diff --git a/.DS_Store b/.DS_Store
new file mode 100644
index 00000000..90ba71fe
Binary files /dev/null and b/.DS_Store differ
diff --git a/.vscode/launch.json b/.vscode/launch.json
new file mode 100644
index 00000000..98dd0751
--- /dev/null
+++ b/.vscode/launch.json
@@ -0,0 +1,21 @@
+{
+ "version": "0.2.0",
+ "configurations": [
+ {
+ "name": "Python: tseda serve",
+ "type": "debugpy",
+ "request": "launch",
+ "module": "tseda", // Use the module 'tseda' directly
+ "args": [
+ "serve", "tests/data/test.trees.tseda" // Arguments to the module
+ ],
+ "console": "integratedTerminal",
+ "env": {
+ "PYTHONPATH": "${workspaceFolder}"
+ },
+ "justMyCode": true,
+ "python": "${workspaceFolder}/.venv/bin/python"
+ }
+ ]
+ }
+
\ No newline at end of file
diff --git a/src/tseda/__main__.py b/src/tseda/__main__.py
index a9ac30e8..64b2a325 100644
--- a/src/tseda/__main__.py
+++ b/src/tseda/__main__.py
@@ -49,8 +49,8 @@ def cli():
),
)
def preprocess(tszip_path, output):
- """
- Preprocess a tskit tree sequence or tszip file, producing a .tseda file.
+ """Preprocess a tskit tree sequence or tszip file, producing a .tseda file.
+
Calls tsbrowse.preprocess.preprocess.
"""
tszip_path = pathlib.Path(tszip_path)
@@ -79,9 +79,7 @@ def preprocess(tszip_path, output):
help="Do not filter the output log (advanced debugging only)",
)
def serve(path, port, show, log_level, no_log_filter, admin):
- """
- Run the tseda datastore server, version based on View base class.
- """
+ """Run the tseda datastore server, version based on View base class."""
setup_logging(log_level, no_log_filter)
tsm = TSModel(path)
@@ -91,8 +89,8 @@ def serve(path, port, show, log_level, no_log_filter, admin):
app_ = app.DataStoreApp(
datastore=datastore.DataStore(
tsm=tsm,
- individuals_table=individuals_table,
sample_sets_table=sample_sets_table,
+ individuals_table=individuals_table,
),
title="TSEda Datastore App",
views=[IndividualsTable],
diff --git a/src/tseda/app.py b/src/tseda/app.py
index d6dd4e11..9ac2c0c1 100644
--- a/src/tseda/app.py
+++ b/src/tseda/app.py
@@ -1,8 +1,8 @@
"""Main application for tseda.
-Provides the DataStoreApp class that is the main application for
-tseda. The DataStoreApp subclasses the Viewer class from panel and
-renders a panel.FastListTemplate object.
+Provides the DataStoreApp class that is the main application for tseda. The
+DataStoreApp subclasses the Viewer class from panel and renders a
+panel.FastListTemplate object.
"""
import time
@@ -20,7 +20,7 @@
RAW_CSS = """
.sidenav#sidebar {
- background-color: #15E3AC;
+ background-color: WhiteSmoke;
}
.title {
font-size: var(--type-ramp-plus-2-font-size);
@@ -50,7 +50,20 @@
class DataStoreApp(Viewer):
- """Main application class for tseda visualization app."""
+ """Main application class for tseda visualization app.
+
+ Attributes:
+ datastore (DataStore): The data store instance for accessing and
+ managing data.
+ title (str): The title of the application.
+ views (List[str]): A list of views to show on startup.
+
+ Methods:
+ __init__(**params): Initializes the application, loads pages, and sets
+ up data update listeners.
+ view(): Creates the main application view, including a header selector
+ for switching between different pages.
+ """
datastore = param.ClassSelector(class_=datastore.DataStore)
@@ -71,21 +84,28 @@ def __init__(self, **params):
logger.info(f"Initialised pages in {time.time() - t:.2f}s")
updating = (
- self.datastore.individuals_table.data.rx.updating()
- | self.datastore.sample_sets_table.data.rx.updating()
+ self.datastore.sample_sets_table.data.rx.updating()
+ | self.datastore.individuals_table.data.rx.updating()
)
updating.rx.watch(
- lambda updating: pn.state.curdoc.hold()
- if updating
- else pn.state.curdoc.unhold()
+ lambda updating: (
+ pn.state.curdoc.hold()
+ if updating
+ else pn.state.curdoc.unhold()
+ )
)
@param.depends("views")
def view(self):
- """Main application view that renders a radio button group on
- top with links to pages. Each page consists of a main content
- page with plots and sidebars that provide user options for
- configuring plots and outputs."""
+ """Creates the main application view. Main application view that
+ renders a radio button group on top with links to pages. Each page
+ consists of a main content page with plots and sidebars that provide
+ user options for configuring plots and outputs.
+
+ Returns:
+ pn.template.FastListTemplate: A Panel template containing the
+ header selector, sidebar, and main content.
+ """
page_titles = list(self.pages.keys())
header_selector = pn.widgets.RadioButtonGroup(
options=page_titles,
@@ -105,9 +125,11 @@ def get_sidebar(selected_page):
yield self.pages[selected_page].sidebar
self._template = pn.template.FastListTemplate(
- title=self.datastore.tsm.name[:75] + "..."
- if len(self.datastore.tsm.name) > 75
- else self.datastore.tsm.name,
+ title=(
+ self.datastore.tsm.name[:75] + "..."
+ if len(self.datastore.tsm.name) > 75
+ else self.datastore.tsm.name
+ ),
header=[header_selector],
sidebar=get_sidebar,
main=get_content,
diff --git a/src/tseda/cache.py b/src/tseda/cache.py
index e519d66e..686405ee 100644
--- a/src/tseda/cache.py
+++ b/src/tseda/cache.py
@@ -1,3 +1,6 @@
+"""This module provides a caching mechanism for the TSeDA application,
+utilizing the `diskcache` library."""
+
import pathlib
import appdirs
@@ -7,7 +10,14 @@
logger = daiquiri.getLogger("cache")
-def get_cache_dir():
+def get_cache_dir() -> pathlib.Path:
+ """Retrieves the user's cache directory for the TSeDA application. Creates
+ the directory if it doesn't exist, ensuring its creation along with any
+ necessary parent directories.
+
+ Returns:
+ pathlib.Path: The path to the cache directory.
+ """
cache_dir = pathlib.Path(appdirs.user_cache_dir("tseda", "tseda"))
cache_dir.mkdir(exist_ok=True, parents=True)
return cache_dir
diff --git a/src/tseda/config.py b/src/tseda/config.py
index 83e4adea..5e88884d 100644
--- a/src/tseda/config.py
+++ b/src/tseda/config.py
@@ -1,3 +1,9 @@
+"""Config file.
+
+This file stores configurations for the entire application such as figure
+dimensions and color schemes.
+"""
+
import holoviews as hv
from holoviews.plotting.util import process_cmap
@@ -8,9 +14,9 @@
PLOT_COLOURS = ["#15E3AC", "#0FA57E", "#0D5160"]
# VCard settings
-SIDEBAR_BACKGROUND = "#15E3AC"
+SIDEBAR_BACKGROUND = "#5CB85D"
VCARD_STYLE = {
- "background": "#15E3AC",
+ "background": "WhiteSmoke",
}
# Global color map
diff --git a/src/tseda/datastore.py b/src/tseda/datastore.py
index 5ddcea58..0dd09e3a 100644
--- a/src/tseda/datastore.py
+++ b/src/tseda/datastore.py
@@ -1,4 +1,35 @@
+"""This module provides a collection of classes and functions for analyzing and
+visualizing population genetic data. It uses the `tsbrowse` library for working
+with TreeSequence data and the `panel` library for creating interactive
+visualizations.
+
+Key Classes:
+
+- `SampleSetsTable`: Manages and displays information about sample sets,
+including
+ their names, colors, and predefined status.
+- `IndividualsTable`: Handles individual data, including their population,
+sample set
+ assignments, and selection status. Enables filtering and modification of
+ individual
+ attributes.
+- `DataStore`: Provides access to the underlying TreeSequence data, sample
+sets,
+ and individuals data. Also includes methods for calculating haplotype
+ GNNs and
+ retrieving sample and population information.
+
+Methods:
+
+- `make_individuals_table`: Creates an `IndividualsTable` object from a given
+TreeSequence.
+- `make_sample_sets_table`: Creates a `SampleSetsTable` object from a given
+TreeSequence.
+- `preprocess`: Calls `make_individuals_table`and `make_sample_sets_table`.
+"""
+
import random
+from typing import Dict, List, Optional, Tuple
import daiquiri
import pandas as pd
@@ -15,45 +46,383 @@
logger = daiquiri.getLogger("tseda")
-def make_individuals_table(tsm):
- result = []
- for ts_ind in tsm.ts.individuals():
- ind = Individual(individual=ts_ind)
- result.append(ind)
- return IndividualsTable(table=pd.DataFrame(result))
+class SampleSetsTable(Viewer):
+ """SampleSetsTable class represents a table for managing sample sets.
+
+ Attributes:
+ columns (list):
+ The default columns displayed in the table (["name", "color",
+ "predefined"]).
+ editors (dict):
+ Dictionary specifying editor types for each column in the table.
+ formatters (dict):
+ Dictionary defining formatters for each column.
+ create_sample_set_textinput (String):
+ Parameter for entering a new sample set name (default=None).
+ create_sample_set_button (pn.widget.Button):
+ Button to create sample set.
+ sample_set_warning (pn.pane.Alert):
+ Warning alert for duplicate sample set names.
+ table (param.DataFrame):
+ Underlying DataFrame holding sample set data.
+
+ Methods:
+ tooltip() -> pn.widgets.TooltipIcon:
+ Returns a tooltip for the table.
+ def __panel__():
+ Creates the main panel for the table with functionalities.
+ get_ids() -> List:
+ Returns a list of sample set IDs.
+ sidebar_table() -> pn.Column:
+ Generates a sidebar table with quick view functionalities.
+ sidebar() - > pn.Column:
+ Creates the sidebar with options for managing sample sets.
+ color_by_name (dict):
+ Returns a dictionary with sample set colors as key-value pairs
+ (name-color).
+ names (dict):
+ Returns a dictionary with sample set names as key-value pairs
+ (index-name).
+ loc(self, i: int) -> pd.core.series.Series:
+ Returns a pd.core.series.Series (row) of a dataframe for a
+ specific id
+ """
+
+ columns = ["name", "color", "predefined"]
+ editors = {k: None for k in columns}
+ editors["color"] = {
+ "type": "list",
+ "values": config.COLORS,
+ "valueLookup": True,
+ }
+ editors = {
+ "name": {"type": "input", "validator": "unique", "search": True},
+ "color": {
+ "type": "list",
+ "values": [
+ {
+ "value": color,
+ "label": (
+ f''
+ ),
+ }
+ for color in config.COLORS
+ ],
+ },
+ "predefined": {"type": "tickCross"},
+ "valueLookup": True,
+ }
+ formatters = {
+ "color": {"type": "color"},
+ "predefined": {"type": "tickCross"},
+ }
+ create_sample_set_textinput = param.String(
+ doc="Enter name of new sample set.",
+ default=None,
+ label="Create new sample set",
+ )
+ create_sample_set_button = pn.widgets.Button(
+ description="Create new sample set.",
+ name="Create",
+ button_type="success",
+ align="end",
+ )
+ sample_set_warning = pn.pane.Alert(
+ "This sample set name already exists, pick a unique name.",
+ alert_type="warning",
+ visible=False,
+ )
+ table = param.DataFrame()
+ def __init__(self, **params):
+ super().__init__(**params)
+ self.table.set_index(["sample_set_id"], inplace=True)
+ self.data = self.param.table.rx()
-def make_sample_sets_table(tsm):
- result = []
- for ts_pop in tsm.ts.populations():
- ss = SampleSet(id=ts_pop.id, population=ts_pop, predefined=True)
- result.append(ss)
- return SampleSetsTable(table=pd.DataFrame(result))
+ @property
+ def tooltip(self) -> pn.widgets.TooltipIcon:
+ """Returns a TooltipIcon widget containing instructions for editing
+ sample set names and colors, and assigning individuals to sample sets.
+
+ Returns:
+ pn.widgets.TooltipIcon: A TooltipIcon widget displaying the
+ instructions.
+ """
+ return pn.widgets.TooltipIcon(
+ value=(
+ "The name and color of each sample set are editable. In the "
+ "color column, select a color from the dropdown list. In the "
+ "individuals table, you can assign individuals to sample sets."
+ ),
+ )
+ def create_new_sample_set(self):
+ """Creates a new sample set with the provided name in the
+ create_sample_set_textinput widget, if a name is entered and it's not
+ already in use."""
+ if self.create_sample_set_textinput is not None:
+ previous_names = [
+ self.table.name[i] for i in range(len(self.table))
+ ]
+ if self.create_sample_set_textinput in previous_names:
+ self.sample_set_warning.visible = True
+ else:
+ previous_colors = [
+ self.table.color[i] for i in range(len(self.table))
+ ]
+ unused_colors = [
+ color
+ for color in config.COLORS
+ if color not in previous_colors
+ ]
+ if len(unused_colors) != 0:
+ colors = unused_colors
+ else:
+ colors = config.COLORS
+ self.sample_set_warning.visible = False
+ i = max(self.param.table.rx.value.index) + 1
+ self.param.table.rx.value.loc[i] = [
+ self.create_sample_set_textinput,
+ colors[random.randint(0, len(colors) - 1)],
+ False,
+ ]
+ self.create_sample_set_textinput = None
-def preprocess(tsm):
- """Take a tsbrowse.TSModel and make individuals and sample sets tables."""
- logger.info(
- "Preprocessing data: making individuals and sample sets tables"
- )
- individuals_table = make_individuals_table(tsm)
- sample_sets_table = make_sample_sets_table(tsm)
- return individuals_table, sample_sets_table
+ def get_ids(self) -> List:
+ """Returns the sample set IDs.
+
+ Returns:
+ List: A list of the sample set IDs as integers
+
+ Raises:
+ TypeError: If the sample set table is not a valid
+ Dataframe (not yet populated)
+ """
+ if isinstance(self.table, pd.DataFrame):
+ return self.table.index.values.tolist()
+ else:
+ raise TypeError("self.table is not a valid pandas DataFrame.")
+
+ @property
+ def color_by_name(self) -> Dict[str, str]:
+ """Return the color of all sample sets as a dictionary with sample set
+ names as keys.
+
+ Returns:
+ Dict: dictionary of
+ """
+ d = {}
+ for _, row in self.data.rx.value.iterrows():
+ d[row["name"]] = row.color
+ return d
+
+ @property
+ def names(self) -> Dict[int, str]:
+ # TODO: see why this is called 6 times in a row - unecessary
+ """Return the names of all sample sets as a dictionary.
+
+ Returns:
+ Dict: dictionary of indices (int) as keys and
+ names (str) as values
+ """
+ d = {}
+ for index, row in self.data.rx.value.iterrows():
+ d[index] = row["name"]
+
+ return d
+
+ def loc(self, i: int) -> pd.core.series.Series:
+ """Returns sample set pd.core.series.Series object (dataframe row) by
+ index.
+
+ Arguments:
+ i: Index for the sample set wanted
+
+ Returns:
+ pd.core.series.Series object:
+ Containing name, color and predefined status.
+ """
+ return self.data.rx.value.loc[i]
+
+ @pn.depends("create_sample_set_button.value")
+ def __panel__(self) -> pn.Column:
+ """Returns the main content of the page which is retrieved from the
+ `datastore.tsm.ts` attribute.
+
+ Returns:
+ pn.Column: The layout for the main content area.
