diff --git a/code-samples/geoscience-objects/README.md b/code-samples/geoscience-objects/README.md index f2876a8c..77affe8a 100644 --- a/code-samples/geoscience-objects/README.md +++ b/code-samples/geoscience-objects/README.md @@ -6,6 +6,8 @@ The `publish-*` directories contain Jupyter notebooks with sample code for uploa **New users should start with `simplified-object-interactions/`** - This example demonstrates the recommended approach for most users and geologists using the typed objects API (`PointSet`, `Regular3DGrid`, etc.) with the `evo.widgets` extension for rich HTML display. It provides a simpler, more intuitive way to upload and download geoscience objects. +**For geostatistical workflows, see `running-kriging-compute/`** - This example demonstrates a complete workflow including creating pointsets, variogram models, and visualizing them together with Plotly. It also includes WIP sections for kriging estimation using Evo Compute. + The `publish-*` examples use the lower-level `evo-schemas` approach, which offers more control but requires more boilerplate code. ## Requirements diff --git a/code-samples/geoscience-objects/running-kriging-compute/README.md b/code-samples/geoscience-objects/running-kriging-compute/README.md new file mode 100644 index 00000000..103e01bd --- /dev/null +++ b/code-samples/geoscience-objects/running-kriging-compute/README.md @@ -0,0 +1,55 @@ +# Running Kriging Compute + +This example demonstrates a complete geostatistical workflow using the Evo Python SDK: + +1. **Load downhole assay data** as a PointSet +2. **Define a variogram model** for spatial correlation +3. **Visualize** the pointset and variogram together with Plotly +4. **Run kriging estimation** using Evo Compute (WIP) + +## Overview + +The workflow uses the WP_assay.csv dataset containing copper (CU_pct) and gold (AU_gpt) assay values from 55 downhole. We'll: + +- Create a `PointSet` from the CSV data +- Define a nested spherical `Variogram` model for copper grades +- Extract and scale `Ellipsoid` objects for search neighborhoods +- Visualize the data, variogram curves, and anisotropy ellipsoids with Plotly +- Set up kriging estimation parameters (WIP) + +## Dataset Characteristics + +- **8,332 sample points** from 55 downhole +- **Spatial extent**: ~936m (X) × ~1,416m (Y) × ~855m (Z) +- **Coordinate system**: EPSG:32650 (UTM Zone 50N) +- **Target attribute**: CU_pct (copper percentage) + - Mean: 0.95%, Variance: 0.84 + +## Variogram Model + +The variogram uses two nested spherical structures aligned with the dominant orientation of the downhole data: +- **Nugget**: 0.08 (~10% nugget effect) +- **Short-range structure**: Contribution 0.25, ranges 80m × 60m × 40m +- **Long-range structure**: Contribution 0.51, ranges 250m × 180m × 100m +- **Anisotropy**: Dip 70°, Azimuth 15° (NNE strike direction) + +## WIP: Kriging Compute + +The notebook includes work-in-progress sections demonstrating: +- Creating a target `BlockModel` for estimation +- Configuring `KrigingParameters` with search neighborhoods +- Running kriging tasks with `evo.compute` +- Running multiple scenarios in parallel for sensitivity analysis + +## Requirements + +- Python 3.10+ +- Seequent account with Evo entitlement +- Evo application credentials (client ID and redirect URL) + +## Quick Start + +1. Open `running-kriging-compute.ipynb` in Jupyter +2. Update the `client_id` and `redirect_url` with your Evo app credentials +3. Run the cells to create objects and visualize the geostatistical model + diff --git a/code-samples/geoscience-objects/running-kriging-compute/running-kriging-compute.ipynb b/code-samples/geoscience-objects/running-kriging-compute/running-kriging-compute.ipynb new file mode 100644 index 00000000..1ea9e9aa --- /dev/null +++ b/code-samples/geoscience-objects/running-kriging-compute/running-kriging-compute.ipynb @@ -0,0 +1,749 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Running Kriging Compute\n", + "\n", + "This notebook demonstrates a complete geostatistical workflow:\n", + "\n", + "1. Load downhole assay data as a **PointSet**\n", + "2. Define a **Variogram** model for spatial correlation\n", + "3. **Visualize** the pointset and variogram together with Plotly\n", + "4. Run **kriging estimation** using Evo Compute (WIP)\n", + "\n", + "## Requirements\n", + "\n", + "You must have a Seequent account with the Evo entitlement. You'll need:\n", + "- The client ID of your Evo application\n", + "- The callback/redirect URL of your Evo application\n", + "\n", + "To obtain these credentials, refer to the [Apps and tokens guide](https://developer.seequent.com/docs/guides/getting-started/apps-and-tokens)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Authentication\n", + "\n", + "Authenticate using the `ServiceManagerWidget` which handles OAuth login and workspace selection." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from evo.notebooks import ServiceManagerWidget\n", + "\n", + "# Replace with your Evo app credentials\n", + "client_id = \"\"\n", + "redirect_url = \"\"\n", + "\n", + "manager = await ServiceManagerWidget.with_auth_code(\n", + " client_id=client_id,\n", + " redirect_url=redirect_url,\n", + " cache_location=\"./notebook-data\",\n", + ").login()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Load the widgets extension for rich HTML display\n", + "%load_ext evo.widgets" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. Load and Create PointSet from Drill Hole Data\n", + "\n", + "The WP_assay.csv dataset contains:\n", + "- **8,332 sample points** from 55 downholes\n", + "- **Coordinates**: X, Y, Z (EPSG:32650 - UTM Zone 50N)\n", + "- **Attributes**: Hole ID, CU_pct (copper %), AU_gpt (gold g/t), DENSITY" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "# Load the sample assay data\n", + "input_file = \"sample-data/WP_assay.csv\"\n", + "df = pd.read_csv(input_file)\n", + "\n", + "print(f\"Loaded {len(df)} sample points from {df['Hole ID'].nunique()} downholes\")\n", + "print(\"\\nSpatial extent:\")\n", + "print(f\" X: {df['X'].min():.1f} to {df['X'].max():.1f} ({df['X'].max() - df['X'].min():.1f}m)\")\n", + "print(f\" Y: {df['Y'].min():.1f} to {df['Y'].max():.1f} ({df['Y'].max() - df['Y'].min():.1f}m)\")\n", + "print(f\" Z: {df['Z'].min():.1f} to {df['Z'].max():.1f} ({df['Z'].max() - df['Z'].min():.1f}m)\")\n", + "print(\"\\nCopper (CU_pct) statistics:\")\n", + "print(f\" Mean: {df['CU_pct'].mean():.3f}%, Variance: {df['CU_pct'].var():.3f}\")\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from evo.objects.typed import EpsgCode, PointSet, PointSetData\n", + "\n", + "# Prepare the DataFrame with required column names (lowercase x, y, z)\n", + "locations_df = df.rename(columns={\"X\": \"x\", \"Y\": \"y\", \"Z\": \"z\"})\n", + "\n", + "# Create the pointset data\n", + "pointset_data = PointSetData(\n", + " name=\"WP Drill Hole Assays\",\n", + " description=\"Copper and gold assay data from 55 downholes\",\n", + " locations=locations_df,\n", + " coordinate_reference_system=EpsgCode(32650), # UTM Zone 50N\n", + ")\n", + "\n", + "# Create the pointset in Evo\n", + "pointset = await PointSet.create(manager, pointset_data)\n", + "print(f\"Created pointset with {pointset.num_points} points\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Display the pointset with rich HTML formatting\n", + "pointset" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# View available attributes\n", + "pointset.attributes" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 3. Create a Variogram Model\n", + "\n", + "Variograms are geostatistical models that describe spatial correlation structure. They are fundamental to kriging interpolation and resource estimation.\n", + "\n", + "A variogram consists of:\n", + "- **Nugget**: The variance at zero lag (y-intercept), representing measurement error or micro-scale variation\n", + "- **Sill**: The total variance (plateau value)\n", + "- **Structures**: Mathematical models (spherical, exponential, etc.) that define how correlation decreases with distance\n", + "- **Anisotropy**: Directional variation in correlation ranges\n", + "\n", + "We define a nested spherical variogram for the copper grades (CU_pct) with:\n", + "\n", + "- **Sill**: 0.84 (total variance of the copper data)\n", + "- **Nugget**: 0.08 (~10% nugget effect for measurement error)\n", + "- **Two nested structures**:\n", + " - Short-range: 30% contribution, ranges 80m × 60m × 40m\n", + " - Long-range: 60% contribution, ranges 250m × 180m × 100m\n", + "\n", + "The anisotropy is aligned with the dominant NNE-SSW trend of the downholes:\n", + "- Dip azimuth: 15° (strike direction)\n", + "- Dip: 70° (steep dip to the east)\n", + "- Pitch: 0°" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from evo.objects.typed import (\n", + " Ellipsoid,\n", + " EllipsoidRanges,\n", + " Rotation,\n", + " SphericalStructure,\n", + " Variogram,\n", + " VariogramData,\n", + ")\n", + "\n", + "# Define the variogram model for copper grades\n", + "variogram_data = VariogramData(\n", + " name=\"CU_pct Variogram\",\n", + " description=\"Nested spherical variogram for copper grades from WP downholes\",\n", + " sill=0.84, # Total variance (nugget + all contributions must equal sill)\n", + " nugget=0.08, # ~10% nugget effect\n", + " is_rotation_fixed=True, # All structures share the same rotation\n", + " modelling_space=\"data\", # Original units (not normal score transformed)\n", + " data_variance=0.84, # Variance of the input data\n", + " attribute=\"CU_pct\", # The attribute this variogram models\n", + " structures=[\n", + " # Short-range structure (30% of sill variance)\n", + " SphericalStructure(\n", + " contribution=0.25, # nugget(0.08) + 0.25 + 0.51 = 0.84\n", + " anisotropy=Ellipsoid(\n", + " ranges=EllipsoidRanges(\n", + " major=80.0, # 80m in major (along strike)\n", + " semi_major=60.0, # 60m in semi-major (across strike)\n", + " minor=40.0, # 40m in minor (vertical)\n", + " ),\n", + " rotation=Rotation(\n", + " dip=70.0, # Steep dip\n", + " dip_azimuth=15.0, # NNE strike direction\n", + " pitch=0.0,\n", + " ),\n", + " ),\n", + " ),\n", + " # Long-range structure (60% of sill variance)\n", + " SphericalStructure(\n", + " contribution=0.51,\n", + " anisotropy=Ellipsoid(\n", + " ranges=EllipsoidRanges(\n", + " major=250.0, # 250m in major direction\n", + " semi_major=180.0, # 180m in semi-major direction\n", + " minor=100.0, # 100m in minor direction\n", + " ),\n", + " rotation=Rotation(\n", + " dip=70.0,\n", + " dip_azimuth=15.0,\n", + " pitch=0.0,\n", + " ),\n", + " ),\n", + " ),\n", + " ],\n", + ")\n", + "\n", + "# Create the variogram object in Evo\n", + "variogram = await Variogram.create(manager, variogram_data)\n", + "print(f\"Created variogram: {variogram.name}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Display the variogram with rich HTML formatting\n", + "variogram" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Inspecting Variogram Properties" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(f\"Variogram: {variogram.name}\")\n", + "print(f\"Sill: {variogram.sill}\")\n", + "print(f\"Nugget: {variogram.nugget}\")\n", + "print(f\"Number of structures: {len(variogram.structures)}\")\n", + "print(f\"Modelling space: {variogram.modelling_space}\")\n", + "print(f\"Attribute: {variogram.attribute}\")\n", + "\n", + "# Inspect each structure\n", + "for i, struct in enumerate(variogram.structures):\n", + " vtype = struct.get(\"variogram_type\")\n", + " contribution = struct.get(\"contribution\")\n", + " ranges = struct.get(\"anisotropy\", {}).get(\"ellipsoid_ranges\", {})\n", + " print(f\"\\nStructure {i + 1}: {vtype}\")\n", + " print(f\" Contribution: {contribution}\")\n", + " print(\n", + " f\" Ranges: major={ranges.get('major')}m, semi_major={ranges.get('semi_major')}m, minor={ranges.get('minor')}m\"\n", + " )" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4. Visualize Variogram Curves\n", + "\n", + "The `get_principal_directions()` method returns variogram curves for plotting along the three principal axes." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Get variogram curves for the three principal directions\n", + "major, semi_major, minor = variogram.get_principal_directions()\n", + "\n", + "print(f\"Major direction: range={major.range_value}m, sill={major.sill}\")\n", + "print(f\"Semi-major direction: range={semi_major.range_value}m\")\n", + "print(f\"Minor direction: range={minor.range_value}m\")\n", + "print(f\"Points per curve: {len(major.distance)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import plotly.graph_objects as go\n", + "\n", + "# Create variogram curve plot\n", + "fig = go.Figure()\n", + "\n", + "# Add curves for each principal direction\n", + "fig.add_trace(\n", + " go.Scatter(\n", + " x=minor.distance,\n", + " y=minor.semivariance,\n", + " name=f\"Minor (range={minor.range_value:.0f}m)\",\n", + " line=dict(color=\"blue\", width=2),\n", + " )\n", + ")\n", + "\n", + "fig.add_trace(\n", + " go.Scatter(\n", + " x=semi_major.distance,\n", + " y=semi_major.semivariance,\n", + " name=f\"Semi-major (range={semi_major.range_value:.0f}m)\",\n", + " line=dict(color=\"green\", width=2),\n", + " )\n", + ")\n", + "\n", + "fig.add_trace(\n", + " go.Scatter(\n", + " x=major.distance,\n", + " y=major.semivariance,\n", + " name=f\"Major (range={major.range_value:.0f}m)\",\n", + " line=dict(color=\"red\", width=2),\n", + " )\n", + ")\n", + "\n", + "# Add reference lines for nugget and sill\n", + "fig.add_hline(\n", + " y=variogram.nugget,\n", + " line_dash=\"dash\",\n", + " line_color=\"gray\",\n", + " annotation_text=\"Nugget\",\n", + " annotation_position=\"right\",\n", + ")\n", + "fig.add_hline(\n", + " y=variogram.sill,\n", + " line_dash=\"dash\",\n", + " line_color=\"black\",\n", + " annotation_text=\"Sill\",\n", + " annotation_position=\"right\",\n", + ")\n", + "\n", + "fig.update_layout(\n", + " title=\"CU_pct Variogram Model - Principal Directions\",\n", + " xaxis_title=\"Lag Distance (m)\",\n", + " yaxis_title=\"Semivariance γ(h)\",\n", + " legend=dict(yanchor=\"bottom\", y=0.01, xanchor=\"right\", x=0.99),\n", + " template=\"plotly_white\",\n", + ")\n", + "\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 5. Working with Ellipsoids\n", + "\n", + "Ellipsoids represent 3D spatial regions and are used for:\n", + "- **Search neighborhoods** in kriging - defining which samples influence each estimated point\n", + "- **Variogram anisotropy** - visualizing the directional ranges of spatial correlation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Get the ellipsoid from the variogram (uses structure with largest volume by default)\n", + "var_ellipsoid = variogram.get_ellipsoid()\n", + "\n", + "print(\"Variogram ellipsoid ranges:\")\n", + "print(f\" Major: {var_ellipsoid.ranges.major}m\")\n", + "print(f\" Semi-major: {var_ellipsoid.ranges.semi_major}m\")\n", + "print(f\" Minor: {var_ellipsoid.ranges.minor}m\")\n", + "\n", + "# Create a search ellipsoid scaled by 2x (typical for kriging)\n", + "search_ellipsoid = var_ellipsoid.scaled(2.0)\n", + "\n", + "print(f\"\\nSearch ellipsoid (2x): major={search_ellipsoid.ranges.major}m\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6. Visualize PointSet and Variogram Ellipsoid Together\n", + "\n", + "Create a 3D visualization showing:\n", + "- Drill hole sample points colored by copper grade\n", + "- Variogram anisotropy ellipsoid at the data centroid\n", + "- Search ellipsoid (2× variogram range) for kriging" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Get pointset data for visualization\n", + "points_df = await pointset.to_dataframe()\n", + "\n", + "# Calculate centroid for ellipsoid placement\n", + "center = (\n", + " points_df[\"x\"].mean(),\n", + " points_df[\"y\"].mean(),\n", + " points_df[\"z\"].mean(),\n", + ")\n", + "print(f\"Data centroid: ({center[0]:.1f}, {center[1]:.1f}, {center[2]:.1f})\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Generate surface mesh points for visualization\n", + "vx, vy, vz = var_ellipsoid.surface_points(center=center, n_points=25)\n", + "sx, sy, sz = search_ellipsoid.surface_points(center=center, n_points=25)\n", + "\n", + "# Create 3D figure\n", + "fig = go.Figure()\n", + "\n", + "# Add sample points colored by CU_pct\n", + "fig.add_trace(\n", + " go.Scatter3d(\n", + " x=points_df[\"x\"],\n", + " y=points_df[\"y\"],\n", + " z=points_df[\"z\"],\n", + " mode=\"markers\",\n", + " marker=dict(\n", + " size=2,\n", + " color=points_df[\"CU_pct\"],\n", + " colorscale=\"Viridis\",\n", + " colorbar=dict(title=\"CU_pct (%)\", x=1.02),\n", + " cmin=0,\n", + " cmax=3, # Cap at 3% for better color distribution\n", + " ),\n", + " name=\"Drill Hole Samples\",\n", + " hovertemplate=\"X: %{x:.1f}
Y: %{y:.1f}
Z: %{z:.1f}
