=!1,n=0;n<t.length;n++)if(e===t[n]){r=!0;break}!1===r&&t.push(e)}p.estimateScale=function(t,e){for(var r=1+function(t){if(0!==t.length){for(var e=1,r=0;r<t.length;r++)e=y(e,t[r]);return e}}(0===e?this.calcXnums(t):this.calcYnums(t));r<b;)r*=2;for(;r>_;)r--,r/=v(r),++r<b&&(r=_);var n=Math.round(r/t);return n>1?n:1},p.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],a=t[0].shape[1],o=0|Math.floor(t[0].shape[0]*e+1),s=0|Math.floor(t[0].shape[1]*r+1),l=1+n+1,c=1+a+1,u=i(new Float32Array(l*c),[l,c]),f=[1/e,0,0,0,1/r,0,0,0,1],h=0;h<t.length;++h){this.surface.padField(u,t[h]);var p=i(new Float32Array(o*s),[o,s]);T(p,u,f),t[h]=p}},p.setContourLevels=function(){var t,e,r,n=[[],[],[]],i=[!1,!1,!1],a=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(a=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(a){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=i[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},p.update=function(t){var e,r,n,a,l=this.scene,h=l.fullSceneLayout,p=this.surface,d=c(t),m=l.dataScale,g=t.z[0].length,v=t._ylength,y=l.contourLevels;this.data=t;var x=[];for(e=0;e<3;e++)for(x[e]=[],r=0;r<g;r++)x[e][r]=[];for(r=0;r<g;r++)for(n=0;n<v;n++)x[0][r][n]=this.getXat(r,n,t.xcalendar,h.xaxis),x[1][r][n]=this.getYat(r,n,t.ycalendar,h.yaxis),x[2][r][n]=this.getZat(r,n,t.zcalendar,h.zaxis);if(t.connectgaps)for(t._emptypoints=s(x[2]),o(x[2],t._emptypoints),t._interpolatedZ=[],r=0;r<g;r++)for(t._interpolatedZ[r]=[],n=0;n<v;n++)t._interpolatedZ[r][n]=x[2][r][n];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<v;n++)null==(a=x[e][r][n])?x[e][r][n]=NaN:a=x[e][r][n]*=m[e];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(this.minValues[e]>a&&(this.minValues[e]=a),this.maxValues[e]<a&&(this.maxValues[e]=a));for(e=0;e<3;e++)this.objectOffset[e]=.5*(this.minValues[e]+this.maxValues[e]);for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(x[e][r][n]-=this.objectOffset[e]);var b=[i(new Float32Array(g*v),[g,v]),i(new Float32Array(g*v),[g,v]),i(new Float32Array(g*v),[g,v])];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<v;n++)b[e].set(r,n,x[e][r][n]);x=[];var w={colormap:d,levels:[[],[],[]],showContour:[!0,!0,!0],showSurface:!t.hidesurface,contourProject:[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],contourWidth:[1,1,1],contourColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],contourTint:[1,1,1],dynamicColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],dynamicWidth:[1,1,1],dynamicTint:[1,1,1],opacityscale:t.opacityscale,opacity:t.opacity},T=f(t);if(w.intensityBounds=[T.min,T.max],t.surfacecolor){var k=i(new Float32Array(g*v),[g,v]);for(r=0;r<g;r++)for(n=0;n<v;n++)k.set(r,n,t.surfacecolor[n][r]);b.push(k)}else w.intensityBounds[0]*=m[2],w.intensityBounds[1]*=m[2];(_<b[0].shape[0]||_<b[0].shape[1])&&(this.refineData=!1),!0===this.refineData&&(this.dataScaleX=this.estimateScale(b[0].shape[0],0),this.dataScaleY=this.estimateScale(b[0].shape[1],1),1===this.dataScaleX&&1===this.dataScaleY||this.refineCoords(b)),t.surfacecolor&&(w.intensity=b.pop());var M=[!0,!0,!0],A=[\"x\",\"y\",\"z\"];for(e=0;e<3;++e){var S=t.contours[A[e]];M[e]=S.highlight,w.showContour[e]=S.show||S.highlight,w.showContour[e]&&(w.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,w.levels[e]=y[e],p.highlightColor[e]=w.contourColor[e]=u(S.color),S.usecolormap?p.highlightTint[e]=w.contourTint[e]=0:p.highlightTint[e]=w.contourTint[e]=1,w.contourWidth[e]=S.width,this.contourStart[e]=S.start,this.contourEnd[e]=S.end,this.contourSize[e]=S.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),S.highlight&&(w.dynamicColor[e]=u(S.highlightcolor),w.dynamicWidth[e]=S.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(d)&&(w.vertexColor=!0),w.objectOffset=this.objectOffset,w.coords=b,p.update(w),p.visible=t.visible,p.enableDynamic=M,p.enableHighlight=M,p.snapToData=!0,\"lighting\"in t&&(p.ambientLight=t.lighting.ambient,p.diffuseLight=t.lighting.diffuse,p.specularLight=t.lighting.specular,p.roughness=t.lighting.roughness,p.fresnel=t.lighting.fresnel),\"lightposition\"in t&&(p.lightPosition=[t.lightposition.x,t.lightposition.y,t.lightposition.z])},p.dispose=function(){this.scene.glplot.remove(this.surface),this.surface.dispose()},e.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new h(t,i,e.uid);return i._trace=a,a.update(e),t.glplot.add(i),a}},{\"../../components/colorscale\":674,\"../../lib\":799,\"../../lib/gl_format_color\":795,\"../../lib/str2rgbarray\":823,\"../heatmap/find_empties\":1087,\"../heatmap/interp2d\":1090,\"gl-surface3d\":350,ndarray:479,\"ndarray-linear-interpolate\":473}],1341:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),o=t(\"./attributes\");function s(t,e,r,n){var i=n(\"opacityscale\");\"max\"===i?e.opacityscale=[[0,.1],[1,1]]:\"min\"===i?e.opacityscale=[[0,1],[1,.1]]:\"extremes\"===i?e.opacityscale=function(t,e){for(var r=[],n=0;n<32;n++){var i=n/31,a=e+(1-e)*(1-Math.pow(Math.sin(t*i*Math.PI),2));r.push([i,Math.max(0,Math.min(1,a))])}return r}(1,.1):function(t){var e=0;if(!Array.isArray(t)||t.length<2)return!1;if(!t[0]||!t[t.length-1])return!1;if(0!=+t[0][0]||1!=+t[t.length-1][0])return!1;for(var r=0;r<t.length;r++){var n=t[r];if(2!==n.length||+n[0]<e)return!1;e=+n[0]}return!0}(i)||(e.opacityscale=void 0)}function l(t,e,r){e in t&&!(r in t)&&(t[r]=t[e])}e.exports={supplyDefaults:function(t,e,r,c){var u,f;function h(r,n){return i.coerce(t,e,o,r,n)}var p=h(\"x\"),d=h(\"y\"),m=h(\"z\");if(!m||!m.length||p&&p.length<1||d&&d.length<1)e.visible=!1;else{e._xlength=Array.isArray(p)&&i.isArrayOrTypedArray(p[0])?m.length:m[0].length,e._ylength=m.length,n.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\",\"z\"],c),h(\"text\"),h(\"hovertext\"),h(\"hovertemplate\"),h(\"xhoverformat\"),h(\"yhoverformat\"),h(\"zhoverformat\"),[\"lighting.ambient\",\"lighting.diffuse\",\"lighting.specular\",\"lighting.roughness\",\"lighting.fresnel\",\"lightposition.x\",\"lightposition.y\",\"lightposition.z\",\"hidesurface\",\"connectgaps\",\"opacity\"].forEach((function(t){h(t)}));var g=h(\"surfacecolor\"),v=[\"x\",\"y\",\"z\"];for(u=0;u<3;++u){var 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n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../../components/colorscale/attributes\"),o=t(\"../../plots/domain\").attributes,s=t(\"../pie/attributes\"),l=t(\"../sunburst/attributes\"),c=t(\"./constants\"),u=t(\"../../lib/extend\").extendFlat;e.exports={labels:l.labels,parents:l.parents,values:l.values,branchvalues:l.branchvalues,count:l.count,level:l.level,maxdepth:l.maxdepth,tiling:{packing:{valType:\"enumerated\",values:[\"squarify\",\"binary\",\"dice\",\"slice\",\"slice-dice\",\"dice-slice\"],dflt:\"squarify\",editType:\"plot\"},squarifyratio:{valType:\"number\",min:1,dflt:1,editType:\"plot\"},flip:{valType:\"flaglist\",flags:[\"x\",\"y\"],dflt:\"\",editType:\"plot\"},pad:{valType:\"number\",min:0,dflt:3,editType:\"plot\"},editType:\"calc\"},marker:u({pad:{t:{valType:\"number\",min:0,editType:\"plot\"},l:{valType:\"number\",min:0,editType:\"plot\"},r:{valType:\"number\",min:0,editType:\"plot\"},b:{valType:\"number\",min:0,editType:\"plot\"},editType:\"calc\"},colors:l.marker.colors,depthfade:{valType:\"enumerated\",values:[!0,!1,\"reversed\"],editType:\"style\"},line:l.marker.line,editType:\"calc\"},a(\"marker\",{colorAttr:\"colors\",anim:!1})),pathbar:{visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},side:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},edgeshape:{valType:\"enumerated\",values:[\">\",\"<\",\"|\",\"/\",\"\\\\\"],dflt:\">\",editType:\"plot\"},thickness:{valType:\"number\",min:12,editType:\"plot\"},textfont:u({},s.textfont,{}),editType:\"calc\"},text:s.text,textinfo:l.textinfo,texttemplate:i({editType:\"plot\"},{keys:c.eventDataKeys.concat([\"label\",\"value\"])}),hovertext:s.hovertext,hoverinfo:l.hoverinfo,hovertemplate:n({},{keys:c.eventDataKeys}),textfont:s.textfont,insidetextfont:s.insidetextfont,outsidetextfont:u({},s.outsidetextfont,{}),textposition:{valType:\"enumerated\",values:[\"top 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v=h(\"pathbar.visible\");s(t,e,c,h,\"auto\",{hasPathbar:v,moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),h(\"textposition\");var y=-1!==e.textposition.indexOf(\"bottom\");h(\"marker.line.width\")&&h(\"marker.line.color\",c.paper_bgcolor);var x=h(\"marker.colors\");(e._hasColorscale=u(t,\"marker\",\"colors\")||(t.marker||{}).coloraxis)?f(t,e,c,h,{prefix:\"marker.\",cLetter:\"c\"}):h(\"marker.depthfade\",!(x||[]).length);var b=2*e.textfont.size;h(\"marker.pad.t\",y?b/4:b),h(\"marker.pad.l\",b/4),h(\"marker.pad.r\",b/4),h(\"marker.pad.b\",y?b:b/4),e._hovered={marker:{line:{width:2,color:a.contrast(c.paper_bgcolor)}}},v&&(h(\"pathbar.thickness\",e.pathbar.textfont.size+2*l),h(\"pathbar.side\"),h(\"pathbar.edgeshape\")),h(\"sort\"),h(\"root.color\"),o(e,c,h),e._length=null}else 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d=p.barDifY,m=p.width,g=p.height,v=p.viewX,y=p.viewY,x=p.pathSlice,b=p.toMoveInsideSlice,_=p.strTransform,w=p.hasTransition,T=p.handleSlicesExit,k=p.makeUpdateSliceInterpolator,M=p.makeUpdateTextInterpolator,A={},S=t._fullLayout,E=e[0],L=E.trace,C=E.hierarchy,P=m/L._entryDepth,I=u.listPath(r.data,\"id\"),O=s(C.copy(),[m,g],{packing:\"dice\",pad:{inner:0,top:0,left:0,right:0,bottom:0}}).descendants();(O=O.filter((function(t){var e=I.indexOf(t.data.id);return-1!==e&&(t.x0=P*e,t.x1=P*(e+1),t.y0=d,t.y1=d+g,t.onPathbar=!0,!0)}))).reverse(),(h=h.data(O,u.getPtId)).enter().append(\"g\").classed(\"pathbar\",!0),T(h,!0,A,[m,g],x),h.order();var z=h;w&&(z=z.transition().each(\"end\",(function(){var e=n.select(this);u.setSliceCursor(e,t,{hideOnRoot:!1,hideOnLeaves:!1,isTransitioning:!1})}))),z.each((function(s){s._hoverX=v(s.x1-Math.min(m,g)/2),s._hoverY=y(s.y1-g/2);var h=n.select(this),p=i.ensureSingle(h,\"path\",\"surface\",(function(t){t.style(\"pointer-events\",\"all\")}));w?p.transition().attrTween(\"d\",(function(t){var e=k(t,!0,A,[m,g]);return function(t){return x(e(t))}})):p.attr(\"d\",x),h.call(f,r,t,e,{styleOne:l,eventDataKeys:c.eventDataKeys,transitionTime:c.CLICK_TRANSITION_TIME,transitionEasing:c.CLICK_TRANSITION_EASING}).call(u.setSliceCursor,t,{hideOnRoot:!1,hideOnLeaves:!1,isTransitioning:t._transitioning}),p.call(l,s,L,{hovered:!1}),s._text=(u.getPtLabel(s)||\"\").split(\"<br>\").join(\" \")||\"\";var d=i.ensureSingle(h,\"g\",\"slicetext\"),T=i.ensureSingle(d,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),E=i.ensureUniformFontSize(t,u.determineTextFont(L,s,S.font,{onPathbar:!0}));T.text(s._text||\" 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n=t(\"../../components/colorscale/attributes\"),i=t(\"../isosurface/attributes\"),a=t(\"../surface/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/edit_types\").overrideAll,c=e.exports=l(s({x:i.x,y:i.y,z:i.z,value:i.value,isomin:i.isomin,isomax:i.isomax,surface:i.surface,spaceframe:{show:{valType:\"boolean\",dflt:!1},fill:{valType:\"number\",min:0,max:1,dflt:1}},slices:i.slices,caps:i.caps,text:i.text,hovertext:i.hovertext,xhoverformat:i.xhoverformat,yhoverformat:i.yhoverformat,zhoverformat:i.zhoverformat,valuehoverformat:i.valuehoverformat,hovertemplate:i.hovertemplate},n(\"\",{colorAttr:\"`value`\",showScaleDflt:!0,editTypeOverride:\"calc\"}),{colorbar:i.colorbar,opacity:i.opacity,opacityscale:a.opacityscale,lightposition:i.lightposition,lighting:i.lighting,flatshading:i.flatshading,contour:i.contour,hoverinfo:s({},o.hoverinfo),showlegend:s({},o.showlegend,{dflt:!1})}),\"calc\",\"nested\");c.x.editType=c.y.editType=c.z.editType=c.value.editType=\"calc+clearAxisTypes\",c.transforms=void 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                       {\"responsive\": true}                    ).then(function(){\n",
+              "                            \n",
+              "var gd = document.getElementById('4a37aafc-3c0b-41f2-aa6d-d472be5173ce');\n",
+              "var x = new MutationObserver(function (mutations, observer) {{\n",
+              "        var display = window.getComputedStyle(gd).display;\n",
+              "        if (!display || display === 'none') {{\n",
+              "            console.log([gd, 'removed!']);\n",
+              "            Plotly.purge(gd);\n",
+              "            observer.disconnect();\n",
+              "        }}\n",
+              "}});\n",
+              "\n",
+              "// Listen for the removal of the full notebook cells\n",
+              "var notebookContainer = gd.closest('#notebook-container');\n",
+              "if (notebookContainer) {{\n",
+              "    x.observe(notebookContainer, {childList: true});\n",
+              "}}\n",
+              "\n",
+              "// Listen for the clearing of the current output cell\n",
+              "var outputEl = gd.closest('.output');\n",
+              "if (outputEl) {{\n",
+              "    x.observe(outputEl, {childList: true});\n",
+              "}}\n",
+              "\n",
+              "                        })                };                });            </script>        </div>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "#PCA plot\n",
+        "from sklearn.decomposition import PCA\n",
+        "import plotly.express as px\n",
+        "\n",
+        "pca = PCA(n_components=2)\n",
+        "features_pca = pca.fit_transform(data_df.drop(['rid','row_id'],axis=1).transpose())\n",
+        "\n",
+        "fig = px.scatter(features_pca, x=0, y=1, color=samples_df['curated_cell_line'])\n",
+        "fig.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "source": [
+        "### Comparing levels of a metabolite of interest across an attribute"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 37,
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "outputs": [],
+      "source": [
+        "#make sure sample ids are consistent in the data and the metadata file\n",
+        "samples_df.to_csv('met_metadata.csv',index=False)\n",
+        "data_df[data_df.index == 33].to_csv('met_data.csv',index=False) #data values for one of the metabolites"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 40,
+      "metadata": {
+        "kernel": "R"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "Using rid, row_id as id variables\n",
+            "\n"
+          ]
+        },
+        {
+          "data": {
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BqIfiOPDiFM/+uJ1z/+yXon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\nTttPmF9Ua/ynr8w79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+            "text/plain": [
+              "plot without title"
+            ]
+          },
+          "metadata": {
+            "image/png": {
+              "height": 600,
+              "width": 960
+            }
+          },
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "## Plotting levels of metabolite across cell line\n",
+        "\n",
+        "library(ggplot2)\n",
+        "\n",
+        "input_matrix <-reshape2::melt(read.csv(\"met_data.csv\"))\n",
+        "\n",
+        "metadata <-read.csv(\"met_metadata.csv\")\n",
+        "\n",
+        "input_matrix  <- cbind(input_matrix,metadata)\n",
+        "# Run script\n",
+        "\n",
+        "plot_boxplot <- function(df, x_col, y_col,facet_by){\n",
+        "  require(ggplot2)\n",
+        "  \n",
+        "  # color lables for filling\n",
+        "  fill <- \"#4271AE\"\n",
+        "  lines <- \"#1F3552\"\n",
+        "\n",
+        "  # function for plottings\n",
+        "  p <- ggplot(df) + aes(x = as.factor(df[,x_col]), y = df[,y_col]) + \n",
+        "    stat_boxplot(geom ='errorbar') + # Adding horizontal bars\n",
+        "    geom_boxplot(aes(fill=curated_disease)) + # boxplot function with black borders \n",
+        "    labs(x=\"Disease\", y=\"Normalised expression\",fill=\"Disease\") +# x-axis labels \n",
+        "    theme(panel.grid.major = element_blank(), # no major grids\n",
+        "          panel.grid.minor = element_blank(), # no minor grids\n",
+        "          panel.border = element_blank(), # no border\n",
+        "          panel.background = element_blank(), # no background \n",
+        "          axis.title = element_text(colour=\"black\", size = 16, face = \"bold\"), # axis title \n",
+        "          axis.text.x = element_text(colour=\"black\", size = 16, margin=unit(c(0.5,0.5,0.1,0.1), \"cm\"),angle=90), # x-axis text in fontsize 10\n",
+        "          axis.text.y = element_text(colour=\"black\", size = 16, margin=unit(c(0.5,0.5,0.1,0.1), \"cm\"), face = \"bold\"), # y-axis text in fontsize 10\n",
+        "          axis.line = element_line(size=1, colour = \"black\"), # axis line defined\n",
+        "          axis.ticks.length = unit(0.5, \"cm\"),\n",
+        "          text = element_text(size = 20))  # ticks facing inward with 0.25cm length\n",
+        "  p <- p + facet_grid(rid~.)\n",
+        "  return(p)\n",
+        "}\n",
+        "options(repr.plot.width=16, repr.plot.height=10)\n",
+        "plot_boxplot(input_matrix, \"curated_cell_line\", \"value\",\"rid\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "R"
+      },
+      "source": [
+        "### Differential analysis using Limma"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 41,
+      "metadata": {
+        "kernel": "Python3"
+      },
+      "outputs": [],
+      "source": [
+        "data_df.to_csv('met_data.csv',index=False)\n",
+        "samples_df.to_csv('met_metadata.csv',index=False)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 43,
+      "metadata": {
+        "kernel": "R",
+        "scrolled": true
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "Warning message:\n",
+            "“Zero sample variances detected, have been offset away from zero”\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<table class=\"dataframe\">\n",
+              "<caption>A data.frame: 39 × 7</caption>\n",
+              "<thead>\n",
+              "\t<tr><th></th><th scope=col>logFC</th><th scope=col>AveExpr</th><th scope=col>t</th><th scope=col>P.Value</th><th scope=col>adj.P.Val</th><th scope=col>B</th><th scope=col>BH</th></tr>\n",
+              "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
+              "</thead>\n",
+              "<tbody>\n",
+              "\t<tr><th scope=row>beta-Alanine_CHEBI:16958</th><td> -13.322222</td><td>   6.661111</td><td>-48.116151</td><td>3.429304e-19</td><td>1.337429e-17</td><td>18.806919</td><td>1.337429e-17</td></tr>\n",
+              "\t<tr><th scope=row>L-Asparagine_CHEBI:17196</th><td>  35.688889</td><td>  30.033333</td><td> 26.008087</td><td>7.766249e-15</td><td>1.514419e-13</td><td>16.698049</td><td>1.514419e-13</td></tr>\n",
+              "\t<tr><th scope=row>NAD_CHEBI:44215</th><td>  24.155556</td><td>  37.544444</td><td> 21.756250</td><td>1.367935e-13</td><td>1.778316e-12</td><td>15.656895</td><td>1.778316e-12</td></tr>\n",
+              "\t<tr><th scope=row>L-Proline_CHEBI:17203</th><td>  85.177778</td><td>  89.900000</td><td> 20.887545</td><td>2.622041e-13</td><td>2.556490e-12</td><td>15.387073</td><td>2.556490e-12</td></tr>\n",
+              "\t<tr><th scope=row>L-Lysine_CHEBI:18019</th><td> 100.055556</td><td>  76.561111</td><td> 20.565697</td><td>3.358302e-13</td><td>2.619475e-12</td><td>15.281051</td><td>2.619475e-12</td></tr>\n",
+              "\t<tr><th scope=row>L-Threonine_CHEBI:16857</th><td> 296.222222</td><td> 324.100000</td><td> 19.801519</td><td>6.133421e-13</td><td>3.986724e-12</td><td>15.015120</td><td>3.986724e-12</td></tr>\n",
+              "\t<tr><th scope=row>L-Methionine_CHEBI:16643</th><td> 169.511111</td><td> 106.933333</td><td> 19.563843</td><td>7.429607e-13</td><td>4.139352e-12</td><td>14.928108</td><td>4.139352e-12</td></tr>\n",
+              "\t<tr><th scope=row>Taurine_CHEBI:15891</th><td> 123.866667</td><td> 223.944444</td><td> 19.067959</td><td>1.116165e-12</td><td>4.894688e-12</td><td>14.739579</td><td>4.894688e-12</td></tr>\n",
+              "\t<tr><th scope=row>L-Leucine_CHEBI:15603</th><td> 169.955556</td><td> 140.144444</td><td> 19.053618</td><td>1.129543e-12</td><td>4.894688e-12</td><td>14.733982</td><td>4.894688e-12</td></tr>\n",
+              "\t<tr><th scope=row>Glycine_CHEBI:15428</th><td> 773.288889</td><td>1065.155556</td><td> 18.313546</td><td>2.113022e-12</td><td>8.240786e-12</td><td>14.433471</td><td>8.240786e-12</td></tr>\n",
+              "\t<tr><th scope=row>L-Aspartate_CHEBI:17053</th><td> 223.544444</td><td> 207.316667</td><td> 18.082490</td><td>2.581559e-12</td><td>9.152799e-12</td><td>14.334764</td><td>9.152799e-12</td></tr>\n",
+              "\t<tr><th scope=row>L-Tyrosine_CHEBI:17895</th><td> 177.877778</td><td> 130.005556</td><td> 17.592594</td><td>3.978202e-12</td><td>1.292916e-11</td><td>14.117304</td><td>1.292916e-11</td></tr>\n",
+              "\t<tr><th scope=row>L-Glutamine_CHEBI:18050</th><td> 593.555556</td><td> 770.511111</td><td> 17.351121</td><td>4.943165e-12</td><td>1.455889e-11</td><td>14.005857</td><td>1.455889e-11</td></tr>\n",
+              "\t<tr><th scope=row>Pantothenate_CHEBI:7916</th><td> -15.277778</td><td>  13.627778</td><td>-17.289683</td><td>5.226268e-12</td><td>1.455889e-11</td><td>13.977037</td><td>1.455889e-11</td></tr>\n",
+              "\t<tr><th scope=row>L-Tryptophan_CHEBI:16828</th><td>  49.188889</td><td>  35.316667</td><td> 17.148086</td><td>5.946082e-12</td><td>1.507831e-11</td><td>13.909884</td><td>1.507831e-11</td></tr>\n",
+              "\t<tr><th scope=row>2-Oxoisocaproate_CHEBI:48430</th><td>  10.600000</td><td>   5.300000</td><td> 17.104892</td><td>6.185975e-12</td><td>1.507831e-11</td><td>13.889195</td><td>1.507831e-11</td></tr>\n",
+              "\t<tr><th scope=row>L-Glutamic acid_CHEBI:16015</th><td> 497.911111</td><td> 602.022222</td><td> 16.753014</td><td>8.566715e-12</td><td>1.965305e-11</td><td>13.716991</td><td>1.965305e-11</td></tr>\n",
+              "\t<tr><th scope=row>UDP-N-Acetylglucosamine_CHEBI:16264</th><td> 115.911111</td><td> 123.055556</td><td> 16.493968</td><td>1.093011e-11</td><td>2.368190e-11</td><td>13.585939</td><td>2.368190e-11</td></tr>\n",
+              "\t<tr><th scope=row>L-Isoleucine_CHEBI:17191</th><td> 214.077778</td><td> 179.261111</td><td> 16.367409</td><td>1.232705e-11</td><td>2.530290e-11</td><td>13.520550</td><td>2.530290e-11</td></tr>\n",
+              "\t<tr><th scope=row>L-Phenylalanine_CHEBI:17295</th><td> 243.566667</td><td> 171.605556</td><td> 16.309983</td><td>1.302204e-11</td><td>2.539298e-11</td><td>13.490580</td><td>2.539298e-11</td></tr>\n",
+              "\t<tr><th scope=row>myo-Inositol_CHEBI:17268</th><td>-142.233333</td><td> 201.772222</td><td>-15.503892</td><td>2.865087e-11</td><td>5.275338e-11</td><td>13.049202</td><td>5.275338e-11</td></tr>\n",
+              "\t<tr><th scope=row>L-Valine_CHEBI:16414</th><td> 219.155556</td><td> 183.133333</td><td> 15.466025</td><td>2.975831e-11</td><td>5.275338e-11</td><td>13.027481</td><td>5.275338e-11</td></tr>\n",
+              "\t<tr><th scope=row>Pyroglutamic acid_CHEBI:16010</th><td>  50.755556</td><td>  65.822222</td><td> 15.343107</td><td>3.367578e-11</td><td>5.710241e-11</td><td>12.956336</td><td>5.710241e-11</td></tr>\n",
+              "\t<tr><th scope=row>Adenosine triphosphate_CHEBI:15422</th><td>  66.922222</td><td> 101.516667</td><td> 14.104590</td><td>1.231598e-10</td><td>2.001347e-10</td><td>12.181716</td><td>2.001347e-10</td></tr>\n",
+              "\t<tr><th scope=row>Adenosine monophosphate_CHEBI:16027</th><td>  -9.522222</td><td>   4.761111</td><td>-11.408381</td><td>3.001678e-09</td><td>4.682618e-09</td><td>10.059255</td><td>4.682618e-09</td></tr>\n",
+              "\t<tr><th scope=row>O-Phosphocholine_CHEBI:18132</th><td> 169.544444</td><td> 443.727778</td><td> 10.969776</td><td>5.339824e-09</td><td>8.009736e-09</td><td> 9.645757</td><td>8.009736e-09</td></tr>\n",
+              "\t<tr><th scope=row>Creatine phosphate_CHEBI:17287</th><td>  16.688889</td><td>  33.611111</td><td>  9.547933</td><td>3.931667e-08</td><td>5.679075e-08</td><td> 8.146605</td><td>5.679075e-08</td></tr>\n",