+ """
+ self.create_new_sample_set()
+
+ table = pn.widgets.Tabulator(
+ self.data,
+ layout="fit_data_table",
+ selectable=True,
+ page_size=10,
+ pagination="remote",
+ margin=10,
+ formatters=self.formatters,
+ editors=self.editors,
+ configuration={
+ "rowHeight": 40,
+ },
+ height=500,
+ )
+ return pn.Column(
+ self.tooltip,
+ table,
+ )
+
+ def sidebar_table(self) -> pn.Card:
+ """Generates a sidebar table with quick view functionalities.
+
+ Returns:
+ pn.Card: The layout for the sidebar.
+ """
+ table = pn.widgets.Tabulator(
+ self.data,
+ layout="fit_data_table",
+ selectable=True,
+ page_size=10,
+ pagination="remote",
+ margin=10,
+ formatters=self.formatters,
+ editors=self.editors,
+ hidden_columns=["id"],
+ )
+ return pn.Card(
+ pn.Column(self.tooltip, table),
+ title="Sample sets table quick view",
+ collapsed=True,
+ header_background=config.SIDEBAR_BACKGROUND,
+ active_header_background=config.SIDEBAR_BACKGROUND,
+ styles=config.VCARD_STYLE,
+ )
+
+ def sidebar(self) -> pn.Column:
+ """Returns the content of the sidebar.
+
+ Returns:
+ pn.Column: The layout for the sidebar.
+ """
+ return pn.Column(
+ pn.Card(
+ self.param.create_sample_set_textinput,
+ self.create_sample_set_button,
+ title="Sample sets table options",
+ collapsed=False,
+ header_background=config.SIDEBAR_BACKGROUND,
+ active_header_background=config.SIDEBAR_BACKGROUND,
+ styles=config.VCARD_STYLE,
+ ),
+ self.sample_set_warning,
+ )
class IndividualsTable(Viewer):
- """Class to hold and view individuals and perform calculations to
- change filters."""
+ """Class represents a table for managing individuals and perform
+ calculations to change filters.
+
+ Attributes:
+ sample_sets_table (param.ClassSelector):
+ ClassSelector for the SampleSetsTable class.
+ columns (list):
+ The default columns displayed in the table (["name", "color",
+ "predefined"]).
+ editors (dict):
+ Dictionary specifying editor types for each column in the table.
+ formatters (dict):
+ Dictionary defining formatters for each column.
+ filters (dict):
+ Filter configurations for the columns.
+ table (param.DataFrame):
+ Underlying data stored as a DataFrame.
+ page_size (param.Selector):
+ Number of rows per page to display.
+ sample_select (pn.widgets.MultiChoice):
+ Widget for selecting sample sets.
+ population_from (pn.widgets.Select):
+ Widget for selecting the original population ID.
+ sample_set_to (pn.widgets.Select):
+ Widget for selecting the new sample set ID.
+ mod_update_button (pn.widgets.Button):
+ Button to apply reassignment of population IDs.
+ refresh_button (pn.widgets.Button):
+ Button to refresh the table view.
+ restore_button (pn.widgets.Button):
+ Button to restore data to its original state.
+ data_mod_warning (pn.pane.Alert):
+ Warning alert for invalid modifications.
+
+
+ Methods:
+
+ tooltip() -> pn.widgets.TooltipIcon :
+ Returns a TooltipIcon widget containing information about the
+ individuals
+ table and how to edit it.
+
+ sample_sets(only_selected: Optional[bool] = True):
+ Returns a dictionary with a sample set id to samples list mapping.
+
+ get_population_ids() -> List[int]:
+ Returns a sorted list of unique population IDs present in the data.
+
+ get_sample_set_ids() -> List[int]:
+ Returns a sorted list of unique sample set IDs present in the data.
+ This method combines IDs from two sources:
+ 1. Underlying data ("sample_set_id" column).
+ 2. Optional SampleSetsTable object (if defined).
+
+ sample2ind -> Dict[int, int]:
+ Creates a dictionary mapping sample (tskit node) IDs to
+ individual IDs.
+
+ samples():
+ Yields all sample (tskit node) IDs present in the data.
+
+ loc(i: int) -> pd.core.series.Series:
+ Returns the individual data (pd.Series) for a specific index (ID).
+
+ reset_modification():
+ Resets the "sample_set_id" column to the original values from
+ "population".
+
+ combine_tables(individuals_table: param.reactive.rx) ->
+ pn.widgets.Tabulator:
+ Combines individuals and sample set data into a single table using
+ pandas.merge.
+
+ __panel__ -> pn.Column:
+ The main content of the page, retrieved from `datastore.tsm.ts`.
+ Updates options based on button interactions and returns a Column
+ layout.
+
+ options_sidebar() -> pn.Card:
+ Creates a Panel card containing options for the individuals table:
+ - Page size selector.
+ - Sample set selector.
+
+ modification_sidebar() -> pn.Column:
+ Creates a Panel column containing data modification options:
+ - Card with population from and sample set to selectors.
+ - Restore and update buttons.
+ - Warning message for invalid data.
+ """
+ sample_sets_table = param.ClassSelector(class_=SampleSetsTable)
columns = [
- "name",
+ "color",
"population",
"sample_set_id",
- "selected",
+ "name_sample_set",
+ "name_individual",
"longitude",
"latitude",
+ "selected",
]
- editors = {k: None for k in columns} # noqa
+ editors = {k: None for k in columns}
editors["sample_set_id"] = {
"type": "number",
"valueLookup": True,
@@ -63,36 +432,16 @@ class IndividualsTable(Viewer):
"values": [False, True],
"valuesLookup": True,
}
- formatters = {"selected": {"type": "tickCross"}}
-
- table = param.DataFrame()
-
- page_size = param.Selector(
- objects=[10, 20, 50, 100, 200, 500],
- default=20,
- doc="Number of rows per page to display",
- )
- sample_select = pn.widgets.MultiChoice(
- name="Select sample sets",
- description="Select samples based on the sample set ID.",
- options=[],
- )
- population_from = param.Integer(
- label="Population ID",
- default=None,
- bounds=(0, None),
- doc=("Reassign individuals with this population ID."),
- )
- sample_set_to = param.Integer(
- label="New sample set ID",
- default=None,
- bounds=(0, None),
- doc=("Reassign individuals to this sample set ID."),
- )
- mod_update_button = pn.widgets.Button(name="Update")
-
+ formatters = {
+ "selected": {"type": "tickCross"},
+ "color": {"type": "color"},
+ }
filters = {
- "name": {"type": "input", "func": "like", "placeholder": "Enter name"},
+ "name_individual": {
+ "type": "input",
+ "func": "like",
+ "placeholder": "Enter name",
+ },
"population": {
"type": "input",
"func": "like",
@@ -107,19 +456,78 @@ class IndividualsTable(Viewer):
"type": "tickCross",
"tristate": True,
"indeterminateValue": None,
- "placeholder": "Enter True/False",
+ },
+ "name_sample_set": {
+ "type": "input",
+ "func": "like",
+ "placeholder": "Enter name",
},
}
+ table = param.DataFrame()
+ page_size = param.Selector(
+ objects=[10, 20, 50, 100, 200, 500],
+ default=20,
+ doc="Number of rows per page to display",
+ )
+ sample_select = pn.widgets.MultiChoice(
+ name="Select sample sets",
+ description="Select samples based on the sample set ID.",
+ options=[],
+ )
+ population_from = pn.widgets.Select(
+ name="Original population ID",
+ value=None,
+ sizing_mode="stretch_width",
+ description=("Reassign individuals with this population ID."),
+ )
+ sample_set_to = pn.widgets.Select(
+ name="New sample set ID",
+ value=None,
+ sizing_mode="stretch_width",
+ description=("Reassign individuals to this sample set ID."),
+ )
+ mod_update_button = pn.widgets.Button(
+ name="Reassign",
+ button_type="success",
+ margin=(10, 10),
+ description="Apply reassignment.",
+ )
+ refresh_button = pn.widgets.Button(
+ name="Refresh",
+ button_type="success",
+ margin=(10, 0),
+ description="Refresh to apply updates to entire page.",
+ )
+ restore_button = pn.widgets.Button(
+ name="Restore",
+ button_type="danger",
+ margin=(10, 10),
+ description="Restore sample sets to their original state.",
+ )
+ data_mod_warning = pn.pane.Alert(
+ """Please enter a valid population ID and
+ a non-negative new sample set ID""",
+ alert_type="warning",
+ visible=False,
+ )
def __init__(self, **params):
super().__init__(**params)
self.table.set_index(["id"], inplace=True)
self.data = self.param.table.rx()
- self.sample_select.options = self.sample_set_indices()
- self.sample_select.value = self.sample_set_indices()
+ all_sample_set_ids = self.get_sample_set_ids()
+ self.sample_select.options = all_sample_set_ids
+ self.sample_select.value = all_sample_set_ids
@property
- def tooltip(self):
+ def tooltip(self) -> pn.widgets.TooltipIcon:
+ """Returns a TooltipIcon widget containing information about the
+ individuals table and how to edit it.
+
+ Returns:
+ pn.widgets.TooltipIcon: A TooltipIcon widget displaying
+ information.
+ """
return pn.widgets.TooltipIcon(
value=(
"Individuals table with columns relevant for modifying plots. "
@@ -136,34 +544,75 @@ def tooltip(self):
),
)
- def sample_set_indices(self):
- """Return indices of sample groups."""
- return sorted(self.data.rx.value["sample_set_id"].unique().tolist())
+ def sample_sets(self, only_selected: Optional[bool] = True):
+ """Returns a dictionary with a sample set id to samples list mapping.
+
+ Arguments:
+ only_selected (bool, optional): If True, only considers
+ individuals marked as selected in the table. Defaults to True.
- def sample_sets(self):
+ Returns:
+ dict: A dictionary where keys are sample set IDs and values are
+ lists of samples (tskit node IDs) belonging to that set. If
+ `only_selected` is True, only samples marked as selected are
+ included in the lists.
+ """
sample_sets = {}
- samples = []
inds = self.data.rx.value
for _, ind in inds.iterrows():
- if not ind.selected:
+ if not ind.selected and only_selected:
continue
sample_set = ind.sample_set_id
if sample_set not in sample_sets:
sample_sets[sample_set] = []
sample_sets[sample_set].extend(ind.nodes)
- samples.extend(ind.nodes)
- return samples, sample_sets
+ return sample_sets
- def get_sample_sets(self, indexes=None):
- """Return list of sample sets and their samples."""
- samples, sample_sets = self.sample_sets()
- if indexes:
- return [sample_sets[i] for i in indexes]
- return [sample_sets[i] for i in sample_sets]
+ def get_population_ids(self) -> List[int]:
+ """Returns a sorted list of unique population IDs present in the data.
+
+ Returns:
+ list: A list containing all unique population IDs in the table.
+ """
+ return sorted(self.data.rx.value["population"].unique().tolist())
+
+ def get_sample_set_ids(self) -> List[int]:
+ """Returns a sorted list of unique sample set IDs present in the data.
+
+ This method combines sample set IDs from two sources:
+
+ 1. Unique IDs from the "sample_set_id" column of the underlying data
+ (self.data.rx.value).
+ 2. (Optional) IDs retrieved from the SampleSetsTable object
+ (accessed through self.sample_sets_table) iff it is defined.
+
+ Returns:
+ list: A sorted list containing all unique sample set IDs found in
+ the data and potentially from the `SampleSetsTable`.
+ """
+ individuals_sets = sorted(self.data.rx.value["sample_set_id"].tolist())
+ if self.sample_sets_table is not None: # Nonetype when not yet defined
+ individuals_sets = (
+ individuals_sets + self.sample_sets_table.get_ids()
+ )
+ return sorted(list(set(individuals_sets)))
@property
- def sample2ind(self):
- """Map sample (tskit node) ids to individual ids"""
+ def sample2ind(self) -> Dict[int, int]:
+ """Creates a dictionary that maps sample (tskit node) IDs to individual
+ IDs.
+
+ This method iterates through the underlying data and builds a
+ dictionary where:
+ Keys are sample (tskit node) IDs. Values are the corresponding
+ individual IDs
+ (indices) in the data.
+
+ Returns:
+ dict: A dictionary mapping sample (tskit node) IDs to their
+ corresponding
+ individual IDs.
+ """
inds = self.data.rx.value
d = {}
for index, ind in inds.iterrows():
@@ -172,252 +621,248 @@ def sample2ind(self):
return d
def samples(self):
- """Return all samples"""
+ """Yields all sample (tskit node) IDs present in the data.
+
+ This method iterates through the underlying data and yields each sample
+ (tskit node) ID.
+
+ Yields:
+ int: Sample (tskit node) ID from the data.
+ """
+
for _, ind in self.data.rx.value.iterrows():
for node in ind.nodes:
yield node
- def loc(self, i):
- """Return individual by index"""
+ def loc(self, i: int) -> pd.core.series.Series:
+ """Returns the individual data, pd.core.series.Series object, for a
+ specific index (ID) i.
+
+ Arguments:
+ i (int): The index (ID) of the individual to retrieve.
+
+ Returns:
+ pd.core.series.Series: A pandas Series representing the individual
+ data corresponding to the provided index.
+ """
return self.data.rx.value.loc[i]
- @pn.depends("page_size", "sample_select.value", "mod_update_button.value")
- def __panel__(self):
- self.data.rx.value["selected"] = False
- if (
- isinstance(self.sample_select.value, list)
- and self.sample_select.value
- ):
- for sample_set_id in self.sample_select.value:
- self.data.rx.value.loc[
- self.data.rx.value.sample_set_id == sample_set_id,
- "selected",
- ] = True
- if self.sample_set_to is not None:
- if self.population_from is not None:
- try:
- self.table.loc[
- self.table["population"] == self.population_from, # pyright: ignore[reportIndexIssue]
- "sample_set_id",
- ] = self.sample_set_to
- except IndexError:
- logger.error("No such population %i", self.population_from)
- else:
- logger.info("No population defined")
- data = self.data[self.columns]
+ def reset_modification(self):
+ """Resets the "sample_set_id" column of the underlying data
+ (`self.data.rx.value`) back to the original values from the
+ "population" column.
+
+ This effectively undoes any modifications made to sample set
+ assignments.
+ """
+ self.data.rx.value.sample_set_id = self.data.rx.value.population
+
+ def combine_tables(
+ self, individuals_table: param.reactive.rx
+ ) -> pn.widgets.Tabulator:
+ """Combines individuals data and sample set data into a single table.
+
+ This method merges the data from two sources:
+
+ 1. The individuals data (`individuals_table.rx.value`) from the
+ provided
+ `individuals_table` argument.
+ 2. The sample set data (`self.sample_sets_table.data.rx.value`)
+ from the `SampleSetsTable` object (accessed through
+ `self.sample_sets_table`)
+ if it's defined.
+
+ The merge is performed using pandas.merge based on the
+ "sample_set_id" column.
+ The resulting table includes additional columns with suffixes
+ indicating their
+ origin (e.g., "_individual" for data from `individuals_table`).
+
+ Arguments:
+ individuals_table (aram.reactive.rx object):
+ An object containing the individuals data table.
+
+ Returns:
+ pn.widgets.Tabulator:
+ A Tabulator widget representing the combined individuals and
+ sample set data.