CU: %{marker.color:.2f}%\",\n", + " )\n", + ")\n", + "\n", + "# Add variogram ellipsoid as semi-transparent mesh\n", + "fig.add_trace(\n", + " go.Mesh3d(\n", + " x=vx,\n", + " y=vy,\n", + " z=vz,\n", + " alphahull=0,\n", + " opacity=0.3,\n", + " color=\"blue\",\n", + " name=f\"Variogram Ellipsoid ({var_ellipsoid.ranges.major:.0f}m)\",\n", + " )\n", + ")\n", + "\n", + "# Add search ellipsoid as semi-transparent mesh\n", + "fig.add_trace(\n", + " go.Mesh3d(\n", + " x=sx,\n", + " y=sy,\n", + " z=sz,\n", + " alphahull=0,\n", + " opacity=0.15,\n", + " color=\"gold\",\n", + " name=f\"Search Ellipsoid (2×, {search_ellipsoid.ranges.major:.0f}m)\",\n", + " )\n", + ")\n", + "\n", + "# Add centroid marker\n", + "fig.add_trace(\n", + " go.Scatter3d(\n", + " x=[center[0]],\n", + " y=[center[1]],\n", + " z=[center[2]],\n", + " mode=\"markers\",\n", + " marker=dict(size=8, color=\"red\", symbol=\"diamond\"),\n", + " name=\"Centroid\",\n", + " )\n", + ")\n", + "\n", + "fig.update_layout(\n", + " title=\"WP Drill Hole Data with Variogram Anisotropy\",\n", + " scene=dict(\n", + " xaxis_title=\"Easting (m)\",\n", + " yaxis_title=\"Northing (m)\",\n", + " zaxis_title=\"Elevation (m)\",\n", + " aspectmode=\"data\",\n", + " ),\n", + " template=\"plotly_white\",\n", + " showlegend=True,\n", + ")\n", + "\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 7. View Objects in Evo\n", + "\n", + "Generate URLs to view the created objects in the Evo Portal and Viewer." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from evo.widgets import get_viewer_url_for_objects\n", + "\n", + "# Generate a viewer URL to see both objects together\n", + "viewer_url = get_viewer_url_for_objects(manager, [pointset, variogram])\n", + "print(f\"View in Evo Viewer: {viewer_url}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "## WIP: Creating Kriging and Compute\n", + "\n", + "The following sections demonstrate how to run kriging estimation using Evo Compute.\n", + "\n", + "**Note:** This functionality is under development. The code below shows the expected API pattern." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### WIP: Create Target Block Model\n", + "\n", + "Create a Block Model to hold the kriging results. The block model defines the estimation grid." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# WIP: Create target block model for kriging estimation\n", + "#\n", + "# from evo.objects.typed import BlockModel, RegularBlockModelData, Point3, Size3i, Size3d\n", + "# from evo.blockmodels import Units\n", + "#\n", + "# # Define block model covering the downhole extent\n", + "# bm_data = RegularBlockModelData(\n", + "# name=\"CU Kriging Estimate\",\n", + "# description=\"Block model with kriged copper grades\",\n", + "# origin=Point3(x=444750, y=492850, z=2350),\n", + "# n_blocks=Size3i(nx=50, ny=75, nz=45), # 50x75x45 blocks\n", + "# block_size=Size3d(dx=20.0, dy=20.0, dz=20.0), # 20m blocks\n", + "# crs=\"EPSG:32650\",\n", + "# size_unit_id=Units.METRES,\n", + "# )\n", + "#\n", + "# block_model = await BlockModel.create_regular(manager, bm_data)\n", + "# print(f\"Created Block Model: {block_model.name}\")\n", + "# print(f\"Bounding Box: {block_model.bounding_box}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### WIP: Define Kriging Parameters\n", + "\n", + "Configure the kriging search neighborhood and estimation parameters." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# WIP: Define kriging parameters\n", + "#\n", + "# from evo.compute.tasks import SearchNeighborhood\n", + "# from evo.compute.tasks.kriging import KrigingParameters\n", + "#\n", + "# # Use the search ellipsoid we created earlier (2x variogram range)\n", + "# params = KrigingParameters(\n", + "# source=pointset.attributes[\"CU_pct\"], # Source attribute\n", + "# target=block_model.attributes[\"CU_estimate\"], # Target attribute\n", + "# variogram=variogram,\n", + "# search=SearchNeighborhood(\n", + "# ellipsoid=search_ellipsoid,\n", + "# max_samples=16, # Maximum samples per estimate\n", + "# min_samples=4, # Minimum samples required\n", + "# ),\n", + "# )\n", + "#\n", + "# print(f\"Kriging source: {params.source}\")\n", + "# print(f\"Search ellipsoid: major={search_ellipsoid.ranges.major}m\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### WIP: Run Kriging Task\n", + "\n", + "Submit and run the kriging task using Evo Compute." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# WIP: Run kriging task\n", + "#\n", + "# from evo.compute.tasks import run\n", + "#\n", + "# # Submit kriging task (progress feedback is shown by default)\n", + "# print(\"Submitting kriging task...\")\n", + "# results = await run(manager, [params])\n", + "#\n", + "# print(f\"Kriging complete!\")\n", + "# print(f\"Result: {results[0].message}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### WIP: View Kriging Results\n", + "\n", + "Refresh the block model and view the estimated grades." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# WIP: View kriging results\n", + "#\n", + "# # Refresh block model to see new attributes\n", + "# block_model = await block_model.refresh()\n", + "#\n", + "# # Display the block model (pretty-printed with Portal/Viewer links)\n", + "# block_model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# WIP: Query estimated values\n", + "#\n", + "# # Get the kriged values as a DataFrame\n", + "# results_df = await block_model.to_dataframe(columns=[\"CU_estimate\"])\n", + "#\n", + "# print(f\"Estimated {len(results_df)} blocks\")\n", + "# print(f\"\\nStatistics:\")\n", + "# print(results_df[\"CU_estimate\"].describe())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### WIP: Running Multiple Kriging Scenarios\n", + "\n", + "Run multiple kriging tasks concurrently to compare different parameters." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# WIP: Multiple kriging scenarios with different max_samples\n", + "#\n", + "# max_samples_values = [5, 10, 15, 20]\n", + "#\n", + "# # Create parameter sets for each scenario\n", + "# parameter_sets = []\n", + "# for max_samples in max_samples_values:\n", + "# params = KrigingParameters(\n", + "# source=pointset.attributes[\"CU_pct\"],\n", + "# target=block_model.attributes[f\"CU_samples_{max_samples}\"],\n", + "# variogram=variogram,\n", + "# search=SearchNeighborhood(\n", + "# ellipsoid=search_ellipsoid,\n", + "# max_samples=max_samples,\n", + "# ),\n", + "# )\n", + "# parameter_sets.append(params)\n", + "#\n", + "# # Run all scenarios in parallel\n", + "# print(f\"Submitting {len(parameter_sets)} kriging tasks...\")\n", + "# results = await run(manager, parameter_sets)\n", + "# print(f\"All {len(results)} scenarios completed!\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.0" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/code-samples/geoscience-objects/running-kriging-compute/sample-data/WP_assay.csv b/code-samples/geoscience-objects/running-kriging-compute/sample-data/WP_assay.csv new file mode 100644 index 00000000..51a59581 --- /dev/null +++ b/code-samples/geoscience-objects/running-kriging-compute/sample-data/WP_assay.csv @@ -0,0 +1,8333 @@ +X,Y,Z,Hole ID,CU_pct,AU_gpt,DENSITY +445198.861763,494110.588391,3052.607679,WP001,0.79,1.75, +445200.147289,494110.577172,3051.075590,WP001,0.83,1.73, +445201.432816,494110.565953,3049.543501,WP001,0.84,6, 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+445469.560207,493600.000000,2837.475954,WP058,,0.26,2.98 +445468.876167,493600.000000,2835.596568,WP058,,0.31,2.89 +445468.192127,493600.000000,2833.717183,WP058,,0.35,2.98 +445467.508086,493600.000000,2831.837798,WP058,,0.36,2.92 +445466.824046,493600.000000,2829.958413,WP058,,0.5,2.9 +445466.140006,493600.000000,2828.079027,WP058,,0.47,2.94 +445465.455966,493600.000000,2826.199642,WP058,,0.38,2.93 +445464.771925,493600.000000,2824.320257,WP058,,0.65,2.81 +445464.181941,493600.000000,2822.699289,WP058,,0.66,2.97 diff --git a/code-samples/geoscience-objects/simplified-object-interactions/README.md b/code-samples/geoscience-objects/simplified-object-interactions/README.md index 6b7fcdc0..fa80389c 100644 --- a/code-samples/geoscience-objects/simplified-object-interactions/README.md +++ b/code-samples/geoscience-objects/simplified-object-interactions/README.md @@ -42,7 +42,7 @@ For advanced use cases, you may need the lower-level `evo-schemas` approach (as ## Sample Data -The `sample-data/WP_assay.csv` file contains drill hole assay data with: +The `sample-data/WP_assay.csv` file contains downhole assay data with: - X, Y, Z coordinates - Hole ID - Assay values (CU_pct, AU_gpt, DENSITY) diff --git a/code-samples/geoscience-objects/simplified-object-interactions/simplified-object-interactions.ipynb b/code-samples/geoscience-objects/simplified-object-interactions/simplified-object-interactions.ipynb index 0c09b52f..db29e6c5 100644 --- a/code-samples/geoscience-objects/simplified-object-interactions/simplified-object-interactions.ipynb +++ b/code-samples/geoscience-objects/simplified-object-interactions/simplified-object-interactions.ipynb @@ -2,6 +2,7 @@ "cells": [ { "cell_type": "markdown", + "id": "0", "metadata": {}, "source": [ "# Simplified Object Interactions\n", @@ -25,6 +26,7 @@ }, { "cell_type": "markdown", + "id": "1", "metadata": {}, "source": [ "## 1. Authentication\n", @@ -35,6 +37,7 @@ { "cell_type": "code", "execution_count": null, + "id": "2", "metadata": {}, "outputs": [], "source": [ @@ -53,6 +56,7 @@ }, { "cell_type": "markdown", + "id": "3", "metadata": {}, "source": [ "## 2. Load the Widgets Extension\n", @@ -63,6 +67,7 @@ { "cell_type": "code", "execution_count": null, + "id": "4", "metadata": {}, "outputs": [], "source": [ @@ -71,16 +76,18 @@ }, { "cell_type": "markdown", + "id": "5", "metadata": {}, "source": [ "## 3. Load Sample Data\n", "\n", - "We'll load drill hole assay data from a CSV file. The data contains X, Y, Z coordinates along with assay values." + "We'll load downhole assay data from a CSV file. The data contains X, Y, Z coordinates along with assay values." ] }, { "cell_type": "code", "execution_count": null, + "id": "6", "metadata": {}, "outputs": [], "source": [ @@ -96,6 +103,7 @@ }, { "cell_type": "markdown", + "id": "7", "metadata": {}, "source": [ "## 4. Create a PointSet Object\n", @@ -108,6 +116,7 @@ { "cell_type": "code", "execution_count": null, + "id": "8", "metadata": {}, "outputs": [], "source": [ @@ -130,6 +139,7 @@ }, { "cell_type": "markdown", + "id": "9", "metadata": {}, "source": [ "## 5. View the Created Object\n", @@ -143,6 +153,7 @@ { "cell_type": "code", "execution_count": null, + "id": "10", "metadata": {}, "outputs": [], "source": [ @@ -152,6 +163,7 @@ }, { "cell_type": "markdown", + "id": "11", "metadata": {}, "source": [ "## 6. Inspect Object Properties\n", @@ -162,6 +174,7 @@ { "cell_type": "code", "execution_count": null, + "id": "12", "metadata": {}, "outputs": [], "source": [ @@ -174,6 +187,7 @@ }, { "cell_type": "markdown", + "id": "13", "metadata": {}, "source": [ "## 7. View Available Attributes\n", @@ -184,6 +198,7 @@ { "cell_type": "code", "execution_count": null, + "id": "14", "metadata": {}, "outputs": [], "source": [ @@ -192,6 +207,7 @@ }, { "cell_type": "markdown", + "id": "15", "metadata": {}, "source": [ "## 8. Get Data as DataFrame\n", @@ -202,6 +218,7 @@ { "cell_type": "code", "execution_count": null, + "id": "16", "metadata": {}, "outputs": [], "source": [ @@ -212,6 +229,7 @@ }, { "cell_type": "markdown", + "id": "17", "metadata": {}, "source": [ "## 9. Download an Existing Object\n", @@ -222,6 +240,7 @@ { "cell_type": "code", "execution_count": null, + "id": "18", "metadata": {}, "outputs": [], "source": [ @@ -236,6 +255,7 @@ }, { "cell_type": "markdown", + "id": "19", "metadata": {}, "source": [ "## 10. View Objects in Evo Viewer\n", @@ -246,6 +266,7 @@ { "cell_type": "code", "execution_count": null, + "id": "20", "metadata": {}, "outputs": [], "source": [ @@ -258,6 +279,7 @@ }, { "cell_type": "markdown", + "id": "21", "metadata": {}, "source": [ "## Summary\n", @@ -275,25 +297,7 @@ ] } ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.0" - } - }, + "metadata": {}, "nbformat": 4, - "nbformat_minor": 4 + "nbformat_minor": 5 } diff --git a/packages/evo-objects/docs/examples/typed-objects-variograms.ipynb b/packages/evo-objects/docs/examples/typed-objects-variograms.ipynb new file mode 100644 index 00000000..17e191b2 --- /dev/null +++ b/packages/evo-objects/docs/examples/typed-objects-variograms.ipynb @@ -0,0 +1,627 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "0", + "metadata": {}, + "source": [ + "# Typed Objects" + ] + }, + { + "cell_type": "markdown", + "id": "1", + "metadata": {}, + "source": [ + "In addition to the interfaces offered by `ObjectAPIClient` and `DownloadedObject`, which provides access to Geoscience Objects in a way that is agnostic to the specific object type, the `evo-objects` package also provides a set of \"typed objects\" that represent specific object types." + ] + }, + { + "cell_type": "markdown", + "id": "2", + "metadata": {}, + "source": [ + "As usual, we need to first authenticate, which we can do using the `ServiceManagerWidget` from the `evo-notebooks` package" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3", + "metadata": {}, + "outputs": [], + "source": [ + "from evo.notebooks import ServiceManagerWidget\n", + "\n", + "manager = await ServiceManagerWidget.with_auth_code(\n", + " client_id=\"your-client-id\",\n", + " cache_location=\"./notebook-data\",\n", + ").login()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4", + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext evo.widgets" + ] + }, + { + "cell_type": "markdown", + "id": "5", + "metadata": {}, + "source": [ + "## Working with Variograms\n", + "\n", + "Variograms are geostatistical models that describe spatial correlation structure. They are fundamental to kriging interpolation and resource estimation.\n", + "\n", + "A variogram consists of:\n", + "- **Nugget**: The variance at zero lag (y-intercept), representing measurement error or micro-scale variation\n", + "- **Sill**: The total variance (plateau value)\n", + "- **Structures**: Mathematical models (spherical, exponential, etc.) that define how correlation decreases with distance\n", + "- **Anisotropy**: Directional variation in correlation ranges" + ] + }, + { + "cell_type": "markdown", + "id": "6", + "metadata": {}, + "source": [ + "### Creating a Variogram\n", + "\n", + "To create a variogram, use `VariogramData` with one or more structure types. Common structures include:\n", + "- `SphericalStructure` - Most common, reaches sill at finite range\n", + "- `ExponentialStructure` - Approaches sill asymptotically\n", + "- `GaussianStructure` - Smooth near origin, parabolic behavior\n", + "- `CubicStructure` - Smooth transitions, bounded" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7", + "metadata": {}, + "outputs": [], + "source": [ + "from evo.objects.typed import (\n", + " Ellipsoid,\n", + " EllipsoidRanges,\n", + " Rotation,\n", + " SphericalStructure,\n", + " Variogram,\n", + " VariogramData,\n", + ")\n", + "\n", + "# Define a variogram with two nested structures\n", + "variogram_data = VariogramData(\n", + " name=\"Gold Grade Variogram\",\n", + " description=\"Nested spherical variogram for Au grades\",\n", + " sill=1.0, # Total variance (nugget + all contributions must equal sill)\n", + " nugget=0.1, # 10% nugget effect\n", + " is_rotation_fixed=True, # All structures share the same rotation\n", + " modelling_space=\"data\", # Original units (not normal score transformed)\n", + " data_variance=1.0, # Variance of the input data\n", + " attribute=\"grade\", # The attribute this variogram models\n", + " structures=[\n", + " # Short-range structure (30% of variance)\n", + " SphericalStructure(\n", + " contribution=0.3,\n", + " anisotropy=Ellipsoid(\n", + " ranges=EllipsoidRanges(\n", + " major=15, # 100m range in major direction\n", + " semi_major=13, # 75m in semi-major direction\n", + " minor=8.5, # 50m in minor (vertical) direction\n", + " ),\n", + " rotation=Rotation(\n", + " dip=65, # Horizontal\n", + " dip_azimuth=100, # Strike direction\n", + " pitch=75,\n", + " ),\n", + " ),\n", + " ),\n", + " # Long-range structure (60% of variance, nugget + 0.3 + 0.6 = 1.0)\n", + " SphericalStructure(\n", + " contribution=0.6,\n", + " anisotropy=Ellipsoid(\n", + " ranges=EllipsoidRanges(\n", + " major=134, # 300m range in major direction\n", + " semi_major=90, # 200m in semi-major direction\n", + " minor=40, # 100m in minor direction\n", + " ),\n", + " rotation=Rotation(\n", + " dip=65,\n", + " dip_azimuth=100,\n", + " pitch=75,\n", + " ),\n", + " ),\n", + " ),\n", + " ],\n", + ")\n", + "\n", + "# Create the variogram object\n", + "created_variogram = await Variogram.create(manager, variogram_data)\n", + "print(f\"Created variogram: {created_variogram.metadata.url}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8", + "metadata": {}, + "outputs": [], + "source": [ + "created_variogram" + ] + }, + { + "cell_type": "markdown", + "id": "9", + "metadata": {}, + "source": [ + "### Inspecting a Variogram\n", + "\n", + "The `Variogram` class provides properties to access the variogram model parameters and methods for visualization." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "10", + "metadata": {}, + "outputs": [], + "source": [ + "# Load the variogram we just created\n", + "variogram = await Variogram.from_reference(manager, created_variogram.metadata.url)\n", + "\n", + "print(f\"Variogram: {variogram.name}\")\n", + "print(f\"Sill: {variogram.sill}\")\n", + "print(f\"Nugget: {variogram.nugget}\")\n", + "print(f\"Number of structures: {len(variogram.structures)}\")\n", + "print(f\"Modelling space: {variogram.modelling_space}\")\n", + "print(f\"Attribute: {variogram.attribute}\")\n", + "\n", + "# Inspect the structures\n", + "for i, struct in enumerate(variogram.structures):\n", + " vtype = struct.get(\"variogram_type\")\n", + " contribution = struct.get(\"contribution\")\n", + " ranges = struct.get(\"anisotropy\", {}).get(\"ellipsoid_ranges\", {})\n", + " print(f\"\\nStructure {i + 1}: {vtype}\")\n", + " print(f\" Contribution: {contribution}\")\n", + " print(f\" Ranges: major={ranges.get('major')}, semi_major={ranges.get('semi_major')}, minor={ranges.get('minor')}\")" + ] + }, + { + "cell_type": "markdown", + "id": "11", + "metadata": {}, + "source": [ + "### Getting Variogram Curve Data\n", + "\n", + "The `get_principal_directions()` method returns variogram curves for plotting along the three principal axes." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "12", + "metadata": {}, + "outputs": [], + "source": [ + "# Get curve data for the three principal directions\n", + "major, semi_major, minor = variogram.get_principal_directions()\n", + "\n", + "print(f\"Major direction: range={major.range_value}, sill={major.sill}\")\n", + "print(f\"Semi-major direction: range={semi_major.range_value}\")\n", + "print(f\"Minor direction: range={minor.range_value}\")\n", + "print(f\"Points per curve: {len(major.distance)}\")" + ] + }, + { + "cell_type": "markdown", + "id": "13", + "metadata": {}, + "source": [ + "### Visualizing Variograms with Plotly\n", + "\n", + "Use `plotly` to create interactive variogram plots. The variogram curve shows how spatial correlation decreases with distance." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "14", + "metadata": {}, + "outputs": [], + "source": [ + "import plotly.graph_objects as go\n", + "\n", + "# Create variogram curve plot\n", + "fig = go.Figure()\n", + "\n", + "# Add curves for each principal direction\n", + "fig.add_trace(\n", + " go.Scatter(\n", + " x=minor.distance,\n", + " y=minor.semivariance,\n", + " name=f\"Minor (range={minor.range_value:.0f}m)\",\n", + " line=dict(color=\"blue\", width=2),\n", + " )\n", + ")\n", + "\n", + "fig.add_trace(\n", + " go.Scatter(\n", + " x=semi_major.distance,\n", + " y=semi_major.semivariance,\n", + " name=f\"Semi-major (range={semi_major.range_value:.0f}m)\",\n", + " line=dict(color=\"green\", width=2),\n", + " )\n", + ")\n", + "\n", + "fig.add_trace(\n", + " go.Scatter(\n", + " x=major.distance,\n", + " y=major.semivariance,\n", + " name=f\"Major (range={major.range_value:.0f}m)\",\n", + " line=dict(color=\"red\", width=2),\n", + " )\n", + ")\n", + "\n", + "# Add reference lines for nugget and sill\n", + "fig.add_hline(\n", + " y=variogram.nugget, line_dash=\"dash\", line_color=\"gray\", annotation_text=\"Nugget\", annotation_position=\"right\"\n", + ")\n", + "fig.add_hline(\n", + " y=variogram.sill, line_dash=\"dash\", line_color=\"black\", annotation_text=\"Sill\", annotation_position=\"right\"\n", + ")\n", + "\n", + "fig.update_layout(\n", + " title=\"Variogram Model - Principal Directions\",\n", + " xaxis_title=\"Lag Distance (m)\",\n", + " yaxis_title=\"Semivariance γ(h)\",\n", + " legend=dict(yanchor=\"bottom\", y=0.01, xanchor=\"right\", x=0.99),\n", + " template=\"plotly_white\",\n", + ")\n", + "\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "15", + "metadata": {}, + "source": [ + "### Variogram in Arbitrary Directions\n", + "\n", + "Use `get_direction()` to calculate the variogram curve in any direction specified by azimuth and dip angles." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "16", + "metadata": {}, + "outputs": [], + "source": [ + "# Calculate variogram in an arbitrary direction\n", + "distance, semivariance = variogram.get_direction(azimuth=90, dip=30)\n", + "\n", + "fig = go.Figure()\n", + "\n", + "# Add the principal directions for comparison\n", + "fig.add_trace(go.Scatter(x=major.distance, y=major.semivariance, name=\"Major\", line=dict(dash=\"dot\")))\n", + "fig.add_trace(go.Scatter(x=minor.distance, y=minor.semivariance, name=\"Minor\", line=dict(dash=\"dot\")))\n", + "\n", + "# Add the custom direction\n", + "fig.add_trace(\n", + " go.Scatter(\n", + " x=distance,\n", + " y=semivariance,\n", + " name=\"Az=90°, Dip=30°\",\n", + " line=dict(color=\"purple\", width=3),\n", + " )\n", + ")\n", + "\n", + "fig.update_layout(\n", + " title=\"Variogram in Custom Direction\",\n", + " xaxis_title=\"Lag Distance (m)\",\n", + " yaxis_title=\"Semivariance γ(h)\",\n", + " template=\"plotly_white\",\n", + ")\n", + "\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "17", + "metadata": {}, + "source": [ + "## Working with Ellipsoids\n", + "\n", + "Ellipsoids represent 3D spatial regions and are used for:\n", + "- **Search neighborhoods** in kriging - defining which samples influence each estimated point\n", + "- **Variogram anisotropy** - visualizing the directional ranges of spatial correlation\n", + "- **Geological domains** - representing oriented geological features\n", + "\n", + "The `Ellipsoid` class provides methods for creating, scaling, and visualizing ellipsoids." + ] + }, + { + "cell_type": "markdown", + "id": "18", + "metadata": {}, + "source": [ + "### Creating an Ellipsoid\n", + "\n", + "Create an ellipsoid directly using `Ellipsoid`, `EllipsoidRanges`, and `Rotation`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "19", + "metadata": {}, + "outputs": [], + "source": [ + "from evo.objects.typed import Ellipsoid, EllipsoidRanges, Rotation\n", + "\n", + "# Create an ellipsoid with specified ranges and rotation\n", + "ellipsoid = Ellipsoid(\n", + " ranges=EllipsoidRanges(\n", + " major=134, # 200m in the major direction\n", + " semi_major=90, # 150m in the semi-major direction\n", + " minor=40, # 75m in the minor direction\n", + " ),\n", + " rotation=Rotation(\n", + " dip=65, # Dip angle (degrees)\n", + " dip_azimuth=100, # Strike direction (degrees from north)\n", + " pitch=75, # Pitch/rake angle\n", + " ),\n", + ")\n", + "\n", + "print(\n", + " f\"Ellipsoid ranges: major={ellipsoid.ranges.major}, semi_major={ellipsoid.ranges.semi_major}, minor={ellipsoid.ranges.minor}\"\n", + ")\n", + "print(f\"Rotation: azimuth={ellipsoid.rotation.dip_azimuth}°, dip={ellipsoid.rotation.dip}°\")" + ] + }, + { + "cell_type": "markdown", + "id": "20", + "metadata": {}, + "source": [ + "### Extracting Ellipsoids from Variograms\n", + "\n", + "The `Variogram.get_ellipsoid()` method extracts an ellipsoid from the variogram structures. By default, it selects the structure with the largest volume." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "21", + "metadata": {}, + "outputs": [], + "source": [ + "# Get the ellipsoid from the variogram (uses structure with largest volume by default)\n", + "var_ellipsoid = variogram.get_ellipsoid()\n", + "\n", + "print(\"Variogram ellipsoid ranges:\")\n", + "print(f\" Major: {var_ellipsoid.ranges.major}m\")\n", + "print(f\" Semi-major: {var_ellipsoid.ranges.semi_major}m\")\n", + "print(f\" Minor: {var_ellipsoid.ranges.minor}m\")\n", + "\n", + "# Or get ellipsoid from a specific structure\n", + "first_structure_ellipsoid = variogram.get_ellipsoid(structure_index=0)\n", + "print(f\"\\nFirst structure ranges: major={first_structure_ellipsoid.ranges.major}m\")" + ] + }, + { + "cell_type": "markdown", + "id": "22", + "metadata": {}, + "source": [ + "### Scaling Ellipsoids for Search Neighborhoods\n", + "\n", + "When using ellipsoids for kriging search neighborhoods, it's common to scale them (typically 2-3x the variogram range)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "23", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a search ellipsoid scaled by 2x\n", + "search_ellipsoid = var_ellipsoid.scaled(2.0)\n", + "\n", + "print(f\"Variogram ellipsoid: major={var_ellipsoid.ranges.major}m\")\n", + "print(f\"Search ellipsoid (2x): major={search_ellipsoid.ranges.major}m\")" + ] + }, + { + "cell_type": "markdown", + "id": "24", + "metadata": {}, + "source": [ + "### Visualizing Ellipsoids with Plotly\n", + "\n", + "The `Ellipsoid` class provides methods for 3D visualization:\n", + "- `surface_points()` - Generate mesh points for solid rendering\n", + "- `wireframe_points()` - Generate wireframe for lighter visualization" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "25", + "metadata": {}, + "outputs": [], + "source": [ + "import plotly.graph_objects as go\n", + "\n", + "# Define a center point for visualization\n", + "center = (500, 500, 100) # Example coordinates\n", + "\n", + "# Generate surface mesh points\n", + "x_surf, y_surf, z_surf = var_ellipsoid.surface_points(center=center, n_points=25)\n", + "\n", + "# Generate wireframe points\n", + "x_wire, y_wire, z_wire = var_ellipsoid.wireframe_points(center=center, n_points=50)\n", + "\n", + "# Create 3D figure\n", + "fig = go.Figure()\n", + "\n", + "# Add semi-transparent surface mesh\n", + "fig.add_trace(\n", + " go.Mesh3d(\n", + " x=x_surf,\n", + " y=y_surf,\n", + " z=z_surf,\n", + " alphahull=0,\n", + " opacity=0.3,\n", + " color=\"blue\",\n", + " name=\"Variogram Ellipsoid\",\n", + " )\n", + ")\n", + "\n", + "# Add wireframe for clearer shape definition\n", + "fig.add_trace(\n", + " go.Scatter3d(\n", + " x=x_wire,\n", + " y=y_wire,\n", + " z=z_wire,\n", + " mode=\"lines\",\n", + " line=dict(color=\"darkblue\", width=2),\n", + " name=\"Wireframe\",\n", + " )\n", + ")\n", + "\n", + "# Add center point\n", + "fig.add_trace(\n", + " go.Scatter3d(\n", + " x=[center[0]],\n", + " y=[center[1]],\n", + " z=[center[2]],\n", + " mode=\"markers\",\n", + " marker=dict(size=8, color=\"red\"),\n", + " name=\"Center\",\n", + " )\n", + ")\n", + "\n", + "fig.update_layout(\n", + " title=\"Variogram Anisotropy Ellipsoid\",\n", + " scene=dict(\n", + " xaxis_title=\"Easting (m)\",\n", + " yaxis_title=\"Northing (m)\",\n", + " zaxis_title=\"Elevation (m)\",\n", + " aspectmode=\"data\", # Equal aspect ratio\n", + " ),\n", + " template=\"plotly_white\",\n", + ")\n", + "\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "26", + "metadata": {}, + "source": [ + "### Comparing Variogram and Search Ellipsoids\n", + "\n", + "Visualize both the variogram ellipsoid and a scaled search ellipsoid together." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "27", + "metadata": {}, + "outputs": [], + "source": [ + "# Get the scaled search ellipsoid\n", + "search_ellipsoid = var_ellipsoid.scaled(2.0)\n", + "\n", + "# Generate points for both\n", + "x_var, y_var, z_var = var_ellipsoid.wireframe_points(center=center, n_points=50)\n", + "x_search, y_search, z_search = search_ellipsoid.wireframe_points(center=center, n_points=50)\n", + "\n", + "fig = go.Figure()\n", + "\n", + "# Variogram ellipsoid (range)\n", + "fig.add_trace(\n", + " go.Scatter3d(\n", + " x=x_var,\n", + " y=y_var,\n", + " z=z_var,\n", + " mode=\"lines\",\n", + " line=dict(color=\"blue\", width=3),\n", + " name=f\"Variogram Range (major={var_ellipsoid.ranges.major:.0f}m)\",\n", + " )\n", + ")\n", + "\n", + "# Search ellipsoid (2x range)\n", + "fig.add_trace(\n", + " go.Scatter3d(\n", + " x=x_search,\n", + " y=y_search,\n", + " z=z_search,\n", + " mode=\"lines\",\n", + " line=dict(color=\"orange\", width=2, dash=\"dash\"),\n", + " name=f\"Search (2x, major={search_ellipsoid.ranges.major:.0f}m)\",\n", + " )\n", + ")\n", + "\n", + "# Center point\n", + "fig.add_trace(\n", + " go.Scatter3d(\n", + " x=[center[0]],\n", + " y=[center[1]],\n", + " z=[center[2]],\n", + " mode=\"markers\",\n", + " marker=dict(size=8, color=\"red\"),\n", + " name=\"Center\",\n", + " )\n", + ")\n", + "\n", + "fig.update_layout(\n", + " title=\"Variogram Range vs Search Ellipsoid\",\n", + " scene=dict(\n", + " xaxis_title=\"Easting (m)\",\n", + " yaxis_title=\"Northing (m)\",\n", + " zaxis_title=\"Elevation (m)\",\n", + " aspectmode=\"data\",\n", + " ),\n", + " template=\"plotly_white\",\n", + ")\n", + "\n", + "fig.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/packages/evo-objects/src/evo/objects/typed/__init__.py b/packages/evo-objects/src/evo/objects/typed/__init__.py index 23ed5abc..f73440c1 100644 --- a/packages/evo-objects/src/evo/objects/typed/__init__.py +++ b/packages/evo-objects/src/evo/objects/typed/__init__.py @@ -30,7 +30,30 @@ Tensor3DGrid, Tensor3DGridData, ) -from .types import BoundingBox, CoordinateReferenceSystem, EpsgCode, Point3, Rotation, Size3d, Size3i +from .types import ( + BoundingBox, + CoordinateReferenceSystem, + Ellipsoid, + EllipsoidRanges, + EpsgCode, + Point3, + Rotation, + Size3d, + Size3i, +) +from .variogram import ( + CubicStructure, + ExponentialStructure, + GaussianStructure, + GeneralisedCauchyStructure, + LinearStructure, + SphericalStructure, + SpheroidalStructure, + Variogram, + VariogramCurveData, + VariogramData, + VariogramStructure, +) __all__ = [ "Attribute", @@ -39,7 +62,14 @@ "BaseSpatialObject", "BoundingBox", "CoordinateReferenceSystem", + "CubicStructure", + "Ellipsoid", + "EllipsoidRanges", "EpsgCode", + "ExponentialStructure", + "GaussianStructure", + "GeneralisedCauchyStructure", + "LinearStructure", "Locations", "MaskedCells", "Point3", @@ -52,8 +82,14 @@ "Rotation", "Size3d", "Size3i", + "SphericalStructure", + "SpheroidalStructure", "Tensor3DGrid", "Tensor3DGridData", + "Variogram", + "VariogramCurveData", + "VariogramData", + "VariogramStructure", "object_from_path", "object_from_reference", "object_from_uuid", diff --git a/packages/evo-objects/src/evo/objects/typed/_model.py b/packages/evo-objects/src/evo/objects/typed/_model.py index fc6210c9..d221bc80 100644 --- a/packages/evo-objects/src/evo/objects/typed/_model.py +++ b/packages/evo-objects/src/evo/objects/typed/_model.py @@ -242,7 +242,9 @@ def __init_subclass__(cls, **kwargs: Any) -> None: # To robustly check for SchemaModel/SchemaList, we need to strip any generic or Annotated wrappers bare_base_type = get_origin(base_type) or base_type - if issubclass(bare_base_type, (SchemaModel, SchemaList)): + # Check if it's a class before using issubclass (handles Literal, Union, etc.) + is_sub_model = isinstance(bare_base_type, type) and issubclass(bare_base_type, (SchemaModel, SchemaList)) + if is_sub_model: data_field = data_location.field_path if data_location else None sub_models[field_name] = SubModelMetadata( model_type=base_type, diff --git a/packages/evo-objects/src/evo/objects/typed/types.py b/packages/evo-objects/src/evo/objects/typed/types.py index 7b17928a..8d2744a3 100644 --- a/packages/evo-objects/src/evo/objects/typed/types.py +++ b/packages/evo-objects/src/evo/objects/typed/types.py @@ -22,6 +22,8 @@ __all__ = [ "BoundingBox", "CoordinateReferenceSystem", + "Ellipsoid", + "EllipsoidRanges", "EpsgCode", "Point3", "Rotation", @@ -286,3 +288,127 @@ def as_rotation_matrix(self) -> np.ndarray: # Combined intrinsic rotations: dip_azimuth -> dip -> pitch return dip_azimuth_rotation_matrix @ dip_rotation_matrix @ pitch_rotation_matrix + + +@dataclass +class EllipsoidRanges: + """The ranges (semi-axes lengths) of an ellipsoid.""" + + major: float + semi_major: float + minor: float + + def __init__(self, major: float, semi_major: float, minor: float): + self.major = major + self.semi_major = semi_major + self.minor = minor + + def to_dict(self) -> dict[str, Any]: + return {"major": self.major, "semi_major": self.semi_major, "minor": self.minor} + + def scaled(self, factor: float) -> "EllipsoidRanges": + return EllipsoidRanges( + major=self.major * factor, + semi_major=self.semi_major * factor, + minor=self.minor * factor, + ) + + +@dataclass +class Ellipsoid: + """An ellipsoid defining a spatial region.""" + + ranges: EllipsoidRanges + _rotation: Rotation | None = None + + def __init__(self, ranges: EllipsoidRanges, rotation: Rotation | None = None): + self.ranges = ranges + self._rotation = rotation + + @property + def rotation(self) -> Rotation: + """The rotation of the ellipsoid, defaulting to no rotation if not specified.""" + return self._rotation or Rotation(0, 0, 0) + + def to_dict(self) -> dict[str, Any]: + return { + "ellipsoid_ranges": self.ranges.to_dict(), + "rotation": { + "dip_azimuth": self.rotation.dip_azimuth, + "dip": self.rotation.dip, + "pitch": self.rotation.pitch, + }, + } + + def scaled(self, factor: float) -> "Ellipsoid": + return Ellipsoid( + ranges=self.ranges.scaled(factor), + rotation=Rotation( + dip_azimuth=self.rotation.dip_azimuth, + dip=self.rotation.dip, + pitch=self.rotation.pitch, + ), + ) + + def surface_points( + self, + center: tuple[float, float, float] = (0, 0, 0), + n_points: int = 20, + ) -> tuple[npt.NDArray[np.floating[Any]], npt.NDArray[np.floating[Any]], npt.NDArray[np.floating[Any]]]: + """Generate surface mesh points for 3D visualization.""" + rot_matrix = self.rotation.as_rotation_matrix() + + u = np.linspace(0, 2 * np.pi, n_points) + v = np.linspace(0, np.pi, n_points) + u, v = np.meshgrid(u, v) + + # Leapfrog convention: major=X, semi_major=Y, minor=Z + x = self.ranges.major * np.cos(u) * np.sin(v) # major along X + y = self.ranges.semi_major * np.sin(u) * np.sin(v) # semi_major along Y + z = self.ranges.minor * np.cos(v) # minor along Z + + points = np.array([x.flatten(), y.flatten(), z.flatten()]) + rotated = rot_matrix @ points + + return rotated[0] + center[0], rotated[1] + center[1], rotated[2] + center[2] + + def wireframe_points( + self, + center: tuple[float, float, float] = (0, 0, 0), + n_points: int = 30, + ) -> tuple[npt.NDArray[np.floating[Any]], npt.NDArray[np.floating[Any]], npt.NDArray[np.floating[Any]]]: + """Generate wireframe points for 3D visualization. + + - Major axis along X + - Semi-major axis along Y + - Minor axis along Z (up) + """ + rot_matrix = self.rotation.as_rotation_matrix() + theta = np.linspace(0, 2 * np.pi, n_points) + cos_theta = np.cos(theta) + sin_theta = np.sin(theta) + center_arr = np.array(center)[:, np.newaxis] + + # Ellipse coefficient matrices: each row is [cos_coeff, sin_coeff] for x, y, z + planes = [ + # XY plane (major-semi_major): horizontal slice + [[self.ranges.major, 0], [0, self.ranges.semi_major], [0, 0]], + # XZ plane (major-minor): vertical slice along major axis + [[self.ranges.major, 0], [0, 0], [0, self.ranges.minor]], + # YZ plane (semi_major-minor): vertical slice along semi_major axis + [[0, 0], [self.ranges.semi_major, 0], [0, self.ranges.minor]], + ] + + # Pre-allocate array for 3 planes, each with n_points + 1 (for NaN separator) + total_points = 3 * (n_points + 1) + result = np.empty((3, total_points)) + + trig = np.array([cos_theta, sin_theta]) # (2, n_points) + for i, coeffs in enumerate(planes): + points = np.array(coeffs) @ trig # (3, n_points) + rotated = rot_matrix @ points + center_arr + offset = i * (n_points + 1) + result[:, offset : offset + n_points] = rotated + result[:, offset + n_points] = np.nan + + return result[0], result[1], result[2] diff --git a/packages/evo-objects/src/evo/objects/typed/variogram.py b/packages/evo-objects/src/evo/objects/typed/variogram.py new file mode 100644 index 00000000..9be2f719 --- /dev/null +++ b/packages/evo-objects/src/evo/objects/typed/variogram.py @@ -0,0 +1,663 @@ +# Copyright © 2025 Bentley Systems, Incorporated +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# http://www.apache.org/licenses/LICENSE-2.0 +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +from dataclasses import dataclass, field, replace +from typing import TYPE_CHECKING, Annotated, Any, Literal + +import numpy as np + +from evo.objects import SchemaVersion + +from ._model import SchemaLocation +from .base import BaseObject, BaseObjectData +from .types import Ellipsoid, EllipsoidRanges, Rotation + +if TYPE_CHECKING: + from numpy.typing import NDArray + +__all__ = [ + "CubicStructure", + "EllipsoidRanges", + "ExponentialStructure", + "GaussianStructure", + "GeneralisedCauchyStructure", + "LinearStructure", + "SphericalStructure", + "SpheroidalStructure", + "Variogram", + "VariogramCurveData", + "VariogramData", + "VariogramStructure", +] + + +@dataclass(frozen=True, kw_only=True) +class VariogramStructure: + """Base class for variogram structures.""" + + contribution: float + """The contribution of this structure to the total variance.""" + + anisotropy: Ellipsoid + """The anisotropy ellipsoid for this structure.""" + + variogram_type: str = field(init=False) + """The type of variogram structure (set by subclasses).""" + + def to_dict(self) -> dict[str, Any]: + """Convert to dictionary format for the schema.""" + return { + "variogram_type": self.variogram_type, + "contribution": self.contribution, + "anisotropy": self.anisotropy.to_dict(), + } + + def to_ellipsoid(self) -> Ellipsoid: + """Return this structure's anisotropy ellipsoid. + + Returns the Ellipsoid that can be used for: + - 3D visualization with surface_points() or wireframe_points() + - Creating search ellipsoids via scaled() + - Kriging search neighborhoods + + Example: + >>> # Get ellipsoid from variogram structure + >>> var_ell = variogram.structures[0].to_ellipsoid() + >>> + >>> # Create search ellipsoid scaled by 2x + >>> search_ell = var_ell.scaled(2.0) + >>> + >>> # Visualize with Plotly + >>> x, y, z = var_ell.surface_points(center=(100, 200, 50)) + >>> mesh = go.Mesh3d(x=x, y=y, z=z, alphahull=0, opacity=0.3) + """ + return self.anisotropy + + +@dataclass(frozen=True, kw_only=True) +class SphericalStructure(VariogramStructure): + """Spherical variogram structure. + + The spherical model is one of the most commonly used variogram models. + It reaches its sill at a finite range. + """ + + variogram_type: str = field(default="spherical", init=False) + + +@dataclass(frozen=True, kw_only=True) +class ExponentialStructure(VariogramStructure): + """Exponential variogram structure. + + The exponential model approaches its sill asymptotically. + The practical range is about 3 times the effective range parameter. + """ + + variogram_type: str = field(default="exponential", init=False) + + +@dataclass(frozen=True, kw_only=True) +class GaussianStructure(VariogramStructure): + """Gaussian variogram structure. + + The Gaussian model has a parabolic behavior near the origin, + indicating very smooth spatial variation. + """ + + variogram_type: str = field(default="gaussian", init=False) + + +@dataclass(frozen=True, kw_only=True) +class CubicStructure(VariogramStructure): + """Cubic variogram structure. + + The cubic model provides smooth transitions and is bounded. + """ + + variogram_type: str = field(default="cubic", init=False) + + +@dataclass(frozen=True, kw_only=True) +class LinearStructure(VariogramStructure): + """Linear variogram structure. + + The linear model has no sill and increases indefinitely. + Useful for modeling trends or unbounded variability. + """ + + variogram_type: str = field(default="linear", init=False) + + +@dataclass(frozen=True, kw_only=True) +class SpheroidalStructure(VariogramStructure): + """Spheroidal variogram structure. + + The spheroidal model is a generalization of the spherical model + with a shape parameter (alpha) that controls the curvature. + """ + + alpha: Literal[3, 5, 7, 9] + """Shape factor of the spheroidal model. Valid values: 3, 5, 7, or 9.""" + + variogram_type: str = field(default="spheroidal", init=False) + + def to_dict(self) -> dict[str, Any]: + """Convert to dictionary format for the schema.""" + return { + "variogram_type": self.variogram_type, + "contribution": self.contribution, + "anisotropy": self.anisotropy.to_dict(), + "alpha": self.alpha, + } + + +@dataclass(frozen=True, kw_only=True) +class GeneralisedCauchyStructure(VariogramStructure): + """Generalised Cauchy variogram structure. + + The Generalised Cauchy model allows for long-range correlation with + a shape parameter (alpha) that controls the decay behavior. + """ + + alpha: Literal[3, 5, 7, 9] + """Shape factor of the Cauchy model. Valid values: 3, 5, 7, or 9.""" + + variogram_type: str = field(default="generalisedcauchy", init=False) + + def to_dict(self) -> dict[str, Any]: + """Convert to dictionary format for the schema.""" + return { + "variogram_type": self.variogram_type, + "contribution": self.contribution, + "anisotropy": self.anisotropy.to_dict(), + "alpha": self.alpha, + } + + +def _convert_structures(structures: list[VariogramStructure | dict[str, Any]]) -> list[dict[str, Any]]: + """Convert a list of structures to dictionary format.""" + result = [] + for struct in structures: + if isinstance(struct, VariogramStructure): + result.append(struct.to_dict()) + else: + # Already a dict, pass through + result.append(struct) + return result + + +@dataclass +class VariogramCurveData: + """Data for rendering a 2D variogram curve. + + This dataclass contains numpy arrays for plotting a variogram model curve + in one of the principal directions. + + Attributes: + distance: Lag distances (x-axis values). + semivariance: Semivariance γ(h) values (y-axis values). + direction: Direction label ("major", "semi_major", or "minor"). + range_value: The effective range in this direction. + sill: The variogram sill value. + """ + + distance: "NDArray[np.floating[Any]]" + semivariance: "NDArray[np.floating[Any]]" + direction: str + range_value: float + sill: float + + +def _evaluate_structure( + structure_type: str, + h: "NDArray[np.floating[Any]]", + contribution: float, + range_val: float, + alpha: int | None = None, +) -> "NDArray[np.floating[Any]]": + """Evaluate a variogram structure model.""" + h_norm = h / range_val if range_val > 0 else h + + if structure_type == "spherical": + gamma = np.where( + h_norm < 1, + contribution * (1.5 * h_norm - 0.5 * h_norm**3), + contribution, + ) + elif structure_type == "exponential": + gamma = contribution * (1 - np.exp(-3 * h_norm)) + elif structure_type == "gaussian": + gamma = contribution * (1 - np.exp(-3 * h_norm**2)) + elif structure_type == "cubic": + gamma = np.where( + h_norm < 1, + contribution * (7 * h_norm**2 - 8.75 * h_norm**3 + 3.5 * h_norm**5 - 0.75 * h_norm**7), + contribution, + ) + elif structure_type == "linear": + gamma = contribution * h_norm + elif structure_type == "spheroidal": + if alpha is None: + alpha = 3 + gamma = np.where( + h_norm < 1, + contribution * (1 - (1 - h_norm**2) ** (alpha / 2)), + contribution, + ) + elif structure_type == "generalisedcauchy": + if alpha is None: + alpha = 3 + gamma = contribution * (1 - (1 + h_norm**2) ** (-alpha / 2)) + else: + raise KeyError("Unsupported structure type") + + return gamma + + +@dataclass(kw_only=True, frozen=True) +class VariogramData(BaseObjectData): + """Data for creating a Variogram. + + A variogram is a geostatistical model describing spatial correlation structure. + The variogram model is defined by the nugget and multiple structures using the + leapfrog-convention rotation. + + Note: + When using a variogram with kriging tasks, the following fields should be set: + - `modelling_space`: Set to "data" for original units or "normalscore" for gaussian space + - `data_variance`: Should match the sill value for non-normalized data + + Example using typed structures (recommended): + >>> data = VariogramData( + ... name="My Variogram", + ... sill=1.0, + ... nugget=0.1, + ... is_rotation_fixed=True, + ... modelling_space="data", # Required for kriging + ... data_variance=1.0, # Required for kriging + ... structures=[ + ... SphericalStructure( + ... contribution=0.9, + ... anisotropy=Ellipsoid( + ... ranges=EllipsoidRanges(major=200, semi_major=150, minor=100), + ... rotation=Rotation(dip_azimuth=0, dip=0, pitch=0), + ... ), + ... ), + ... ], + ... attribute="grade", + ... ) + """ + + sill: float + """The variance of the variogram. Must be within a very small tolerance of the nugget + plus the sum of all structure's contributions.""" + + is_rotation_fixed: bool + """Boolean value specifying whether all structure's rotations are the same.""" + + structures: list[VariogramStructure | dict[str, Any]] + """A list of at least one mathematical model, which are parameterised to represent + the spatial structure of the variogram model. Can use typed classes like + SphericalStructure, ExponentialStructure, GaussianStructure, CubicStructure, + or raw dictionaries.""" + + nugget: float = 0.0 + """The variance between two samples separated by near-zero lag distance, representing + the randomness present. When plotted, this value is the y-intercept.""" + + data_variance: float | None = None + """The variance of the data, if different from the sill value, this is used for + normalising or rescaling the variogram.""" + + modelling_space: Literal["data", "normalscore"] | None = None + """The modelling space the variogram model was fitted in - either 'data' for original + units or 'normalscore' for gaussian space.""" + + domain: str | None = None + """The domain the variogram is modelled for.""" + + attribute: str | None = None + """The attribute the variogram is modelled for.""" + + def get_structures_as_dicts(self) -> list[dict[str, Any]]: + """Get structures as a list of dictionaries for serialization.""" + return _convert_structures(self.structures) + + +class Variogram(BaseObject): + """A GeoscienceObject representing a variogram. + + The variogram describes the spatial correlation structure of a variable, + used in geostatistical modeling and kriging interpolation. + """ + + _data_class = VariogramData + + sub_classification = "variogram" + # Note: Using v1.1.0 for compatibility with kriging task runtime + # v1.2.0 adds spheroidal and linear structures, but the task runtime + # currently only supports v1.1.0 schemas + creation_schema_version = SchemaVersion(major=1, minor=1, patch=0) + + @classmethod + async def _data_to_schema(cls, data: VariogramData, context: Any) -> dict[str, Any]: + """Convert VariogramData to a dictionary for creating the Geoscience Object. + + Overrides the base implementation to handle typed structure conversion. + """ + # Convert structures to dicts BEFORE calling super() to avoid Pydantic + # serialization warnings (it expects dict but gets dataclass objects) + converted_structures = data.get_structures_as_dicts() + + # Create a modified data object with pre-converted structures + # This avoids the warning from TypeAdapter.dump_python() + modified_data = replace(data, structures=converted_structures) + + # Get base dict from parent class (now with dict structures) + result = await super()._data_to_schema(modified_data, context) + + return result + + sill: Annotated[float, SchemaLocation("sill")] + """The variance of the variogram.""" + + is_rotation_fixed: Annotated[bool, SchemaLocation("is_rotation_fixed")] + """Boolean value specifying whether all structure's rotations are the same.""" + + structures: Annotated[list[dict[str, Any]], SchemaLocation("structures")] + """List of variogram structures (exponential, gaussian, spherical, etc.).""" + + nugget: Annotated[float, SchemaLocation("nugget")] = 0.0 + """The variance between two samples separated by near-zero lag distance.""" + + data_variance: Annotated[float | None, SchemaLocation("data_variance")] + """The variance of the data, used for normalising or rescaling the variogram.""" + + modelling_space: Annotated[Literal["data", "normalscore"] | None, SchemaLocation("modelling_space")] + """The modelling space the variogram model was fitted in.""" + + domain: Annotated[str | None, SchemaLocation("domain")] + """The domain the variogram is modelled for.""" + + attribute: Annotated[str | None, SchemaLocation("attribute")] + """The attribute the variogram is modelled for.""" + + def get_ellipsoid(self, structure_index: int | None = None) -> "Ellipsoid": + """Get an Ellipsoid from a variogram structure for visualization or search. + + Returns an Ellipsoid from evo.objects.typed that can be used for: + - 3D visualization with surface_points() or wireframe_points() + - Creating search ellipsoids via scaled() + - Kriging search neighborhoods + + Args: + structure_index: Index of the structure to use. If None (default), selects + the structure with the largest volume (major × semi_major × minor). + + Returns: + Ellipsoid configured with the structure's anisotropy ranges and rotation. + + Example: + >>> # Get ellipsoid from structure with largest range (default) + >>> var_ell = variogram.get_ellipsoid() + >>> + >>> # Or explicitly select a structure by index + >>> var_ell = variogram.get_ellipsoid(structure_index=0) + >>> + >>> # Create search ellipsoid scaled by 2x + >>> search_ell = var_ell.scaled(2.0) + >>> + >>> # Visualize with Plotly + >>> x, y, z = var_ell.surface_points(center=(100, 200, 50)) + >>> mesh = go.Mesh3d(x=x, y=y, z=z, alphahull=0, opacity=0.3) + """ + if not self.structures: + raise ValueError("Variogram has no structures") + + # If no index specified, find structure with largest volume + if structure_index is None: + max_volume = -1.0 + structure_index = 0 + for i, struct in enumerate(self.structures): + anisotropy = struct.get("anisotropy", {}) + ranges = anisotropy.get("ellipsoid_ranges", {}) + volume = ranges.get("major", 1.0) * ranges.get("semi_major", 1.0) * ranges.get("minor", 1.0) + if volume > max_volume: + max_volume = volume + structure_index = i + + if structure_index >= len(self.structures): + raise ValueError(f"structure_index {structure_index} out of range (max {len(self.structures) - 1})") + + struct = self.structures[structure_index] + anisotropy = struct.get("anisotropy", {}) + ranges_dict = anisotropy.get("ellipsoid_ranges", {}) + rotation_dict = anisotropy.get("rotation", {}) + + return Ellipsoid( + ranges=EllipsoidRanges( + major=ranges_dict.get("major", 1.0), + semi_major=ranges_dict.get("semi_major", 1.0), + minor=ranges_dict.get("minor", 1.0), + ), + rotation=Rotation( + dip_azimuth=rotation_dict.get("dip_azimuth", 0.0), + dip=rotation_dict.get("dip", 0.0), + pitch=rotation_dict.get("pitch", 0.0), + ), + ) + + def get_principal_directions( + self, + max_distance: float | None = None, + n_points: int = 200, + ) -> tuple["VariogramCurveData", "VariogramCurveData", "VariogramCurveData"]: + """Generate variogram curve data for the three principal directions. + + Calculates the variogram model along the major, semi-major, and minor + axis directions. Each direction uses the corresponding range from the + anisotropy ellipsoid. + + Args: + max_distance: Maximum distance for the curves. If None, uses 1.2x the maximum range. + n_points: Number of points for smooth curves. + + Returns: + Tuple of (major_curve, semi_major_curve, minor_curve) as VariogramCurveData. + + Example with Plotly: + >>> major, semi_maj, minor = variogram.get_principal_directions() + >>> import plotly.graph_objects as go + >>> fig = go.Figure() + >>> fig.add_trace(go.Scatter(x=minor.distance, y=minor.semivariance, + ... name='Minor', line=dict(color='blue'))) + >>> fig.add_trace(go.Scatter(x=semi_maj.distance, y=semi_maj.semivariance, + ... name='Semi-major', line=dict(color='green'))) + >>> fig.add_trace(go.Scatter(x=major.distance, y=major.semivariance, + ... name='Major', line=dict(color='red'))) + >>> fig.update_layout(xaxis_title='Distance', yaxis_title='Semivariance') + >>> fig.show() + """ + max_ranges = {"major": 0.0, "semi_major": 0.0, "minor": 0.0} + for struct in self.structures: + anisotropy = struct.get("anisotropy", {}) + ranges = anisotropy.get("ellipsoid_ranges", {}) + for direction in max_ranges: + max_ranges[direction] = max(max_ranges[direction], ranges.get(direction, 