+              "\t<tr><th scope=row>Glutathione_CHEBI:16856</th><td>  69.122222</td><td> 237.561111</td><td>  7.627703</td><td>8.354953e-07</td><td>1.124656e-06</td><td> 5.676325</td><td>1.124656e-06</td></tr>\n",
+              "\t<tr><th scope=row>sn-Glycero-3-phosphocholine_CHEBI:16870</th><td> -43.955556</td><td> 139.255556</td><td> -7.627153</td><td>8.362826e-07</td><td>1.124656e-06</td><td> 5.675535</td><td>1.124656e-06</td></tr>\n",
+              "\t<tr><th scope=row>Creatine_CHEBI:16919</th><td>   8.211111</td><td>  25.927778</td><td>  5.824279</td><td>2.279425e-05</td><td>2.963252e-05</td><td> 2.817898</td><td>2.963252e-05</td></tr>\n",
+              "\t<tr><th scope=row>Serine_CHEBI:17822</th><td> -22.666667</td><td> 129.400000</td><td> -3.494357</td><td>2.880446e-03</td><td>3.623787e-03</td><td>-1.557547</td><td>3.623787e-03</td></tr>\n",
+              "\t<tr><th scope=row>Lactate_CHEBI:78320</th><td>-122.200000</td><td> 434.444444</td><td> -3.102187</td><td>6.648459e-03</td><td>8.102809e-03</td><td>-2.315554</td><td>8.102809e-03</td></tr>\n",
+              "\t<tr><th scope=row>L-Alanine_CHEBI:16977</th><td>  84.977778</td><td> 445.122222</td><td>  3.008518</td><td>8.105689e-03</td><td>9.579450e-03</td><td>-2.494233</td><td>9.579450e-03</td></tr>\n",
+              "\t<tr><th scope=row>Formate_CHEBI:30751</th><td>   5.466667</td><td>  19.788889</td><td>  2.775695</td><td>1.320765e-02</td><td>1.487298e-02</td><td>-2.932204</td><td>1.487298e-02</td></tr>\n",
+              "\t<tr><th scope=row>D-Glucose_CHEBI:4167</th><td>  99.455556</td><td> 280.305556</td><td>  2.770631</td><td>1.334755e-02</td><td>1.487298e-02</td><td>-2.941614</td><td>1.487298e-02</td></tr>\n",
+              "\t<tr><th scope=row>Fumarate_CHEBI:18012</th><td>  -0.500000</td><td>   3.250000</td><td> -1.827734</td><td>8.571259e-02</td><td>9.285531e-02</td><td>-4.554625</td><td>9.285531e-02</td></tr>\n",
+              "\t<tr><th scope=row>1-Methylnicotinamide_CHEBI:16797</th><td>   0.000000</td><td>   0.000000</td><td>  0.000000</td><td>1.000000e+00</td><td>1.000000e+00</td><td>-6.076924</td><td>1.000000e+00</td></tr>\n",
+              "\t<tr><th scope=row>2-Aminoadipate_CHEBI:37024</th><td>   0.000000</td><td>   0.000000</td><td>  0.000000</td><td>1.000000e+00</td><td>1.000000e+00</td><td>-6.076924</td><td>1.000000e+00</td></tr>\n",
+              "\t<tr><th scope=row>D-Glucitol_CHEBI:17924</th><td>   0.000000</td><td>   0.000000</td><td>  0.000000</td><td>1.000000e+00</td><td>1.000000e+00</td><td>-6.076924</td><td>1.000000e+00</td></tr>\n",
+              "</tbody>\n",
+              "</table>\n"
+            ],
+            "text/latex": [
+              "A data.frame: 39 × 7\n",
+              "\\begin{tabular}{r|lllllll}\n",
+              "  & logFC & AveExpr & t & P.Value & adj.P.Val & B & BH\\\\\n",
+              "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
+              "\\hline\n",
+              "\tbeta-Alanine\\_CHEBI:16958 &  -13.322222 &    6.661111 & -48.116151 & 3.429304e-19 & 1.337429e-17 & 18.806919 & 1.337429e-17\\\\\n",
+              "\tL-Asparagine\\_CHEBI:17196 &   35.688889 &   30.033333 &  26.008087 & 7.766249e-15 & 1.514419e-13 & 16.698049 & 1.514419e-13\\\\\n",
+              "\tNAD\\_CHEBI:44215 &   24.155556 &   37.544444 &  21.756250 & 1.367935e-13 & 1.778316e-12 & 15.656895 & 1.778316e-12\\\\\n",
+              "\tL-Proline\\_CHEBI:17203 &   85.177778 &   89.900000 &  20.887545 & 2.622041e-13 & 2.556490e-12 & 15.387073 & 2.556490e-12\\\\\n",
+              "\tL-Lysine\\_CHEBI:18019 &  100.055556 &   76.561111 &  20.565697 & 3.358302e-13 & 2.619475e-12 & 15.281051 & 2.619475e-12\\\\\n",
+              "\tL-Threonine\\_CHEBI:16857 &  296.222222 &  324.100000 &  19.801519 & 6.133421e-13 & 3.986724e-12 & 15.015120 & 3.986724e-12\\\\\n",
+              "\tL-Methionine\\_CHEBI:16643 &  169.511111 &  106.933333 &  19.563843 & 7.429607e-13 & 4.139352e-12 & 14.928108 & 4.139352e-12\\\\\n",
+              "\tTaurine\\_CHEBI:15891 &  123.866667 &  223.944444 &  19.067959 & 1.116165e-12 & 4.894688e-12 & 14.739579 & 4.894688e-12\\\\\n",
+              "\tL-Leucine\\_CHEBI:15603 &  169.955556 &  140.144444 &  19.053618 & 1.129543e-12 & 4.894688e-12 & 14.733982 & 4.894688e-12\\\\\n",
+              "\tGlycine\\_CHEBI:15428 &  773.288889 & 1065.155556 &  18.313546 & 2.113022e-12 & 8.240786e-12 & 14.433471 & 8.240786e-12\\\\\n",
+              "\tL-Aspartate\\_CHEBI:17053 &  223.544444 &  207.316667 &  18.082490 & 2.581559e-12 & 9.152799e-12 & 14.334764 & 9.152799e-12\\\\\n",
+              "\tL-Tyrosine\\_CHEBI:17895 &  177.877778 &  130.005556 &  17.592594 & 3.978202e-12 & 1.292916e-11 & 14.117304 & 1.292916e-11\\\\\n",
+              "\tL-Glutamine\\_CHEBI:18050 &  593.555556 &  770.511111 &  17.351121 & 4.943165e-12 & 1.455889e-11 & 14.005857 & 1.455889e-11\\\\\n",
+              "\tPantothenate\\_CHEBI:7916 &  -15.277778 &   13.627778 & -17.289683 & 5.226268e-12 & 1.455889e-11 & 13.977037 & 1.455889e-11\\\\\n",
+              "\tL-Tryptophan\\_CHEBI:16828 &   49.188889 &   35.316667 &  17.148086 & 5.946082e-12 & 1.507831e-11 & 13.909884 & 1.507831e-11\\\\\n",
+              "\t2-Oxoisocaproate\\_CHEBI:48430 &   10.600000 &    5.300000 &  17.104892 & 6.185975e-12 & 1.507831e-11 & 13.889195 & 1.507831e-11\\\\\n",
+              "\tL-Glutamic acid\\_CHEBI:16015 &  497.911111 &  602.022222 &  16.753014 & 8.566715e-12 & 1.965305e-11 & 13.716991 & 1.965305e-11\\\\\n",
+              "\tUDP-N-Acetylglucosamine\\_CHEBI:16264 &  115.911111 &  123.055556 &  16.493968 & 1.093011e-11 & 2.368190e-11 & 13.585939 & 2.368190e-11\\\\\n",
+              "\tL-Isoleucine\\_CHEBI:17191 &  214.077778 &  179.261111 &  16.367409 & 1.232705e-11 & 2.530290e-11 & 13.520550 & 2.530290e-11\\\\\n",
+              "\tL-Phenylalanine\\_CHEBI:17295 &  243.566667 &  171.605556 &  16.309983 & 1.302204e-11 & 2.539298e-11 & 13.490580 & 2.539298e-11\\\\\n",
+              "\tmyo-Inositol\\_CHEBI:17268 & -142.233333 &  201.772222 & -15.503892 & 2.865087e-11 & 5.275338e-11 & 13.049202 & 5.275338e-11\\\\\n",
+              "\tL-Valine\\_CHEBI:16414 &  219.155556 &  183.133333 &  15.466025 & 2.975831e-11 & 5.275338e-11 & 13.027481 & 5.275338e-11\\\\\n",
+              "\tPyroglutamic acid\\_CHEBI:16010 &   50.755556 &   65.822222 &  15.343107 & 3.367578e-11 & 5.710241e-11 & 12.956336 & 5.710241e-11\\\\\n",
+              "\tAdenosine triphosphate\\_CHEBI:15422 &   66.922222 &  101.516667 &  14.104590 & 1.231598e-10 & 2.001347e-10 & 12.181716 & 2.001347e-10\\\\\n",
+              "\tAdenosine monophosphate\\_CHEBI:16027 &   -9.522222 &    4.761111 & -11.408381 & 3.001678e-09 & 4.682618e-09 & 10.059255 & 4.682618e-09\\\\\n",
+              "\tO-Phosphocholine\\_CHEBI:18132 &  169.544444 &  443.727778 &  10.969776 & 5.339824e-09 & 8.009736e-09 &  9.645757 & 8.009736e-09\\\\\n",
+              "\tCreatine phosphate\\_CHEBI:17287 &   16.688889 &   33.611111 &   9.547933 & 3.931667e-08 & 5.679075e-08 &  8.146605 & 5.679075e-08\\\\\n",
+              "\tGlutathione\\_CHEBI:16856 &   69.122222 &  237.561111 &   7.627703 & 8.354953e-07 & 1.124656e-06 &  5.676325 & 1.124656e-06\\\\\n",
+              "\tsn-Glycero-3-phosphocholine\\_CHEBI:16870 &  -43.955556 &  139.255556 &  -7.627153 & 8.362826e-07 & 1.124656e-06 &  5.675535 & 1.124656e-06\\\\\n",
+              "\tCreatine\\_CHEBI:16919 &    8.211111 &   25.927778 &   5.824279 & 2.279425e-05 & 2.963252e-05 &  2.817898 & 2.963252e-05\\\\\n",
+              "\tSerine\\_CHEBI:17822 &  -22.666667 &  129.400000 &  -3.494357 & 2.880446e-03 & 3.623787e-03 & -1.557547 & 3.623787e-03\\\\\n",
+              "\tLactate\\_CHEBI:78320 & -122.200000 &  434.444444 &  -3.102187 & 6.648459e-03 & 8.102809e-03 & -2.315554 & 8.102809e-03\\\\\n",
+              "\tL-Alanine\\_CHEBI:16977 &   84.977778 &  445.122222 &   3.008518 & 8.105689e-03 & 9.579450e-03 & -2.494233 & 9.579450e-03\\\\\n",
+              "\tFormate\\_CHEBI:30751 &    5.466667 &   19.788889 &   2.775695 & 1.320765e-02 & 1.487298e-02 & -2.932204 & 1.487298e-02\\\\\n",
+              "\tD-Glucose\\_CHEBI:4167 &   99.455556 &  280.305556 &   2.770631 & 1.334755e-02 & 1.487298e-02 & -2.941614 & 1.487298e-02\\\\\n",
+              "\tFumarate\\_CHEBI:18012 &   -0.500000 &    3.250000 &  -1.827734 & 8.571259e-02 & 9.285531e-02 & -4.554625 & 9.285531e-02\\\\\n",
+              "\t1-Methylnicotinamide\\_CHEBI:16797 &    0.000000 &    0.000000 &   0.000000 & 1.000000e+00 & 1.000000e+00 & -6.076924 & 1.000000e+00\\\\\n",
+              "\t2-Aminoadipate\\_CHEBI:37024 &    0.000000 &    0.000000 &   0.000000 & 1.000000e+00 & 1.000000e+00 & -6.076924 & 1.000000e+00\\\\\n",
+              "\tD-Glucitol\\_CHEBI:17924 &    0.000000 &    0.000000 &   0.000000 & 1.000000e+00 & 1.000000e+00 & -6.076924 & 1.000000e+00\\\\\n",
+              "\\end{tabular}\n"
+            ],
+            "text/markdown": [
+              "\n",
+              "A data.frame: 39 × 7\n",
+              "\n",
+              "| <!--/--> | logFC &lt;dbl&gt; | AveExpr &lt;dbl&gt; | t &lt;dbl&gt; | P.Value &lt;dbl&gt; | adj.P.Val &lt;dbl&gt; | B &lt;dbl&gt; | BH &lt;dbl&gt; |\n",
+              "|---|---|---|---|---|---|---|---|\n",
+              "| beta-Alanine_CHEBI:16958 |  -13.322222 |    6.661111 | -48.116151 | 3.429304e-19 | 1.337429e-17 | 18.806919 | 1.337429e-17 |\n",
+              "| L-Asparagine_CHEBI:17196 |   35.688889 |   30.033333 |  26.008087 | 7.766249e-15 | 1.514419e-13 | 16.698049 | 1.514419e-13 |\n",
+              "| NAD_CHEBI:44215 |   24.155556 |   37.544444 |  21.756250 | 1.367935e-13 | 1.778316e-12 | 15.656895 | 1.778316e-12 |\n",
+              "| L-Proline_CHEBI:17203 |   85.177778 |   89.900000 |  20.887545 | 2.622041e-13 | 2.556490e-12 | 15.387073 | 2.556490e-12 |\n",
+              "| L-Lysine_CHEBI:18019 |  100.055556 |   76.561111 |  20.565697 | 3.358302e-13 | 2.619475e-12 | 15.281051 | 2.619475e-12 |\n",
+              "| L-Threonine_CHEBI:16857 |  296.222222 |  324.100000 |  19.801519 | 6.133421e-13 | 3.986724e-12 | 15.015120 | 3.986724e-12 |\n",
+              "| L-Methionine_CHEBI:16643 |  169.511111 |  106.933333 |  19.563843 | 7.429607e-13 | 4.139352e-12 | 14.928108 | 4.139352e-12 |\n",
+              "| Taurine_CHEBI:15891 |  123.866667 |  223.944444 |  19.067959 | 1.116165e-12 | 4.894688e-12 | 14.739579 | 4.894688e-12 |\n",
+              "| L-Leucine_CHEBI:15603 |  169.955556 |  140.144444 |  19.053618 | 1.129543e-12 | 4.894688e-12 | 14.733982 | 4.894688e-12 |\n",
+              "| Glycine_CHEBI:15428 |  773.288889 | 1065.155556 |  18.313546 | 2.113022e-12 | 8.240786e-12 | 14.433471 | 8.240786e-12 |\n",
+              "| L-Aspartate_CHEBI:17053 |  223.544444 |  207.316667 |  18.082490 | 2.581559e-12 | 9.152799e-12 | 14.334764 | 9.152799e-12 |\n",
+              "| L-Tyrosine_CHEBI:17895 |  177.877778 |  130.005556 |  17.592594 | 3.978202e-12 | 1.292916e-11 | 14.117304 | 1.292916e-11 |\n",
+              "| L-Glutamine_CHEBI:18050 |  593.555556 |  770.511111 |  17.351121 | 4.943165e-12 | 1.455889e-11 | 14.005857 | 1.455889e-11 |\n",
+              "| Pantothenate_CHEBI:7916 |  -15.277778 |   13.627778 | -17.289683 | 5.226268e-12 | 1.455889e-11 | 13.977037 | 1.455889e-11 |\n",
+              "| L-Tryptophan_CHEBI:16828 |   49.188889 |   35.316667 |  17.148086 | 5.946082e-12 | 1.507831e-11 | 13.909884 | 1.507831e-11 |\n",
+              "| 2-Oxoisocaproate_CHEBI:48430 |   10.600000 |    5.300000 |  17.104892 | 6.185975e-12 | 1.507831e-11 | 13.889195 | 1.507831e-11 |\n",
+              "| L-Glutamic acid_CHEBI:16015 |  497.911111 |  602.022222 |  16.753014 | 8.566715e-12 | 1.965305e-11 | 13.716991 | 1.965305e-11 |\n",
+              "| UDP-N-Acetylglucosamine_CHEBI:16264 |  115.911111 |  123.055556 |  16.493968 | 1.093011e-11 | 2.368190e-11 | 13.585939 | 2.368190e-11 |\n",
+              "| L-Isoleucine_CHEBI:17191 |  214.077778 |  179.261111 |  16.367409 | 1.232705e-11 | 2.530290e-11 | 13.520550 | 2.530290e-11 |\n",
+              "| L-Phenylalanine_CHEBI:17295 |  243.566667 |  171.605556 |  16.309983 | 1.302204e-11 | 2.539298e-11 | 13.490580 | 2.539298e-11 |\n",
+              "| myo-Inositol_CHEBI:17268 | -142.233333 |  201.772222 | -15.503892 | 2.865087e-11 | 5.275338e-11 | 13.049202 | 5.275338e-11 |\n",
+              "| L-Valine_CHEBI:16414 |  219.155556 |  183.133333 |  15.466025 | 2.975831e-11 | 5.275338e-11 | 13.027481 | 5.275338e-11 |\n",
+              "| Pyroglutamic acid_CHEBI:16010 |   50.755556 |   65.822222 |  15.343107 | 3.367578e-11 | 5.710241e-11 | 12.956336 | 5.710241e-11 |\n",
+              "| Adenosine triphosphate_CHEBI:15422 |   66.922222 |  101.516667 |  14.104590 | 1.231598e-10 | 2.001347e-10 | 12.181716 | 2.001347e-10 |\n",
+              "| Adenosine monophosphate_CHEBI:16027 |   -9.522222 |    4.761111 | -11.408381 | 3.001678e-09 | 4.682618e-09 | 10.059255 | 4.682618e-09 |\n",
+              "| O-Phosphocholine_CHEBI:18132 |  169.544444 |  443.727778 |  10.969776 | 5.339824e-09 | 8.009736e-09 |  9.645757 | 8.009736e-09 |\n",
+              "| Creatine phosphate_CHEBI:17287 |   16.688889 |   33.611111 |   9.547933 | 3.931667e-08 | 5.679075e-08 |  8.146605 | 5.679075e-08 |\n",
+              "| Glutathione_CHEBI:16856 |   69.122222 |  237.561111 |   7.627703 | 8.354953e-07 | 1.124656e-06 |  5.676325 | 1.124656e-06 |\n",
+              "| sn-Glycero-3-phosphocholine_CHEBI:16870 |  -43.955556 |  139.255556 |  -7.627153 | 8.362826e-07 | 1.124656e-06 |  5.675535 | 1.124656e-06 |\n",
+              "| Creatine_CHEBI:16919 |    8.211111 |   25.927778 |   5.824279 | 2.279425e-05 | 2.963252e-05 |  2.817898 | 2.963252e-05 |\n",
+              "| Serine_CHEBI:17822 |  -22.666667 |  129.400000 |  -3.494357 | 2.880446e-03 | 3.623787e-03 | -1.557547 | 3.623787e-03 |\n",
+              "| Lactate_CHEBI:78320 | -122.200000 |  434.444444 |  -3.102187 | 6.648459e-03 | 8.102809e-03 | -2.315554 | 8.102809e-03 |\n",
+              "| L-Alanine_CHEBI:16977 |   84.977778 |  445.122222 |   3.008518 | 8.105689e-03 | 9.579450e-03 | -2.494233 | 9.579450e-03 |\n",
+              "| Formate_CHEBI:30751 |    5.466667 |   19.788889 |   2.775695 | 1.320765e-02 | 1.487298e-02 | -2.932204 | 1.487298e-02 |\n",
+              "| D-Glucose_CHEBI:4167 |   99.455556 |  280.305556 |   2.770631 | 1.334755e-02 | 1.487298e-02 | -2.941614 | 1.487298e-02 |\n",
+              "| Fumarate_CHEBI:18012 |   -0.500000 |    3.250000 |  -1.827734 | 8.571259e-02 | 9.285531e-02 | -4.554625 | 9.285531e-02 |\n",
+              "| 1-Methylnicotinamide_CHEBI:16797 |    0.000000 |    0.000000 |   0.000000 | 1.000000e+00 | 1.000000e+00 | -6.076924 | 1.000000e+00 |\n",
+              "| 2-Aminoadipate_CHEBI:37024 |    0.000000 |    0.000000 |   0.000000 | 1.000000e+00 | 1.000000e+00 | -6.076924 | 1.000000e+00 |\n",
+              "| D-Glucitol_CHEBI:17924 |    0.000000 |    0.000000 |   0.000000 | 1.000000e+00 | 1.000000e+00 | -6.076924 | 1.000000e+00 |\n",
+              "\n"
+            ],
+            "text/plain": [
+              "                                        logFC       AveExpr     t         \n",
+              "beta-Alanine_CHEBI:16958                 -13.322222    6.661111 -48.116151\n",
+              "L-Asparagine_CHEBI:17196                  35.688889   30.033333  26.008087\n",
+              "NAD_CHEBI:44215                           24.155556   37.544444  21.756250\n",
+              "L-Proline_CHEBI:17203                     85.177778   89.900000  20.887545\n",
+              "L-Lysine_CHEBI:18019                     100.055556   76.561111  20.565697\n",
+              "L-Threonine_CHEBI:16857                  296.222222  324.100000  19.801519\n",
+              "L-Methionine_CHEBI:16643                 169.511111  106.933333  19.563843\n",
+              "Taurine_CHEBI:15891                      123.866667  223.944444  19.067959\n",
+              "L-Leucine_CHEBI:15603                    169.955556  140.144444  19.053618\n",
+              "Glycine_CHEBI:15428                      773.288889 1065.155556  18.313546\n",
+              "L-Aspartate_CHEBI:17053                  223.544444  207.316667  18.082490\n",
+              "L-Tyrosine_CHEBI:17895                   177.877778  130.005556  17.592594\n",
+              "L-Glutamine_CHEBI:18050                  593.555556  770.511111  17.351121\n",
+              "Pantothenate_CHEBI:7916                  -15.277778   13.627778 -17.289683\n",
+              "L-Tryptophan_CHEBI:16828                  49.188889   35.316667  17.148086\n",
+              "2-Oxoisocaproate_CHEBI:48430              10.600000    5.300000  17.104892\n",
+              "L-Glutamic acid_CHEBI:16015              497.911111  602.022222  16.753014\n",
+              "UDP-N-Acetylglucosamine_CHEBI:16264      115.911111  123.055556  16.493968\n",
+              "L-Isoleucine_CHEBI:17191                 214.077778  179.261111  16.367409\n",
+              "L-Phenylalanine_CHEBI:17295              243.566667  171.605556  16.309983\n",
+              "myo-Inositol_CHEBI:17268                -142.233333  201.772222 -15.503892\n",
+              "L-Valine_CHEBI:16414                     219.155556  183.133333  15.466025\n",
+              "Pyroglutamic acid_CHEBI:16010             50.755556   65.822222  15.343107\n",
+              "Adenosine triphosphate_CHEBI:15422        66.922222  101.516667  14.104590\n",
+              "Adenosine monophosphate_CHEBI:16027       -9.522222    4.761111 -11.408381\n",
+              "O-Phosphocholine_CHEBI:18132             169.544444  443.727778  10.969776\n",
+              "Creatine phosphate_CHEBI:17287            16.688889   33.611111   9.547933\n",
+              "Glutathione_CHEBI:16856                   69.122222  237.561111   7.627703\n",
+              "sn-Glycero-3-phosphocholine_CHEBI:16870  -43.955556  139.255556  -7.627153\n",
+              "Creatine_CHEBI:16919                       8.211111   25.927778   5.824279\n",
+              "Serine_CHEBI:17822                       -22.666667  129.400000  -3.494357\n",
+              "Lactate_CHEBI:78320                     -122.200000  434.444444  -3.102187\n",
+              "L-Alanine_CHEBI:16977                     84.977778  445.122222   3.008518\n",
+              "Formate_CHEBI:30751                        5.466667   19.788889   2.775695\n",
+              "D-Glucose_CHEBI:4167                      99.455556  280.305556   2.770631\n",
+              "Fumarate_CHEBI:18012                      -0.500000    3.250000  -1.827734\n",
+              "1-Methylnicotinamide_CHEBI:16797           0.000000    0.000000   0.000000\n",
+              "2-Aminoadipate_CHEBI:37024                 0.000000    0.000000   0.000000\n",
+              "D-Glucitol_CHEBI:17924                     0.000000    0.000000   0.000000\n",
+              "                                        P.Value      adj.P.Val    B        \n",
+              "beta-Alanine_CHEBI:16958                3.429304e-19 1.337429e-17 18.806919\n",
+              "L-Asparagine_CHEBI:17196                7.766249e-15 1.514419e-13 16.698049\n",
+              "NAD_CHEBI:44215                         1.367935e-13 1.778316e-12 15.656895\n",
+              "L-Proline_CHEBI:17203                   2.622041e-13 2.556490e-12 15.387073\n",
+              "L-Lysine_CHEBI:18019                    3.358302e-13 2.619475e-12 15.281051\n",
+              "L-Threonine_CHEBI:16857                 6.133421e-13 3.986724e-12 15.015120\n",
+              "L-Methionine_CHEBI:16643                7.429607e-13 4.139352e-12 14.928108\n",
+              "Taurine_CHEBI:15891                     1.116165e-12 4.894688e-12 14.739579\n",
+              "L-Leucine_CHEBI:15603                   1.129543e-12 4.894688e-12 14.733982\n",
+              "Glycine_CHEBI:15428                     2.113022e-12 8.240786e-12 14.433471\n",
+              "L-Aspartate_CHEBI:17053                 2.581559e-12 9.152799e-12 14.334764\n",
+              "L-Tyrosine_CHEBI:17895                  3.978202e-12 1.292916e-11 14.117304\n",
+              "L-Glutamine_CHEBI:18050                 4.943165e-12 1.455889e-11 14.005857\n",
+              "Pantothenate_CHEBI:7916                 5.226268e-12 1.455889e-11 13.977037\n",
+              "L-Tryptophan_CHEBI:16828                5.946082e-12 1.507831e-11 13.909884\n",
+              "2-Oxoisocaproate_CHEBI:48430            6.185975e-12 1.507831e-11 13.889195\n",
+              "L-Glutamic acid_CHEBI:16015             8.566715e-12 1.965305e-11 13.716991\n",
+              "UDP-N-Acetylglucosamine_CHEBI:16264     1.093011e-11 2.368190e-11 13.585939\n",
+              "L-Isoleucine_CHEBI:17191                1.232705e-11 2.530290e-11 13.520550\n",
+              "L-Phenylalanine_CHEBI:17295             1.302204e-11 2.539298e-11 13.490580\n",
+              "myo-Inositol_CHEBI:17268                2.865087e-11 5.275338e-11 13.049202\n",
+              "L-Valine_CHEBI:16414                    2.975831e-11 5.275338e-11 13.027481\n",
+              "Pyroglutamic acid_CHEBI:16010           3.367578e-11 5.710241e-11 12.956336\n",
+              "Adenosine triphosphate_CHEBI:15422      1.231598e-10 2.001347e-10 12.181716\n",
+              "Adenosine monophosphate_CHEBI:16027     3.001678e-09 4.682618e-09 10.059255\n",
+              "O-Phosphocholine_CHEBI:18132            5.339824e-09 8.009736e-09  9.645757\n",
+              "Creatine phosphate_CHEBI:17287          3.931667e-08 5.679075e-08  8.146605\n",
+              "Glutathione_CHEBI:16856                 8.354953e-07 1.124656e-06  5.676325\n",
+              "sn-Glycero-3-phosphocholine_CHEBI:16870 8.362826e-07 1.124656e-06  5.675535\n",
+              "Creatine_CHEBI:16919                    2.279425e-05 2.963252e-05  2.817898\n",
+              "Serine_CHEBI:17822                      2.880446e-03 3.623787e-03 -1.557547\n",
+              "Lactate_CHEBI:78320                     6.648459e-03 8.102809e-03 -2.315554\n",
+              "L-Alanine_CHEBI:16977                   8.105689e-03 9.579450e-03 -2.494233\n",
+              "Formate_CHEBI:30751                     1.320765e-02 1.487298e-02 -2.932204\n",
+              "D-Glucose_CHEBI:4167                    1.334755e-02 1.487298e-02 -2.941614\n",
+              "Fumarate_CHEBI:18012                    8.571259e-02 9.285531e-02 -4.554625\n",
+              "1-Methylnicotinamide_CHEBI:16797        1.000000e+00 1.000000e+00 -6.076924\n",
+              "2-Aminoadipate_CHEBI:37024              1.000000e+00 1.000000e+00 -6.076924\n",
+              "D-Glucitol_CHEBI:17924                  1.000000e+00 1.000000e+00 -6.076924\n",
+              "                                        BH          \n",
+              "beta-Alanine_CHEBI:16958                1.337429e-17\n",
+              "L-Asparagine_CHEBI:17196                1.514419e-13\n",
+              "NAD_CHEBI:44215                         1.778316e-12\n",
+              "L-Proline_CHEBI:17203                   2.556490e-12\n",
+              "L-Lysine_CHEBI:18019                    2.619475e-12\n",
+              "L-Threonine_CHEBI:16857                 3.986724e-12\n",
+              "L-Methionine_CHEBI:16643                4.139352e-12\n",
+              "Taurine_CHEBI:15891                     4.894688e-12\n",
+              "L-Leucine_CHEBI:15603                   4.894688e-12\n",
+              "Glycine_CHEBI:15428                     8.240786e-12\n",
+              "L-Aspartate_CHEBI:17053                 9.152799e-12\n",
+              "L-Tyrosine_CHEBI:17895                  1.292916e-11\n",
+              "L-Glutamine_CHEBI:18050                 1.455889e-11\n",
+              "Pantothenate_CHEBI:7916                 1.455889e-11\n",
+              "L-Tryptophan_CHEBI:16828                1.507831e-11\n",
+              "2-Oxoisocaproate_CHEBI:48430            1.507831e-11\n",