+ """
+
+ combined_df = pd.merge(
+ individuals_table.rx.value,
+ self.sample_sets_table.data.rx.value,
+ left_on="sample_set_id",
+ right_index=True,
+ suffixes=("_individual", "_sample_set"),
+ )
- table = pn.widgets.Tabulator(
- data,
+ combined_df["id"] = combined_df.index
+ combined_df = combined_df[self.columns]
+
+ combined_table = pn.widgets.Tabulator(
+ combined_df,
pagination="remote",
layout="fit_columns",
selectable=True,
page_size=self.page_size,
formatters=self.formatters,
editors=self.editors,
+ sorters=[
+ {"field": "id", "dir": "asc"},
+ {"field": "selected", "dir": "des"},
+ ],
margin=10,
text_align={col: "right" for col in self.columns},
header_filters=self.filters,
)
- return pn.Column(self.tooltip, table)
-
- def options_sidebar(self):
- return pn.Card(
- self.param.page_size,
- self.sample_select,
- collapsed=False,
- title="Individuals table options",
- header_background=config.SIDEBAR_BACKGROUND,
- active_header_background=config.SIDEBAR_BACKGROUND,
- styles=config.VCARD_STYLE,
- )
-
- modification_header = pn.pane.Markdown("#### Batch reassign indivuduals:")
-
- def modification_sidebar(self):
- return pn.Card(
- pn.Column(
- self.modification_header,
- pn.Row(self.param.population_from, self.param.sample_set_to),
- self.mod_update_button,
- ),
- collapsed=False,
- title="Data modification",
- header_background=config.SIDEBAR_BACKGROUND,
- active_header_background=config.SIDEBAR_BACKGROUND,
- styles=config.VCARD_STYLE,
- )
-
-
-class SampleSetsTable(Viewer):
- default_columns = ["name", "color", "predefined"]
- editors = {k: None for k in default_columns}
- editors["color"] = {
- "type": "list",
- "values": config.COLORS,
- "valueLookup": True,
- }
- editors["name"] = {"type": "input", "validator": "unique", "search": True}
- formatters = {
- "color": {"type": "color"},
- "predefined": {"type": "tickCross"},
- }
-
- create_sample_set_textinput = param.String(
- doc="New sample set name. Press Enter (⏎) to create.",
- default=None,
- label="New sample set name",
- )
-
- warning_pane = pn.pane.Alert(
- "This sample set name already exists, pick a unique name.",
- alert_type="warning",
- visible=False,
+ return combined_table
+
+ @pn.depends(
+ "page_size",
+ "sample_select.value",
+ "mod_update_button.value",
+ "refresh_button.value",
+ "restore_button.value",
+ "sample_sets_table.create_sample_set_button.value",
)
+ def __panel__(self) -> pn.Column:
+ """Returns the main content of the page which is retrieved from the
+ `datastore.tsm.ts` attribute.
+
+ Returns:
+ pn.Column: The layout for the main content area.
+ """
+ self.population_from.options = self.get_population_ids()
+ all_sample_set_ids = self.get_sample_set_ids()
+ self.sample_set_to.options = all_sample_set_ids
+ self.sample_select.options = all_sample_set_ids
+
+ if isinstance(self.sample_select.value, list):
+ self.data.rx.value["selected"] = False
+ for sample_set_id in self.sample_select.value:
+ self.data.rx.value.loc[
+ self.data.rx.value.sample_set_id == sample_set_id,
+ "selected",
+ ] = True
+ if (
+ isinstance(self.mod_update_button.value, bool)
+ and self.mod_update_button.value
+ ):
+ self.table.loc[
+ self.table["population"] == self.population_from.value, # pyright: ignore[reportIndexIssue]
+ "sample_set_id",
+ ] = self.sample_set_to.value
- page_size = param.Selector(objects=[10, 20, 50, 100], default=20)
+ if (
+ isinstance(self.restore_button.value, bool)
+ and self.restore_button.value
+ ):
+ self.reset_modification()
- table = param.DataFrame()
+ data = self.data
- def __init__(self, **params):
- super().__init__(**params)
- self.table.set_index(["id"], inplace=True)
- self.data = self.param.table.rx()
+ table = self.combine_tables(data)
- @property
- def tooltip(self):
- return pn.widgets.TooltipIcon(
- value=(
- "The name and color of each sample set are editable. In the "
- "color column, select a color from the dropdown list. In the "
- "individuals table, you can assign individuals to sample sets."
- ),
- )
+ return pn.Column(pn.Row(self.tooltip, align=("start", "end")), table)
- @pn.depends("page_size", "create_sample_set_textinput") # , "columns")
- def __panel__(self):
- if self.create_sample_set_textinput is not None:
- previous_names = [
- self.table.name[i] for i in range(len(self.table))
- ]
- if self.create_sample_set_textinput in previous_names:
- self.warning_pane.visible = True
- else:
- previous_colors = [
- self.table.color[i] for i in range(len(self.table))
- ]
- unused_colors = [
- color
- for color in config.COLORS
- if color not in previous_colors
- ]
- if len(unused_colors) != 0:
- colors = unused_colors
- else:
- colors = config.COLORS
- self.warning_pane.visible = False
- i = max(self.param.table.rx.value.index) + 1
- self.param.table.rx.value.loc[i] = [
- self.create_sample_set_textinput,
- colors[random.randint(0, len(colors) - 1)],
- False,
- ]
- self.create_sample_set_textinput = None
- table = pn.widgets.Tabulator(
- self.data,
- layout="fit_data_table",
- selectable=True,
- page_size=self.page_size,
- pagination="remote",
- margin=10,
- formatters=self.formatters,
- editors=self.editors,
- )
- return pn.Column(self.tooltip, table)
+ def options_sidebar(self) -> pn.Card:
+ """Creates a Panel card containing options for the individuals table.
- def sidebar_table(self):
- table = pn.widgets.Tabulator(
- self.data,
- layout="fit_data_table",
- selectable=True,
- page_size=10,
- pagination="remote",
- margin=10,
- formatters=self.formatters,
- editors=self.editors,
- hidden_columns=["id"],
- )
+ Returns:
+ pn.Card: A Panel card containing the following options:
+ - Page size selector: Allows the user to adjust the number of
+ rows per page.
+ - Sample set selector: Allows the user to select specific
+ sample sets to filter the data.
+ """
return pn.Card(
- pn.Column(self.tooltip, table),
- title="Sample sets table quick view",
- collapsed=True,
+ self.param.page_size,
+ self.sample_select,
+ collapsed=False,
+ title="Individuals table options",
header_background=config.SIDEBAR_BACKGROUND,
active_header_background=config.SIDEBAR_BACKGROUND,
styles=config.VCARD_STYLE,
)
- def sidebar(self):
+ def modification_sidebar(self) -> pn.Column:
+ """Creates a Panel column containing the data modification options.
+
+ Returns:
+ pn.Column: A Panel column containing the following elements:
+ - A card with the following options:
+ - Population from selector: Allows the user to select the
+ original population ID.
+ - Sample set to selector: Allows the user to select the
+ new sample set ID.
+ - Restore button: Resets modifications.
+ - Update button: Applies the modifications.
+ - A warning message (`self.data_mod_warning`) that is displayed
+ when invalid data is entered.
+ """
+ modification_header = pn.pane.HTML(
+ "Batch reassign individuals
"
+ )
return pn.Column(
pn.Card(
- self.param.page_size,
- self.param.create_sample_set_textinput,
- title="Sample sets table options",
+ modification_header,
+ pn.Row(self.population_from, self.sample_set_to),
+ pn.Row(
+ pn.Spacer(width=120),
+ self.restore_button,
+ self.mod_update_button,
+ align="end",
+ ),
collapsed=False,
+ title="Data modification",
header_background=config.SIDEBAR_BACKGROUND,
active_header_background=config.SIDEBAR_BACKGROUND,
styles=config.VCARD_STYLE,
),
- self.warning_pane,
+ self.data_mod_warning,
)
- @property
- def color(self):
- """Return the color of all sample sets as a dictionary"""
- d = {}
- for index, row in self.data.rx.value.iterrows():
- d[index] = row.color
- return d
-
- @property
- def color_by_name(self):
- """Return the color of all sample sets as a dictionary with
- sample set names as keys"""
- d = {}
- for _, row in self.data.rx.value.iterrows():
- d[row["name"]] = row.color
- return d
-
- @property
- def names(self):
- """Return the names of all sample sets as a dictionary"""
- d = {}
- for index, row in self.data.rx.value.iterrows():
- d[index] = row["name"]
- return d
-
- @property
- def names2id(self):
- """Return the sample sets as dictionary with names as keys,
- ids as values"""
- d = {}
- for index, row in self.data.rx.value.iterrows():
- d[row["name"]] = index
- return d
-
- def loc(self, i):
- """Return sample set by index"""
- return self.data.rx.value.loc[i]
-
class DataStore(Viewer):
+ """Class representing a data store for managing and accessing data used for
+ analysis. This class provides access to various data sources and
+ functionalities related to individuals, sample sets, and the underlying
+ TreeSequenceModel.
+
+ Attributes:
+ tsm (param.ClassSelector):
+ ClassSelector for the model.TSModel object holding the TreeSequence
+ data.
+ sample_sets_table (param.ClassSelector):
+ ClassSelector for the SampleSetsTable object managing sample set
+ information.
+ individuals_table (param.ClassSelector):
+ ClassSelector for the IndividualsTable object handling individual
+ data and filtering.
+ views (param.List, constant=True):
+ A list of views to be displayed.
+
+ Methods:
+ color(self) -> pd.core.series.Series:
+ Returns a pandas DataFrame containing the colors of selected
+ individuals
+ merged with their corresponding sample set names.
+
+ haplotype_gnn(self, focal_ind, windows=None):
+ Calculates and returns the haplotype Genealogical Nearest
+ Neighbors (GNN)
+ for a specified focal individual and optional window sizes.
+ """
+
tsm = param.ClassSelector(class_=model.TSModel)
- individuals_table = param.ClassSelector(class_=IndividualsTable)
sample_sets_table = param.ClassSelector(class_=SampleSetsTable)
+ individuals_table = param.ClassSelector(class_=IndividualsTable)
views = param.List(constant=True)
@property
- def color(self):
- """Return colors of selected individuals"""
+ def color(self) -> pd.core.series.Series:
+ """Return colors of selected individuals."""
color = pd.merge(
self.individuals_table.data.rx.value,
self.sample_sets_table.data.rx.value,
@@ -426,8 +871,27 @@ def color(self):
)
return color.loc[color.selected].color
- def haplotype_gnn(self, focal_ind, windows=None):
- samples, sample_sets = self.individuals_table.sample_sets()
+ def haplotype_gnn(
+ self, focal_ind: int, windows: Optional[List[int]] = None
+ ) -> pd.DataFrame:
+ """Calculates and returns the haplotype Genealogical Nearest Neighbors
+ (GNN) for a specified focal individual and optional window sizes.
+
+ Arguments:
+ focal_ind (int): The index (ID) of the focal individual within the
+ individuals table.
+ windows (List[int], optional): A list of window sizes for
+ calculating
+ GNNs within those specific windows. If None, GNNs are
+ calculated
+ across the entire sequence length.
+
+ Returns:
+ pandas.DataFrame: A DataFrame containing GNN information for each
+ haplotype.
+ """
+ print("ksbhflbsdfj", type(focal_ind), type(windows))
+ sample_sets = self.individuals_table.sample_sets()
ind = self.individuals_table.loc(focal_ind)
hap = windowed_genealogical_nearest_neighbours(
self.tsm.ts, ind.nodes, sample_sets, windows=windows
@@ -457,9 +921,71 @@ def haplotype_gnn(self, focal_ind, windows=None):
df.set_index(["haplotype", "start", "end"], inplace=True)
return df
- # Not needed? Never used?
- def __panel__(self):
- return pn.Row(
- self.individuals_table,
- self.sample_sets_table,
+
+def make_individuals_table(tsm: model.TSModel) -> IndividualsTable:
+ """Creates an IndividualsTable object from the data in the provided TSModel
+ object, by iterating through the individuals in the tree sequence and
+ creates an Individual object for each one, creating a Pandas DataFrame
+ populated with the individual level information.
+
+ Arguments:
+ tsm (model.TSModel): The TSModel object containing the tree
+ sequence data.
+
+ Returns:
+ IndividualsTable: An IndividualsTable object populated with
+ individual level information from the tree sequence.
+ """
+ result = []
+ for ts_ind in tsm.ts.individuals():
+ ind = Individual(individual=ts_ind)
+ result.append(ind)
+ return IndividualsTable(table=pd.DataFrame(result))
+
+
+def make_sample_sets_table(tsm: model.TSModel) -> SampleSetsTable:
+ """Creates a SampleSetsTable object from the data in the provided TSModel
+ object, by iterating through the populations in the tree sequence and
+ creates a SampleSet object for each one, creating a Pandas DataFrame
+ populated with the population level information.
+
+ Arguments:
+ tsm (model.TSModel): The TSModel object containing the tree
+ sequence data.
+
+ Returns:
+ SampleSet: A SampleSet object populated with
+ population level information from the tree sequence.
+ """
+ result = []
+ for ts_pop in tsm.ts.populations():
+ ss = SampleSet(
+ sample_set_id=ts_pop.id, population=ts_pop, predefined=True
)
+ result.append(ss)
+ return SampleSetsTable(table=pd.DataFrame(result))
+
+
+def preprocess(tsm: model.TSModel) -> Tuple[IndividualsTable, SampleSetsTable]:
+ """Take a TSModel and creates IndividualsTable and SampleSetsTable objects
+ from the data in the provided TSModel object.
+
+ Arguments:
+ tsm (model.TSModel): The TSModel object containing the tree sequence
+ data.
+
+ Returns:
+ Tuple[IndividualsTable, SampleSetsTable]: A tuple containing two
+ elements:
+ IndividualsTable: An IndividualsTable object populated with
+ individual
+ information from the tree sequence.
+ SampleSetsTable: A SampleSetsTable object populated with population
+ information from the tree sequence.
+ """
+ logger.info(
+ "Preprocessing data: making individuals and sample sets tables"
+ )
+ sample_sets_table = make_sample_sets_table(tsm)
+ individuals_table = make_individuals_table(tsm)
+ return individuals_table, sample_sets_table
diff --git a/src/tseda/gnn.py b/src/tseda/gnn.py
index de27625a..e3d00567 100644
--- a/src/tseda/gnn.py
+++ b/src/tseda/gnn.py
@@ -1,10 +1,8 @@
-"""Helper code to compute genealogical nearest neighbours along
-haplotypes.
+"""Helper code to compute genealogical nearest neighbours along haplotypes.
Based on code from tskit.tests.test_stats:
https://github.com/tskit-dev/tskit/pull/683/files#diff-e5e589330499b325320b2e3c205eaf350660b50691d3e1655f8789683e49dca6R399
-
"""
import numpy as np
diff --git a/src/tseda/main.py b/src/tseda/main.py
index 3ab85f92..17f49bba 100644
--- a/src/tseda/main.py
+++ b/src/tseda/main.py
@@ -1,14 +1,16 @@
-"""Helper module for serving the TSEda app from the command line using
-panel serve.
+"""Helper module for serving the TSEda app from the command line using panel
+serve.
-This module is used to serve the TSEda app from the command line using
-panel serve. One use case is for development purposes where the --dev
-argument enables automated reloading of the app when the source code
-changes. To launch the app from the command line run:
+This module is used to serve the TSEda app from the command line using panel
+serve. One use case is for development purposes where the --dev argument
+enables automated reloading of the app when the source code changes. To launch
+the app from the command line run:
- $ panel serve --dev --admin --show --args path/to/tszip_file.zip
+$ panel serve --dev --admin --show --args path/to/tszip_file.zip
-See https://panel.holoviz.org/how_to/server/commandline.html for more
+See
+https://panel.holoviz.org/how_to/server/commandline.html
+for more
information.
"""
@@ -36,8 +38,8 @@
app_ = app.DataStoreApp(
datastore=datastore.DataStore(
tsm=tsm,
- individuals_table=individuals_table,
sample_sets_table=sample_sets_table,
+ individuals_table=individuals_table,
),
title="TSEda Datastore App",
views=[datastore.IndividualsTable],
diff --git a/src/tseda/model.py b/src/tseda/model.py
index 679c60f0..569b9dd3 100644
--- a/src/tseda/model.py
+++ b/src/tseda/model.py
@@ -13,7 +13,6 @@
- simplify haplotype_gnn function
- cache computations!