0)) + + if max_distance is None: + max_distance = max(max_ranges.values()) * 1.2 if max(max_ranges.values()) > 0 else 100.0 + + h = np.linspace(0, max_distance, n_points) + + results = [] + for direction in ["major", "semi_major", "minor"]: + gamma = np.full_like(h, self.nugget, dtype=float) + + for struct in self.structures: + vtype = struct.get("variogram_type", "unknown") + contribution = struct.get("contribution", 0) + alpha = struct.get("alpha") + anisotropy = struct.get("anisotropy", {}) + ranges = anisotropy.get("ellipsoid_ranges", {}) + range_val = ranges.get(direction, 1.0) + + gamma += _evaluate_structure(vtype, h, contribution, range_val, alpha) + + results.append( + VariogramCurveData( + distance=h.copy(), + semivariance=gamma, + direction=direction, + range_value=max_ranges[direction], + sill=self.sill, + ) + ) + + return results[0], results[1], results[2] + + def get_direction( + self, + azimuth: float, + dip: float, + max_distance: float | None = None, + n_points: int = 200, + ) -> tuple["NDArray[np.floating[Any]]", "NDArray[np.floating[Any]]"]: + """Calculate variogram model curve in an arbitrary direction. + + Computes the variogram semivariance along a specified direction defined by + azimuth and dip angles. The effective range in that direction is calculated + using the anisotropic transform. + + Args: + azimuth: Azimuth angle in degrees (0-360), measured clockwise from north. + dip: Dip angle in degrees (-90 to 90), positive downward. + max_distance: Maximum distance for the curve. If None, uses 1.3x the + effective range in the specified direction. + n_points: Number of points for smooth curve. + + Returns: + Tuple of (distance, semivariance) as numpy arrays, suitable for plotting. + + Example with Plotly: + >>> distance, semivariance = variogram.get_direction(azimuth=45, dip=30) + >>> import plotly.graph_objects as go + >>> fig = go.Figure() + >>> fig.add_trace(go.Scatter(x=distance, y=semivariance, name='Az=45°, Dip=30°')) + >>> fig.update_layout(xaxis_title='Distance', yaxis_title='Semivariance') + >>> fig.show() + + Example with Matplotlib: + >>> distance, semivariance = variogram.get_direction(azimuth=0, dip=0) + >>> import matplotlib.pyplot as plt + >>> plt.plot(distance, semivariance) + >>> plt.xlabel('Distance') + >>> plt.ylabel('Semivariance') + >>> plt.show() + """ + # Convert azimuth/dip to a unit direction vector + # Azimuth is clockwise from north (Y-axis), dip is angle below horizontal + az_rad = np.radians(azimuth) + dip_rad = np.radians(dip) + + # Direction vector in world coordinates + # X = east, Y = north, Z = up + direction = np.array( + [ + np.sin(az_rad) * np.cos(dip_rad), # X (east) + np.cos(az_rad) * np.cos(dip_rad), # Y (north) + -np.sin(dip_rad), # Z (down is positive dip) + ] + ) + + # Calculate effective range in this direction for each structure + # Using anisotropic transform: range = 1 / ||A^(-1) * direction|| + # where A is the diagonal scaling matrix with ranges + total_range = 0.0 + for struct in self.structures: + anisotropy = struct.get("anisotropy", {}) + ranges = anisotropy.get("ellipsoid_ranges", {}) + rotation_dict = anisotropy.get("rotation", {}) + + major = ranges.get("major", 1.0) + semi_major = ranges.get("semi_major", 1.0) + minor = ranges.get("minor", 1.0) + + dip_azimuth = rotation_dict.get("dip_azimuth", 0.0) + struct_dip = rotation_dict.get("dip", 0.0) + pitch = rotation_dict.get("pitch", 0.0) + + # Build rotation matrix (same as ellipsoid) + rot_matrix = Rotation(dip_azimuth, struct_dip, pitch).as_rotation_matrix() + + # Transform direction to local (ellipsoid-aligned) coordinates + local_dir = rot_matrix.T @ direction # Inverse rotation + + # Apply anisotropic scaling (divide by ranges) + if major > 0 and semi_major > 0 and minor > 0: + scaled_dir = np.array( + [ + local_dir[0] / major, + local_dir[1] / semi_major, + local_dir[2] / minor, + ] + ) + # Effective range = 1 / ||scaled_direction|| + norm = np.linalg.norm(scaled_dir) + if norm > 0: + total_range += 1.0 / norm + + # Use 1.3x the total effective range as default max distance + if max_distance is None: + max_distance = total_range * 1.3 if total_range > 0 else 100.0 + + h = np.linspace(0, max_distance, n_points) + gamma = np.full_like(h, self.nugget, dtype=float) + + # Evaluate variogram model for each structure + for struct in self.structures: + vtype = struct.get("variogram_type", "unknown") + contribution = struct.get("contribution", 0) + alpha = struct.get("alpha") + anisotropy = struct.get("anisotropy", {}) + ranges = anisotropy.get("ellipsoid_ranges", {}) + rotation_dict = anisotropy.get("rotation", {}) + + major = ranges.get("major", 1.0) + semi_major = ranges.get("semi_major", 1.0) + minor = ranges.get("minor", 1.0) + + dip_azimuth = rotation_dict.get("dip_azimuth", 0.0) + struct_dip = rotation_dict.get("dip", 0.0) + pitch = rotation_dict.get("pitch", 0.0) + + # Calculate effective range in this direction for this structure + rot_matrix = Rotation(dip_azimuth, struct_dip, pitch).as_rotation_matrix() + local_dir = rot_matrix.T @ direction + + if major > 0 and semi_major > 0 and minor > 0: + scaled_dir = np.array( + [ + local_dir[0] / major, + local_dir[1] / semi_major, + local_dir[2] / minor, + ] + ) + norm = np.linalg.norm(scaled_dir) + effective_range = 1.0 / norm if norm > 0 else major + else: + effective_range = major + + gamma += _evaluate_structure(vtype, h, contribution, effective_range, alpha) + + return h, gamma diff --git a/packages/evo-objects/tests/typed/test_ellipsoid.py b/packages/evo-objects/tests/typed/test_ellipsoid.py new file mode 100644 index 00000000..900a576c --- /dev/null +++ b/packages/evo-objects/tests/typed/test_ellipsoid.py @@ -0,0 +1,833 @@ +# Copyright © 2025 Bentley Systems, Incorporated +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# http://www.apache.org/licenses/LICENSE-2.0 +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tests for ellipsoid and variogram data generation functions.""" + +import unittest + +import numpy as np +from parameterized import parameterized + +from evo.objects.typed.types import ( + Ellipsoid, + EllipsoidRanges, + Rotation, +) +from evo.objects.typed.variogram import ( + VariogramCurveData, + _evaluate_structure, +) + + +class TestEllipsoidWireframe(unittest.TestCase): + """Tests for ellipsoid wireframe generation.""" + + def test_wireframe_shape(self): + """Wireframe should return coordinate arrays of same length.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + x, y, z = ell.wireframe_points(n_points=20) + self.assertEqual(len(x), len(y)) + self.assertEqual(len(y), len(z)) + self.assertGreater(len(x), 0) + + def test_wireframe_bounds(self): + """Wireframe points should be within ellipsoid bounds.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + x, y, z = ell.wireframe_points(n_points=30) + + # Filter out NaN separators + valid = ~np.isnan(x) + self.assertTrue(np.all(np.abs(x[valid]) <= 100 * 1.01)) + self.assertTrue(np.all(np.abs(y[valid]) <= 50 * 1.01)) + self.assertTrue(np.all(np.abs(z[valid]) <= 25 * 1.01)) + + def test_wireframe_has_nan_separators(self): + """Wireframe should have NaN values separating line segments.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + x, y, z = ell.wireframe_points() + self.assertTrue(np.any(np.isnan(x))) + + def test_wireframe_with_rotation(self): + """Wireframe should apply rotation.""" + ell_no_rot = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25), rotation=Rotation(0, 0, 0)) + ell_rot = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25), rotation=Rotation(45, 30, 0)) + x1, y1, z1 = ell_no_rot.wireframe_points() + x2, y2, z2 = ell_rot.wireframe_points() + # Rotated should have different coordinates + self.assertFalse(np.allclose(x1, x2, equal_nan=True)) + + +class TestEllipsoidSurface(unittest.TestCase): + """Tests for ellipsoid surface mesh generation.""" + + def test_surface_shape(self): + """Surface should return flattened 1D arrays.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + x, y, z = ell.surface_points(n_points=15) + self.assertEqual(x.ndim, 1) + self.assertEqual(y.ndim, 1) + self.assertEqual(z.ndim, 1) + self.assertEqual(len(x), 15 * 15) + + def test_surface_bounds(self): + """Surface points should be within ellipsoid bounds.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + x, y, z = ell.surface_points() + self.assertTrue(np.all(np.abs(x) <= 100 * 1.01)) + self.assertTrue(np.all(np.abs(y) <= 50 * 1.01)) + self.assertTrue(np.all(np.abs(z) <= 25 * 1.01)) + + +class TestEvaluateStructure(unittest.TestCase): + """Tests for variogram structure evaluation.""" + + def test_spherical_at_zero(self): + """Spherical model should be 0 at origin.""" + h = np.array([0.0]) + gamma = _evaluate_structure("spherical", h, contribution=1.0, range_val=100) + np.testing.assert_array_almost_equal(gamma, [0]) + + def test_spherical_at_range(self): + """Spherical model should reach sill at range.""" + h = np.array([100.0]) + gamma = _evaluate_structure("spherical", h, contribution=1.0, range_val=100) + np.testing.assert_array_almost_equal(gamma, [1.0]) + + def test_spherical_beyond_range(self): + """Spherical model should stay at sill beyond range.""" + h = np.array([150.0, 200.0, 500.0]) + gamma = _evaluate_structure("spherical", h, contribution=1.0, range_val=100) + np.testing.assert_array_almost_equal(gamma, [1.0, 1.0, 1.0]) + + def test_exponential_approaches_sill(self): + """Exponential model should approach sill asymptotically.""" + h = np.array([0.0, 100.0, 300.0]) + gamma = _evaluate_structure("exponential", h, contribution=1.0, range_val=100) + self.assertAlmostEqual(gamma[0], 0, places=5) + self.assertGreater(gamma[1], 0.5) + self.assertAlmostEqual(gamma[2], 1.0, places=2) + + def test_gaussian_smooth_at_origin(self): + """Gaussian model should have smooth behavior near origin.""" + h = np.array([0.0, 1.0, 5.0, 10.0]) + gamma = _evaluate_structure("gaussian", h, contribution=1.0, range_val=100) + self.assertAlmostEqual(gamma[0], 0, places=5) + self.assertLess(gamma[1], 0.01) + + def test_cubic_reaches_sill(self): + """Cubic model should reach sill at range.""" + h = np.array([100.0, 150.0]) + gamma = _evaluate_structure("cubic", h, contribution=1.0, range_val=100) + np.testing.assert_array_almost_equal(gamma, [1.0, 1.0]) + + def test_linear_unbounded(self): + """Linear model should increase without bound.""" + h = np.array([50.0, 100.0, 200.0]) + gamma = _evaluate_structure("linear", h, contribution=1.0, range_val=100) + self.assertAlmostEqual(gamma[0], 0.5) + self.assertAlmostEqual(gamma[1], 1.0) + self.assertAlmostEqual(gamma[2], 2.0) + + +class TestVariogramMethods(unittest.TestCase): + """Tests for Variogram class methods like get_ellipsoid, get_principal_directions, get_direction.""" + + def _create_mock_variogram(self, structures): + """Create a mock variogram object with given structure dicts.""" + from unittest.mock import MagicMock + + variogram = MagicMock() + variogram.structures = structures + variogram.nugget = 0.1 + variogram.sill = 1.0 + return variogram + + def test_get_ellipsoid_default_selects_largest_volume(self): + """get_ellipsoid() with no args should select structure with largest volume.""" + from evo.objects.typed.variogram import Variogram + + # Create mock variogram with two structures + # Structure 0: 100 * 50 * 25 = 125,000 + # Structure 1: 200 * 100 * 50 = 1,000,000 (larger) + structures = [ + { + "variogram_type": "spherical", + "contribution": 0.3, + "anisotropy": { + "ellipsoid_ranges": {"major": 100.0, "semi_major": 50.0, "minor": 25.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + { + "variogram_type": "spherical", + "contribution": 0.6, + "anisotropy": { + "ellipsoid_ranges": {"major": 200.0, "semi_major": 100.0, "minor": 50.0}, + "rotation": {"dip_azimuth": 45.0, "dip": 30.0, "pitch": 15.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + # Bind the method from Variogram class + ellipsoid = Variogram.get_ellipsoid(variogram) + + # Should select structure 1 (larger volume) + self.assertEqual(ellipsoid.ranges.major, 200.0) + self.assertEqual(ellipsoid.ranges.semi_major, 100.0) + self.assertEqual(ellipsoid.ranges.minor, 50.0) + self.assertEqual(ellipsoid.rotation.dip_azimuth, 45.0) + + def test_get_ellipsoid_explicit_index(self): + """get_ellipsoid(structure_index=0) should select first structure.""" + from evo.objects.typed.variogram import Variogram + + structures = [ + { + "variogram_type": "spherical", + "contribution": 0.3, + "anisotropy": { + "ellipsoid_ranges": {"major": 100.0, "semi_major": 50.0, "minor": 25.0}, + "rotation": {"dip_azimuth": 10.0, "dip": 20.0, "pitch": 30.0}, + }, + }, + { + "variogram_type": "spherical", + "contribution": 0.6, + "anisotropy": { + "ellipsoid_ranges": {"major": 200.0, "semi_major": 100.0, "minor": 50.0}, + "rotation": {"dip_azimuth": 45.0, "dip": 30.0, "pitch": 15.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + # Explicitly select structure 0 + ellipsoid = Variogram.get_ellipsoid(variogram, structure_index=0) + + self.assertEqual(ellipsoid.ranges.major, 100.0) + self.assertEqual(ellipsoid.rotation.dip_azimuth, 10.0) + + def test_get_principal_directions_returns_three_curves(self): + """get_principal_directions() should return major, semi_major, minor curves.""" + from evo.objects.typed.variogram import Variogram + + structures = [ + { + "variogram_type": "spherical", + "contribution": 0.9, + "anisotropy": { + "ellipsoid_ranges": {"major": 200.0, "semi_major": 100.0, "minor": 50.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + major, semi_major, minor = Variogram.get_principal_directions(variogram, n_points=50) + + # Check that each is a VariogramCurveData + self.assertIsInstance(major, VariogramCurveData) + self.assertIsInstance(semi_major, VariogramCurveData) + self.assertIsInstance(minor, VariogramCurveData) + + # Check direction labels + self.assertEqual(major.direction, "major") + self.assertEqual(semi_major.direction, "semi_major") + self.assertEqual(minor.direction, "minor") + + # Check that arrays have expected length + self.assertEqual(len(major.distance), 50) + self.assertEqual(len(major.semivariance), 50) + + def test_get_principal_directions_respects_max_distance(self): + """get_principal_directions(max_distance=...) should limit the distance range.""" + from evo.objects.typed.variogram import Variogram + + structures = [ + { + "variogram_type": "spherical", + "contribution": 0.9, + "anisotropy": { + "ellipsoid_ranges": {"major": 200.0, "semi_major": 100.0, "minor": 50.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + major, _, _ = Variogram.get_principal_directions(variogram, max_distance=150.0) + + # Max distance should be 150 + self.assertAlmostEqual(major.distance[-1], 150.0) + + def test_get_direction_returns_arrays(self): + """get_direction() should return (distance, semivariance) tuple of arrays.""" + from evo.objects.typed.variogram import Variogram + + structures = [ + { + "variogram_type": "spherical", + "contribution": 0.9, + "anisotropy": { + "ellipsoid_ranges": {"major": 200.0, "semi_major": 100.0, "minor": 50.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + distance, semivariance = Variogram.get_direction(variogram, azimuth=45.0, dip=30.0, n_points=100) + + self.assertIsInstance(distance, np.ndarray) + self.assertIsInstance(semivariance, np.ndarray) + self.assertEqual(len(distance), 100) + self.assertEqual(len(semivariance), 100) + + def test_get_direction_starts_at_nugget(self): + """get_direction() should start at nugget value at distance 0.""" + from evo.objects.typed.variogram import Variogram + + structures = [ + { + "variogram_type": "spherical", + "contribution": 0.9, + "anisotropy": { + "ellipsoid_ranges": {"major": 200.0, "semi_major": 100.0, "minor": 50.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + distance, semivariance = Variogram.get_direction(variogram, azimuth=0, dip=0) + + # First value should be at distance 0 with semivariance = nugget + self.assertAlmostEqual(distance[0], 0.0) + self.assertAlmostEqual(semivariance[0], 0.1) # nugget = 0.1 + + def test_get_direction_reaches_sill(self): + """get_direction() should reach the sill (nugget + contributions) at/beyond range.""" + from evo.objects.typed.variogram import Variogram + + structures = [ + { + "variogram_type": "spherical", + "contribution": 0.9, + "anisotropy": { + "ellipsoid_ranges": {"major": 100.0, "semi_major": 100.0, "minor": 100.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + # Get curve in any direction (isotropic, so all directions same) + distance, semivariance = Variogram.get_direction(variogram, azimuth=0, dip=0, n_points=200) + + # Sill should be nugget (0.1) + contribution (0.9) = 1.0 + # At distances >= range, semivariance should be at the sill + expected_sill = 0.1 + 0.9 # nugget + contribution + self.assertAlmostEqual(semivariance[-1], expected_sill, places=2) + + def test_get_direction_anisotropic_different_ranges(self): + """get_direction() should show different ranges in different directions for anisotropic variograms.""" + from evo.objects.typed.variogram import Variogram + + # Anisotropic variogram: major=200, semi_major=100, minor=50 + structures = [ + { + "variogram_type": "spherical", + "contribution": 0.9, + "anisotropy": { + "ellipsoid_ranges": {"major": 200.0, "semi_major": 100.0, "minor": 50.