From 1bc4cd45591dcce92c60b190c985f6b04a3d30b0 Mon Sep 17 00:00:00 2001 From: Zaf4 Date: Thu, 5 Mar 2026 13:20:20 +0300 Subject: [PATCH] restructure docs for deployment --- docs/{_build => }/.buildinfo | 2 +- docs/.doctrees/API.doctree | Bin 0 -> 35220 bytes .../_templates/autoapi/python/module.doctree | Bin 3813 -> 3815 bytes .../_templates/autosummary/table.doctree | Bin 2963 -> 2965 bytes .../{_build => }/.doctrees/environment.pickle | Bin 68197 -> 68196 bytes .../generated/cellestial.bar.doctree | Bin 42702 -> 42704 bytes .../generated/cellestial.boxplot.doctree | Bin 93592 -> 93594 bytes .../generated/cellestial.boxplots.doctree | Bin 149755 -> 149757 bytes .../generated/cellestial.build_frame.doctree | Bin 20046 -> 20048 bytes .../cellestial.cluster_outlines.doctree | Bin 21158 -> 21160 bytes .../generated/cellestial.dimensional.doctree | Bin 122770 -> 122772 bytes .../generated/cellestial.dimensionals.doctree | Bin 182241 -> 182243 bytes .../generated/cellestial.dotplot.doctree | 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Source code for cellestial.frames.build

-from __future__ import annotations
-
-from typing import TYPE_CHECKING, Literal
-
-import pandas as pd
-import polars as pl
-from anndata import AnnData
-
-from cellestial.util.errors import KeyNotFoundError
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-
-def _anndata_variable_columns(
-    data: AnnData, column_names: list[str], keys: str | Sequence[str]
-) -> list[pl.Series]:
-    """Return a list of variable columns as Polars `Series`."""
-    columns = []
-    if isinstance(keys, str):
-        keys = [keys]
-    for key in keys:
-        if key in column_names:  # check for repeats
-            continue
-        elif key in data.var_names:
-            values = data.obs_vector(key)
-            # add the variable column to the list of columns
-            columns.append(pl.Series(key, values).cast(pl.Float32))
-            column_names.append(key)
-        else:
-            msg = f"Key `{key}` not found in data."
-            raise KeyNotFoundError(msg)
-
-    return columns
-
-
-def anndata_observations_frame(
-    data: AnnData,
-    /,
-    variable_keys: str | Sequence[str] | None = None,
-    *,
-    observations_name="barcode",
-    include_dimensions: bool | int = False,
-) -> pl.DataFrame:
-    """
-    Build an Observations DataFrame from an AnnData object.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object containing the observations.
-    variable_keys : str | Sequence[str] | None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    observations_name : str, optional
-        The name of the observations column, default is 'barcode'.
-    include_dimensions : bool | int
-        Whether to include dimensions from `obsm` in the DataFrame, default is False.
-        Providing an integer will limit the number of dimensions to given number.
-
-    Returns
-    -------
-    DataFrame
-        A DataFrame containing the observations, with optional variable keys and dimensions.
-    """
-    # Check if data is an AnnData object
-    if not isinstance(data, AnnData):
-        msg = "data must be an `AnnData` object"
-        raise TypeError(msg)
-    if not isinstance(data.obs, pd.DataFrame):  # in case of Dataset2D
-        part = data.obs.to_memory()
-    else:
-        part = data.obs
-    partm = data.obsm
-    # PART 1: INITIALIZE
-    columns = [pl.Series(observations_name, data.obs_names)]
-    # PART 2: ADD AnnData.obs
-    for key in part.columns:
-        # handle categorical integer data
-        if part.dtypes[key] == "category" and part[key].cat.categories.dtype.kind in "iuf":
-            # Check if the categories are numeric (integer 'i','u' or float 'f' kinds)
-            # Only convert if the category dtype is numeric ('i', 'u', 'f')
-            # Convert to string (str) and then back to categorical
-            columns.append(pl.Series(part[key].astype(str)).cast(pl.Categorical))
-        else:
-            columns.append(pl.Series(part[key]))
-
-    # PART 3: ADD dimensions if needed
-    if include_dimensions:
-        for X in partm:
-            total_cols = partm[X].shape[1]  # Number of dimensions (columns)
-            if isinstance(include_dimensions, int) and not isinstance(include_dimensions, bool):
-                if include_dimensions >= 0:
-                    col_count = min(include_dimensions, total_cols)
-                else:
-                    msg = "Number of dimensions cannot be a negative number."
-                    raise ValueError(msg)
-            elif isinstance(include_dimensions, bool):
-                col_count = total_cols
-            else:
-                msg = "Argument for `include_dimensions` MUST be either a `bool` or an `int` type."
-                msg += f" You provided type {type(include_dimensions)}"
-                raise TypeError(msg)
-
-            for col in range(col_count):
-                columns.append(pl.Series(f"{X.upper()}{col + 1}", partm[X][:, col]))
-
-    # PART 4: ADD keys if provided
-    if variable_keys is not None:
-        column_names = [column.name for column in columns]
-        columns.extend(
-            _anndata_variable_columns(data=data, column_names=column_names, keys=variable_keys)
-        )
-
-    return pl.DataFrame(columns)
-
-
-def anndata_variables_frame(
-    data: AnnData,
-    *,
-    variables_name: str = "variable",
-    include_dimensions: bool | int = False,
-) -> pl.DataFrame:
-    """
-    Build a Variables DataFrame from an AnnData object.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object containing the variables.
-    variables_name : str
-        Name for the variables index column, default is 'variable'
-    include_dimensions : bool | int
-        Whether to include dimensions from `varm` in the DataFrame, default is False.
-        Providing an integer will limit the number of dimensions to given number.
-
-    Returns
-    -------
-    DataFrame
-        A DataFrame containing the variables.
-    """
-    # PART 1: INITIALIZE
-    if not isinstance(data, AnnData):
-        msg = "data must be an `AnnData` object"
-        raise TypeError(msg)
-    if not isinstance(data.var, pd.DataFrame):  # in case of Dataset2D
-        part = data.var.to_memory()
-    else:
-        part = data.var
-    partm = data.varm
-    # PART1: initalize columns
-    columns = [pl.Series(variables_name, data.var_names)]
-    # PART 3: ADD AnnData.var
-    for key in part.columns:
-        # handle categorical integer data
-        if part.dtypes[key] == "category" and part[key].cat.categories.dtype.kind in "iuf":
-            # Check if the categories are numeric (integer 'i','u' or float 'f' kinds)
-            # Only convert if the category dtype is numeric ('i', 'u', 'f')
-            # Convert to string (str) and then back to categorical
-            columns.append(pl.Series(part[key].astype(str)).cast(pl.Categorical))
-        else:
-            columns.append(pl.Series(part[key]))
-
-    # PART 4: ADD dimensions if needed
-    if include_dimensions:
-        for X in partm:
-            total_cols = partm[X].shape[1]  # Number of dimensions (columns)
-            if isinstance(include_dimensions, int) and not isinstance(include_dimensions, bool):
-                if include_dimensions >= 0:
-                    col_count = min(include_dimensions, total_cols)
-                else:
-                    msg = "Number of dimensions cannot be a negative number."
-                    raise ValueError(msg)
-            elif isinstance(include_dimensions, bool):
-                col_count = total_cols
-            else:
-                msg = "Argument for `include_dimensions` MUST be either a `bool` or an `int` type."
-                msg += f" You provided type {type(include_dimensions)}"
-                raise TypeError(msg)
-
-            for col in range(col_count):
-                columns.append(pl.Series(f"{X.upper()}{col + 1}", partm[X][:, col]))
-
-    return pl.DataFrame(columns)
-
-
-

-[docs]
-def build_frame(
-    data: AnnData,
-    *,
-    variable_keys: str | Sequence[str] | None = None,
-    axis: Literal[0, 1] | None = None,
-    observations_name: str = "barcode",
-    variables_name: str = "variable",
-    include_dimensions: bool | int = False,
-) -> pl.DataFrame:
-    """
-    Build a `polars.DataFrame` from an AnnData object.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object containing the variables.
-    variable_keys : str | Sequence[str] | None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    axis : Literal[0,1] | None
-        The axis to build the frame for. 0 for observations, 1 for variables.
-    observations_name : str
-        The name of the observations column, default is 'barcode'.
-    variables_name : str
-        Name for the variables index column, default is 'variable'
-    include_dimensions : bool | int
-        Whether to include dimensions in the DataFrame, default is False.
-        Providing an integer will limit the number of dimensions to given number.
-
-
-    Returns
-    -------
-    DataFrame
-        A polars DataFrame containing the variables.
-    """
-    if isinstance(data, AnnData):
-        # infer the axis if not provided
-        if axis is None and variable_keys is not None:
-            axis = 0
-
-        if axis == 0:
-            frame = anndata_observations_frame(
-                data,
-                variable_keys=variable_keys,
-                observations_name=observations_name,
-                include_dimensions=include_dimensions,
-            )
-        elif axis == 1:
-            frame = anndata_variables_frame(
-                data,
-                variables_name=variables_name,
-                include_dimensions=include_dimensions,
-            )
-        elif axis is None:
-            msg = "`axis` parameter must be specified, 0 for observations, 1 for variables."
-            raise ValueError(msg)
-    else:
-        msg = f"Unsupported data type: `{type(data)}`"
-        raise TypeError(msg)
-
-    return frame

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- - - - - -
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- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/layers/outline.html b/docs/_build/_modules/cellestial/layers/outline.html deleted file mode 100644 index 6a93e94..0000000 --- a/docs/_build/_modules/cellestial/layers/outline.html +++ /dev/null @@ -1,633 +0,0 @@ - - - - - - - - - - cellestial.layers.outline - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for cellestial.layers.outline

-from collections.abc import Sequence
-from typing import Literal
-
-import numpy as np
-import polars as pl
-from lets_plot import aes, geom_path
-from lets_plot.plot.core import FeatureSpec, LayerSpec, PlotSpec
-from polars import DataFrame
-
-from cellestial.util import get_mapping
-
-
-def _get_density_boundaries(
-    frame: DataFrame,
-    x: str,
-    y: str,
-    group_by: str,
-    groups: str | Sequence[str | Sequence[str]],
-    padding: float = 1,
-    level: float = 0.1,
-    grid_size: int = 200,
-) -> pl.DataFrame:
-    """Creates and Returns a DataFrame to encircle the cluster via `geom_path`."""
-    from scipy.stats import gaussian_kde
-    from skimage import measure
-
-    # 1. Normalize input to a Sequence of Sequences: List[List[str]]
-    if isinstance(groups, str):
-        groups = [[groups]]
-    else:
-        groups = [
-            [g] if isinstance(g, str) else list(g)
-            for g in groups
-        ]
-
-    boundaries = []
-    for group in groups:
-        group_label = "+".join(group) if len(group) > 1 else group[0]
-        points = frame.filter(pl.col(group_by).is_in(group)).select([x, y]).to_numpy()
-        if len(points) < 5:
-            continue
-
-        # 2. KDE Calculation
-        kde = gaussian_kde(points.T)
-
-        # 3. Create Grid
-        x_min, y_min = points.min(axis=0) - padding
-        x_max, y_max = points.max(axis=0) + padding
-
-        x_range = np.linspace(x_min, x_max, grid_size)
-        y_range = np.linspace(y_min, y_max, grid_size)
-        xi, yi = np.meshgrid(x_range, y_range)
-
-        # 4. Evaluate Density
-        zi = kde(np.vstack([xi.flatten(), yi.flatten()])).reshape(xi.shape)
-
-        # 5. Extract Contours (The skimage magic)
-        threshold = zi.max() * level
-        # find_contours returns a list of [row, col] arrays
-        contours = measure.find_contours(zi, threshold)
-
-        for i, contour in enumerate(contours):
-            # Map grid indices back to DIM coordinates
-            # Note: skimage returns (row, col) which maps to (y_index, x_index)
-            actual_x = np.interp(contour[:, 1], np.arange(grid_size), x_range)
-            actual_y = np.interp(contour[:, 0], np.arange(grid_size), y_range)
-
-            boundaries.append(
-                pl.DataFrame(
-                    {
-                        x: actual_x,
-                        y: actual_y,
-                        group_by: [group_label] * len(actual_x),
-                        "path": [f"{group_label}_{i}"] * len(actual_x),
-                    }
-                )
-            )
-
-    return pl.concat(boundaries)
-
-
-

-[docs]
-def cluster_outlines(
-    plot: PlotSpec,
-    groups: str | Sequence[str | Sequence[str]],
-    *,
-    padding: float = 1.5,
-    level: float = 0.04,
-    grid_size: int = 200,
-    color: str = "#1f1f1f",
-    linetype: Literal[
-        "blank", "solid", "dashed", "dotted", "dotdash", "longdash", "twodash"
-    ] = "dashed",
-    mapping: FeatureSpec | None = None,
-    size: float = 1,
-    group_by: str | None = None,
-    x: str | None = None,
-    y: str | None = None,
-    **geom_kwargs,
-) -> LayerSpec:
-    """
-    Returns a Layer of `geom_path` that outlines the given clusters.
-
-    Parameters
-    ----------
-    plot : PlotSpec
-        The plot to which the layer will be added. Used to extract data and aesthetics.
-    groups : str | Sequence[str | Sequence[str]]
-        The group(s) to outline. Can be a single group name or a list of group
-        Providing string(s) will outline clusters with those group names.
-        Providing nested sequences of strings combines each sequence into a their own group.
-        E.g `groups=[['A', 'B']]` will outline groups A and B as if they were one cluster.
-    padding : float, default=1.5
-        The spatial buffer added to the cluster's bounding box before calculating density.
-        Increasing this value allows the density 'cloud' to expand further from the outermost
-        points, ensuring the resulting curve is smooth and not truncated at the data edges.
-    level : float, default=0.04
-        The density threshold for the outline, expressed as a fraction of the peak density
-        (0.0 to 1.0). A lower value creates a larger, more inclusive 'bubble' that captures
-        outliers, while a higher value creates a tighter boundary around the cluster's core.
-    grid_size : int, default=200
-        The resolution of the internal sampling grid used for the Marching Squares algorithm.
-        A higher value produces a smoother, more 'curvy' path by increasing the number of
-        interpolation points, while a lower value improves calculation speed but may
-        result in a more jagged or 'pixelated' appearance.
-    color : str, default='#1f1f1f'
-        The color of the outline.
-    linetype : str, default='dashed'
-        The linetype of the outline. E.g 'dashed', 'dotted',
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    size : float, default=1
-        The size of the outline.
-    group_by : str | None, default=None
-        The column name in the data used to group clusters by. e.g 'cell_type'.
-        If None, it will be inferred from the plot aesthetics.
-    x : str | None, default=None
-        The column name in the data used for x-axis coordinates. e.g 'X_UMAP1'.
-        If None, it will be inferred from the plot aesthetics.
-    y : str | None, default=None
-        The column name in the data used for y-axis coordinates. e.g 'X_UMAP2'.
-        If None, it will be inferred from the plot aesthetics.
-    **geom_kwargs
-        Additional parameters for the `geom_path` layer.
-        For more information on geom_path parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_path.html
-
-    """
-    # get mapping
-    _mapping = get_mapping(plot, index=0)
-    x = _mapping.get("x") if x is None else x
-    y = _mapping.get("y") if y is None else y
-    group_by = _mapping.get("color") if group_by is None else group_by
-    if x is None:
-        msg = "`x` is present neither as argument nor in the plot aesthetics."
-        raise ValueError(msg)
-    if y is None:
-        msg = "`y` is present neither as argument nor in the plot aesthetics."
-        raise ValueError(msg)
-    if group_by is None:
-        msg = "`group_by` is present neither as argument nor in the plot aesthetics."
-        raise ValueError(msg)
-    # get data
-    frame = plot.get_plot_shared_data()
-    # get boundaries
-    frame = _get_density_boundaries(
-        frame,
-        x=x,
-        y=y,
-        group_by=group_by,
-        groups=groups,
-        padding=padding,
-        level=level,
-        grid_size=grid_size,
-    )
-    # create and return the plot
-    if mapping is None:
-        mapping = aes()
-    return geom_path(
-        data=frame,
-        mapping=aes(x=x, y=y, group="path", **mapping.as_dict()),
-        color=color,
-        linetype=linetype,
-        size=size,
-        **geom_kwargs,
-    )

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- - - - - -
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- -
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- - - - - -
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- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/single/base/base.html b/docs/_build/_modules/cellestial/single/base/base.html deleted file mode 100644 index 896074a..0000000 --- a/docs/_build/_modules/cellestial/single/base/base.html +++ /dev/null @@ -1,546 +0,0 @@ - - - - - - - - - - cellestial.single.base.base - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for cellestial.single.base.base

-from __future__ import annotations
-
-from typing import TYPE_CHECKING, Literal
-
-from anndata import AnnData
-from lets_plot import ggplot
-
-from cellestial.frames import build_frame
-from cellestial.util import _determine_axis
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-    from lets_plot.plot.core import FeatureSpec, PlotSpec
-
-
-

-[docs]
-def plot(
-    data: AnnData,
-    mapping: FeatureSpec | None = None,
-    *,
-    axis: Literal[0, 1] | None = None,
-    variable_keys: Sequence[str] | None = None,
-    observations_name: str = "Barcode",
-    variables_name: str = "Variable",
-    include_dimensions: bool | int = False,
-) -> PlotSpec:
-    """
-    Base plot (for plots without data wrangling).
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    mapping : FeatureSpec | None, default=None
-        Aesthetic mappings for the plot, the result of `aes()`.
-    axis : Literal[0,1] | None, default=None
-        axis of the data, 0 for observations and 1 for variables.
-    variable_keys : str | Sequence[str] | None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    observations_name : str
-        The name of the observations column, default is 'barcode'.
-    variables_name : str
-        Name for the variables index column, default is 'variable'
-    include_dimensions : bool | int, default=False
-        Whether to include dimensions in the DataFrame.
-        Providing an integer will limit the number of dimensions to given number.
-
-    Returns
-    -------
-    PlotSpec
-        Base ggplot object.
-
-    Examples
-    --------
-    .. jupyter-execute::
-        :linenos:
-        :emphasize-lines: 10
-
-        from lets_plot import *
-        LetsPlot.setup_html()
-
-        import cellestial as cl
-        import scanpy as sc
-
-        data = sc.read_h5ad('data/pbmc3k_pped.h5ad')
-
-        p1 = (
-            cl.plot(data, aes(x='cell_type_lvl1', y='n_genes'))
-        )
-        p1 # plot object without layers
-
-
-    .. jupyter-execute::
-        :linenos:
-        :emphasize-lines: 10-13
-
-        from lets_plot import *
-        LetsPlot.setup_html()
-
-        import cellestial as cl
-        import scanpy as sc
-
-        data = sc.read_h5ad('data/pbmc3k_pped.h5ad')
-
-        p2 = (
-            cl.plot(data, aes(x='cell_type_lvl1', y='n_genes'))
-            + geom_violin(aes(fill='cell_type_lvl1'), scale='width')
-            + geom_boxplot(width=0.2,outlier_size=0)
-            + scale_fill_viridis()
-        )
-        p2
-
-    """
-    # Handling Data types
-    if not isinstance(data, AnnData):
-        msg = "data must be an `AnnData` object"
-        raise TypeError(msg)
-
-    # BUILD: the dataframe
-    if mapping is not None:
-        keys = [v for v in mapping.as_dict().values() if v is not None]
-        axis = _determine_axis(data=data, keys=keys) if axis is None else axis
-    frame = build_frame(
-        data=data,
-        variable_keys=variable_keys,
-        axis=axis,
-        observations_name=observations_name,
-        variables_name=variables_name,
-        include_dimensions=include_dimensions,
-    )
-
-    return ggplot(data=frame, mapping=mapping)

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- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/single/basic/bar.html b/docs/_build/_modules/cellestial/single/basic/bar.html deleted file mode 100644 index ef37ee6..0000000 --- a/docs/_build/_modules/cellestial/single/basic/bar.html +++ /dev/null @@ -1,554 +0,0 @@ - - - - - - - - - - cellestial.single.basic.bar - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
- - - - - - -
- - - Ctrl+K -
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Source code for cellestial.single.basic.bar

-from __future__ import annotations
-
-from typing import TYPE_CHECKING, Literal
-
-from lets_plot import geom_bar, ggtb
-
-from cellestial.single.base import plot as baseplot
-from cellestial.util import _determine_axis
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-    from anndata import AnnData
-    from lets_plot.plot.core import FeatureSpec, PlotSpec
-
-
-

-[docs]
-def bar(
-    data: AnnData,
-    mapping: FeatureSpec | None = None,
-    *,
-    axis: Literal[0, 1] | None = None,
-    variable_keys: Sequence[str] | None = None,
-    observations_name: str = "Barcode",
-    variables_name: str = "Variable",
-    include_dimensions: bool | int = False,
-    interactive: bool = False,
-    **geom_kwargs,
-) -> PlotSpec:
-    """
-    Bar Plot.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    mapping : FeatureSpec | None, default=None
-        Aesthetic mappings for the plot, the result of `aes()`.
-    axis : Literal[0,1] | None, default=None
-        axis of the data, 0 for observations and 1 for variables.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    axis : Literal[0,1] | None, default=None
-        The axis to build the frame for. 0 for observations, 1 for variables.
-    observations_name : str, default='Barcode'
-        The name of the observations column.
-    variables_name : str, default='Variable'
-        Name for the variables index column.
-    include_dimensions : bool | int, default=False
-        Whether to include dimensions in the DataFrame.
-        Providing an integer will limit the number of dimensions to given number.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    **geom_kwargs
-        Additional parameters for the `geom_bar` layer.
-        For more information on geom_bar parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_bar.html
-
-    Returns
-    -------
-    PlotSpec
-        Bar plot.
-
-    Examples
-    --------
-    .. jupyter-execute::
-        :linenos:
-        :emphasize-lines: 10-11
-
-        from lets_plot import *
-        LetsPlot.setup_html()
-
-        import cellestial as cl
-        import scanpy as sc
-
-        data = sc.read_h5ad('data/pbmc3k_pped.h5ad')
-
-        p1 = (
-            cl.bar(data, mapping=aes('leiden', fill='predicted_doublet'))
-            + scale_fill_brewer(palette='Set2', direction=-1)
-        )
-        p1
-
-    Example 2
-
-    .. jupyter-execute::
-        :linenos:
-        :emphasize-lines: 10-11
-
-        from lets_plot import *
-        LetsPlot.setup_html()
-
-        import cellestial as cl
-        import scanpy as sc
-
-        data = sc.read_h5ad('data/pbmc3k_pped.h5ad')
-
-        p2 = (
-            cl.bar(data, mapping=aes('cell_type_lvl1', fill='leiden'))
-            + scale_fill_brewer(palette='Set2')
-        )
-        p2
-
-    """
-    if mapping is not None:
-        keys = [v for v in mapping.as_dict().values() if v is not None]
-        axis = _determine_axis(data=data, keys=keys) if axis is None else axis
-    br = baseplot(
-        data=data,
-        mapping=None,
-        axis=axis,
-        variable_keys=variable_keys,
-        observations_name=observations_name,
-        variables_name=variables_name,
-        include_dimensions=include_dimensions,
-    ) + geom_bar(mapping=mapping, **geom_kwargs)
-
-    if interactive:
-        br += ggtb(size_zoomin=-1)
-
-    return br