-
"""
import dataclasses
@@ -32,9 +31,7 @@
class DataTypes(Enum):
- """
- Enum for getter method data types
- """
+ """Enum for getter method data types."""
LIST = "list"
DATAFRAME = "df"
@@ -42,7 +39,7 @@ class DataTypes(Enum):
def decode_metadata(obj):
- """Decode metadata from bytes to dict"""
+ """Decode metadata from bytes to dict."""
if not hasattr(obj, "metadata"):
return None
if isinstance(obj.metadata, bytes):
@@ -55,7 +52,7 @@ def decode_metadata(obj):
def parse_metadata(obj, regex):
- """Retrieve metadata value pairs based on key regex"""
+ """Retrieve metadata value pairs based on key regex."""
md = decode_metadata(obj)
if md is None:
return
@@ -66,7 +63,7 @@ def parse_metadata(obj, regex):
def palette(cmap=Set3[12], n=12, start=0, end=1):
- """Make a small colorblind-friendly palette"""
+ """Make a small colorblind-friendly palette."""
import matplotlib
linspace = np.linspace(start, end, n)
@@ -80,13 +77,11 @@ def palette(cmap=Set3[12], n=12, start=0, end=1):
@dataclasses.dataclass
class SampleSet:
- """
- A class to contain sample sets.
- """
+ """A class to contain sample sets."""
name_re = re.compile(r"^(name|Name|population|Population)$")
- id: np.int32
+ sample_set_id: np.int32
name: str = None
color: str = None
population: dataclasses.InitVar[tskit.Population | None] = None
@@ -96,18 +91,16 @@ class SampleSet:
def __post_init__(self, population):
if self.color is None:
- self.color = self.colormap[self.id % len(self.colormap)]
+ self.color = self.colormap[self.sample_set_id % len(self.colormap)]
if population is not None:
self.name = parse_metadata(population, self.name_re)
if self.name is None:
- self.name = f"SampleSet-{self.id}"
+ self.name = f"SampleSet-{self.sample_set_id}"
@dataclasses.dataclass
class Individual(tskit.Individual):
- """
- A class to handle individuals.
- """
+ """A class to handle individuals."""
name_re = re.compile(r"^(name|Name|SM)$")
longitude_re = re.compile(r"^(longitude|Longitude|lng|long)$")
@@ -140,17 +133,17 @@ def __post_init__(self) -> None:
@property
def samples(self):
- """Return samples (nodes) associated with individual"""
+ """Return samples (nodes) associated with individual."""
return self.nodes
def toggle(self) -> None:
- """Toggle selection status"""
+ """Toggle selection status."""
self.selected = not self.selected
def select(self) -> None:
- """Select individual"""
+ """Select individual."""
self.selected = True
def deselect(self) -> None:
- """Deselect individual"""
+ """Deselect individual."""
self.selected = False
diff --git a/src/tseda/vpages/__init__.py b/src/tseda/vpages/__init__.py
index a481db36..25f0ec95 100644
--- a/src/tseda/vpages/__init__.py
+++ b/src/tseda/vpages/__init__.py
@@ -2,7 +2,6 @@
ignn,
individuals,
overview,
- sample_sets,
stats,
structure,
trees,
@@ -10,7 +9,6 @@
PAGES = [
overview.OverviewPage,
- sample_sets.SampleSetsPage,
individuals.IndividualsPage,
structure.StructurePage,
ignn.IGNNPage,
diff --git a/src/tseda/vpages/core.py b/src/tseda/vpages/core.py
index 544bf7ae..2b193abc 100644
--- a/src/tseda/vpages/core.py
+++ b/src/tseda/vpages/core.py
@@ -1,7 +1,7 @@
"""Core vpages module.
-Provides View helper class for panel plots and helper functions common
-to pages.
+Provides View helper class for panel plots and helper functions common to
+pages.
"""
import numpy as np
diff --git a/src/tseda/vpages/ignn.py b/src/tseda/vpages/ignn.py
index dce4dd57..482b064f 100644
--- a/src/tseda/vpages/ignn.py
+++ b/src/tseda/vpages/ignn.py
@@ -15,6 +15,8 @@
- linked brushing between the map and the GNN plot
"""
+from typing import Any, Union
+
import holoviews as hv
import hvplot.pandas # noqa
import pandas as pd
@@ -37,11 +39,30 @@
class GNNHaplotype(View):
- """Make GNN haplotype plot."""
+ """Make GNN haplotype plot. This class creates a Panel object that displays
+ a GNN haplotype plot for a selected individual.
+
+ Attributes:
+ individual_id (int): the ID of the individual to visualize (0-indexed).
+ Defaults to None.
+ window_size (int): The size of the window to use for visualization.
+ Defaults to 10000. Must be greater than 0.
+ warning_pane (pn.Alert): a warning panel that is displayed if no
+ samples are selected.
+ individual_id_warning (pn.Alert): a warning panel that is displayed
+ if an invalid individual ID is entered.
+
+ Methods:
+ plot(haplotype=0): makes the haplotype plot.
+ plot_haplotype0(): calls the plot function for haplotype 0.
+ plot_haplotype1(): calls the plot function for haplotype 1.
+ __panel__() -> pn.Column: Defines the layout of the main content area
+ or sends out a warning message if the user input isn't valid.
+ sidebar() -> pn.Card: Defines the layout of the sidebar content area.
+ """
individual_id = param.Integer(
default=None,
- bounds=(0, None),
doc="Individual ID (0-indexed)",
)
@@ -56,9 +77,32 @@ class GNNHaplotype(View):
visible=False,
)
- def plot(self, haplotype=0):
+ individual_id_warning = pn.pane.Alert(
+ "",
+ alert_type="warning",
+ visible=False,
+ )
+
+ def plot(
+ self, haplotype: int = 0
+ ) -> Union[hv.core.overlay.NdOverlay, pn.pane.Markdown]:
+ """Creates the GNN Haplotype plot.
+
+ Args:
+ haplotype (int): Can be either 0 or 1 and will be used to plot
+ haplotype 0 or haplotype 1.
+
+
+ Returns:
+ pn.pane.Markdown: A message directed to the user to enter a valid
+ correct sample ID.
+ pn.pane.Markdown: A placeholder pane in place to show the
+ warningmessage when a incorrect sample ID is entered.
+ hv.core.overlay.NdOverlay: A GNN Haplotype plot.
+ """
+
if self.individual_id is None:
- return
+ return pn.pane.Markdown("Enter a sample ID")
if self.window_size is not None:
windows = make_windows(
self.window_size, self.datastore.tsm.ts.sequence_length
@@ -122,25 +166,121 @@ def plot(self, haplotype=0):
)
return p
+ def plot_haplotype0(
+ self,
+ ) -> Union[hv.core.overlay.NdOverlay, pn.pane.Markdown]:
+ """Creates the GNN Haplotype plot for haplotype 0.
+
+ Returns:
+ pn.pane.Markdown: A message directed to the user to enter a valid
+ correct sample ID.
+ pn.pane.Markdown: A placeholder pane in place to show the
+ warningmessage when a incorrect sample ID is entered.
+ hv.core.overlay.NdOverlay: A GNN Haplotype plot for haplotype 0.
+ """
+ return self.plot(0)
+
+ def plot_haplotype1(
+ self,
+ ) -> Union[hv.core.overlay.NdOverlay, pn.pane.Markdown]:
+ """Creates the GNN Haplotype plot for haplotype 1.
+
+ Returns:
+ pn.pane.Markdown: A message directed to the user to enter a valid
+ correct sample ID.
+ pn.pane.Markdown: A placeholder pane in place to show the
+ warningmessage when a incorrect sample ID is entered.
+ hv.core.overlay.NdOverlay: A GNN Haplotype plot for haplotype 1.
+ """
+ return self.plot(1)
+
+ def check_inputs(self, inds: pd.core.frame.DataFrame) -> tuple:
+ """Checks the inputs to the GNN Haplotype plot.
+
+ Args:
+ inds (pandas.core.frame.DataFrame): Contains the data in the
+ individuals table.
+
+ Returns:
+ pn.pane.Column: If the input argument is valid this coloumn will
+ return the nodes of the index and an empty Coloumn. Otherwise it
+ will return a None value and a Coloumn telling the user to enter a
+ valid sample ID.
+ """
+ max_id = inds.index.max()
+ info_column = pn.Column(
+ pn.pane.Markdown(
+ "**Enter a valid sample id to see the GNN haplotype plot.**"
+ ),
+ )
+ if self.individual_id is None:
+ self.individual_id_warning.visible = False # No warning for None
+ return None, info_column
+
+ try:
+ if (
+ not isinstance(self.individual_id, (int, float))
+ or self.individual_id < 0
+ ):
+ self.individual_id_warning.object = (
+ "The individual ID does not exist. "
+ f"Valid IDs are in the range 0-{max_id}."
+ )
+ self.individual_id_warning.visible = True
+ return (None, info_column)
+ else:
+ self.individual_id_warning.visible = False
+ nodes = inds.loc[self.individual_id].nodes
+ info_column = pn.Column(pn.pane.Markdown(""))
+ return (nodes, info_column)
+ except KeyError:
+ self.individual_id_warning.object = (
+ "The individual ID does not exist. "
+ f"Valid IDs are in the range 0-{max_id}."
+ )
+ self.individual_id_warning.visible = True
+ return (None, info_column)
+
@pn.depends("individual_id", "window_size")
- def __panel__(self, **params):
+ def __panel__(self, **params) -> pn.Column:
+ """Returns the main content for the GNN Haplotype plot which is
+ retrieved from the `datastore.tsm.ts` attribute.
+
+ Returns:
+ pn.Column: The layout for the main content area of the GNN
+ Haplotype plot or a warning message if the input isn't validated.
+ """
+
inds = self.datastore.individuals_table.data.rx.value
- if self.individual_id is None:
- return pn.pane.Markdown("")
- nodes = inds.loc[self.individual_id].nodes
- return pn.Column(
- pn.pane.Markdown(f"## Individual id {self.individual_id}"),
- self.warning_pane,
- pn.pane.Markdown(f"### Haplotype 0 (sample id {nodes[0]})"),
- self.plot(0),
- pn.pane.Markdown(f"### Haplotype 1 (sample id {nodes[1]})"),
- self.plot(1),
- )
+ nodes = self.check_inputs(inds)
+ if nodes[0] is not None:
+ return pn.Column(
+ pn.pane.HTML(
+ ""
+ f"- Individual id {self.individual_id}
",
+ sizing_mode="stretch_width",
+ ),
+ self.warning_pane,
+ pn.pane.Markdown(f"### Haplotype 0 (sample id {nodes[0][0]})"),
+ self.plot_haplotype0,
+ pn.pane.Markdown(f"### Haplotype 1 (sample id {nodes[0][1]})"),
+ self.plot_haplotype0,
+ )
+ else:
+ return nodes[1]
- def sidebar(self):
+ def sidebar(self) -> pn.Card:
+ """Returns the content of the sidbar options for the GNN Haplotype
+ plot.
+
+ Returns:
+ pn.Card: The layout for the sidebar content area connected to the
+ GNN Haplotype plot.
+ """
return pn.Card(
self.param.individual_id,
self.param.window_size,
+ self.individual_id_warning,
collapsed=False,
title="GNN haplotype options",
header_background=config.SIDEBAR_BACKGROUND,
@@ -150,7 +290,24 @@ def sidebar(self):
class VBar(View):
- """Make VBar plot of GNN output."""
+ """Make VBar plot of GNN output. This class creates a Panel object that
+ displays a VBar plot of the sample sets.
+
+ Attributes:
+ sorting (pn.Selector): the selected population to base the sort order
+ on.
+ sort_order (pn.Selector): the selected sorting order
+ (Ascending/Descending)
+ warning_pane (pn.Alert): a warning panel that is displayed if no
+ samples are selected.
+
+ Methods:
+ gnn() -> pd.DataFrame: gets the data for the GNN VBar plot.
+ __panel__() -> pn.panel: creates the panel containing the GNN VBar
+ plot.
+ sidebar() -> pn.Card: defines the layout of the sidebar content area
+ for the VBar options.
+ """
sorting = param.Selector(
doc="Select what population to base the sort order on. Default is "
@@ -173,9 +330,18 @@ class VBar(View):
)
# TODO: move to DataStore class?
- def gnn(self):
+ def gnn(self) -> pd.DataFrame:
+ """Creates the data for the GNN VBar plot.
+
+ Returns:
+ pd.DataFrame: a dataframe containing all the information for the
+ GNN VBar plot.
+ """
inds = self.datastore.individuals_table.data.rx.value
- samples, sample_sets = self.datastore.individuals_table.sample_sets()
+ sample_sets = self.datastore.individuals_table.sample_sets()
+ samples = [
+ sample for sublist in sample_sets.values() for sample in sublist
+ ]
self.param.sorting.objects = [""] + list(
self.datastore.sample_sets_table.names.values()
)
@@ -196,9 +362,19 @@ def gnn(self):
return df
@pn.depends("sorting", "sort_order")
- def __panel__(self):
- samples, sample_sets = self.datastore.individuals_table.sample_sets()
+ def __panel__(self) -> Union[pn.pane.plot.Bokeh, pn.pane.Alert, Any]:
+ # TODO: Does not accept pn.panel so Any is included as quickfix
+ """Returns the main content of the plot which is retrieved from the
+ `datastore.tsm.ts` attribute by the gnn() function.
+
+ Returns:
+ pn.pane.Alert: a warning pane telling the user that it needs to
+ select a sample.
+ pn.pane.plot.Bokeh: a panel with the GNN VBar plot.
+ """
+ sample_sets = self.datastore.individuals_table.sample_sets()
if len(list(sample_sets.keys())) < 1:
+ print(type(self.warning_pane))
return self.warning_pane
df = self.gnn()
sample_sets = self.datastore.sample_sets_table.data.rx.value
@@ -233,6 +409,15 @@ def __panel__(self):
["sample_set_id"] + [self.sorting] + ["sample_id", "id"] # pyright: ignore[reportOperatorIssue]
)
ascending = [True, False, False, False]
+
+ columns = df.columns.tolist()
+ columns.remove(self.sorting)
+ id_index = columns.index("id")
+ columns.insert(id_index + 1, self.sorting)
+ df = df[columns]
+ sorting_index = groups.index(self.sorting)
+ groups[sorting_index], groups[0] = groups[0], groups[sorting_index]
+ color[sorting_index], color[0] = color[0], color[sorting_index]
else:
sort_by = ["sample_set_id", "sample_id", "id"]
ascending = [True, False, False]
@@ -288,10 +473,15 @@ def __panel__(self):
fig.xaxis.separator_line_width = 2.0
fig.xaxis.separator_line_color = "grey"
fig.xaxis.separator_line_alpha = 0.5
-
return pn.panel(fig)
def sidebar(self):
+ """Returns the content of the sidbar options for the VBar plot.
+
+ Returns:
+ pn.Card: The layout for the sidebar content area connected to the
+ VBar plot.
+ """
return pn.Card(
self.param.sorting,
self.param.sort_order,
@@ -304,6 +494,25 @@ def sidebar(self):
class IGNNPage(View):
+ """Make the iGNN page. This class creates the iGNN page.
+
+ Attributes:
+ key (str): A unique identifier for the iGNN instance.
+ title (str): The display title for the iGNN instance.
+ geomap (GeoMap): An instance of the GeoMap class, providing geographic
+ visualizations of genomic data.
+ vbar (VBar): An instance of the VBar class, providing bar plot
+ visualizations of genomic data.
+ gnnhaplotype (GNNHaplotype): An instance of the GNNHaplotype class,
+ handling GNN-based haplotype analysis.
+ sample_sets (pandas.DataFrame): A DataFrame containing information
+ about the available sample sets.
+
+ Methods:
+ __panel__() -> pn.Column: Defines the layout of the main content area.