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + # With no rotation, the ellipsoid axes map to: + # - major (200) -> X axis -> azimuth=90, dip=0 + # - semi_major (100) -> Y axis -> azimuth=0, dip=0 + # - minor (50) -> Z axis -> azimuth=0, dip=90 + + # Direction along major axis (azimuth=90, dip=0 -> X direction, which is major) + dist_major, sv_major = Variogram.get_direction(variogram, azimuth=90, dip=0, max_distance=300, n_points=100) + + # Direction along semi_major axis (azimuth=0, dip=0 -> Y direction, which is semi_major) + dist_semi, sv_semi = Variogram.get_direction(variogram, azimuth=0, dip=0, max_distance=300, n_points=100) + + # Direction along minor axis (azimuth=0, dip=90 -> -Z direction, which is minor) + dist_minor, sv_minor = Variogram.get_direction(variogram, azimuth=0, dip=90, max_distance=300, n_points=100) + + # At distance 75 (1.5x minor range, beyond minor but within semi_major and major) + idx_75 = np.searchsorted(dist_major, 75) + + # Minor direction should be at sill (75 > 50) + # For spherical: at h_norm=1.5, gamma = contribution = 0.9, plus nugget=0.1 = 1.0 + self.assertGreater(sv_minor[idx_75], 0.95) # Should be at or near sill (1.0) + + # Semi-major direction should be part way (75 < 100) + # For spherical at h_norm=0.75: gamma = 0.9 * (1.5*0.75 - 0.5*0.75^3) ≈ 0.82, plus nugget = 0.92 + # This is close to sill, so use a relative comparison + self.assertLess(sv_semi[idx_75], sv_minor[idx_75]) # Should be less than minor (which is at sill) + + # Major direction should be even less (75 < 200) + # For spherical at h_norm=0.375: gamma ≈ 0.47, plus nugget ≈ 0.57 + self.assertLess(sv_major[idx_75], sv_semi[idx_75]) + + def test_get_direction_with_max_distance(self): + """get_direction(max_distance=...) should respect the specified max distance.""" + from evo.objects.typed.variogram import Variogram + + structures = [ + { + "variogram_type": "spherical", + "contribution": 0.9, + "anisotropy": { + "ellipsoid_ranges": {"major": 200.0, "semi_major": 100.0, "minor": 50.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + distance, _ = Variogram.get_direction(variogram, azimuth=45, dip=30, max_distance=500.0, n_points=50) + + self.assertAlmostEqual(distance[-1], 500.0) + self.assertEqual(len(distance), 50) + + def test_get_direction_auto_max_distance(self): + """get_direction() should auto-calculate max_distance as 1.3x effective range.""" + from evo.objects.typed.variogram import Variogram + + structures = [ + { + "variogram_type": "spherical", + "contribution": 0.9, + "anisotropy": { + "ellipsoid_ranges": {"major": 100.0, "semi_major": 100.0, "minor": 100.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + # For isotropic variogram with range=100, auto max should be ~130 + distance, _ = Variogram.get_direction(variogram, azimuth=0, dip=0) + + # Should be approximately 1.3 * 100 = 130 + self.assertAlmostEqual(distance[-1], 130.0, places=0) + + def test_get_direction_with_rotation(self): + """get_direction() should correctly handle rotated variogram structures.""" + from evo.objects.typed.variogram import Variogram + + # Rotated anisotropic variogram + structures = [ + { + "variogram_type": "spherical", + "contribution": 0.9, + "anisotropy": { + "ellipsoid_ranges": {"major": 200.0, "semi_major": 100.0, "minor": 50.0}, + "rotation": {"dip_azimuth": 90.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + # With dip_azimuth rotation of 90°, the local coordinate system is rotated: + # World Y (azimuth=0) maps to local X (major direction, range=200) + # World X (azimuth=90) maps to local -Y (semi_major direction, range=100) + dist_x, sv_x = Variogram.get_direction(variogram, azimuth=90, dip=0, max_distance=300, n_points=100) + dist_y, sv_y = Variogram.get_direction(variogram, azimuth=0, dip=0, max_distance=300, n_points=100) + + # At distance 150 (between semi_major=100 and major=200) + idx_150 = np.searchsorted(dist_x, 150) + + # X direction (semi_major in rotated system, range=100) should be at or near sill at 150 + self.assertGreater(sv_x[idx_150], 0.95) + + # Y direction (major in rotated system, range=200) should be less than sill at 150 + self.assertLess(sv_y[idx_150], 0.95) + + def test_get_direction_multiple_structures(self): + """get_direction() should correctly sum contributions from multiple structures.""" + from evo.objects.typed.variogram import Variogram + + structures = [ + { + "variogram_type": "spherical", + "contribution": 0.4, + "anisotropy": { + "ellipsoid_ranges": {"major": 50.0, "semi_major": 50.0, "minor": 50.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + { + "variogram_type": "spherical", + "contribution": 0.5, + "anisotropy": { + "ellipsoid_ranges": {"major": 200.0, "semi_major": 200.0, "minor": 200.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + distance, semivariance = Variogram.get_direction(variogram, azimuth=0, dip=0, max_distance=300, n_points=100) + + # At distance 75 (beyond first structure range of 50) + idx_75 = np.searchsorted(distance, 75) + # First structure contributes full 0.4, second structure partial + # Nugget (0.1) + first (0.4) = 0.5, plus some from second + self.assertGreater(semivariance[idx_75], 0.5) + self.assertLess(semivariance[idx_75], 1.0) + + # Total sill should be nugget + all contributions = 0.1 + 0.4 + 0.5 = 1.0 + self.assertAlmostEqual(semivariance[-1], 1.0, places=2) + + def test_get_direction_exponential_structure(self): + """get_direction() should work with exponential variogram structures.""" + from evo.objects.typed.variogram import Variogram + + structures = [ + { + "variogram_type": "exponential", + "contribution": 0.9, + "anisotropy": { + "ellipsoid_ranges": {"major": 100.0, "semi_major": 100.0, "minor": 100.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + distance, semivariance = Variogram.get_direction(variogram, azimuth=0, dip=0, max_distance=300, n_points=100) + + # Exponential approaches sill asymptotically + # At 3x range (300), should be very close to sill + self.assertAlmostEqual(semivariance[-1], 1.0, places=1) + + # Should start at nugget + self.assertAlmostEqual(semivariance[0], 0.1) + + def test_get_direction_gaussian_structure(self): + """get_direction() should work with gaussian variogram structures.""" + from evo.objects.typed.variogram import Variogram + + structures = [ + { + "variogram_type": "gaussian", + "contribution": 0.9, + "anisotropy": { + "ellipsoid_ranges": {"major": 100.0, "semi_major": 100.0, "minor": 100.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ] + variogram = self._create_mock_variogram(structures) + + distance, semivariance = Variogram.get_direction(variogram, azimuth=0, dip=0, max_distance=300, n_points=100) + + # Gaussian has parabolic behavior near origin (slow initial increase) + # Check that early slope is small + early_slope = (semivariance[5] - semivariance[0]) / (distance[5] - distance[0]) + later_slope = (semivariance[20] - semivariance[15]) / (distance[20] - distance[15]) + + # Gaussian should have smaller slope near origin than later + self.assertLess(early_slope, later_slope) + + +class TestEllipsoidClass(unittest.TestCase): + """Tests for the Ellipsoid class.""" + + def test_basic_creation(self): + """Should create ellipsoid with ranges and rotation.""" + ell = Ellipsoid( + ranges=EllipsoidRanges(100, 50, 25), + rotation=Rotation(45, 30, 0), + ) + self.assertEqual(ell.ranges.major, 100) + self.assertEqual(ell.ranges.semi_major, 50) + self.assertEqual(ell.ranges.minor, 25) + self.assertEqual(ell.rotation.dip_azimuth, 45) + + def test_surface_points(self): + """Should generate surface points as 1D arrays.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + x, y, z = ell.surface_points(center=(0, 0, 0), n_points=10) + + self.assertEqual(len(x), 100) # 10 x 10 + self.assertEqual(len(y), 100) + self.assertEqual(len(z), 100) + + def test_surface_points_with_center(self): + """Should offset surface points by center.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + x1, y1, z1 = ell.surface_points(center=(0, 0, 0)) + x2, y2, z2 = ell.surface_points(center=(100, 200, 50)) + + # Second ellipsoid should be offset + self.assertAlmostEqual(np.mean(x2) - np.mean(x1), 100, places=1) + self.assertAlmostEqual(np.mean(y2) - np.mean(y1), 200, places=1) + self.assertAlmostEqual(np.mean(z2) - np.mean(z1), 50, places=1) + + def test_wireframe_points(self): + """Should generate wireframe points with NaN separators.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + x, y, z = ell.wireframe_points(center=(0, 0, 0)) + + # Should have NaN separators + self.assertTrue(np.any(np.isnan(x))) + self.assertTrue(np.any(np.isnan(y))) + self.assertTrue(np.any(np.isnan(z))) + + def test_scaled(self): + """Should create scaled ellipsoid.""" + ell = Ellipsoid( + ranges=EllipsoidRanges(100, 50, 25), + rotation=Rotation(45, 30, 0), + ) + scaled = ell.scaled(2.0) + + self.assertEqual(scaled.ranges.major, 200) + self.assertEqual(scaled.ranges.semi_major, 100) + self.assertEqual(scaled.ranges.minor, 50) + # Rotation should be preserved + self.assertEqual(scaled.rotation.dip_azimuth, 45) + + def test_to_dict(self): + """Should serialize to dictionary.""" + ell = Ellipsoid( + ranges=EllipsoidRanges(100, 50, 25), + rotation=Rotation(45, 30, 0), + ) + d = ell.to_dict() + + self.assertEqual(d["ellipsoid_ranges"]["major"], 100) + self.assertEqual(d["rotation"]["dip_azimuth"], 45) + + +class TestEllipsoidWireframeAxisAlignment(unittest.TestCase): + """Parameterized tests for ellipsoid wireframe axis alignment after rotation. + + Uses a convenient 4:2:1 ratio for major:semi_major:minor to make axis identification clear. + The unrotated ellipsoid has major along X, semi_major along Y, minor along Z. + """ + + def _get_axis_extent(self, wireframe_points: tuple, axis: str) -> float: + """Get the extent (max - min) of wireframe points along a given axis.""" + x, y, z = wireframe_points + axis_map = {"x": x, "y": y, "z": z} + values = axis_map[axis] + valid = ~np.isnan(values) + return np.max(values[valid]) - np.min(values[valid]) + + @parameterized.expand( + [ + # (dip, dip_azimuth, pitch, major_axis, semi_major_axis, minor_axis, description) + (90, 0, 0, "x", "z", "y", "Dip 90: major=X, semi_major=Z, minor=Y"), + (0, 90, 0, "y", "x", "z", "Dip azimuth 90: major=Y, semi_major=X, minor=Z"), + (0, 0, 90, "y", "x", "z", "Pitch 90: major=Y, semi_major=X, minor=Z"), + (0, 90, 90, "x", "y", "z", "Dip azimuth 90, pitch 90: major=X, semi_major=Y, minor=Z"), + (90, 90, 90, "z", "y", "x", "Dip 90, dip_azimuth 90, pitch 90: major=Z, semi_major=Y, minor=X"), + (90, 90, 0, "y", "z", "x", "Dip 90, dip_azimuth 90: major=Y, semi_major=Z, minor=X"), + (90, 0, 90, "z", "x", "y", "Dip 90, pitch 90: major=Z, semi_major=X, minor=Y"), + ] + ) + # fmt: on + def test_simple_axis_alignment( + self, + dip: float, + dip_azimuth: float, + pitch: float, + major_axis: str, + semi_major_axis: str, + minor_axis: str, + description: str, + ): + """Test that wireframe axes align correctly after simple rotations.""" + # Use 4:2:1 ratio for clear axis identification + major_range = 400 + semi_major_range = 200 + minor_range = 100 + + ell = Ellipsoid( + ranges=EllipsoidRanges(major_range, semi_major_range, minor_range), + rotation=Rotation(dip_azimuth, dip, pitch), + ) + wireframe = ell.wireframe_points() + + # Check major axis extent (should be 2*major_range = 800) + major_extent = self._get_axis_extent(wireframe, major_axis) + self.assertAlmostEqual( + major_extent, + 2 * major_range, + delta=major_range * 0.1, + msg=f"{description}: Major axis extent on {major_axis} should be ~{2 * major_range}, got {major_extent}", + ) + + # Check semi_major axis extent (should be 2*semi_major_range = 400) + semi_major_extent = self._get_axis_extent(wireframe, semi_major_axis) + self.assertAlmostEqual( + semi_major_extent, + 2 * semi_major_range, + delta=semi_major_range * 0.1, + msg=f"{description}: Semi-major axis extent on {semi_major_axis} should be ~{2 * semi_major_range}, got {semi_major_extent}", + ) + + # Check minor axis extent (should be 2*minor_range = 200) + minor_extent = self._get_axis_extent(wireframe, minor_axis) + self.assertAlmostEqual( + minor_extent, + 2 * minor_range, + delta=minor_range * 0.1, + msg=f"{description}: Minor axis extent on {minor_axis} should be ~{2 * minor_range}, got {minor_extent}", + ) + + @parameterized.expand( + [ + # (major, semi_major, minor, dip_azimuth, dip, pitch, center, expected_major_p1, expected_semi_p1, expected_minor_p1, description) + ( + 134.0, + 90.0, + 40.0, + 100.0, + 65.0, + 75.0, + (500, 500, 100), + (440, 475, 217), + (495, 413, 79), + (536, 494, 117), + "Complex case 1: ranges=(134, 90, 40), rotation=(dip=65, dip_az=100, pitch=75)", + ), + ( + 100.0, + 50.0, + 10.0, + 300.0, + 13.0, + 105.0, + (500, 500, 100), + (569, 431, 122), + (535, 536, 103), + (498, 501, 110), + "Complex case 2: ranges=(100, 50, 10), rotation=(dip=13, dip_az=300, pitch=105)", + ), + ] + ) + def test_complex_rotation_endpoints( + self, + major: float, + semi_major: float, + minor: float, + dip_azimuth: float, + dip: float, + pitch: float, + center: tuple[float, float, float], + expected_major_p1: tuple[float, float, float], + expected_semi_p1: tuple[float, float, float], + expected_minor_p1: tuple[float, float, float] | None, + description: str, + ): + """Test ellipsoid axis endpoints against known reference values. + + This verifies that the rotation matrix produces correct axis directions + by comparing computed endpoints to values from a reference tool. + """ + + # Get the rotation matrix + R = Rotation(dip_azimuth, dip, pitch).as_rotation_matrix() + + # Compute axis directions and endpoints + center_arr = np.array(center) + major_dir = R @ np.array([1, 0, 0]) + semi_dir = R @ np.array([0, 1, 0]) + minor_dir = R @ np.array([0, 0, 1]) + + major_p1 = center_arr + major * major_dir + semi_p1 = center_arr + semi_major * semi_dir + minor_p1 = center_arr + minor * minor_dir + + # Tolerance of ±1 for each coordinate + tolerance = 1.0 + + # Check major axis endpoint + for i, (axis, computed, expected) in enumerate(zip(["X", "Y", "Z"], major_p1, expected_major_p1)): + self.assertAlmostEqual( + computed, + expected, + delta=tolerance, + msg=f"{description}: Major P1 {axis} should be ~{expected}, got {computed:.1f}", + ) + + # Check semi-major axis endpoint + for i, (axis, computed, expected) in enumerate(zip(["X", "Y", "Z"], semi_p1, expected_semi_p1)): + self.assertAlmostEqual( + computed, + expected, + delta=tolerance, + msg=f"{description}: Semi P1 {axis} should be ~{expected}, got {computed:.1f}", + ) + + # Check minor axis endpoint (if expected values provided) + if expected_minor_p1 is not None: + for i, (axis, computed, expected) in enumerate(zip(["X", "Y", "Z"], minor_p1, expected_minor_p1)): + self.assertAlmostEqual( + computed, + expected, + delta=tolerance, + msg=f"{description}: Minor P1 {axis} should be ~{expected}, got {computed:.1f}", + ) + + def test_identity_rotation_baseline(self): + """Test that with no rotation, axes are in default positions (X=major, Y=semi_major, Z=minor).""" + major_range = 400 + semi_major_range = 200 + minor_range = 100 + + ell = Ellipsoid( + ranges=EllipsoidRanges(major_range, semi_major_range, minor_range), + rotation=Rotation(0, 0, 0), + ) + wireframe = ell.wireframe_points() + + x_extent = self._get_axis_extent(wireframe, "x") + y_extent = self._get_axis_extent(wireframe, "y") + z_extent = self._get_axis_extent(wireframe, "z") + + # X should have major extent (800) + self.assertAlmostEqual( + x_extent, + 2 * major_range, + delta=major_range * 0.1, + msg=f"X extent should be ~{2 * major_range}, got {x_extent}", + ) + # Y should have semi_major extent (400) + self.assertAlmostEqual( + y_extent, + 2 * semi_major_range, + delta=semi_major_range * 0.1, + msg=f"Y extent should be ~{2 * semi_major_range}, got {y_extent}", + ) + # Z should have minor extent (200) + self.assertAlmostEqual( + z_extent, + 2 * minor_range, + delta=minor_range * 0.1, + msg=f"Z extent should be ~{2 * minor_range}, got {z_extent}", + ) + + +if __name__ == "__main__": + unittest.main() diff --git a/packages/evo-objects/tests/typed/test_types.py b/packages/evo-objects/tests/typed/test_types.py index 54f47e7b..3eae1b6a 100644 --- a/packages/evo-objects/tests/typed/test_types.py +++ b/packages/evo-objects/tests/typed/test_types.py @@ -18,7 +18,17 @@ from parameterized import parameterized from pydantic import TypeAdapter -from evo.objects.typed import BoundingBox, CoordinateReferenceSystem, EpsgCode, Point3, Rotation, Size3d, Size3i +from evo.objects.typed import ( + BoundingBox, + CoordinateReferenceSystem, + Ellipsoid, + EllipsoidRanges, + EpsgCode, + Point3, + Rotation, + Size3d, + Size3i, +) class TestTypes(TestCase): @@ -128,3 +138,119 @@ def test_bounding_box_from_regular_grid_with_rotation(self): self.assertAlmostEqual(box.max_x, 50.0) self.assertAlmostEqual(box.max_y, 0.0) self.assertAlmostEqual(box.max_z, 25.0) + + +class TestEllipsoidRanges(TestCase): + """Tests for EllipsoidRanges class.""" + + def test_creation(self): + """Should create ellipsoid ranges.""" + ranges = EllipsoidRanges(100, 50, 25) + self.assertEqual(ranges.major, 100) + self.assertEqual(ranges.semi_major, 50) + self.assertEqual(ranges.minor, 25) + + def test_to_dict(self): + """Should serialize to dictionary.""" + ranges = EllipsoidRanges(100, 50, 25) + d = ranges.to_dict() + self.assertEqual(d, {"major": 100, "semi_major": 50, "minor": 25}) + + def test_scaled(self): + """Should create scaled ranges.""" + ranges = EllipsoidRanges(100, 50, 25) + scaled = ranges.scaled(2.0) + self.assertEqual(scaled.major, 200) + self.assertEqual(scaled.semi_major, 100) + self.assertEqual(scaled.minor, 50) + + +class TestEllipsoid(TestCase): + """Tests for the Ellipsoid class.""" + + def test_basic_creation(self): + """Should create ellipsoid with ranges and rotation.""" + ell = Ellipsoid( + ranges=EllipsoidRanges(100, 50, 25), + rotation=Rotation(45, 30, 0), + ) + self.assertEqual(ell.ranges.major, 100) + self.assertEqual(ell.ranges.semi_major, 50) + self.assertEqual(ell.ranges.minor, 25) + self.assertEqual(ell.rotation.dip_azimuth, 45) + + def test_default_rotation(self): + """Should use default rotation when not specified.