+              "L-Glutamic acid_CHEBI:16015             1.965305e-11\n",
+              "UDP-N-Acetylglucosamine_CHEBI:16264     2.368190e-11\n",
+              "L-Isoleucine_CHEBI:17191                2.530290e-11\n",
+              "L-Phenylalanine_CHEBI:17295             2.539298e-11\n",
+              "myo-Inositol_CHEBI:17268                5.275338e-11\n",
+              "L-Valine_CHEBI:16414                    5.275338e-11\n",
+              "Pyroglutamic acid_CHEBI:16010           5.710241e-11\n",
+              "Adenosine triphosphate_CHEBI:15422      2.001347e-10\n",
+              "Adenosine monophosphate_CHEBI:16027     4.682618e-09\n",
+              "O-Phosphocholine_CHEBI:18132            8.009736e-09\n",
+              "Creatine phosphate_CHEBI:17287          5.679075e-08\n",
+              "Glutathione_CHEBI:16856                 1.124656e-06\n",
+              "sn-Glycero-3-phosphocholine_CHEBI:16870 1.124656e-06\n",
+              "Creatine_CHEBI:16919                    2.963252e-05\n",
+              "Serine_CHEBI:17822                      3.623787e-03\n",
+              "Lactate_CHEBI:78320                     8.102809e-03\n",
+              "L-Alanine_CHEBI:16977                   9.579450e-03\n",
+              "Formate_CHEBI:30751                     1.487298e-02\n",
+              "D-Glucose_CHEBI:4167                    1.487298e-02\n",
+              "Fumarate_CHEBI:18012                    9.285531e-02\n",
+              "1-Methylnicotinamide_CHEBI:16797        1.000000e+00\n",
+              "2-Aminoadipate_CHEBI:37024              1.000000e+00\n",
+              "D-Glucitol_CHEBI:17924                  1.000000e+00"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "#Differential Expression\n",
+        "\n",
+        "#Read files \n",
+        "metadata_met <- read.csv('met_metadata.csv')\n",
+        "metadata_met1 <- metadata_met[,-2]\n",
+        "rownames(metadata_met1) <- metadata_met[,2] \n",
+        "\n",
+        "data_met <- read.csv('met_data.csv')\n",
+        "data_met1 <- data_met[,-1]\n",
+        "rownames(data_met1) <- data_met[,1] \n",
+        "\n",
+        "# Run script\n",
+        "\n",
+        "diff_exp_limma <- function(data_matrix, metadata, cohortCol, cohort_a, cohort_b, p_val_correct_methods) {\n",
+        "    \n",
+        "    # Subset the metadata dataframe to have samples from the provided cohorts only\n",
+        "    metadata <- metadata[metadata[, cohortCol] %in% c(cohort_a, cohort_b),]\n",
+        "    # Create a comparison column\n",
+        "    metadata[, \"comparison\"] <- NA\n",
+        "    metadata[metadata[, cohortCol] %in% cohort_a, \"comparison\"] <- \"A\"\n",
+        "    metadata[metadata[, cohortCol] %in% cohort_b, \"comparison\"] <- \"B\"\n",
+        "    \n",
+        "    condition <- metadata[, \"comparison\"]\n",
+        "    ### Creating design matrix of comparisons required (without batch)\n",
+        "    design <- model.matrix(~ condition + 0)\n",
+        "    colnames(design) <- gsub(\"condition\", \"\", colnames(design))\n",
+        "    contrast_matrix <- limma::makeContrasts(contrasts = c(paste(\"B\", \"A\", sep = \"-\")), levels = design)\n",
+        "\n",
+        "    data_matrix <- data_matrix[, rownames(metadata)]\n",
+        "    data_matrix <- data_matrix[!apply(data_matrix, 1, anyNA), ]\n",
+        "\n",
+        "    ### Fitting linear model to log2 normalised expression data\n",
+        "    fit <- limma::lmFit(data_matrix, design)\n",
+        "    fit <- limma::contrasts.fit(fit, contrast_matrix)\n",
+        "    fit <- limma::eBayes(fit)\n",
+        "    limma_results_df <- limma::topTable(fit, coef = paste(\"B\", \"A\", sep = \"-\"), number = nrow(data_matrix))\n",
+        "\n",
+        "    ### p value correction\n",
+        "    for (p_val_correct in p_val_correct_methods) {\n",
+        "        if (p_val_correct == \"Bonferroni\") {\n",
+        "            p_val_correct_method <- \"bonferroni\"\n",
+        "        }else {\n",
+        "            p_val_correct_method <- \"BH\"\n",
+        "        }    \n",
+        "        limma_results_df[, p_val_correct] <- p.adjust(limma_results_df$P.Value, method = p_val_correct_method)\n",
+        "    }\n",
+        "    return(limma_results_df)\n",
+        "}\n",
+        "\n",
+        "diff_exp_matrix <- diff_exp_limma(data_met1, metadata_met1, 'curated_cell_line', 'HCC-1937 cell', 'MCF-7 cell', 'BH')\n",
+        "diff_exp_matrix"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "R"
+      },
+      "source": [
+        "### Performing MSEA \n",
+        "- MSEA helps in identifying and interpreting patterns of human or mammalian metabolite concentration changes in a biologically meaningful context\n",
+        "    - MSEA offers three different enrichment analyses for metabolomic studies \n",
+        "        - Overrepresentation analysis (ORA) - Requires only compound names\n",
+        "        - Single sample profiling (SSP) - Requires compound names and compound concentrations\n",
+        "        - Quantitative enrichment analysis (QEA) -  Requires compound names and compound concentrations\n",
+        "- The below function for MSEA performs ORA\n",
+        "- References\n",
+        "     - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896187/\n",
+        "     - https://www.metaboanalyst.ca/docs/RTutorial.xhtml"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 48,
+      "metadata": {
+        "kernel": "R"
+      },
+      "outputs": [],
+      "source": [
+        "perform_MSEA <- function(data_matrix) {\n",
+        "    library(\"MetaboAnalystR\")\n",
+        "    library(png)\n",
+        "    metabolites <- c()\n",
+        "    for (compound in rownames(data_matrix)){\n",
+        "        name <- strsplit(compound,'_')[[1]][1]\n",
+        "        metabolites<- c(name,metabolites)\n",
+        "    }\n",
+        "    tmp.vec <- metabolites\n",
+        "    mSet<-InitDataObjects(\"conc\", \"pathora\", FALSE) \n",
+        "    mSet<-Setup.MapData(mSet, tmp.vec)\n",
+        "    mSet<-CrossReferencing(mSet, \"name\")\n",
+        "    mSet<-CreateMappingResultTable(mSet)\n",
+        "    # Use \"current\" for the latest KEGG pathway library or \"v2018\" for the KEGG pathway library version prior to November 2019.\n",
+        "    mSet<-SetKEGG.PathLib(mSet, \"hsa\", \"current\")\n",
+        "    # Set the metabolite filter\n",
+        "    mSet<-SetMetabolomeFilter(mSet, F)\n",
+        "    mSet<-SetCurrentMsetLib(mSet, \"kegg_pathway\", 2);\n",
+        "    # Calculate hypergeometric score, results table generated in your working directory\n",
+        "    mSet<-CalculateHyperScore(mSet)\n",
+        "    # Plot the ORA, bar-graph\n",
+        "    mSet<-PlotORA(mSet, \"msea_results_\", \"bar\", \"png\", 72, width=NA)\n",
+        "    img <- readPNG('msea_results_dpi72.png')\n",
+        "    grid::grid.raster(img)\n",
+        "    print('MSEA results stored in msea_ora_result.csv file')\n",
+        "    print('Compound mapping stored in name_map.csv file') \n",
+        "}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 49,
+      "metadata": {
+        "kernel": "R"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "[1] \"Please download the sqlite zipped folder from Google Drive (link in vignette) and \\n          create an R objected named url.pre with the path to the sqlite folder.\"\n",
+            "[1] \"MetaboAnalyst R objects initialized ...\"\n",
+            "[1] \"Loaded files from MetaboAnalyst web-server.\"\n",
+            "[1] \"Loaded files from MetaboAnalyst web-server.\"\n",
+            "[1] \"1\"                                                                              \n",
+            "[2] \"Name matching OK, please inspect (and manual correct) the results then proceed.\"\n",
+            "[1] \"Loaded files from MetaboAnalyst web-server.\"\n",
+            "[1] \"Loaded files from MetaboAnalyst web-server.\"\n",
+            "[1] \"http://api.xialab.ca/msetora\"\n",
+            "[1] \"Mset ORA via api.metaboanalyst.ca successful!\"\n"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "Warning message in space + width:\n",
+            "“longer object length is not a multiple of shorter object length”\n",
+            "Warning message in space + width:\n",
+            "“longer object length is not a multiple of shorter object length”\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "[1] \"MSEA results stored in msea_ora_result.csv file\"\n",
+            "[1] \"Compound mapping stored in name_map.csv file\"\n"
+          ]
+        },
+        {
+          "data": {
+            "image/png": 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vvcW2tXLwkU5u5JSFh5SPS/+sf/7FB76/BDATSFMdcS9v/Rib5jY21+WSDRhMgd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\nELGc+mKldG1HL2pfuC2mJdY1LLrHZc7LY4wRyqyWPv7p9Mp0DmP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lud96dPeOTo9FljgOY9aoyFstJWRZfv7555944gmEkNaqq9Xc9NnzJ7/zg7Kz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\nsj+Mm6nK9OXkqiOWdFtxqbS5OTWbmcvi2i09oDEhgtUlObx6fr0YL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dHT1rO9OhEPfEhjn99oAoDleEn2BZTKlmT73oaGhgj/4TaB7l4E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\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fWy08xhZKdI3JeVWVb3Lp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\nI0/uy7gZzuAz+NbV11z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cyOcXRzkd3XduKkbDLV/59cH959S3Lm7f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\n5KhoKSP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Mjuee34339v71/+v4/094Qs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\n7Qv5RB9LMO1gxfaAq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XnTrl0NqpPOpRajMhH0KDOnl6du9V69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",
+            "text/plain": [
+              "plot without title"
+            ]
+          },
+          "metadata": {
+            "image/png": {
+              "height": 600,
+              "width": 960
+            }
+          },
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "perform_MSEA(data_met1)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 50,
+      "metadata": {
+        "kernel": "R"
+      },
+      "outputs": [],
+      "source": [
+        "#result files gnerated\n",
+        "msea_res <- read.csv('msea_ora_result.csv')\n",
+        "name_map <- read.csv('name_map.csv')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 51,
+      "metadata": {
+        "kernel": "R",
+        "scrolled": true
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<table class=\"dataframe\">\n",
+              "<caption>A data.frame: 45 × 7</caption>\n",
+              "<thead>\n",
+              "\t<tr><th scope=col>X</th><th scope=col>total</th><th scope=col>expected</th><th scope=col>hits</th><th scope=col>Raw.p</th><th scope=col>Holm.p</th><th scope=col>FDR</th></tr>\n",
+              "\t<tr><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
+              "</thead>\n",
+              "<tbody>\n",
+              "\t<tr><td>Aminoacyl-tRNA biosynthesis                           </td><td>48</td><td>1.2300</td><td>16</td><td>1.46e-15</td><td>1.22e-13</td><td>1.22e-13</td></tr>\n",
+              "\t<tr><td>Valine, leucine and isoleucine biosynthesis           </td><td> 8</td><td>0.2050</td><td> 5</td><td>4.51e-07</td><td>3.74e-05</td><td>1.89e-05</td></tr>\n",
+              "\t<tr><td>D-Glutamine and D-glutamate metabolism                </td><td> 6</td><td>0.1540</td><td> 4</td><td>5.34e-06</td><td>4.38e-04</td><td>1.49e-04</td></tr>\n",
+              "\t<tr><td>Alanine, aspartate and glutamate metabolism           </td><td>28</td><td>0.7170</td><td> 6</td><td>4.75e-05</td><td>3.85e-03</td><td>9.97e-04</td></tr>\n",
+              "\t<tr><td>Arginine biosynthesis                                 </td><td>14</td><td>0.3590</td><td> 4</td><td>3.07e-04</td><td>2.46e-02</td><td>5.16e-03</td></tr>\n",
+              "\t<tr><td>Pantothenate and CoA biosynthesis                     </td><td>19</td><td>0.4870</td><td> 4</td><td>1.08e-03</td><td>8.56e-02</td><td>1.52e-02</td></tr>\n",
+              "\t<tr><td>Phenylalanine, tyrosine and tryptophan biosynthesis   </td><td> 4</td><td>0.1020</td><td> 2</td><td>3.72e-03</td><td>2.90e-01</td><td>4.46e-02</td></tr>\n",
+              "\t<tr><td>Glutathione metabolism                                </td><td>28</td><td>0.7170</td><td> 4</td><td>4.84e-03</td><td>3.73e-01</td><td>5.09e-02</td></tr>\n",
+              "\t<tr><td>Nicotinate and nicotinamide metabolism                </td><td>15</td><td>0.3840</td><td> 3</td><td>5.72e-03</td><td>4.35e-01</td><td>5.34e-02</td></tr>\n",
+              "\t<tr><td>Glyoxylate and dicarboxylate metabolism               </td><td>32</td><td>0.8200</td><td> 4</td><td>7.90e-03</td><td>5.93e-01</td><td>6.64e-02</td></tr>\n",
+              "\t<tr><td>Nitrogen metabolism                                   </td><td> 6</td><td>0.1540</td><td> 2</td><td>9.00e-03</td><td>6.66e-01</td><td>6.87e-02</td></tr>\n",
+              "\t<tr><td>Arginine and proline metabolism                       </td><td>38</td><td>0.9740</td><td> 4</td><td>1.45e-02</td><td>1.00e+00</td><td>1.02e-01</td></tr>\n",
+              "\t<tr><td>Valine, leucine and isoleucine degradation            </td><td>40</td><td>1.0200</td><td> 4</td><td>1.73e-02</td><td>1.00e+00</td><td>1.12e-01</td></tr>\n",
+              "\t<tr><td>Phenylalanine metabolism                              </td><td>10</td><td>0.2560</td><td> 2</td><td>2.53e-02</td><td>1.00e+00</td><td>1.52e-01</td></tr>\n",
+              "\t<tr><td>Galactose metabolism                                  </td><td>27</td><td>0.6920</td><td> 3</td><td>2.97e-02</td><td>1.00e+00</td><td>1.67e-01</td></tr>\n",
+              "\t<tr><td>Glycine, serine and threonine metabolism              </td><td>33</td><td>0.8460</td><td> 3</td><td>4.99e-02</td><td>1.00e+00</td><td>2.50e-01</td></tr>\n",
+              "\t<tr><td>Neomycin, kanamycin and gentamicin biosynthesis       </td><td> 2</td><td>0.0512</td><td> 1</td><td>5.06e-02</td><td>1.00e+00</td><td>2.50e-01</td></tr>\n",
+              "\t<tr><td>Histidine metabolism                                  </td><td>16</td><td>0.4100</td><td> 2</td><td>6.12e-02</td><td>1.00e+00</td><td>2.86e-01</td></tr>\n",
+              "\t<tr><td>beta-Alanine metabolism                               </td><td>21</td><td>0.5380</td><td> 2</td><td>9.90e-02</td><td>1.00e+00</td><td>4.38e-01</td></tr>\n",
+              "\t<tr><td>Pyruvate metabolism                                   </td><td>22</td><td>0.5640</td><td> 2</td><td>1.07e-01</td><td>1.00e+00</td><td>4.50e-01</td></tr>\n",
+              "\t<tr><td>Lysine degradation                                    </td><td>25</td><td>0.6410</td><td> 2</td><td>1.33e-01</td><td>1.00e+00</td><td>5.31e-01</td></tr>\n",
+              "\t<tr><td>Phosphonate and phosphinate metabolism                </td><td> 6</td><td>0.1540</td><td> 1</td><td>1.44e-01</td><td>1.00e+00</td><td>5.52e-01</td></tr>\n",
+              "\t<tr><td>Porphyrin and chlorophyll metabolism                  </td><td>30</td><td>0.7690</td><td> 2</td><td>1.78e-01</td><td>1.00e+00</td><td>6.31e-01</td></tr>\n",
+              "\t<tr><td>Ascorbate and aldarate metabolism                     </td><td> 8</td><td>0.2050</td><td> 1</td><td>1.88e-01</td><td>1.00e+00</td><td>6.31e-01</td></tr>\n",
+              "\t<tr><td>Taurine and hypotaurine metabolism                    </td><td> 8</td><td>0.2050</td><td> 1</td><td>1.88e-01</td><td>1.00e+00</td><td>6.31e-01</td></tr>\n",
+              "\t<tr><td>Ubiquinone and other terpenoid-quinone biosynthesis   </td><td> 9</td><td>0.2310</td><td> 1</td><td>2.09e-01</td><td>1.00e+00</td><td>6.75e-01</td></tr>\n",
+              "\t<tr><td>Biotin metabolism                                     </td><td>10</td><td>0.2560</td><td> 1</td><td>2.29e-01</td><td>1.00e+00</td><td>6.80e-01</td></tr>\n",
+              "\t<tr><td>Purine metabolism                                     </td><td>65</td><td>1.6700</td><td> 3</td><td>2.30e-01</td><td>1.00e+00</td><td>6.80e-01</td></tr>\n",
+              "\t<tr><td>Glycerophospholipid metabolism                        </td><td>36</td><td>0.9220</td><td> 2</td><td>2.35e-01</td><td>1.00e+00</td><td>6.80e-01</td></tr>\n",
+              "\t<tr><td>Pyrimidine metabolism                                 </td><td>39</td><td>0.9990</td><td> 2</td><td>2.64e-01</td><td>1.00e+00</td><td>7.39e-01</td></tr>\n",
+              "\t<tr><td>Tyrosine metabolism                                   </td><td>42</td><td>1.0800</td><td> 2</td><td>2.93e-01</td><td>1.00e+00</td><td>7.94e-01</td></tr>\n",
+              "\t<tr><td>Glycosylphosphatidylinositol (GPI)-anchor biosynthesis</td><td>14</td><td>0.3590</td><td> 1</td><td>3.06e-01</td><td>1.00e+00</td><td>8.03e-01</td></tr>\n",
+              "\t<tr><td>Butanoate metabolism                                  </td><td>15</td><td>0.3840</td><td> 1</td><td>3.24e-01</td><td>1.00e+00</td><td>8.19e-01</td></tr>\n",
+              "\t<tr><td>Primary bile acid biosynthesis                        </td><td>46</td><td>1.1800</td><td> 2</td><td>3.31e-01</td><td>1.00e+00</td><td>8.19e-01</td></tr>\n",
+              "\t<tr><td>Starch and sucrose metabolism                         </td><td>18</td><td>0.4610</td><td> 1</td><td>3.75e-01</td><td>1.00e+00</td><td>8.77e-01</td></tr>\n",
+              "\t<tr><td>Citrate cycle (TCA cycle)                             </td><td>20</td><td>0.5120</td><td> 1</td><td>4.07e-01</td><td>1.00e+00</td><td>8.77e-01</td></tr>\n",
+              "\t<tr><td>Fructose and mannose metabolism                       </td><td>20</td><td>0.5120</td><td> 1</td><td>4.07e-01</td><td>1.00e+00</td><td>8.77e-01</td></tr>\n",
+              "\t<tr><td>Selenocompound metabolism                             </td><td>20</td><td>0.5120</td><td> 1</td><td>4.07e-01</td><td>1.00e+00</td><td>8.77e-01</td></tr>\n",
+              "\t<tr><td>Ether lipid metabolism                                </td><td>20</td><td>0.5120</td><td> 1</td><td>4.07e-01</td><td>1.00e+00</td><td>8.77e-01</td></tr>\n",
+              "\t<tr><td>Propanoate metabolism                                 </td><td>23</td><td>0.5890</td><td> 1</td><td>4.52e-01</td><td>1.00e+00</td><td>9.49e-01</td></tr>\n",
+              "\t<tr><td>Glycolysis / Gluconeogenesis                          </td><td>26</td><td>0.6660</td><td> 1</td><td>4.94e-01</td><td>1.00e+00</td><td>1.00e+00</td></tr>\n",
+              "\t<tr><td>Phosphatidylinositol signaling system                 </td><td>28</td><td>0.7170</td><td> 1</td><td>5.20e-01</td><td>1.00e+00</td><td>1.00e+00</td></tr>\n",
+              "\t<tr><td>Inositol phosphate metabolism                         </td><td>30</td><td>0.7690</td><td> 1</td><td>5.45e-01</td><td>1.00e+00</td><td>1.00e+00</td></tr>\n",
+              "\t<tr><td>Cysteine and methionine metabolism                    </td><td>33</td><td>0.8460</td><td> 1</td><td>5.79e-01</td><td>1.00e+00</td><td>1.00e+00</td></tr>\n",
+              "\t<tr><td>Tryptophan metabolism                                 </td><td>41</td><td>1.0500</td><td> 1</td><td>6.60e-01</td><td>1.00e+00</td><td>1.00e+00</td></tr>\n",
+              "</tbody>\n",
+              "</table>\n"
+            ],
+            "text/latex": [
+              "A data.frame: 45 × 7\n",
+              "\\begin{tabular}{lllllll}\n",
+              " X & total & expected & hits & Raw.p & Holm.p & FDR\\\\\n",
+              " <fct> & <int> & <dbl> & <int> & <dbl> & <dbl> & <dbl>\\\\\n",
+              "\\hline\n",
+              "\t Aminoacyl-tRNA biosynthesis                            & 48 & 1.2300 & 16 & 1.46e-15 & 1.22e-13 & 1.22e-13\\\\\n",
+              "\t Valine, leucine and isoleucine biosynthesis            &  8 & 0.2050 &  5 & 4.51e-07 & 3.74e-05 & 1.89e-05\\\\\n",
+              "\t D-Glutamine and D-glutamate metabolism                 &  6 & 0.1540 &  4 & 5.34e-06 & 4.38e-04 & 1.49e-04\\\\\n",
+              "\t Alanine, aspartate and glutamate metabolism            & 28 & 0.7170 &  6 & 4.75e-05 & 3.85e-03 & 9.97e-04\\\\\n",
+              "\t Arginine biosynthesis                                  & 14 & 0.3590 &  4 & 3.07e-04 & 2.46e-02 & 5.16e-03\\\\\n",
+              "\t Pantothenate and CoA biosynthesis                      & 19 & 0.4870 &  4 & 1.08e-03 & 8.56e-02 & 1.52e-02\\\\\n",
+              "\t Phenylalanine, tyrosine and tryptophan biosynthesis    &  4 & 0.1020 &  2 & 3.72e-03 & 2.90e-01 & 4.46e-02\\\\\n",
+              "\t Glutathione metabolism                                 & 28 & 0.7170 &  4 & 4.84e-03 & 3.73e-01 & 5.09e-02\\\\\n",
+              "\t Nicotinate and nicotinamide metabolism                 & 15 & 0.3840 &  3 & 5.72e-03 & 4.35e-01 & 5.34e-02\\\\\n",
+              "\t Glyoxylate and dicarboxylate metabolism                & 32 & 0.8200 &  4 & 7.90e-03 & 5.93e-01 & 6.64e-02\\\\\n",
+              "\t Nitrogen metabolism                                    &  6 & 0.1540 &  2 & 9.00e-03 & 6.66e-01 & 6.87e-02\\\\\n",
+              "\t Arginine and proline metabolism                        & 38 & 0.9740 &  4 & 1.45e-02 & 1.00e+00 & 1.02e-01\\\\\n",
+              "\t Valine, leucine and isoleucine degradation             & 40 & 1.0200 &  4 & 1.73e-02 & 1.00e+00 & 1.12e-01\\\\\n",
+              "\t Phenylalanine metabolism                               & 10 & 0.2560 &  2 & 2.53e-02 & 1.00e+00 & 1.52e-01\\\\\n",
+              "\t Galactose metabolism                                   & 27 & 0.6920 &  3 & 2.97e-02 & 1.00e+00 & 1.67e-01\\\\\n",
+              "\t Glycine, serine and threonine metabolism               & 33 & 0.8460 &  3 & 4.99e-02 & 1.00e+00 & 2.50e-01\\\\\n",
+              "\t Neomycin, kanamycin and gentamicin biosynthesis        &  2 & 0.0512 &  1 & 5.06e-02 & 1.00e+00 & 2.50e-01\\\\\n",
+              "\t Histidine metabolism                                   & 16 & 0.4100 &  2 & 6.12e-02 & 1.00e+00 & 2.86e-01\\\\\n",
+              "\t beta-Alanine metabolism                                & 21 & 0.5380 &  2 & 9.90e-02 & 1.00e+00 & 4.38e-01\\\\\n",
+              "\t Pyruvate metabolism                                    & 22 & 0.5640 &  2 & 1.07e-01 & 1.00e+00 & 4.50e-01\\\\\n",
+              "\t Lysine degradation                                     & 25 & 0.6410 &  2 & 1.33e-01 & 1.00e+00 & 5.31e-01\\\\\n",
+              "\t Phosphonate and phosphinate metabolism                 &  6 & 0.1540 &  1 & 1.44e-01 & 1.00e+00 & 5.52e-01\\\\\n",
+              "\t Porphyrin and chlorophyll metabolism                   & 30 & 0.7690 &  2 & 1.78e-01 & 1.00e+00 & 6.31e-01\\\\\n",
+              "\t Ascorbate and aldarate metabolism                      &  8 & 0.2050 &  1 & 1.88e-01 & 1.00e+00 & 6.31e-01\\\\\n",
+              "\t Taurine and hypotaurine metabolism                     &  8 & 0.2050 &  1 & 1.88e-01 & 1.00e+00 & 6.31e-01\\\\\n",
+              "\t Ubiquinone and other terpenoid-quinone biosynthesis    &  9 & 0.2310 &  1 & 2.09e-01 & 1.00e+00 & 6.75e-01\\\\\n",
+              "\t Biotin metabolism                                      & 10 & 0.2560 &  1 & 2.29e-01 & 1.00e+00 & 6.80e-01\\\\\n",
+              "\t Purine metabolism                                      & 65 & 1.6700 &  3 & 2.30e-01 & 1.00e+00 & 6.80e-01\\\\\n",
+              "\t Glycerophospholipid metabolism                         & 36 & 0.9220 &  2 & 2.35e-01 & 1.00e+00 & 6.80e-01\\\\\n",
+              "\t Pyrimidine metabolism                                  & 39 & 0.9990 &  2 & 2.64e-01 & 1.00e+00 & 7.39e-01\\\\\n",
+              "\t Tyrosine metabolism                                    & 42 & 1.0800 &  2 & 2.93e-01 & 1.00e+00 & 7.94e-01\\\\\n",