+ sidebar() -> pn.Column: Defines the layout of the sidebar content area.
+ """
+
key = "iGNN"
title = "iGNN"
geomap = param.ClassSelector(class_=GeoMap)
@@ -317,17 +526,62 @@ def __init__(self, **params):
self.gnnhaplotype = GNNHaplotype(datastore=self.datastore)
self.sample_sets = self.datastore.sample_sets_table
- def __panel__(self):
+ def __panel__(self) -> pn.Column:
+ """Returns the main content of the page which is retrieved from the
+ `datastore.tsm.ts` attribute.
+
+ Returns:
+ pn.Column: The layout for the main content area.
+ """
+
return pn.Column(
- pn.Row(
- self.geomap,
+ pn.Accordion(
+ pn.Column(
+ self.geomap,
+ pn.pane.Markdown(
+ "**Map** - Displays the geographical locations "
+ "where samples were collected and visually "
+ "represents their group sample affiliations "
+ "through colors.",
+ sizing_mode="stretch_width",
+ ),
+ name="Geomap",
+ ),
+ pn.Column(
+ self.vbar,
+ pn.pane.Markdown(
+ "**vBar** - Lorem ipsum",
+ sizing_mode="stretch_width",
+ ),
+ name="VBar Plot",
+ ),
+ pn.Column(self.gnnhaplotype, name="GNN Haplotype Plot"),
+ active=[0, 1, 2],
),
- self.vbar,
- self.gnnhaplotype,
)
- def sidebar(self):
+ def sidebar(self) -> pn.Column:
+ """Returns the sidebar content of the page which is retrieved from the
+ `datastore.tsm.ts` attribute.
+
+ Returns:
+ pn.Column: The layout for the sidebar content area.
+ """
+
return pn.Column(
+ pn.pane.HTML(
+ "iGNN
", sizing_mode="stretch_width"
+ ),
+ pn.pane.Markdown(
+ (
+ "This section provides interactive visualizations for "
+ "**Genealogical Nearest Neighbors "
+ "(GNN)** analysis.
"
+ "Use the controls below to customize the plots and "
+ "adjust parameters."
+ ),
+ sizing_mode="stretch_width",
+ ),
self.geomap.sidebar,
self.vbar.sidebar,
self.gnnhaplotype.sidebar,
diff --git a/src/tseda/vpages/individuals.py b/src/tseda/vpages/individuals.py
index 106d9e60..ca30f328 100644
--- a/src/tseda/vpages/individuals.py
+++ b/src/tseda/vpages/individuals.py
@@ -12,29 +12,143 @@
import panel as pn
import param
-from tseda.datastore import IndividualsTable
+from tseda.datastore import IndividualsTable, SampleSetsTable
from .core import View
from .map import GeoMap
class IndividualsPage(View):
- key = "individuals"
- title = "Individuals"
+ """This class represents a view for the individuals page.
+
+ Attributes:
+ key (str): A unique identifier for this view.
+ title (str): The title displayed for this view.
+ sample_sets_table (param.ClassSelector): A reference to a
+ `SampleSetsTable` object containing information about sample sets.
+ individuals_table (param.ClassSelector): A reference to an
+ `IndividualsTable` object managing individual data and filtering
+ options.
+ geomap (param.ClassSelector): A reference to a `GeoMap` object
+ displaying
+ geographical locations and sample set affiliations (optional).
+
+ Methods:
+ __panel__(): Defines the layout of the view using Panel components.
+ sidebar(): Defines the sidebar content with descriptions and controls.
+ Contains:
+ sample_sets_accordion_toggled(event): Handles the toggling event
+ of the sample sets accordion
+ """
+
+ key = "individuals and sets"
+ title = "Individuals & sets"
+ sample_sets_table = param.ClassSelector(class_=SampleSetsTable)
+ individuals_table = param.ClassSelector(class_=IndividualsTable)
geomap = param.ClassSelector(class_=GeoMap)
- data = param.ClassSelector(class_=IndividualsTable)
def __init__(self, **params):
super().__init__(**params)
self.geomap = GeoMap(datastore=self.datastore)
- self.data = self.datastore.individuals_table
+ self.sample_sets_table = self.datastore.sample_sets_table
+ self.individuals_table = self.datastore.individuals_table
+ self.individuals_table.sample_sets_table = self.sample_sets_table
+
+ @pn.depends(
+ "individuals_table.sample_select.value",
+ "individuals_table.refresh_button.value",
+ )
+ def __panel__(self) -> pn.Column:
+ """Defines the layout of the view using Panel components. This method
+ is called dynamically when dependent parameters change.
+
+ Returns:
+ pn.Column: A Panel column containing the layout of the view.
+ """
+ sample_sets_accordion = pn.Accordion(
+ pn.Column(
+ self.sample_sets_table,
+ sizing_mode="stretch_width",
+ name="Sample Sets Table",
+ ),
+ max_width=400,
+ active=[0],
+ )
+
+ def sample_sets_accordion_toggled(event):
+ """Handles the toggling event of the sample sets accordion.
+
+ This function dynamically adjusts the maximum width of the
+ accordion based on its active state. If the accordion is closed
+ (active state is an empty list), the width is set to 180 pixels.
+ Otherwise, when the accordion is open, the width is set to 400
+ pixels.
+
+ Arguments:
+ event (param.Event): The event object triggered by the
+ accordion's toggle. NOTE: event should not be provided, but
+ Panel
+ does not recognize the function without it.
+ """
+ if sample_sets_accordion.active == []:
+ sample_sets_accordion.max_width = 180
+ else:
+ sample_sets_accordion.max_width = 400
+
+ sample_sets_accordion.param.watch(
+ sample_sets_accordion_toggled, "active"
+ )
+ return pn.Column(
+ pn.Row(
+ pn.Accordion(
+ pn.Column(
+ self.geomap,
+ pn.pane.Markdown(
+ "**Map** - Displays the geographical locations "
+ "where samples were collected and visually "
+ "represents their group sample affiliations "
+ "through colors.",
+ sizing_mode="stretch_width",
+ ),
+ min_width=400,
+ name="Geomap",
+ ),
+ active=[0],
+ ),
+ pn.Spacer(sizing_mode="stretch_width", max_width=5),
+ sample_sets_accordion,
+ ),
+ pn.Accordion(
+ pn.Column(self.individuals_table, name="Individuals Table"),
+ active=[0],
+ ),
+ )
- def __panel__(self):
- return pn.Column(self.geomap, self.data)
+ def sidebar(self) -> pn.Column:
+ """Defines the content for the sidebar of the view containing
+ descriptive text and control elements.
- def sidebar(self):
+ Returns:
+ pn.Column: A Panel column containing the sidebar content.
+ """
return pn.Column(
+ pn.pane.HTML(
+ "Individuals & sets
",
+ sizing_mode="stretch_width",
+ ),
+ pn.pane.Markdown(
+ (
+ "This section allows you to manage and explore"
+ "individual samples in your dataset "
+ "and customize Sample Sets.
"
+ "Use the controls below to customize the plots,"
+ "adjust parameters, and add new samples."
+ ),
+ sizing_mode="stretch_width",
+ ),
+ self.individuals_table.refresh_button,
self.geomap.sidebar,
- self.data.options_sidebar,
- self.data.modification_sidebar,
+ self.sample_sets_table.sidebar,
+ self.individuals_table.options_sidebar,
+ self.individuals_table.modification_sidebar,
)
diff --git a/src/tseda/vpages/map.py b/src/tseda/vpages/map.py
index c306c19d..5d857c42 100644
--- a/src/tseda/vpages/map.py
+++ b/src/tseda/vpages/map.py
@@ -1,4 +1,4 @@
-"""Module for creating a map of the world with sample locations
+"""Module for creating a map of the world with sample locations.
Generate a hvplot map of the world with sample locations based on a
GeoPandas representation of the individuals data. The map is
@@ -9,16 +9,17 @@
- Add linked brushing between the map and other panel objects /
widgets
- Fix issue where map is rendered small and repeated tiles
-
"""
import geopandas
import hvplot.pandas # noqa
+import pandas as pd
import panel as pn
import param
import xyzservices.providers as xyz
from tseda import config
+from tseda.datastore import IndividualsTable
from .core import View
@@ -34,8 +35,24 @@
class GeoMap(View):
- height = param.Integer(default=400, doc="Height of the map")
- width = param.Integer(default=1200, doc="Width of the map")
+ """Make the Geomap plot. This class creates a hvplot that displays the map
+ where the different samples were collected.
+
+ Attributes:
+ tiles_selector (pn.Selector): the selected tiles for the map
+ vizualisation.
+ tiles (str): the selected tile for the map.
+ individuals_table (IndividualsTable): An instance of the
+ IndividualsTable class, containing the information from the individuals
+ table.
+
+ Methods:
+ __panel__() -> gdf.hvplot: Returns the Geomap as an Hvplot.
+ sidebar() -> pn.Card: Defines the layout of the sidebar options for
+ the Geomap.
+ """
+
+ individuals_table = param.ClassSelector(class_=IndividualsTable)
tiles_selector = param.Selector(
default="WorldPhysical",
@@ -44,8 +61,18 @@ class GeoMap(View):
)
tiles = tiles_options[tiles_selector.default]
- @pn.depends("tiles_selector", "height", "width")
+ def __init__(self, **params):
+ super().__init__(**params)
+ self.individuals_table = self.datastore.individuals_table
+
+ @pn.depends("individuals_table.refresh_button.value")
def __panel__(self):
+ """Returns the main content for the Geomap plot which is retrieved from
+ the `datastore.tsm.ts` attribute.
+
+ Returns:
+ gdf.hvplot: the geomap plot as a Hvplot.
+ """
self.tiles = tiles_options[self.tiles_selector]
df = self.datastore.individuals_table.data.rx.value
df = df.loc[df.selected]
@@ -56,25 +83,51 @@ def __panel__(self):
)
color = color.loc[~gdf.geometry.is_empty.values]
gdf = gdf[~gdf.geometry.is_empty]
- return gdf.hvplot.points(
+
+ kw = {
+ "geo": True,
+ "tiles": self.tiles,
+ "tiles_opts": {"alpha": 0.5},
+ "responsive": True,
+ "max_height": 200,
+ "min_height": 199,
+ "xlim": (-180, 180),
+ "ylim": (-60, 70),
+ "tools": ["wheel_zoom", "box_select", "tap", "pan", "reset"],
+ }
+
+ if gdf.empty:
+ gdf = geopandas.GeoDataFrame(
+ pd.DataFrame(index=[0]),
+ geometry=geopandas.points_from_xy([0.0], [0.0]),
+ )
+ return gdf.hvplot(
+ **kw,
+ hover_cols=None,
+ size=100,
+ color=None,
+ fill_alpha=0.0,
+ line_color=None,
+ )
+ return gdf.hvplot(
+ **kw,
hover_cols=["name", "population", "sample_set_id"],
- geo=True,
- tiles=self.tiles,
- tiles_opts={"alpha": 0.5},
- max_height=self.height,
- min_height=self.height,
size=100,
color=color,
- tools=["wheel_zoom", "box_select", "tap", "pan", "reset"],
fill_alpha=0.5,
line_color="black",
- responsive=True,
)
def sidebar(self):
+ """Returns the content of the sidbar options for the Geomap plot.
+
+ Returns:
+ pn.Card: The layout for the sidebar content area connected to the
+ Geomap plot.
+ """
return pn.Card(
self.param.tiles_selector,
- collapsed=False,
+ collapsed=True,
title="Map options",
header_background=config.SIDEBAR_BACKGROUND,
active_header_background=config.SIDEBAR_BACKGROUND,
diff --git a/src/tseda/vpages/overview.py b/src/tseda/vpages/overview.py
index 577aa162..b43a3e4a 100644
--- a/src/tseda/vpages/overview.py
+++ b/src/tseda/vpages/overview.py
@@ -1,11 +1,56 @@
+"""Overview page.
+
+This file contains the class for the application's overview page. The page
+includes both the main content with the information about the data file given
+to the application as well as a sidebar with a short description of the
+application.
+"""
+
import panel as pn
from .core import View
class OverviewPage(View):
+ """Represents the overview page of the tseda application.
+
+ Attributes:
+ key (str): A unique identifier for this view within the application.
+ title (str): The title displayed on the page.
+
+ Methods:
+ __panel__() -> pn.Column: Defines the layout of the main content area.
+ sidebar() -> pn.Column: Defines the layout of the sidebar content area.
+ """
+
key = "overview"
title = "Overview"
- def __panel__(self):
+ def __panel__(self) -> pn.Column:
+ """Returns the main content of the page which is retrieved from the
+ `datastore.tsm.ts` attribute.
+
+ Returns:
+ pn.Column: The layout for the main content area.
+ """
return pn.Column(pn.pane.HTML(self.datastore.tsm.ts))
+
+ def sidebar(self) -> pn.Column:
+ """Returns the content of the sidebar.
+
+ Returns:
+ pn.Column: The layout for the sidebar.
+ """
+ return pn.Column(
+ pn.pane.HTML(
+ "Overview
",
+ sizing_mode="stretch_width",
+ ),
+ pn.pane.Markdown(
+ (
+ "Welcome to **tseda**! This is a tool that "
+ "you can use to analyze your tskit data file."
+ ),
+ sizing_mode="stretch_width",
+ ),
+ )
diff --git a/src/tseda/vpages/sample_sets.py b/src/tseda/vpages/sample_sets.py
deleted file mode 100644
index 0d16eca7..00000000
--- a/src/tseda/vpages/sample_sets.py
+++ /dev/null
@@ -1,37 +0,0 @@
-"""Sample sets editor page.
-
-Panel showing a simple sample set editor page. The page consists of
-an editable table showing the sample sets.
-
-The sample sets table allows the user to edit the name and color of
-each sample set. In addition, new sample sets can be added that allows
-the user to reassign individuals to different sample sets in the
-individuals table.
-
-TODO:
-
-- change from/to params to param.NumericTuple?
-"""
-
-import panel as pn
-import param
-
-from tseda.datastore import SampleSetsTable
-
-from .core import View
-
-
-class SampleSetsPage(View):
- key = "sample_sets"
- title = "Sample Sets"
- data = param.ClassSelector(class_=SampleSetsTable)
-
- def __init__(self, **params):
- super().__init__(**params)
- self.data = self.datastore.sample_sets_table
-
- def __panel__(self):
- return pn.Column(self.data)
-
- def sidebar(self):
- return pn.Column(self.data.sidebar)
diff --git a/src/tseda/vpages/stats.py b/src/tseda/vpages/stats.py
index 0966f8fb..f863e8b3 100644
--- a/src/tseda/vpages/stats.py
+++ b/src/tseda/vpages/stats.py
@@ -9,6 +9,8 @@
"""
import ast
+import itertools
+from typing import Union
import holoviews as hv
import pandas as pd
@@ -25,9 +27,10 @@
# TODO: make sure this is safe
-def eval_sample_sets(sample_sets):
- """Evaluate sample sets parameter."""
- return ast.literal_eval(sample_sets)
+def eval_comparisons(comparisons):
+ """Evaluate comparisons parameter."""
+ evaluated = ast.literal_eval(str(comparisons).replace(" & ", ","))
+ return [tuple(map(int, item.split(","))) for item in evaluated]
def eval_indexes(indexes):
@@ -36,10 +39,41 @@ def eval_indexes(indexes):
class OnewayStats(View):
+ """This class defines a view for one-way population genetic statistics
+ plots.
+
+ Attributes:
+ mode (param.Selector):
+ A parameter to select the calculation mode ("site" or "branch").
+ Branch mode is only available for calibrated data. (default: "site")
+ statistic (param.Selector):
+ A parameter to select the statistic to calculate
+ (e.g., "Tajimas_D", "diversity").
+ Names correspond to tskit method names. (default: "diversity")
+ window_size (param.Integer):
+ A parameter to define the size of the window for window-based
+ statistics.