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + self.assertEqual(ell.rotation.dip_azimuth, 0) + self.assertEqual(ell.rotation.dip, 0) + self.assertEqual(ell.rotation.pitch, 0) + + def test_scaled(self): + """Should create scaled ellipsoid.""" + ell = Ellipsoid( + ranges=EllipsoidRanges(100, 50, 25), + rotation=Rotation(45, 30, 0), + ) + scaled = ell.scaled(2.0) + self.assertEqual(scaled.ranges.major, 200) + self.assertEqual(scaled.ranges.semi_major, 100) + self.assertEqual(scaled.ranges.minor, 50) + # Rotation should be preserved + self.assertEqual(scaled.rotation.dip_azimuth, 45) + + def test_to_dict(self): + """Should serialize to dictionary.""" + ell = Ellipsoid( + ranges=EllipsoidRanges(100, 50, 25), + rotation=Rotation(45, 30, 0), + ) + d = ell.to_dict() + self.assertEqual(d["ellipsoid_ranges"]["major"], 100) + self.assertEqual(d["rotation"]["dip_azimuth"], 45) + + def test_surface_points(self): + """Should generate surface points as 1D arrays.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + x, y, z = ell.surface_points(center=(0, 0, 0), n_points=10) + self.assertEqual(len(x), 100) # 10 x 10 + self.assertEqual(len(y), 100) + self.assertEqual(len(z), 100) + + def test_surface_points_with_center(self): + """Should offset surface points by center.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + x1, y1, z1 = ell.surface_points(center=(0, 0, 0)) + x2, y2, z2 = ell.surface_points(center=(100, 200, 50)) + # Second ellipsoid should be offset + self.assertAlmostEqual(np.mean(x2) - np.mean(x1), 100, places=1) + self.assertAlmostEqual(np.mean(y2) - np.mean(y1), 200, places=1) + self.assertAlmostEqual(np.mean(z2) - np.mean(z1), 50, places=1) + + def test_wireframe_points(self): + """Should generate wireframe points with NaN separators.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + x, y, z = ell.wireframe_points(center=(0, 0, 0)) + # Should have NaN separators + self.assertTrue(np.any(np.isnan(x))) + self.assertTrue(np.any(np.isnan(y))) + self.assertTrue(np.any(np.isnan(z))) + + def test_wireframe_bounds(self): + """Wireframe points should be within ellipsoid bounds.""" + ell = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25)) + x, y, z = ell.wireframe_points(n_points=30) + # Filter out NaN separators + valid = ~np.isnan(x) + self.assertTrue(np.all(np.abs(x[valid]) <= 100 * 1.01)) + self.assertTrue(np.all(np.abs(y[valid]) <= 50 * 1.01)) + self.assertTrue(np.all(np.abs(z[valid]) <= 25 * 1.01)) + + def test_wireframe_with_rotation(self): + """Wireframe should apply rotation.""" + ell_no_rot = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25), rotation=Rotation(0, 0, 0)) + ell_rot = Ellipsoid(ranges=EllipsoidRanges(100, 50, 25), rotation=Rotation(45, 30, 0)) + x1, y1, z1 = ell_no_rot.wireframe_points() + x2, y2, z2 = ell_rot.wireframe_points() + # Rotated should have different coordinates + self.assertFalse(np.allclose(x1, x2, equal_nan=True)) diff --git a/packages/evo-objects/tests/typed/test_variogram.py b/packages/evo-objects/tests/typed/test_variogram.py new file mode 100644 index 00000000..1f27355c --- /dev/null +++ b/packages/evo-objects/tests/typed/test_variogram.py @@ -0,0 +1,483 @@ +# Copyright © 2025 Bentley Systems, Incorporated +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# http://www.apache.org/licenses/LICENSE-2.0 +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +import contextlib +import dataclasses +import uuid +from unittest.mock import patch + +from parameterized import parameterized + +from evo.common import Environment, StaticContext +from evo.common.test_tools import BASE_URL, ORG, WORKSPACE_ID, TestWithConnector +from evo.objects import ObjectReference +from evo.objects.typed import ( + CubicStructure, + Ellipsoid, + EllipsoidRanges, + ExponentialStructure, + GaussianStructure, + GeneralisedCauchyStructure, + LinearStructure, + Rotation, + SphericalStructure, + SpheroidalStructure, + Variogram, + VariogramData, +) +from evo.objects.typed.base import BaseObject + +from .helpers import MockClient + + +class TestVariogram(TestWithConnector): + def setUp(self) -> None: + TestWithConnector.setUp(self) + self.environment = Environment(hub_url=BASE_URL, org_id=ORG.id, workspace_id=WORKSPACE_ID) + self.context = StaticContext.from_environment( + environment=self.environment, + connector=self.connector, + ) + + @contextlib.contextmanager + def _mock_geoscience_objects(self): + mock_client = MockClient(self.environment) + with ( + patch("evo.objects.typed.base.create_geoscience_object", mock_client.create_geoscience_object), + patch("evo.objects.typed.base.replace_geoscience_object", mock_client.replace_geoscience_object), + patch("evo.objects.DownloadedObject.from_context", mock_client.from_reference), + ): + yield mock_client + + example_variogram = VariogramData( + name="Test Variogram", + sill=1.5, + is_rotation_fixed=True, + structures=[ + SphericalStructure( + contribution=0.8, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=100.0, semi_major=50.0, minor=25.0), + rotation=Rotation(dip_azimuth=0.0, dip=0.0, pitch=0.0), + ), + ), + ExponentialStructure( + contribution=0.5, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=200.0, semi_major=100.0, minor=50.0), + rotation=Rotation(dip_azimuth=0.0, dip=0.0, pitch=0.0), + ), + ), + ], + nugget=0.2, + data_variance=1.5, + modelling_space="data", + domain="ore_zone", + attribute="gold_grade", + ) + + @parameterized.expand([BaseObject, Variogram]) + async def test_create(self, class_to_call): + with self._mock_geoscience_objects(): + result = await class_to_call.create(context=self.context, data=self.example_variogram) + self.assertIsInstance(result, Variogram) + self.assertEqual(result.name, "Test Variogram") + + @parameterized.expand([BaseObject, Variogram]) + async def test_replace(self, class_to_call): + data = dataclasses.replace(self.example_variogram, name="Replaced Variogram") + with self._mock_geoscience_objects(): + result = await class_to_call.replace( + context=self.context, + reference=ObjectReference.new( + environment=self.context.get_environment(), + object_id=uuid.uuid4(), + ), + data=data, + ) + self.assertIsInstance(result, Variogram) + self.assertEqual(result.name, "Replaced Variogram") + + @parameterized.expand([BaseObject, Variogram]) + async def test_create_or_replace(self, class_to_call): + with self._mock_geoscience_objects(): + result = await class_to_call.create_or_replace( + context=self.context, + reference=ObjectReference.new( + environment=self.context.get_environment(), + object_id=uuid.uuid4(), + ), + data=self.example_variogram, + ) + self.assertIsInstance(result, Variogram) + self.assertEqual(result.name, "Test Variogram") + + async def test_from_reference(self): + with self._mock_geoscience_objects(): + original = await Variogram.create(context=self.context, data=self.example_variogram) + + result = await Variogram.from_reference(context=self.context, reference=original.metadata.url) + self.assertEqual(result.name, "Test Variogram") + + async def test_update(self): + with self._mock_geoscience_objects(): + obj = await Variogram.create(context=self.context, data=self.example_variogram) + + self.assertEqual(obj.metadata.version_id, "1") + obj.name = "Updated Variogram" + obj.description = "An updated variogram model" + + await obj.update() + + self.assertEqual(obj.name, "Updated Variogram") + self.assertEqual(obj.description, "An updated variogram model") + self.assertEqual(obj.metadata.version_id, "2") + + async def test_minimal_variogram(self): + """Test creating a variogram with only required fields using typed classes.""" + minimal_data = VariogramData( + name="Minimal Variogram", + sill=1.0, + is_rotation_fixed=False, + structures=[ + SphericalStructure( + contribution=1.0, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=100.0, semi_major=100.0, minor=100.0), + ), + ) + ], + ) + with self._mock_geoscience_objects(): + result = await Variogram.create(context=self.context, data=minimal_data) + self.assertIsInstance(result, Variogram) + self.assertEqual(result.name, "Minimal Variogram") + + async def test_variogram_with_normalscore(self): + """Test creating a variogram with normalscore modelling space.""" + normalscore_data = VariogramData( + name="Normalscore Variogram", + sill=1.0, + is_rotation_fixed=True, + structures=[ + GaussianStructure( + contribution=0.9, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=150.0, semi_major=75.0, minor=30.0), + rotation=Rotation(dip_azimuth=0.0, dip=0.0, pitch=0.0), + ), + ) + ], + nugget=0.1, + modelling_space="normalscore", + attribute="copper_grade", + ) + with self._mock_geoscience_objects(): + result = await Variogram.create(context=self.context, data=normalscore_data) + self.assertIsInstance(result, Variogram) + self.assertEqual(result.name, "Normalscore Variogram") + + async def test_variogram_multiple_structures(self): + """Test creating a variogram with multiple structure types using typed classes.""" + multi_structure_data = VariogramData( + name="Multi-Structure Variogram", + sill=2.0, + is_rotation_fixed=False, + structures=[ + SphericalStructure( + contribution=0.5, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=100.0, semi_major=50.0, minor=25.0), + rotation=Rotation(dip_azimuth=0.0, dip=0.0, pitch=0.0), + ), + ), + ExponentialStructure( + contribution=0.8, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=200.0, semi_major=100.0, minor=50.0), + rotation=Rotation(dip_azimuth=0.0, dip=0.0, pitch=0.0), + ), + ), + GaussianStructure( + contribution=0.5, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=300.0, semi_major=150.0, minor=75.0), + rotation=Rotation(dip_azimuth=0.0, dip=0.0, pitch=0.0), + ), + ), + ], + nugget=0.2, + data_variance=2.0, + ) + with self._mock_geoscience_objects(): + result = await Variogram.create(context=self.context, data=multi_structure_data) + self.assertIsInstance(result, Variogram) + self.assertEqual(result.name, "Multi-Structure Variogram") + + async def test_cubic_structure(self): + """Test creating a variogram with cubic structure.""" + cubic_data = VariogramData( + name="Cubic Variogram", + sill=1.0, + is_rotation_fixed=True, + structures=[ + CubicStructure( + contribution=1.0, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=100.0, semi_major=100.0, minor=100.0), + ), + ) + ], + ) + with self._mock_geoscience_objects(): + result = await Variogram.create(context=self.context, data=cubic_data) + self.assertIsInstance(result, Variogram) + self.assertEqual(result.name, "Cubic Variogram") + + def test_structure_to_dict(self): + """Test that typed structures correctly convert to dictionaries.""" + structure = SphericalStructure( + contribution=0.8, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=100.0, semi_major=50.0, minor=25.0), + rotation=Rotation(dip_azimuth=45.0, dip=30.0, pitch=15.0), + ), + ) + result = structure.to_dict() + + self.assertEqual(result["variogram_type"], "spherical") + self.assertEqual(result["contribution"], 0.8) + self.assertEqual(result["anisotropy"]["ellipsoid_ranges"]["major"], 100.0) + self.assertEqual(result["anisotropy"]["ellipsoid_ranges"]["semi_major"], 50.0) + self.assertEqual(result["anisotropy"]["ellipsoid_ranges"]["minor"], 25.0) + self.assertEqual(result["anisotropy"]["rotation"]["dip_azimuth"], 45.0) + self.assertEqual(result["anisotropy"]["rotation"]["dip"], 30.0) + self.assertEqual(result["anisotropy"]["rotation"]["pitch"], 15.0) + + def test_ellipsoid_ranges_to_dict(self): + """Test EllipsoidRanges to_dict method.""" + ranges = EllipsoidRanges(major=200.0, semi_major=150.0, minor=100.0) + result = ranges.to_dict() + + self.assertEqual(result, {"major": 200.0, "semi_major": 150.0, "minor": 100.0}) + + def test_ellipsoid_default_rotation(self): + """Test Ellipsoid with default rotation.""" + ellipsoid = Ellipsoid( + ranges=EllipsoidRanges(major=100.0, semi_major=50.0, minor=25.0), + ) + result = ellipsoid.to_dict() + + self.assertEqual(result["ellipsoid_ranges"]["major"], 100.0) + self.assertEqual(result["rotation"]["dip_azimuth"], 0.0) + self.assertEqual(result["rotation"]["dip"], 0.0) + self.assertEqual(result["rotation"]["pitch"], 0.0) + + def test_variogram_data_get_structures_as_dicts(self): + """Test that VariogramData correctly converts mixed typed and dict structures.""" + data = VariogramData( + name="Mixed Structures", + sill=1.0, + is_rotation_fixed=True, + structures=[ + SphericalStructure( + contribution=0.5, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=100.0, semi_major=50.0, minor=25.0), + ), + ), + { + "variogram_type": "exponential", + "contribution": 0.5, + "anisotropy": { + "ellipsoid_ranges": {"major": 200.0, "semi_major": 100.0, "minor": 50.0}, + "rotation": {"dip_azimuth": 0.0, "dip": 0.0, "pitch": 0.0}, + }, + }, + ], + ) + result = data.get_structures_as_dicts() + + self.assertEqual(len(result), 2) + self.assertEqual(result[0]["variogram_type"], "spherical") + self.assertEqual(result[1]["variogram_type"], "exponential") + + def test_all_structure_types(self): + """Test that all structure types have correct variogram_type.""" + self.assertEqual( + SphericalStructure( + contribution=1.0, + anisotropy=Ellipsoid(ranges=EllipsoidRanges(major=1, semi_major=1, minor=1)), + ).variogram_type, + "spherical", + ) + + self.assertEqual( + ExponentialStructure( + contribution=1.0, + anisotropy=Ellipsoid(ranges=EllipsoidRanges(major=1, semi_major=1, minor=1)), + ).variogram_type, + "exponential", + ) + + self.assertEqual( + GaussianStructure( + contribution=1.0, + anisotropy=Ellipsoid(ranges=EllipsoidRanges(major=1, semi_major=1, minor=1)), + ).variogram_type, + "gaussian", + ) + + self.assertEqual( + CubicStructure( + contribution=1.0, + anisotropy=Ellipsoid(ranges=EllipsoidRanges(major=1, semi_major=1, minor=1)), + ).variogram_type, + "cubic", + ) + + self.assertEqual( + LinearStructure( + contribution=1.0, + anisotropy=Ellipsoid(ranges=EllipsoidRanges(major=1, semi_major=1, minor=1)), + ).variogram_type, + "linear", + ) + + self.assertEqual( + SpheroidalStructure( + contribution=1.0, + alpha=5, + anisotropy=Ellipsoid(ranges=EllipsoidRanges(major=1, semi_major=1, minor=1)), + ).variogram_type, + "spheroidal", + ) + + self.assertEqual( + GeneralisedCauchyStructure( + contribution=1.0, + alpha=7, + anisotropy=Ellipsoid(ranges=EllipsoidRanges(major=1, semi_major=1, minor=1)), + ).variogram_type, + "generalisedcauchy", + ) + + async def test_linear_structure(self): + """Test creating a variogram with linear structure.""" + linear_data = VariogramData( + name="Linear Variogram", + sill=1.0, + is_rotation_fixed=True, + structures=[ + LinearStructure( + contribution=1.0, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=100.0, semi_major=100.0, minor=100.0), + ), + ) + ], + ) + with self._mock_geoscience_objects(): + result = await Variogram.create(context=self.context, data=linear_data) + self.assertIsInstance(result, Variogram) + self.assertEqual(result.name, "Linear Variogram") + + async def test_spheroidal_structure(self): + """Test creating a variogram with spheroidal structure.""" + spheroidal_data = VariogramData( + name="Spheroidal Variogram", + sill=1.0, + is_rotation_fixed=True, + structures=[ + SpheroidalStructure( + contribution=1.0, + alpha=5, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=100.0, semi_major=75.0, minor=50.0), + rotation=Rotation(dip_azimuth=45.0, dip=30.0, pitch=15.0), + ), + ) + ], + ) + with self._mock_geoscience_objects(): + result = await Variogram.create(context=self.context, data=spheroidal_data) + self.assertIsInstance(result, Variogram) + self.assertEqual(result.name, "Spheroidal Variogram") + + async def test_generalisedcauchy_structure(self): + """Test creating a variogram with generalised cauchy structure.""" + cauchy_data = VariogramData( + name="Generalised Cauchy Variogram", + sill=1.0, + is_rotation_fixed=True, + structures=[ + GeneralisedCauchyStructure( + contribution=1.0, + alpha=7, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=150.0, semi_major=100.0, minor=75.0), + ), + ) + ], + ) + with self._mock_geoscience_objects(): + result = await Variogram.create(context=self.context, data=cauchy_data) + self.assertIsInstance(result, Variogram) + self.assertEqual(result.name, "Generalised Cauchy Variogram") + + def test_spheroidal_structure_to_dict(self): + """Test that spheroidal structure correctly includes alpha in dict.""" + structure = SpheroidalStructure( + contribution=0.8, + alpha=5, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=100.0, semi_major=50.0, minor=25.0), + ), + ) + result = structure.to_dict() + + self.assertEqual(result["variogram_type"], "spheroidal") + self.assertEqual(result["contribution"], 