+              "\t Glycosylphosphatidylinositol (GPI)-anchor biosynthesis & 14 & 0.3590 &  1 & 3.06e-01 & 1.00e+00 & 8.03e-01\\\\\n",
+              "\t Butanoate metabolism                                   & 15 & 0.3840 &  1 & 3.24e-01 & 1.00e+00 & 8.19e-01\\\\\n",
+              "\t Primary bile acid biosynthesis                         & 46 & 1.1800 &  2 & 3.31e-01 & 1.00e+00 & 8.19e-01\\\\\n",
+              "\t Starch and sucrose metabolism                          & 18 & 0.4610 &  1 & 3.75e-01 & 1.00e+00 & 8.77e-01\\\\\n",
+              "\t Citrate cycle (TCA cycle)                              & 20 & 0.5120 &  1 & 4.07e-01 & 1.00e+00 & 8.77e-01\\\\\n",
+              "\t Fructose and mannose metabolism                        & 20 & 0.5120 &  1 & 4.07e-01 & 1.00e+00 & 8.77e-01\\\\\n",
+              "\t Selenocompound metabolism                              & 20 & 0.5120 &  1 & 4.07e-01 & 1.00e+00 & 8.77e-01\\\\\n",
+              "\t Ether lipid metabolism                                 & 20 & 0.5120 &  1 & 4.07e-01 & 1.00e+00 & 8.77e-01\\\\\n",
+              "\t Propanoate metabolism                                  & 23 & 0.5890 &  1 & 4.52e-01 & 1.00e+00 & 9.49e-01\\\\\n",
+              "\t Glycolysis / Gluconeogenesis                           & 26 & 0.6660 &  1 & 4.94e-01 & 1.00e+00 & 1.00e+00\\\\\n",
+              "\t Phosphatidylinositol signaling system                  & 28 & 0.7170 &  1 & 5.20e-01 & 1.00e+00 & 1.00e+00\\\\\n",
+              "\t Inositol phosphate metabolism                          & 30 & 0.7690 &  1 & 5.45e-01 & 1.00e+00 & 1.00e+00\\\\\n",
+              "\t Cysteine and methionine metabolism                     & 33 & 0.8460 &  1 & 5.79e-01 & 1.00e+00 & 1.00e+00\\\\\n",
+              "\t Tryptophan metabolism                                  & 41 & 1.0500 &  1 & 6.60e-01 & 1.00e+00 & 1.00e+00\\\\\n",
+              "\\end{tabular}\n"
+            ],
+            "text/markdown": [
+              "\n",
+              "A data.frame: 45 × 7\n",
+              "\n",
+              "| X &lt;fct&gt; | total &lt;int&gt; | expected &lt;dbl&gt; | hits &lt;int&gt; | Raw.p &lt;dbl&gt; | Holm.p &lt;dbl&gt; | FDR &lt;dbl&gt; |\n",
+              "|---|---|---|---|---|---|---|\n",
+              "| Aminoacyl-tRNA biosynthesis                            | 48 | 1.2300 | 16 | 1.46e-15 | 1.22e-13 | 1.22e-13 |\n",
+              "| Valine, leucine and isoleucine biosynthesis            |  8 | 0.2050 |  5 | 4.51e-07 | 3.74e-05 | 1.89e-05 |\n",
+              "| D-Glutamine and D-glutamate metabolism                 |  6 | 0.1540 |  4 | 5.34e-06 | 4.38e-04 | 1.49e-04 |\n",
+              "| Alanine, aspartate and glutamate metabolism            | 28 | 0.7170 |  6 | 4.75e-05 | 3.85e-03 | 9.97e-04 |\n",
+              "| Arginine biosynthesis                                  | 14 | 0.3590 |  4 | 3.07e-04 | 2.46e-02 | 5.16e-03 |\n",
+              "| Pantothenate and CoA biosynthesis                      | 19 | 0.4870 |  4 | 1.08e-03 | 8.56e-02 | 1.52e-02 |\n",
+              "| Phenylalanine, tyrosine and tryptophan biosynthesis    |  4 | 0.1020 |  2 | 3.72e-03 | 2.90e-01 | 4.46e-02 |\n",
+              "| Glutathione metabolism                                 | 28 | 0.7170 |  4 | 4.84e-03 | 3.73e-01 | 5.09e-02 |\n",
+              "| Nicotinate and nicotinamide metabolism                 | 15 | 0.3840 |  3 | 5.72e-03 | 4.35e-01 | 5.34e-02 |\n",
+              "| Glyoxylate and dicarboxylate metabolism                | 32 | 0.8200 |  4 | 7.90e-03 | 5.93e-01 | 6.64e-02 |\n",
+              "| Nitrogen metabolism                                    |  6 | 0.1540 |  2 | 9.00e-03 | 6.66e-01 | 6.87e-02 |\n",
+              "| Arginine and proline metabolism                        | 38 | 0.9740 |  4 | 1.45e-02 | 1.00e+00 | 1.02e-01 |\n",
+              "| Valine, leucine and isoleucine degradation             | 40 | 1.0200 |  4 | 1.73e-02 | 1.00e+00 | 1.12e-01 |\n",
+              "| Phenylalanine metabolism                               | 10 | 0.2560 |  2 | 2.53e-02 | 1.00e+00 | 1.52e-01 |\n",
+              "| Galactose metabolism                                   | 27 | 0.6920 |  3 | 2.97e-02 | 1.00e+00 | 1.67e-01 |\n",
+              "| Glycine, serine and threonine metabolism               | 33 | 0.8460 |  3 | 4.99e-02 | 1.00e+00 | 2.50e-01 |\n",
+              "| Neomycin, kanamycin and gentamicin biosynthesis        |  2 | 0.0512 |  1 | 5.06e-02 | 1.00e+00 | 2.50e-01 |\n",
+              "| Histidine metabolism                                   | 16 | 0.4100 |  2 | 6.12e-02 | 1.00e+00 | 2.86e-01 |\n",
+              "| beta-Alanine metabolism                                | 21 | 0.5380 |  2 | 9.90e-02 | 1.00e+00 | 4.38e-01 |\n",
+              "| Pyruvate metabolism                                    | 22 | 0.5640 |  2 | 1.07e-01 | 1.00e+00 | 4.50e-01 |\n",
+              "| Lysine degradation                                     | 25 | 0.6410 |  2 | 1.33e-01 | 1.00e+00 | 5.31e-01 |\n",
+              "| Phosphonate and phosphinate metabolism                 |  6 | 0.1540 |  1 | 1.44e-01 | 1.00e+00 | 5.52e-01 |\n",
+              "| Porphyrin and chlorophyll metabolism                   | 30 | 0.7690 |  2 | 1.78e-01 | 1.00e+00 | 6.31e-01 |\n",
+              "| Ascorbate and aldarate metabolism                      |  8 | 0.2050 |  1 | 1.88e-01 | 1.00e+00 | 6.31e-01 |\n",
+              "| Taurine and hypotaurine metabolism                     |  8 | 0.2050 |  1 | 1.88e-01 | 1.00e+00 | 6.31e-01 |\n",
+              "| Ubiquinone and other terpenoid-quinone biosynthesis    |  9 | 0.2310 |  1 | 2.09e-01 | 1.00e+00 | 6.75e-01 |\n",
+              "| Biotin metabolism                                      | 10 | 0.2560 |  1 | 2.29e-01 | 1.00e+00 | 6.80e-01 |\n",
+              "| Purine metabolism                                      | 65 | 1.6700 |  3 | 2.30e-01 | 1.00e+00 | 6.80e-01 |\n",
+              "| Glycerophospholipid metabolism                         | 36 | 0.9220 |  2 | 2.35e-01 | 1.00e+00 | 6.80e-01 |\n",
+              "| Pyrimidine metabolism                                  | 39 | 0.9990 |  2 | 2.64e-01 | 1.00e+00 | 7.39e-01 |\n",
+              "| Tyrosine metabolism                                    | 42 | 1.0800 |  2 | 2.93e-01 | 1.00e+00 | 7.94e-01 |\n",
+              "| Glycosylphosphatidylinositol (GPI)-anchor biosynthesis | 14 | 0.3590 |  1 | 3.06e-01 | 1.00e+00 | 8.03e-01 |\n",
+              "| Butanoate metabolism                                   | 15 | 0.3840 |  1 | 3.24e-01 | 1.00e+00 | 8.19e-01 |\n",
+              "| Primary bile acid biosynthesis                         | 46 | 1.1800 |  2 | 3.31e-01 | 1.00e+00 | 8.19e-01 |\n",
+              "| Starch and sucrose metabolism                          | 18 | 0.4610 |  1 | 3.75e-01 | 1.00e+00 | 8.77e-01 |\n",
+              "| Citrate cycle (TCA cycle)                              | 20 | 0.5120 |  1 | 4.07e-01 | 1.00e+00 | 8.77e-01 |\n",
+              "| Fructose and mannose metabolism                        | 20 | 0.5120 |  1 | 4.07e-01 | 1.00e+00 | 8.77e-01 |\n",
+              "| Selenocompound metabolism                              | 20 | 0.5120 |  1 | 4.07e-01 | 1.00e+00 | 8.77e-01 |\n",
+              "| Ether lipid metabolism                                 | 20 | 0.5120 |  1 | 4.07e-01 | 1.00e+00 | 8.77e-01 |\n",
+              "| Propanoate metabolism                                  | 23 | 0.5890 |  1 | 4.52e-01 | 1.00e+00 | 9.49e-01 |\n",
+              "| Glycolysis / Gluconeogenesis                           | 26 | 0.6660 |  1 | 4.94e-01 | 1.00e+00 | 1.00e+00 |\n",
+              "| Phosphatidylinositol signaling system                  | 28 | 0.7170 |  1 | 5.20e-01 | 1.00e+00 | 1.00e+00 |\n",
+              "| Inositol phosphate metabolism                          | 30 | 0.7690 |  1 | 5.45e-01 | 1.00e+00 | 1.00e+00 |\n",
+              "| Cysteine and methionine metabolism                     | 33 | 0.8460 |  1 | 5.79e-01 | 1.00e+00 | 1.00e+00 |\n",
+              "| Tryptophan metabolism                                  | 41 | 1.0500 |  1 | 6.60e-01 | 1.00e+00 | 1.00e+00 |\n",
+              "\n"
+            ],
+            "text/plain": [
+              "   X                                                      total expected hits\n",
+              "1  Aminoacyl-tRNA biosynthesis                            48    1.2300   16  \n",
+              "2  Valine, leucine and isoleucine biosynthesis             8    0.2050    5  \n",
+              "3  D-Glutamine and D-glutamate metabolism                  6    0.1540    4  \n",
+              "4  Alanine, aspartate and glutamate metabolism            28    0.7170    6  \n",
+              "5  Arginine biosynthesis                                  14    0.3590    4  \n",
+              "6  Pantothenate and CoA biosynthesis                      19    0.4870    4  \n",
+              "7  Phenylalanine, tyrosine and tryptophan biosynthesis     4    0.1020    2  \n",
+              "8  Glutathione metabolism                                 28    0.7170    4  \n",
+              "9  Nicotinate and nicotinamide metabolism                 15    0.3840    3  \n",
+              "10 Glyoxylate and dicarboxylate metabolism                32    0.8200    4  \n",
+              "11 Nitrogen metabolism                                     6    0.1540    2  \n",
+              "12 Arginine and proline metabolism                        38    0.9740    4  \n",
+              "13 Valine, leucine and isoleucine degradation             40    1.0200    4  \n",
+              "14 Phenylalanine metabolism                               10    0.2560    2  \n",
+              "15 Galactose metabolism                                   27    0.6920    3  \n",
+              "16 Glycine, serine and threonine metabolism               33    0.8460    3  \n",
+              "17 Neomycin, kanamycin and gentamicin biosynthesis         2    0.0512    1  \n",
+              "18 Histidine metabolism                                   16    0.4100    2  \n",
+              "19 beta-Alanine metabolism                                21    0.5380    2  \n",
+              "20 Pyruvate metabolism                                    22    0.5640    2  \n",
+              "21 Lysine degradation                                     25    0.6410    2  \n",
+              "22 Phosphonate and phosphinate metabolism                  6    0.1540    1  \n",
+              "23 Porphyrin and chlorophyll metabolism                   30    0.7690    2  \n",
+              "24 Ascorbate and aldarate metabolism                       8    0.2050    1  \n",
+              "25 Taurine and hypotaurine metabolism                      8    0.2050    1  \n",
+              "26 Ubiquinone and other terpenoid-quinone biosynthesis     9    0.2310    1  \n",
+              "27 Biotin metabolism                                      10    0.2560    1  \n",
+              "28 Purine metabolism                                      65    1.6700    3  \n",
+              "29 Glycerophospholipid metabolism                         36    0.9220    2  \n",
+              "30 Pyrimidine metabolism                                  39    0.9990    2  \n",
+              "31 Tyrosine metabolism                                    42    1.0800    2  \n",
+              "32 Glycosylphosphatidylinositol (GPI)-anchor biosynthesis 14    0.3590    1  \n",
+              "33 Butanoate metabolism                                   15    0.3840    1  \n",
+              "34 Primary bile acid biosynthesis                         46    1.1800    2  \n",
+              "35 Starch and sucrose metabolism                          18    0.4610    1  \n",
+              "36 Citrate cycle (TCA cycle)                              20    0.5120    1  \n",
+              "37 Fructose and mannose metabolism                        20    0.5120    1  \n",
+              "38 Selenocompound metabolism                              20    0.5120    1  \n",
+              "39 Ether lipid metabolism                                 20    0.5120    1  \n",
+              "40 Propanoate metabolism                                  23    0.5890    1  \n",
+              "41 Glycolysis / Gluconeogenesis                           26    0.6660    1  \n",
+              "42 Phosphatidylinositol signaling system                  28    0.7170    1  \n",
+              "43 Inositol phosphate metabolism                          30    0.7690    1  \n",
+              "44 Cysteine and methionine metabolism                     33    0.8460    1  \n",
+              "45 Tryptophan metabolism                                  41    1.0500    1  \n",
+              "   Raw.p    Holm.p   FDR     \n",
+              "1  1.46e-15 1.22e-13 1.22e-13\n",
+              "2  4.51e-07 3.74e-05 1.89e-05\n",
+              "3  5.34e-06 4.38e-04 1.49e-04\n",
+              "4  4.75e-05 3.85e-03 9.97e-04\n",
+              "5  3.07e-04 2.46e-02 5.16e-03\n",
+              "6  1.08e-03 8.56e-02 1.52e-02\n",
+              "7  3.72e-03 2.90e-01 4.46e-02\n",
+              "8  4.84e-03 3.73e-01 5.09e-02\n",
+              "9  5.72e-03 4.35e-01 5.34e-02\n",
+              "10 7.90e-03 5.93e-01 6.64e-02\n",
+              "11 9.00e-03 6.66e-01 6.87e-02\n",
+              "12 1.45e-02 1.00e+00 1.02e-01\n",
+              "13 1.73e-02 1.00e+00 1.12e-01\n",
+              "14 2.53e-02 1.00e+00 1.52e-01\n",
+              "15 2.97e-02 1.00e+00 1.67e-01\n",
+              "16 4.99e-02 1.00e+00 2.50e-01\n",
+              "17 5.06e-02 1.00e+00 2.50e-01\n",
+              "18 6.12e-02 1.00e+00 2.86e-01\n",
+              "19 9.90e-02 1.00e+00 4.38e-01\n",
+              "20 1.07e-01 1.00e+00 4.50e-01\n",
+              "21 1.33e-01 1.00e+00 5.31e-01\n",
+              "22 1.44e-01 1.00e+00 5.52e-01\n",
+              "23 1.78e-01 1.00e+00 6.31e-01\n",
+              "24 1.88e-01 1.00e+00 6.31e-01\n",
+              "25 1.88e-01 1.00e+00 6.31e-01\n",
+              "26 2.09e-01 1.00e+00 6.75e-01\n",
+              "27 2.29e-01 1.00e+00 6.80e-01\n",
+              "28 2.30e-01 1.00e+00 6.80e-01\n",
+              "29 2.35e-01 1.00e+00 6.80e-01\n",
+              "30 2.64e-01 1.00e+00 7.39e-01\n",
+              "31 2.93e-01 1.00e+00 7.94e-01\n",
+              "32 3.06e-01 1.00e+00 8.03e-01\n",
+              "33 3.24e-01 1.00e+00 8.19e-01\n",
+              "34 3.31e-01 1.00e+00 8.19e-01\n",
+              "35 3.75e-01 1.00e+00 8.77e-01\n",
+              "36 4.07e-01 1.00e+00 8.77e-01\n",
+              "37 4.07e-01 1.00e+00 8.77e-01\n",
+              "38 4.07e-01 1.00e+00 8.77e-01\n",
+              "39 4.07e-01 1.00e+00 8.77e-01\n",
+              "40 4.52e-01 1.00e+00 9.49e-01\n",
+              "41 4.94e-01 1.00e+00 1.00e+00\n",
+              "42 5.20e-01 1.00e+00 1.00e+00\n",
+              "43 5.45e-01 1.00e+00 1.00e+00\n",
+              "44 5.79e-01 1.00e+00 1.00e+00\n",
+              "45 6.60e-01 1.00e+00 1.00e+00"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "msea_res"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 52,
+      "metadata": {
+        "kernel": "R",
+        "scrolled": true
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<table class=\"dataframe\">\n",
+              "<caption>A data.frame: 39 × 7</caption>\n",
+              "<thead>\n",
+              "\t<tr><th scope=col>Query</th><th scope=col>Match</th><th scope=col>HMDB</th><th scope=col>PubChem</th><th scope=col>KEGG</th><th scope=col>SMILES</th><th scope=col>Comment</th></tr>\n",
+              "\t<tr><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
+              "</thead>\n",
+              "<tbody>\n",
+              "\t<tr><td>beta-Alanine               </td><td>Beta-Alanine                           </td><td>HMDB0000056</td><td>    239</td><td>C00099</td><td>C(CN)C(=O)O                                                                                                                      </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Valine                   </td><td>L-Valine                               </td><td>HMDB0000883</td><td>   6287</td><td>C00183</td><td>CC(C)[C@@H](C(=O)O)N                                                                                                             </td><td>1</td></tr>\n",
+              "\t<tr><td>UDP-N-Acetylglucosamine    </td><td>Uridine diphosphate-N-acetylglucosamine</td><td>HMDB0000290</td><td>9547196</td><td>C00043</td><td>CC(=O)N[C@@H]1[C@H]([C@@H]([C@H](O[C@@H]1OP(=O)(O)OP(=O)(O)OC[C@@H]2[C@H]([C@H]([C@@H](O2)N3C=CC(=O)NC3=O)O)O)CO)O)O             </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Tyrosine                 </td><td>L-Tyrosine                             </td><td>HMDB0000158</td><td>   6057</td><td>C00082</td><td>C1=CC(=CC=C1C[C@@H](C(=O)O)N)O                                                                                                   </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Tryptophan               </td><td>L-Tryptophan                           </td><td>HMDB0000929</td><td>   6305</td><td>C00078</td><td>C1=CC=C2C(=C1)C(=CN2)C[C@@H](C(=O)O)N                                                                                            </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Threonine                </td><td>L-Threonine                            </td><td>HMDB0000167</td><td>   6288</td><td>C00188</td><td>C[C@H]([C@@H](C(=O)O)N)O                                                                                                         </td><td>1</td></tr>\n",
+              "\t<tr><td>Taurine                    </td><td>Taurine                                </td><td>HMDB0000251</td><td>   1123</td><td>C00245</td><td>C(CS(=O)(=O)O)N                                                                                                                  </td><td>1</td></tr>\n",
+              "\t<tr><td>sn-Glycero-3-phosphocholine</td><td>Glycerophosphocholine                  </td><td>HMDB0000086</td><td>  71920</td><td>C00670</td><td>C[N+](C)(C)CCOP(=O)([O-])OC[C@H](CO)O                                                                                            </td><td>1</td></tr>\n",
+              "\t<tr><td>Serine                     </td><td>Serine                                 </td><td>HMDB0062263</td><td>   5951</td><td>C00716</td><td>N[C@@H](CO)C(O)=O                                                                                                                </td><td>1</td></tr>\n",
+              "\t<tr><td>Pyroglutamic acid          </td><td>Pyroglutamic acid                      </td><td>HMDB0000267</td><td>   7405</td><td>C01879</td><td>C1CC(=O)N[C@@H]1C(=O)O                                                                                                           </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Proline                  </td><td>L-Proline                              </td><td>HMDB0000162</td><td> 145742</td><td>C00148</td><td>C1C[C@H](NC1)C(=O)O                                                                                                              </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Phenylalanine            </td><td>L-Phenylalanine                        </td><td>HMDB0000159</td><td>   6140</td><td>C00079</td><td>C1=CC=C(C=C1)C[C@@H](C(=O)O)N                                                                                                    </td><td>1</td></tr>\n",
+              "\t<tr><td>Pantothenate               </td><td>Pantothenic acid                       </td><td>HMDB0000210</td><td>   6613</td><td>C00864</td><td>CC(C)(CO)C(C(=O)NCCC(=O)O)O                                                                                                      </td><td>1</td></tr>\n",
+              "\t<tr><td>O-Phosphocholine           </td><td>Phosphorylcholine                      </td><td>HMDB0001565</td><td>   8691</td><td>C00588</td><td>C[N+](C)(C)CCOP(=O)(O)O                                                                                                          </td><td>1</td></tr>\n",
+              "\t<tr><td>NAD                        </td><td>NAD                                    </td><td>HMDB0000902</td><td>   5893</td><td>C00003</td><td>C1=CC(=C[N+](=C1)[C@H]2[C@@H]([C@@H]([C@H](O2)COP(=O)(O)OP(=O)(O)OC[C@@H]3[C@H]([C@H]([C@@H](O3)N4C=NC5=C4N=CN=C5N)O)O)O)O)C(=O)N</td><td>1</td></tr>\n",
+              "\t<tr><td>myo-Inositol               </td><td>myo-Inositol                           </td><td>HMDB0000211</td><td>     NA</td><td>C00137</td><td>O[C@H]1[C@H](O)[C@@H](O)[C@H](O)[C@H](O)[C@@H]1O                                                                                 </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Methionine               </td><td>L-Methionine                           </td><td>HMDB0000696</td><td>   6137</td><td>C00073</td><td>CSCC[C@@H](C(=O)O)N                                                                                                              </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Lysine                   </td><td>L-Lysine                               </td><td>HMDB0000182</td><td>   5962</td><td>C00047</td><td>C(CCN)C[C@@H](C(=O)O)N                                                                                                           </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Leucine                  </td><td>L-Leucine                              </td><td>HMDB0000687</td><td>   6106</td><td>C00123</td><td>CC(C)C[C@@H](C(=O)O)N                                                                                                            </td><td>1</td></tr>\n",
+              "\t<tr><td>Lactate                    </td><td>L-Lactic acid                          </td><td>HMDB0000190</td><td>  61503</td><td>C00186</td><td>C[C@@H](C(=O)O)O                                                                                                                 </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Isoleucine               </td><td>L-Isoleucine                           </td><td>HMDB0000172</td><td>   6306</td><td>C00407</td><td>CC[C@H](C)[C@@H](C(=O)O)N                                                                                                        </td><td>1</td></tr>\n",
+              "\t<tr><td>Glycine                    </td><td>Glycine                                </td><td>HMDB0000123</td><td>    750</td><td>C00037</td><td>C(C(=O)O)N                                                                                                                       </td><td>1</td></tr>\n",
+              "\t<tr><td>Glutathione                </td><td>Glutathione                            </td><td>HMDB0062697</td><td>    745</td><td>C00051</td><td>NC(CCC(O)=NC(CS)C(O)=NCC(O)=O)C(O)=O                                                                                             </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Glutamine                </td><td>L-Glutamine                            </td><td>HMDB0000641</td><td>   5961</td><td>C00064</td><td>C(CC(=O)N)[C@@H](C(=O)O)N                                                                                                        </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Glutamic acid            </td><td>L-Glutamic acid                        </td><td>HMDB0000148</td><td>  33032</td><td>C00025</td><td>C(CC(=O)O)[C@@H](C(=O)O)N                                                                                                        </td><td>1</td></tr>\n",
+              "\t<tr><td>D-Glucose                  </td><td>D-Glucose                              </td><td>HMDB0000122</td><td>   5793</td><td>C00221</td><td>C([C@@H]1[C@H]([C@@H]([C@H](C(O1)O)O)O)O)O                                                                                       </td><td>1</td></tr>\n",