+ (default: 10000, bounds=(1, None))
+ sample_select_warning (pn.pane.Alert):
+ An alert panel displayed when no sample sets are selected.
+ tooltip (pn.widgets.TooltipIcon):
+ A tooltip icon providing information about the plot.
+
+ Methods:
+ tooltip() -> pn.widgets.TooltipIcon:
+ Returns a tooltip for the plot.
+ __panel__() -> pn.Column:
+ Generates the view containing the one-way statistics plot.
+ Raises a warning if no sample sets are selected.
+ sidebar() -> pn.Card:
+ Creates the sidebar panel with controls for the plot.
+ """
+
mode = param.Selector(
- objects=["branch", "site"],
+ objects=["site"],
default="site",
- doc="Select mode for statistics.",
+ doc="""Select mode (site or branch) for statistics.
+ Branch mode is only available for calibrated data.""",
)
statistic = param.Selector(
objects=["Tajimas_D", "diversity"],
@@ -49,13 +83,21 @@ class OnewayStats(View):
window_size = param.Integer(
default=10000, bounds=(1, None), doc="Size of window"
)
- sample_sets = param.String(
- default="[0,1]",
- doc="Comma-separated list of sample sets (0-indexed) to plot.",
+ sample_select_warning = pn.pane.Alert(
+ """Select at least 1 sample set to see this plot.
+ Sample sets are selected on the Individuals page""",
+ alert_type="warning",
)
@property
def tooltip(self):
+ """Returns a TooltipIcon widget containing information about the oneway
+ statistical plot and how to edit it.
+
+ Returns:
+ pn.widgets.TooltipIcon: A TooltipIcon widget displaying
+ the information.
+ """
return pn.widgets.TooltipIcon(
value=(
"Oneway statistical plot. The colors can be modified "
@@ -63,28 +105,38 @@ def tooltip(self):
)
)
- @param.depends("mode", "statistic", "window_size", "sample_sets")
- def __panel__(self):
+ def __init__(self, **params):
+ super().__init__(**params)
+ if self.datastore.tsm.ts.time_units != "uncalibrated":
+ self.param.mode.objects = ["branch", "site"]
+
+ @param.depends("mode", "statistic", "window_size")
+ def __panel__(self) -> Union[pn.Column, pn.pane.Alert]:
+ """Returns the plot.
+
+ Returns:
+ pn.Column: The layout for the plot.
+ """
data = None
windows = make_windows(
self.window_size, self.datastore.tsm.ts.sequence_length
)
- sample_sets_list = eval_sample_sets(self.sample_sets)
- try:
- sample_sets = self.datastore.individuals_table.get_sample_sets(
- sample_sets_list
- )
- except KeyError:
- return pn.pane.Alert("Sample set error. Check sample set indexes.")
+ sample_sets_dictionary = self.datastore.individuals_table.sample_sets()
+ sample_sets_ids = list(sample_sets_dictionary.keys())
+ if len(sample_sets_ids) < 1:
+ return self.sample_select_warning
+ sample_sets_individuals = list(sample_sets_dictionary.values())
if self.statistic == "Tajimas_D":
data = self.datastore.tsm.ts.Tajimas_D(
- sample_sets, windows=windows, mode=self.mode
+ sample_sets_individuals, windows=windows, mode=self.mode
)
+ fig_text = "**Oneway Tajimas_D plot** - Lorem Ipsum"
elif self.statistic == "diversity":
data = self.datastore.tsm.ts.diversity(
- sample_sets, windows=windows, mode=self.mode
+ sample_sets_individuals, windows=windows, mode=self.mode
)
+ fig_text = "**Oneway Diversity plot** - Lorem Ipsum"
else:
raise ValueError("Invalid statistic")
@@ -92,7 +144,7 @@ def __panel__(self):
data,
columns=[
self.datastore.sample_sets_table.names[i]
- for i in sample_sets_list
+ for i in sample_sets_ids
],
)
position = hv.Dimension(
@@ -110,17 +162,24 @@ def __panel__(self):
}
kdims = [hv.Dimension("ss", label="Sample set")]
holomap = hv.HoloMap(data_dict, kdims=kdims)
- return pn.panel(
- holomap.overlay("ss").opts(legend_position="right"),
- sizing_mode="stretch_width",
+ return pn.Column(
+ pn.panel(
+ holomap.overlay("ss").opts(legend_position="right"),
+ sizing_mode="stretch_width",
+ ),
+ pn.pane.Markdown(fig_text),
)
- def sidebar(self):
+ def sidebar(self) -> pn.Card:
+ """Returns the content of the sidebar.
+
+ Returns:
+ pn.Card: The layout for the sidebar.
+ """
return pn.Card(
self.param.mode,
self.param.statistic,
self.param.window_size,
- self.param.sample_sets,
collapsed=False,
title="Oneway statistics plotting options",
header_background=config.SIDEBAR_BACKGROUND,
@@ -130,10 +189,47 @@ def sidebar(self):
class MultiwayStats(View):
+ """This class defines a view for multi-way population genetic statistics
+ plots.
+
+ Attributes:
+ mode (param.Selector):
+ A parameter to select the calculation mode ("site" or "branch").
+ Branch mode is only available for calibrated data. (default: "site")
+ statistic (param.Selector):
+ A parameter to select the statistic to calculate (e.g., "Fst",
+ "divergence").
+ Names correspond to tskit method names. (default: "Fst")
+ window_size (param.Integer):
+ A parameter to define the size of the window for window-based
+ statistics.
+ (default: 10000, bounds=(1, None))
+ comparisons (pn.widgets.MultiChoice):
+ A multi-choice widget for selecting sample set pairs to compare.
+ sample_select_warning (pn.pane.Alert):
+ An alert panel displayed when no sample sets are selected.
+ cmaps (dict):
+ A dictionary containing available Holoviews colormaps.
+ colormap (param.Selector):
+ A parameter to select the colormap for the plot.
+ (default: "glasbey_dark")
+
+ Methods:
+ set_multichoice_options():
+ Updates the options for the comparisons multi-choice widget based
+ on available sample sets.
+ __panel__() -> pn.Column:
+ Generates the view containing the multiway statistics plot.
+ Raises a warning if no sample sets are selected.
+ sidebar() -> pn.Card:
+ Creates the sidebar panel with controls for the plot.
+ """
+
mode = param.Selector(
- objects=["branch", "site"],
+ objects=["site"],
default="site",
- doc="Select mode for statistics.",
+ doc="""Select mode (site or branch) for statistics.
+ Branch mode is only available for calibrated data.""",
)
statistic = param.Selector(
objects=["Fst", "divergence"],
@@ -143,16 +239,13 @@ class MultiwayStats(View):
window_size = param.Integer(
default=10000, bounds=(1, None), doc="Size of window"
)
- sample_sets = param.String(
- default="[0,1,2]",
- doc="Comma-separated list of sample sets (0-indexed) to compare.",
+ comparisons = pn.widgets.MultiChoice(
+ name="Comparisons", description="Choose indexes to compare.", value=[]
)
- indexes = param.String(
- default="[(0,1), (0,2), (1,2)]",
- doc=(
- "Comma-separated list of tuples of sample sets "
- "(0-indexed) indexes to compare."
- ),
+ sample_select_warning = pn.pane.Alert(
+ """Select at least 2 sample sets to see this plot.
+ Sample sets are selected on the Individuals page""",
+ alert_type="warning",
)
cmaps = {
cm.name: cm
@@ -167,8 +260,20 @@ class MultiwayStats(View):
doc="Holoviews colormap for sample set pairs",
)
+ def __init__(self, **params):
+ super().__init__(**params)
+ if self.datastore.tsm.ts.time_units != "uncalibrated":
+ self.param.mode.objects = ["branch", "site"]
+
@property
def tooltip(self):
+ """Returns a TooltipIcon widget containing information about the
+ multiway statistical plot and how to edit it.
+
+ Returns:
+ pn.widgets.TooltipIcon: A TooltipIcon widget displaying
+ the information.
+ """
return pn.widgets.TooltipIcon(
value=(
"Multiway statistical plot. The colors can be modified "
@@ -176,44 +281,81 @@ def tooltip(self):
)
)
+ def set_multichoice_options(self):
+ """This method dynamically populates the `comparisons` widget with a
+ list of possible sample set pairs based on the currently selected
+ sample sets in the `individuals_table`."""
+ sample_sets = self.datastore.individuals_table.sample_sets()
+ all_comparisons = list(
+ f"{x} & {y}"
+ for x, y in itertools.combinations(
+ list(sample_sets.keys()),
+ 2,
+ )
+ )
+ self.comparisons.options = all_comparisons
+
@pn.depends(
- "mode",
- "statistic",
- "window_size",
- "sample_sets",
- "indexes",
- "colormap",
+ "mode", "statistic", "window_size", "colormap", "comparisons.value"
)
def __panel__(self):
+ """Returns the multiway plot.
+
+ Returns:
+ pn.Column: The layout for the main content area.
+ """
+ self.set_multichoice_options()
+
data = None
tsm = self.datastore.tsm
- sample_sets_list = []
windows = []
- indexes_list = []
colormap_list = []
windows = make_windows(self.window_size, tsm.ts.sequence_length)
- sample_sets_list = eval_sample_sets(self.sample_sets)
- indexes_list = eval_indexes(self.indexes)
- try:
- sample_sets = self.datastore.individuals_table.get_sample_sets(
- sample_sets_list
+ comparisons = eval_comparisons(self.comparisons.value)
+
+ selected_sample_sets = self.datastore.individuals_table.sample_sets()
+ selected_sample_sets_ids = list(selected_sample_sets.keys())
+ if len(selected_sample_sets_ids) < 2:
+ return self.sample_select_warning
+ elif self.comparisons.value == []:
+ return pn.pane.Markdown(
+ "**Select which sample sets to compare to see this plot.**"
+ )
+ all_sample_sets = self.datastore.individuals_table.sample_sets(
+ only_selected=False
+ )
+ all_sample_sets_sorted = {
+ key: all_sample_sets[key] for key in sorted(all_sample_sets)
+ }
+ sample_sets_individuals = list(all_sample_sets_sorted.values())
+ comparisons_indexes = [
+ (
+ list(all_sample_sets_sorted.keys()).index(x),
+ list(all_sample_sets_sorted.keys()).index(y),
+ )
+ for x, y in comparisons
+ if x in all_sample_sets_sorted and y in all_sample_sets_sorted
+ ]
+ if comparisons_indexes == []:
+ return pn.pane.Markdown(
+ "**Select which sample sets to compare to see this plot.**"
)
- except KeyError:
- return pn.pane.Alert("Sample set error. Check sample set indexes.")
if self.statistic == "Fst":
data = tsm.ts.Fst(
- sample_sets,
+ sample_sets_individuals,
windows=windows,
- indexes=indexes_list,
+ indexes=comparisons_indexes,
mode=self.mode,
)
+ fig_text = "**Multiway Fst plot** - Lorem Ipsum"
elif self.statistic == "divergence":
data = tsm.ts.divergence(
- sample_sets,
+ sample_sets_individuals,
windows=windows,
- indexes=indexes_list,
+ indexes=comparisons_indexes,
mode=self.mode,
)
+ fig_text = "**Multiway divergence plot** - Lorem Ipsum"
else:
raise ValueError("Invalid statistic")
sample_sets_table = self.datastore.sample_sets_table
@@ -226,7 +368,7 @@ def __panel__(self):
sample_sets_table.loc(j)["name"],
]
)
- for i, j in indexes_list
+ for i, j in comparisons_indexes
],
)
position = hv.Dimension(
@@ -245,18 +387,25 @@ def __panel__(self):
}
kdims = [hv.Dimension("sspair", label="Sample set combination")]
holomap = hv.HoloMap(data_dict, kdims=kdims)
- return pn.panel(
- holomap.overlay("sspair").opts(legend_position="right"),
- sizing_mode="stretch_width",
+ return pn.Column(
+ pn.panel(
+ holomap.overlay("sspair").opts(legend_position="right"),
+ sizing_mode="stretch_width",
+ ),
+ pn.pane.Markdown(fig_text),
)
- def sidebar(self):
+ def sidebar(self) -> pn.Card:
+ """Returns the content of the sidebar.
+
+ Returns:
+ pn.Card: The layout for the sidebar.
+ """
return pn.Card(
self.param.mode,
self.param.statistic,
self.param.window_size,
- self.param.sample_sets,
- self.param.indexes,
+ self.comparisons,
self.param.colormap,
collapsed=False,
title="Multiway statistics plotting options",
@@ -267,6 +416,28 @@ def sidebar(self):
class StatsPage(View):
+ """This class defines a view for the "Statistics" page.
+
+ Attributes:
+ key (str):
+ The unique key for the page (default: "stats").
+ title (str):
+ The title of the page (default: "Statistics").
+ oneway (param.ClassSelector):
+ A parameter to select the OnewayStats class for one-way plots.
+ multiway (param.ClassSelector):
+ A parameter to select the MultiwayStats class for multi-way plots.
+ sample_sets (SampleSetsTable): # Assuming SampleSetsTable exists elsewhere
+ The SampleSetsTable object for managing sample set information.
+
+ Methods:
+ __panel__() -> pn.Column:
+ Generates the panel for the "Statistics" page with one-way and
+ multi-way plot accordions.
+ sidebar() -> pn.Card:
+ Creates the sidebar panel for the "Statistics"
+ """
+
key = "stats"
title = "Statistics"
oneway = param.ClassSelector(class_=OnewayStats)
@@ -276,22 +447,52 @@ def __init__(self, **kwargs):
super().__init__(**kwargs)
self.oneway = OnewayStats(datastore=self.datastore)
self.multiway = MultiwayStats(datastore=self.datastore)
+ self.sample_sets = self.datastore.sample_sets_table
def __panel__(self):
+ """Returns the main content of the page.
+
+ Returns:
+ pn.Column: The layout for the main content area.
+ """
return pn.Column(
- pn.Column(
- self.oneway.tooltip,
- self.oneway,
- ),
- pn.Column(
- self.multiway.tooltip,
- self.multiway,
+ pn.Accordion(
+ pn.Column(
+ self.oneway.tooltip,
+ self.oneway,
+ name="Oneway Statistics Plot",
+ ),
+ pn.Column(
+ self.multiway.tooltip,
+ self.multiway,
+ name="Multiway Statistics Plot",
+ ),
+ active=[0, 1],
),
)
def sidebar(self):
+ """Returns the content of the sidebar.
+
+ Returns:
+ pn.Card: The layout for the sidebar.
+ """
return pn.Column(
- pn.pane.Markdown("# Statistics"),
+ pn.pane.HTML(
+ "Statistics
",
+ sizing_mode="stretch_width",
+ ),
+ pn.pane.Markdown(
+ (
+ "This section provides **population genetic "
+ "statistics** to analyze genetic variation "
+ "and divergence among sample sets.
"
+ "Use the controls below to customize the plots and "
+ "adjust parameters."
+ ),
+ sizing_mode="stretch_width",
+ ),
self.oneway.sidebar,
self.multiway.sidebar,
+ self.sample_sets.sidebar_table,
)
diff --git a/src/tseda/vpages/structure.py b/src/tseda/vpages/structure.py
index 1f55e579..4f9e4eb9 100644
--- a/src/tseda/vpages/structure.py
+++ b/src/tseda/vpages/structure.py
@@ -6,10 +6,10 @@
TODO:
- add PCA
- add parameter to subset sample sets of interest
-
"""
import itertools
+from typing import Union
import colorcet as cc
import holoviews as hv
@@ -26,7 +26,15 @@
class GNN(View):
- """Make aggregated GNN plot."""
+ """Makes the GNN plot.
+
+ Attributes:
+ warnimng_pane (pn.pane.Alert): A warning message that is activated
+ if less than two sample sets are selected.