-
-
- -
- - - - - -
- - - - -
-
- -
- -
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- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/single/basic/heatmap.html b/docs/_build/_modules/cellestial/single/basic/heatmap.html deleted file mode 100644 index 6115ae3..0000000 --- a/docs/_build/_modules/cellestial/single/basic/heatmap.html +++ /dev/null @@ -1,516 +0,0 @@ - - - - - - - - - - cellestial.single.basic.heatmap - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for cellestial.single.basic.heatmap

-from __future__ import annotations
-
-from typing import TYPE_CHECKING, Literal
-
-from lets_plot import geom_tile, ggtb
-
-from cellestial.single.base import plot as baseplot
-from cellestial.themes import _THEME_HEATMAP
-from cellestial.util import _determine_axis
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-    from anndata import AnnData
-    from lets_plot.plot.core import FeatureSpec, PlotSpec
-
-
-

-[docs]
-def heatmap(
-    data: AnnData,
-    mapping: FeatureSpec | None = None,
-    *,
-    axis: Literal[0, 1] | None = None,
-    variable_keys: Sequence[str] | None = None,
-    observations_name: str = "Barcode",
-    variables_name: str = "Variable",
-    include_dimensions: bool | int = False,
-    interactive: bool = False,
-    **geom_kwargs,
-) -> PlotSpec:
-    """
-    Heatmap.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    mapping : FeatureSpec | None, default=None
-        Aesthetic mappings for the plot, the result of `aes()`.
-    axis : Literal[0,1] | None, default=None
-        axis of the data, 0 for observations and 1 for variables.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    observations_name : str, default='Barcode'
-        The name of the observations column.
-    variables_name : str, default='Variable'
-        Name for the variables index column.
-    include_dimensions : bool | int, default=False
-        Whether to include dimensions in the DataFrame.
-        Providing an integer will limit the number of dimensions to given number.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    **geom_kwargs
-        Additional parameters for the `geom_bar` layer.
-        For more information on geom_bar parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_bar.html
-
-    Returns
-    -------
-    PlotSpec
-        Heatmap.
-    """
-    if mapping is not None:
-        keys = [v for v in mapping.as_dict().values() if v is not None]
-        axis = _determine_axis(data=data, keys=keys) if axis is None else axis
-    htmp = (
-        baseplot(
-            data=data,
-            mapping=None,
-            axis=axis,
-            variable_keys=variable_keys,
-            observations_name=observations_name,
-            variables_name=variables_name,
-            include_dimensions=include_dimensions,
-        )
-        + geom_tile(mapping=mapping, **geom_kwargs)
-        + _THEME_HEATMAP
-    )
-
-    if interactive:
-        htmp += ggtb(size_zoomin=-1)
-
-    return htmp

-
-
- -
- - - - - -
- - - - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/single/basic/scatter.html b/docs/_build/_modules/cellestial/single/basic/scatter.html deleted file mode 100644 index 37812b8..0000000 --- a/docs/_build/_modules/cellestial/single/basic/scatter.html +++ /dev/null @@ -1,519 +0,0 @@ - - - - - - - - - - cellestial.single.basic.scatter - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for cellestial.single.basic.scatter

-from __future__ import annotations
-
-from typing import TYPE_CHECKING, Literal
-
-# Data retrieval
-from lets_plot import (
-    geom_point,
-    ggtb,
-)
-
-from cellestial.single.base import plot as baseplot
-from cellestial.util import _determine_axis
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-    from anndata import AnnData
-    from lets_plot.plot.core import FeatureSpec, PlotSpec
-
-
-

-[docs]
-def scatter(
-    data: AnnData,
-    mapping: FeatureSpec | None = None,
-    *,
-    axis: Literal[0, 1] | None = None,
-    variable_keys: Sequence[str] | None = None,
-    observations_name: str = "Barcode",
-    variables_name: str = "Variable",
-    include_dimensions: bool | int = False,
-    interactive: bool = False,
-    **geom_kwargs,
-) -> PlotSpec:
-    """
-    Scatter Plot.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    mapping : FeatureSpec | None, default=None
-        Aesthetic mappings for the plot, the result of `aes()`.
-    axis : Literal[0,1] | None, default=None
-        axis of the data, 0 for observations and 1 for variables.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    axis : Literal[0,1] | None, default=None
-        The axis to build the frame for. 0 for observations, 1 for variables.
-    observations_name : str, default='Barcode'
-        The name of the observations column.
-    variables_name : str, default='Variable'
-        Name for the variables index column.
-    include_dimensions : bool | int, default=False
-        Whether to include dimensions in the DataFrame.
-        Providing an integer will limit the number of dimensions to given number.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    **geom_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    PlotSpec
-        Scatter plot.
-
-    """
-    if mapping is not None:
-        keys = [v for v in mapping.as_dict().values() if v is not None]
-        axis = _determine_axis(data=data, keys=keys) if axis is None else axis
-    # BUILD: the scatter plot
-    scttr = baseplot(
-        data=data,
-        mapping=None,
-        axis=axis,
-        variable_keys=variable_keys,
-        observations_name=observations_name,
-        variables_name=variables_name,
-        include_dimensions=include_dimensions,
-    ) + geom_point(mapping=mapping, **geom_kwargs)
-
-    if interactive:
-        scttr += ggtb(size_zoomin=-1)
-
-    return scttr

-
-
- -
- - - - - -
- - - - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/single/common/xyplot.html b/docs/_build/_modules/cellestial/single/common/xyplot.html deleted file mode 100644 index 0917399..0000000 --- a/docs/_build/_modules/cellestial/single/common/xyplot.html +++ /dev/null @@ -1,579 +0,0 @@ - - - - - - - - - - cellestial.single.common.xyplot - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
- - - - - - -
- - - Ctrl+K -
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- - - -
- - -
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    -
  • - - - - - - - - - - GitHub -
    • -
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    • -
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Source code for cellestial.single.common.xyplot

-from __future__ import annotations
-
-from collections.abc import Sequence
-from typing import TYPE_CHECKING, Literal
-
-from anndata import AnnData
-from lets_plot import (
-    aes,
-    geom_point,
-    ggplot,
-    ggtb,
-    labs,
-    layer_tooltips,
-)
-from lets_plot.plot.core import FeatureSpec
-
-from cellestial.frames import build_frame
-from cellestial.themes import _THEME_SCATTER
-from cellestial.util import (
-    _determine_axis,
-    _select_variable_keys,
-)
-
-if TYPE_CHECKING:
-    from lets_plot.plot.core import PlotSpec
-
-
-

-[docs]
-def xyplot(
-    data: AnnData,
-    x: str,
-    y: str,
-    *,
-    mapping: FeatureSpec | None = None,
-    axis: Literal[0, 1] | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    observations_name: str = "Barcode",
-    variables_name: str = "Variable",
-    include_dimensions: bool | int = False,
-    **point_kwargs,
-) -> PlotSpec:
-    """
-    Scatter Plot.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    x : str
-        The key for the x-axis.
-    y : str
-        The key for the y-axis.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    axis : Literal[0,1] | None, default=None
-        axis of the data, 0 for observations and 1 for variables.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    variables_name : str, default='Variable'
-        The name to give to variable index column in the dataframe.
-    include_dimensions : bool | int, default=False
-        Whether to include dimensions in the DataFrame.
-        Providing an integer will limit the number of dimensions to given number.
-    **point_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    PlotSpec
-        Scatter plot.
-
-    """
-    # Handling Data types
-    if not isinstance(data, AnnData):
-        msg = "data must be an `AnnData` object"
-        raise TypeError(msg)
-
-    # HANDLE: mapping
-    _mapping = aes(x=x, y=y)
-    if mapping is None:
-        mapping = _mapping
-    elif isinstance(mapping, FeatureSpec):
-        merged = _mapping.as_dict() | mapping.as_dict()
-        mapping = aes(**merged)
-
-    # Determine variable keys
-    keys = [key for key in mapping.as_dict().values() if key is not None]
-    variable_keys = _select_variable_keys(data=data, keys=keys)
-    # include dimensions if a dimensional key provided
-    if not include_dimensions:
-        _keys = keys.copy()
-        for key in keys:
-            if key.startswith("X_"):
-                include_dimensions = True
-                _keys.remove(key)
-
-    # HANDLE: tooltips
-    if tooltips is None:
-        tooltips = keys
-        tooltips_spec = layer_tooltips(tooltips)
-    elif tooltips == "none" or isinstance(tooltips, str):
-        tooltips_spec = tooltips
-    elif isinstance(tooltips, Sequence):
-        tooltips = list(tooltips)
-        tooltips_spec = layer_tooltips(tooltips)
-        tooltips_variables = _select_variable_keys(data, tooltips)
-        if not set(tooltips_variables).issubset(variable_keys):
-            variable_keys.extend(tooltips_variables)
-    elif isinstance(tooltips, FeatureSpec):
-        tooltips_spec = tooltips
-
-    # BUILD: the dataframe
-    axis = _determine_axis(data=data, keys=_keys) if axis is None else axis
-    frame = build_frame(
-        data=data,
-        variable_keys=variable_keys,
-        axis=axis,
-        observations_name=observations_name,
-        variables_name=variables_name,
-        include_dimensions=include_dimensions,
-    )
-
-    # BUILD: the scatterplot
-    scttr = (
-        ggplot(data=frame)
-        + geom_point(
-            mapping=mapping,
-            tooltips=tooltips_spec,
-            **point_kwargs,
-        )
-        + labs(x=x, y=y)
-        + _THEME_SCATTER
-    )
-    if interactive:
-        scttr += ggtb(size_zoomin=-1)
-
-    return scttr

-
-
- -
- - - - - -
- - - - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/single/common/xyplots.html b/docs/_build/_modules/cellestial/single/common/xyplots.html deleted file mode 100644 index 2b4d0aa..0000000 --- a/docs/_build/_modules/cellestial/single/common/xyplots.html +++ /dev/null @@ -1,610 +0,0 @@ - - - - - - - - - - cellestial.single.common.xyplots - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
- - - - - - -
- - - Ctrl+K -
- - -
- -
- - -
-
- - - -
- -
- - - - - -
- -
- -
- -
- -
-
- -
- - -
- -
- - - -
- - -
- -
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    -
  • - - - - - - - - - - GitHub -
    • -
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    • -
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Source code for cellestial.single.common.xyplots

-from __future__ import annotations
-
-from typing import TYPE_CHECKING, Literal
-
-from lets_plot import gggrid
-from lets_plot.plot.core import FeatureSpec, LayerSpec
-
-from cellestial.single.common.xyplot import xyplot
-from cellestial.util.errors import ConfilictingLengthError
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-    from anndata import AnnData
-    from lets_plot.plot.subplots import SupPlotsSpec
-
-
-

-[docs]
-def xyplots(
-    data: AnnData,
-    x: str | Sequence[str],
-    y: str | Sequence[str],
-    *,
-    mapping: FeatureSpec | None = None,
-    axis: Literal[0, 1] | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    observations_name: str = "Barcode",
-    variables_name: str = "Variable",
-    include_dimensions: bool | int = False,
-    # multi plot args
-    layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None,
-    # grid args
-    ncol: int | None = None,
-    sharex: str | None = None,
-    sharey: str | None = None,
-    widths: list[float] | None = None,
-    heights: list[float] | None = None,
-    hspace: float | None = None,
-    vspace: float | None = None,
-    fit: bool | None = None,
-    align: bool | None = None,
-    guides: str = "auto",
-    **point_kwargs,
-) -> SupPlotsSpec:
-    """
-    Scatter Plots.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    x : str
-        The key(s) for the x-axis.
-    y : str
-        The key(s) for the y-axis.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    axis : Literal[0,1] | None, default=None
-        axis of the data, 0 for observations and 1 for variables.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    variables_name : str, default='Variable'
-        The name to give to variable index column in the dataframe.
-    include_dimensions : bool | int, default=False
-        Whether to include dimensions in the DataFrame.
-        Providing an integer will limit the number of dimensions to given number.
-    layers : Sequence[FeatureSpec|LayerSpec] | FeatureSpec | LayerSpec | None, default=None
-        Layers to add to all the plots in the grid.
-    ncol : int, default=None
-        Number of columns in grid. If not specified, shows plots horizontally, in one row.
-    sharex, sharey : bool, default=None
-        Controls sharing of axis limits between subplots in the grid.
-        `all`/True - share limits between all subplots.
-        `none`/False - do not share limits between subplots.
-        `row` - share limits between subplots in the same row.
-        `col` - share limits between subplots in the same column.
-    widths : list[float], default=None
-        Relative width of each column of grid, left to right.
-    heights : list[float], default=None
-        Relative height of each row of grid, top-down.
-    hspace : float | None = None
-        Cell horizontal spacing in px.
-    vspace : float | None = None
-        Cell vertical spacing in px.
-    fit : bool, default=True
-        Whether to stretch each plot to match the aspect ratio of its cell (fit=True),
-        or to preserve the original aspect ratio of plots (fit=False).
-    align : bool, default=False
-        If True, align inner areas (i.e. “geom” bounds) of plots.
-        However, cells containing other (sub)grids are not participating
-        in the plot “inner areas” layouting.
-    guides : str, default='auto'
-        Specifies how guides (legends and colorbars) should be treated in the layout.
-            - 'collect' collect guides from all subplots, removing duplicates.
-            - 'keep' keep guides in their original subplots; do not collect at this level.
-            - 'auto' allow guides to be collected if an upper-level layout uses guides='collect';
-
-        otherwise, keep them in subplots.
-        Duplicates are identified by comparing visual properties:
-        For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.).
-        For colorbars: title, domain limits, breaks, and color gradient.
-
-        For more information on gggrid parameters:
-        https://lets-plot.org/python/pages/api/lets_plot.gggrid.html
-
-    **point_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    PlotSpec
-        Scatter plot.
-    """
-    # str to list for x and y
-    if isinstance(x, str):
-        x = [x]
-    if isinstance(y, str):
-        y = [y]
-
-    # check for broadcasting
-    if len(x) != len(y):
-        if len(x) == 1:
-            x = list(x) * len(y)
-        elif len(y) == 1:
-            y = list(y) * len(x)
-        else:
-            msg = f"Length of x ({len(x)}) and y ({len(y)}) must be the same, or one of them must be of length 1."
-            raise ConfilictingLengthError(msg)
-
-    # build plots
-    plots = []
-    for xi, yi in zip(x, y, strict=True):
-        plot = xyplot(
-            data,
-            x=xi,
-            y=yi,
-            mapping=mapping,
-            axis=axis,
-            tooltips=tooltips,
-            interactive=interactive,
-            observations_name=observations_name,
-            variables_name=variables_name,
-            include_dimensions=include_dimensions,
-            **point_kwargs,
-        )
-        # handle the layers
-        if layers is not None:
-            if isinstance(layers, (FeatureSpec, LayerSpec)):
-                layers = [layers]
-            for layer in layers:
-                plot += layer
-        plots.append(plot)
-
-    scttrs = gggrid(
-        plots,
-        ncol=ncol,
-        sharex=sharex,
-        sharey=sharey,
-        widths=widths,
-        heights=heights,
-        hspace=hspace,
-        vspace=vspace,
-        fit=fit,
-        align=align,
-        guides=guides,
-    )
-
-    return scttrs

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- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/single/core/dimensional.html b/docs/_build/_modules/cellestial/single/core/dimensional.html deleted file mode 100644 index b3e57ab..0000000 --- a/docs/_build/_modules/cellestial/single/core/dimensional.html +++ /dev/null @@ -1,744 +0,0 @@ - - - - - - - - - - cellestial.single.core.dimensional - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for cellestial.single.core.dimensional

-from __future__ import annotations
-
-import warnings
-from collections.abc import Sequence
-from typing import TYPE_CHECKING, Literal
-
-# Core scverse libraries
-import polars as pl
-from anndata import AnnData
-
-# Data retrieval
-from lets_plot import (
-    aes,
-    geom_point,
-    ggplot,
-    ggtb,
-    labs,
-    layer_tooltips,
-    scale_color_brewer,
-)
-from lets_plot.plot.core import FeatureSpec, PlotSpec
-
-from cellestial.frames import build_frame
-from cellestial.themes import _THEME_DIMENSION
-from cellestial.util import (
-    _add_arrow_axis,
-    _color_gradient,
-    _is_variable_key,
-    _legend_ondata,
-    _select_variable_keys,
-)
-
-if TYPE_CHECKING:
-    from lets_plot.plot.core import PlotSpec
-
-
-

-[docs]
-def dimensional(
-    data: AnnData,
-    key: str | None = None,
-    *,
-    mapping : FeatureSpec | None = None,
-    dimensions: Literal["umap", "pca", "tsne"] = "umap",
-    use_key: str | None = None,
-    xy: tuple[int, int] | Sequence[int] = (1, 2),
-    size: float = 0.8,
-    variable_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    observations_name: str = "Barcode",
-    color_low: str = "#e6e6e6",
-    color_mid: str | None = None,
-    color_high: str = "#377eb8",
-    mid_point: Literal["mean", "median", "mid"] | float = "median",
-    axis_type: Literal["axis", "arrow"] | None = None,
-    arrow_length: float = 0.25,
-    arrow_size: float = 1,
-    arrow_color: str = "#3f3f3f",
-    arrow_angle: float = 10,
-    legend_ondata: bool = False,
-    ondata_size: float = 12,
-    ondata_color: str = "#3f3f3f",
-    ondata_fontface: str = "bold",
-    ondata_family: str = "sans",
-    ondata_alpha: float = 1,
-    ondata_weighted: bool = True,
-    **point_kwargs,
-) -> PlotSpec:
-    """
-    Dimensionality reduction plot.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    key : str, default=None
-        The key (cell feature) to color the points by.
-        e.g., 'leiden' or 'louvain' to color by clusters or gene name for expression.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    dimensions : Literal['umap', 'pca', 'tsne'], default='umap'
-        The dimensional reduction method to use.
-        e.g., 'umap' or 'pca' or 'tsne'.
-    xy : tuple[int, int] | Sequence[int], default=(1, 2)
-        The x and y axes to use for the plot.
-        e.g., (1, 2) for UMAP1 and UMAP2.
-    use_key : str, default=None
-        The specific key to use for the desired dimensions.
-        e.g., 'X_umap_2d' or 'X_pca_2d'.
-        Otherwise, the function will decide on the key based on the dimensions.
-    size : float, default=0.8
-        The size of the points.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    color_low : str, default='#e6e6e6'
-        The color to use for the low end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_mid : str, default=None
-        The color to use for the middle part of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_high : str, default='#377EB8'
-        The color to use for the high end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    mid_point : Literal['mean', 'median', 'mid'] | float, default='median'
-        The midpoint (in data value) of the color gradient.
-        Can be 'mean', 'median' and 'mid' or a number (float or int).
-        - If 'mean', the midpoint is the mean of the data.
-        - If 'median', the midpoint is the median of the data.
-        - If 'mid', the midpoint is the mean of 'min' and 'max' of the data.
-
-    axis_type : Literal['axis', 'arrow'] | None
-        Whether to use regular axis or arrows as the axis.
-    arrow_length : float, default=0.25
-        Length of the arrow head (px).
-    arrow_size : float, default=1
-        Size of the arrow.
-    arrow_color : str, default='#3f3f3f'
-        Color of the arrows.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    arrow_angle : float, default=10
-        Angle of the arrow head in degrees.
-    legend_ondata: bool, default=False
-        whether to show legend on data
-    ondata_size: float, default=12
-        size of the legend (text) on data.
-    ondata_color: str, default='#3f3f3f'
-        color of the legend (text) on data
-    ondata_fontface: str, default='bold'
-        fontface of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-face
-    ondata_family: str, default='sans'
-        family of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-family
-    ondata_alpha: float, default=1
-        alpha (transparency) of the legend on data.
-    ondata_weighted: bool, default=True
-        whether to use weighted mean for the legend on data.
-        If True, the weighted mean of the group means is used.
-        If False, the arithmetic mean of the group means is used.
-    **point_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    PlotSpec
-        Dimensional reduction plot.
-
-    """
-    # HANDLE: Data types
-    if not isinstance(data, AnnData):
-        msg = "data must be an `AnnData` object"
-        raise TypeError(msg)
-
-    # HANDLE: mapping
-    if mapping is None:
-        mapping = aes()
-
-    #  HANDLE: XY
-    if len(xy) != 2:
-        msg = f"xy MUST be of length 2, (len(xy)=={len(xy)})"
-        raise KeyError(msg)
-    if use_key is None:
-        x = f"X_{dimensions.upper()}{xy[0]}"  # e.g. X_UMAP1
-        y = f"X_{dimensions.upper()}{xy[1]}"  # e.g. X_UMAP2
-    else:
-        x = f"{use_key}{xy[0]}"  # e.g. X_UMAP1
-        y = f"{use_key}{xy[1]}"  # e.g. X_UMAP2
-
-    # HANDLE: variable_keys
-    if variable_keys is None:
-        variable_keys = []
-    elif isinstance(variable_keys, str):
-        variable_keys = [variable_keys]
-    elif isinstance(variable_keys, Sequence):
-        variable_keys = list(variable_keys)
-
-    # Append the key if it is a variable key
-    if _is_variable_key(data, key):
-        variable_keys.append(key)  # ty:ignore[invalid-argument-type]
-
-    # HANDLE: tooltips
-    if tooltips is None:
-        tooltips = [observations_name]
-        if key is not None:
-            tooltips.append(key)
-        tooltips_spec = layer_tooltips(tooltips)
-    elif tooltips == "none" or isinstance(tooltips, str):
-        tooltips_spec = tooltips
-    elif isinstance(tooltips, Sequence):
-        tooltips = list(tooltips)
-        tooltips_spec = layer_tooltips(tooltips)
-        tooltips_variables = _select_variable_keys(data, tooltips)
-        if not set(tooltips_variables).issubset(variable_keys):
-            variable_keys.extend(tooltips_variables)
-    elif isinstance(tooltips, FeatureSpec):
-        tooltips_spec = tooltips
-
-    # BUILD: dataframe
-    frame = build_frame(
-        data=data,
-        variable_keys=variable_keys,
-        axis=0,
-        observations_name=observations_name,
-        include_dimensions=max(xy),
-    )
-
-    # BUILD: scatter plot
-    scttr = (
-        ggplot(data=frame)
-        + geom_point(
-            mapping=aes(x=x, y=y, color=key,**mapping.as_dict()),
-            size=size,
-            tooltips=tooltips_spec,
-            **point_kwargs,
-        )
-        + _THEME_DIMENSION
-    )
-
-    if key is not None:
-        # CASE1 ---------------------- CATEGORICAL DATA ----------------------
-        if frame[key].dtype == pl.Categorical:
-            scttr += scale_color_brewer(palette="Set2")
-
-        # CASE2 ---------------------- CONTINUOUS DATA ----------------------
-        elif frame[key].dtype.is_numeric():
-            scttr += _color_gradient(
-                frame[key],
-                color_low=color_low,
-                color_mid=color_mid,
-                color_high=color_high,
-                mid_point=mid_point,
-            )
-        # else: let letsplot handle it
-
-    # HANDLE: tSNE label, a special case for labels
-    if dimensions == "tsne":
-        x_label = f"tSNE{xy[0]}"
-        y_label = f"tSNE{xy[1]}"
-        scttr += labs(x=x_label, y=y_label)
-    else:
-        # UMAP1 and UMAP2 rather than X_UMAP1 and X_UMAP2 etc.,
-        scttr += labs(
-            x=x.replace("X_", ""),
-            y=y.replace("X_", ""),
-        )
-
-    # HANDLE: arrow axis
-    scttr += _add_arrow_axis(
-        frame=frame,
-        x=x,
-        y=y,
-        axis_type=axis_type,
-        arrow_size=arrow_size,
-        arrow_color=arrow_color,
-        arrow_angle=arrow_angle,
-        arrow_length=arrow_length,
-    )
-    # HANDLE: interactive
-    if interactive:
-        scttr += ggtb(size_zoomin=-1)
-
-    # HANDLE: legend on data
-    if key is not None and legend_ondata:
-        if frame[key].dtype == pl.Categorical:
-            scttr += _legend_ondata(
-                frame=frame,
-                x=x,
-                y=y,
-                group_by=key,
-                size=ondata_size,
-                color=ondata_color,
-                fontface=ondata_fontface,
-                family=ondata_family,
-                alpha=ondata_alpha,
-                weighted=ondata_weighted,
-            )
-        elif frame[key].dtype != pl.Categorical:
-            msg = f"key `{key}` is not categorical, legend on data will not be added"
-            warnings.warn(msg, stacklevel=1)
-
-    return scttr