+              "\t<tr><td>D-Glucitol                 </td><td>Sorbitol                               </td><td>HMDB0000247</td><td>   5780</td><td>C00794</td><td>C([C@H]([C@H]([C@@H]([C@H](CO)O)O)O)O)O                                                                                          </td><td>1</td></tr>\n",
+              "\t<tr><td>Fumarate                   </td><td>Fumaric acid                           </td><td>HMDB0000134</td><td> 444972</td><td>C00122</td><td>C(=C/C(=O)O)\\C(=O)O                                                                                                             </td><td>1</td></tr>\n",
+              "\t<tr><td>Formate                    </td><td>Formic acid                            </td><td>HMDB0000142</td><td>    284</td><td>C00058</td><td>C(=O)O                                                                                                                           </td><td>1</td></tr>\n",
+              "\t<tr><td>Creatine phosphate         </td><td>Phosphocreatine                        </td><td>HMDB0001511</td><td>    587</td><td>C02305</td><td>CN(CC(=O)O)C(=NP(=O)(O)O)N                                                                                                       </td><td>1</td></tr>\n",
+              "\t<tr><td>Creatine                   </td><td>Creatine                               </td><td>HMDB0000064</td><td>    586</td><td>C00300</td><td>CN(CC(=O)O)C(=N)N                                                                                                                </td><td>1</td></tr>\n",
+              "\t<tr><td>Adenosine triphosphate     </td><td>Adenosine triphosphate                 </td><td>HMDB0000538</td><td>   5957</td><td>C00002</td><td>C1=NC2=C(C(=N1)N)N=CN2[C@H]3[C@@H]([C@@H]([C@H](O3)COP(=O)(O)OP(=O)(O)OP(=O)(O)O)O)O                                             </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Aspartate                </td><td>L-Aspartic acid                        </td><td>HMDB0000191</td><td>   5960</td><td>C00049</td><td>C([C@@H](C(=O)O)N)C(=O)O                                                                                                         </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Asparagine               </td><td>L-Asparagine                           </td><td>HMDB0000168</td><td>   6267</td><td>C00152</td><td>C([C@@H](C(=O)O)N)C(=O)N                                                                                                         </td><td>1</td></tr>\n",
+              "\t<tr><td>Adenosine monophosphate    </td><td>Adenosine monophosphate                </td><td>HMDB0000045</td><td>   6083</td><td>C00020</td><td>C1=NC2=C(C(=N1)N)N=CN2[C@H]3[C@@H]([C@@H]([C@H](O3)COP(=O)(O)O)O)O                                                               </td><td>1</td></tr>\n",
+              "\t<tr><td>L-Alanine                  </td><td>L-Alanine                              </td><td>HMDB0000161</td><td>   5950</td><td>C00041</td><td>C[C@@H](C(=O)O)N                                                                                                                 </td><td>1</td></tr>\n",
+              "\t<tr><td>2-Oxoisocaproate           </td><td>Ketoleucine                            </td><td>HMDB0000695</td><td>     70</td><td>C00233</td><td>CC(C)CC(=O)C(=O)O                                                                                                                </td><td>1</td></tr>\n",
+              "\t<tr><td>2-Aminoadipate             </td><td>Aminoadipic acid                       </td><td>HMDB0000510</td><td>    469</td><td>C00956</td><td>C(CC(C(=O)O)N)CC(=O)O                                                                                                            </td><td>1</td></tr>\n",
+              "\t<tr><td>1-Methylnicotinamide       </td><td>1-Methylnicotinamide                   </td><td>HMDB0000699</td><td>    457</td><td>C02918</td><td>C[N+]1=CC=CC(=C1)C(=O)N                                                                                                          </td><td>1</td></tr>\n",
+              "</tbody>\n",
+              "</table>\n"
+            ],
+            "text/latex": [
+              "A data.frame: 39 × 7\n",
+              "\\begin{tabular}{lllllll}\n",
+              " Query & Match & HMDB & PubChem & KEGG & SMILES & Comment\\\\\n",
+              " <fct> & <fct> & <fct> & <int> & <fct> & <fct> & <int>\\\\\n",
+              "\\hline\n",
+              "\t beta-Alanine                & Beta-Alanine                            & HMDB0000056 &     239 & C00099 & C(CN)C(=O)O                                                                                                                       & 1\\\\\n",
+              "\t L-Valine                    & L-Valine                                & HMDB0000883 &    6287 & C00183 & CC(C){[}C@@H{]}(C(=O)O)N                                                                                                              & 1\\\\\n",
+              "\t UDP-N-Acetylglucosamine     & Uridine diphosphate-N-acetylglucosamine & HMDB0000290 & 9547196 & C00043 & CC(=O)N{[}C@@H{]}1{[}C@H{]}({[}C@@H{]}({[}C@H{]}(O{[}C@@H{]}1OP(=O)(O)OP(=O)(O)OC{[}C@@H{]}2{[}C@H{]}({[}C@H{]}({[}C@@H{]}(O2)N3C=CC(=O)NC3=O)O)O)CO)O)O              & 1\\\\\n",
+              "\t L-Tyrosine                  & L-Tyrosine                              & HMDB0000158 &    6057 & C00082 & C1=CC(=CC=C1C{[}C@@H{]}(C(=O)O)N)O                                                                                                    & 1\\\\\n",
+              "\t L-Tryptophan                & L-Tryptophan                            & HMDB0000929 &    6305 & C00078 & C1=CC=C2C(=C1)C(=CN2)C{[}C@@H{]}(C(=O)O)N                                                                                             & 1\\\\\n",
+              "\t L-Threonine                 & L-Threonine                             & HMDB0000167 &    6288 & C00188 & C{[}C@H{]}({[}C@@H{]}(C(=O)O)N)O                                                                                                          & 1\\\\\n",
+              "\t Taurine                     & Taurine                                 & HMDB0000251 &    1123 & C00245 & C(CS(=O)(=O)O)N                                                                                                                   & 1\\\\\n",
+              "\t sn-Glycero-3-phosphocholine & Glycerophosphocholine                   & HMDB0000086 &   71920 & C00670 & C{[}N+{]}(C)(C)CCOP(=O)({[}O-{]})OC{[}C@H{]}(CO)O                                                                                             & 1\\\\\n",
+              "\t Serine                      & Serine                                  & HMDB0062263 &    5951 & C00716 & N{[}C@@H{]}(CO)C(O)=O                                                                                                                 & 1\\\\\n",
+              "\t Pyroglutamic acid           & Pyroglutamic acid                       & HMDB0000267 &    7405 & C01879 & C1CC(=O)N{[}C@@H{]}1C(=O)O                                                                                                            & 1\\\\\n",
+              "\t L-Proline                   & L-Proline                               & HMDB0000162 &  145742 & C00148 & C1C{[}C@H{]}(NC1)C(=O)O                                                                                                               & 1\\\\\n",
+              "\t L-Phenylalanine             & L-Phenylalanine                         & HMDB0000159 &    6140 & C00079 & C1=CC=C(C=C1)C{[}C@@H{]}(C(=O)O)N                                                                                                     & 1\\\\\n",
+              "\t Pantothenate                & Pantothenic acid                        & HMDB0000210 &    6613 & C00864 & CC(C)(CO)C(C(=O)NCCC(=O)O)O                                                                                                       & 1\\\\\n",
+              "\t O-Phosphocholine            & Phosphorylcholine                       & HMDB0001565 &    8691 & C00588 & C{[}N+{]}(C)(C)CCOP(=O)(O)O                                                                                                           & 1\\\\\n",
+              "\t NAD                         & NAD                                     & HMDB0000902 &    5893 & C00003 & C1=CC(=C{[}N+{]}(=C1){[}C@H{]}2{[}C@@H{]}({[}C@@H{]}({[}C@H{]}(O2)COP(=O)(O)OP(=O)(O)OC{[}C@@H{]}3{[}C@H{]}({[}C@H{]}({[}C@@H{]}(O3)N4C=NC5=C4N=CN=C5N)O)O)O)O)C(=O)N & 1\\\\\n",
+              "\t myo-Inositol                & myo-Inositol                            & HMDB0000211 &      NA & C00137 & O{[}C@H{]}1{[}C@H{]}(O){[}C@@H{]}(O){[}C@H{]}(O){[}C@H{]}(O){[}C@@H{]}1O                                                                                  & 1\\\\\n",
+              "\t L-Methionine                & L-Methionine                            & HMDB0000696 &    6137 & C00073 & CSCC{[}C@@H{]}(C(=O)O)N                                                                                                               & 1\\\\\n",
+              "\t L-Lysine                    & L-Lysine                                & HMDB0000182 &    5962 & C00047 & C(CCN)C{[}C@@H{]}(C(=O)O)N                                                                                                            & 1\\\\\n",
+              "\t L-Leucine                   & L-Leucine                               & HMDB0000687 &    6106 & C00123 & CC(C)C{[}C@@H{]}(C(=O)O)N                                                                                                             & 1\\\\\n",
+              "\t Lactate                     & L-Lactic acid                           & HMDB0000190 &   61503 & C00186 & C{[}C@@H{]}(C(=O)O)O                                                                                                                  & 1\\\\\n",
+              "\t L-Isoleucine                & L-Isoleucine                            & HMDB0000172 &    6306 & C00407 & CC{[}C@H{]}(C){[}C@@H{]}(C(=O)O)N                                                                                                         & 1\\\\\n",
+              "\t Glycine                     & Glycine                                 & HMDB0000123 &     750 & C00037 & C(C(=O)O)N                                                                                                                        & 1\\\\\n",
+              "\t Glutathione                 & Glutathione                             & HMDB0062697 &     745 & C00051 & NC(CCC(O)=NC(CS)C(O)=NCC(O)=O)C(O)=O                                                                                              & 1\\\\\n",
+              "\t L-Glutamine                 & L-Glutamine                             & HMDB0000641 &    5961 & C00064 & C(CC(=O)N){[}C@@H{]}(C(=O)O)N                                                                                                         & 1\\\\\n",
+              "\t L-Glutamic acid             & L-Glutamic acid                         & HMDB0000148 &   33032 & C00025 & C(CC(=O)O){[}C@@H{]}(C(=O)O)N                                                                                                         & 1\\\\\n",
+              "\t D-Glucose                   & D-Glucose                               & HMDB0000122 &    5793 & C00221 & C({[}C@@H{]}1{[}C@H{]}({[}C@@H{]}({[}C@H{]}(C(O1)O)O)O)O)O                                                                                        & 1\\\\\n",
+              "\t D-Glucitol                  & Sorbitol                                & HMDB0000247 &    5780 & C00794 & C({[}C@H{]}({[}C@H{]}({[}C@@H{]}({[}C@H{]}(CO)O)O)O)O)O                                                                                           & 1\\\\\n",
+              "\t Fumarate                    & Fumaric acid                            & HMDB0000134 &  444972 & C00122 & C(=C/C(=O)O)\\textbackslash{}C(=O)O                                                                                                              & 1\\\\\n",
+              "\t Formate                     & Formic acid                             & HMDB0000142 &     284 & C00058 & C(=O)O                                                                                                                            & 1\\\\\n",
+              "\t Creatine phosphate          & Phosphocreatine                         & HMDB0001511 &     587 & C02305 & CN(CC(=O)O)C(=NP(=O)(O)O)N                                                                                                        & 1\\\\\n",
+              "\t Creatine                    & Creatine                                & HMDB0000064 &     586 & C00300 & CN(CC(=O)O)C(=N)N                                                                                                                 & 1\\\\\n",
+              "\t Adenosine triphosphate      & Adenosine triphosphate                  & HMDB0000538 &    5957 & C00002 & C1=NC2=C(C(=N1)N)N=CN2{[}C@H{]}3{[}C@@H{]}({[}C@@H{]}({[}C@H{]}(O3)COP(=O)(O)OP(=O)(O)OP(=O)(O)O)O)O                                              & 1\\\\\n",
+              "\t L-Aspartate                 & L-Aspartic acid                         & HMDB0000191 &    5960 & C00049 & C({[}C@@H{]}(C(=O)O)N)C(=O)O                                                                                                          & 1\\\\\n",
+              "\t L-Asparagine                & L-Asparagine                            & HMDB0000168 &    6267 & C00152 & C({[}C@@H{]}(C(=O)O)N)C(=O)N                                                                                                          & 1\\\\\n",
+              "\t Adenosine monophosphate     & Adenosine monophosphate                 & HMDB0000045 &    6083 & C00020 & C1=NC2=C(C(=N1)N)N=CN2{[}C@H{]}3{[}C@@H{]}({[}C@@H{]}({[}C@H{]}(O3)COP(=O)(O)O)O)O                                                                & 1\\\\\n",
+              "\t L-Alanine                   & L-Alanine                               & HMDB0000161 &    5950 & C00041 & C{[}C@@H{]}(C(=O)O)N                                                                                                                  & 1\\\\\n",
+              "\t 2-Oxoisocaproate            & Ketoleucine                             & HMDB0000695 &      70 & C00233 & CC(C)CC(=O)C(=O)O                                                                                                                 & 1\\\\\n",
+              "\t 2-Aminoadipate              & Aminoadipic acid                        & HMDB0000510 &     469 & C00956 & C(CC(C(=O)O)N)CC(=O)O                                                                                                             & 1\\\\\n",
+              "\t 1-Methylnicotinamide        & 1-Methylnicotinamide                    & HMDB0000699 &     457 & C02918 & C{[}N+{]}1=CC=CC(=C1)C(=O)N                                                                                                           & 1\\\\\n",
+              "\\end{tabular}\n"
+            ],
+            "text/markdown": [
+              "\n",
+              "A data.frame: 39 × 7\n",
+              "\n",
+              "| Query &lt;fct&gt; | Match &lt;fct&gt; | HMDB &lt;fct&gt; | PubChem &lt;int&gt; | KEGG &lt;fct&gt; | SMILES &lt;fct&gt; | Comment &lt;int&gt; |\n",
+              "|---|---|---|---|---|---|---|\n",
+              "| beta-Alanine                | Beta-Alanine                            | HMDB0000056 |     239 | C00099 | C(CN)C(=O)O                                                                                                                       | 1 |\n",
+              "| L-Valine                    | L-Valine                                | HMDB0000883 |    6287 | C00183 | CC(C)[C@@H](C(=O)O)N                                                                                                              | 1 |\n",
+              "| UDP-N-Acetylglucosamine     | Uridine diphosphate-N-acetylglucosamine | HMDB0000290 | 9547196 | C00043 | CC(=O)N[C@@H]1[C@H]([C@@H]([C@H](O[C@@H]1OP(=O)(O)OP(=O)(O)OC[C@@H]2[C@H]([C@H]([C@@H](O2)N3C=CC(=O)NC3=O)O)O)CO)O)O              | 1 |\n",
+              "| L-Tyrosine                  | L-Tyrosine                              | HMDB0000158 |    6057 | C00082 | C1=CC(=CC=C1C[C@@H](C(=O)O)N)O                                                                                                    | 1 |\n",
+              "| L-Tryptophan                | L-Tryptophan                            | HMDB0000929 |    6305 | C00078 | C1=CC=C2C(=C1)C(=CN2)C[C@@H](C(=O)O)N                                                                                             | 1 |\n",
+              "| L-Threonine                 | L-Threonine                             | HMDB0000167 |    6288 | C00188 | C[C@H]([C@@H](C(=O)O)N)O                                                                                                          | 1 |\n",
+              "| Taurine                     | Taurine                                 | HMDB0000251 |    1123 | C00245 | C(CS(=O)(=O)O)N                                                                                                                   | 1 |\n",
+              "| sn-Glycero-3-phosphocholine | Glycerophosphocholine                   | HMDB0000086 |   71920 | C00670 | C[N+](C)(C)CCOP(=O)([O-])OC[C@H](CO)O                                                                                             | 1 |\n",
+              "| Serine                      | Serine                                  | HMDB0062263 |    5951 | C00716 | N[C@@H](CO)C(O)=O                                                                                                                 | 1 |\n",
+              "| Pyroglutamic acid           | Pyroglutamic acid                       | HMDB0000267 |    7405 | C01879 | C1CC(=O)N[C@@H]1C(=O)O                                                                                                            | 1 |\n",
+              "| L-Proline                   | L-Proline                               | HMDB0000162 |  145742 | C00148 | C1C[C@H](NC1)C(=O)O                                                                                                               | 1 |\n",
+              "| L-Phenylalanine             | L-Phenylalanine                         | HMDB0000159 |    6140 | C00079 | C1=CC=C(C=C1)C[C@@H](C(=O)O)N                                                                                                     | 1 |\n",
+              "| Pantothenate                | Pantothenic acid                        | HMDB0000210 |    6613 | C00864 | CC(C)(CO)C(C(=O)NCCC(=O)O)O                                                                                                       | 1 |\n",
+              "| O-Phosphocholine            | Phosphorylcholine                       | HMDB0001565 |    8691 | C00588 | C[N+](C)(C)CCOP(=O)(O)O                                                                                                           | 1 |\n",
+              "| NAD                         | NAD                                     | HMDB0000902 |    5893 | C00003 | C1=CC(=C[N+](=C1)[C@H]2[C@@H]([C@@H]([C@H](O2)COP(=O)(O)OP(=O)(O)OC[C@@H]3[C@H]([C@H]([C@@H](O3)N4C=NC5=C4N=CN=C5N)O)O)O)O)C(=O)N | 1 |\n",
+              "| myo-Inositol                | myo-Inositol                            | HMDB0000211 |      NA | C00137 | O[C@H]1[C@H](O)[C@@H](O)[C@H](O)[C@H](O)[C@@H]1O                                                                                  | 1 |\n",
+              "| L-Methionine                | L-Methionine                            | HMDB0000696 |    6137 | C00073 | CSCC[C@@H](C(=O)O)N                                                                                                               | 1 |\n",
+              "| L-Lysine                    | L-Lysine                                | HMDB0000182 |    5962 | C00047 | C(CCN)C[C@@H](C(=O)O)N                                                                                                            | 1 |\n",
+              "| L-Leucine                   | L-Leucine                               | HMDB0000687 |    6106 | C00123 | CC(C)C[C@@H](C(=O)O)N                                                                                                             | 1 |\n",
+              "| Lactate                     | L-Lactic acid                           | HMDB0000190 |   61503 | C00186 | C[C@@H](C(=O)O)O                                                                                                                  | 1 |\n",
+              "| L-Isoleucine                | L-Isoleucine                            | HMDB0000172 |    6306 | C00407 | CC[C@H](C)[C@@H](C(=O)O)N                                                                                                         | 1 |\n",
+              "| Glycine                     | Glycine                                 | HMDB0000123 |     750 | C00037 | C(C(=O)O)N                                                                                                                        | 1 |\n",
+              "| Glutathione                 | Glutathione                             | HMDB0062697 |     745 | C00051 | NC(CCC(O)=NC(CS)C(O)=NCC(O)=O)C(O)=O                                                                                              | 1 |\n",
+              "| L-Glutamine                 | L-Glutamine                             | HMDB0000641 |    5961 | C00064 | C(CC(=O)N)[C@@H](C(=O)O)N                                                                                                         | 1 |\n",
+              "| L-Glutamic acid             | L-Glutamic acid                         | HMDB0000148 |   33032 | C00025 | C(CC(=O)O)[C@@H](C(=O)O)N                                                                                                         | 1 |\n",
+              "| D-Glucose                   | D-Glucose                               | HMDB0000122 |    5793 | C00221 | C([C@@H]1[C@H]([C@@H]([C@H](C(O1)O)O)O)O)O                                                                                        | 1 |\n",
+              "| D-Glucitol                  | Sorbitol                                | HMDB0000247 |    5780 | C00794 | C([C@H]([C@H]([C@@H]([C@H](CO)O)O)O)O)O                                                                                           | 1 |\n",
+              "| Fumarate                    | Fumaric acid                            | HMDB0000134 |  444972 | C00122 | C(=C/C(=O)O)\\C(=O)O                                                                                                              | 1 |\n",
+              "| Formate                     | Formic acid                             | HMDB0000142 |     284 | C00058 | C(=O)O                                                                                                                            | 1 |\n",
+              "| Creatine phosphate          | Phosphocreatine                         | HMDB0001511 |     587 | C02305 | CN(CC(=O)O)C(=NP(=O)(O)O)N                                                                                                        | 1 |\n",
+              "| Creatine                    | Creatine                                | HMDB0000064 |     586 | C00300 | CN(CC(=O)O)C(=N)N                                                                                                                 | 1 |\n",
+              "| Adenosine triphosphate      | Adenosine triphosphate                  | HMDB0000538 |    5957 | C00002 | C1=NC2=C(C(=N1)N)N=CN2[C@H]3[C@@H]([C@@H]([C@H](O3)COP(=O)(O)OP(=O)(O)OP(=O)(O)O)O)O                                              | 1 |\n",
+              "| L-Aspartate                 | L-Aspartic acid                         | HMDB0000191 |    5960 | C00049 | C([C@@H](C(=O)O)N)C(=O)O                                                                                                          | 1 |\n",