+
+ Methods:
+ __panel__() -> Union[pn.Column, pn.pane.Alert]: Defines the GNN plot.
+ """
warning_pane = pn.pane.Alert(
"""Please select at least 2 samples to visualize this graph.
@@ -34,12 +42,20 @@ class GNN(View):
alert_type="warning",
)
- def __panel__(self):
- samples, sample_sets = self.datastore.individuals_table.sample_sets()
+ def __panel__(self) -> Union[pn.Column, pn.pane.Alert]:
+ """Returns the GNN cluster plot as a heatmap or a warning message if
+ less than 2 samples are selected.
+
+ Returns:
+ Union[pn.Column, pn.pane.Alert]: The layout for the GNN cluster
+ plot with a descriptive markdown element or a warning message.
+ """
+ sample_sets = self.datastore.individuals_table.sample_sets()
+ samples = [
+ sample for sublist in sample_sets.values() for sample in sublist
+ ]
if len(sample_sets) <= 1:
- return pn.Column(
- pn.pane.Markdown("## GNN cluster plot\n"), self.warning_pane
- )
+ return self.warning_pane
else:
sstable = self.datastore.sample_sets_table.data.rx.value
inds = self.datastore.individuals_table.data.rx.value
@@ -62,16 +78,30 @@ def __panel__(self):
mean_gnn = df.groupby("focal_population").mean()
# Z-score normalization here!
return pn.Column(
- pn.pane.Markdown("## GNN cluster plot\n"),
mean_gnn.hvplot.heatmap(
cmap=cc.bgy, height=300, responsive=True
),
+ pn.pane.Markdown(
+ "**GNN cluster plot** - This heatmap visualizes the "
+ "genealogical relationships between individuals based on "
+ "the proportions of their genealogical nearest neighbors "
+ "(GNN).",
+ sizing_mode="stretch_width",
+ ),
pn.pane.Markdown("FIXME: dendrogram and Z-score\n"),
)
class Fst(View):
- """Make Fst plot."""
+ """Makes the Fst plot.
+
+ Attributes:
+ warnimng_pane (pn.pane.Alert): A warning message that is activated
+ if less than two sample sets are selected.
+
+ Methods:
+ __panel__() -> Union[pn.Column, pn.pane.Alert]: Defines the Fst plot.
+ """
warning_pane = pn.pane.Alert(
"""Please select at least 2 samples to visualize this graph.
@@ -79,10 +109,17 @@ class Fst(View):
alert_type="warning",
)
- def __panel__(self):
- samples, sample_sets = self.datastore.individuals_table.sample_sets()
+ def __panel__(self) -> Union[pn.Column, pn.pane.Alert]:
+ """Returns the Fst plot as a heatmap or a warning message if less than
+ 2 samples are selected.
+
+ Returns:
+ Union[pn.Column, pn.pane.Alert]: The layout for the Fst
+ plot with a descriptive markdown element or a warning message.
+ """
+ sample_sets = self.datastore.individuals_table.sample_sets()
if len(sample_sets) <= 1:
- return pn.Column(pn.pane.Markdown("## Fst\n"), self.warning_pane)
+ return self.warning_pane
else:
sstable = self.datastore.sample_sets_table.data.rx.value
ts = self.datastore.tsm.ts
@@ -94,13 +131,29 @@ def __panel__(self):
np.reshape(fst, newshape=(k, k)), columns=groups, index=groups
)
return pn.Column(
- pn.pane.Markdown("## Fst\n"),
df.hvplot.heatmap(cmap=cc.bgy, height=300, responsive=True),
+ pn.pane.Markdown(
+ "**Fst Plot** - Shows the fixation index (Fst) between "
+ "different sample sets, allowing comparison of genetic "
+ "diversity across populations.",
+ sizing_mode="stretch_width",
+ ),
)
class StructurePage(View):
- """Make structure page."""
+ """Represents the structure page of the tseda application.
+
+ Attributes:
+ key (str): A unique identifier for this view within the application.
+ title (str): The title displayed on the page.
+ gnn (param.ClassSelector): The gnn plot.
+ fst (param.ClassSelector): The fst plot.
+
+ Methods:
+ __panel__() -> pn.Column: Defines the layout of the main content area.
+ sidebar() -> pn.Column: Defines the layout of the sidebar content area.
+ """
key = "structure"
title = "Structure"
@@ -111,9 +164,40 @@ def __init__(self, **params):
super().__init__(**params)
self.gnn = GNN(datastore=self.datastore)
self.fst = Fst(datastore=self.datastore)
+ self.sample_sets = self.datastore.sample_sets_table
+
+ def __panel__(self) -> pn.Column:
+ """Returns the main content of the structure page.
- def __panel__(self):
+ Returns:
+ pn.Column: The layout for the main content area.
+ """
return pn.Column(
- self.gnn,
- self.fst,
+ pn.Accordion(
+ pn.Column(self.gnn, name="GNN Cluster Plot"),
+ pn.Column(self.fst, name="Fst"),
+ active=[0, 1],
+ )
+ )
+
+ def sidebar(self) -> pn.Column:
+ """Returns the content of the sidebar.
+
+ Returns:
+ pn.Column: The layout for the sidebar.
+ """
+ return pn.Column(
+ pn.pane.HTML(
+ "Structure
",
+ sizing_mode="stretch_width",
+ ),
+ pn.pane.Markdown(
+ (
+ "This section provides an analysis of the **population "
+ "structure** based on genomic data. "
+ "You can explore two types of plots."
+ ),
+ sizing_mode="stretch_width",
+ ),
+ self.sample_sets.sidebar_table,
)
diff --git a/src/tseda/vpages/trees.py b/src/tseda/vpages/trees.py
index af5782ae..11eeeebe 100644
--- a/src/tseda/vpages/trees.py
+++ b/src/tseda/vpages/trees.py
@@ -1,15 +1,18 @@
-"""Module to plot local trees
+"""Tree page structure.
-TODO:
+This is a module to plot local trees.
+TODO:
- fix bounds of position / treeid parameters
"""
import ast
+from typing import Tuple, Union
import holoviews as hv
import panel as pn
import param
+import tskit
from tseda import config
@@ -18,12 +21,86 @@
hv.extension("bokeh")
-def eval_options(options):
- """Evaluate options parameter."""
+def eval_options(options: str) -> dict:
+ """Converts the option string to a dictionary.
+
+ Args:
+ options (str): The options inputted by the user.
+
+ Returns:
+ dict: A dictionary containing the options.
+ """
return ast.literal_eval(options)
class Tree(View):
+ """This class represents a panel component for visualizing tskit trees.
+
+ Attributes:
+ search_by (pn.widgets.ToggleGroup): Select the method for searching
+ for trees.
+ tree_index (param.Integer): Get tree by zero-based index.
+ position (param.Integer): Get tree at genome position (bp).
+ position_index_warning (pn.pane.Alert): Warning message displayed
+ when position or tree index is invalid.
+ width (param.Integer): Width of the tree plot.
+ height (param.Integer): Height of the tree plot.
+ num_trees (pn.widgets.Select): Select the number of trees to display.
+ y_axis (pn.widgets.Checkbox): Toggle to include y-axis in the plot.
+ y_ticks (pn.widgets.Checkbox): Toggle to include y-axis ticks in the
+ plot.
+ x_axis (pn.widgets.Checkbox): Toggle to include x-axis in the plot.
+ sites_mutations (pn.widgets.Checkbox): Toggle to clude sites and
+ mutations
+ in the plot.
+ pack_unselected (pn.widgets.Checkbox): Toggle to pack unselected
+ sample sets
+ in the plot.
+ options_doc (pn.widgets.TooltipIcon): Tooltip explaining advanced
+ options.
+ symbol_size (param.Number): Size of the symbols representing tree
+ nodes.
+ node_labels (param.String): Dictionary specifying custom labels for
+ tree nodes.
+ additional_options (param.String): Dictionary specifying additional
+ plot options.
+ advanced_warning (pn.pane.Alert): Warning message displayed when
+ advanced options
+ are invalid.
+ next (param.Action): Action triggered by the "Next tree" button.
+ prev (param.Action): Action triggered by the "Previous tree" button.
+ slider (pn.widgets.IntSlider): Slider for selecting chromosome
+ position.
+
+ Methods:
+ __init__(self, **params): Initializes the `Tree` class with provided
+ parameters.
+ default_css(self): Generates default CSS styles for tree nodes.
+ next_tree(self): Increments the tree index to display the next tree.
+ prev_tree(self): Decrements the tree index to display the previous
+ tree.
+ check_inputs(self): Raises a ValueError if position or tree index is
+ invalid.
+ handle_advanced(self): Processes advanced options for plotting.
+ update_slider(self): Updates the slider value based on the selected
+ position.
+ update_position(self): Updates the position based on the slider value.
+ plot_tree(self, tree, omit_sites, y_ticks, node_labels,
+ additional_options): Generates
+ the HTML plot for a single tree with specified options.
+ get_all_trees(self, trees): Constructs a panel layout displaying all
+ provided trees.
+ multiple_trees(self): Adjusts layout and options for displaying
+ multiple trees.
+ advanced_options(self): Defines the layout for the advanced options
+ in the sidebar.
+ __panel__(self): Defines the layout of the main content on the page.
+ update_sidebar(self): Created the sidebar based on the chosen search
+ method.
+ sidebar(self): Calls the update_sidebar method whenever chosen search
+ method changes.
+ """
+
search_by = pn.widgets.ToggleGroup(
name="Search By",
options=["Position", "Tree Index"],
@@ -31,26 +108,81 @@ class Tree(View):
button_type="primary",
)
- tree_index = param.Integer(default=0, doc="Get tree by zero-based index")
+ tree_index = param.Integer(
+ default=0,
+ doc="""Get tree by zero-based index. If multiple trees are
+ shown, this is the index of the first tree.""",
+ )
position = param.Integer(
- default=None, doc="Get tree at genome position (bp)"
+ default=None,
+ doc="""Get tree at genome position (bp). If multiple trees are
+ shown, this is the position of the first tree.""",
)
- warning_pane = pn.pane.Alert(
- "The input for position or tree index is out of bounds.",
+ position_index_warning = pn.pane.Alert(
+ """The input for position or tree index is
+ out of bounds for the specified number
+ of trees.""",
alert_type="warning",
visible=False,
)
width = param.Integer(default=750, doc="Width of the tree plot")
height = param.Integer(default=520, doc="Height of the tree plot")
- options = param.String(
- default="{'y_axis': 'time', 'node_labels': {}}",
+
+ num_trees = pn.widgets.Select(
+ name="Number of trees",
+ options=[1, 2, 3, 4, 5, 6],
+ value=1,
+ description="""Select the number of trees to display. The first tree
+ will represent your selected chromosome position or tree index.""",
+ )
+
+ y_axis = pn.widgets.Checkbox(name="Include y-axis", value=True)
+ y_ticks = pn.widgets.Checkbox(name="Include y-ticks", value=True)
+ x_axis = pn.widgets.Checkbox(name="Include x-axis", value=False)
+ sites_mutations = pn.widgets.Checkbox(
+ name="Include sites and mutations", value=True
+ )
+ pack_unselected = pn.widgets.Checkbox(
+ name="Pack unselected sample sets", value=False, width=197
+ )
+ options_doc = pn.widgets.TooltipIcon(
+ value=(
+ """Select various elements to include in your graph.
+ Pack unselected sample sets: Selecting this option
+ will allow large polytomies involving unselected
+ samples to be summarised as a dotted line. Selection
+ of samples and sample sets can be done on the
+ Individuals page."""
+ ),
+ )
+
+ symbol_size = param.Number(default=8, bounds=(0, None), doc="Symbol size")
+
+ node_labels = param.String(
+ default="{}",
doc=(
- "Additional options for configuring tree plot. "
- "Must be a valid dictionary string."
+ """Show custom labels for the nodes (specified by ID).
+ Any nodes not present will not have a label.
+ Examle: {1: 'label1', 2: 'label2',...}"""
),
)
+ additional_options = param.String(
+ default="{}",
+ doc=(
+ """Add more options as specified by the documentation.
+ Must be a valid dictionary.
+ Examle: {'title': 'My Tree',...}"""
+ ),
+ )
+
+ advanced_warning = pn.pane.Alert(
+ "The inputs for the advanced options are not valid.",
+ alert_type="warning",
+ visible=False,
+ )
+
next = param.Action(
lambda x: x.next_tree(), doc="Next tree", label="Next tree"
)
@@ -58,85 +190,340 @@ class Tree(View):
lambda x: x.prev_tree(), doc="Previous tree", label="Previous tree"
)
- symbol_size = param.Number(default=8, bounds=(0, None), doc="Symbol size")
+ slider = pn.widgets.IntSlider(name="Chromosome Position")
- def next_tree(self):
- self.position = None
- self.tree_index = min(
- self.datastore.tsm.ts.num_trees - 1, int(self.tree_index) + 1
- )
- # pyright: ignore[reportOperatorIssue]
-
- def prev_tree(self):
- self.position = None
- self.tree_index = max(0, int(self.tree_index) - 1)
- # pyright: ignore[reportOperatorIssue]
+ def __init__(self, **params):
+ super().__init__(**params)
+ self.slider.end = int(self.datastore.tsm.ts.sequence_length - 1)
@property
- def default_css(self):
- """Default css styles for tree nodes"""
+ def default_css(self) -> str:
+ """Default css styles for tree nodes.
+
+ Returns:
+ str: A string with the css styling.
+ """
styles = []
sample_sets = self.datastore.sample_sets_table.data.rx.value
individuals = self.datastore.individuals_table.data.rx.value
sample2ind = self.datastore.individuals_table.sample2ind
+ selected_sample_sets = self.datastore.individuals_table.sample_sets()
+ selected_samples = [
+ int(i)
+ for sublist in list(selected_sample_sets.values())
+ for i in sublist
+ ]
for n in self.datastore.individuals_table.samples():
ssid = individuals.loc[sample2ind[n]].sample_set_id
ss = sample_sets.loc[ssid]
- s = f".node.n{n} > .sym " + "{" + f"fill: {ss.color} " + "}"
+ if n in selected_samples:
+ s = (
+ f".node.n{n} > .sym "
+ + "{"
+ + f"fill: {ss.color}; stroke: black; stroke-width: 2px;"
+ + "}"
+ )
+ else:
+ s = f".node.n{n} > .sym " + "{" + f"fill: {ss.color} " + "}"
styles.append(s)
css_string = " ".join(styles)
return css_string
- @param.depends("position", "tree_index", watch=True)
+ def next_tree(self):
+ """Increments the tree index to display the next tree."""
+ self.position = None
+ self.tree_index = min(
+ self.datastore.tsm.ts.num_trees - self.num_trees.value,
+ int(self.tree_index) + 1,
+ ) # pyright: ignore[reportOperatorIssue]
+
+ def prev_tree(self):
+ """Decrements the tree index to display the previous tree."""
+ self.position = None
+ self.tree_index = max(0, int(self.tree_index) - 1) # pyright: ignore[reportOperatorIssue]
+
def check_inputs(self):
- if self.position is not None and (
- int(self.position) < 0
- or int(self.position) > self.datastore.tsm.ts.sequence_length
- ):
- self.warning_pane.visible = True
- raise ValueError
- if (
- self.tree_index is not None
- and int(self.tree_index) < 0
- or int(self.tree_index) > self.datastore.tsm.ts.num_trees
+ """Checks the inputs for position and tree index.
+
+ Raises
+ ValueError: If the position or tree index is invalid.