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- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/single/core/distribution.html b/docs/_build/_modules/cellestial/single/core/distribution.html deleted file mode 100644 index a4c14d1..0000000 --- a/docs/_build/_modules/cellestial/single/core/distribution.html +++ /dev/null @@ -1,882 +0,0 @@ - - - - - - - - - - cellestial.single.core.distribution - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for cellestial.single.core.distribution

-from __future__ import annotations
-
-from collections.abc import Sequence
-from typing import TYPE_CHECKING, Any, Literal
-
-from anndata import AnnData
-from lets_plot import (
-    aes,
-    geom_boxplot,
-    geom_jitter,
-    geom_point,
-    geom_sina,
-    geom_violin,
-    ggplot,
-    ggtb,
-    layer_tooltips,
-)
-from lets_plot.plot.core import FeatureSpec, PlotSpec
-
-from cellestial.frames import build_frame
-from cellestial.themes import _THEME_DIST
-from cellestial.util import (
-    _determine_axis,
-    _select_variable_keys,
-)
-
-if TYPE_CHECKING:
-    from lets_plot.plot.core import PlotSpec
-
-
-def _distribution(
-    data: AnnData,
-    key: str | Sequence[str],
-    *,
-    mapping: FeatureSpec | None = None,
-    geom: Literal["violin", "boxplot"] = "violin",
-    axis: Literal[0, 1] | None = None,
-    color: str | None = None,
-    fill: str | None = None,
-    add_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    geom_fill: str | None = "#FF00FF",
-    geom_color: str | None = "#2f2f2f",
-    point_color: str = "#1f1f1f",
-    point_alpha: float = 0.7,
-    point_size: float = 0.5,
-    point_geom: Literal["jitter", "point", "sina"] = "jitter",
-    observations_name: str = "Barcode",
-    variables_name: str = "Variable",
-    show_points: bool = True,
-    interactive: bool = False,
-    value_column: str = "value",
-    variable_column: str = "variable",
-    point_kwargs: dict[str, Any] | None = None,
-    **geom_kwargs,
-) -> PlotSpec:
-    # Handling Data types
-    if not isinstance(data, AnnData):
-        msg = "data must be an `AnnData` object"
-        raise TypeError(msg)
-
-    # HANDLE: mapping
-    if mapping is None:
-        mapping = aes()
-
-    # convert to list if single string
-    if isinstance(key, str):
-        keys = [key]
-    elif isinstance(key, Sequence):
-        keys = list(key)
-
-    # handle value_column if single key is provided
-    if len(keys) == 1:
-        value_column = keys[0]
-
-    # determine separator
-    separator = None
-    if fill is not None:
-        separator = fill
-    elif color is not None:
-        separator = color
-
-    if point_kwargs is None:
-        point_kwargs = {}
-
-    # determine index to unpivot
-    index = [x for x in [fill, color] if x is not None]
-    if add_keys is not None:
-        if isinstance(add_keys, str):
-            add_keys = [add_keys]
-        index.extend(add_keys)
-
-    # DETERMINE: axis if not provided
-    axis = _determine_axis(data=data, keys=keys) if axis is None else axis
-
-    # handle fill and color
-    geom_fill = None if fill is not None else geom_fill
-    geom_color = None if color is not None else geom_color
-
-    # BUILD: the DataFrame
-    variable_keys = _select_variable_keys(data=data, keys=keys)
-    variable_keys.extend(_select_variable_keys(data=data, keys=add_keys))
-    frame = build_frame(
-        data=data,
-        variable_keys=variable_keys,
-        axis=axis,
-        observations_name=observations_name,
-        variables_name=variables_name,
-    )
-
-    frame = frame.unpivot(
-        on=keys, index=index, value_name=value_column, variable_name=variable_column
-    )
-    if separator is None or len(keys) > 1:
-        separator = variable_column
-
-    # HANDLE: tooltips
-    if tooltips is None:
-        tooltips = [variable_column, value_column]
-        tooltips_spec = layer_tooltips(tooltips)
-    elif tooltips == "none" or isinstance(tooltips, str):
-        tooltips_spec = tooltips
-    elif isinstance(tooltips, Sequence):
-        tooltips = list(tooltips)
-        tooltips_spec = layer_tooltips(tooltips)
-    elif isinstance(tooltips, FeatureSpec):
-        tooltips_spec = tooltips
-
-    # BUILD: the plot
-    dst = ggplot(data=frame) + _THEME_DIST
-
-    # add the geom layer
-    if geom == "violin":
-        dst += geom_violin(
-            mapping=aes(
-                x=separator,
-                y=value_column,
-                color=color,
-                fill=fill,
-                **mapping.as_dict(),
-            ),
-            fill=geom_fill,
-            color=geom_color,
-            tooltips=layer_tooltips(frame.columns),
-            **geom_kwargs,
-        )
-    elif geom == "boxplot":
-        dst += geom_boxplot(
-            mapping=aes(
-                x=separator,
-                y=value_column,
-                color=color,
-                fill=fill,
-                **mapping.as_dict(),
-            ),
-            fill=geom_fill,
-            color=geom_color,
-            tooltips=layer_tooltips(frame.columns),
-            **geom_kwargs,
-        )
-
-    # handle the points (jitter,point,sina)
-    if show_points:
-        if point_geom in ["jitter", "point", "sina"]:
-            geom_functions = {
-                "jitter": geom_jitter,
-                "point": geom_point,
-                "sina": geom_sina,
-            }
-            geom_function = geom_functions.get(point_geom, geom_jitter)
-
-            dst += geom_function(
-                data=frame,
-                mapping=aes(x=separator, y=value_column),
-                color=point_color,
-                alpha=point_alpha,
-                size=point_size,
-                tooltips=tooltips_spec,
-                **point_kwargs,
-            )
-        else:
-            msg = "point_geom must be one of ['jitter','point','sina']."
-            raise KeyError(msg)
-
-    # handle interactive
-    if interactive:
-        dst += ggtb(size_zoomin=-1)
-
-    return dst
-
-
-

-[docs]
-def violin(
-    data: AnnData,
-    key: str | Sequence[str],
-    *,
-    mapping: FeatureSpec | None = None,
-    axis: Literal[0, 1] | None = None,
-    color: str | None = None,
-    fill: str | None = None,
-    add_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    geom_fill: str | None = "#FF00FF",
-    geom_color: str | None = "#2f2f2f",
-    point_color: str = "#1f1f1f",
-    point_alpha: float = 0.7,
-    point_size: float = 0.5,
-    point_geom: Literal["jitter", "point", "sina"] = "jitter",
-    observations_name: str = "Barcode",
-    variables_name: str = "Variable",
-    show_points: bool = True,
-    interactive: bool = False,
-    value_column: str = "value",
-    variable_column: str = "variable",
-    point_kwargs: dict[str, Any] | None = None,
-    **geom_kwargs,
-) -> PlotSpec:
-    """
-    Violin Plot.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    key : str | Sequence[str]
-        The key(s) to get the values (numerical).
-        e.g., 'total_counts' or a gene name.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    axis : Literal[0,1] | None, default=None
-        axis of the data, 0 for observations and 1 for variables.
-    color : str | None, default=None
-        Color aesthetic to split the violin plot (categorical).
-        e,g., 'cell_type' or 'leiden'.
-    fill : str | None, default=None
-        Fill aesthetic to split the violin plot (categorical).
-        e,g., 'cell_type' or 'leiden'.
-    add_keys : Sequence[str] | str | None, default=None
-        Additional keys to include in the dataframe.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    geom_fill : str | None, default='#FF00FF'
-        Fill color for all violins in the violin plot.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-    geom_color : str | None, default='#2f2f2f'
-        Border color for all violins in the violin plot.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-    point_color : str, default='#1f1f1f'
-        Color for the points in the violin plot.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-    point_alpha : float, default=0.7
-        Alpha (transparency) for the points in the violin plot.
-    point_size : float, default=0.5
-        Size for the points in the violin plot.
-    point_geom : Literal['jitter','point','sina'], default is 'jitter',
-        Geom type of the points, default is geom_jitter.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    variables_name : str, default='Variable'
-        The name to give to variable index column in the dataframe.
-    show_points : bool, default=True
-        Whether to show points.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    variable_column : str, default='variable'
-        The name of the variable column in the dataframe.
-    value_column : str, default='value'
-        The name of the value column in the dataframe.
-    point_kwargs : dict[str, Any] | None, default=None
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-    **geom_kwargs
-        Additional parameters for the `geom_violin` layer.
-        For more information on geom_violin parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_violin.html
-
-    Returns
-    -------
-    PlotSpec
-        Violin plot.
-    """
-    return _distribution(
-        data=data,
-        key=key,
-        mapping=mapping,
-        geom="violin",
-        axis=axis,
-        color=color,
-        fill=fill,
-        add_keys=add_keys,
-        tooltips=tooltips,
-        geom_fill=geom_fill,
-        geom_color=geom_color,
-        point_color=point_color,
-        point_alpha=point_alpha,
-        point_size=point_size,
-        point_geom=point_geom,
-        observations_name=observations_name,
-        variables_name=variables_name,
-        show_points=show_points,
-        interactive=interactive,
-        value_column=value_column,
-        variable_column=variable_column,
-        point_kwargs=point_kwargs,
-        **geom_kwargs,
-    )

-
-
-
-

-[docs]
-def boxplot(
-    data: AnnData,
-    key: str | Sequence[str],
-    *,
-    mapping: FeatureSpec | None = None,
-    axis: Literal[0, 1] | None = None,
-    color: str | None = None,
-    fill: str | None = None,
-    add_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    geom_fill: str | None = "#FF00FF",
-    geom_color: str | None = "#2f2f2f",
-    point_color: str = "#1f1f1f",
-    point_alpha: float = 0.7,
-    point_size: float = 0.5,
-    point_geom: Literal["jitter", "point", "sina"] = "jitter",
-    observations_name: str = "Barcode",
-    variables_name: str = "Variable",
-    show_points: bool = True,
-    interactive: bool = False,
-    value_column: str = "value",
-    variable_column: str = "variable",
-    point_kwargs: dict[str, Any] | None = None,
-    **geom_kwargs,
-) -> PlotSpec:
-    """
-    Boxplot.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    key : str | Sequence[str]
-        The key(s) to get the values (numerical).
-        e.g., 'total_counts' or a gene name.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    axis : Literal[0,1] | None, default=None
-        axis of the data, 0 for observations and 1 for variables.
-    color : str | None, default=None
-        Color aesthetic to split the boxplot (categorical).
-        e,g., 'cell_type' or 'leiden'.
-    fill : str | None, default=None
-        Fill aesthetic to split the boxplot (categorical).
-        e,g., 'cell_type' or 'leiden'.
-    add_keys : Sequence[str] | str | None, default=None
-        Additional keys to include in the dataframe.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    geom_fill : str | None, default='#FF00FF'
-        Fill color for all boxplots in the boxplot.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-    geom_color : str | None, default='#2f2f2f'
-        Border color for all boxplots in the boxplot.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-    point_color : str, default='#1f1f1f'
-        Color for the points in the boxplot.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-    point_alpha : float, default=0.7
-        Alpha (transparency) for the points in the boxplot.
-    point_size : float, default=0.5
-        Size for the points in the boxplot.
-    point_geom : Literal['jitter','point','sina'], default is 'jitter',
-        Geom type of the points, default is geom_jitter.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    variables_name : str, default='Variable'
-        The name to give to variable index column in the dataframe.
-    show_points : bool, default=True
-        Whether to show points.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    variable_column : str, default='variable'
-        The name of the variable column in the dataframe.
-    value_column : str, default='value'
-        The name of the value column in the dataframe.
-    point_kwargs : dict[str, Any] | None, default=None
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-    **geom_kwargs
-        Additional parameters for the `geom_boxplot` layer.
-        For more information on geom_boxplot parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_boxplot.html
-
-    Returns
-    -------
-    PlotSpec
-        Boxplot.
-    """
-    return _distribution(
-        data=data,
-        key=key,
-        mapping=mapping,
-        geom="boxplot",
-        axis=axis,
-        color=color,
-        fill=fill,
-        add_keys=add_keys,
-        tooltips=tooltips,
-        geom_fill=geom_fill,
-        geom_color=geom_color,
-        point_color=point_color,
-        point_alpha=point_alpha,
-        point_size=point_size,
-        point_geom=point_geom,
-        observations_name=observations_name,
-        variables_name=variables_name,
-        show_points=show_points,
-        interactive=interactive,
-        value_column=value_column,
-        variable_column=variable_column,
-        point_kwargs=point_kwargs,
-        **geom_kwargs,
-    )

-
-
- -
- - - - - -
- - - - -
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- -
- -
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- - - - - -
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- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/single/core/distributions.html b/docs/_build/_modules/cellestial/single/core/distributions.html deleted file mode 100644 index ea5f83f..0000000 --- a/docs/_build/_modules/cellestial/single/core/distributions.html +++ /dev/null @@ -1,885 +0,0 @@ - - - - - - - - - - cellestial.single.core.distributions - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for cellestial.single.core.distributions

-from __future__ import annotations
-
-from typing import TYPE_CHECKING, Any, Literal
-
-from lets_plot import gggrid
-from lets_plot.plot.core import FeatureSpec, LayerSpec
-
-from cellestial.single.core.distribution import boxplot, violin
-from cellestial.util import _share_axis, _share_ticks
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-    from anndata import AnnData
-    from lets_plot.plot.subplots import SupPlotsSpec
-
-
-

-[docs]
-def violins(
-    data: AnnData,
-    keys: Sequence[str],
-    *,
-    mapping: FeatureSpec | None = None,
-    axis: Literal[0, 1] | None = None,
-    color: str | None = None,
-    fill: str | None = None,
-    add_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    geom_fill: str = "#FF00FF",
-    geom_color: str = "#2f2f2f",
-    point_color: str = "#1f1f1f",
-    point_alpha: float = 0.7,
-    point_size: float = 0.5,
-    point_geom: Literal["jitter", "point", "sina"] = "jitter",
-    observations_name: str = "Barcode",
-    variables_name: str = "Variable",
-    show_points: bool = True,
-    interactive: bool = False,
-    value_column: str = "value",
-    variable_column: str = "variable",
-    # multi plot args
-    share_axis: bool = False,
-    share_ticks: bool = False,
-    layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None,
-    # grid args
-    ncol: int | None = None,
-    sharex: str | None = None,
-    sharey: str | None = None,
-    widths: list | None = None,
-    heights: list | None = None,
-    hspace: float | None = None,
-    vspace: float | None = None,
-    fit: bool | None = None,
-    align: bool | None = None,
-    guides: str = "auto",
-    # other kwargs
-    point_kwargs: dict[str, Any] | None = None,
-    **geom_kwargs,
-) -> SupPlotsSpec:
-    """
-    Violin Plots.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    keys : list[str] | tuple[str] | Sequence[str]
-        The keys to get the values (numerical).
-        e.g., ['total_counts', 'pct_counts_in_top_50_genes'] or a list of gene names.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    axis : Literal[0,1] | None, default=None
-        axis of the data, 0 for observations and 1 for variables.
-    color : str | None, default=None
-        Color aesthetic to split the violin plot (categorical).
-        e,g., 'cell_type' or 'leiden'.
-    fill : str | None, default=None
-        Fill aesthetic to split the violin plot (categorical).
-        e,g., 'cell_type' or 'leiden'.
-    add_keys : Sequence[str] | str | None, default=None
-        Additional keys to include in the dataframe.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    geom_fill : str, default='#FF00FF'
-        Fill color for all violins in the violin plot.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-    geom_color : str, default='#2f2f2f'
-        Border color for all violins in the violin plot.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-    point_color : str, default='#1f1f1f'
-        Color for the points in the violin plot.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-    point_alpha : float, default=0.7
-        Alpha (transparency) for the points in the violin plot.
-    point_size : float, default=0.5
-        Size for the points in the violin plot.
-    point_geom : Literal['jitter','point','sina'], default is 'jitter',
-        Geom type of the points, default is geom_jitter.
-    trim : bool, default=False
-        Whether to trim the violin plot.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    variables_name : str, default='Gene'
-        The name to give to variable index column in the dataframe.
-    show_points : bool, default=True
-        Whether to show points.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    share_ticks : bool, default=True
-        Whether to share the labels across all plots.
-        If True, only X tick texts on bottom row and Y tick text on left column are shown.
-    share_axis : bool, default=False
-        Whether to share the axis across all plots.
-        If True, only X axis on bottom row and Y axis on left column is shown.
-    layers : Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None, default=None
-        Additional layers to add to the plot.
-    variable_column : str, default='variable'
-        The name of the variable column in the dataframe.
-    value_column : str, default='value'
-        The name of the value column in the dataframe.
-    ncol : int, default=None
-        Number of columns in grid. If not specified, shows plots horizontally, in one row.
-    sharex, sharey : bool, default=None
-        Controls sharing of axis limits between subplots in the grid.
-        `all`/True - share limits between all subplots.
-        `none`/False - do not share limits between subplots.
-        `row` - share limits between subplots in the same row.
-        `col` - share limits between subplots in the same column.
-    widths : list[float], default=None
-        Relative width of each column of grid, left to right.
-    heights : list[float], default=None
-        Relative height of each row of grid, top-down.
-    hspace : float | None = None
-        Cell horizontal spacing in px.
-    vspace : float | None = None
-        Cell vertical spacing in px.
-    fit : bool, default=True
-        Whether to stretch each plot to match the aspect ratio of its cell (fit=True),
-        or to preserve the original aspect ratio of plots (fit=False).
-    align : bool, default=False
-        If True, align inner areas (i.e. “geom” bounds) of plots.
-        However, cells containing other (sub)grids are not participating
-        in the plot “inner areas” layouting.
-    guides : str, default='auto'
-        Specifies how guides (legends and colorbars) should be treated in the layout.
-            - 'collect' collect guides from all subplots, removing duplicates.
-            - 'keep' keep guides in their original subplots; do not collect at this level.
-            - 'auto' allow guides to be collected if an upper-level layout uses guides='collect';
-
-        otherwise, keep them in subplots.
-        Duplicates are identified by comparing visual properties:
-        For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.).
-        For colorbars: title, domain limits, breaks, and color gradient.
-
-        For more information on gggrid parameters:
-        https://lets-plot.org/python/pages/api/lets_plot.gggrid.html
-
-    point_kwargs : dict[str, Any] | None, default=None
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-    **geom_kwargs
-        Additional parameters for the `geom_violin` layer.
-        For more information on geom_violin parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_violin.html
-
-    Returns
-    -------
-    SupPlotsSpec
-        Violin Plots.
-    """
-    plots = []
-    for i,key in enumerate(keys):
-        plot = violin(
-            data=data,
-            key=key,
-            mapping=mapping,
-            axis=axis,
-            color=color,
-            fill=fill,
-            add_keys=add_keys,
-            tooltips=tooltips,
-            geom_fill=geom_fill,
-            geom_color=geom_color,
-            point_color=point_color,
-            point_alpha=point_alpha,
-            point_size=point_size,
-            point_geom=point_geom,
-            observations_name=observations_name,
-            variables_name=variables_name,
-            show_points=show_points,
-            interactive=interactive,
-            value_column=value_column,
-            variable_column=variable_column,
-            point_kwargs=point_kwargs,
-            **geom_kwargs,
-        )
-        # handle the layers
-        if layers is not None:
-            if isinstance(layers, (FeatureSpec, LayerSpec)):
-                layers = [layers]
-            for layer in layers:
-                plot += layer
-        if share_ticks:
-            plot = _share_ticks(plot, i, keys, ncol)
-        if share_axis:
-            plot = _share_axis(plot, i, keys, ncol, "axis")
-        plots.append(plot)
-
-    return gggrid(
-        plots,
-        ncol=ncol,
-        sharex=sharex,
-        sharey=sharey,
-        widths=widths,
-        heights=heights,
-        hspace=hspace,
-        vspace=vspace,
-        fit=fit,
-        align=align,
-        guides=guides,
-    )