+              "| L-Asparagine                | L-Asparagine                            | HMDB0000168 |    6267 | C00152 | C([C@@H](C(=O)O)N)C(=O)N                                                                                                          | 1 |\n",
+              "| Adenosine monophosphate     | Adenosine monophosphate                 | HMDB0000045 |    6083 | C00020 | C1=NC2=C(C(=N1)N)N=CN2[C@H]3[C@@H]([C@@H]([C@H](O3)COP(=O)(O)O)O)O                                                                | 1 |\n",
+              "| L-Alanine                   | L-Alanine                               | HMDB0000161 |    5950 | C00041 | C[C@@H](C(=O)O)N                                                                                                                  | 1 |\n",
+              "| 2-Oxoisocaproate            | Ketoleucine                             | HMDB0000695 |      70 | C00233 | CC(C)CC(=O)C(=O)O                                                                                                                 | 1 |\n",
+              "| 2-Aminoadipate              | Aminoadipic acid                        | HMDB0000510 |     469 | C00956 | C(CC(C(=O)O)N)CC(=O)O                                                                                                             | 1 |\n",
+              "| 1-Methylnicotinamide        | 1-Methylnicotinamide                    | HMDB0000699 |     457 | C02918 | C[N+]1=CC=CC(=C1)C(=O)N                                                                                                           | 1 |\n",
+              "\n"
+            ],
+            "text/plain": [
+              "   Query                       Match                                  \n",
+              "1  beta-Alanine                Beta-Alanine                           \n",
+              "2  L-Valine                    L-Valine                               \n",
+              "3  UDP-N-Acetylglucosamine     Uridine diphosphate-N-acetylglucosamine\n",
+              "4  L-Tyrosine                  L-Tyrosine                             \n",
+              "5  L-Tryptophan                L-Tryptophan                           \n",
+              "6  L-Threonine                 L-Threonine                            \n",
+              "7  Taurine                     Taurine                                \n",
+              "8  sn-Glycero-3-phosphocholine Glycerophosphocholine                  \n",
+              "9  Serine                      Serine                                 \n",
+              "10 Pyroglutamic acid           Pyroglutamic acid                      \n",
+              "11 L-Proline                   L-Proline                              \n",
+              "12 L-Phenylalanine             L-Phenylalanine                        \n",
+              "13 Pantothenate                Pantothenic acid                       \n",
+              "14 O-Phosphocholine            Phosphorylcholine                      \n",
+              "15 NAD                         NAD                                    \n",
+              "16 myo-Inositol                myo-Inositol                           \n",
+              "17 L-Methionine                L-Methionine                           \n",
+              "18 L-Lysine                    L-Lysine                               \n",
+              "19 L-Leucine                   L-Leucine                              \n",
+              "20 Lactate                     L-Lactic acid                          \n",
+              "21 L-Isoleucine                L-Isoleucine                           \n",
+              "22 Glycine                     Glycine                                \n",
+              "23 Glutathione                 Glutathione                            \n",
+              "24 L-Glutamine                 L-Glutamine                            \n",
+              "25 L-Glutamic acid             L-Glutamic acid                        \n",
+              "26 D-Glucose                   D-Glucose                              \n",
+              "27 D-Glucitol                  Sorbitol                               \n",
+              "28 Fumarate                    Fumaric acid                           \n",
+              "29 Formate                     Formic acid                            \n",
+              "30 Creatine phosphate          Phosphocreatine                        \n",
+              "31 Creatine                    Creatine                               \n",
+              "32 Adenosine triphosphate      Adenosine triphosphate                 \n",
+              "33 L-Aspartate                 L-Aspartic acid                        \n",
+              "34 L-Asparagine                L-Asparagine                           \n",
+              "35 Adenosine monophosphate     Adenosine monophosphate                \n",
+              "36 L-Alanine                   L-Alanine                              \n",
+              "37 2-Oxoisocaproate            Ketoleucine                            \n",
+              "38 2-Aminoadipate              Aminoadipic acid                       \n",
+              "39 1-Methylnicotinamide        1-Methylnicotinamide                   \n",
+              "   HMDB        PubChem KEGG  \n",
+              "1  HMDB0000056     239 C00099\n",
+              "2  HMDB0000883    6287 C00183\n",
+              "3  HMDB0000290 9547196 C00043\n",
+              "4  HMDB0000158    6057 C00082\n",
+              "5  HMDB0000929    6305 C00078\n",
+              "6  HMDB0000167    6288 C00188\n",
+              "7  HMDB0000251    1123 C00245\n",
+              "8  HMDB0000086   71920 C00670\n",
+              "9  HMDB0062263    5951 C00716\n",
+              "10 HMDB0000267    7405 C01879\n",
+              "11 HMDB0000162  145742 C00148\n",
+              "12 HMDB0000159    6140 C00079\n",
+              "13 HMDB0000210    6613 C00864\n",
+              "14 HMDB0001565    8691 C00588\n",
+              "15 HMDB0000902    5893 C00003\n",
+              "16 HMDB0000211      NA C00137\n",
+              "17 HMDB0000696    6137 C00073\n",
+              "18 HMDB0000182    5962 C00047\n",
+              "19 HMDB0000687    6106 C00123\n",
+              "20 HMDB0000190   61503 C00186\n",
+              "21 HMDB0000172    6306 C00407\n",
+              "22 HMDB0000123     750 C00037\n",
+              "23 HMDB0062697     745 C00051\n",
+              "24 HMDB0000641    5961 C00064\n",
+              "25 HMDB0000148   33032 C00025\n",
+              "26 HMDB0000122    5793 C00221\n",
+              "27 HMDB0000247    5780 C00794\n",
+              "28 HMDB0000134  444972 C00122\n",
+              "29 HMDB0000142     284 C00058\n",
+              "30 HMDB0001511     587 C02305\n",
+              "31 HMDB0000064     586 C00300\n",
+              "32 HMDB0000538    5957 C00002\n",
+              "33 HMDB0000191    5960 C00049\n",
+              "34 HMDB0000168    6267 C00152\n",
+              "35 HMDB0000045    6083 C00020\n",
+              "36 HMDB0000161    5950 C00041\n",
+              "37 HMDB0000695      70 C00233\n",
+              "38 HMDB0000510     469 C00956\n",
+              "39 HMDB0000699     457 C02918\n",
+              "   SMILES                                                                                                                           \n",
+              "1  C(CN)C(=O)O                                                                                                                      \n",
+              "2  CC(C)[C@@H](C(=O)O)N                                                                                                             \n",
+              "3  CC(=O)N[C@@H]1[C@H]([C@@H]([C@H](O[C@@H]1OP(=O)(O)OP(=O)(O)OC[C@@H]2[C@H]([C@H]([C@@H](O2)N3C=CC(=O)NC3=O)O)O)CO)O)O             \n",
+              "4  C1=CC(=CC=C1C[C@@H](C(=O)O)N)O                                                                                                   \n",
+              "5  C1=CC=C2C(=C1)C(=CN2)C[C@@H](C(=O)O)N                                                                                            \n",
+              "6  C[C@H]([C@@H](C(=O)O)N)O                                                                                                         \n",
+              "7  C(CS(=O)(=O)O)N                                                                                                                  \n",
+              "8  C[N+](C)(C)CCOP(=O)([O-])OC[C@H](CO)O                                                                                            \n",
+              "9  N[C@@H](CO)C(O)=O                                                                                                                \n",
+              "10 C1CC(=O)N[C@@H]1C(=O)O                                                                                                           \n",
+              "11 C1C[C@H](NC1)C(=O)O                                                                                                              \n",
+              "12 C1=CC=C(C=C1)C[C@@H](C(=O)O)N                                                                                                    \n",
+              "13 CC(C)(CO)C(C(=O)NCCC(=O)O)O                                                                                                      \n",
+              "14 C[N+](C)(C)CCOP(=O)(O)O                                                                                                          \n",
+              "15 C1=CC(=C[N+](=C1)[C@H]2[C@@H]([C@@H]([C@H](O2)COP(=O)(O)OP(=O)(O)OC[C@@H]3[C@H]([C@H]([C@@H](O3)N4C=NC5=C4N=CN=C5N)O)O)O)O)C(=O)N\n",
+              "16 O[C@H]1[C@H](O)[C@@H](O)[C@H](O)[C@H](O)[C@@H]1O                                                                                 \n",
+              "17 CSCC[C@@H](C(=O)O)N                                                                                                              \n",
+              "18 C(CCN)C[C@@H](C(=O)O)N                                                                                                           \n",
+              "19 CC(C)C[C@@H](C(=O)O)N                                                                                                            \n",
+              "20 C[C@@H](C(=O)O)O                                                                                                                 \n",
+              "21 CC[C@H](C)[C@@H](C(=O)O)N                                                                                                        \n",
+              "22 C(C(=O)O)N                                                                                                                       \n",
+              "23 NC(CCC(O)=NC(CS)C(O)=NCC(O)=O)C(O)=O                                                                                             \n",
+              "24 C(CC(=O)N)[C@@H](C(=O)O)N                                                                                                        \n",
+              "25 C(CC(=O)O)[C@@H](C(=O)O)N                                                                                                        \n",
+              "26 C([C@@H]1[C@H]([C@@H]([C@H](C(O1)O)O)O)O)O                                                                                       \n",
+              "27 C([C@H]([C@H]([C@@H]([C@H](CO)O)O)O)O)O                                                                                          \n",
+              "28 C(=C/C(=O)O)\\\\C(=O)O                                                                                                             \n",
+              "29 C(=O)O                                                                                                                           \n",
+              "30 CN(CC(=O)O)C(=NP(=O)(O)O)N                                                                                                       \n",
+              "31 CN(CC(=O)O)C(=N)N                                                                                                                \n",
+              "32 C1=NC2=C(C(=N1)N)N=CN2[C@H]3[C@@H]([C@@H]([C@H](O3)COP(=O)(O)OP(=O)(O)OP(=O)(O)O)O)O                                             \n",
+              "33 C([C@@H](C(=O)O)N)C(=O)O                                                                                                         \n",
+              "34 C([C@@H](C(=O)O)N)C(=O)N                                                                                                         \n",
+              "35 C1=NC2=C(C(=N1)N)N=CN2[C@H]3[C@@H]([C@@H]([C@H](O3)COP(=O)(O)O)O)O                                                               \n",
+              "36 C[C@@H](C(=O)O)N                                                                                                                 \n",
+              "37 CC(C)CC(=O)C(=O)O                                                                                                                \n",
+              "38 C(CC(C(=O)O)N)CC(=O)O                                                                                                            \n",
+              "39 C[N+]1=CC=CC(=C1)C(=O)N                                                                                                          \n",
+              "   Comment\n",
+              "1  1      \n",
+              "2  1      \n",
+              "3  1      \n",
+              "4  1      \n",
+              "5  1      \n",
+              "6  1      \n",
+              "7  1      \n",
+              "8  1      \n",
+              "9  1      \n",
+              "10 1      \n",
+              "11 1      \n",
+              "12 1      \n",
+              "13 1      \n",
+              "14 1      \n",
+              "15 1      \n",
+              "16 1      \n",
+              "17 1      \n",
+              "18 1      \n",
+              "19 1      \n",
+              "20 1      \n",
+              "21 1      \n",
+              "22 1      \n",
+              "23 1      \n",
+              "24 1      \n",
+              "25 1      \n",
+              "26 1      \n",
+              "27 1      \n",
+              "28 1      \n",
+              "29 1      \n",
+              "30 1      \n",
+              "31 1      \n",
+              "32 1      \n",
+              "33 1      \n",
+              "34 1      \n",
+              "35 1      \n",
+              "36 1      \n",
+              "37 1      \n",
+              "38 1      \n",
+              "39 1      "
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "name_map"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "kernel": "R"
+      },
+      "source": [
+        "### Visualising differential expression in KEGG pathway\n",
+        "- Requires differential analysis results\n",
+        "- Requires MSEA ORA results (Metabolite name to ID mapping matrix)\n",
+        "- Reference - https://bioconductor.org/packages/release/bioc/vignettes/pathview/inst/doc/pathview.pdf"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 88,
+      "metadata": {
+        "kernel": "R"
+      },
+      "outputs": [],
+      "source": [
+        "view_in_pathway <- function(diff_exp_matrix,name_map,pathway_name) {\n",
+        "    library(KEGGREST)\n",
+        "    library(pathview)\n",
+        "    path_n_id <- keggFind('pathway',pathway_name)\n",
+        "    if (identical(path_n_id,character(0))) {\n",
+        "        return('Pathway ID not found')\n",
+        "    }\n",
+        "    path_id <- substr(names(path_n_id),9,nchar(names(path_n_id)))\n",
+        "    metabolites <- c()\n",
+        "    for (compound in rownames(diff_exp_matrix)){\n",
+        "        metabolites<- c(metabolites, strsplit(compound,'_')[[1]][1])\n",
+        "    }\n",
+        "    diff_exp_matrix$metabolite <- metabolites\n",
+        "    diff_exp_matrix2 <- merge(diff_exp_matrix, name_map, by.x = \"metabolite\", by.y = \"Query\")\n",
+        "    compound_data <- diff_exp_matrix2$logFC\n",
+        "    names(compound_data) <- diff_exp_matrix2$KEGG\n",
+        "    pv.out <- pathview(cpd.data = compound_data,pathway.id = path_id, species = \"hsa\",\n",
+        "                   out.suffix = gsub(\" \",\"_\",pathway_name), keys.align = \"y\", kegg.native = T, key.pos = 'topright')\n",
+        "    str(pv.out)\n",
+        "    print('Image file saved in the working directory')\n",
+        "    file_name <- paste('hsa',path_id,'.',gsub(\" \",\"_\",pathway_name),'.png',sep=\"\")\n",
+        "    img <- readPNG(file_name)\n",
+        "    grid::grid.raster(img)\n",
+        "}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 96,
+      "metadata": {
+        "kernel": "R"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "Info: Downloading xml files for hsa00770, 1/1 pathways..\n",
+            "\n",
+            "Info: Downloading png files for hsa00770, 1/1 pathways..\n",
+            "\n",
+            "'select()' returned 1:1 mapping between keys and columns\n",
+            "\n",
+            "Info: Working in directory /import\n",
+            "\n",
+            "Info: Writing image file hsa00770.Pantothenate_and_CoA_biosynthesis.png\n",
+            "\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "List of 2\n",
+            " $ plot.data.gene:'data.frame':\t16 obs. of  10 variables:\n",
+            "  ..$ kegg.names: chr [1:16] \"80347\" \"5167\" \"53354\" \"60490\" ...\n",
+            "  ..$ labels    : chr [1:16] \"COASY\" \"ENPP1\" \"PANK1\" \"PPCDC\" ...\n",
+            "  ..$ all.mapped: chr [1:16] \"\" \"\" \"\" \"\" ...\n",
+            "  ..$ type      : chr [1:16] \"gene\" \"gene\" \"gene\" \"gene\" ...\n",
+            "  ..$ x         : num [1:16] 701 646 561 622 560 519 273 186 100 445 ...\n",
+            "  ..$ y         : num [1:16] 579 540 471 445 417 339 503 502 513 432 ...\n",
+            "  ..$ width     : num [1:16] 46 46 46 46 46 46 46 46 46 46 ...\n",
+            "  ..$ height    : num [1:16] 17 17 17 17 17 17 17 17 17 17 ...\n",
+            "  ..$ mol.data  : num [1:16] NA NA NA NA NA NA NA NA NA NA ...\n",
+            "  ..$ mol.col   : Factor w/ 1 level \"#FFFFFF\": 1 1 1 1 1 1 1 1 1 1 ...\n",
+            " $ plot.data.cpd :'data.frame':\t30 obs. of  10 variables:\n",
+            "  ..$ kegg.names: chr [1:30] \"C03688\" \"C00022\" \"C04272\" \"C00141\" ...\n",
+            "  ..$ labels    : chr [1:30] \"C03688\" \"C00022\" \"C04272\" \"C00141\" ...\n",
+            "  ..$ all.mapped: chr [1:30] \"\" \"\" \"\" \"\" ...\n",
+            "  ..$ type      : chr [1:30] \"compound\" \"compound\" \"compound\" \"compound\" ...\n",
+            "  ..$ x         : num [1:30] 740 173 478 478 664 298 298 444 691 621 ...\n",
+            "  ..$ y         : num [1:30] 560 129 129 195 195 195 338 338 358 416 ...\n",
+            "  ..$ width     : num [1:30] 8 8 8 8 8 8 8 8 8 8 ...\n",
+            "  ..$ height    : num [1:30] 8 8 8 8 8 8 8 8 8 8 ...\n",
+            "  ..$ mol.data  : num [1:30] NA NA NA NA 219 ...\n",
+            "  ..$ mol.col   : Factor w/ 3 levels \"#0000FF\",\"#FFFF00\",..: 3 3 3 3 2 3 3 1 3 3 ...\n",
+            "[1] \"Image file saved in the working directory\"\n"
+          ]
+        },
+        {
+          "data": {
+            "image/png": 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CDg8Xg8Hk/4c4pyuVyhUMhkMkEQpP+9poiiOHHixJkzZ9bW1ra0tLS2ttbU1OzZ\nsycvLy8nJ0er1SqVSp/P193d3dTUVFZWduzYscbGxmAwmJ2dPW/ePIvFMugzu9cUn88XvmiJ\nNMbCh6Lf7/d6vQMHniiKwjU56q58BNAYZRaL5aGHHho/fvyGDRumT5/+//7f/0tISAgvUFNT\n89vf/ra8vHzt2rWRPoudlZX1/e9/PyMj49lnnx2mWEFBwfjx43/1q1/V1tauWrXq29/+thTa\nCoKQl5e3du1a6dH+F1544U9/+tPdd98tTd/bt2/fhg0bQjsJBALbtm3bsWPHd77znccee6xf\nFX/4wx/WrVu3du3a8ABasnz58ieeeEIQhMbGxg0bNjQ1NX3/+98vLCwUBOHVV1+tqakRBEGn\n0919990TJ0589tlnfT7f6tWrCwsLw3sjPj7+vvvuy8nJefbZZxMTE9euXZuXlyeK4i233DJ1\n6tRnn322oqLioYceWrZsWXjVPp/vpz/96a5duy6xr4YpPwyz2XzfffcVFRUJgvD+++8/++yz\nixYtWrt2rVqtttvtzz77rHTsU6ZM+eEPf5ienn7mzJlQX4WTto2uDZfCarWuXbv297//vdTO\noaxYsSIvL++nP/3pBx98MNTxhpcvKyv7zW9+U1NTk5OTcykBdElJyYsvvvjII488//zzoQ/3\n7t3729/+9sSJExdd+OWyGeb81tTU/OY3vzl27NjAa1+6b2RlZT377LPSfSMnJye8gPT0g06n\ne/TRR1NTU8N/dfbs2Zdeeunw4cNr164NBdA+n2/Q63f79u1PPfVUc3Nz+F8kA9scWoUmKyur\nuLhYaph0fi0WS/j1O0xXDLqt9Je6dLzS9bt169bwvpLuG52dncL/HZNFRUXFxcX9lscJXb8n\nT54MXb+iKPart9/A27NnT3jLR6uvBj1HXV1dL7300j/+8Y/29vakpKRhugsAAABXIK/X63K5\nQnGzx+NxuVwejyf0ic/n6+vrczqdvb29oa2USqVOp7tmQ0BRFKdMmdLX17dnz57Tp087nc7q\n6uo//elPt9xyizSDJC4uzul01tXVffLJJ3v27KmpqbHb7TKZbMqUKStWrLiUlRWvGtLAC/3Y\n19c3cOC5XK7e3t7wKY8qlUoul4/iSp4YRQTQGGUqlSo1NTU1NVWlUhkMhvHjx48bNy68QEtL\nS0dHhyiK4ZFZX1/fvn37jh07Ji3N8eGHHzY3Ny9evLjfdD+NRpOWlpaSktLXJjYAACAASURB\nVCKKYmVl5a9//evFixfPnTu3XxuMRqPRaJSC1MTERCluTklJufPOOw0GQ15entQks9ksl8uT\nkpKkqMvj8dx///3p6ekajaa0tPTTTz/1+Xw33njjzJkz+2VhgiDMmzevq6vr5MmTf/nLXxYt\nWiTNoc7NzX3ooYcWLlwolRdFUa/Xq9XqtLQ06ZPly5c7HI7CwkKFQpGUlJSRkaHVan0+X0ZG\nRr+1laU3D0iN0ev1WVlZUpulgzIajUqlMjU1tV/D/H7/l7/85czMzIkTJ15KX4WrqKjYt2+f\nQqG49957L1y4EH68ITKZbMmSJXFxcdddd53UJKlek8k0YcIEjUbT29u7atWqWbNmZWVlabVa\n6XjlcrnZbB7YtwsXLnzwwQenT58+Ws8ctbe379u3r6am5sYbb9RoNH/+85/nzp173XXX9Sum\n1+ulFxbLZLKDBw9u2bJl0aJF06dP71fMbDYbDAaTySSdo0GPN7y8x+O54YYbenp6XnvttUHr\nvaja2tq9e/c2NzcXFRUVFBSE91hXV9eNN94oiuK+ffsi3W24/fv3Hzp0KDU19eabby4vL3e7\n3YsWLep35Y6QTqfT6XSDnt+Wlpb29nbp2/5+Ww28b4S+COnu7t67d29VVdWECROmTJmSm5vb\nr2EajWbZsmU2m+2f//xnfX196L7R3t7e2NhoMBjC2zBnzpyioqI9e/acOXNmJG222+379++3\n2+133nnnwoULJ02aJE1GCF2/Npvt9ddfH+p+lZ6ePvBauOGGGyZOnDh//nypon71ms3mO++8\n0263WyyW8DGZkJAw8Ouuoa7fgfWGb+V2u0P3OumTUekrt9vd2NhosVjCb029vb2LFi2y2+2X\nOEQBAABwmQWDwWAwWFVVVVJSEpqL6vf7e3p6Tp06FXpusra29m9/+5vRaAyfYjJp0qSlS5fG\nx8dL01GvNXK5XHr31ZIlS3w+X2lpaVdX1/HjxxUKRWtrq9ls1ul0Lperubn5+PHjn332WVdX\nV3Jy8qRJkwoKCqZMmRKaVXNtkgbe0aNHd+/eHfrQ5/P19PTU1NSEvueoqqp6++23TSZT+L/C\npk+fvmTJEqPReG0OvCscpwRXBKfT+dZbbx0+fPiZZ54RRfHJJ588fvz47Nmzh3nx6759+w4e\nPPj0008PDFUHlZ2d/b3vfU8mkw11J5o8efLq1atlMplSqSwpKXn66ac3bNjw6KOPDvrwyy23\n3FJYWPjUU09t3bpVepeXIAiFhYUzZ84cJjZdtGjR/PnzY3crlMvlq1at+spXvtKvzZH2Vb9t\n165du2bNmh//+Mf9jvei9YZIM0YDgcBIjt1qtU6bNi307Myla2pqevnllz0ez4YNGyorK598\n8slvfetbwwfBO3fuLC0tlWbjXmLt0rh6/fXXR1LvoEpLS59++ul7771348aN/fpE6qu4uLiD\nBw9eSiN37NixZcuW9evXz5kzZ926dXv27MnJyYkugB51drv9tddeq6+v/5//+Z+FCxcOHBXS\nbOKPPvroqaeeuuh9Q7oG161bFx6qDkOa1ZuUlLR+/fqJEycOrP3kyZMvvPBCS0vL8PWGXPRa\nkJ5+CAaDsXvsbsqUKaF73TDFIu2rQUnHO3Xq1La2tqh3AgAAgMsvGAwGAoGDBw+uX7/e4/H0\n+zwUSZeVlUlvHgqf77xy5crc3NxrOQdUKpUpKSm33HKLWq1uaGg4derUhQsXmpqadu3apVAo\n5HK53++XulGa0jtx4sSvfvWr8+bNy8zMvGZnjkukAfavf/3rJz/5ycDPQ5OZDh06VFpaKvzf\ngXfPPffk5eVpNJprduBdyTgluFJIy/eIoiiKotfr9Xq9w5efO3duUVFRX1/f+vXri4qKpDUu\nhiGXy4dfAEGhUISyY+kxIplMNtSbZ5VKpVqtDgQCbrc7EAgM3MOgpKMbvp1RKCsre++99+bO\nnXvzzTcrlcqBoVKkfRXO7/f39fUJgjDweEOkJGuYMOuiUZfdbn/vvfccDkdRUdH48eNH930L\nwWBQWi5KqVTK5XK3233RBSuuv/7666+//syZM//7v/9bVFQ0ZcqUqGuXRkVBQcGaNWscDsd/\n//d/r1y5MqIYWjoFwWBw4GiUdr5kyZJnnnlm8eLF4b86derUjh07mpqaQiWLioqGqtfn87nd\nbrlcrlKpfD5fIBAY3QW4L4V0+rxer1Kp7LegvERq9gjvG9I1uHLlytTU1IKCgvBfzZ49+8kn\nn3Q4HE899VSor6Ta/X6/SqUadAzn5OQUFRWNGzfuxRdfXLp06c033zx8Ay56LchkskEP8xI5\nnc4dO3acP39eGs8jucSG6auRk443KyvrwQcfDAaDA9fTBwAAwJVM+sfIMH9mS2tA9/vQ6/VK\n81hj3LorlBSJSk95zp8/PxgMVlRUnDhxorm5ubW1VVrOWBRFg8EQHx8vPTBdUFCwYMGCjIwM\nlo+Q+P3+8MWdBy0Qvki0RBp4sWwXokcAjbHndDrtdrsoinFxcUqlMvR/7Ha79Lj3oFsVFBQ8\n8cQTv/jFL373u9+lpKRMnjxZq9XGIriJNa/X63A4Ojo6Bv6qq6trqKjU7/d3d3dLWx08ePDF\nF198+OGHhwq/ousrj8fjdDr9fn98fLxWq5XJZHq93mAw9PX1dXV16XS6Sw/T+/r6pEM4f/78\nG2+80dLSYrVaB64zELVAIOB0Ont6ejQajUwmUygUKpUqPj5eJpN1dHTodLqhvmBYtmzZ9773\nvXXr1r3//vvZ2dnSsr+XcrxWq9VqtW7cuPG///u/k5OTo5gHPYzCwsLwLxWkxbBqamreeOON\n2tpa6UPpxXTTp0/X6XThp15ar00mk8XHx6vVaoVCYTQa3W53T09PT0+PTqe7lD+AQudXMsx4\njgWdTmcymTwej9QGaR06KXiVvmDoVz50jtatW5eUlDR//nyn0+l0OnU6ncFgGKofJkyY8NBD\nDx0/fvypp54KBAJz584dZlxdCpfLNehdQhCEYd7s53a7Ozo6NBpNZ2fn1q1by8vLc3NzB36h\nEmlfDUpa8UOtVnd1dUn7