+ """
+ if self.position is not None:
+ if (
+ int(self.position) < 0
+ or int(self.position) >= self.datastore.tsm.ts.sequence_length
+ ):
+ raise ValueError
+ elif int(
+ self.datastore.tsm.ts.at(self.position).index
+ + self.num_trees.value
+ ) > int(self.datastore.tsm.ts.num_trees):
+ raise ValueError
+ if self.tree_index is not None and (
+ int(self.tree_index) < 0
+ or int(self.tree_index) + int(self.num_trees.value)
+ > self.datastore.tsm.ts.num_trees
):
- self.warning_pane.visible = True
raise ValueError
else:
- self.warning_pane.visible = False
+ self.position_index_warning.visible = False
- @param.depends(
- "width", "height", "position", "options", "symbol_size", "tree_index"
- )
- def __panel__(self):
- options = eval_options(self.options)
- if self.position is not None:
- tree = self.datastore.tsm.ts.at(self.position)
- self.tree_index = tree.index
+ def handle_advanced(self) -> Tuple[bool, Union[dict, None]]:
+ """Handles advanced options so that they are returned in the correct
+ format.
+
+ Returns
+ bool: Whether mutations & sites should be included in the tree.
+ Union[dict, None]: Specified the option for ticks on the y-axis.
+ """
+ if self.sites_mutations.value is True:
+ omit_sites = not self.sites_mutations.value
+ else:
+ omit_sites = True
+ if self.y_ticks.value is True:
+ y_ticks = None
else:
- tree = self.datastore.tsm.ts.at_index(self.tree_index)
+ y_ticks = {}
+ if self.node_labels == "":
+ self.node_labels = "{}"
+ if self.additional_options == "":
+ self.additional_options = "{}"
+ return omit_sites, y_ticks
+
+ @param.depends("position", watch=True)
+ def update_slider(self):
+ """Updates the slider value based on the selected position."""
+ if self.position is not None:
+ self.slider.value = self.position
+
+ @param.depends("slider.value_throttled", watch=True)
+ def update_position(self):
+ """Updates the position based on the slider value."""
+ self.position = self.slider.value
+
+ def plot_tree(
+ self,
+ tree: tskit.trees.Tree,
+ omit_sites: bool,
+ y_ticks: Union[None, dict],
+ node_labels: dict,
+ additional_options: dict,
+ ) -> Union[pn.Accordion, pn.Column]:
+ """Plots a single tree.
+
+ Arguments:
+ tree (tskit.trees.Tree): The tree to be plotted.
+ omit_sites (bool): If sites & mutaions should be included in the
+ plot.
+ y_ticks (Union[None, dict]): If y_ticks should be included in the
+ plot.
+ nodel_labels (dict): Any customised node labels.
+ additional_options (dict): Any additional plotting options.
+
+ Returns:
+ Union[pn.Accordion, pn.Column]: A panel element containing the
+ tree.
+ """
+ try:
+ plot = tree.draw_svg(
+ size=(self.width, self.height),
+ symbol_size=self.symbol_size,
+ y_axis=self.y_axis.value,
+ x_axis=self.x_axis.value,
+ omit_sites=omit_sites,
+ node_labels=node_labels,
+ y_ticks=y_ticks,
+ pack_untracked_polytomies=self.pack_unselected.value,
+ style=self.default_css,
+ **additional_options,
+ )
+ self.advanced_warning.visible = False
+ except (ValueError, SyntaxError, TypeError):
+ plot = tree.draw_svg(
+ size=(self.width, self.height),
+ y_axis=True,
+ node_labels={},
+ style=self.default_css,
+ )
+ self.advanced_warning.visible = True
pos1 = int(tree.get_interval()[0])
pos2 = int(tree.get_interval()[1]) - 1
+ if int(self.num_trees.value) > 1:
+ return pn.Accordion(
+ pn.Column(
+ pn.pane.HTML(plot),
+ name=f"Tree index {tree.index} (position {pos1} - {pos2})",
+ ),
+ active=[0],
+ )
+ else:
+ return pn.Column(
+ pn.pane.HTML(
+ f"Tree index {tree.index}"
+ f" (position {pos1} - {pos2})
",
+ sizing_mode="stretch_width",
+ ),
+ pn.pane.HTML(plot),
+ )
+
+ def get_all_trees(self, trees: list) -> Union[None, pn.Column]:
+ """Returns all trees in columns and rows.
+
+ Arguments:
+ trees: A list of all trees to be displayed.
+
+ Returns:
+ Union[None, pn.Column]: A column of rows with trees,
+ if there are any trees to display.
+ """
+ if not trees:
+ return None
+ rows = [pn.Row(*trees[i : i + 2]) for i in range(0, len(trees), 2)]
+ return pn.Column(*rows)
+
+ @param.depends("num_trees.value", watch=True)
+ def multiple_trees(self):
+ """Sets the default setting depending on if one or several trees are
+ displayed."""
+ if int(self.num_trees.value) > 1:
+ self.width = 470
+ self.height = 470
+ self.y_axis.value = False
+ self.x_axis.value = False
+ self.y_ticks.value = False
+ self.sites_mutations.value = False
+ self.pack_unselected.value = True
+ self.symbol_size = 6
+ else:
+ self.width = 750
+ self.height = 520
+ self.y_axis.value = True
+ self.x_axis.value = False
+ self.y_ticks.value = True
+ self.sites_mutations.value = True
+ self.pack_unselected.value = False
+ self.symbol_size = 8
+
+ def advanced_options(self):
+ """Defined the content of the advanced options card in the sidebar."""
+ doc_link = (
+ "https://tskit.dev/tskit/docs/"
+ "stable/python-api.html#tskit.TreeSequence.draw_svg"
+ )
+ sidebar_content = pn.Column(
+ pn.Card(
+ pn.pane.HTML(
+ f"""See the
+ tskit documentation for more information
+ about these plotting options."""
+ ),
+ self.num_trees,
+ pn.Row(pn.pane.HTML("Options", width=30), self.options_doc),
+ self.x_axis,
+ self.y_axis,
+ self.y_ticks,
+ self.sites_mutations,
+ self.pack_unselected,
+ self.param.symbol_size,
+ self.param.node_labels,
+ self.param.additional_options,
+ collapsed=True,
+ title="Advanced plotting options",
+ header_background=config.SIDEBAR_BACKGROUND,
+ active_header_background=config.SIDEBAR_BACKGROUND,
+ styles=config.VCARD_STYLE,
+ ),
+ self.advanced_warning,
+ )
+ return sidebar_content
+
+ @param.depends(
+ "width",
+ "height",
+ "position",
+ "symbol_size",
+ "tree_index",
+ "num_trees.value",
+ "y_axis.value",
+ "y_ticks.value",
+ "x_axis.value",
+ "sites_mutations.value",
+ "pack_unselected.value",
+ "node_labels",
+ "additional_options",
+ "slider.value_throttled",
+ )
+ def __panel__(self) -> pn.Column:
+ """Returns the main content of the Trees page.
+
+ Returns:
+ pn.Column: The layout for the main content area.
+
+ Raises:
+ ValueError: If inputs are not in the correct format
+ """
+ try:
+ self.check_inputs()
+ except ValueError:
+ self.position_index_warning.visible = True
+ raise ValueError("Inputs for position or tree index are not valid")
+
+ sample_sets = self.datastore.individuals_table.sample_sets()
+ selected_samples = [
+ int(i) for sublist in list(sample_sets.values()) for i in sublist
+ ]
+ if len(selected_samples) < 1:
+ self.pack_unselected.value = False
+ self.pack_unselected.disabled = True
+ else:
+ self.pack_unselected.disabled = False
+ omit_sites, y_ticks = self.handle_advanced()
+ try:
+ node_labels = eval_options(self.node_labels)
+ additional_options = eval_options(self.additional_options)
+ except (ValueError, SyntaxError, TypeError):
+ node_labels = None
+ additional_options = None
+ self.advanced_warning.visible = True
+ trees = []
+ for i in range(self.num_trees.value):
+ if self.position is not None:
+ tree = self.datastore.tsm.ts.at(self.position)
+ self.tree_index = tree.index
+ tree = self.datastore.tsm.ts.at_index(
+ (tree.index + i), tracked_samples=selected_samples
+ )
+ else:
+ tree = self.datastore.tsm.ts.at_index(
+ int(self.tree_index) + i, tracked_samples=selected_samples
+ )
+ self.slider.value = int(tree.get_interval()[0])
+ trees.append(
+ self.plot_tree(
+ tree, omit_sites, y_ticks, node_labels, additional_options
+ )
+ )
+ all_trees = self.get_all_trees(trees)
return pn.Column(
+ all_trees,
pn.pane.Markdown(
- f"## Tree index {self.tree_index} (position {pos1} - {pos2})"
- ),
- pn.pane.HTML(
- tree.draw_svg(
- size=(self.width, self.height),
- symbol_size=self.symbol_size,
- style=self.default_css,
- **options,
- ),
+ """**Tree plot** - Lorem Ipsum...
+ Selected samples are marked with a black outline."""
),
+ self.slider,
pn.Row(
self.param.prev,
self.param.next,
),
)
- def update_sidebar(self):
- """Dynamically update the sidebar based on searchBy value."""
+ def update_sidebar(self) -> pn.Column:
+ """Renders the content of the sidebar based on searchBy value.
+
+ Returns:
+ pn.Column: The sidebar content.
+ """
if self.search_by.value == "Tree Index":
self.position = None
fields = [self.param.tree_index]
@@ -149,24 +536,42 @@ def update_sidebar(self):
*fields,
self.param.width,
self.param.height,
- self.param.options,
- self.param.symbol_size,
collapsed=False,
title="Tree plotting options",
header_background=config.SIDEBAR_BACKGROUND,
active_header_background=config.SIDEBAR_BACKGROUND,
styles=config.VCARD_STYLE,
),
- self.warning_pane,
+ self.position_index_warning,
)
return sidebar_content
@param.depends("search_by.value", watch=True)
- def sidebar(self):
+ def sidebar(self) -> pn.Column:
+ """Makes sure the sidebar is updated whenever the search-by value is
+ toggled.
+
+ Returns:
+ pn.Column: The sidebar content.
+ """
return self.update_sidebar()
class TreesPage(View):
+ """Represents the trees page of the tseda application.
+
+ Attributes:
+ key (str): A unique identifier for this view within the application.
+ title (str): The title displayed on the page.
+ data (param.ClassSelector): The main content of the page.
+
+ Methods:
+ __init__(self, **params): Initializes the `TreesPage` class with
+ provided parameters.
+ __panel__() -> pn.Column: Defines the layout of the main content area.
+ sidebar() -> pn.Column: Defines the layout of the sidebar content area.
+ """
+
key = "trees"
title = "Trees"
data = param.ClassSelector(class_=Tree)
@@ -177,12 +582,36 @@ def __init__(self, **params):
self.sample_sets = self.datastore.sample_sets_table
def __panel__(self):
+ """Returns the main content of the page.
+
+ Returns:
+ pn.Column: The layout for the main content area.
+ """
return pn.Column(
self.data,
)
def sidebar(self):
+ """Returns the content of the sidebar.
+
+ Returns:
+ pn.Column: The layout for the sidebar.
+ """
return pn.Column(
+ pn.pane.HTML(
+ "Trees
",
+ sizing_mode="stretch_width",
+ ),
+ pn.pane.Markdown(
+ (
+ "This section allows you to explore local genealogical "
+ "trees.
"
+ "Use the controls below to customize the plots and adjust"
+ "parameters."
+ ),
+ sizing_mode="stretch_width",
+ ),
self.data.sidebar,
+ self.data.advanced_options,
self.sample_sets.sidebar_table,
)
diff --git a/tests/.DS_Store b/tests/.DS_Store
new file mode 100644
index 00000000..7fbe4a19
Binary files /dev/null and b/tests/.DS_Store differ
diff --git a/tests/test_datastore.py b/tests/test_datastore.py
index 4f58cb37..df43b563 100644
--- a/tests/test_datastore.py
+++ b/tests/test_datastore.py
@@ -14,7 +14,7 @@ def test_datastore_preprocess(tsm):
individuals_table, sample_sets_table = datastore.preprocess(tsm)
assert individuals_table is not None
assert sample_sets_table is not None
- samples, sample_sets = individuals_table.sample_sets()
+ sample_sets = individuals_table.sample_sets()
assert len(sample_sets) == 6
np.testing.assert_equal(sample_sets[1], np.arange(0, 12))
@@ -28,7 +28,7 @@ def test_individuals_table(individuals_table):
assert ind.name == 5
assert individuals_table.sample2ind[ind.nodes[0]] == 5
assert individuals_table.sample2ind[ind.nodes[1]] == 5
- _, ss = individuals_table.sample_sets()
+ ss = individuals_table.sample_sets()
assert len(ss) == 6
assert len(ss[0]) == 12
samples = list(individuals_table.samples())
diff --git a/tests/test_model.py b/tests/test_model.py
index 90e78ba5..9c96ff7e 100644
--- a/tests/test_model.py
+++ b/tests/test_model.py
@@ -21,12 +21,12 @@ def test_sample_set_init(ts):
for pop in ts.populations():
ss = model.SampleSet(pop.id, population=pop)
assert ss is not None
- assert ss.id == pop.id
+ assert ss.sample_set_id == pop.id
assert ss.name == json.loads(pop.metadata.decode())["population"]
assert ss.color == ss.colormap[pop.id]
ss = model.SampleSet(0, name="test")
assert ss is not None
- assert ss.id == 0
+ assert ss.sample_set_id == 0
assert ss.name == "test"
assert ss.population is None
diff --git a/tests/test_trees.py b/tests/test_trees.py
index e292193f..c691eda1 100644
--- a/tests/test_trees.py
+++ b/tests/test_trees.py
@@ -19,4 +19,7 @@ def test_treespage(treespage):
def test_tree(tree):
- assert ".node.n26 > .sym {fill: #e4ae38 }" in tree.default_css
+ assert (
+ ".node.n26 > .sym {fill: #e4ae38}" in tree.default_css
+ or ".node.n26 > .sym {fill: #e4ae38}; stroke: black; stroke-width: 2px;"
+ )
diff --git a/tests/test_ui.py b/tests/test_ui.py
index 60359d5e..a0aacc18 100644
--- a/tests/test_ui.py
+++ b/tests/test_ui.py
@@ -23,24 +23,29 @@ def test_component(page, port, ds):
page.set_viewport_size({"width": 1920, "height": 1080})
- page.get_by_role("button", name="Sample Sets").click()
- expect(page.get_by_text("New sample set name")).to_be_visible()
- expect(page.get_by_text("predefined")).to_be_visible()
-
- page.get_by_role("button", name="Individuals").click()
- expect(page.get_by_text("Data modification")).to_be_visible()
- expect(page.get_by_text("Population ID")).to_be_visible()
+ page.get_by_role("button", name="Individuals & sets").click()
+ time.sleep(10)
+ expect(page.get_by_text("Geomap").nth(0)).to_be_visible()
+ expect(page.get_by_text("Original population ID").nth(0)).to_be_visible()
+ expect(page.get_by_text("Create new sample set").nth(0)).to_be_visible()
page.get_by_role("button", name="Structure").click()
- expect(page.get_by_text("GNN cluster plot")).to_be_visible()
+ time.sleep(10)
+ expect(page.get_by_text("GNN cluster plot").nth(0)).to_be_visible()
+ expect(page.get_by_text("Structure").nth(0)).to_be_visible()
page.get_by_role("button", name="iGNN").click()
- expect(page.get_by_text("Sample sets table quick view")).to_be_visible()
+ time.sleep(10)
+ expect(
+ page.get_by_text("Sample sets table quick view").nth(0)
+ ).to_be_visible()
page.get_by_role("button", name="Statistics").click()
+ time.sleep(10)
expect(
- page.get_by_text("Oneway statistics plotting options")
+ page.get_by_text("Oneway statistics plotting options").nth(0)
).to_be_visible()
page.get_by_role("button", name="Trees").click()
- expect(page.get_by_text("Tree plotting options")).to_be_visible()
+ time.sleep(10)
+ expect(page.get_by_text("Tree plotting options").nth(0)).to_be_visible()