-
-
-

-[docs]
-def boxplots(
-    data: AnnData,
-    keys: Sequence[str],
-    *,
-    mapping: FeatureSpec | None = None,
-    axis: Literal[0, 1] | None = None,
-    color: str | None = None,
-    fill: str | None = None,
-    add_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    geom_fill: str = "#FF00FF",
-    geom_color: str = "#2f2f2f",
-    point_color: str = "#1f1f1f",
-    point_alpha: float = 0.7,
-    point_size: float = 0.5,
-    point_geom: Literal["jitter", "point", "sina"] = "jitter",
-    observations_name: str = "Barcode",
-    variables_name: str = "Variable",
-    show_points: bool = True,
-    interactive: bool = False,
-    value_column: str = "value",
-    variable_column: str = "variable",
-    # multi plot args
-    share_axis: bool = False,
-    share_ticks: bool = False,
-    layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None,
-    # grid args
-    ncol: int | None = None,
-    sharex: str | None = None,
-    sharey: str | None = None,
-    widths: list | None = None,
-    heights: list | None = None,
-    hspace: float | None = None,
-    vspace: float | None = None,
-    fit: bool | None = None,
-    align: bool | None = None,
-    guides: str = "auto",
-    # other kwargs
-    point_kwargs: dict[str, Any] | None = None,
-    **geom_kwargs,
-) -> SupPlotsSpec:
-    """
-    Boxplots.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    keys : list[str] | tuple[str] | Sequence[str]
-        The keys to get the values (numerical).
-        e.g., ['total_counts', 'pct_counts_in_top_50_genes'] or a list of gene names.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    axis : Literal[0,1] | None, default=None
-        axis of the data, 0 for observations and 1 for variables.
-    color : str | None, default=None
-        Color aesthetic to split the boxplot (categorical).
-        e,g., 'cell_type' or 'leiden'.
-    fill : str | None, default=None
-        Fill aesthetic to split the boxplot (categorical).
-        e,g., 'cell_type' or 'leiden'.
-    add_keys : Sequence[str] | str | None, default=None
-        Additional keys to include in the dataframe.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    geom_fill : str, default='#FF00FF'
-        Fill color for all boxplots in the boxplot.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-    geom_color : str, default='#2f2f2f'
-        Border color for all boxplots in the boxplot.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-    point_color : str, default='#1f1f1f'
-        Color for the points in the boxplot.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-    point_alpha : float, default=0.7
-        Alpha (transparency) for the points in the boxplot.
-    point_size : float, default=0.5
-        Size for the points in the boxplot.
-    point_geom : Literal['jitter','point','sina'], default is 'jitter',
-        Geom type of the points, default is geom_jitter.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    variables_name : str, default='Gene'
-        The name to give to variable index column in the dataframe.
-    show_points : bool, default=True
-        Whether to show points.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    share_ticks : bool, default=True
-        Whether to share the labels across all plots.
-        If True, only X tick texts on bottom row and Y tick text on left column are shown.
-    share_axis : bool, default=False
-        Whether to share the axis across all plots.
-        If True, only X axis on bottom row and Y axis on left column is shown.
-    layers : Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None, default=None
-        Additional layers to add to the plot.
-    variable_column : str, default='variable'
-        The name of the variable column in the dataframe.
-    value_column : str, default='value'
-        The name of the value column in the dataframe.
-    ncol : int, default=None
-        Number of columns in grid. If not specified, shows plots horizontally, in one row.
-    sharex, sharey : bool, default=None
-        Controls sharing of axis limits between subplots in the grid.
-        `all`/True - share limits between all subplots.
-        `none`/False - do not share limits between subplots.
-        `row` - share limits between subplots in the same row.
-        `col` - share limits between subplots in the same column.
-    widths : list[float], default=None
-        Relative width of each column of grid, left to right.
-    heights : list[float], default=None
-        Relative height of each row of grid, top-down.
-    hspace : float | None = None
-        Cell horizontal spacing in px.
-    vspace : float | None = None
-        Cell vertical spacing in px.
-    fit : bool, default=True
-        Whether to stretch each plot to match the aspect ratio of its cell (fit=True),
-        or to preserve the original aspect ratio of plots (fit=False).
-    align : bool, default=False
-        If True, align inner areas (i.e. “geom” bounds) of plots.
-        However, cells containing other (sub)grids are not participating
-        in the plot “inner areas” layouting.
-    guides : str, default='auto'
-        Specifies how guides (legends and colorbars) should be treated in the layout.
-            - 'collect' collect guides from all subplots, removing duplicates.
-            - 'keep' keep guides in their original subplots; do not collect at this level.
-            - 'auto' allow guides to be collected if an upper-level layout uses guides='collect';
-
-        otherwise, keep them in subplots.
-        Duplicates are identified by comparing visual properties:
-        For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.).
-        For colorbars: title, domain limits, breaks, and color gradient.
-
-        For more information on gggrid parameters:
-        https://lets-plot.org/python/pages/api/lets_plot.gggrid.html
-
-    point_kwargs : dict[str, Any] | None, default=None
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-    **geom_kwargs
-        Additional parameters for the `geom_boxplot` layer.
-        For more information on geom_boxplot parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_boxplot.html
-
-    Returns
-    -------
-    SupPlotsSpec
-        Boxplots.
-    """
-    plots = []
-    for i,key in enumerate(keys):
-        plot = boxplot(
-            data=data,
-            key=key,
-            mapping=mapping,
-            axis=axis,
-            color=color,
-            fill=fill,
-            add_keys=add_keys,
-            tooltips=tooltips,
-            geom_fill=geom_fill,
-            geom_color=geom_color,
-            point_color=point_color,
-            point_alpha=point_alpha,
-            point_size=point_size,
-            point_geom=point_geom,
-            observations_name=observations_name,
-            variables_name=variables_name,
-            show_points=show_points,
-            interactive=interactive,
-            value_column=value_column,
-            variable_column=variable_column,
-            point_kwargs=point_kwargs,
-            **geom_kwargs,
-        )
-        # handle the layers
-        if layers is not None:
-            if isinstance(layers, (FeatureSpec, LayerSpec)):
-                layers = [layers]
-            for layer in layers:
-                plot += layer
-        if share_ticks:
-            plot = _share_ticks(plot, i, keys, ncol)
-        if share_axis:
-            plot = _share_axis(plot, i, keys, ncol, "axis")
-
-        plots.append(plot)
-
-    return gggrid(
-        plots,
-        ncol=ncol,
-        sharex=sharex,
-        sharey=sharey,
-        widths=widths,
-        heights=heights,
-        hspace=hspace,
-        vspace=vspace,
-        fit=fit,
-        align=align,
-        guides=guides,
-    )

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- - © Copyright 2026, datavil. -
- -

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- Created using Sphinx 9.1.0. -
-

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- - Built with the PyData Sphinx Theme 0.16.1. -

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- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/single/core/subdimensional.html b/docs/_build/_modules/cellestial/single/core/subdimensional.html deleted file mode 100644 index 149974f..0000000 --- a/docs/_build/_modules/cellestial/single/core/subdimensional.html +++ /dev/null @@ -1,1137 +0,0 @@ - - - - - - - - - - cellestial.single.core.subdimensional - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for cellestial.single.core.subdimensional

-from __future__ import annotations
-
-from typing import TYPE_CHECKING, Literal
-
-from cellestial.single.core.dimensional import dimensional
-from cellestial.util import _is_variable_key
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-    from anndata import AnnData
-    from lets_plot.plot.core import FeatureSpec, PlotSpec
-
-
-

-[docs]
-def umap(
-    data: AnnData,
-    key: str | None = None,
-    *,
-    mapping : FeatureSpec | None = None,
-    use_key: str | None = None,
-    xy: tuple[int, int] | Sequence[int] = (1, 2),
-    size: float = 0.8,
-    variable_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    observations_name: str = "Barcode",
-    color_low: str = "#e6e6e6",
-    color_mid: str | None = None,
-    color_high: str = "#377eb8",
-    mid_point: Literal["mean", "median", "mid"] | float = "median",
-    axis_type: Literal["axis", "arrow"] | None = None,
-    arrow_length: float = 0.25,
-    arrow_size: float = 1,
-    arrow_color: str = "#3f3f3f",
-    arrow_angle: float = 10,
-    legend_ondata: bool = False,
-    ondata_size: float = 12,
-    ondata_color: str = "#3f3f3f",
-    ondata_fontface: str = "bold",
-    ondata_family: str = "sans",
-    ondata_alpha: float = 1,
-    ondata_weighted: bool = True,
-    **point_kwargs,
-) -> PlotSpec:
-    """
-    UMAP Dimensionality reduction plot.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    key : str, default=None
-        The key (cell feature) to color the points by.
-        e.g., 'leiden' or 'louvain' to color by clusters or gene name for expression.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    use_key : str, default=None
-        The specific key to use for the desired dimensions.
-        e.g., 'X_umap_2d' or 'X_pca_2d'.
-        Otherwise, the function will decide on the key based on the dimensions.
-    xy : tuple[int, int] | Sequence[int], default=(1, 2)
-        The x and y axes to use for the plot.
-        e.g., (1, 2) for UMAP1 and UMAP2.
-    size : float, default=0.8
-        The size of the points.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    color_low : str, default='#e6e6e6'
-        The color to use for the low end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_mid : str, default=None
-        The color to use for the middle part of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_high : str, default='#377EB8'
-        The color to use for the high end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    mid_point : Literal['mean', 'median', 'mid'] | float, default='median'
-        The midpoint (in data value) of the color gradient.
-        Can be 'mean', 'median' and 'mid' or a number (float or int).
-        - If 'mean', the midpoint is the mean of the data.
-        - If 'median', the midpoint is the median of the data.
-        - If 'mid', the midpoint is the mean of 'min' and 'max' of the data.
-
-    axis_type : Literal['axis', 'arrow'] | None
-        Whether to use regular axis or arrows as the axis.
-    arrow_length : float, default=0.25
-        Length of the arrow head (px).
-    arrow_size : float, default=1
-        Size of the arrow.
-    arrow_color : str, default='#3f3f3f'
-        Color of the arrows.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    arrow_angle : float, default=10
-        Angle of the arrow head in degrees.
-    legend_ondata: bool, default=False
-        whether to show legend on data
-    ondata_size: float, default=12
-        size of the legend (text) on data.
-    ondata_color: str, default='#3f3f3f'
-        color of the legend (text) on data
-    ondata_fontface: str, default='bold'
-        fontface of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-face
-    ondata_family: str, default='sans'
-        family of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-family
-    ondata_alpha: float, default=1
-        alpha (transparency) of the legend on data.
-    ondata_weighted: bool, default=True
-        whether to use weighted mean for the legend on data.
-        If True, the weighted mean of the group means is used.
-        If False, the arithmetic mean of the group means is used.
-    **point_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    PlotSpec
-        Dimensional reduction plot.
-
-    """
-    return dimensional(
-        data=data,
-        key=key,
-        mapping=mapping,
-        dimensions="umap",
-        use_key=use_key,
-        xy=xy,
-        size=size,
-        variable_keys=variable_keys,
-        tooltips=tooltips,
-        interactive=interactive,
-        observations_name=observations_name,
-        color_low=color_low,
-        color_mid=color_mid,
-        color_high=color_high,
-        mid_point=mid_point,
-        axis_type=axis_type,
-        arrow_length=arrow_length,
-        arrow_size=arrow_size,
-        arrow_color=arrow_color,
-        arrow_angle=arrow_angle,
-        legend_ondata=legend_ondata,
-        ondata_size=ondata_size,
-        ondata_color=ondata_color,
-        ondata_fontface=ondata_fontface,
-        ondata_family=ondata_family,
-        ondata_alpha=ondata_alpha,
-        ondata_weighted=ondata_weighted,
-        **point_kwargs,
-    )

-
-
-
-

-[docs]
-def tsne(
-    data: AnnData,
-    key: str | None = None,
-    *,
-    mapping : FeatureSpec | None = None,
-    use_key: str | None = None,
-    xy: tuple[int, int] | Sequence[int] = (1, 2),
-    size: float = 0.8,
-    variable_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    observations_name: str = "Barcode",
-    color_low: str = "#e6e6e6",
-    color_mid: str | None = None,
-    color_high: str = "#377eb8",
-    mid_point: Literal["mean", "median", "mid"] | float = "median",
-    axis_type: Literal["axis", "arrow"] | None = None,
-    arrow_length: float = 0.25,
-    arrow_size: float = 1,
-    arrow_color: str = "#3f3f3f",
-    arrow_angle: float = 10,
-    legend_ondata: bool = False,
-    ondata_size: float = 12,
-    ondata_color: str = "#3f3f3f",
-    ondata_fontface: str = "bold",
-    ondata_family: str = "sans",
-    ondata_alpha: float = 1,
-    ondata_weighted: bool = True,
-    **point_kwargs,
-) -> PlotSpec:
-    """
-    tSNE Dimensionality reduction plot.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    key : str, default=None
-        The key (cell feature) to color the points by.
-        e.g., 'leiden' or 'louvain' to color by clusters or gene name for expression.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    use_key : str, default=None
-        The specific key to use for the desired dimensions.
-        e.g., 'X_umap_2d' or 'X_pca_2d'.
-        Otherwise, the function will decide on the key based on the dimensions.
-    xy : tuple[int, int] | Sequence[int], default=(1, 2)
-        The x and y axes to use for the plot.
-        e.g., (1, 2) for UMAP1 and UMAP2.
-    size : float, default=0.8
-        The size of the points.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    color_low : str, default='#e6e6e6'
-        The color to use for the low end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_mid : str, default=None
-        The color to use for the middle part of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_high : str, default='#377EB8'
-        The color to use for the high end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    mid_point : Literal['mean', 'median', 'mid'] | float, default='median'
-        The midpoint (in data value) of the color gradient.
-        Can be 'mean', 'median' and 'mid' or a number (float or int).
-        - If 'mean', the midpoint is the mean of the data.
-        - If 'median', the midpoint is the median of the data.
-        - If 'mid', the midpoint is the mean of 'min' and 'max' of the data.
-
-    axis_type : Literal['axis', 'arrow'] | None
-        Whether to use regular axis or arrows as the axis.
-    arrow_length : float, default=0.25
-        Length of the arrow head (px).
-    arrow_size : float, default=1
-        Size of the arrow.
-    arrow_color : str, default='#3f3f3f'
-        Color of the arrows.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    arrow_angle : float, default=10
-        Angle of the arrow head in degrees.
-    legend_ondata: bool, default=False
-        whether to show legend on data
-    ondata_size: float, default=12
-        size of the legend (text) on data.
-    ondata_color: str, default='#3f3f3f'
-        color of the legend (text) on data
-    ondata_fontface: str, default='bold'
-        fontface of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-face
-    ondata_family: str, default='sans'
-        family of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-family
-    ondata_alpha: float, default=1
-        alpha (transparency) of the legend on data.
-    ondata_weighted: bool, default=True
-        whether to use weighted mean for the legend on data.
-        If True, the weighted mean of the group means is used.
-        If False, the arithmetic mean of the group means is used.
-    **point_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    PlotSpec
-        Dimensional reduction plot.
-
-    """  # noqa: D403
-    return dimensional(
-        data=data,
-        key=key,
-        mapping=mapping,
-        dimensions="tsne",
-        use_key=use_key,
-        xy=xy,
-        size=size,
-        variable_keys=variable_keys,
-        tooltips=tooltips,
-        interactive=interactive,
-        observations_name=observations_name,
-        color_low=color_low,
-        color_mid=color_mid,
-        color_high=color_high,
-        mid_point=mid_point,
-        axis_type=axis_type,
-        arrow_length=arrow_length,
-        arrow_size=arrow_size,
-        arrow_color=arrow_color,
-        arrow_angle=arrow_angle,
-        legend_ondata=legend_ondata,
-        ondata_size=ondata_size,
-        ondata_color=ondata_color,
-        ondata_fontface=ondata_fontface,
-        ondata_family=ondata_family,
-        ondata_alpha=ondata_alpha,
-        ondata_weighted=ondata_weighted,
-        **point_kwargs,
-    )

-
-
-
-

-[docs]
-def pca(
-    data: AnnData,
-    key: str | None = None,
-    *,
-    mapping : FeatureSpec | None = None,
-    use_key: str | None = None,
-    xy: tuple[int, int] | Sequence[int] = (1, 2),
-    size: float = 0.8,
-    variable_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    observations_name: str = "Barcode",
-    color_low: str = "#e6e6e6",
-    color_mid: str | None = None,
-    color_high: str = "#377eb8",
-    mid_point: Literal["mean", "median", "mid"] | float = "median",
-    axis_type: Literal["axis", "arrow"] | None = None,
-    arrow_length: float = 0.25,
-    arrow_size: float = 1,
-    arrow_color: str = "#3f3f3f",
-    arrow_angle: float = 10,
-    legend_ondata: bool = False,
-    ondata_size: float = 12,
-    ondata_color: str = "#3f3f3f",
-    ondata_fontface: str = "bold",
-    ondata_family: str = "sans",
-    ondata_alpha: float = 1,
-    ondata_weighted: bool = True,
-    **point_kwargs,
-) -> PlotSpec:
-    """
-    PCA Dimensionality reduction plot.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    key : str, default=None
-        The key (cell feature) to color the points by.
-        e.g., 'leiden' or 'louvain' to color by clusters or gene name for expression.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    use_key : str, default=None
-        The specific key to use for the desired dimensions.
-        e.g., 'X_umap_2d' or 'X_pca_2d'.
-        Otherwise, the function will decide on the key based on the dimensions.
-    xy : tuple[int, int] | Sequence[int], default=(1, 2)
-        The x and y axes to use for the plot.
-        e.g., (1, 2) for UMAP1 and UMAP2.
-    size : float, default=0.8
-        The size of the points.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    color_low : str, default='#e6e6e6'
-        The color to use for the low end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_mid : str, default=None
-        The color to use for the middle part of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_high : str, default='#377EB8'
-        The color to use for the high end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    mid_point : Literal['mean', 'median', 'mid'] | float, default='median'
-        The midpoint (in data value) of the color gradient.
-        Can be 'mean', 'median' and 'mid' or a number (float or int).
-        - If 'mean', the midpoint is the mean of the data.
-        - If 'median', the midpoint is the median of the data.
-        - If 'mid', the midpoint is the mean of 'min' and 'max' of the data.
-
-    axis_type : Literal['axis', 'arrow'] | None
-        Whether to use regular axis or arrows as the axis.
-    arrow_length : float, default=0.25
-        Length of the arrow head (px).
-    arrow_size : float, default=1
-        Size of the arrow.
-    arrow_color : str, default='#3f3f3f'
-        Color of the arrows.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    arrow_angle : float, default=10
-        Angle of the arrow head in degrees.
-    legend_ondata: bool, default=False
-        whether to show legend on data
-    ondata_size: float, default=12
-        size of the legend (text) on data.
-    ondata_color: str, default='#3f3f3f'
-        color of the legend (text) on data
-    ondata_fontface: str, default='bold'
-        fontface of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-face
-    ondata_family: str, default='sans'
-        family of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-family
-    ondata_alpha: float, default=1
-        alpha (transparency) of the legend on data.
-    ondata_weighted: bool, default=True
-        whether to use weighted mean for the legend on data.
-        If True, the weighted mean of the group means is used.
-        If False, the arithmetic mean of the group means is used.
-    **point_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    PlotSpec
-        Dimensional reduction plot.
-
-    """
-    return dimensional(
-        data=data,
-        key=key,
-        mapping=mapping,
-        dimensions="pca",
-        use_key=use_key,
-        xy=xy,
-        size=size,
-        variable_keys=variable_keys,
-        tooltips=tooltips,
-        interactive=interactive,
-        observations_name=observations_name,
-        color_low=color_low,
-        color_mid=color_mid,
-        color_high=color_high,
-        mid_point=mid_point,
-        axis_type=axis_type,
-        arrow_length=arrow_length,
-        arrow_size=arrow_size,
-        arrow_color=arrow_color,
-        arrow_angle=arrow_angle,
-        legend_ondata=legend_ondata,
-        ondata_size=ondata_size,
-        ondata_color=ondata_color,
-        ondata_fontface=ondata_fontface,
-        ondata_family=ondata_family,
-        ondata_alpha=ondata_alpha,
-        ondata_weighted=ondata_weighted,
-        **point_kwargs,
-    )

-
-
-
-

-[docs]
-def expression(
-    data: AnnData,
-    key: str,
-    *,
-    mapping : FeatureSpec | None = None,
-    dimensions: Literal["umap", "pca", "tsne"] = "umap",
-    use_key: str | None = None,
-    xy: tuple[int, int] | Sequence[int] = (1, 2),
-    size: float = 0.8,
-    variable_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    observations_name: str = "Barcode",
-    color_low: str = "#e6e6e6",
-    color_mid: str | None = None,
-    color_high: str = "#377eb8",
-    mid_point: Literal["mean", "median", "mid"] | float = "median",
-    axis_type: Literal["axis", "arrow"] | None = "arrow",
-    arrow_length: float = 0.25,
-    arrow_size: float = 1,
-    arrow_color: str = "#3f3f3f",
-    arrow_angle: float = 10,
-    legend_ondata: bool = False,
-    ondata_size: float = 12,
-    ondata_color: str = "#3f3f3f",
-    ondata_fontface: str = "bold",
-    ondata_family: str = "sans",
-    ondata_alpha: float = 1,
-    ondata_weighted: bool = True,
-    **point_kwargs,
-) -> PlotSpec:
-    """
-    Dimensionality reduction plot of expression data.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    key : str
-        The key (gene names) to color the points by.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    dimensions : Literal['umap', 'pca', 'tsne'], default='umap'
-        The dimensional reduction method to use.
-        e.g., 'umap' or 'pca' or 'tsne'.
-    use_key : str, default=None
-        The specific key to use for the desired dimensions.
-        e.g., 'X_umap_2d' or 'X_pca_2d'.
-        Otherwise, the function will decide on the key based on the dimensions.
-    xy : tuple[int, int] | Sequence[int], default=(1, 2)
-        The x and y axes to use for the plot.
-        e.g., (1, 2) for UMAP1 and UMAP2.
-    size : float, default=0.8
-        The size of the points.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    color_low : str, default='#e6e6e6'
-        The color to use for the low end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_mid : str, default=None
-        The color to use for the middle part of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_high : str, default='#377EB8'
-        The color to use for the high end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    mid_point : Literal['mean', 'median', 'mid'] | float, default='median'
-        The midpoint (in data value) of the color gradient.
-        Can be 'mean', 'median' and 'mid' or a number (float or int).
-        - If 'mean', the midpoint is the mean of the data.
-        - If 'median', the midpoint is the median of the data.
-        - If 'mid', the midpoint is the mean of 'min' and 'max' of the data.
-
-    axis_type : Literal['axis', 'arrow'] | None
-        Whether to use regular axis or arrows as the axis.
-    arrow_length : float, default=0.25
-        Length of the arrow head (px).
-    arrow_size : float, default=1
-        Size of the arrow.
-    arrow_color : str, default='#3f3f3f'
-        Color of the arrows.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    arrow_angle : float, default=10
-        Angle of the arrow head in degrees.
-    legend_ondata: bool, default=False
-        whether to show legend on data
-    ondata_size: float, default=12
-        size of the legend (text) on data.
-    ondata_color: str, default='#3f3f3f'
-        color of the legend (text) on data
-    ondata_fontface: str, default='bold'
-        fontface of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-face
-    ondata_family: str, default='sans'
-        family of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-family
-    ondata_alpha: float, default=1
-        alpha (transparency) of the legend on data.
-    ondata_weighted: bool, default=True
-        whether to use weighted mean for the legend on data.
-        If True, the weighted mean of the group means is used.
-        If False, the arithmetic mean of the group means is used.
-    **point_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    PlotSpec
-        Dimensional reduction plot.
-
-    """
-    if not _is_variable_key(data, key):
-        msg = f"'{key}' is not present in `variable` names"
-        raise ValueError(msg)
-    return dimensional(
-        data=data,
-        key=key,
-        mapping=mapping,
-        dimensions=dimensions,
-        use_key=use_key,
-        xy=xy,
-        size=size,
-        variable_keys=variable_keys,
-        tooltips=tooltips,
-        interactive=interactive,
-        observations_name=observations_name,
-        color_low=color_low,
-        color_mid=color_mid,
-        color_high=color_high,
-        mid_point=mid_point,
-        axis_type=axis_type,
-        arrow_length=arrow_length,
-        arrow_size=arrow_size,
-        arrow_color=arrow_color,
-        arrow_angle=arrow_angle,
-        legend_ondata=legend_ondata,
-        ondata_size=ondata_size,
-        ondata_color=ondata_color,
-        ondata_fontface=ondata_fontface,
-        ondata_family=ondata_family,
-        ondata_alpha=ondata_alpha,
-        ondata_weighted=ondata_weighted,
-        **point_kwargs,
-    )