Cb3mOykp6etf//qIjhMAAABXErVanZCQMDBiHp7RaAy9hPCapVQq\nx40bJy0wOG3atN27d0tv5+7u7u7r69NoNPHx8VlZWTNnzly0aNHkyZOzsrJIn0O0Wm18fHyk\nW0n/cLvGB94ViwAaY2/nzp07d+6cMGFCUVFRbm6uXC5fvXr1iRMnnnvuuRtvvPGuu+4aZttb\nbrklKSnp7Nmzzz///N133221Wi9bs0fLqVOnXnjhhUHvra2trWfPnk1LSxv4K2lZiR07dgiC\ncPr06fAXPgwl0r6qrKx86623RFFcv359YWGh9Ch9bm6u9CKFe+65JzMzc2SHOKRdu3Z1dXUJ\ngtDb21tZWZmSknKJO+xHWtqlrKxsyZIlM2bMSE1NVavVP/nJT06fPv2jH/3onnvu+dKXvjTU\ntrE43sujqanprbfeOn/+/De+8Y3QQmyBQODcuXMbNmy45557wtPqffv2vfXWW2lpac8888zc\nuXOTkpIeeuih6urq119//fjx4/fcc4/RaIy6JaHzK2ltbbXZbBk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I7B8vLyampqenp68Es2mx0YGNjb23v06FEfHx8/P79R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zab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\nnU0IUavVra2t9vb2dLP09PSPP/54586dr7zyyvr163Nzcz/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eeecdf3///g06Ojpu3LjR3d1NHKFQKIsXL3Z0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\nTqf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kl0dPSr\nr77aXy2JRJKRkXHu3LmSkhLcZXjSwhP63bhxg1gTEBAQFRU1mIFHcd2cnBwulxsWFoYQys/P\nz8jIeIHhDldgYGBMTAwxZIexsfFgfnLg8/np6ekdHR3btm3D6Z709PTKysqBa9nY2ERHR2sP\njwvPPYCXTkREBIPBOHPmzP3793u8FB4eHhUVhS/5obp27VpCQgKxaGhouHjxYl9f394PNAwS\nj8c7c+aMSqXau3fvzJkzh7cRhFBmZmZjYyOxSKfT16xZw+Vytcf5aWlpSU1N9fPzW7x4sVKp\n/O6772bMmBEdHX3hwoWsrCwXFxft6W3b29v3798/d+7cyMjIjIyM27dva98n09PTfX19o6Ki\nLl68ePPmzZMnT5aUlMyaNQuPZUTUxb/bDa/dpUuXDvtoAAAAmOQgAQ0AAACMLwYGBra2tlZW\nVmKxGHf8NDU1xc/GKhSKlpaW7u5u9J/hAkY4FC/oU0dHx927d01MTGJjY3HKb9++ff/4xz+c\nnZ0HSEArFIrHjx/n5OSQSCQmk9nY2NjY2Ghubv7cnqpisbi6utrQ0HDUH+seXXQ6fcqUKVQq\nVSgU4pms+iupVqt5PN5vv/1GrJHL5fPnzx9MK2q1+saNG+np6cnJyUTP62vXro08/lHn5eX1\n7rvvWlpaajSalpYWiUQymISXUCj8+eefuVzun/70J0tLS7lcXllZ+dwEtIWFRVRUFM4cdXZ2\ntrS0DDAxJgDj08yZM728vEpKSnonoAMDAzdt2jS8zZaVlTU1NSGElEqlWCzmcDjJycnDSxzL\nZLKWlpb8/PwLFy4sXLjw/fffNzAw6P30wyAVFxfX1tYSi7NmzSI+UwgSiSQ3N9fAwGDVqlUC\ngSA+Pl4mky1ZsuTOnTtHjx5NTk5+++23icI//PDD3/72NwMDg9dff/3GjRunT5/esWNHTEyM\nmZnZ9evXS0tL586du2nTpubm5qtXrz569IhMJu/YsQN/bGnXHXa7kIAGAAAwbJCABgAAAMYX\nR0fHTZs2ubi4pKamNjQ0IIQiIiKWLVuGEBIKhceOHcPDIAQGBsbGxgYHB+s43ImIxWKtX79+\n4cKFtra2g69Fp9NXrlz5yiuvIIREItHx48efPHkSGxtrYmIycMXMzMzff/+dy+VGR0eP567T\nHA5n+/btjx8/3r1796pVq/A52Sc9Pb3o6Gg/Pz9ijb29/bB7I45/SqUyIyPj/v37sbGxISEh\nL7q5Bw8eHDt2LDw8/M0333zRbQEw/oWHh69btw79Z6QaPFjz8AgEgqNHj3Z1dX3wwQf+/v4j\nHHGC+OzGbGxsen+mmJubr1+/PjIy0snJSSAQDGn7YrH42LFj1dXVsbGxHA5nx44dtra2OGY6\nnb569eqlS5f295kyknYBAACAYYAENAAAADC+6OvrW1lZWVhYEF99mUzmlClTEEIymYyYSI3N\nZi9dunQwYxqAoTIxMQkLC5s1a9aQaunr6wcFBQUFBSGELl26dOjQIblcvmbNmgGqiEQigUBQ\nXFzc1NTk7e29YMGCEcU9dBQKxdXVVSwW19XVFRcXOzo64mfDa2pqKioqRCKRXC7n8/mFhYVs\nNtve3t7e3r6zs/PChQtFRUV2dnYIIRqNxmazEUJCobCtrS0gIAAPhczlcrlcbp/7W1NTo1Kp\nysvL8/Pz2Wx2j57UJBLJycnJ19e3ubn57t27CCE+ny+Tyerr6+/du2dgYNDe3t7Y2CiVSktK\nSnDd8vJypVJZW1t77949HAxCqLOzs6ioSKPReHt702i0Bw8eUKlU/FJdXZ2tra2JiYn2nFoa\njaaqqurhw4dsNltfX18gEGi36+bmhjunE+26ubkxmcz8/Hw8cWJJSQme27Cjo2NIdRUKRY/j\njOMh6hoZGbm6ura1tdXV1eEDwuPxBAJBe3t7f28rPs4jScO91PA5OYypPoEOEdcvi8Uaal1P\nT0/8tERVVVVWVlZ1dfVgajU2NgoEAmJ8eQMDA0dHx5aWFjzx4KuvviqTyR48eIAQ0r7nsNls\n7fvks2fPiA0aGRmx2WztRxP8/PxwYAOg0+l4MuEh7TK+T3I4HI1GU1FR8fDhQ2dnZ3Nzc1NT\nUzxSPJVKDQoKGuAzZXjtqtVqoVAoEomINebm5mw2G49VBQAAAAwAEtAAAADA+CIQCL799tsb\nN27gCcoQQufPn8/Pz0cISSQS6Kk0kWRnZ6ekpMybN++LL74gMo9jiU6nr1q1ytvb++zZs/n5\n+Zs2bXJzc0MIZWVlHThwoKqqSiwWHz16tLKycsuWLRwOByEUFhbm4OBw7ty5+Ph4hJCLi8um\nTZvIZHJKSgqTyfz0008HmKEL7+/Tp08lEsnJkycFAsGmTZtmzJihXYZCocTExHh6ep49e/bo\n0aMIoZaWlubm5uzs7GfPnpHJZKVSKRAIOjo6Dh06lJaWhhBqbGzs6urKysrCG5w+fTpCSCAQ\n/N///d/MmTPff//9kpKSXbt2KRQK3ASLxVqyZMn06dO1eyOqVKozZ87gPbWysiKuQdzuhx9+\nuHjxYoRQXV3doUOHXnnllXXr1tXW1u7bt6+rq0tPT2/x4sUrV650dnbWvn4HUxcnvrWPM3Gs\ncN01a9asXr3a19f37Nmzhw8fRggFBwcP5jhrz342qeBzssd5BcY54vpdsWLF2LT44MGDlJSU\n1tZWvGhra7tp0yb8WxGPx/viiy+IpKpSqayqqurs7Dx06FBVVZX2ffLgwYPEBn19fYn75IuG\n75P4JBcIBGfPnq2qqkIIvfHGG8MeyWQw8H3y1KlTxJpXX311y5YtQ3paCAAAwOQECWgAAABA\n9/CYueXl5QghPJalj4+Pj49Pj2Lt7e11dXU6iA+MtpqamsLCwrKyMisrKx8fHy6Xy+PxeDwe\nh8OxsbEZszCoVKqbm1t3d3ddXV1NTY1EIsHrGQyGra0tkVOwsLAgug/j9eXl5UVFRQghS0tL\nAwODxsbGx48fc7ncqVOnDtArn06ns1gsYiwOXLdHGTKZ7OzsbGRk9OTJEzwEjVqtplAoIpFI\nJBIh5IOQJ0JTEELFxUQlFkKcmhp+ff1tvDtTpkzBQ067uroGBwdTKJS8vDwiIevo6MjlcrWv\nLw8Pj+joaBySoaGhvr6+ubm59jXIYDCoVGpgYCBOV7m4uAQGBlpYWOTl5bW3t+vp6fn6+uLO\n783NzUOqiw+p9nG2s7NbuHBhfX09Udfd3d3AwKCoqKitrQ0h5ObmNn369AGGdhGJRHfv3nV1\ndR3PI7q8CHK5nMfjtbe3E1lFME6Ul5fzeDy1Wi2TyaysrGJiYnqXIZPJZWVlp0+fRgiZm5tz\nOBwLC4shtUKn06dPn25ubs7j8chkMofD0Z7urwcajWZtbU08VGRlZWVoaGhubv7qq6/26IUt\nl8vr6+tlMpmZmZm5uTnxcBKDwdAuqX2fHAPt7e3t7e0cDsfS0rKgoKCiooLH402bNg0/+qBQ\nKPLy8qZMmTLqnykmJibae21mZvbceQ4AAAAABAloAAAAYDxQKpVnzpz54YcfEEI+Pj4ffvih\n9vi5hNLS0i+//BJn5cBLjcfjffnll4GBgYmJidbW1rhHcH5+/o4dO8YyAd2fefPmTZs2jVg0\nMDDoMd1lZGRkaGgoQohKpZqbmzc2Ng5ms2FhYb6+vsTQELhunyXNzMxiY2NxX8gLFy58+eWX\n/0mORyL0UT+bP6hUFqWnpxcWFn744Yd//OMfEUJ0Ot3MzOy57RL7S6FQcIJpy5YtMpmMKGBq\naop7iy9atAghhBNVlpaWLi4uarUaIURskM1mD7UuAR9nlUq1c+dOYgJS/BKLxdq4caNUKkUI\nGRkZDZBWI0RGRn70UX/HamJqbW394osvSkpKdB0I6Ck7O/vLL7+UyWQmJiYffvhhn2emQqH4\n7rvv8KMVU6dO3bVr11AT0Obm5rGxsbm5uQcOHHj06NGuXbsGuFKCg4NdXV2Ja1BPT8/MzKz3\ntY/+c17xeLyNGzcuXLiQuNife598cfD/Ga5cubJjx4558+Zt2bKFzWZ/8cUXRAGJRHL8+HE+\nnz+6nyl4fP958+YRa+h0+gQe3x8AAMAoggQ0AAAAoDMlJSXZ2dnd3d0ajUalUuHn9J2cnHx8\nfJycnHqX19fXX7VqFX7Cl8lk/vTTTxQKhUwmh4aGjtn33onNwMBg3rx5ZmZm+fn5T58+JdbL\nZLIPP/zQ398fL4pEouzsbDqdHhoaKhAIcnJyVCqV9na6urrmz58fEBCAu9epVKqcnJzKysrQ\n0FAjI6Ps7OyLFy8+efKERCKdO3eOSqVKJJJbt251dHTgDCP6z7nh4+Mzc+ZMhFBHR0d2dvbV\nq1dFIpFEIklNTZ07d25oaOgI58jCzM3Nly5dKhAILl++XF9fHxYWxmQymUzmAFXMzMzwKdfc\n3Hz58uXi4mLt/e2PiYnJc6dkxKRSaV5eHn4mID+/QyJ5AyE8gMZrCDn1U2keQl0tLaisjHrr\nVm1Hx+8IIRcXl9DQUCaTOXC7vfe3zyfKLS0ttft36+vrGxkZ9ShjYGAw7LqE3lkzfX39oWaR\nzMzM+ryNTGAtLS0DHFUwxvB9Eo8XLBaLFyxYoNFo6HQ6l8vt88xUKpUzZszAyV8ajZaVlXXn\nzh1c991331UoFIcPHw4LC/P29kYICYXCnJycq1evdnd3P3z48MCBA6GhoQEBAdbW1t7e3nPn\nzm1qajp16hTukjxjxgw/P7/s7Oz8/PyAgAAHBwcLCwsjI6M+z5be1y8+r6hUqo2NjXbn3z7v\nk+Xl5dnZ2Tdv3lSpVHfv3tWOWVteXt6tW7cKCgo6OjouXLig0WjCwsLwSzwe7+DBg1Qq9a23\n3qqpqUlJSSFqtbW1rVu3Ds902tLSUlxcfPr06YqKCoRQR0fHihUrQkJCcH9kKpXK5XL9/Pzu\n3r3L4/GIugYGBgcOHBh2uyQSycLCYqg/DAAAAAAIIaQBo+fx48cIoY8++kgqleo6FgAAAC+B\nH3/80d7e3sDAwNjY+G9/+5tUKpVKpd3d3SqVqs/yKpVKJpPhYv/+97/t7Oxw3ZSUFIFA8MYb\nb0yfPj0nJ2eM9+Jl8dVXX1Gp1L///e8DlFGr1XK5PC8vb9GiRQZaPv30U6lUqlAocLG7d+++\n+uqrq1atqqioOHDgAJPJNPhvERERubm5MplMrVZrNBqZTBYfH+/m5vbrr7/iulQqlUQiUSgU\nogqFQvH19c3MzMRN4HNj586deFEoFK5Zs0ZfX59EIpHJZH19/T/+8Y+D/P/Gc88NfF6dO3du\n2rRpGzZsaGxsHOQh1Wg0hYWFS5Ys6bG/I4f3Fx8ZKnU5iVSMkBQhKUIKhDT9/FP8p0wZlboS\n18Xv0aiE9BL59ttvDQwMEhMTdR3IWGtubo6NjdW+joAO4XsdvhI3bdokFovxh5dSqeyzPL79\n4jI3b96cPXu2dt3t27fb2tqmpqbiwpcvXw4KCsK/wFEoFPw5iF9SqVTd3d1paWl47BoDA4Ov\nv/66ubk5Li5u6tSpZ8+elclk/X3I9mlI59WZM2c8PDxwYHp6etoxa/vmm2/wbR8hRKVSZ8+e\nfefOnV9//ZXNZuPPhcTExNra2nfeeUf7k+Wdd96prq6Wy+UymWzz5s24Ln5p+fLlpaWlcrlc\nrVZv377dzMzs0KFD2p9luO6XX345knYHf9AAAODlRdxj8/PzdR3LhAI9oAEAAACdwd+Tp0+f\nHhkZOXPmzIF7jyKEcOYR/x0YGJiQkHDhwoVr16716H4Lho1EIlGpVAcHhzfffBN3PcZCQkK0\n350pU6Zs2LCBwWCYmpoGBwfv2LEDD5hAcHZ2dnBwIN4sCoWycOFCZ2dnHx8fY2PjDRs2LFiw\noHfrVlZW7u7u+G9/f/+tW7dyuVy8aGJisnz5cu2BWQIDA0el+zP6z3nl5eX1wQcf2NjY0On0\nwde1trZeu3atRqPR3t+R02g0crlcJrNGKBKh+QjZIPScqwMhvf8822elUKxCyByh8zhjMlpR\nAQAGD1/Frq6ukZGRr732mpGR0cC3LHz7xX2WXVxc/vCHP0yZMuX8+fMajQbffvGvsyY9dVAA\nACAASURBVLiwi4vLe++9RwxIRaFQXnnlFfw3mUw2MDDw9/f/+OOP8bDpuJOvQqGQy+V6enpD\nvVPRaLTly5eHhoYS9+cBeHt7b9myBbeL6wYEBPQuFhoaumfPHmLR3t5+ypQpZmZmf/7zn3Hd\nOXPmmJqaLlu2DE94iPn7+5uZmVGpVPzIlHZ3bE9PT2tra+1BqHt8luG6c+bM0b4lDrXd5x8s\nAAAAoB+QgAYAAAB0QKFQSCQShUJhamo6b968Tz75ZKhb4HA4HA6HRCLl5+erVKrW1lZijjUw\nQlZWVqtXrx6ggL29/fr16/HfQUFBePa5AVAolAULFhBJZ6LuAPD7Sywymcxly5Y9t9ZIuLi4\nuLi4DLXWc48VJpfLJRIJHm6VRqPRaLT+Smo0GolE0traLpfrI+SF0AaEXhliUEyEliHkiFCl\nXG7Q2tre1dVFp9NJJNIQtwMAQGgo1y+mUqkkEolEIqHT6W5ubps3b3Z0dBxSi/gea25uXlRU\nRKFQxGIxiUQyNTVVKBRtbW00Gu259ytPT09iEk6JRCISiahUKpPJHEYWlUaj4QGyBkO73QGE\nhITgkTR6V9deXLx4cZ9N9/hM6U/v+/MI2wUAAACGDRLQAAAAgA6UlpaePHlSoVB88skn2rMY\nDdW8efNMTEwqKir27t1bUFCg3R8KgPGjoKDg5MmTeK7C5cuXD5DaUKlU6enp6em3CgqmIuTT\n/4jPz8VGaAuPV5SY+H109MzVq1dD9z0AhqegoODEiRNNTU3oedcvJhaLT5w4wefzlyxZ4u/v\nP+xJ6jgczq5du0pLS3fu3Mlms7dv315eXv7NN98QcyEM0vnz5y9evOjq6rpo0SIvL6/hBQMA\nAACAkYAENAAAgOFobm4WiUTW1tZmZmYikai1tbV3GRKJxGKxtCeraWtrE4lExsbGLBaLTCYP\nsH21Wl1fX9/c3NznqzY2NlZWViPcBd2qra3NyMjgcrkJCQnaU5MNFYfD8fT0TEhIyMjIYLFY\nrq6uQxo/AYCxIRQKf/3118rKSoQQk8nUnoLMyMiIxWIRI5yo1ep79+798st5hJIRWjSCNq0Q\nihQKu4XCg7a2lBUrVkACGiEkFotFIhExjgGVSmWxWANMONnd3S0SiTo7O7VX9r6396BUKkUi\nkVQqZbFYxsbGA4eEPxcUCjzJJKJQKCwWS3tW1aHGDEadUCj85ZdfBAIBet71i3V2dl6/fr26\nunr16tXaYxkNFZvNZrPZKSkpP//88549e1auXPnNN98UFRURA1wMUk1NzZMnTxYtWhQdHT3s\nYAYgl8tFIlF7eztCyMTEhMVijeJ4REOC/2/W2NioUqmqq6vLysoGcw0CAAAAYwAS0AAAAIYj\nJyfnyJEja9euXbRoUVpa2qVLl3qXoVKpcXFxUVFRxJrCwsIjR44EBwfHxcUN/PUM94LMyMjo\n89W33357ME/9Tyqmpqbr169ftGgRm83WdSwADCQzM7O0tJRYnDZt2rvvvuvs7KzDkCaP3Nzc\nI0eOEPk7GxubuLi4WbNm9VdeJBIdOXIkNzdXe2Xve3sPUqn05MmTZWVlcXFxzx2gprCw8NCh\nQ/X19XjR2Nh448aN8+fPH3bM4IXS4fVLo9FWrVrV1tY2mDEutEVERPj5+b24vs9isTg1NTU7\nOxshFBoaunHjRhsbmxfU1sDw/82KiorwNVhdXT2YaxAAAAAYA5CABgAAMDT19fV8Pr+4uFh7\nIvv29nY+n48Q8vDwMDIywiWVSmVxcbGZmZmnpyf+MqbRaNRqtUAguHLlipeX18ADOOKhYEtL\nS2UymYeHh6mpKfFSWVnZtWvXPDw87O3tR7g7TU1NfD7f2NjY09NzVLosSaVSPp/f3d3t6emp\nHTOhs7OztLS0qqqKw+H4+fmNvFcmiUTy8vKaPXs27lcOA90OQKPRlJSU9Pl7yQTW0NBAZPfG\ng7KysrKyMmKxsbHR0dGRuBsoFCqhkI7QbIRGJYNjjdCsZ88YV65k+fg8554zseF7HY/H6+7u\nxoP5IoQkEkl+fr6+vn7v+5VCoSgtLS0oKGhsbCTKI4Sqqqqqqqq0E8Q9lJWVFRQUXLx4sba2\nduAOp62trXw+//Hjx8T4wgghmUzG4/EYDIaHhwdCaEgxgzEwwPXr5OTk5uaG3zIWi2Vvbz8q\nb5CDg8Nrr72mUqlycnI8PDyGNPgG5uHhgU+nPqnVaj6f39DQQPxfZZAqKyufPn2K//Og0WjE\nYnFpaSmdTpdKpUONcOTq6+tLS0vx/81cXV1dXV0RQmq1GmZhBQAAME5AAhoAAMDQ8Hi85ORk\nb2/vvXv3Ojg40On0lStXOjs7//Wvf9VoNPHx8cTXPKVSefz48cTExISEBJyt4HA427dvP3fu\n3O7duz/44IMBkkEUCiUqKsrV1TUpKam+vn7Tpk1cLpd4NS0tbc+ePfHx8TExMSPcHT6fn5yc\njEexGJUEdGtra2pqan19fUJCgnbMBNyjsL29fc2aNQEBAQwGY4Qt4mPl7e39008/3b17t792\nAUJIpVJlZGTgfmqTh0KhqKurG7cjn+JrkHiEX6PRq6tbg1AsQrajsXkOQttzcs5VVOz++OOB\n7jkTHj7OLBZr27ZtxCP5jY2Nx48f7/O+IZFITp48mZeXt3bt2o8++ohY/69//evAgQMDNJSZ\nmfn999/X1dXZ2dkNHJJQKExJSaFSqe+//z4xqlJnZ+fPP/+cnZ29detWEok0pJjB2NO+fjds\n2PDRRx+lp6dfvnx5zZo1c+bMsbUdhas4NDTUxcXl5MmTe/bsSUhIGPkPzz3gJ66uX7++devW\nAX5Z6S0rK+vAgQNbt25dvnz5+vXrnZ2dk5KSRje2wePxeElJSb6+vnv37iV+2DY0NByVtwAA\nAAAYOUhAAwAAGJr29vaSkhIXFxdfX1/8ndPBwaGtrc3Y2FitVnt4ePj7++OScrlcJpMVFxcT\nj04zmUwmk3nlypWioqKGhoYBWiGTyfb29iqVislkdnR0uLm5EZtFCJ04caKoqEgsFo98dzo7\nO/l8Pp1OJwYYHSGFQiEQCKqrqyUSSZ8Furu7Kysr1er/j707D2vqWhcGvjJDAgTCFMYAMkMI\nMsisAk5QFbR6EAe8rUO15XD7eaytaH1a6tReTidtbdXeU7Wt2qpgtTggoSiDFhAhIGFQCDIE\nkEAQAoEM3x/rnP3khkFkCsP6Pf5hkr32frNn3qz9LoW1tbWVldXYl4itq46OjmGWi7DZ7Li4\nOE1HoTFz5syZmpXTu7q6VDtUAkACgAKAyzjNng4Ava3tTlvbS845M56enp6LiwuLxfLw8MCS\nubW1tUOdNwgEAovFUiqVHA5Htc/pS0c6NTc39/DwkEqlLw0JdnOm0+kcDgcrhS8SieBp+cWL\nF5aWlq8UMzL5VI/f9PR0HR2djIyMJ0+e6Ovr29vbj8sijIyMjIyMzp8/P17XfTVKpbKxsZHP\n579qaenW1lYej/f8+XMymcxisZqamjQ4BgO8N7O3t8fuzRAEQRBkSkEJaARBEARBZoXQ0FA/\nPz9NR6ExRCJx7N3tkenL0dFx165dI98NqFRqTEyMTCZ71d0mIiKCw+EcOHCAx+MNP6W1tXV8\nfDwejx9qEa8aM6JZmZmZDx486O7u1lQFZARBEARBpiyUgEYQBEFGqqGhgcvl1tbWrlu3zs/P\nj0AgjG4+Xl5eu3fv7uvr+/LLL8PCwlS7No9OTU0Nl8ttbW0FAPj7+y9cuBAAIBaLuVwuHCvJ\n0dExLCzsyZMnmZmZQUFBAQEBAIDW1tbMzMxbt261traWlpZ+9dVX4eHhISEhXC63sLAQmzls\nixWy7OnpyczMLCkpAQDY2tqGhoaamJjAj+RyOZfLzcjIqKioEIvF586dEwqF2HJlMpmWllZY\nWBgejx/j9x1GY2PjuXPn7t69O3GLQJBRKCsr6+jo0GwMWVlZE3r0TR15eXkDH+kgk8mvVGUI\nj8djnY4hHo/H5XJ7e3vfe+89b2/voRrSaDRDQ0MKhfLSRZBIJLUawVlZWbm5udbW1hwOx9bW\nVi1meI7Nz893cXEJCwsbqhTD8+fPf/3110ePHr00AGSEysrKRtI7uKenZxLKH8Nr99OnTwEA\nbDY7NDQUPsOEXbvNzc3DwsIsLS0BAIWFhdj1Nzw8nMlkZmZmKpVK7Nqdl5cHG4rF4tTUVIlE\nMrAtXK6xsXFoaCgs4wOPhT///FOhUNy5c4dEIoWGhqoGCdti9xvQSO5VwsPDq6urR9gWgvdm\nt2/fFovFDx8+TE5ODg8P9/T05HK58EcgtXsVBEEQBNEIlIBGEARBRurZs2cnTpxgMpnJycmD\nllJVKpX9/f19fX3wZV9fHw6HI5PJakmfwMDAwMDAxMTEpKQkPT29lyag1WYLwdkqFAq5XM7n\n87/55pvS0lIAwK5duwIDAwkEglgsvnjx4uXLl+Vy+cqVK11dXXNzc5OSkj744ANvb28CgdDS\n0nLu3LmbN2/K5fKWlpbS0tL+/n4fH5/r16+fOHECW9DKlSvd3Nx0dHQIBIJcLheLxVeuXDl7\n9iwAIDw83MHBgcFgEAgEHA4nl8vT0tK++eYb+Pfq6dOnW1tb3dzc4HJ7e3sZDIaOjo63t/fE\nDQpUX19/+vTpCR2HEK5z1XeIRCIa+RAZnlKpxPI4mpKRkZGZmanZGCbHwIN0XBQWFn7yySdb\nt249evTouM9cLpfDU+ipU6c+//zz//qv/xo4QU9Pz9WrV69fv56cnLxmzZqhZgXP7eikNI5G\nePzi8Xh4oZy4SGQyWUNDw5kzZ9LT0wEAGzdu9PLyIhKJfX192LV73rx5NjY2pqamRCLxwYMH\nSUlJ3d3ddDpdR0fHx8fnzJkzCoUCu3ZnZ2d//PHHcrlcoVBcvHhRIBA4ODiYm5vLZDLs2g0X\n7erqymQyraysCARCUVHRp59+2tLSAndaPp9vamoKi54rFIq+vj61+w14hzDovUp7e7vqvYq7\nu/vI28J+APC6n5ubK5PJHjx4UFBQgMfjbW1tL1++/NNPP4EB9yoTt3UQBEEQZBgoAY0gCIKM\nm4qKin/+859YKU8cDmdkZLRv374x9nEWCATHjx+/fPky9o6hoWFSUtK8efOam5tTU1MFAkFs\nbCzscNfe3v7+++9HR0d7eXnFxcWZm5unpKSUlpYePXrUysrqk08+EYlEBw4ciI6OdnBw2Lp1\nq5WV1dWrVy0sLFatWtXX17dv3z4jIyPVcYS6urpOnjzp7+8fHR198+ZNLpdrY2MDJ5BIJLAq\n5apVq2CGOjo6Wl9fPyUlpaOjY9WqVcbGxidPnqRSqZ988gn8G7K2tjYzM5PP5zs5OY1lnQzF\n2tp61apVtra2EzFzKD8/PyUlpbu7G740MDCIjo5GQ4EhwysuLr569WpbW5sGY4iIiHilEcam\nr3v37qWmpmo6ileTk5Nz9erVYZ7e4HK5IxxB1NTUNDo62sVlvMqII6C4uDg1NVUkEg0/WVhY\nWGRkJLwoT0QYcGBMPp8fEhKydOlSAEBnZ+dnn30ml8vh/Qa8NPf29l6/fr2qqio6OjooKOjI\nkSNw18LaAgDOnz9fXl4eFRUVGhr66aefpqamlpaWRkVFLVu2zMbGhsfjpaSkyOVyeO2GS+/r\n67t3755AIIiKivLx8fnoo4+uX7+elpYWFRW1YsUKDw+P58+fAwBKS0sPHz6ser+xatUqa2vr\noe5V5s6dq3qv8kptFyxYAABgsVjx8fH29vapqalubm5RUVGdnZ2ffvqpnZ2d6r0K/L46OjoT\nsWkQBEEQ5KVQAhpBEAQZN62trVlZWXD4dbFY3N3dnZyc/MYbb4xxtu3t7dnZ2aoPdL/33nvb\nt28HAFRUVNy/f18ikSxevHjOnDkAgBMnTnzzzTe2trYLFiyIjIxkMBj3798vLi6+c+fOli1b\nduzY8fHHH588edLR0dHf3z8qKkpbWzs7O9vZ2Xnbtm2nT58+ceJEcnJyQkICtqwrV67s3r1b\nKpWuWLGCz+dnZGTs2LEjMjISAHDv3r0zZ840NzdHRETABPSCBQtsbW15PF59ff3atWuFQuHu\n3btDQkI2btxIoVA6OjoOHz7822+/AQAmKAHNZDLXrl0bGBg4ETPv6ekRiUQUCqWkpAR7HNvC\nwmLNmjVwhUxxYrF4Igawmi4oFIqBgYGmBqe6cuVKZmbmoAloLS0tBoOBnTc6OronKIaAgADV\nQ3sGw+Px165dG34apVIpEomEQiGNRjMzMxtJxYwJVVNTc/36dalUamlp2dvb29DQwGAwtLW1\nsQmqq6uvX78OAGAymd3d3U1NTUPtz4aGhjCTOHnRz3RXrlzJyMgYNAGtevwuWrTonXfeqamp\nmaAEdH9/f1FRER6PT0xMhLnXH3/88csvv+zv7zcxMdmxY8fKlSsBAEVFRRcvXqyurg4PD+dw\nOBwOp6GhISMjA2srlUp3797d2tq6dOlSHx8fDw8PGHNkZCTsWZ+Xl/fjjz8uX75837592D5W\nWlq6e/fuhw8fBgcHe3h4uLq6ikSimzdvLliwAHbYhwnopqYmtfsNZ2dnGo129epViUSSmJjo\n7OwMRnyv4uzsrK+vP8x9DvjPdZ9AIGRkZHh4eLzzzjtJSUn/+te/9u/fD1cIvFeB3xcloBEE\nQRBNQQloBEEQZNw4OjrGxcWxWCwAQGpq6q+//jous2WxWJs3b1bN2Lq7u8P/MJnMrVu3FhcX\nnz9/HlaYhYUU1bi7u8fFxQUGBhKJY7rwRUREWFhYPHr0aPfu3QCA5ubmpqaml7bKycnZu3cv\nHo/v6+t76ahcU1llZeXZs2dxONyePXuwdBWVSh17Fe/JweVyf/75Z01HoTGOjo5qx9EUoXbe\n+Pnn8TlvIMOTyWRXr17Nysry9PTkcDg2NjaajQf2VIXlC4qKiv75z39u2rRp7ty52AShoaHG\nxsYAgO7u7kePHlVUVEzN/Xm2UT1+J3pzUKnUdevWrVy5Um1BYWFhsbGx2KVZJBLV1tbCkAZt\nC0dxmCDu7u6bN28OCAgYeL8BnxKj0+lg6HuVgW1HeJ+jBvYWv3//PhjxvQqCIAiCTCiUgEYQ\nBEHGjamp6eLFi2E6srq6eoQJaIlEIhAIVAc4Mjc3t7a2xl4yGIzQ0NBBe/WSSCQjIyMdHR2R\nSNTY2AgAGHSgJAsLi4iIiEHrVr8SPT09JpMplUrr6+vhsvr7+1/aqqurq6GhAT7Ga2pqampq\nCgAwNzevrq6mUqksFgv2HRs1hUJRV1dXXl5uaGior68/Ef2b4DYqKiqqqanhcDivvfaa2tBh\n00JFRcWVK1esra2ZTKamY5lUfX19AoGgvr5++fLlmo4FAACsrKxgsVTIz88vKirK3t4eACCR\nSKqqagWC3ubmhwCwADAc89JEAAhMTXtYLN+hxqybhRoaGmpqavh8fmdnJ4fDCQsL03REwN7e\nHu4DIpHo9u3bBQUFS5YsUZ3A2dkZdh2tra29du3a1NmfZ5thjl8AQH9/v42Njaura1tbW2lp\nKYvFUhvKchSEQqFAIGhoaCCRSD4+Pmo7BgBAV1fX3Ny8oKAAXpq7urrUBo0AAKi2ndAEtIWF\nRWRk5KC/6Eil0ubm5hcvXgAAaDSan5+f2sVo0LYjvM9Ro1AoRCIRNli0s7PznDlzxvgbPPJK\n4L2ZUCjUdCAI8n9QKBRra2tDw7HfXyHIK0MXIQRBEETDhELhqVOnYD8daNOmTTt37hx5W5FI\ntGHDBjMzMwDAuXPnfvjhhwkKNS0t7dKlS8uXL4+JiQEA/PXXX8ePH39pq+Dg4Pj4eDKZrPpm\nZWXlzz//XFZW9ve//32MyVy5XJ6SknLnzp0VK1YEBgZORE9G1fXs4eFBo9HGfRGTg0AgrFq1\nau3atZoOZFI1Nzd//fXXPT09mg7k3yIjI+Pi4rCX+vr68OAFAISFhbFYNsePX7906RMAEgAI\nHfPSSgA4HhxsGx9/0N5+zpjnNkNwudxTp07BU5nG+z4j08swxy/4zznW0dHx+vXrBQUFCQkJ\nbDZ7jEvMzs4+fvx4dXX1UBNwudza2trly5d//vnnAICysrKvv/56jAudCI6OjrBYM3yJw+FG\ncvSN7j6HSqXGxsaqVscyNjaevtfu6Qjem8GqawgydZiZmcXHx4eGjv3+CkFeGUpAIwiCIBPC\n0dFx5cqVXV1dN27c8PDwGKbvIZFINDAwUO0HNPI+vBKJ5PHjx3BEe9jzepgxrMaurq7u4cOH\n69evh92xu7q6qFTqS1sxmUx/f38tLS1YgqO9vZ3NZnd1dVVVVdFoNJlMNsaolEplTU0Nj8d7\n4403xr0aBoy5uLi4r6/Pzs7O29t7WqercDicra3tBNXInrLq6uoMDQ1h30BNMTc3X7p0aXNz\nMwBg8eLFQ20CS0tLExOTy5cvAVAIwLiMWCgC4CGTyfT399NU/espRSAQ8Hi82tpaJpPp5ubm\n7OxcWlrK4/HYbPYw/aGam5t5PF5ra+vixYvd3NwmM2BkKjA3N1+2bFlLSwsY9vgFAODxeFtb\nWxwO9+OPP9bX18PevmMkFArv378vlUp1dHQKCwstLS3ZbDZ8lghqaGhoaWlZs2YNDAyPx4+9\n2/VE0NfX9/T0hJfpioqK8vJyWFVmeKO7zyESifb29nCFwONXLBYrFIoxfwlkSHA9d3Z2wpcK\nhaK1tXW2PXGFTH00Gq24uFh1TBQ7OzsPDw88Hq/BqJBZAiWgEQRBkAkRHh7OZrO/++67gwcP\n7tu3b5gENJPJ3L59u2r3TFghceaBNRmLi4sTExM1HctIwZjz8/N37tw5f/58BoOh6YiQaYnN\nZu/btw/+3DId67fMGPn5+YcPH162bNlnn33GYDDa29vPnDnT1NS0f//+YRLQFRUVycnJNjY2\nH3zwgWp9JGSWYLPZ+/fv1/jxK5FIzp8/X1lZmZiYqJqAno64XO4XX3yRmJiIdYieOPD4dXd3\nt7Oz0/hwozMYXM98Ph++JJFIO3bsgL3yEWTqEAqFJ06c+PLLL7F3Nm/e7OrqqvakJoJMBJSA\nRhAEQUbK1NT09ddff/78+dWrV728vIKCgohEYm9vb05ODpfLraurUyqV58+fb25uDg4OptPp\nNBrN399foVAUFxc/ffoUAGBnZxcUFCQQCHJyckgk0tatW11cXMhk8sC/JOVyeU5OTlZW1pMn\nTzo6Oi5fvtzR0REUFKSWm2YwGCtXrhQIBOnp6bBPUF5enkKhuHfvHvwlv7a2VigUSiSSs2fP\nhoaGBgUFAQCkUmlGRoaWlhZ8CQCoqKg4ffq0VCp96623xGKxamGNFy9eREVFBQQEEAgEf3//\n7u7upqYmOAGfz29ra4Nt58+fr9oprLm5+fLly0ZGRlFRUTo6OqdOncLhcHK5nEQizZ8/39jY\nGIfDxcbGdnV1/fzzz76+vqPuk1tYWJibm0un0zdv3jxnzjhXGMjLy/vrr79IJNKiRYvc3d1R\nRx5k1Gg02gif/sbj8SEhIWIxISen6smT3wAIBsDs5c0GIQQg286uKigoav78AKwW6qxVV1eX\nk5OTlpZWWVlpZGQEy/i2tbXl5eVRKBSpVAonKykpycnJ8fX19fHxwdr29vY2NjYymUwLCwsD\nAwPV2QqFwuzsbCqVGhwcrKenBwDIy8u7d+8en88XiUS///67VCoNCgoyMjKC08Nze01NTVBQ\nkI6OTnZ2tlqNVLlcbmFh4eDgYG1tDWNua/s/feH7+/sdHBz8/f3RGWnSjPz4hXR1dZctW1ZR\nUZGTk9PR0YHtG6/qyZMn2dnZ7e3t27Zty8vLKy0t9fT0dHd3v3//PhzRVywWb9iwQS6X43A4\n7NqNXffPnDkDf1YpLCyE130ymYxd9/l8Prx2w139xYsXN2/eVCqVwcHBdnZ2mzdvVigU8NoN\np5dKpRwOx8rKSvWnmkHvN86cObNw4ULV+422tjYOhwMAwO5V2traYLnnzs7OnJycjIyMkbfF\n7nPodHpQUJBqCpvH4504cYJEIm3atKmhoQGukO7ubjc3Nw6HgxJME6StrS0nJ6e8vNzNzQ3b\nHEQicbo/NIbMSLq6uiEhIaqPiSgUiu+//z4gIED1uo8gE0KJjJ9Hjx4BAN55552enh5Nx4Ig\nCDL+5HJ5b2/vr7/+6uTk9O6778JzXVtb2/bt28lkMh6Px+PxZDL5zTffbG1tVSqVCoWir6+v\nqqrqb3/7G4VCoVAoMTExT58+/fbbb+l0+qFDh3p6evr7+wddllQq3bVrF4VCwePxOByOTCbD\ntgNDkkqlf/zxh5eXF1wEHGOHSCTCl2QyGYfDwcBgzHv37oUTeHl53bp169atW2w2G4/HUyiU\nDz74QCwWJyQkUFSsWbOmvLy8r68Pfp3GxsYtW7bAj0gkEpw5hULZt28fDEkgELz++uswZtj2\n66+/ptPpFAqFyWSeOnWqt7dXJpPJZLLe3t5//etf5ubmWNtR+J//+R9dXd0vv/yyp6dHJpON\nej6D+vDDD1VjHt+ZT74jR46QSKSvvvpK04FMNrhP+vn55eTkaDqWl4MHWmVl1apVfwNgPgB5\nAChH9e8+AAuiotY8fvzv41fT32zyHDt2jEKhHDp0SPXN9PR0Hx8feIYkEAjYGRKPx6vuG/D8\n/Omnn6q2hefJzZs3w3O7qvv37y9YsCAmJqa2tha+8+GHH2KnbhKJ9Nprr5WUlGDTw3O7o6Pj\n5cuXYVvK/8VkMn/44Qd4zoExq03g4OBw4cKF3t5euVyuFkxbW9vmzZvd3Nxu3LgxLmsSGR2F\nQiGVSu/evTt//nzVfeNVpaSkwLrJ7e3t7733noGBwcmTJwsLC1977TW4M7zxxhv19fU9PT2q\n127V6z58B/7+NOh1f9++fVKp9O9//zsAAP5CnJeXBy/Q2LUbmjt37rVr16RSKbbjHTlyZIT3\nG7Ct6r3KBx98AG+BamtrY2NjX6ktdp8DjyMYzOXLl1ksFjy0Dx061NjY+MYb7wH/mwAAIABJ\nREFUb8DpIyIiCgoKZttpcDKVlpauWLECruceFUPd4iKIBsHzs+qO+vXXX+vq6qpd92c57LpQ\nXFys6VhmFNQDGkEQBBkp+NcagUDo6+vr7++Hb2pra69YsYLFYmGTsdlsWBkZZh+MjY1jYmJg\n/x0nJyd9fX2YyAYADFOSlUAgLF26VLWfEWw7MCQymezs7Lxz505YnnIY3t7eRCJxyZIlsMa0\nsbHxnDlzcDhcQkICbBsQEECj0V577TXVHtlOTk6mpqYkEgkAQCKR9PX1o6Oj7ezs1GYeEBAA\n/0On09evX+/l5YW1DQgISExMlMlk2travr6+2AOwBAIBj8fDLk44HC4iIuKV+kE/fPgwLS0t\nIyOjt7cXh8NNRH1bmUwmlUrhdh/3mSPIoOB5g0Ih4/FyAKoB+BaAJwBEADDy8i8dAKQBcAuA\najyeQaGQ4fE7y9nZ2b311luDnictLCywwhq+vr6JiYnBwcGqE9jb2yckJDCZzIFV7y0tLd98\n800ajYY9nhIWFqZ6OrK1tVU9o8Jzu52dnaurq66u7ptvvrlkyRLVGWpra8Ok81Ax0+l0DoeD\nTkpTWUdHx40bN27duvXkyROhUPjZZ58tXbo0IiJi5EdiXV1dWlpaenp6c3OzUqnU0tKCWVcS\niWRlZbVx40Z4ufTw8DAwMNDS0oI/dby0Lseg130CgbB8+XLYod7CwsLS0pJAIBAIBOzajbWF\nz2xhc1uwYMGhQ4cGXdDA+w0XFxccDofdqwQEBMDDhE6nr1mzxt3dfeRtMXQ63dXVFf7fzc3t\nvffeE4vFAICFCxfq6+uvXr0a9sa1tbW1srJCp8Fxd/v27T///BMAgMfjfX197e3trays0GAD\nyBQHu8iovhMQELBv3z6JRAIrBJqamkZGRjo4OGgoQGQmQwloBEEQ5NWQyWR9fX0CgdDe3q6v\nr6+trb18+fLly5cPNT2dTl+9ejX8f19fn0QikcvlBgYG2trawyyFQCAsWbJELTExFDs7u4EZ\n4aEsXLhw4cKFas1VXw6/3Ff6vpCPj89QD7WRyWQDA4OKioqamhoGg+Hs7AwAIBAIVCp10L8V\nZTIZ7FMDACgqKvrxxx9FIhGDwUB/8IwLiUQCfxqBiEQilUqFWY9h9Pb2SiQS7CWBQNDW1h7m\nSWeZTCaRSHA4HJVKfWldCNg5RXXmavvG6GKePhoBOAeACACX/7yjDcBQp44eAOC6qgfgAoGQ\nRqVSdXR00Lg60AjPk4Oer4Zpa2FhERcXp/rOwHOsKrVzu1rb0cWMaJxUKpVIJEqlEr6sr6+/\nfv36H3/8Ac91P//8M5FIhL+/wlPfoL8fKJVKiUQCq8FUV1dfunTp4cOHeDxe7WcPY2PjdevW\nqbV9pXsGMLLr/jDXbiggIAD77XlQL73fAADATPHo2qpycnJycnJSfWf4exVk7P7888+jR49S\nqVQOh5OUlBQeHq7piBBkNOC57pNPPjlx4oREInFwcHBxcUEJaGQizJi/TxAEQZBJAgcT4/P5\n+/btW7169Sv9eVNSUnLx4kUymXzo0CFUaAwA4OPjk5SUJJVKFQrF06dPd+3aBQCYM2fOunXr\nBr3zEwqFFy9ehLUvmUzm+++/TyKR8Hg8WpnjIi0t7fr169hLd3f3mJgYKyur4VtlZ2dfvHgR\neybA0tIyJiaGzWYPNb1AIDh//jydTo+JiTExMRl+5lwu97fffsNeDtw3RhfzdMMD4BAAsF7h\nGgCGOudwAYDrqhuAEhaLFRsbGx4ePszYegiCjIv8/PyLFy++ePECvtTS0po7d+6cOXMuXLhA\np9PXrVsnlUr37dunUChoNFpsbKxaF3tILpenpqamp6cDAPT09FasWLFx40YAgLOzM+q9i0xN\nVCp13bp1y5cvhx0IEGT6ioyMZDAY58+f7+jo0HQsyIyFEtAIgiDIq2GxWCwW65dffrly5crw\nfX8G6ujo4PF4ISEhGzZsQA9QAwDs7e3hE7L9/f3JyckFBQUAALFY7Obmho0JpurZs2cPHz4s\nLi4GAKxcuXLNmjVqA4KNl7a2NqFQiMfjXVxcJmgRUwr8vo8ePYKbAOrr63N1dcXhcEwmc9A+\nxWKxWCgUFhcXFxYW9vX1YW/Ch6AH6uvrEwqF9+/fv3Tpkp2d3WuvvTZMArq9vX1gSHDfgHVy\nX7x4MYqYpyM9vQ4msxRmoJqb7Z8/txl0MiOjRyYm+UKhUCQSAQCMjf0iIyNHPbwngiBDkclk\nQqFQNUlRXFxcUFCAJaAtLCxWr16tp6eXkZHBZDLXrFmTm5t75coVqVSqo6Pj6uo6sKAWnG1R\nURE8oXE4nDfffNPT0xMA0NbWxufzW1tb5XJ5fX19VVUVk8lUHUELQSYZdo/E4XCWL18eHR2t\n6YgQZKy8vb3t7e2bmpoKCwufP39eW1vLZDLRE5bI+Johf5kgCIIgkywoKMjIyGjOnDmv1IrN\nZu/du9fY2HjGpMbGC4FAiI6Onjt3LgCgqanp2rVrTU1NAyczNDQMCQnZtGkTAMDc3JxGo01Q\nPDk5OadPn/b19U1KSlJ7qndGwr5vcnIy9qZAIPjll18eP368bds2rL6tqtLS0tOnT5uYmCQl\nJWG7tI6OzlBrrKOj4+zZs3/88YdAIHhpYYHCwsJTp045OjqqhgT3jbKysq1bt+bn548i5unI\n3d1969atZmZmAIAff8y5eHH3oJOFhvpu2nT09OnTv//+++QGiCCzS09Pz8WLF2FXZcjV1XXP\nnj1YZS1tbW0nJ6fa2lpsAnjPoFAoent77969e+3atYGzJRAIISEh8IRGp9OxsSXg+bmsrAwu\nt76+fuvWrei5H0SDVO+RUN9nZMbQ1taOiYlxcXHJysoqLS3dtm2bra2tpoNCZhT09z+CIAgy\nGrAf9Ku2MjU1fekYQbMT7Gvs4uICACgvLy8uLm5oaBg4GY1G8/b29vX1neh46urqbt++7e/v\nP0tqGiqVSoVCYW9vv2zZMuzN27dvf/PNN3g8Hiuvoaa5uTkrK4vNZoeEhDg6Oo6kWC1cEFYp\n9aVT2tjYqIZ0//79U6dOicXinp6e0cU89SkUisrKyoKCgubmZvgODofD4/EsFsvR0fHu3bsA\n3FJrYmZm5uTktHSpzdKlS9PT07W0tBwdHZ2dnSsrK6lUqqOj48Ch82aDqqqq27dvazqKSfXi\nxYvGxkZNRzHDVVVVlZSU3Lp1Kzc318nJCZa4MTc3DwsLw3706unpqays5PP58MSopaXFZDLh\nPUNnZ2d1dXVpaSkAoK2trbKyUk9Pz9HRkUQiEQgEZ2dn1RMaBM91c+bMgb95j/AUiiATobm5\nuaKiory8XCaT2dvbz5J7JGSWIJPJbDZbV1e3tLT0+fPnubm53d3djo6Ow4xrgiCvBCWgEQRB\nEGRqsba2jo+PVx3XDqOlpQX7gSLjKygoyM7ObnS/juTk5Dx9+vS///u/X5qA1tfXj4uLs7W1\nVe2zPBQfHx9zc3MGgzHUBGOJeSqDdWDPnDmDPQTA4/GOHDmyefNmWCR9IG9v7927dzs6OsKX\n2Hr++eefi4uL//GPf8zOBPSNGzcKCws1HcWkksvlTU1N5ubmmg5kJrtx48b333/f1NTEZDK3\nbt0aFBQEADAwMFB9IkckEp09e7ampmbDhg3e3t6q5zEqlRoTEwNH/MvNzf38889dXFx27dpl\nYGCAw+EGvcDBcx2WdEbXQUSDeDxecnKym5vbJ598MuOGW0AQAABgMpnbtm3Ly8s7f/48n8/f\ntWsXSkAj4wUloBEEQRBkaqHRaLAwNDJpjIyMjIyMsJft7e0FBQWlpaXz58/ncDhD1Su3trZ+\n/fXXW1tbAQANDQ3nz5/38fEZZtxwMpnMYrGamppGkg81MDAYvvq2WswzhlKpbGxs5PP52Dud\nnZ2dnZ0NDQ1DdXs0MDBwc3Nramq6ceOGnp7e+vXr58+fD3ORSqUSK889ezg7O2/atGn69oIf\nI0tLSwsLC01HMWOZm5t7eHhIpVItLS1bW1sPD4+B0/T39wsEgsbGRjMzMxsbG9WPiESilZUV\nzNwJhUItLS14/A5zNpup5zpkOurs7OTz+fb29m5ubqg8LjIjaWlp2dnZVVdX19XVGRkZyeVy\nTUeEzBwoAY0gCIIgCPJ/CIXC06dP9/b27tmzx8PDY6ha22w2287OTqFQAAC++OKLAwcOfPzx\nx8MkoJEJxeVyjx49umfPns2bN9NotKKiIk1HpDFBQUFw9LbZiUAgTFx9fCQiIoLD4Rw4cIDH\n42k6FgRBEARBpg2UgEYQBEEQBPm3np6ezMzM9PT0R48esVgsXV1dXV3doSamUChY5+j58+cr\nFIrq6uoffvghNDR0JPWgkYHy8vK4XO6ghSMePnyYnJycl5c38KPS0tKvvvoqPz+/ra2NQCAM\nU7dkltDW1saGg0OQ8UWj0SwsLFavXm1nZ5efny8Wi0NDQ01MTOCncrmcy+Xm5+e7uLiEhYWh\nrugIoqawsDAzM1Mmk8GXxsbGoaGhOByOy+UymczQ0NDJrBlVU1OjkeW+qp6eHi6XC3/0srW1\nVT3nTBq4ruBDbwEBAQsWLBh0ssLCQi6XGxwcHBAQMI5L5/F4XC7X09NzqOUiyLSAEtAIgiAI\ngiD/1tPTk5qa+uOPPwIA7OzsZDKZTCYjEAg4HG74hkuXLvX19d29e/evv/5qYWEx7glopVIJ\ngyESiUTiIPdvCoVCLpfL5fKhJpgWsrKy9u/fP+hHeXl5g2afAQBFRUVFRUV4PF5bWxuPx8M3\ncTgciUSC4zGOcCMiCDISVCp17dq1rq6uH3zwQW5uroODA4PBgIeYXC6/du3a77//npycvGbN\nGk1HiqiDl4lBP8Lj8eg8OQx4kVUoFCQSaXQXWYVCIZPJcnNzk5KSent74Zuurq5MJhMA8OWX\nX3p7e/v5+Y0xEaxUKmGcRCIRuyAOpbq6+ttvv507d+7Ylzuhenp6UlJSzpw5I5fLFy1a5OLi\nMjkJaLgylUolgUCA66q4uFgul+/du3eoRPCDBw8+/vjjDz/8cHwT0EVFRZ9++umWLVtQAhqZ\n1qbr3ycIgiAIgiDjjkql/u1vf3N3dwcASCSS8+fPl5WVrVq1SkdHR7OBtbe3p6am8vn85cuX\nu7m5GRoaqk3Q3NycmpoqEAhiY2M5HM4sLEEQFhYWFRUVHBwMX7JYrPj4+KqqqpMnT/r7+0dH\nR5NIJM1GiCAzCRyEsLy8/Pz58+Xl5VFRURo/TyIvxeVyr127NuhHISEh6Dw5jLq6upSUlNbW\n1h07dnh7e48iB83j8VJSUuRy+SeffIIl+vv6+u7du8fn87Fxd8dILpdfvXqVx+NFR0e/tBaT\nk5PTP/7xD2Nj4yl+zwAHLzU2Nk5JSZnM5UokktTU