0.8) + self.assertEqual(result["alpha"], 5) + self.assertEqual(result["anisotropy"]["ellipsoid_ranges"]["major"], 100.0) + + def test_generalisedcauchy_structure_to_dict(self): + """Test that generalised cauchy structure correctly includes alpha in dict.""" + structure = GeneralisedCauchyStructure( + contribution=0.7, + alpha=9, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=200.0, semi_major=150.0, minor=100.0), + rotation=Rotation(dip_azimuth=90.0, dip=45.0, pitch=0.0), + ), + ) + result = structure.to_dict() + + self.assertEqual(result["variogram_type"], "generalisedcauchy") + self.assertEqual(result["contribution"], 0.7) + self.assertEqual(result["alpha"], 9) + self.assertEqual(result["anisotropy"]["rotation"]["dip_azimuth"], 90.0) + + def test_linear_structure_to_dict(self): + """Test that linear structure correctly converts to dict.""" + structure = LinearStructure( + contribution=0.5, + anisotropy=Ellipsoid( + ranges=EllipsoidRanges(major=100.0, semi_major=100.0, minor=100.0), + ), + ) + result = structure.to_dict() + + self.assertEqual(result["variogram_type"], "linear") + self.assertEqual(result["contribution"], 0.5) + self.assertNotIn("alpha", result) # Linear doesn't have alpha diff --git a/packages/evo-widgets/docs/examples/displaying-typed-objects.ipynb b/packages/evo-widgets/docs/examples/displaying-typed-objects.ipynb index de4610db..9a87af2a 100644 --- a/packages/evo-widgets/docs/examples/displaying-typed-objects.ipynb +++ b/packages/evo-widgets/docs/examples/displaying-typed-objects.ipynb @@ -130,9 +130,20 @@ ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": null, "id": "10", "metadata": {}, + "outputs": [], + "source": [ + "variogram = await object_from_path(manager, \"/Gold Grade Variogram.json\")\n", + "variogram" + ] + }, + { + "cell_type": "markdown", + "id": "11", + "metadata": {}, "source": [ "## Viewing Object Attributes\n", "\n", @@ -142,7 +153,7 @@ { "cell_type": "code", "execution_count": null, - "id": "11", + "id": "12", "metadata": {}, "outputs": [], "source": [ @@ -153,7 +164,7 @@ { "cell_type": "code", "execution_count": null, - "id": "12", + "id": "13", "metadata": {}, "outputs": [], "source": [ @@ -163,7 +174,7 @@ }, { "cell_type": "markdown", - "id": "13", + "id": "14", "metadata": {}, "source": [ "## Accessing Object Properties\n", @@ -174,7 +185,7 @@ { "cell_type": "code", "execution_count": null, - "id": "14", + "id": "15", "metadata": {}, "outputs": [], "source": [ @@ -188,7 +199,7 @@ }, { "cell_type": "markdown", - "id": "15", + "id": "16", "metadata": {}, "source": [ "## Generating Portal and Viewer URLs\n", @@ -199,7 +210,7 @@ { "cell_type": "code", "execution_count": null, - "id": "16", + "id": "17", "metadata": {}, "outputs": [], "source": [ @@ -212,7 +223,7 @@ }, { "cell_type": "markdown", - "id": "17", + "id": "18", "metadata": {}, "source": [ "## Working with DataFrames\n", @@ -223,7 +234,7 @@ { "cell_type": "code", "execution_count": null, - "id": "18", + "id": "19", "metadata": {}, "outputs": [], "source": [ @@ -235,7 +246,7 @@ { "cell_type": "code", "execution_count": null, - "id": "19", + "id": "20", "metadata": {}, "outputs": [], "source": [ @@ -246,7 +257,7 @@ }, { "cell_type": "markdown", - "id": "20", + "id": "21", "metadata": {}, "source": [ "## Summary\n", @@ -267,13 +278,7 @@ ] } ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - } - }, + "metadata": {}, "nbformat": 4, "nbformat_minor": 5 } diff --git a/packages/evo-widgets/src/evo/widgets/__init__.py b/packages/evo-widgets/src/evo/widgets/__init__.py index 481f1d4d..b4944d93 100644 --- a/packages/evo-widgets/src/evo/widgets/__init__.py +++ b/packages/evo-widgets/src/evo/widgets/__init__.py @@ -33,7 +33,7 @@ from typing import TYPE_CHECKING -from .formatters import format_attributes_collection, format_base_object +from .formatters import format_attributes_collection, format_base_object, format_variogram from .urls import ( get_evo_base_url, get_hub_code, @@ -53,6 +53,7 @@ __all__ = [ "format_attributes_collection", "format_base_object", + "format_variogram", "get_evo_base_url", "get_hub_code", "get_portal_url", @@ -86,6 +87,13 @@ def _register_formatters(ipython: InteractiveShell) -> None: format_base_object, ) + # Register formatter for Variogram (overrides BaseObject for variogram-specific rendering) + html_formatter.for_type_by_name( + "evo.objects.typed.variogram", + "Variogram", + format_variogram, + ) + # Register formatter for Attributes collection html_formatter.for_type_by_name( "evo.objects.typed.attributes", @@ -108,8 +116,10 @@ def _unregister_formatters(ipython: InteractiveShell) -> None: # Try to get the actual types and remove them from evo.objects.typed.attributes import Attributes from evo.objects.typed.base import _BaseObject + from evo.objects.typed.variogram import Variogram html_formatter.type_printers.pop(_BaseObject, None) + html_formatter.type_printers.pop(Variogram, None) html_formatter.type_printers.pop(Attributes, None) except ImportError: # If types can't be imported, try to clean up by string name diff --git a/packages/evo-widgets/src/evo/widgets/formatters.py b/packages/evo-widgets/src/evo/widgets/formatters.py index 9cf2b7a0..e303f536 100644 --- a/packages/evo-widgets/src/evo/widgets/formatters.py +++ b/packages/evo-widgets/src/evo/widgets/formatters.py @@ -31,17 +31,18 @@ __all__ = [ "format_attributes_collection", "format_base_object", + "format_variogram", ] -def format_base_object(obj: Any) -> str: - """Format a BaseObject (or subclass) as HTML. - - This formatter handles any typed geoscience object (PointSet, Regular3DGrid, etc.) - by extracting metadata and rendering it as a styled HTML table with Portal/Viewer links. +def _get_base_metadata(obj: Any) -> tuple[str, list[tuple[str, str]] | None, list[tuple[str, str]]]: + """Extract common metadata from a geoscience object. - :param obj: A typed geoscience object with `as_dict()`, `metadata`, and `_sub_models` attributes. - :return: HTML string representation. + :param obj: A typed geoscience object with `as_dict()` and `metadata` attributes. + :return: A tuple of (name, title_links, rows) where: + - name: The object name + - title_links: List of (label, url) tuples for Portal/Viewer links, or None + - rows: List of (label, value) tuples for Object ID, Schema, and Tags """ doc = obj.as_dict() @@ -69,6 +70,54 @@ def format_base_object(obj: Any) -> str: tags_str = ", ".join(f"{k}: {v}" for k, v in tags.items()) rows.append(("Tags:", tags_str)) + return name, title_links, rows + + +def _build_html_from_rows( + name: str, + title_links: list[tuple[str, str]] | None, + rows: list[tuple[str, str]], + extra_content: str = "", +) -> str: + """Build HTML output from formatted rows. + + :param name: The object name for the title. + :param title_links: List of (label, url) tuples for title links, or None. + :param rows: List of (label, value) tuples for the table. + :param extra_content: Additional HTML content to append after the table. + :return: Complete HTML string with stylesheet. + """ + # Build unified table with all rows + table_rows = [] + for label, value in rows: + if label in ("Bounding box:",) or label.endswith(":") and isinstance(value, str) and "{''.join(table_rows)}" + html += extra_content + html += "" + + return html + + +def format_base_object(obj: Any) -> str: + """Format a BaseObject (or subclass) as HTML. + + This formatter handles any typed geoscience object (PointSet, Regular3DGrid, etc.) + by extracting metadata and rendering it as a styled HTML table with Portal/Viewer links. + + :param obj: A typed geoscience object with `as_dict()`, `metadata`, and `_sub_models` attributes. + :return: HTML string representation. + """ + doc = obj.as_dict() + name, title_links, rows = _get_base_metadata(obj) + # Add bounding box if present (as nested table) if bbox := doc.get("bounding_box"): bbox_rows = [ @@ -100,22 +149,7 @@ def format_base_object(obj: Any) -> str: attrs_table = build_nested_table(["Attribute", "Type"], attr_rows) rows.append((f"{dataset_name}:", attrs_table)) - # Build unified table with all rows - table_rows = [] - for label, value in rows: - if label in ("Bounding box:",) or label.endswith(":") and isinstance(value, str) and "{''.join(table_rows)}" - html += "" - - return html + return _build_html_from_rows(name, title_links, rows) def format_attributes_collection(obj: Any) -> str: @@ -147,3 +181,85 @@ def format_attributes_collection(obj: Any) -> str: # Use nested table for a clean header/row structure table_html = build_nested_table(headers, rows) return f'{STYLESHEET}
{table_html}
' + + +def format_variogram(obj: Any) -> str: + """Format a Variogram object as HTML. + + This formatter renders a variogram with its properties and structures + as a styled HTML table with Portal/Viewer links. + + :param obj: A Variogram object with `as_dict()`, `metadata`, `sill`, `nugget`, + `structures`, and other variogram-specific attributes. + :return: HTML string representation. + """ + doc = obj.as_dict() + name, title_links, rows = _get_base_metadata(obj) + + # Add variogram specific rows + sill = getattr(obj, "sill", doc.get("sill", 0)) + nugget = getattr(obj, "nugget", doc.get("nugget", 0)) + is_rotation_fixed = getattr(obj, "is_rotation_fixed", doc.get("is_rotation_fixed", False)) + + rows.append(("Sill:", f"{sill:.4g}")) + rows.append(("Nugget:", f"{nugget:.4g}")) + rows.append(("Rotation Fixed:", str(is_rotation_fixed))) + + # Add optional fields + attribute = getattr(obj, "attribute", doc.get("attribute")) + domain = getattr(obj, "domain", doc.get("domain")) + modelling_space = getattr(obj, "modelling_space", doc.get("modelling_space")) + data_variance = getattr(obj, "data_variance", doc.get("data_variance")) + + if attribute: + rows.append(("Attribute:", attribute)) + if domain: + rows.append(("Domain:", domain)) + if modelling_space: + rows.append(("Modelling Space:", modelling_space)) + if data_variance is not None: + rows.append(("Data Variance:", f"{data_variance:.4g}")) + + # Build structures section + extra_content = "" + structures = getattr(obj, "structures", doc.get("structures", [])) + if structures: + struct_rows = [] + for i, struct in enumerate(structures): + vtype = struct.get("variogram_type", "unknown") + contribution = struct.get("contribution", 0) + + # Calculate standardized sill (% of variance) + standardized_sill = round(contribution / sill, 2) if sill != 0 else 0.0 + + # Extract anisotropy info + anisotropy = struct.get("anisotropy", {}) + ranges = anisotropy.get("ellipsoid_ranges", {}) + rotation = anisotropy.get("rotation", {}) + + range_str = ( + f"({ranges.get('major', 0):.1f}, {ranges.get('semi_major', 0):.1f}, {ranges.get('minor', 0):.1f})" + ) + # Rotation order: dip, dip_az, pitch + rot_str = f"({rotation.get('dip', 0):.1f}°, {rotation.get('dip_azimuth', 0):.1f}°, {rotation.get('pitch', 0):.1f}°)" + + struct_rows.append( + [ + f"{i + 1}", + vtype, + f"{contribution:.4g}", + f"{standardized_sill:.2f}", + range_str, + rot_str, + ] + ) + + structures_table = build_nested_table( + ["#", "Type", "Contribution", "Std. Sill", "Ranges (maj, semi, min)", "Rotation (dip, dip_az, pitch)"], + struct_rows, + ) + extra_content = ( + f'
Structures ({len(structures)}):
{structures_table}' + ) + + return _build_html_from_rows(name, title_links, rows, extra_content) diff --git a/packages/evo-widgets/tests/test_formatters.py b/packages/evo-widgets/tests/test_formatters.py index 2187fd52..9222366e 100644 --- a/packages/evo-widgets/tests/test_formatters.py +++ b/packages/evo-widgets/tests/test_formatters.py @@ -14,7 +14,7 @@ import unittest from unittest.mock import MagicMock -from evo.widgets.formatters import format_attributes_collection, format_base_object +from evo.widgets.formatters import format_attributes_collection, format_base_object, format_variogram class TestFormatBaseObject(unittest.TestCase): @@ -161,5 +161,191 @@ def test_formats_collection_with_attributes(self): self.assertIn("category", html) +class TestFormatVariogram(unittest.TestCase): + """Tests for the format_variogram function.""" + + def _create_mock_variogram(self, **kwargs): + """Create a mock variogram object with the given properties.""" + obj = MagicMock() + + # Default values + defaults = { + "name": "Test Variogram", + "schema": "objects/variogram/v1.1.0", + "uuid": "12345-abcd", + "sill": 1.5, + "nugget": 0.2, + "is_rotation_fixed": True, + "attribute": None, + "domain": None, + "modelling_space": None, + "data_variance": None, + "structures": [ + { + "variogram_type": "spherical", + "contribution": 0.8, + "anisotropy": { + "ellipsoid_ranges": {"major": 100.0, "semi_major": 50.0, "minor": 25.0}, + "rotation": {"dip": 0.0, "dip_azimuth": 0.0, "pitch": 0.0}, + }, + } + ], + "tags": None, + } + defaults.update(kwargs) + + # Set up as_dict return value + obj.as_dict.return_value = { + "name": defaults["name"], + "schema": defaults["schema"], + "uuid": defaults["uuid"], + "sill": defaults["sill"], + "nugget": defaults["nugget"], + "is_rotation_fixed": defaults["is_rotation_fixed"], + "structures": defaults["structures"], + "tags": defaults["tags"], + } + if defaults["attribute"]: + obj.as_dict.return_value["attribute"] = defaults["attribute"] + if defaults["domain"]: + obj.as_dict.return_value["domain"] = defaults["domain"] + if defaults["modelling_space"]: + obj.as_dict.return_value["modelling_space"] = defaults["modelling_space"] + if defaults["data_variance"] is not None: + obj.as_dict.return_value["data_variance"] = defaults["data_variance"] + + # Set up direct attributes + obj.sill = defaults["sill"] + obj.nugget = defaults["nugget"] + obj.is_rotation_fixed = defaults["is_rotation_fixed"] + obj.attribute = defaults["attribute"] + obj.domain = defaults["domain"] + obj.modelling_space = defaults["modelling_space"] + obj.data_variance = defaults["data_variance"] + obj.structures = defaults["structures"] + + # Set up metadata for URL generation + obj.metadata = MagicMock() + obj.metadata.environment = MagicMock() + obj.metadata.environment.org_id = "org-123" + obj.metadata.environment.workspace_id = "ws-456" + obj.metadata.environment.hub_url = "https://test.api.seequent.com" + obj.metadata.id = defaults["uuid"] + + return obj + + def test_formats_variogram_with_basic_properties(self): + """Test formatting a variogram with basic properties.""" + obj = self._create_mock_variogram() + + html = format_variogram(obj) + + self.assertIn("Test Variogram", html) + self.assertIn("objects/variogram/v1.1.0", html) + self.assertIn("12345-abcd", html) + self.assertIn("Sill:", html) + self.assertIn("1.5", html) + self.assertIn("Nugget:", html) + self.assertIn("0.2", html) + self.assertIn("Rotation Fixed:", html) + self.assertIn("True", html) + + def test_formats_variogram_with_optional_fields(self): + """Test formatting a variogram with optional fields.""" + obj = self._create_mock_variogram( + attribute="gold_grade", + domain="ore_zone", + modelling_space="data", + data_variance=1.5, + ) + + html = format_variogram(obj) + + self.assertIn("Attribute:", html) + self.assertIn("gold_grade", html) + self.assertIn("Domain:", html) + self.assertIn("ore_zone", html) + self.assertIn("Modelling Space:", html) + self.assertIn("data", html) + self.assertIn("Data Variance:", html) + + def test_formats_variogram_structures(self): + """Test that variogram structures are rendered.""" + obj = self._create_mock_variogram( + structures=[ + { + "variogram_type": "spherical", + "contribution": 0.8, + "anisotropy": { + "ellipsoid_ranges": {"major": 100.0, "semi_major": 50.0, "minor": 25.0}, + "rotation": {"dip": 0.0, "dip_azimuth": 0.0, "pitch": 0.0}, + }, + }, + { + "variogram_type": "exponential", + "contribution": 0.5, + "anisotropy": { + "ellipsoid_ranges": {"major": 200.0, "semi_major": 100.0, "minor": 50.0}, + "rotation": {"dip": 10.0, "dip_azimuth": 45.0, "pitch": 5.0}, + }, + }, + ] + ) + + html = format_variogram(obj) + + self.assertIn("Structures (2):", html) + self.assertIn("spherical", html) + self.assertIn("exponential", html) + self.assertIn("0.8", html) + self.assertIn("0.5", html) + + def test_formats_variogram_without_optional_fields(self): + """Test that optional fields are not shown when not present.""" + obj = self._create_mock_variogram() + + html = format_variogram(obj) + + self.assertNotIn("Attribute:", html) + self.assertNotIn("Domain:", html) + self.assertNotIn("Modelling Space:", html) + self.assertNotIn("Data Variance:", html) + + def test_formats_variogram_with_tags(self): + """Test formatting a variogram with tags.""" + obj = self._create_mock_variogram(tags={"project": "mining", "stage": "exploration"}) + + html = format_variogram(obj) + + self.assertIn("Tags:", html) + self.assertIn("project", html) + self.assertIn("mining", html) + + def test_formats_variogram_structure_ranges(self): + """Test that structure ranges are properly formatted.""" + obj = self._create_mock_variogram( + structures=[ + { + "variogram_type": "spherical", + "contribution": 1.0, + "anisotropy": { + "ellipsoid_ranges": {"major": 150.5, "semi_major": 75.2, "minor": 30.8}, + "rotation": {"dip": 15.0, "dip_azimuth": 90.0, "pitch": 0.0}, + }, + }, + ] + ) + + html = format_variogram(obj) + + # Check ranges are formatted + self.assertIn("150.5", html) + self.assertIn("75.2", html) + self.assertIn("30.8", html) + # Check rotation values are included + self.assertIn("15.0", html) + self.assertIn("90.0", html) + + if __name__ == "__main__": unittest.main()