-
-
- -
- - - - - -
- - - - -
-
- -
- -
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-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/single/core/subdimensionals.html b/docs/_build/_modules/cellestial/single/core/subdimensionals.html deleted file mode 100644 index e1f6337..0000000 --- a/docs/_build/_modules/cellestial/single/core/subdimensionals.html +++ /dev/null @@ -1,1789 +0,0 @@ - - - - - - - - - - cellestial.single.core.subdimensionals - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for cellestial.single.core.subdimensionals

-from __future__ import annotations
-
-from collections.abc import Sequence
-from typing import TYPE_CHECKING, Literal
-
-from lets_plot import gggrid
-from lets_plot.plot.core import FeatureSpec, LayerSpec
-
-from cellestial.single.core.dimensional import dimensional
-from cellestial.single.core.subdimensional import expression, pca, tsne, umap
-from cellestial.util import _share_axis, _share_labels
-
-if TYPE_CHECKING:
-    from anndata import AnnData
-    from lets_plot.plot.subplots import SupPlotsSpec
-
-
-

-[docs]
-def dimensionals(
-    data: AnnData,
-    keys: Sequence[str],
-    *,
-    mapping: FeatureSpec | None = None,
-    dimensions: Literal["umap", "pca", "tsne"] = "umap",
-    use_key: str | None = None,
-    xy: tuple[int, int] | Sequence[int] = (1, 2),
-    size: float = 0.8,
-    variable_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    observations_name: str = "Barcode",
-    color_low: str = "#e6e6e6",
-    color_mid: str | None = None,
-    color_high: str = "#377eb8",
-    mid_point: Literal["mean", "median", "mid"] | float = "median",
-    axis_type: Literal["axis", "arrow"] | None = None,
-    arrow_length: float = 0.25,
-    arrow_size: float = 1,
-    arrow_color: str = "#3f3f3f",
-    arrow_angle: float = 10,
-    legend_ondata: bool = False,
-    ondata_size: float = 12,
-    ondata_color: str = "#3f3f3f",
-    ondata_fontface: str = "bold",
-    ondata_family: str = "sans",
-    ondata_alpha: float = 1,
-    ondata_weighted: bool = True,
-    # multi plot args
-    share_labels: bool = True,
-    share_axis: bool = False,
-    layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None,
-    # grid args
-    ncol: int | None = None,
-    sharex: str | None = None,
-    sharey: str | None = None,
-    widths: list[float] | None = None,
-    heights: list[float] | None = None,
-    hspace: float | None = None,
-    vspace: float | None = None,
-    fit: bool | None = None,
-    align: bool | None = None,
-    guides: str = "auto",
-    **point_kwargs,
-) -> SupPlotsSpec:
-    """
-    Grid of dimensionality reduction plots.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    keys : list[str] | tuple[str] | Sequence[str]
-        The keys (cell features) to color the points by.
-        e.g., 'leiden' or 'louvain' to color by clusters or gene name for expression.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    dimensions : Literal['umap', 'pca', 'tsne'], default='umap'
-        The dimensional reduction method to use.
-        e.g., 'umap' or 'pca' or 'tsne'.
-    xy : tuple[int, int] | Sequence[int], default=(1, 2)
-        The x and y axes to use for the plot.
-        e.g., (1, 2) for UMAP1 and UMAP2.
-    use_key : str, default=None
-        The specific key to use for the desired dimensions.
-        e.g., 'X_umap_2d' or 'X_pca_2d'.
-        Otherwise, the function will decide on the key based on the dimensions.
-    size : float, default=0.8
-        The size of the points.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    cluster_name : str, default='Cluster'
-        The name to overwrite the clustering key in the dataframe and the plot.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    color_low : str, default='#e6e6e6'
-        The color to use for the low end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_mid : str, default=None
-        The color to use for the middle part of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_high : str, default='#377EB8'
-        The color to use for the high end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    mid_point : Literal['mean', 'median', 'mid'] | float, default='median'
-        The midpoint (in data value) of the color gradient.
-        Can be 'mean', 'median' and 'mid' or a number (float or int).
-        - If 'mean', the midpoint is the mean of the data.
-        - If 'median', the midpoint is the median of the data.
-        - If 'mid', the midpoint is the mean of 'min' and 'max' of the data.
-
-    axis_type : Literal['axis', 'arrow'] | None
-        Whether to use regular axis or arrows as the axis.
-    arrow_length : float, default=0.25
-        Length of the arrow head (px).
-    arrow_size : float, default=1
-        Size of the arrow.
-    arrow_color : str, default='#3f3f3f'
-        Color of the arrows.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    arrow_angle : float, default=10
-        Angle of the arrow head in degrees.
-    legend_ondata: bool, default=False
-        whether to show legend on data
-    ondata_size: float, default=12
-        size of the legend (text) on data.
-    ondata_color: str, default='#3f3f3f'
-        color of the legend (text) on data
-    ondata_fontface: str, default='bold'
-        fontface of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-face
-    ondata_family: str, default='sans'
-        family of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-family
-    ondata_alpha: float, default=1
-        alpha (transparency) of the legend on data.
-    ondata_weighted: bool, default=True
-        whether to use weighted mean for the legend on data.
-        If True, the weighted mean of the group means is used.
-        If False, the arithmetic mean of the group means is used.
-    share_labels : bool, default=True
-        Whether to share the labels across all plots.
-        If True, only X labels on bottom row and Y labels on left column are shown.
-    share_axis : bool, default=False
-        Whether to share the axis across all plots.
-        If True, only X axis on bottom row and Y axis on left column is shown.
-    layers : Sequence[FeatureSpec|LayerSpec] | FeatureSpec | LayerSpec | None, default=None
-        Layers to add to all the plots in the grid.
-    ncol : int, default=None
-        Number of columns in grid. If not specified, shows plots horizontally, in one row.
-    sharex, sharey : bool, default=None
-        Controls sharing of axis limits between subplots in the grid.
-        `all`/True - share limits between all subplots.
-        `none`/False - do not share limits between subplots.
-        `row` - share limits between subplots in the same row.
-        `col` - share limits between subplots in the same column.
-    widths : list[float], default=None
-        Relative width of each column of grid, left to right.
-    heights : list[float], default=None
-        Relative height of each row of grid, top-down.
-    hspace : float | None = None
-        Cell horizontal spacing in px.
-    vspace : float | None = None
-        Cell vertical spacing in px.
-    fit : bool, default=True
-        Whether to stretch each plot to match the aspect ratio of its cell (fit=True),
-        or to preserve the original aspect ratio of plots (fit=False).
-    align : bool, default=False
-        If True, align inner areas (i.e. “geom” bounds) of plots.
-        However, cells containing other (sub)grids are not participating
-        in the plot “inner areas” layouting.
-    guides : str, default='auto'
-        Specifies how guides (legends and colorbars) should be treated in the layout.
-            - 'collect' collect guides from all subplots, removing duplicates.
-            - 'keep' keep guides in their original subplots; do not collect at this level.
-            - 'auto' allow guides to be collected if an upper-level layout uses guides='collect';
-
-        otherwise, keep them in subplots.
-        Duplicates are identified by comparing visual properties:
-        For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.).
-        For colorbars: title, domain limits, breaks, and color gradient.
-
-        For more information on gggrid parameters:
-        https://lets-plot.org/python/pages/api/lets_plot.gggrid.html
-
-    **point_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    SupPlotsSpec
-        Grid of dimensionality reduction plots.
-
-    """
-    if not isinstance(keys, Sequence) or isinstance(keys, str):
-        msg = "keys must be an Sequence of strings"
-        raise TypeError(msg)
-
-    plots = []
-    for i, key in enumerate(keys):
-        plot = dimensional(
-            data=data,
-            key=key,
-            mapping=mapping,
-            dimensions=dimensions,
-            use_key=use_key,
-            xy=xy,
-            size=size,
-            variable_keys=variable_keys,
-            tooltips=tooltips,
-            interactive=interactive,
-            observations_name=observations_name,
-            color_low=color_low,
-            color_mid=color_mid,
-            color_high=color_high,
-            mid_point=mid_point,
-            axis_type=axis_type,
-            arrow_length=arrow_length,
-            arrow_size=arrow_size,
-            arrow_color=arrow_color,
-            arrow_angle=arrow_angle,
-            legend_ondata=legend_ondata,
-            ondata_size=ondata_size,
-            ondata_color=ondata_color,
-            ondata_fontface=ondata_fontface,
-            ondata_family=ondata_family,
-            ondata_alpha=ondata_alpha,
-            ondata_weighted=ondata_weighted,
-            **point_kwargs,
-        )
-
-        # handle the layers
-        if layers is not None:
-            if isinstance(layers, (FeatureSpec, LayerSpec)):
-                layers = [layers]
-            for layer in layers:
-                plot += layer
-        if share_labels:
-            plot = _share_labels(plot, i, keys, ncol)
-        if share_axis:
-            if axis_type is not None:
-                plot = _share_axis(plot, i, keys, ncol, axis_type)
-
-        plots.append(plot)
-
-    return gggrid(
-        plots,
-        ncol=ncol,
-        sharex=sharex,
-        sharey=sharey,
-        widths=widths,
-        heights=heights,
-        hspace=hspace,
-        vspace=vspace,
-        fit=fit,
-        align=align,
-        guides=guides,
-    )

-
-
-
-

-[docs]
-def umaps(
-    data: AnnData,
-    keys: Sequence[str],
-    *,
-    mapping: FeatureSpec | None = None,
-    use_key: str | None = None,
-    xy: tuple[int, int] | Sequence[int] = (1, 2),
-    size: float = 0.8,
-    variable_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    observations_name: str = "Barcode",
-    color_low: str = "#e6e6e6",
-    color_mid: str | None = None,
-    color_high: str = "#377eb8",
-    mid_point: Literal["mean", "median", "mid"] | float = "median",
-    axis_type: Literal["axis", "arrow"] | None = None,
-    arrow_length: float = 0.25,
-    arrow_size: float = 1,
-    arrow_color: str = "#3f3f3f",
-    arrow_angle: float = 10,
-    legend_ondata: bool = False,
-    ondata_size: float = 12,
-    ondata_color: str = "#3f3f3f",
-    ondata_fontface: str = "bold",
-    ondata_family: str = "sans",
-    ondata_alpha: float = 1,
-    ondata_weighted: bool = True,
-    # multi plot args
-    share_labels: bool = True,
-    share_axis: bool = False,
-    layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None,
-    # grid args
-    ncol: int | None = None,
-    sharex: str | None = None,
-    sharey: str | None = None,
-    widths: list[float] | None = None,
-    heights: list[float] | None = None,
-    hspace: float | None = None,
-    vspace: float | None = None,
-    fit: bool | None = None,
-    align: bool | None = None,
-    guides: str = "auto",
-    **point_kwargs,
-) -> SupPlotsSpec:
-    """
-    Grid of dimensionality reduction plots.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    keys : list[str] | tuple[str] | Sequence[str]
-        The keys (cell features) to color the points by.
-        e.g., 'leiden' or 'louvain' to color by clusters or gene name for expression.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    xy : tuple[int, int] | Sequence[int], default=(1, 2)
-        The x and y axes to use for the plot.
-        e.g., (1, 2) for UMAP1 and UMAP2.
-    use_key : str, default=None
-        The specific key to use for the desired dimensions.
-        e.g., 'X_umap_2d' or 'X_pca_2d'.
-        Otherwise, the function will decide on the key based on the dimensions.
-    size : float, default=0.8
-        The size of the points.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    cluster_name : str, default='Cluster'
-        The name to overwrite the clustering key in the dataframe and the plot.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    color_low : str, default='#e6e6e6'
-        The color to use for the low end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_mid : str, default=None
-        The color to use for the middle part of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_high : str, default='#377EB8'
-        The color to use for the high end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    mid_point : Literal['mean', 'median', 'mid'] | float, default='median'
-        The midpoint (in data value) of the color gradient.
-        Can be 'mean', 'median' and 'mid' or a number (float or int).
-        - If 'mean', the midpoint is the mean of the data.
-        - If 'median', the midpoint is the median of the data.
-        - If 'mid', the midpoint is the mean of 'min' and 'max' of the data.
-
-    axis_type : Literal['axis', 'arrow'] | None
-        Whether to use regular axis or arrows as the axis.
-    arrow_length : float, default=0.25
-        Length of the arrow head (px).
-    arrow_size : float, default=1
-        Size of the arrow.
-    arrow_color : str, default='#3f3f3f'
-        Color of the arrows.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    arrow_angle : float, default=10
-        Angle of the arrow head in degrees.
-    legend_ondata: bool, default=False
-        whether to show legend on data
-    ondata_size: float, default=12
-        size of the legend (text) on data.
-    ondata_color: str, default='#3f3f3f'
-        color of the legend (text) on data
-    ondata_fontface: str, default='bold'
-        fontface of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-face
-    ondata_family: str, default='sans'
-        family of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-family
-    ondata_alpha: float, default=1
-        alpha (transparency) of the legend on data.
-    ondata_weighted: bool, default=True
-        whether to use weighted mean for the legend on data.
-        If True, the weighted mean of the group means is used.
-        If False, the arithmetic mean of the group means is used.
-    share_labels : bool, default=True
-        Whether to share the labels across all plots.
-        If True, only X labels on bottom row and Y labels on left column are shown.
-    share_axis : bool, default=False
-        Whether to share the axis across all plots.
-        If True, only X axis on bottom row and Y axis on left column is shown.
-    layers : Sequence[FeatureSpec|LayerSpec] | FeatureSpec | LayerSpec | None, default=None
-        Layers to add to all the plots in the grid.
-    ncol : int, default=None
-        Number of columns in grid. If not specified, shows plots horizontally, in one row.
-    sharex, sharey : bool, default=None
-        Controls sharing of axis limits between subplots in the grid.
-        `all`/True - share limits between all subplots.
-        `none`/False - do not share limits between subplots.
-        `row` - share limits between subplots in the same row.
-        `col` - share limits between subplots in the same column.
-    widths : list[float], default=None
-        Relative width of each column of grid, left to right.
-    heights : list[float], default=None
-        Relative height of each row of grid, top-down.
-    hspace : float | None = None
-        Cell horizontal spacing in px.
-    vspace : float | None = None
-        Cell vertical spacing in px.
-    fit : bool, default=True
-        Whether to stretch each plot to match the aspect ratio of its cell (fit=True),
-        or to preserve the original aspect ratio of plots (fit=False).
-    align : bool, default=False
-        If True, align inner areas (i.e. “geom” bounds) of plots.
-        However, cells containing other (sub)grids are not participating
-        in the plot “inner areas” layouting.
-    guides : str, default='auto'
-        Specifies how guides (legends and colorbars) should be treated in the layout.
-            - 'collect' collect guides from all subplots, removing duplicates.
-            - 'keep' keep guides in their original subplots; do not collect at this level.
-            - 'auto' allow guides to be collected if an upper-level layout uses guides='collect';
-
-        otherwise, keep them in subplots.
-        Duplicates are identified by comparing visual properties:
-        For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.).
-        For colorbars: title, domain limits, breaks, and color gradient.
-
-        For more information on gggrid parameters:
-        https://lets-plot.org/python/pages/api/lets_plot.gggrid.html
-
-    **point_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    SupPlotsSpec
-        Grid of dimensionality reduction plots.
-
-    """
-    if not isinstance(keys, Sequence) or isinstance(keys, str):
-        msg = "keys must be an Sequence of strings"
-        raise TypeError(msg)
-
-    plots = []
-    for i, key in enumerate(keys):
-        plot = umap(
-            data=data,
-            key=key,
-            mapping=mapping,
-            use_key=use_key,
-            xy=xy,
-            size=size,
-            variable_keys=variable_keys,
-            tooltips=tooltips,
-            interactive=interactive,
-            observations_name=observations_name,
-            color_low=color_low,
-            color_mid=color_mid,
-            color_high=color_high,
-            mid_point=mid_point,
-            axis_type=axis_type,
-            arrow_length=arrow_length,
-            arrow_size=arrow_size,
-            arrow_color=arrow_color,
-            arrow_angle=arrow_angle,
-            legend_ondata=legend_ondata,
-            ondata_size=ondata_size,
-            ondata_color=ondata_color,
-            ondata_fontface=ondata_fontface,
-            ondata_family=ondata_family,
-            ondata_alpha=ondata_alpha,
-            ondata_weighted=ondata_weighted,
-            **point_kwargs,
-        )
-
-        # handle the layers
-        if layers is not None:
-            if isinstance(layers, (FeatureSpec, LayerSpec)):
-                layers = [layers]
-            for layer in layers:
-                plot += layer
-        if share_labels:
-            plot = _share_labels(plot, i, keys, ncol)
-        if share_axis:
-            if axis_type is not None:
-                plot = _share_axis(plot, i, keys, ncol, axis_type)
-
-        plots.append(plot)
-
-    return gggrid(
-        plots,
-        ncol=ncol,
-        sharex=sharex,
-        sharey=sharey,
-        widths=widths,
-        heights=heights,
-        hspace=hspace,
-        vspace=vspace,
-        fit=fit,
-        align=align,
-        guides=guides,
-    )

-
-
-
-

-[docs]
-def tsnes(
-    data: AnnData,
-    keys: Sequence[str],
-    *,
-    mapping: FeatureSpec | None = None,
-    use_key: str | None = None,
-    xy: tuple[int, int] | Sequence[int] = (1, 2),
-    size: float = 0.8,
-    variable_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    observations_name: str = "Barcode",
-    color_low: str = "#e6e6e6",
-    color_mid: str | None = None,
-    color_high: str = "#377eb8",
-    mid_point: Literal["mean", "median", "mid"] | float = "median",
-    axis_type: Literal["axis", "arrow"] | None = None,
-    arrow_length: float = 0.25,
-    arrow_size: float = 1,
-    arrow_color: str = "#3f3f3f",
-    arrow_angle: float = 10,
-    legend_ondata: bool = False,
-    ondata_size: float = 12,
-    ondata_color: str = "#3f3f3f",
-    ondata_fontface: str = "bold",
-    ondata_family: str = "sans",
-    ondata_alpha: float = 1,
-    ondata_weighted: bool = True,
-    # multi plot args
-    share_labels: bool = True,
-    share_axis: bool = False,
-    layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None,
-    # grid args
-    ncol: int | None = None,
-    sharex: str | None = None,
-    sharey: str | None = None,
-    widths: list[float] | None = None,
-    heights: list[float] | None = None,
-    hspace: float | None = None,
-    vspace: float | None = None,
-    fit: bool | None = None,
-    align: bool | None = None,
-    guides: str = "auto",
-    **point_kwargs,
-) -> SupPlotsSpec:
-    """
-    Grid of dimensionality reduction plots.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    keys : list[str] | tuple[str] | Sequence[str]
-        The keys (cell features) to color the points by.
-        e.g., 'leiden' or 'louvain' to color by clusters or gene name for expression.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    xy : tuple[int, int] | Sequence[int], default=(1, 2)
-        The x and y axes to use for the plot.
-        e.g., (1, 2) for UMAP1 and UMAP2.
-    use_key : str, default=None
-        The specific key to use for the desired dimensions.
-        e.g., 'X_umap_2d' or 'X_pca_2d'.
-        Otherwise, the function will decide on the key based on the dimensions.
-    size : float, default=0.8
-        The size of the points.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    cluster_name : str, default='Cluster'
-        The name to overwrite the clustering key in the dataframe and the plot.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    color_low : str, default='#e6e6e6'
-        The color to use for the low end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_mid : str, default=None
-        The color to use for the middle part of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_high : str, default='#377EB8'
-        The color to use for the high end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    mid_point : Literal['mean', 'median', 'mid'] | float, default='median'
-        The midpoint (in data value) of the color gradient.
-        Can be 'mean', 'median' and 'mid' or a number (float or int).
-        - If 'mean', the midpoint is the mean of the data.
-        - If 'median', the midpoint is the median of the data.
-        - If 'mid', the midpoint is the mean of 'min' and 'max' of the data.
-
-    axis_type : Literal['axis', 'arrow'] | None
-        Whether to use regular axis or arrows as the axis.
-    arrow_length : float, default=0.25
-        Length of the arrow head (px).
-    arrow_size : float, default=1
-        Size of the arrow.
-    arrow_color : str, default='#3f3f3f'
-        Color of the arrows.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    arrow_angle : float, default=10
-        Angle of the arrow head in degrees.
-    legend_ondata: bool, default=False
-        whether to show legend on data
-    ondata_size: float, default=12
-        size of the legend (text) on data.
-    ondata_color: str, default='#3f3f3f'
-        color of the legend (text) on data
-    ondata_fontface: str, default='bold'
-        fontface of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-face
-    ondata_family: str, default='sans'
-        family of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-family
-    ondata_alpha: float, default=1
-        alpha (transparency) of the legend on data.
-    ondata_weighted: bool, default=True
-        whether to use weighted mean for the legend on data.
-        If True, the weighted mean of the group means is used.
-        If False, the arithmetic mean of the group means is used.
-    share_labels : bool, default=True
-        Whether to share the labels across all plots.
-        If True, only X labels on bottom row and Y labels on left column are shown.
-    share_axis : bool, default=False
-        Whether to share the axis across all plots.
-        If True, only X axis on bottom row and Y axis on left column is shown.
-    layers : Sequence[FeatureSpec|LayerSpec] | FeatureSpec | LayerSpec | None, default=None
-        Layers to add to all the plots in the grid.
-    ncol : int, default=None
-        Number of columns in grid. If not specified, shows plots horizontally, in one row.
-    sharex, sharey : bool, default=None
-        Controls sharing of axis limits between subplots in the grid.
-        `all`/True - share limits between all subplots.
-        `none`/False - do not share limits between subplots.
-        `row` - share limits between subplots in the same row.
-        `col` - share limits between subplots in the same column.
-    widths : list[float], default=None
-        Relative width of each column of grid, left to right.
-    heights : list[float], default=None
-        Relative height of each row of grid, top-down.
-    hspace : float | None = None
-        Cell horizontal spacing in px.
-    vspace : float | None = None
-        Cell vertical spacing in px.
-    fit : bool, default=True
-        Whether to stretch each plot to match the aspect ratio of its cell (fit=True),
-        or to preserve the original aspect ratio of plots (fit=False).
-    align : bool, default=False
-        If True, align inner areas (i.e. “geom” bounds) of plots.
-        However, cells containing other (sub)grids are not participating
-        in the plot “inner areas” layouting.
-    guides : str, default='auto'
-        Specifies how guides (legends and colorbars) should be treated in the layout.
-            - 'collect' collect guides from all subplots, removing duplicates.
-            - 'keep' keep guides in their original subplots; do not collect at this level.
-            - 'auto' allow guides to be collected if an upper-level layout uses guides='collect';
-
-        otherwise, keep them in subplots.
-        Duplicates are identified by comparing visual properties:
-        For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.).
-        For colorbars: title, domain limits, breaks, and color gradient.
-
-        For more information on gggrid parameters:
-        https://lets-plot.org/python/pages/api/lets_plot.gggrid.html
-
-    **point_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    SupPlotsSpec
-        Grid of dimensionality reduction plots.
-
-    """
-    if not isinstance(keys, Sequence) or isinstance(keys, str):
-        msg = "keys must be an Sequence of strings"
-        raise TypeError(msg)
-
-    plots = []
-    for i, key in enumerate(keys):
-        plot = tsne(
-            data=data,
-            key=key,
-            mapping=mapping,
-            use_key=use_key,
-            xy=xy,
-            size=size,
-            variable_keys=variable_keys,
-            tooltips=tooltips,
-            interactive=interactive,
-            observations_name=observations_name,
-            color_low=color_low,
-            color_mid=color_mid,
-            color_high=color_high,
-            mid_point=mid_point,
-            axis_type=axis_type,
-            arrow_length=arrow_length,
-            arrow_size=arrow_size,
-            arrow_color=arrow_color,
-            legend_ondata=legend_ondata,
-            ondata_size=ondata_size,
-            ondata_color=ondata_color,
-            ondata_fontface=ondata_fontface,
-            ondata_family=ondata_family,
-            ondata_alpha=ondata_alpha,
-            ondata_weighted=ondata_weighted,
-            **point_kwargs,
-        )
-
-        # handle the layers
-        if layers is not None:
-            if isinstance(layers, (FeatureSpec, LayerSpec)):
-                layers = [layers]
-            for layer in layers:
-                plot += layer
-        if share_labels:
-            plot = _share_labels(plot, i, keys, ncol)
-        if share_axis:
-            if axis_type is not None:
-                plot = _share_axis(plot, i, keys, ncol, axis_type)
-
-        plots.append(plot)
-
-    return gggrid(
-        plots,
-        ncol=ncol,
-        sharex=sharex,
-        sharey=sharey,
-        widths=widths,
-        heights=heights,
-        hspace=hspace,
-        vspace=vspace,
-        fit=fit,
-        align=align,
-        guides=guides,
-    )