1Lq6ulWrVsF19ccff1y9enWYJkFBQUeP\nHvXz8xvfSHx8fD766CN4d4og0xdKQCMIgiAIgvyblpbWokWLFi1aBAC4ffv27t27m5ubIyIi\nNJhYUSqVIpGouro6Kyurs7MzJibG29tbdQK5XN7e3s7n8zMzMykUyubNm11cXDQVrQZ5e3vH\nx8djL5lM5tq1a69cubJ7926pVLpixQqUWEGQcaSrq+vv79/X15eenv7ixQt3d3c6nd7f308i\nkSwtLadyb8rZpqenRyQSwVFJ8/Pzf//990EnIxAIHA6HTCbj8XgGg4F+TlAjFAp/++03JpP5\n+eefqw2t+VJSqVQkEhUXF9+8eXPp0qU7duzA6ndVVFQcPnz4/v37nZ2d4xKnQqHIysr6/fff\n3d3dX5qAtra2Xr9+/bgsd0JpaWktXrzYzMxs0ApdE0cqlaanpxcUFHh7ey9ZsmT9+vV9fX23\nbt0apgmHw+FwOOMeiaurq6ur67jPFkEmGUpAIwiCIAiCTF0ymezq1at//vnn3LlzORzOwL97\nJRLJr7/+WlhYGBIS4unpaWZmpokwEQSZXYRC4dmzZ4VCYWxsbHt7+2effSaVSvF4vKenZ2Ji\nooeHh6YDRP6tsrLy7NmzAoEAAODi4pKcnDzoZFVVVR9++KFcLtfR0dm8eXNoaOjkhjmTCQSC\nM2fOdHd379y508PDQ7X3NHySwNra+uzZsxqMEEEQZBKgBDSCIAiCIMhY1dXVVVdX6+rqcjgc\nOp0+XrNtaGioqanh8/mdnZ0cDsfX11cgELS1tVlbW2tpaWHLraio6O3t9fHxcXFxqaure/78\nOYvFml4dfltbWwUCQV1d3fjOlsFgzJ07V1tbOz8/387ObpYMiSYUCgUCgVKp1HQg04+2tjaL\nxdLX19d0IFOaTCYTCAQlJSVPnjzR09NbuHBhRUVFRkbG48ePhUJhcHBwZGSkpmOc7eA2ggOm\n8fn8mpqaxsZGAEBYWNhQtbl/++23mzdvSqVSKpXK4/HgQKZ0Ot3a2nqK12eY+kQiUWZmJpPJ\nfPfdd9V+RabT6SEhIWQyuaamZs6cOUQisaGh4dmzZ9gEOjo6LBarv79fIBBIpdKhFmFsbGxt\nbd3S0vL06VOhUCiVSisrK0tLS9XaWllZweugRCIRCARisRhrSyKRFApFXV2dUChUW66+vj6L\nxcIqSg/adqjAsOsRkUhksVjGxsYAgI6Ojrq6OolEAgAwNze3tLSsq6trb2+3trZWrTCm1naY\nNSyVSgUCgUgkAgAwGAwWi9Xe3i4QCCwtLVW/LwBg4P48sC3sn15XV8fn81tbW3t6esrLy62s\nrKytrbFWcF2pxiwSiQauZ0j1+wIAcDgci8WCtb9fvHghEAi6uroAAKampiwWq76+vqWlZfh1\nNb7baFB0Ot3Dw0NPT6+4uNjBwUH1uyPIqKEENIIgCIIgyFilpaVdunRp+fLlb7zxxvB/Jr0S\nLpd76tSp5cuX/+1vf7O1tRUIBMeOHWMwGPHx8fBvG7XlVlZWHj9+3MHB4e9///v0SqIVFBQc\nO3asrKxsfGfLZrMTExO5XO7+/fu3bNkSFxc3vvOfmrKzs48fP97X16fpQKYfOzu7+Ph4f39/\nTQcypcH6+A8fPlyxYoWfn5+ZmZmenl5SUtK//vWvH374QdPRIQD8ZxulpaUBABwdHTds2AAf\njhnmR7jg4GArKyuFQiGRSK5du3bhwgUAwLx58+Lj4+3t7Sct8tnJyclp9+7dNBqNRqNdu3bt\nxIkT2EdsNjs+Pr6tre3YsWPD1ImOjIyMj4/PyMg4ceJEbW1te3v7mTNnBAKBWtsdO3bA66BQ\nKPz+++//+usvrK2+vr5cLk9JSfntt9/UlhsYGJiQkIAlNwdtO1Rg2dnZx44d6+/v19PTS0hI\ngL9OwXuV6upqAEBcXNyWLVtSUlKys7Pj4+NVu96rtR0mByoSic6cOZOZmQkAWLBgQUJCQk5O\nzrFjx7DrPowZADBwfx7YFh4saWlp//u//1tbW9vV1fX999/X1NSolvmC60o15pKSkoHrGVL9\nvgAAEokUHx+/du1aAEBtbe3x48d5PB4A4PXXX09ISEhLS0tNTR1+XY3vNhoU3CezsrKOHj36\n+uuv79ix45WaI8igUAIaQRAEQZDZ7smTJzweT6FQqL7Z1NTk6+sLa2ICABQKBY/Ha2xs9PDw\n0NbWLikpgf1loMbGRnNzczabrVpysa6urqSkxMbGBhvVkMfj/fnnnyKRSKFQ3Lp1KyAggM1m\nEwgEOL1YLC4tLVUqlWw2WywWl5SU3L59Oy8vz8HBwd7evq6urrKyMisry9XVVSqVwpjT09Mf\nPHjg5ORkbW399OnTR48e3b17FwAgk8kmYb2No9bW1r/++qutrW3Uc6isrLxy5cpQH+Xl5S1d\nunTUM5/Kuru7S0tLGxoasHeqqqqMjY3lcrkGo5qmyGRyQUEB7CsKOTo6onGfVJWVlZWUlIjF\nYmtra09PT1iWlEajmZiY1NfXt7W1zZkzR9MxIkAmk1VXV5eVlbm7u9vZ2Xl7e7+0bLGZmRnM\nu7148aK8vLysrIzH4+no6GDdNpGJo6+vj908wKOptLS0qanJ3d2dwWCQSCQtLS1jY+MnT56U\nlJQolUoSieTh4QETsi0tLTwez9HRUSaT0Wg0U1PT1tbWzs5OmHDMzc3t6emh0Wiwv21tbe31\n69fZbDaRSGQwGHg8HmsLl66np6enp8fj8UQikY2Njba2No1Ge/78+dWrV9lstq2tbUlJSUlJ\nSX9/P5yhWCy+ceOGh4eHm5ub2pdqaGjg8XjweqRQKCgUSllZGZlMZrPZZDLZ0NDw8ePHPB7P\nzMzMyMiotbWVRqMVFxfjcDg2m93b2zuwbWVlZUtLi4mJycAVSCAQ9PX1yWQyvJeDPaCNjY1r\na2vhjUFHRwcsg56VldXR0cFmsykUCryvKy4u7u7uhl+np6cnPT3dw8PDw8NDV1fXxMSkublZ\nKpUyGAwGg4HVTqmoqLh69apazKrbaPny5XBKsVgMF0EikeAiAAB4PL6qqurmzZtsNptEIjEY\nDBiJvr6+lZVVY2OjgYHBoOtq4cKF47uNXrpPPnr0qKioyNfXd+QNEWQYKAGNIAiCIMhsl52d\nffjwYbWHW319fXfs2OHh4QGf1pTJZCkpKenp6fv27TMzMzt27JjqYDhbt249ePCggYGB6hwK\nCgoOHjwYExMDE1iwR1JKSkp7ezuBQDh06NCWLVtcXFywBLRQKDx58qRCoUhMTCwvLz948GBN\nTY1MJktNTc3IyAAASKXS9vZ2mPGBMTc3N0skkosXL/7xxx8AgN7eXtW0+KySkZHx8OHDQT96\n8eIF/MtzRoL7FezqCK1aterQoUPwhxPkldTU1Jw4cQL2GoN27tyJEtCq0tLSzp079/bbb69Y\nsYLBYKh+FB4e7uXlpfYmokFMJnP79u1Lly59pY1CpVJjY2MdHR0PHz48cbEhQwkPD3d3dz98\n+PCdO3c2b968atUqAwMDuVy+f//+H3744fHjx/39/VQqdd26dbCayr1797AtFR4ezmazsbbW\n1tbfffcdg8F4++23YS7y9OnT+/fv379//8qVK7dv325ra6u6lYlEYnR0tJOT0+HDh7lc7tdf\nf7148eK33347Ly9v796977777oYNGy5cuFBYWPj222/DpOTNmzePHj26cePGgclNHo938OBB\nX1/fI0eOkEikzs7Ob7/99s6dO/v27fP19d29e7eFhcXTp08zMjJKSkp27NixcuXKEydO3Lt3\nLzExsbW1dWDba9euiUSiQRPQDAZj8+bNdnZ2hw8fhstdu3btkSNHzpw5s2vXLgCAra3t22+/\nDQD47rvvysvL7ezsKBQKvK+7efPmzp073333XQDA3bt3v/3226VLl7q6ukZGRrq5uR08eJDH\n47311luLFy/GjqNBY2az2dg2wgKDPZF7e3t37NiB/TjX39//3XffHTx4MDExMSwsLCEhgcVi\nHTx4MDs7+/Hjx1u3bt27d++g62rctxGCTDKUgEYQBEEQZLazsbGJjIxUy1E6Ozs7OzvDGnwA\nADwe7+bmJpfLzczM9PX1AwMDVYf78/X1HfhwqIWFxZIlS5ydneFLbW1tLy8v7AFJAICbm5vq\nS11dXT8/P4VCoaenB9vCsoBqOByOnp7eoDFD8+bNgxWipxEnJ6etW7eqfd/m5ubs7GwqlRoU\nFKSnp6f6kUgkysnJUSqVQUFBqiUjAQAvXrzIycnp6uoKDg7GOhwBALy9vSf0K0w+uVyek5NT\nWFhIp9Ox/lYAgICAAFtb2+lVBHyKIJPJCxcuVE1wSCSSb7/9NigoiMPhaDCwqaCkpAQeWcuW\nLfP09BxYzIFOp49jBXxk1PLy8v766y8LC4u4uDhfX1/V0+BIEAgEIyMjNpsdExMjEAjS09Nb\nWlqCgoJgVWhkotHpdG1tbT09PSKRaGJiAu80njx5kp2djcfj33rrrby8vPLy8uLiYnNz8+Dg\nYB8fn7i4OEtLSy0tLR0dHSqVirVlMBgikai+vv7WrVvwQpmfn19XV9fV1UUmk5lMpqmpqeqV\nAofDGRoaWlpaUqlUAwODoKCgkJAQBweHgoICWFBYoVA8f/68oqIiKyurubkZAPDgwYMnT560\nt7cP/CJMJjM8PFyhUNy8eROHw0kkkkePHnV1dfX29mpra1tYWBgZGeHxeDs7u+DgYG9vbyaT\n2d3d3dTUJJVKJRJJfX29p6cni8Uik8nd3d1BQUGdnZ3Z2dmDrjRsXVEoFCaTGRwcDK+DCoUC\nFqYPDQ11d3d/9uxZa2vr8+fPsSfeRCJRVVXVvXv3Xrx4AQAoLi6uqqry8fEBABgYGCiVSh0d\nHRKJZGpqqnoc2dvbD4wZVlBRuyHp7++HK8rY2Bh7CqGvr6+/v7++vl4ikWhpaZmZmZmYmBCJ\nRBsbm+DgYF9fX0tLy97e3oaGBrV1Ne7bCEEmGUpAIwiCIAgy2wUFBfn5+am9icfjVYeqJxAI\n0dHRK1asIJFIOBwuPj5edZA31SkxPj4+HA4H6+BsYGAQFxe3ceNG1XmqNmQymVu3boVzYzKZ\nQyW8YGCDxoxNMO2Sj3Bdqb354MGDZ8+eMZnMvXv32traqn5UVlYG/4bctWsXm81W/ejZs2fv\nv/9+Q0ODWjHfQbfRtCaXy69evXrt2rVPPvkkKioKe19tv0JGDh6DqtV4vvjiiw8++ODIkSMo\nAZ2Tk7N37949e/bs3bt32p1hZpUbN26cOnXq0KFDGzZsGPWpAB4Ld+7c+fDDD/l8vqenJ0pA\naxCPxzt8+PCSJUsOHTp08ODBwsLCCxcuPH782MTEJDQ0dNeuXWp3LGpty8vLcTgcAEAmk6n9\nmjsUFosVHx8fGBg48GCHT2vBfKhcLh+q5BebzXZxcTl58uS+ffvgmAT9/f0uLi5qk4WFhSUl\nJRGJxPr6+qGCgT2+XV1dW1paXho5HPvBzs4O3n1RqdSYmJi4uDgikag6uiNGJBKdPXv2p59+\nAgAoFIqRPC81kphHISgo6OjRo1QqtbOzcyTTj30bIcgkQ/emCIIgCIJFce07AAAgAElEQVTM\ndkQi8aV/peNwOBKJhN3lw0HSh0cgELDsM5zD8FUR8Hi86gSqbQedeCYlGdXWFUShUPB4PB6P\np1Aoan264UfwP4N+BNf2tOsJPhKFhYU3btyAhVn19PT++7//m8PhzMhvOvnUjkEAwMKFC5VK\nZUtLS2JiIgDAysoqMjJyHAcaneLq6urS0tLq6uoAACQSac+ePQsXLkQ72xQnk8mkUik8c456\nJvBYIBKJ/f39g6bkVPcNjLa2dmRk5Mx73GSiVVVV3bhxw9zcPCIigkajEQiE5cuXm5iYlJSU\nPH/+PCIiQqFQSKVSpVKppaUVGRkJ6zsrFIqsrCwulwsA8PLygm0HztzZ2TkyMhIrEQYfxnpp\nSHAHGPSmxdjYODIy0sHBAXsnMDBw4GR8Pj8tLa2rq+uDDz4AAPT09KSlpanVOgMAEInEl55S\n4A0Ydt1/aeQUCkU1JwvbDjW9vr5+RESEaqklb2/v4W/ARhLzKBAIBC0trZHf2o19GyHIJJs5\nf7cgCIIgCIIgyIzH4/G+/PLL7u5uOp2elJS0fft2TUc0kwUEBHh7ex84cOC7776TSCReXl4c\nDmf2JKBbWlpSU1NhUWxYmRRln6ey3t5eiUSCw+EMDAzGkn3GkEgkOp1OIpE6OjqoVKq2trZE\nIoE5xOrq6kuXLqlW3u/p6dHW1rayskIJaDVEIlFPT49CoXR2dnZ3d1OpVNgfGQAgk8l6enrK\ny8svXLgwd+7c0NBQmIBesmSJo6Pj7t2779y54+HhoTq3efPmcTgcKpX69OnT/fv3p6enSySS\njRs3Lly4cNAEtJOT0zvvvAPrP8DNR6VSx/J1jI2NY2NjlyxZAgCA5TIG3dkqKiq++eab5cuX\nf/7552QyWSQSPXv2rKCgYCyLngh0On316tWwoHZfX59EIiGRSCPJdE9lI9xGCDLJUAIaQRAE\nQRAEQaaZsLCwmJgYWKoSmVAEAmHVqlVGRkYXL17UdCyTjcViJSQkwMfenZ2dUeWNKS47O/vi\nxYuWlpZwALexzxDmQMvLyz/99NMlS5asWrUqNTU1PT0dAKCnp7dixQrVolKXLl3Kzc0d+0Jn\nHngclZWVwYLy69atww4loVB48eLFhoaG9evXe3p6DppBVpOWlpaZmRkbG+vm5vbWW2/Z2tqO\n/NSEtQ0ODh7991GRn59/8eLFBQsWwATudFdSUnLhwgUOhxMbGztjHjKbYdsImdZmyEGFIAiC\nIAjyUkqlsqmpqbS0VNOBTKqmpqYR1hNEpriuri6hUNjd3e3g4LBo0aK4uDhNRzQrEAgEPz8/\nS0vLxsbGmpoaoVBYV1fHZDKHr6gzM8DnuDUdBTJSfD7/3LlzBw4ciI2NHZcZWlhYWFhYtLe3\nJycnKxQKBweHoqIi2ImVw+G8+eabnp6e2MSVlZUoAT0oeByRyeQ7d+7QaDQ3Nzfs7PHs2bOH\nDx/SaDTY5Vm1FYlEsra2hsPodXR02NrampmZ4XC4hw8f/vTTT3A8ZHNzcy8vr8ePH1taWqpW\njejv76+rq8Pj8UwmU19fv6amBo7x++jRo0ePHi1evLi3t1coFNbW1vb29nZ0dJSXlzs6Ohob\nGzc3N1dUVHR2dkokkqdPn1paWmKD7zU3N1dWVtJoNCsrq+fPn8NbqeLi4oKCAnt7+4HfWk9P\nz8nJiUKhPH78mEgkisXijo4OqVRaW1sL29bX18vl8tbW1rKyMmwpcLl9fX22trZYW/hRVVUV\n/BbV1dUMBoPJZGIf9fX1CYXCp0+fSiSSzs7OiooKOMoiAEAul9fX11dVVWEDR2Pfl8FgmJmZ\n2draisViGFJJSUlhYSEcfhD7IiOMGRbXbmpqUiqVzc3N5eXlTCaTQqHY2Nh0dXXV19djvapl\nMhmZTHZyctLT05NIJPCa0t/fLxKJysrKsE056HLhy4aGhnHZRggyyVACGkEQBEGQ2UIul6em\nphYVFWk6kEnV29vL5/Ox4deR6auiouL06dPa2tp79uxxdXXVdDizC4PB2LRp06NHj65du1ZW\nVrZ9+3ZTU1NNB4UgkyczM1MoFIaEhCQnJwMA6HT67KlFMy7g4Hj3798/cOAANiicoaFhSEiI\nt7c3lh7FqJ5zaDTazp073d3dYWqyp6fn4sWL2dnZAAAWi7V+/XoOh6Pae1okEp07d87T03PF\nihXd3d0nTpyAv0MHBQUlJSU5OzvDQerS09Obmpq6u7s/+uijTZs2bdiwITU19cKFCxUVFVKp\n9Pjx4zU1NViVpxs3bggEgvnz5wcGBmZlZZ09exYA4OrqumfPHjc3t2G+7759++RyeX9/P5/P\n7+zsPHXq1JUrVwAADQ0N3d3dXC5XKBRu3boVDvQqEAiOHz/u4+Ozc+fOmpoa2BbOsKurq7Ky\nEgDwz3/+c/Xq1Vu3bqXT6fCj9vb2s2fPXr9+XSAQNDU1HT58OCYmZtu2bdi6qq+vhy8BAPn5\n+fD7xsXFRUdHz5kz5969e7/99hsAwN7eXnU9Q0KhcCQxw8LcdXV1crn8xo0bjY2N27dv9/f3\n37Zt28OHD3/55Zfnz5/DGRIIhJCQkMTERCcnp9ra2tOnT2dmZopEopycnLa2tjfeeAOWzhh0\nuXAcxZ6ennHZRggyyVACGkEQBEGQWcHW1nbRokUAAIVCoelYJhWZTPbw8HBxcYF/HSHTUVdX\nV0VFRWFhYWdn55w5c8LCwrA/vJHJoa2tPXfuXC0treLiYqFQePfuXXd3d0dHx+HHqkLGS1VV\nVU1NjaajmOr4fP7EXeBgn1BnZ+dly5aNZPrnz59XVlbCLquvytDQ0NHRUVdXF75UKBSVlZVq\nAx6OEA6Hc3Jysra2xt6BnXx7e3tfaT7l5eUdHR1YV9NRMDU1NTU17ejouHfvHraZaDSat7f3\noPVS4Dmnp6fn1KlTTCZz3rx58IdkBweHhQsXgv/czDAYjMDAQDs7O9gKh8M5OzuHhIQAAOh0\nup+fn0gkevDgAZzY3t4+PDwcAFBbW6tUKg0MDAICAmBDuH2VSiWFQsGqTiuVSqVSaWVltXjx\n4v7+fgKBAM97paWl8Hg0Nzcf6nqEfd+7d+8qFAoCgYDlQGEwZmZmMO2uUCjg+IocDgcmyk1M\nTObPn0+hUGBb2IpKpWLDJ6r2UMbi1NPTw9YkbKW2rgwNDQMDA58+fQqb4PF4FxcXAwODioqK\niooKbLnYViYSie7u7o2NjSOJGU5gaWlpaWmJTaCrq+vr64vH44uKimAtIwAAgUBwdnZesGAB\nAEAkEikUCmNjY2NjY+yLDL9cAMB4bSMEmWQoAY0gCIIgyKwQGhrq4uKi6Sg0hkqlDuxghUwX\nQqHw9OnTnZ2dsbGxaj3dkMlkbW0dHx+flZX13XffLVq0aNeuXSgBPTlu3Lhx+vRpTUcx1bW1\ntWFda8ddWFjYu+++O/LrSGVl5eeffw67rL6qwMDAXbt2YQlo+PTSL7/8MopZkUikf/zjH+vX\nr8fe4fF4ycnJMLs3chKJpKmpydnZeRQxqAoKCrKzs8Pyp1paWq96aY6IiFAd5lFHR0d1DgQC\nISoqCpZ4htd9CwuLxMTE/v5+AACWWmUymdu2bVMt1WJiYqLaFtLT02MwGFjMBALBzMyMSqVi\nbQ0MDIa/Hql930HhcDgzMzM9Pb24uLioqKiByx3YRG25DAYDawsZGhoSCARsXWHredeuXfC3\nBxMTk4Ft4XKxmVCp1JiYGNgf+aUxq4HrCv7f0dERWy7WFv6fxWLFx8dLJBKsIZPJHGa5A419\nGyHIpEEJaARBEARBZgUTExPs7w0EmV56e3tramoUCoW1tbWVlZWmw5m9aDSavb19SUnJkydP\nXFxchs+qTC/V1dX5+fmOjo6quS3NEggE+fn5sAttW1sb1vkRGQqfzxcKhRM0c6FQWFhYiL00\nNjb29fUd5qqqp6fn4uKio6MzimXZ29tra2tjL3E4nJWV1eh2ACKRCPuWYvT19d3d3V+1L3Nr\na+u4jKZgZGRkZGQ0kim7urry8/NLSkp8fX3t7e2xNclkMocJHo/Hw8rdqm8O7P2qpaWFdZpW\nNbDtoDEP2nZQI/++AAC1oi4jb0smkwctCDNwXWG/ary0LQCASCRaWVkNf80dSSEaXV3dgcuF\n4DVl4PsvXa6asWwjBJk0KAGNIAiCIAiCIAgyq8G6qBs3bpw6CWgej3f48GFYeOH//b//B0sP\nI8M4ffr0o0ePJmjmmZmZDx48wF76+PgkJSUNk4CGvT6xAr6vhEQiqfbZhD1zly5dOopZAQDU\nun+y2Ww7O7tXrVVSUFBw4MCB0QUwOrCO87Nnz/bs2ePn54c6sSIIMt2hBDSCIAiCIAiCzFit\nra2ZmZmw6iXk7+8Py2KOUE1NDZfLZTKZoaGhVCp14AQVFRVcLlcsFgMAFixYgBUVHWPMSqUy\nNDQUPbgw0eD2bWhoWL169aC1aCeTWCzmcrmwHmt/f/+yZctgojAwMHDk/ShnrdF1Nx4hDocD\nq9ZCRCLx9u3bXC4XAODl5RUWFqY2PZlMJpPJ47JoHA6no6MzXt+OQqFQKJRXbaWvr08kTkby\nJC8vLysrCwCgUCgsLCx8fX0dHR319PRGMav6+vrMzMyGhgYAgJeXV3h4+OhKBhUWFnK5XLlc\nrqWlFR4ezmazsY94PB6Xy/X09FTdNxAEQQaFEtAIgiAIgiAIMkUplUq5XC6TyQgEAoFAwOFw\nr9q2oaHhzJkz6enp2Pu7du0KDAyEMxzJfKqqqr766isvLy8/P79BE9Dl5eVffPHF06dP5XL5\noUOHxp6AbmlpOXfunEKhcHV1RQnoiaNQKORyOZ/P/+abb7y8vI4eParBJC/cXVtaWs6fP5+a\nmgoAiI6O/uyzz+DAa8hI4PF4mPPt6+sb+QE+DLiHKBQKEokUFhZ26NAh7KMHDx7s2bMnLy8P\nAPDWW2/5+/uPrrMzoiY7Oxt2tbaxsTl69Ojq1auHmhJuHQAAgUDA4/EDJ3j27Nnp06dzc3Nl\nMtk777yzcOHC0e0SDx48+Pjjj3t6euh0ur6+vmoCuqio6NNPP92yZQtKQCMI8lIoAY0gCIIg\nCIIgU5REIklNTS0qKgoJCXF2dn6l4apU26o+vd7e3v7+++9HR0ePV8rA3d09MTHxjz/+gHnD\nsWMymVu3blUqlWjkzAnV3NycmpoqEAhiY2M9PT01+4y/XC6/evVqbm6up6cnHAZtzpw5qgOC\nIS8VFBR05MiRlpaWAwcOrFq1ys/Pb4wzrKysTE1N7erq2rNnz7x581Q/goOnvf766wAAsVj8\n4Ycf5ubmjnFxCAAgNDQUVpvR09Pz8PAYZsrm5uaUlBQAQFRU1MDCzQAAGxub+Ph4e3v7MZ6Z\ng4KCjh49+vvvvxcUFKh95OPj89FHH7m7u49l/giCzBIoAY0gCIIgCILMHAQCwcTERC6Xj+Ih\n6ylIKpWmp6cXFBQkJycvW7ZsXNoePXr0m2++sbW1fWkCuq+vr729XSwWGxsba2lpNTQ0EAgE\nAwMDtcns7e3t7e27urquXbv2ShEOxdDQMCoqalxmhQxKLpe3t7fz+fzMzEwKhbJ582YXFxcN\nxiMWi1taWnJzcx88eJCYmBgZGanBYKYvDofD4XASExNPnjzp7Ow89gR0XV3dL7/84uXl9e67\n76r1jmcymWvXroX/P3PmzE8//SSVSq2trSe0DMhs4OPj4+PjM5Ip29raYGY5ODh40AS0mZnZ\n2rVrCQRCRkbGWEKC+1VjY+PABLSrq6urq+tYZo4gyOyBEtAIgiAIgiDIzGFgYLBp06aenh70\n5P7YCYXCs2fPCoXC2NjY9vb2zz77LCIiYuPGjZqOCxkriURy4cIF2Dve09NT4z3NuVzu+fPn\nPT09ExMTh+/1iUxBsOe1QqEgk8lo8yEIgiCDQgloBEEQBEEQZOagUqljr0E883R0dNTV1Ukk\nEgCATCbz8/NjMpkvbdXZ2Zmdna1QKLZv3/7w4cNbt25ZWVmNcIkSiUQgEMCRCY2Nja2trUkk\nkkKhqKurEwqFAAAdHR0Wi9Xf3y8QCPT19VksFh6Pl8lkAoGgtbUVAECn062trWFdiIaGhmfP\nngEAKBSKtbU1mUwWCARkMpnFYmFd3YdqO+4YDMbcuXO1tbXz8/Pt7OwG7Xs4ldXV1VVXV1dW\nVvb29vr4+EyF46WioiI1NTU4OBj1fR47KysrT0/Pzs7O4uJiFoulr68/ipnA47exsdHe3n7O\nnDnDj78Hn4EYbbwz34sXLwQCQVdXFwDA1NSUxWLV19e3tLSwWCxjY2Pwn/MzjUaD50nYSiqV\nCgQCkUgEAGAwGAPPdcXFxfAEW1JSAtu2tLSonicNDQ3VIqmrq2tsbAQAaGtrq+0b2DkWgudn\nXV3dob6U6jXF3Nzc2tpaLWYI+76qy4WRYN8XXhfa29sHjRlBkBkDJaARBEEQBEEQZIarrKw8\nfvx4dXU1ACAsLGwSxnYTCoWnTp26f/8+ACAyMjI+Pl5fX18ul6ekpPz2228AADc3t4SEhLa2\ntmPHjgUGBsbHx1MoFIlEcv78+bS0NADAvHnzYAFTAACXyz1x4gQAwMzMLD4+3tjY+NixYwwG\nIyEhAeu9O1Tbccdms/fv38/lcvfv379ly5a4uLiJWMrESUtLu3Tp0ooVK958802YDEJmksjI\nSAcHh2vXrv3111/x8fH+/v6jmAk8fkUi0YYNGzw8PDRbH3y6EwgEx44d4/F4AIDXX389Pj4+\nLS0tNTU1ISEB/uICz8+Ojo7wPAlbiUSiM2fOZGZmAgAWLFgw8Fx36dKl2tpaAEBycvKaNWvi\n4+MzMjK+++478J/zZGhoqFokaWlpZ8+eBQDY2dklJCSo1vXG2kJsNjs+/v+zd+dxTV1p48BP\n9pUtbEGWAErCFkAgVUEUpGqxUpcuqKM402I/YnmdqfJai44fXqsWrXU6U0fbynzGrVXaacVq\nwapAUdAiKEtAhIhA2IJAAggJkO33x3mbX162oiJBfL5/kZN77nnuTe6NPjl5ToLxeoODGH+m\nxMbGbty4cVDM2Ouvv7558+ZB4yKEjI8Xfy7k5eUNGzMAYMqABDQAAAAAAABTHJVKtba2xlPw\nCARCa2srnnk3djweb+nSpRQKJT093dfXd5Tc7sDAQFlZWVlZ2cDAAJ5n3dXVlZmZKRQKBQKB\nubm5ubm5WCxub293d3dnMBgsFqu9vf3HH3/08/ObNm2ahYUFk8kUi8VsNhtPr0MIsVgsOzu7\n8vLy+/fvu7u7e3h4IIRUKtWVK1f8/PyEQuG9e/fKysq6urrwiGq1Ojc3t7OzUygUjns1cGtr\na2tr65s3bxYUFBiv7jj51dTUiMXi5ubmadOm+fn5BQQEmDoiVF9ff/HiRbVavXz58unTp5s6\nnKkAT1w9ffr0tWvX3NzcNBqNUCi0sLAYY3d8/ebl5eXk5Nja2np4eODLDTwxKpXK4XB0Op1Y\nLLa0tHR0dGxubraysqqoqOjr60MItbS0UCgUw33S29tbLBaXlpb29vbiG5rhXufn50ckEgkE\ngoWFhY2NTUtLC0LIxsYG962rq8Pbs1is0tJSAoFgyCA/ePAgPT29ubkZb0ClUgsLCwcGBoRC\nYWdnp1gsNvQ1uHHjRm9vr1AoHPbrB/yZcvfuXbFYHB4ejo/OOObm5maxWBwYGKjX683MzDgc\njlgsbmxsdHd3t7e3NxwvjUbT6XRtbW3GMcM8aACmJEhAAwAAAAAAMMUJBILExES1Wo0Q+uab\nb7Zt25aUlPRYE4RFItH06dNPnz79u31xfeHbt2/Hx8fjGXaXLl1KSUlZs2aNj4/P8uXLBQLB\nvn37srKy/vGPfyxcuHDTpk03b97csWPHn//8540bN65evZrP5+/bt894n5GRkb6+vvv27Tt9\n+vSJEyeCg4M3bdokl8uPHDmyePFiLy+vjIyMU6dObdq06b333kMIFRYWfvHFF5WVle7u7lNj\nOcpxkZeXt2/fvnXr1u3Zs4fD4Zg6HIQQKiwsrKmpWbt27YEDByZJSFOGTCb76quv6urqkpKS\nxp6AxtfvmTNn5HL5435NBYbF4/E2b97M4/H27NmTl5dXUVGxYcOGDz/88MiRI//85z8RQiKR\naOPGjRKJBN8n+Xz+uXPnLl26FB8f/5e//AUhdO3aNXyv8/b2plKpTCYT3yf37t2LEEpMTKyr\nq0tJSYmOjj506BBCSCaTHT169Pr160lJSTiGvLy8u3fvxsXF4Q1qa2uPHDny66+/JiUlVVRU\n7Nu3b8mSJfgprLy8/IsvviguLt65c+ewCWj8meLo6PjgwQOEkEajGRTzpUuX9uzZgzdesmSJ\nj4/Pnj17fvzxx6+++iosLMxwvF1dXRQKZePGja+99pohZkhAAzAlQQIaAAAAAABMNTKZLC8v\nj8lkhoaGjj3zMoUxGAxDqWIikVhXV9fd3T3Gvg0NDWfOnMHdCwoKfrcvhULx9/fX6/W1tbUP\nHz7EvWpqahQKBYFAsLa2dnJyYjKZVlZWoaGhYWFhHh4eRUVFUqm0q6uLRCLZ2Ng4OjoyGAyd\nTmfYp4WFBYPBMDc3ZzKZQUFBCxYs8Pb2LikpkclkHR0der1eoVDU1NTk5+drNBqE0L179+7d\nu+fs7Gy8kxcTvhZw3W2FQrFo0SKRSIQLtk4Gvb29vb29Op0OVg0dRzQaLTIyks1mI4RYLFZG\nRkZWVhZCKDAwMCQkZNguZWVl+fn5Wq1Wq9XSaLQVK1YghDw9PSEV+PRoNJqDg4OdnR2ZTHZ1\ndQ0NDRWJRE5OTn19fY8ePQoNDZ0/f76np2dDQ0NTU5NCoUAIyeVyiURy/fr1R48eIYRKS0sl\nEklwcDDeoeE+SafTEULTpk2ztLSMiooikUgXL15ECHV0dJSVlTEYjP7+ftzF1dV17ty5IpEI\nX2g9PT1dXV1dXV1qtbqnp0cqlQ66Bpubm+VyOZVKxXfUofBnio2NDZFIxC2GmFksVmho6OzZ\ns9955x0fHx8ikWhlZaXX69lstpmZ2axZs4yPFwcWFBTE5XJ7e3tbWloMMQMAphhIQAMAAAAA\ngKmmvr7+8OHDXC7Xy8sLEtBPqbq6+tChQwQCASGk1WrxH6NgMpmrVq3y8fHZtWvX1atXca+h\nWQwej5eQkBASEmJYdGssrKys1q1b9/rrr1MolJKSEuOn8MxNXGBap9ONlDd50eBrARfj3rBh\nw0cffYTzkmAKw9fgm2++iRDKzs7+61//WlFRgRBKTEwcKQGdn5//4Ycf9vX1WVlZ7d27d82a\nNQghIpE4+vKD4HGFhoZ+/PHHbDYbf43H5XLj4uJeeeWVoedZLpefPHny9OnTCCGdTod/vzIS\nkUgUEBBw6NChxMREhJBer8eLzRqPm5KSwmQyx/+QhsR8//59JycnkUjk5eVFJBJJJJJhAy6X\nu2HDhkWLFhmOd8GCBbt37yaTyY2Njc80NgCAycHHCQAAAAAAmGr0ev3AwMDAwIBerzd1LJOX\nQqHIzMwsLy83tMyePTsqKopCoSiVyoyMjJKSktDQ0Hnz5g3q2NHR8cknn0RFRfn6+g7drUql\nwn1nzZqFs1137tzJzMwctBmBQKBSqVQq9bFixr2GrarBYDCWLFkSGBhoaPHz83vWCZfJDL++\nlZWVkZGRixYtQggFBQWx2exJlVIMDAyMioqKjIw0dSBTCoFAoFAo+KsdT0/P+Ph4/FuEgYEB\nQ02GQSgUyrZt2xBCDAYjODgYT60F445EItHpdMM1OMptEE9qNr7HBgUFGSdzjZWUlGRmZmo0\nml27dqHfrv1Rxh13JBJp6dKluPqzVqv96aeffvzxR4TQ7NmzlyxZMsrxkslkeLMB8IKYRP/4\nAAAAAAAAYFyQyWRzc3Majdbd3d3b28tkMn933u4L6NGjR5cvX8ZpAkyj0SxatIhCofT19V28\neLGoqOjgwYOvvPKKca+BgYHExMQTJ064ubkNm4Ae2vf48eO//PLLMz4aRKfTly5d+sc//hEh\npFarlUolzrk863EnG5VKpVKpEEKNjY0XL15sb2/fs2cPLsY9CQmFwr/85S82NjamDmRSw+9n\nrVZraGEymWN8b7u7u7u7u+O/U1JS/ud//sfwFIlEYjKZer1eqVTGx8cfPHhw4q+Xvr4+pVLJ\nYDAYDMYEDz3JWVhYrFy58o033kAIDQwMKJVKCoViqHcxiFgs/uyzz959993k5GSEUF1dXW1t\nbXNz84RFSyQSQ0NDX3rpJSaTWVJSsmvXrvz8fPy+GvQJAp4L+J6jVqstLS3h2gTjBRLQAAAA\nAABgqsGLPlVUVHz55ZchISGrVq16rDoPLwgOh7N+/frw8HBDi6en59Q4UVVVVWlpaTweLyYm\nxszMzNThTKjs7Gxch4ROp8+cOdPb2xvKKz/v8Pu5oaEBPySTyTExMQsXLnzK3fJ4vNWrV3d1\ndZ05c+apY3xCeXl5aWlpy5YtW7p0qalimPzKysrOnj3r7++/evXqSfULBgOtVpuenl5cXBwT\nE+Pq6rp582YPDw8Tvq/AU8L3HLVa/cEHHxj/rgiApzEZb14AAAAAAAA8DVtb2yVLllCp1Kys\nLCaT6ePj4+zsbGtra+q4TKC/v7+urs64zoZWq/Xx8bG2tmaz2REREUO7tLa23r9/v7OzE/et\nq6vjcrl4amRbW1tjY2NHR4darZZKpTU1NQ4ODmq1WiaTtbS06PX61tbW6upqFovl7Ozc0dGB\nx21sbNRqtW1tbfhhU1NTd3e3SqV68OCBk5MT/tU2HhdvIJFIenp6dDrd/fv3ORwOl8tVKBRD\nx8W95HJ5RUUFkUjk8/m9vb14D2VlZbdv38aFUJ/t+Z18ZDJZUVERQsjR0XHlypW4+AZ4rnV3\nd1dUVNy6dUsmk1lZWTk5OQ175Y5CoVDIZDJ87RsaPTw8AgMDpVLpsDVtnoBGo5HJZCqVisvl\njvGLn4cPH965c2fSztA3YDAY7u7uVCq1traWSqVyudyRJiMPpY31zOgAACAASURBVFQqZTKZ\nVCpVq9X4fuXi4oKLaRjfY/HGbW1td+/epVKpbm5uXV1dxjc0vJTfoJ339PTcv3+/t7fXw8OD\nSCQa32OVSuWDBw8GBgbc3NxoNNrdu3cNyeuGhgYbGxs2m02n0y0tLXGxZuOPCZlMxuVyXVxc\nKBRKR0eHTCZra2vTarWNjY0SiQTffmUymeHeLhaLMzIyfvnll2nTpjEYDBcXl5kzZ5aXlzs4\nOBAIhGE/UwzHW1FRYXiIY8afC49boAmMo+bm5vPnzwcGBiYmJsIvVMB4gQQ0AAAAAACYmoRC\n4Ycffvjrr7/u2rVr7dq1q1atMnVEJiCTyVJTU9PT0w0tIpEoJSXF09NzpC6ZmZmnTp26d+9e\nd3d3amqqVCrdsGGDm5sbQignJ+df//rXvXv35HL5qVOnpFLpu+++q1Aovvrqq8LCQo1Gk5mZ\nWV9fP2/evJCQkOvXr586dQoh1NTU1Nvbm5OT09TUhBBSqVRVVVV9fX2HDx+ura199913DeNW\nVVUhhHp6eqqqqvR6/aeffrpy5cq4uLhhx8W98vPz29vbw8LCtm/ffu3atQsXLiCEeDzemjVr\n/P39WSzWszqzk1VERISjoyNCiMFgCAQCU4cDxgGfz9+6desPP/yQmpoaERHxzjvvjHL9Dquo\nqCg1NZXP5x88eNDQ2NLScuHChZKSErlcPi5xqlSqtLQ0iUQSFxcXHBw8li6hoaE2NjbTp08f\nlwCeHbxoalFR0dGjR8PDw+Pi4saeHq2vrz927FhOTo5cLsf3q7fffht/M4Tvz/geizfOycmR\nyWRhYWHx8fHXr1/Hv2aYMWNGfHy8r6/v0BrQ1dXVn3766axZs7Zt21ZeXo4XIcT32P7+/sOH\nDwcHB8fHx9fW1u7YscNQxcXa2nr+/PmBgYEODg4sFis5OfnGjRu4L+bg4BAdHR0QEMDhcK5c\nuXLs2LG7d+/i17exsRFHm5qampeX19vbm52dLZVKDffny5cvD4rZ+DPl2LFjdXV1huPNzs6W\nyWRxcXH+/v7ot0VT8eeCvb39E75aAIBJCRLQAAAAAABgarK3t7e3t+/s7Lx+/bpEIsnJyeHz\n+Tg39+LQ6/V6vV6n0xlaXF1dFy9ePHoXEolkmCmJ92D8t0AgwJlN3I737+Tk5OTkhBAikUi+\nvr58Pr+iouLBgwcIIQcHBzxjDodBo9H8/PyMd+js7Pzyyy8PDAzgDZhM5syZMw0bjDSunZ1d\nWFhYa2srQmjGjBkLFiy4f/8+nsTH4XBCQkIMpW+nHolEUltbixBis9l8Pt94hppxzV8wNdjY\n2NjY2EgkEgqF4u7uPvr1O0h7e3t1dbVYLO7r63N1dTUuyFtZWVlaWjqOK7Wq1WqxWFxUVLR8\n+fIxduHxeDweb7wCeHYsLS1nz57d3Nx869YtOzs74zvqWOh0OltbW8OvcPR6PZlM9vX1xWWa\n8f1t2rRpERERXV1dCCFPT8/Zs2dXVVXh7+Ts7OzmzZtnmCaMsdnsoKAg/Pe0adMWLFjQ19d3\n/fp19H/vsbgvjUa7du2aIWwWixUcHIy7m5mZOTo6Pnz4EPfFLCwsZs2a5e3tjX67w0+fPh1/\nT2DYiV6vN9zbje/PeAPjmIf9TDEcr06n0+v1dDrd39+/u7sb/d8PHQDAlAEJaAAAAAAAMJWF\nhoa6u7unpaXt2rVry5YtK1asMHVEE4rL5cbFxYWGhhpafrcUSVRUlCGvgRBis9mGehcRERFe\nXl6Gp5hMpoODg6OjY1JSklqtxo0kEsnBwYHJZG7YsOF3Z52bm5tzOBz8Gg2bcbCysmKxWL87\nLpfLZTKZMTExeF6hccxTUmZmZmpqKkJoxowZW7duhZ9Ig5FUV1cfOnSIy+Vu27Zt0DcTLi4u\nCQkJPB7PeFo0GHf4PCuVSkPLsPcrS0tLR0dHrVZLIBAcHBzMzc1jY2OXLVuGfrtPDtotl8vd\nsGHD6tWr0W/3ycjISOMSK9iw91g6nT7oDjmoL77H4r9H6rtly5a+vr6Rjto45mE/Ux73eAEA\nzztIQAMAAAAAgKkMTx6sqqpqbW29d+/e8ePHEULTpk0LDg5+Ef6LS6fT3dzcDLPhxoLL5Q6a\namdgZ2dnZ2c3tN3CwmJoI67aMRb4NRplgzGO6+zs7OzsPMZBnyNtbW2FhYUPHz40tHR0dOCF\noZycnMzNzU0XGpjsenp6qqur2Wy2QCAYdJWxWKwZM2aEhYU1NTX5+/uTSKTbt2+LxWLDBvg+\nKZfLCwsL+/v7RxrC09NTJBKVlJT8+uuvuNTvlStXiESicV/8EM+oxerr6wsLC3t6ehBCgYGB\nAoGgsLDw/v37g8bl8/nGuUvjawGPO7QqxWSDz/PQ9kH3KwaDMegjafS54XQ6fdA3CiPdJ9FT\n3GNH6Tv29V2H/Ux53OMFADzvIAENAAAAAACmvqioqICAgE8++eTTTz9Fv9XJfRES0GAKwHVR\nb926ZWh5//338axVEon0Ata5BuNIKBTi5fXIZHJmZuZnn31meArfJ8vKypKTkzs6OkbaQ1xc\nXEBAQGZm5t/+9rfe3l6NRoPrGhv3pVKpycnJxglosVi8b98+qVSKENqxY4ezs3NaWtqZM2cG\njbt27VrjBLTxtYDHnfwJaAAAAAgS0AAAAAAA4EXAYrGmTZu2cOFCKysrhBCZTE5PT8cL1hmY\nm5svWLDAeHWv27dv5+TkaDSaJxgxMDBwwYIFZPL//nu7ra0tJycH10QeO6VSaTwh8bmgUqmy\ns7Nx2G5ubhERESNNrBtdbW1tdnZ2W1sbQmj27Nnh4eGGp5qamrKzs/FPzoedfD1hcnNziUTi\n4/Z63PeGRqMJDAw0nsYeEhICZTfAuKDRaDQaDf8tEonWrl2blZUlk8kiIiIWL17M4XD4fD5u\nzM3NRb/dJ3G13+rq6qysLDyLWSQSrVu3ztCXz+enp6drtdqVK1fi6g0tLS1Hjx6NiIjA91hX\nV9eYmJisrKzs7GyVSkWj0ebNm6dUKnNyckpLS48dO8bhcFauXKnVaj/55JOIiAgPD4/s7OyK\nigrDtUCj0f72t7+Fh4fPmTNnYs4Vn8+Pj49XKpUTPC4AE6atrS07O1sikeBVKBkMhqkjAlMH\nJKABAAAAAMALgclkvvHGG2+88QZC6MqVK9u3bx+U23VxceFyucYJ6IKCgt27d49S5nIUmzZt\nmjdvniHJ+PDhw1OnTv3888+Pux+tVmtc/vixkMlkCoVCIBCerPuw9Hq9VqvV6XRkMnnY3KtK\npTp37tyJEye0Wu3LL7/s5eX1ZAno+/fvHzlypLS0VKvVfvDBB8YJ6MbGxtTUVHt7+8DAQNMm\noLOysnJych631+O+N2bNmnXgwAHIdoFnbfHixSKRqLOzs6io6O2338YrFtrZ2QmFQgqFcuPG\nDa1Wa2VlFRMT8/rrr5NIpB9//LG8vBy/kwf1JRKJiYmJAQEBKSkpNjY2AwMD27dv//e//21r\na4vvsb6+vr6+viwW69q1awghJpP55ptvenl5NTU1Xb58+Z///Of69etTUlJSU1N37Nhx8OBB\nGxubr7/+uqGhwXAtHDlyZPv27Xq9fsIuDRyzYdygoCASiQRTsMHUgD/cm5qajh8/TiQSU1JS\nhEKhqYMCUwokoAEAAAAAwAtHIBBs3bq1vb3duNHMzGxQreTQ0NCPP/5Yq9U+wRB+fn6GDCP6\nbTHAhQsXPtZOlErluXPnent7nyAAvMiVYb7heNFqtefPnxeLxcuXLw8ICBhpXFtb2/T09KcZ\nCL9GP/300/nz5wc9xePxEhISmEymyYuoREVFPe5rih7/vcHlcl1dXZ8sQgCeUlFRUXp6OpVK\n3b9/f3p6enFx8cmTJ5ubm1esWOHr65uUlOTq6mr8fh7UNzk5mU6n63S6vLy8MY7I5/OXL18e\nGRk5tLwMLsHx/fffI4TKysqe7OcpTwl/Ljx8+HDXrl0rVqyYNWvWxMcAwLhTKpX4Ap8/f76n\np+fUXsgXmAQkoAEAAAAAwAvHxcVlzZo1v7uZv7+/v7//uIxobW29bNmyx+0ll8vv3btXVFT0\nBCPS6fQnyI3+Lp1Ol5ub++OPP/r6+g6bgMbjOjg4FBcX63S6Jx4Iv0YDAwNDpwZzudw333zz\nifc8jubMmbN58+an3MmTvTcAGKS7u1uhUOB6FwghCoUylm9oent7FQoFXhGOQCAQiUQbGxtb\nW9vu7m6ZTMbhcCorK48dOxYXF/fee+91dXXV19ffvXsXIcTn8319fcPDw83MzEaaBSyVSi9d\numT4qYSTkxOTyfzdkPC1P+zSqQqFIi8vz1AzxMnJaeJ/A4E/F5KSkr744gsbGxsnJycOhwOV\nCsBzTaFQNDQ0XL9+vba2dseOHfPmzTN1RGAKggQ0AAAAAAAAAADwfMvPzz916tTAwAB+6OLi\nsm7dut/tVV5efuLEicDAwNjYWCqVin/B4OXldf369aqqqtjYWMOWZDJ5+fLlvr6+CKGOjo6L\nFy8eP34cIfTKK6/gvkN3jgtDm5ub44dMJnPYtPLY8Xi89evX4wrUGI7HJJRKZVpaWnNz87p1\n62bOnGmqMAB4epmZmRcvXpw5c+bKlSuNry8AxhEkoAEAAAAAAJiCNBpNfX09XsTPwsLCxcVF\nqVTW19fb2dm5uLgghPr7++vr6wcGBng8npmZmaGjVCptbm5GCDEYDB6PZ2lpaXiqqanpwYMH\nMpmsv7+/urq6vLycx+Op1er6+vr+/n6EkLOzs6Oj46BI2tra6uvrNRoNgUDg8XhcLtfwlFwu\nN/RFCJHJZB6PZ2trO9JB4ZjlcjlCiMPh8Hg8PBfSEDNmfLyGca2srAYdr0wmq6+vd3JyGhoz\nAM8RfB2Vl5c3NDSo1WrcSKPR+vr6LCws/Pz8zM3NS0tLPTw88LWPPXr0qL6+vrS0tK6uzt3d\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dVFTU29srEonc3d1pNJqt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\nmpru37+PEGIwGE5OTpaWlo/ag1qtl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1Wu3p6bl48eLX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\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6I/HEQiUU9PT0dHB4/Hq6urGxoaqliZ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\n5nK5CIJ4+OGHaxsM1Mb29/c/99xz1WqVJMmdO3eq1epvfvObDz7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+            "text/plain": [
+              "plot without title"
+            ]
+          },
+          "metadata": {
+            "image/png": {
+              "height": 600,
+              "width": 960
+            }
+          },
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "view_in_pathway(diff_exp_matrix,name_map,'Pantothenate and CoA biosynthesis')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "kernel": "R"
+      },
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Pollyglot",
+      "language": "sos",
+      "name": "sos"
+    },
+    "language_info": {
+      "codemirror_mode": "sos",
+      "file_extension": ".sos",
+      "mimetype": "text/x-sos",
+      "name": "sos",
+      "nbconvert_exporter": "sos_notebook.converter.SoS_Exporter",
+      "pygments_lexer": "sos"
+    },
+    "sos": {
+      "kernels": [
+        [
+          "Pollyglot",
+          "sos",
+          "",
+          "",
+          "sos"
+        ],
+        [
+          "Python3",
+          "python3",
+          "Python3",
+          "#FFD91A",
+          {
+            "name": "ipython",
+            "version": 3
+          }
+        ],
+        [
+          "R",
+          "ir",
+          "R",
+          "#DCDCDA",
+          "r"
+        ]
+      ],
+      "panel": {
+        "displayed": true,
+        "height": 0
+      },
+      "version": "1.0.0"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 2
+}
\ No newline at end of file