-
-
-
-

-[docs]
-def pcas(
-    data: AnnData,
-    keys: Sequence[str],
-    *,
-    mapping: FeatureSpec | None = None,
-    use_key: str | None = None,
-    xy: tuple[int, int] | Sequence[int] = (1, 2),
-    size: float = 0.8,
-    variable_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    observations_name: str = "Barcode",
-    color_low: str = "#e6e6e6",
-    color_mid: str | None = None,
-    color_high: str = "#377eb8",
-    mid_point: Literal["mean", "median", "mid"] | float = "median",
-    axis_type: Literal["axis", "arrow"] | None = None,
-    arrow_length: float = 0.25,
-    arrow_size: float = 1,
-    arrow_color: str = "#3f3f3f",
-    arrow_angle: float = 10,
-    legend_ondata: bool = False,
-    ondata_size: float = 12,
-    ondata_color: str = "#3f3f3f",
-    ondata_fontface: str = "bold",
-    ondata_family: str = "sans",
-    ondata_alpha: float = 1,
-    ondata_weighted: bool = True,
-    # multi plot args
-    share_labels: bool = True,
-    share_axis: bool = False,
-    layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None,
-    # grid args
-    ncol: int | None = None,
-    sharex: str | None = None,
-    sharey: str | None = None,
-    widths: list[float] | None = None,
-    heights: list[float] | None = None,
-    hspace: float | None = None,
-    vspace: float | None = None,
-    fit: bool | None = None,
-    align: bool | None = None,
-    guides: str = "auto",
-    **point_kwargs,
-) -> SupPlotsSpec:
-    """
-    Grid of dimensionality reduction plots.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    keys : list[str] | tuple[str] | Sequence[str]
-        The keys (cell features) to color the points by.
-        e.g., 'leiden' or 'louvain' to color by clusters or gene name for expression.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    xy : tuple[int, int] | Sequence[int], default=(1, 2)
-        The x and y axes to use for the plot.
-        e.g., (1, 2) for UMAP1 and UMAP2.
-    use_key : str, default=None
-        The specific key to use for the desired dimensions.
-        e.g., 'X_umap_2d' or 'X_pca_2d'.
-        Otherwise, the function will decide on the key based on the dimensions.
-    size : float, default=0.8
-        The size of the points.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    cluster_name : str, default='Cluster'
-        The name to overwrite the clustering key in the dataframe and the plot.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    color_low : str, default='#e6e6e6'
-        The color to use for the low end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_mid : str, default=None
-        The color to use for the middle part of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_high : str, default='#377EB8'
-        The color to use for the high end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    mid_point : Literal['mean', 'median', 'mid'] | float, default='median'
-        The midpoint (in data value) of the color gradient.
-        Can be 'mean', 'median' and 'mid' or a number (float or int).
-        - If 'mean', the midpoint is the mean of the data.
-        - If 'median', the midpoint is the median of the data.
-        - If 'mid', the midpoint is the mean of 'min' and 'max' of the data.
-
-    axis_type : Literal['axis', 'arrow'] | None
-        Whether to use regular axis or arrows as the axis.
-    arrow_length : float, default=0.25
-        Length of the arrow head (px).
-    arrow_size : float, default=1
-        Size of the arrow.
-    arrow_color : str, default='#3f3f3f'
-        Color of the arrows.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    arrow_angle : float, default=10
-        Angle of the arrow head in degrees.
-    legend_ondata: bool, default=False
-        whether to show legend on data
-    ondata_size: float, default=12
-        size of the legend (text) on data.
-    ondata_color: str, default='#3f3f3f'
-        color of the legend (text) on data
-    ondata_fontface: str, default='bold'
-        fontface of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-face
-    ondata_family: str, default='sans'
-        family of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-family
-    ondata_alpha: float, default=1
-        alpha (transparency) of the legend on data.
-    ondata_weighted: bool, default=True
-        whether to use weighted mean for the legend on data.
-        If True, the weighted mean of the group means is used.
-        If False, the arithmetic mean of the group means is used.
-    share_labels : bool, default=True
-        Whether to share the labels across all plots.
-        If True, only X labels on bottom row and Y labels on left column are shown.
-    share_axis : bool, default=False
-        Whether to share the axis across all plots.
-        If True, only X axis on bottom row and Y axis on left column is shown.
-    layers : Sequence[FeatureSpec|LayerSpec] | FeatureSpec | LayerSpec | None, default=None
-        Layers to add to all the plots in the grid.
-    ncol : int, default=None
-        Number of columns in grid. If not specified, shows plots horizontally, in one row.
-    sharex, sharey : bool, default=None
-        Controls sharing of axis limits between subplots in the grid.
-        `all`/True - share limits between all subplots.
-        `none`/False - do not share limits between subplots.
-        `row` - share limits between subplots in the same row.
-        `col` - share limits between subplots in the same column.
-    widths : list[float], default=None
-        Relative width of each column of grid, left to right.
-    heights : list[float], default=None
-        Relative height of each row of grid, top-down.
-    hspace : float | None = None
-        Cell horizontal spacing in px.
-    vspace : float | None = None
-        Cell vertical spacing in px.
-    fit : bool, default=True
-        Whether to stretch each plot to match the aspect ratio of its cell (fit=True),
-        or to preserve the original aspect ratio of plots (fit=False).
-    align : bool, default=False
-        If True, align inner areas (i.e. “geom” bounds) of plots.
-        However, cells containing other (sub)grids are not participating
-        in the plot “inner areas” layouting.
-    guides : str, default='auto'
-        Specifies how guides (legends and colorbars) should be treated in the layout.
-            - 'collect' collect guides from all subplots, removing duplicates.
-            - 'keep' keep guides in their original subplots; do not collect at this level.
-            - 'auto' allow guides to be collected if an upper-level layout uses guides='collect';
-
-        otherwise, keep them in subplots.
-        Duplicates are identified by comparing visual properties:
-        For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.).
-        For colorbars: title, domain limits, breaks, and color gradient.
-
-        For more information on gggrid parameters:
-        https://lets-plot.org/python/pages/api/lets_plot.gggrid.html
-
-    **point_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    SupPlotsSpec
-        Grid of dimensionality reduction plots.
-
-    """
-    if not isinstance(keys, Sequence) or isinstance(keys, str):
-        msg = "keys must be an Sequence of strings"
-        raise TypeError(msg)
-
-    plots = []
-    for i, key in enumerate(keys):
-        plot = pca(
-            data=data,
-            key=key,
-            mapping=mapping,
-            use_key=use_key,
-            xy=xy,
-            size=size,
-            variable_keys=variable_keys,
-            tooltips=tooltips,
-            interactive=interactive,
-            observations_name=observations_name,
-            color_low=color_low,
-            color_mid=color_mid,
-            color_high=color_high,
-            mid_point=mid_point,
-            axis_type=axis_type,
-            arrow_length=arrow_length,
-            arrow_size=arrow_size,
-            arrow_color=arrow_color,
-            arrow_angle=arrow_angle,
-            legend_ondata=legend_ondata,
-            ondata_size=ondata_size,
-            ondata_color=ondata_color,
-            ondata_fontface=ondata_fontface,
-            ondata_family=ondata_family,
-            ondata_alpha=ondata_alpha,
-            ondata_weighted=ondata_weighted,
-            **point_kwargs,
-        )
-
-        # handle the layers
-        if layers is not None:
-            if isinstance(layers, (FeatureSpec, LayerSpec)):
-                layers = [layers]
-            for layer in layers:
-                plot += layer
-        if share_labels:
-            plot = _share_labels(plot, i, keys, ncol)
-        if share_axis:
-            if axis_type is not None:
-                plot = _share_axis(plot, i, keys, ncol, axis_type)
-
-        plots.append(plot)
-
-    return gggrid(
-        plots,
-        ncol=ncol,
-        sharex=sharex,
-        sharey=sharey,
-        widths=widths,
-        heights=heights,
-        hspace=hspace,
-        vspace=vspace,
-        fit=fit,
-        align=align,
-        guides=guides,
-    )

-
-
-
-

-[docs]
-def expressions(
-    data: AnnData,
-    keys: Sequence[str],
-    *,
-    mapping: FeatureSpec | None = None,
-    dimensions: Literal["umap", "pca", "tsne"] = "umap",
-    use_key: str | None = None,
-    xy: tuple[int, int] | Sequence[int] = (1, 2),
-    size: float = 0.8,
-    variable_keys: Sequence[str] | str | None = None,
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    observations_name: str = "Barcode",
-    color_low: str = "#e6e6e6",
-    color_mid: str | None = None,
-    color_high: str = "#377eb8",
-    mid_point: Literal["mean", "median", "mid"] | float = "median",
-    axis_type: Literal["axis", "arrow"] | None = None,
-    arrow_length: float = 0.25,
-    arrow_size: float = 1,
-    arrow_color: str = "#3f3f3f",
-    arrow_angle: float = 10,
-    legend_ondata: bool = False,
-    ondata_size: float = 12,
-    ondata_color: str = "#3f3f3f",
-    ondata_fontface: str = "bold",
-    ondata_family: str = "sans",
-    ondata_alpha: float = 1,
-    ondata_weighted: bool = True,
-    # multi plot args
-    share_labels: bool = True,
-    share_axis: bool = False,
-    layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None,
-    # grid args
-    ncol: int | None = None,
-    sharex: str | None = None,
-    sharey: str | None = None,
-    widths: list[float] | None = None,
-    heights: list[float] | None = None,
-    hspace: float | None = None,
-    vspace: float | None = None,
-    fit: bool | None = None,
-    align: bool | None = None,
-    guides: str = "auto",
-    **point_kwargs,
-) -> SupPlotsSpec:
-    """
-    Grid of dimensionality reduction plots.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    keys : list[str] | tuple[str] | Sequence[str]
-        The keys (gene names) to color the points by.
-    mapping : FeatureSpec | None, default=None
-        Additional aesthetic mappings for the plot, the result of `aes()`.
-    dimensions : Literal['umap', 'pca', 'tsne'], default='umap'
-        The dimensional reduction method to use.
-        e.g., 'umap' or 'pca' or 'tsne'.
-    xy : tuple[int, int] | Sequence[int], default=(1, 2)
-        The x and y axes to use for the plot.
-        e.g., (1, 2) for UMAP1 and UMAP2.
-    use_key : str, default=None
-        The specific key to use for the desired dimensions.
-        e.g., 'X_umap_2d' or 'X_pca_2d'.
-        Otherwise, the function will decide on the key based on the dimensions.
-    size : float, default=0.8
-        The size of the points.
-    variable_keys : str | Sequence[str] | None, default=None
-        Variable keys to add to the DataFrame. If None, no additional keys are added.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    cluster_name : str, default='Cluster'
-        The name to overwrite the clustering key in the dataframe and the plot.
-    observations_name : str, default='Barcode'
-        The name to give to barcode (or index) column in the dataframe.
-    color_low : str, default='#e6e6e6'
-        The color to use for the low end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_mid : str, default=None
-        The color to use for the middle part of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    color_high : str, default='#377EB8'
-        The color to use for the high end of the color gradient.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    mid_point : Literal['mean', 'median', 'mid'] | float, default='median'
-        The midpoint (in data value) of the color gradient.
-        Can be 'mean', 'median' and 'mid' or a number (float or int).
-        - If 'mean', the midpoint is the mean of the data.
-        - If 'median', the midpoint is the median of the data.
-        - If 'mid', the midpoint is the mean of 'min' and 'max' of the data.
-
-    axis_type : Literal['axis', 'arrow'] | None
-        Whether to use regular axis or arrows as the axis.
-    arrow_length : float, default=0.25
-        Length of the arrow head (px).
-    arrow_size : float, default=1
-        Size of the arrow.
-    arrow_color : str, default='#3f3f3f'
-        Color of the arrows.
-        - Accepts:
-            - hex code e.g. '#f1f1f1'
-            - color name (of a limited set of colors).
-            - RGB/RGBA e.g. 'rgb(0, 0, 255)', 'rgba(0, 0, 255, 0.5)'.
-        - Applies to continuous (non-categorical) data.
-
-    arrow_angle : float, default=10
-        Angle of the arrow head in degrees.
-    legend_ondata: bool, default=False
-        whether to show legend on data
-    ondata_size: float, default=12
-        size of the legend (text) on data.
-    ondata_color: str, default='#3f3f3f'
-        color of the legend (text) on data
-    ondata_fontface: str, default='bold'
-        fontface of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-face
-    ondata_family: str, default='sans'
-        family of the legend (text) on data.
-        https://lets-plot.org/python/pages/aesthetics.html#font-family
-    ondata_alpha: float, default=1
-        alpha (transparency) of the legend on data.
-    ondata_weighted: bool, default=True
-        whether to use weighted mean for the legend on data.
-        If True, the weighted mean of the group means is used.
-        If False, the arithmetic mean of the group means is used.
-    share_labels : bool, default=True
-        Whether to share the labels across all plots.
-        If True, only X labels on bottom row and Y labels on left column are shown.
-    share_axis : bool, default=False
-        Whether to share the axis across all plots.
-        If True, only X axis on bottom row and Y axis on left column is shown.
-    layers : Sequence[FeatureSpec|LayerSpec] | FeatureSpec | LayerSpec | None, default=None
-        Layers to add to all the plots in the grid.
-    ncol : int, default=None
-        Number of columns in grid. If not specified, shows plots horizontally, in one row.
-    sharex, sharey : bool, default=None
-        Controls sharing of axis limits between subplots in the grid.
-        `all`/True - share limits between all subplots.
-        `none`/False - do not share limits between subplots.
-        `row` - share limits between subplots in the same row.
-        `col` - share limits between subplots in the same column.
-    widths : list[float], default=None
-        Relative width of each column of grid, left to right.
-    heights : list[float], default=None
-        Relative height of each row of grid, top-down.
-    hspace : float | None = None
-        Cell horizontal spacing in px.
-    vspace : float | None = None
-        Cell vertical spacing in px.
-    fit : bool, default=True
-        Whether to stretch each plot to match the aspect ratio of its cell (fit=True),
-        or to preserve the original aspect ratio of plots (fit=False).
-    align : bool, default=False
-        If True, align inner areas (i.e. “geom” bounds) of plots.
-        However, cells containing other (sub)grids are not participating
-        in the plot “inner areas” layouting.
-    guides : str, default='auto'
-        Specifies how guides (legends and colorbars) should be treated in the layout.
-            - 'collect' collect guides from all subplots, removing duplicates.
-            - 'keep' keep guides in their original subplots; do not collect at this level.
-            - 'auto' allow guides to be collected if an upper-level layout uses guides='collect';
-
-        otherwise, keep them in subplots.
-        Duplicates are identified by comparing visual properties:
-        For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.).
-        For colorbars: title, domain limits, breaks, and color gradient.
-
-        For more information on gggrid parameters:
-        https://lets-plot.org/python/pages/api/lets_plot.gggrid.html
-
-    **point_kwargs
-        Additional parameters for the `geom_point` layer.
-        For more information on geom_point parameters, see:
-        https://lets-plot.org/python/pages/api/lets_plot.geom_point.html
-
-    Returns
-    -------
-    SupPlotsSpec
-        Grid of dimensionality reduction plots.
-
-    """
-    if not isinstance(keys, Sequence) or isinstance(keys, str):
-        msg = "keys must be an Sequence of strings"
-        raise TypeError(msg)
-
-    plots = []
-    for i, key in enumerate(keys):
-        plot = expression(
-            data=data,
-            key=key,
-            mapping=mapping,
-            dimensions=dimensions,
-            use_key=use_key,
-            xy=xy,
-            size=size,
-            variable_keys=variable_keys,
-            tooltips=tooltips,
-            interactive=interactive,
-            observations_name=observations_name,
-            color_low=color_low,
-            color_mid=color_mid,
-            color_high=color_high,
-            mid_point=mid_point,
-            axis_type=axis_type,
-            arrow_length=arrow_length,
-            arrow_size=arrow_size,
-            arrow_color=arrow_color,
-            arrow_angle=arrow_angle,
-            legend_ondata=legend_ondata,
-            ondata_size=ondata_size,
-            ondata_color=ondata_color,
-            ondata_fontface=ondata_fontface,
-            ondata_family=ondata_family,
-            ondata_alpha=ondata_alpha,
-            ondata_weighted=ondata_weighted,
-            **point_kwargs,
-        )
-
-        # handle the layers
-        if layers is not None:
-            if isinstance(layers, (FeatureSpec, LayerSpec)):
-                layers = [layers]
-            for layer in layers:
-                plot += layer
-        if share_labels:
-            plot = _share_labels(plot, i, keys, ncol)
-        if share_axis:
-            if axis_type is not None:
-                plot = _share_axis(plot, i, keys, ncol, axis_type)
-
-        plots.append(plot)
-
-    return gggrid(
-        plots,
-        ncol=ncol,
-        sharex=sharex,
-        sharey=sharey,
-        widths=widths,
-        heights=heights,
-        hspace=hspace,
-        vspace=vspace,
-        fit=fit,
-        align=align,
-        guides=guides,
-    )

-
-
- -
- - - - - -
- - - - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/single/special/dotplot.html b/docs/_build/_modules/cellestial/single/special/dotplot.html deleted file mode 100644 index 3812253..0000000 --- a/docs/_build/_modules/cellestial/single/special/dotplot.html +++ /dev/null @@ -1,613 +0,0 @@ - - - - - - - - - - cellestial.single.special.dotplot - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for cellestial.single.special.dotplot

-from __future__ import annotations
-
-import contextlib
-from collections.abc import Sequence
-from typing import TYPE_CHECKING, Literal
-
-import polars as pl
-from anndata import AnnData
-from lets_plot import (
-    aes,
-    geom_point,
-    ggplot,
-    ggtb,
-    layer_tooltips,
-    scale_color_gradient,
-    scale_fill_gradient,
-)
-from lets_plot.plot.core import FeatureSpec
-
-from cellestial.frames import build_frame
-from cellestial.themes import _THEME_DOTPLOT
-
-if TYPE_CHECKING:
-    from lets_plot.plot.core import PlotSpec
-
-
-

-[docs]
-def dotplot(
-    data: AnnData,
-    keys: Sequence[str],
-    group_by: str,
-    *,
-    threshold: float = 0,
-    variables_name: str = "gene",
-    value_name: str = "expression",
-    color_low: str = "#e6e6e6",
-    color_high: str = "#D2042D",
-    fill: bool = False,
-    sort_by: str | Sequence[str] | None = None,
-    sort_order: Literal["ascending", "descending"] = "descending",
-    percentage_key: str = "pct_exp",
-    mean_key: str = "avg_exp",
-    tooltips: Literal["none"] | Sequence[str] | FeatureSpec | None = None,
-    interactive: bool = False,
-    **geom_kwargs,
-) -> PlotSpec:
-    """
-    Dotplot.
-
-    Parameters
-    ----------
-    data : AnnData
-        The AnnData object of the single cell data.
-    keys : Sequence[str]
-        The variable keys or names to include in the dotplot.
-    group_by : str
-        The key to group the data by.
-    threshold : float, default=0
-        The expression threshold to consider a gene as expressed.
-    variables_name : str, default='gene'
-        The name of the variable column in the long format.
-    value_name : str, default='expression'
-        The name of the value column in the long format.
-    color_low : str, default='#e6e6e6'
-        The low color for the gradient.
-    color_high : str, default='#D2042D'
-        The high color for the gradient.
-    fill : bool, optional
-        Whether to use fill aesthetic instead of color, by default False.
-    sort_by : str | None
-        The column to sort the results by, by default None.
-    sort_order : str, default='descending'
-        The sort order, either 'ascending' or 'descending'.
-    percentage_key : str, default='pct_exp'
-        The name of the percentage column.
-    mean_key : str, default='avg_exp'
-        The name of the mean expression column.
-    tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None, default=None
-        Tooltips to show when hovering over the geom.
-        Accepts Sequence[str] or result of `layer_tooltips()` for more complex tooltips.
-        Use 'none' to disable tooltips.
-    show_tooltips : bool, default=True
-        Whether to show tooltips.
-    interactive : bool, default=False
-        Whether to make the plot interactive.
-    **geom_kwargs : Any
-        Additional keyword arguments for the geom_point layer.
-
-    Returns
-    -------
-    PlotSpec
-        Dotplot.
-    """
-    # HANDLE: Data types
-    if not isinstance(data, AnnData):
-        msg = "data must be an `AnnData` object"
-        raise TypeError(msg)
-    # BUILD: dataframe
-    frame = build_frame(data=data, axis=0, variable_keys=keys)
-    index_columns = [x for x in frame.columns if x not in keys]
-
-    #  CRITICAL PARTS: Dataframe Operations
-    # 1. Unpivot frame
-    frame = frame.unpivot(
-        on=keys,
-        index=index_columns,
-        variable_name=variables_name,
-        value_name=value_name,
-    )
-    # 2. Aggregate and compute stats
-    frame = frame.group_by([group_by, variables_name]).agg(
-        [
-            pl.col(value_name).mean().alias(mean_key),
-            (pl.col(value_name) > threshold).mean().mul(100).alias(percentage_key),
-        ]
-    )
-
-    # HANDLE: Sorting
-    # In case of pseudo-categorical integer group_by temporarily cast to int for proper sorting
-    with contextlib.suppress(Exception):  # supress errors if sorting fails
-        frame = (
-            frame.with_columns(pl.col(group_by).cast(pl.String).cast(pl.Int64)).sort(
-                group_by, descending=True
-            )
-            # .with_columns(pl.col(group_by).cast(pl.String).cast(pl.Categorical))
-        )
-    # perform sorting
-    if sort_by is not None:
-        frame = frame.sort(
-            by=sort_by,
-            descending=(sort_order == "descending"),
-        )
-    # Cast back to categorical
-    if frame[group_by].dtype == pl.Int64:
-        frame = frame.with_columns(
-            pl.col(group_by).cast(pl.String).cast(pl.Categorical)
-        )
-
-    # HANDLE: tooltips
-    if tooltips is None:
-        tooltips = [variables_name, group_by]
-        tooltips_spec = layer_tooltips(tooltips)
-    elif tooltips == "none" or isinstance(tooltips, str):
-        tooltips_spec = tooltips
-    elif isinstance(tooltips, Sequence):
-        tooltips = list(tooltips)
-        tooltips_spec = layer_tooltips(tooltips)
-        if not set(tooltips).issubset(frame.columns):
-            missing = set(tooltips) - set(frame.columns)
-            msg = f"Some tooltip columns are not in the data: {missing}"
-            raise ValueError(msg)
-    elif isinstance(tooltips, FeatureSpec):
-        tooltips_spec = tooltips
-
-    # BUILD: Dotplot
-    if not fill:  # use color aesthetic
-        dtplt = (
-            ggplot(frame, aes(x=variables_name, y=group_by))
-            + geom_point(
-                aes(size=percentage_key, color=mean_key), tooltips=tooltips_spec, **geom_kwargs
-            )
-            + scale_color_gradient(low=color_low, high=color_high)
-        )
-    else:  # elif fill: use fill aesthetic
-        dtplt = (
-            ggplot(frame, aes(x=variables_name, y=group_by))
-            + geom_point(
-                aes(size=percentage_key, fill=mean_key), tooltips=tooltips_spec, **geom_kwargs
-            )
-            + scale_fill_gradient(low=color_low, high=color_high)
-        )
-
-    # ADD: layers
-    dtplt += _THEME_DOTPLOT
-
-    # HANDLE: interactive
-    if interactive:
-        dtplt += ggtb(size_zoomin=-1)
-
-    return dtplt

-
-
- -
- - - - - -
- - - - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/util/colors.html b/docs/_build/_modules/cellestial/util/colors.html deleted file mode 100644 index 0825d58..0000000 --- a/docs/_build/_modules/cellestial/util/colors.html +++ /dev/null @@ -1,517 +0,0 @@ - - - - - - - - - - cellestial.util.colors - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for cellestial.util.colors

-from lets_plot import (
-    LetsPlot,
-    aes,
-    element_rect,
-    geom_point,
-    geom_text,
-    gggrid,
-    ggplot,
-    ggsize,
-    theme,
-    theme_void,
-)
-
-# Hand-picked colors for cellestial
-TEAL = "#219B9D"
-BLUE = "#377EB8"
-RED = "#D2042D"
-CHERRY = "#AF1740"
-LIGHT_GRAY = "#E6E6E6"
-SNOW = "#F9F9F9"
-PURPLE = "#640D5F"
-PINK = "#E73879"
-ORANGE = "#F14A00"
-TEAL = "#219B9D"
-RED = "#D2042D"
-CHERRY = "#AF1740"
-BLUE = "#377EB8"
-LIGHT_GRAY = "#E6E6E6"
-
-
-

-[docs]
-def show_colors():
-    """Show a grid of hand-picked colors."""
-    colors = {
-        "TEAL": TEAL,
-        "RED": RED,
-        "LIGHT_GRAY": LIGHT_GRAY,
-        "BLUE": BLUE,
-        "CHERRY": CHERRY,
-        "SNOW": SNOW,
-        "PURPLE": PURPLE,
-        "PINK": PINK,
-        "ORANGE": ORANGE,
-    }
-
-    plots = []
-    for color in colors:
-        text_color = "white" if color != "LIGHT_GRAY" and color != "SNOW" else "black"
-
-        plot = (
-            ggplot({"x": [1], "y": [1]})
-            + geom_point(aes(x="x", y="y"), fill=colors[color], shape=22, size=90, color="#1f1f1f")
-            + geom_text(
-                aes(x="x", y="y"),
-                label=f"{color}\n",
-                color=text_color,
-                size=14,
-                fontface="bold",
-                family="Arial",
-            )
-            + geom_text(
-                aes(x="x", y="y"),
-                label=f"\n{colors[color]}",
-                color=text_color,
-                size=10,
-                fontface="regular",
-                family="sans-serif",
-            )
-            + theme_void()
-            + theme(panel_background=element_rect(color=colors[color], size=13))
-        )
-        plots.append(plot)
-
-    ncol = 3
-    nrow = len(colors) // ncol
-    if len(colors) % ncol != 0:
-        nrow += 1
-
-    return gggrid(plots, ncol=3, hspace=0, vspace=0) + ggsize(ncol * 200, nrow * 200)

-
-
-
-if __name__ == "__main__":
-    LetsPlot.setup_html()
-    show_colors().to_html("colors.html")
-
- -
- - - - - -
- - - - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/_modules/cellestial/util/utilities.html b/docs/_build/_modules/cellestial/util/utilities.html deleted file mode 100644 index b854ff9..0000000 --- a/docs/_build/_modules/cellestial/util/utilities.html +++ /dev/null @@ -1,1079 +0,0 @@ - - - - - - - - - - cellestial.util.utilities - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
- - - - - - -
- - - Ctrl+K -
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Source code for cellestial.util.utilities

-from __future__ import annotations
-
-from collections.abc import Sequence
-from math import ceil, log10
-from typing import TYPE_CHECKING, Literal
-
-from anndata import AnnData
-from lets_plot import (
-    arrow,
-    element_blank,
-    element_text,
-    geom_blank,
-    geom_segment,
-    gggrid,
-    guide_legend,
-    guides,
-    layer_tooltips,
-    scale_color_continuous,
-    scale_color_gradient2,
-    theme,
-)
-from lets_plot.plot.core import PlotSpec
-from lets_plot.plot.subplots import SupPlotsSpec
-
-if TYPE_CHECKING:
-    import polars as pl
-    from lets_plot.plot.core import FeatureSpec
-
-
-def _add_arrow_axis(
-    frame: pl.DataFrame,
-    *,
-    x: str,
-    y: str,
-    axis_type: Literal["axis", "arrow"] | None,
-    arrow_size: float,
-    arrow_color: str,
-    arrow_angle: float,
-    arrow_length: float,
-):
-    """
-    Adds arrows as the X and Y axis to the plot.
-
-    Parameters
-    ----------
-    frame : `polars.DataFrame`
-        DataFrame copied from the single cell data.
-    x : str
-        Name of the x axis column.
-    y : str
-        Name of the y axis column.
-    axis_type : Literal['axis', 'arrow'] | None
-        Whether to use regular axis or arrows as the axis.
-    arrow_size : float
-        Size of the arrow.
-    arrow_color : str
-        Color of the arrow.
-    arrow_angle : float
-        Angle of the arrow head in degrees.
-    arrow_length : float
-        Length of the arrow head (px).
-
-    Returns
-    -------
-    `FeatureSpec` or `FeatureSpecArray`
-        Theme feature specification.
-
-    for more information on the arrow parameters, see:
-    https://lets-plot.org/python/pages/api/lets_plot.arrow.html
-    """
-    if axis_type is None:
-        return theme(
-            # remove axis elements
-            axis_text_x=element_blank(),
-            axis_text_y=element_blank(),
-            axis_ticks_y=element_blank(),
-            axis_ticks_x=element_blank(),
-            axis_line=element_blank(),
-        )
-
-    elif axis_type == "axis":
-        return geom_blank()
-
-    elif axis_type == "arrow":
-        new_layer = theme(
-            # remove axis elements
-            axis_text_x=element_blank(),
-            axis_text_y=element_blank(),
-            axis_ticks_y=element_blank(),
-            axis_ticks_x=element_blank(),
-            axis_line=element_blank(),
-            # position axis titles according to arrow size
-            axis_title_x=element_text(hjust=arrow_length / 2.5),  # better than 2
-            axis_title_y=element_text(hjust=arrow_length / 2.5),
-        )
-        x_max = frame[x].max()
-        x_min = frame[x].min()
-        y_max = frame[y].max()
-        y_min = frame[y].min()
-
-        # find total difference between the max and min for both axis
-        x_diff = x_max - x_min  # ty:ignore[unsupported-operator]
-        y_diff = y_max - y_min  # ty:ignore[unsupported-operator]
-
-        # find the ends of the arrows
-        # ensure the arrow length is the same for both axis
-        xend = x_min + arrow_length * min(y_diff, x_diff)
-        yend = y_min + arrow_length * min(y_diff, x_diff)
-
-        # adjust bottom ends of arrows
-        adjust_rate = 0.025
-        x0 = x_min - x_diff * adjust_rate
-        y0 = y_min - y_diff * adjust_rate
-
-        # X axis
-        new_layer += geom_segment(
-            x=x0,
-            y=y0,
-            xend=xend,
-            yend=y0,
-            color=arrow_color,
-            size=arrow_size,
-            arrow=arrow(arrow_angle),
-        )
-        # Y axis
-        new_layer += geom_segment(
-            x=x0,
-            y=y0,
-            xend=x0,
-            yend=yend,
-            color=arrow_color,
-            size=arrow_size,
-            arrow=arrow(arrow_angle),
-        )
-    else:
-        msg = f"expected 'axis' or 'arrow' for 'axis_type' argument, but received {axis_type}"
-        raise ValueError(msg)
-
-    return new_layer
-
-
-# TODO: Deprecate
-def _decide_tooltips(
-    base_tooltips: Sequence[str] | str | None,
-    add_tooltips: Sequence[str] | str | None,
-    custom_tooltips: Sequence[str] | str | None,
-    *,
-    show_tooltips: bool,
-) -> list[str] | Literal["none"]:
-    """
-    Decide on the tooltips.
-
-    Parameters
-    ----------
-    base_tooltips : list[str] | str
-        Base tooltips, default ones by the function.
-    add_tooltips : list[str] | str
-        Additional tooltips, will be appended to the base_tooltips.
-    custom_tooltips : list[str] | str
-        Custom tooltips, will overwrite the base_tooltips.
-    show_tooltips : bool
-        Whether to show tooltips at all.
-        Set tooltip to the Literal 'none' if False.
-
-    Returns
-    -------
-    list[str]
-        Tooltips.
-    """
-    # PART 1: CONVERT str TO list
-    if isinstance(base_tooltips, str):
-        base_tooltips = [base_tooltips]
-    elif base_tooltips is None:
-        base_tooltips = []
-    if isinstance(add_tooltips, str):
-        add_tooltips = [add_tooltips]
-    if isinstance(custom_tooltips, str):
-        custom_tooltips = [custom_tooltips]
-
-    # PART 2: HANDLE TOOLTIP LOGIC
-    if not show_tooltips:
-        tooltips = "none"  # for letsplot, this removes the tooltips
-    else:
-        if isinstance(custom_tooltips, Sequence):
-            tooltips = list(custom_tooltips)
-        elif isinstance(add_tooltips, Sequence):
-            tooltips = list(base_tooltips) + list(add_tooltips)
-        else:
-            tooltips = list(base_tooltips)
-
-    return tooltips
-
-
-def _build_tooltips(
-    *,
-    tooltips: list[str] | str,
-    cluster_name: str,
-    key: str | None = None,
-    title: str | None = None,
-    clustering: bool = False,
-) -> FeatureSpec | Literal["none"]:
-    """Crete the tooltips for the plot."""
-    if tooltips == "none":
-        return "none"
-
-    tooltips_object = layer_tooltips()
-    for tooltip in tooltips:
-        if clustering:
-            if tooltip != key:
-                tooltips_object.line(f"{tooltip}|@{tooltip}")
-            else:
-                tooltips_object.line(f"{cluster_name}|@{key}")
-        else:
-            tooltips_object.line(f"{tooltip}|@{tooltip}")
-    if title is not None:
-        tooltips_object.title(title)
-
-    return tooltips_object
-
-
-def _range_inclusive(start: float, stop: float, step: int) -> list[float]:
-    """Return a list of rounded numbers between start and stop, inclusive."""
-    decimals = 0
-    if stop - start < 1:
-        if stop - start == 0:
-            return [start]
-        decimals = -round(log10(stop - start)) + 1
-
-    diff = round(stop - start, decimals)
-    increment = round(diff / (step - 1), decimals + 1)
-    inc_list = []
-
-    for i in range(step):
-        inc_list.append(round(start + increment * i, decimals + 2))
-    # make unique
-    inc_list = list(set(inc_list))
-    return sorted(inc_list)
-
-
-def _color_gradient(
-    series,
-    color_low=None,
-    color_mid=None,
-    color_high=None,
-    mid_point: Literal["mean", "median", "mid"] | float = "median",
-) -> FeatureSpec:
-    """
-    Create a gradient color feature.
-
-    Parameters
-    ----------
-    series : polars.Series
-        Series to find the mid point of.
-    color_low : str
-        The color to use for the low end of the color gradient.
-    color_mid : str
-       The color to use for the mid part of the color gradient.
-    color_high : str
-        The color to use for the high end of the color gradient.
-    mid_point : float, default='median'
-        The midpoint (in data value) of the color gradient.
-        Can be 'mean', 'median' and 'mid' or a number (float or int).
-        If 'mean', the midpoint is the mean of the data.
-        If 'median', the midpoint is the median of the data.
-        If 'mid', the midpoint is the mean of 'min' and 'max' of the data.
-
-    Returns
-    -------
-    FeatureSpec
-        FeatureSpec object with the gradient color feature.
-    """
-    if color_mid is None:
-        return scale_color_continuous(low=color_low, high=color_high)
-    else:
-        if isinstance(mid_point, (float, int)):
-            mid_value = mid_point
-        elif mid_point == "mean":
-            mid_value = series.mean()
-        elif mid_point == "median":
-            mid_value = series.median()
-        elif mid_point == "mid":
-            mid_value = (series.max() + series.min()) / 2
-
-        return scale_color_gradient2(
-            low=color_low,
-            mid=color_mid,
-            high=color_high,
-            midpoint=mid_value,
-        )
-
-
-

-[docs]
-def get_mapping(plot: PlotSpec, *, index=0) -> dict:
-    """Returns the mapping of the plot."""
-    return {
-        **plot.as_dict().get("mapping"),  # from the global mapping,
-        **plot.as_dict().get("layers")[index].get("mapping"),  # from a layer.
-    }

-
-
-
-

-[docs]
-def retrieve(plot: PlotSpec | SupPlotsSpec, index: int = 0) -> pl.DataFrame:
-    """
-    Retrieves the dataframe from a PlotSpec or SupPlotsSpec using the index.
-
-    plot : PlotSpec | SupPlotsSpec
-        The plot to retrieve the dataframe from.
-    index : int, optional
-        The index of the figure to retrieve the dataframe from, by default 0
-
-    Returns
-    -------
-    pl.DataFrame
-        The dataframe utilized in the plot.
-
-    Raises
-    ------
-    TypeError
-        If the plot is not a PlotSpec or SupPlotsSpec object.
-    """
-    if isinstance(plot, PlotSpec):
-        frame = plot.as_dict().get("data")
-    elif isinstance(plot, SupPlotsSpec):
-        frame = plot.as_dict().get("figures")[index].get("data")
-    else:
-        msg = f"Plot MUST be a `PlotSpec` or `SupPlotsSpec` object, type={type(plot)}"
-        raise TypeError(msg)
-
-    if frame is None:
-        msg = "Could not retrieve the dataframe from the plot."
-        raise ValueError(msg)
-
-    return frame

-
-
-
-

-[docs]
-def slice(
-    grid: SupPlotsSpec, index: int | Sequence[int], **kwargs
-) -> PlotSpec | SupPlotsSpec | None:
-    """
-    Slice a ggrid (SupPlotsSpec) objects with given index.
-
-    Parameters
-    ----------
-    grid : SupPlotsSpec
-        The grid to slice.
-    index : int | Sequence[int]
-        The index or indices of the plots to slice.
-    **kwargs : dict[str, Any]
-        Additional arguments for the `gggrid` function.
-        see: https://lets-plot.org/python/pages/api/lets_plot.gggrid.html
-
-    Returns
-    -------
-    PlotSpec | SupPlotsSpec
-        The sliced grid.
-
-    Raises
-    ------
-    TypeError
-        If the grid is not a SupPlotsSpec object.
-        If the index is not an int or Sequence[int].
-    """
-    if isinstance(grid, SupPlotsSpec):
-        figures = grid.as_dict().get("figures")
-
-        if figures is not None:
-            if isinstance(index, int):
-                plot = figures[index]
-                return plot
-            elif isinstance(index, Sequence):
-                list_plots = [figures[i] for i in index]
-                return gggrid(list_plots, **kwargs)
-            else:
-                msg = f"Expected int or Sequence for index, but received {type(index)}"
-                raise TypeError(msg)
-    else:
-        msg = f"Expected `SupPlotsSpec`, but received {type(grid)}"
-        raise TypeError(msg)

-
-
-
-def _share_labels(plot, i: int, keys: Sequence[str], ncol: int | None) -> SupPlotsSpec:
-    if ncol is None:
-        ncol = len(keys)
-    total = len(keys)
-    nrow = ceil(total / ncol)
-    left_places = [i for i in range(total) if i % ncol == 0]
-    bottom_places = [i for i in range(total) if i >= ncol * (nrow - 1)]
-    if len(bottom_places) < ncol:
-        penultimate_row = list(range((nrow - 2) * ncol, (nrow - 1) * ncol))
-        bottom_places.extend(penultimate_row)
-    if i not in bottom_places:  # remove x axis title except for bottom row
-        plot = plot + theme(axis_title_x=element_blank())
-    if i not in left_places:  # remove y axis title except for left column
-        plot = plot + theme(axis_title_y=element_blank())
-
-    return plot
-
-
-def _share_axis(
-    plot, i: int, keys: Sequence[str], ncol: int | None, axis_type: Literal["axis", "arrow"]
-) -> SupPlotsSpec:
-    total = len(keys)
-    if ncol is None:
-        ncol = len(keys)
-    nrow = ceil(total / ncol)
-    left_places = [i for i in range(total) if i % ncol == 0]
-    bottom_places = [i for i in range(total) if i >= ncol * (nrow - 1)]
-    if len(bottom_places) < ncol:
-        penultimate_row = list(range((nrow - 2) * ncol, (nrow - 1) * ncol))
-        bottom_places.extend(penultimate_row)
-
-    if axis_type == "axis":
-        if i not in bottom_places:  # remove x axis title except for bottom row
-            plot = plot + theme(
-                # remove x axis elements
-                axis_text_x=element_blank(),
-                axis_ticks_x=element_blank(),
-                axis_line_x=element_blank(),
-            )
-        if i not in left_places:  # remove y axis title except for left column
-            plot = plot + theme(
-                # remove y axis elements
-                axis_text_y=element_blank(),
-                axis_ticks_y=element_blank(),
-                axis_line_y=element_blank(),
-            )
-    elif axis_type == "arrow":
-        pass
-    else:
-        msg = f"expected 'axis' or 'arrow' for 'axis_type' argument, but received {axis_type}"
-        raise ValueError(msg)
-
-    return plot
-
-
-def _share_ticks(plot, i: int, keys: Sequence[str], ncol: int | None) -> SupPlotsSpec:
-    if ncol is None:
-        ncol = len(keys)
-    total = len(keys)
-    nrow = ceil(total / ncol)
-    left_places = [i for i in range(total) if i % ncol == 0]
-    bottom_places = [i for i in range(total) if i >= ncol * (nrow - 1)]
-    if len(bottom_places) < ncol:
-        penultimate_row = list(range((nrow - 2) * ncol, (nrow - 1) * ncol))
-        bottom_places.extend(penultimate_row)
-    if i not in bottom_places:  # remove x axis title except for bottom row
-        plot = plot + theme(axis_text_x=element_blank())
-    if i not in left_places:  # remove y axis title except for left column
-        plot = plot + theme(axis_text_y=element_blank())
-
-    return plot
-
-
-'''
-def _key_style(data: AnnData, key: str) -> str:
-    """Find the layers with the given key."""
-    if key in data.obs.columns:
-        origin = "obs"
-    elif key in data.var_names:
-        origin = "obs"
-    elif key in data.var.columns:
-        origin = "var"
-'''
-
-
-def _wrap_legend(
-    frame: pl.DataFrame, fill: str | None, color: str | None, nrow: int = 5
-) -> FeatureSpec:
-    legend = guides()
-    # CASE1: LEGEND IS SEPARATED BY FILL
-    if fill is not None:
-        n_distinct = frame.select(fill).unique().height
-        if n_distinct > 10:
-            ncol = ceil(n_distinct / 10)
-            legend = guides(fill=guide_legend(ncol=ncol))
-    # CASE2: LEGEND IS SEPARATED BY COLOR
-    if color is not None:
-        n_distinct = frame.select(color).unique().height
-        if n_distinct > 10:
-            ncol = ceil(n_distinct / 10)
-            legend = guides(color=guide_legend(ncol=ncol))
-
-    return legend
-
-
-def _is_variable_key(data: AnnData, key: str | None) -> bool:
-    if key is None:
-        return False
-
-    if isinstance(data, AnnData):
-        if key in data.var_names:
-            result = True
-        else:
-            result = False
-    else:
-        msg = f"Unknown data type: {type(data)}."
-        raise TypeError(msg)
-
-    return result
-
-
-def _are_variables(data: AnnData, keys: Sequence[str] | None) -> bool:
-    if keys is None:
-        return False
-
-    if isinstance(data, AnnData):
-        result = all(key in data.var_names for key in keys)
-    else:
-        msg = f"Unknown data type: {type(data)}."
-        raise TypeError(msg)
-
-    return result
-
-
-def _is_observation_key(data: AnnData, key: str | None) -> bool:
-    if key is None:
-        return False
-
-    if isinstance(data, AnnData):
-        if key in data.obs.columns:
-            result = True
-        else:
-            result = False
-    else:
-        msg = f"Unknown data type: {type(data)}."
-        raise TypeError(msg)
-
-    return result
-
-
-def _are_observations(data: AnnData, keys: Sequence[str] | None) -> bool:
-    if keys is None:
-        return False
-
-    if isinstance(data, AnnData):
-        result = all(key in data.obs.columns for key in keys)
-    else:
-        msg = f"Unknown data type: {type(data)}."
-        raise TypeError(msg)
-
-    return result
-
-
-def _select_variable_keys(
-    data: AnnData,
-    keys: Sequence[str] | None,
-) -> list[str]:
-    """From given keys, select only those that are variable keys."""
-    if keys is None:
-        return []
-
-    if isinstance(data, AnnData):
-        variable_keys = [key for key in keys if key in data.var_names]
-    else:
-        msg = f"Unknown data type: {type(data)}."
-        raise TypeError(msg)
-    return variable_keys
-
-
-def _is_observation_feature(data: AnnData, key: str | None) -> bool:
-    """Check whether the key is in observations axis (axis=0)."""
-    if key is None:
-        return False
-
-    if isinstance(data, AnnData):
-        if key in data.obs.columns or key in data.var_names:
-            result = True
-        else:
-            result = False
-    else:
-        msg = f"Unknown data type: {type(data)}."
-        raise TypeError(msg)
-
-    return result
-
-
-def _are_observation_features(data: AnnData, keys: Sequence[str] | None) -> bool:
-    """Check whether all the keys are in observations axis (axis=0)."""
-    if keys is None:
-        return False
-
-    if isinstance(data, AnnData):
-        result = all((key in data.obs.columns or key in data.var_names) for key in keys)
-    else:
-        msg = f"Unknown data type: {type(data)}."
-        raise TypeError(msg)
-
-    return result
-
-
-def _is_variable_feature(data: AnnData, key: str | None) -> bool:
-    """Check whether the key is in variable axis (axis=1)."""
-    if key is None:
-        return False
-
-    if isinstance(data, AnnData):
-        if key in data.var.columns:
-            result = True
-        else:
-            result = False
-    else:
-        msg = f"Unknown data type: {type(data)}."
-        raise TypeError(msg)
-
-    return result
-
-
-def _are_variable_features(data: AnnData, keys: Sequence[str] | None) -> bool:
-    """Check whether all the keys are in variable axis (axis=1)."""
-    if keys is None:
-        return False
-
-    if isinstance(data, AnnData):
-        result = all(key in data.var.columns for key in keys)
-    else:
-        msg = f"Unknown data type: {type(data)}."
-        raise TypeError(msg)
-
-    return result
-
-
-def _determine_axis(
-    data: AnnData,
-    keys: str | Sequence[str],
-) -> Literal[0, 1]:
-    """Determine the axis based on the given key or keys."""
-    if isinstance(keys, str):
-        keys = [keys]
-    if isinstance(data, AnnData):
-        if _are_variable_features(data, keys):
-            axis = 1
-        elif _are_observation_features(data, keys):
-            axis = 0
-        else:
-            msg = f"Could not determine the axis with given keys ({keys})."
-            raise ValueError(msg)
-    else:
-        msg = f"Unknown data type: {type(data)}."
-        raise TypeError(msg)
-
-    return axis
-
- -
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- - © Copyright 2026, datavil. -
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- Created using Sphinx 9.1.0. -
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- - Built with the PyData Sphinx Theme 0.16.1. -

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All modules for which code is available

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- - © Copyright 2026, datavil. -
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-
- -
- - -
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- Created using Sphinx 9.1.0. -
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-
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- - -
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-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
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- -
- - \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.basic.heatmap.heatmap.rst.txt b/docs/_build/_sources/generated/cellestial.single.basic.heatmap.heatmap.rst.txt deleted file mode 100644 index f703d75..0000000 --- a/docs/_build/_sources/generated/cellestial.single.basic.heatmap.heatmap.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.basic.heatmap.heatmap -======================================= - -.. currentmodule:: cellestial.single.basic.heatmap - -.. autofunction:: heatmap \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.basic.scatter.scatter.rst.txt b/docs/_build/_sources/generated/cellestial.single.basic.scatter.scatter.rst.txt deleted file mode 100644 index e17b011..0000000 --- a/docs/_build/_sources/generated/cellestial.single.basic.scatter.scatter.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.basic.scatter.scatter -======================================= - -.. currentmodule:: cellestial.single.basic.scatter - -.. autofunction:: scatter \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.common.xyplot.xyplot.rst.txt b/docs/_build/_sources/generated/cellestial.single.common.xyplot.xyplot.rst.txt deleted file mode 100644 index bcc077c..0000000 --- a/docs/_build/_sources/generated/cellestial.single.common.xyplot.xyplot.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.common.xyplot.xyplot -====================================== - -.. currentmodule:: cellestial.single.common.xyplot - -.. autofunction:: xyplot \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.common.xyplots.xyplots.rst.txt b/docs/_build/_sources/generated/cellestial.single.common.xyplots.xyplots.rst.txt deleted file mode 100644 index 6bff72d..0000000 --- a/docs/_build/_sources/generated/cellestial.single.common.xyplots.xyplots.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.common.xyplots.xyplots -======================================== - -.. currentmodule:: cellestial.single.common.xyplots - -.. autofunction:: xyplots \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.dimensional.dimensional.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.dimensional.dimensional.rst.txt deleted file mode 100644 index 4fb9f1f..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.dimensional.dimensional.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.dimensional.dimensional -============================================== - -.. currentmodule:: cellestial.single.core.dimensional - -.. autofunction:: dimensional \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.distribution.boxplot.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.distribution.boxplot.rst.txt deleted file mode 100644 index ffca415..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.distribution.boxplot.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.distribution.boxplot -=========================================== - -.. currentmodule:: cellestial.single.core.distribution - -.. autofunction:: boxplot \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.distribution.violin.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.distribution.violin.rst.txt deleted file mode 100644 index 5d350f8..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.distribution.violin.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.distribution.violin -========================================== - -.. currentmodule:: cellestial.single.core.distribution - -.. autofunction:: violin \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.distributions.boxplots.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.distributions.boxplots.rst.txt deleted file mode 100644 index 028a10c..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.distributions.boxplots.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.distributions.boxplots -============================================= - -.. currentmodule:: cellestial.single.core.distributions - -.. autofunction:: boxplots \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.distributions.violins.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.distributions.violins.rst.txt deleted file mode 100644 index e7b065b..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.distributions.violins.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.distributions.violins -============================================ - -.. currentmodule:: cellestial.single.core.distributions - -.. autofunction:: violins \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.subdimensional.expression.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.subdimensional.expression.rst.txt deleted file mode 100644 index 82a2e56..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.subdimensional.expression.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.subdimensional.expression -================================================ - -.. currentmodule:: cellestial.single.core.subdimensional - -.. autofunction:: expression \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.subdimensional.pca.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.subdimensional.pca.rst.txt deleted file mode 100644 index 87886f0..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.subdimensional.pca.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.subdimensional.pca -========================================= - -.. currentmodule:: cellestial.single.core.subdimensional - -.. autofunction:: pca \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.subdimensional.tsne.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.subdimensional.tsne.rst.txt deleted file mode 100644 index a6772d8..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.subdimensional.tsne.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.subdimensional.tsne -========================================== - -.. currentmodule:: cellestial.single.core.subdimensional - -.. autofunction:: tsne \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.subdimensional.umap.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.subdimensional.umap.rst.txt deleted file mode 100644 index 13db6f5..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.subdimensional.umap.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.subdimensional.umap -========================================== - -.. currentmodule:: cellestial.single.core.subdimensional - -.. autofunction:: umap \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.dimensionals.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.dimensionals.rst.txt deleted file mode 100644 index 6b4a7ea..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.dimensionals.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.subdimensionals.dimensionals -=================================================== - -.. currentmodule:: cellestial.single.core.subdimensionals - -.. autofunction:: dimensionals \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.expressions.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.expressions.rst.txt deleted file mode 100644 index 7f482ae..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.expressions.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.subdimensionals.expressions -================================================== - -.. currentmodule:: cellestial.single.core.subdimensionals - -.. autofunction:: expressions \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.pcas.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.pcas.rst.txt deleted file mode 100644 index 5397440..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.pcas.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.subdimensionals.pcas -=========================================== - -.. currentmodule:: cellestial.single.core.subdimensionals - -.. autofunction:: pcas \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.tsnes.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.tsnes.rst.txt deleted file mode 100644 index aee9406..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.tsnes.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.subdimensionals.tsnes -============================================ - -.. currentmodule:: cellestial.single.core.subdimensionals - -.. autofunction:: tsnes \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.umaps.rst.txt b/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.umaps.rst.txt deleted file mode 100644 index c63d872..0000000 --- a/docs/_build/_sources/generated/cellestial.single.core.subdimensionals.umaps.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.core.subdimensionals.umaps -============================================ - -.. currentmodule:: cellestial.single.core.subdimensionals - -.. autofunction:: umaps \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.single.special.dotplot.dotplot.rst.txt b/docs/_build/_sources/generated/cellestial.single.special.dotplot.dotplot.rst.txt deleted file mode 100644 index 9b274df..0000000 --- a/docs/_build/_sources/generated/cellestial.single.special.dotplot.dotplot.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.single.special.dotplot.dotplot -========================================= - -.. currentmodule:: cellestial.single.special.dotplot - -.. autofunction:: dotplot \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.util.colors.show_colors.rst.txt b/docs/_build/_sources/generated/cellestial.util.colors.show_colors.rst.txt deleted file mode 100644 index 8fe86bd..0000000 --- a/docs/_build/_sources/generated/cellestial.util.colors.show_colors.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.util.colors.show\_colors -=================================== - -.. currentmodule:: cellestial.util.colors - -.. autofunction:: show_colors \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.util.get_mapping.rst.txt b/docs/_build/_sources/generated/cellestial.util.get_mapping.rst.txt deleted file mode 100644 index a0d37cd..0000000 --- a/docs/_build/_sources/generated/cellestial.util.get_mapping.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.util.get\_mapping -============================ - -.. currentmodule:: cellestial.util - -.. autofunction:: get_mapping \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.util.utilities.get_mapping.rst.txt b/docs/_build/_sources/generated/cellestial.util.utilities.get_mapping.rst.txt deleted file mode 100644 index c02bc5e..0000000 --- a/docs/_build/_sources/generated/cellestial.util.utilities.get_mapping.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.util.utilities.get\_mapping -====================================== - -.. currentmodule:: cellestial.util.utilities - -.. autofunction:: get_mapping \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.util.utilities.retrieve.rst.txt b/docs/_build/_sources/generated/cellestial.util.utilities.retrieve.rst.txt deleted file mode 100644 index 7616294..0000000 --- a/docs/_build/_sources/generated/cellestial.util.utilities.retrieve.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.util.utilities.retrieve -================================== - -.. currentmodule:: cellestial.util.utilities - -.. autofunction:: retrieve \ No newline at end of file diff --git a/docs/_build/_sources/generated/cellestial.util.utilities.slice.rst.txt b/docs/_build/_sources/generated/cellestial.util.utilities.slice.rst.txt deleted file mode 100644 index 37d2d1f..0000000 --- a/docs/_build/_sources/generated/cellestial.util.utilities.slice.rst.txt +++ /dev/null @@ -1,6 +0,0 @@ -cellestial.util.utilities.slice -=============================== - -.. currentmodule:: cellestial.util.utilities - -.. autofunction:: slice \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.basic.heatmap.heatmap.html b/docs/_build/generated/cellestial.single.basic.heatmap.heatmap.html deleted file mode 100644 index ec7c0e7..0000000 --- a/docs/_build/generated/cellestial.single.basic.heatmap.heatmap.html +++ /dev/null @@ -1,494 +0,0 @@ - - - - - - - - - - - cellestial.single.basic.heatmap.heatmap - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.basic.heatmap.heatmap#

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-heatmap(data: AnnData, mapping: FeatureSpec | None = None, *, axis: Literal[0, 1] | None = None, variable_keys: Sequence[str] | None = None, observations_name: str = 'Barcode', variables_name: str = 'Variable', include_dimensions: bool | int = False, interactive: bool = False, **geom_kwargs) → PlotSpec[source]#
-

Heatmap.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • mapping (FeatureSpec | None, default None) – Aesthetic mappings for the plot, the result of aes().

    • -

  • axis (Literal[0,1] | None, default None) – axis of the data, 0 for observations and 1 for variables.

    • -

  • variable_keys (str | Sequence[str] | None, default None) – Variable keys to add to the DataFrame. If None, no additional keys are added.

    • -

  • observations_name (str, default 'Barcode') – The name of the observations column.

    • -

  • variables_name (str, default 'Variable') – Name for the variables index column.

    • -

  • include_dimensions (bool | int, default False) – Whether to include dimensions in the DataFrame. -Providing an integer will limit the number of dimensions to given number.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • **geom_kwargs – Additional parameters for the geom_bar layer. -For more information on geom_bar parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_bar.html

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Returns:
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PlotSpec – Heatmap.

-
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- - © Copyright 2026, datavil. -
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-
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- Created using Sphinx 9.1.0. -
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- - Built with the PyData Sphinx Theme 0.16.1. -

- -
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- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.basic.scatter.scatter.html b/docs/_build/generated/cellestial.single.basic.scatter.scatter.html deleted file mode 100644 index e43f9c4..0000000 --- a/docs/_build/generated/cellestial.single.basic.scatter.scatter.html +++ /dev/null @@ -1,495 +0,0 @@ - - - - - - - - - - - cellestial.single.basic.scatter.scatter - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.basic.scatter.scatter#

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-

Scatter Plot.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • mapping (FeatureSpec | None, default None) – Aesthetic mappings for the plot, the result of aes().

    • -

  • axis (Literal[0,1] | None, default None) – axis of the data, 0 for observations and 1 for variables.

    • -

  • variable_keys (str | Sequence[str] | None, default None) – Variable keys to add to the DataFrame. If None, no additional keys are added.

    • -

  • axis – The axis to build the frame for. 0 for observations, 1 for variables.

    • -

  • observations_name (str, default 'Barcode') – The name of the observations column.

    • -

  • variables_name (str, default 'Variable') – Name for the variables index column.

    • -

  • include_dimensions (bool | int, default False) – Whether to include dimensions in the DataFrame. -Providing an integer will limit the number of dimensions to given number.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • **geom_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

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Returns:
-

PlotSpec – Scatter plot.

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- - © Copyright 2026, datavil. -
- -

-
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- Created using Sphinx 9.1.0. -
-

-
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- - Built with the PyData Sphinx Theme 0.16.1. -

- -
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- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.common.xyplot.xyplot.html b/docs/_build/generated/cellestial.single.common.xyplot.xyplot.html deleted file mode 100644 index 16647f5..0000000 --- a/docs/_build/generated/cellestial.single.common.xyplot.xyplot.html +++ /dev/null @@ -1,498 +0,0 @@ - - - - - - - - - - - cellestial.single.common.xyplot.xyplot - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.common.xyplot.xyplot#

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-xyplot(data: AnnData, x: str, y: str, *, mapping: FeatureSpec | None = None, axis: Literal[0, 1] | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, observations_name: str = 'Barcode', variables_name: str = 'Variable', include_dimensions: bool | int = False, **point_kwargs) → PlotSpec[source]#
-

Scatter Plot.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • x (str) – The key for the x-axis.

    • -

  • y (str) – The key for the y-axis.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • axis (Literal[0,1] | None, default None) – axis of the data, 0 for observations and 1 for variables.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • variables_name (str, default 'Variable') – The name to give to variable index column in the dataframe.

    • -

  • include_dimensions (bool | int, default False) – Whether to include dimensions in the DataFrame. -Providing an integer will limit the number of dimensions to given number.

    • -

  • **point_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -
-
-
Returns:
-

PlotSpec – Scatter plot.

-
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- - -
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- - - - - -
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- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
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- Created using Sphinx 9.1.0. -
-

-
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- - -
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- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
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- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.common.xyplots.xyplots.html b/docs/_build/generated/cellestial.single.common.xyplots.xyplots.html deleted file mode 100644 index fb580dd..0000000 --- a/docs/_build/generated/cellestial.single.common.xyplots.xyplots.html +++ /dev/null @@ -1,534 +0,0 @@ - - - - - - - - - - - cellestial.single.common.xyplots.xyplots - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.common.xyplots.xyplots#

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-xyplots(data: AnnData, x: str | Sequence[str], y: str | Sequence[str], *, mapping: FeatureSpec | None = None, axis: Literal[0, 1] | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, observations_name: str = 'Barcode', variables_name: str = 'Variable', include_dimensions: bool | int = False, layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None, ncol: int | None = None, sharex: str | None = None, sharey: str | None = None, widths: list[float] | None = None, heights: list[float] | None = None, hspace: float | None = None, vspace: float | None = None, fit: bool | None = None, align: bool | None = None, guides: str = 'auto', **point_kwargs) → SupPlotsSpec[source]#
-

Scatter Plots.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • x (str) – The key(s) for the x-axis.

    • -

  • y (str) – The key(s) for the y-axis.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • axis (Literal[0,1] | None, default None) – axis of the data, 0 for observations and 1 for variables.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • variables_name (str, default 'Variable') – The name to give to variable index column in the dataframe.

    • -

  • include_dimensions (bool | int, default False) – Whether to include dimensions in the DataFrame. -Providing an integer will limit the number of dimensions to given number.

    • -

  • layers (Sequence[FeatureSpec|LayerSpec] | FeatureSpec | LayerSpec | None, default None) – Layers to add to all the plots in the grid.

    • -

  • ncol (int, default None) – Number of columns in grid. If not specified, shows plots horizontally, in one row.

    • -

  • sharex (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • sharey (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • widths (list[float], default None) – Relative width of each column of grid, left to right.

    • -

  • heights (list[float], default None) – Relative height of each row of grid, top-down.

    • -

  • hspace (float | None = None) – Cell horizontal spacing in px.

    • -

  • vspace (float | None = None) – Cell vertical spacing in px.

    • -

  • fit (bool, default True) – Whether to stretch each plot to match the aspect ratio of its cell (fit=True), -or to preserve the original aspect ratio of plots (fit=False).

    • -

  • align (bool, default False) – If True, align inner areas (i.e. “geom” bounds) of plots. -However, cells containing other (sub)grids are not participating -in the plot “inner areas” layouting.

    • -

  • guides (str, default 'auto') –

    -
    Specifies how guides (legends and colorbars) should be treated in the layout.
      -

    • ’collect’ collect guides from all subplots, removing duplicates.

      • -

    • ’keep’ keep guides in their original subplots; do not collect at this level.

      • -

    • ’auto’ allow guides to be collected if an upper-level layout uses guides=’collect’;

      • -
    -
    -
    -

    otherwise, keep them in subplots. -Duplicates are identified by comparing visual properties: -For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.). -For colorbars: title, domain limits, breaks, and color gradient.

    -

    For more information on gggrid parameters: -https://lets-plot.org/python/pages/api/lets_plot.gggrid.html

    -

    • -

  • **point_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -
-
-
Returns:
-

PlotSpec – Scatter plot.

-
-
-
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- - -
-
- On this page -
-
- -
- - -
-
- -
- -
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- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.core.dimensional.dimensional.html b/docs/_build/generated/cellestial.single.core.dimensional.dimensional.html deleted file mode 100644 index 63177e6..0000000 --- a/docs/_build/generated/cellestial.single.core.dimensional.dimensional.html +++ /dev/null @@ -1,575 +0,0 @@ - - - - - - - - - - - cellestial.single.core.dimensional.dimensional - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
- - - - - - -
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cellestial.single.core.dimensional.dimensional#

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-dimensional(data: AnnData, key: str | None = None, *, mapping: FeatureSpec | None = None, dimensions: Literal['umap', 'pca', 'tsne'] = 'umap', use_key: str | None = None, xy: tuple[int, int] | Sequence[int] = (1, 2), size: float = 0.8, variable_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, observations_name: str = 'Barcode', color_low: str = '#e6e6e6', color_mid: str | None = None, color_high: str = '#377eb8', mid_point: Literal['mean', 'median', 'mid'] | float = 'median', axis_type: Literal['axis', 'arrow'] | None = None, arrow_length: float = 0.25, arrow_size: float = 1, arrow_color: str = '#3f3f3f', arrow_angle: float = 10, legend_ondata: bool = False, ondata_size: float = 12, ondata_color: str = '#3f3f3f', ondata_fontface: str = 'bold', ondata_family: str = 'sans', ondata_alpha: float = 1, ondata_weighted: bool = True, **point_kwargs) → PlotSpec[source]#
-

Dimensionality reduction plot.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • key (str, default None) – The key (cell feature) to color the points by. -e.g., ‘leiden’ or ‘louvain’ to color by clusters or gene name for expression.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • dimensions (Literal[``’umap’, ``'pca', 'tsne'], default 'umap') – The dimensional reduction method to use. -e.g., ‘umap’ or ‘pca’ or ‘tsne’.

    • -

  • xy (tuple[int, int] | Sequence[int], default (1, 2)) – The x and y axes to use for the plot. -e.g., (1, 2) for UMAP1 and UMAP2.

    • -

  • use_key (str, default None) – The specific key to use for the desired dimensions. -e.g., ‘X_umap_2d’ or ‘X_pca_2d’. -Otherwise, the function will decide on the key based on the dimensions.

    • -

  • size (float, default 0.8) – The size of the points.

    • -

  • variable_keys (str | Sequence[str] | None, default None) – Variable keys to add to the DataFrame. If None, no additional keys are added.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • color_low (str, default '#e6e6e6') –

    The color to use for the low end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_mid (str, default None) –

    The color to use for the middle part of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_high (str, default '#377EB8') –

    The color to use for the high end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • mid_point (Literal[``’mean’, ``'median', 'mid'] | float, default 'median') – The midpoint (in data value) of the color gradient. -Can be ‘mean’, ‘median’ and ‘mid’ or a number (float or int). -- If ‘mean’, the midpoint is the mean of the data. -- If ‘median’, the midpoint is the median of the data. -- If ‘mid’, the midpoint is the mean of ‘min’ and ‘max’ of the data.

    • -

  • axis_type (Literal[``’axis’, ``'arrow'] | None) – Whether to use regular axis or arrows as the axis.

    • -

  • arrow_length (float, default 0.25) – Length of the arrow head (px).

    • -

  • arrow_size (float, default 1) – Size of the arrow.

    • -

  • arrow_color (str, default '#3f3f3f') –

    Color of the arrows. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • arrow_angle (float, default 10) – Angle of the arrow head in degrees.

    • -

  • legend_ondata (bool, default False) – whether to show legend on data

    • -

  • ondata_size (float, default 12) – size of the legend (text) on data.

    • -

  • ondata_color (str, default '#3f3f3f') – color of the legend (text) on data

    • -

  • ondata_fontface (str, default 'bold') – fontface of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-face

    • -

  • ondata_family (str, default 'sans') – family of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-family

    • -

  • ondata_alpha (float, default 1) – alpha (transparency) of the legend on data.

    • -

  • ondata_weighted (bool, default True) – whether to use weighted mean for the legend on data. -If True, the weighted mean of the group means is used. -If False, the arithmetic mean of the group means is used.

    • -

  • **point_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -
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Returns:
-

PlotSpec – Dimensional reduction plot.

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- On this page -
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- - © Copyright 2026, datavil. -
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-
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- Created using Sphinx 9.1.0. -
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- - Built with the PyData Sphinx Theme 0.16.1. -

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- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.core.distribution.boxplot.html b/docs/_build/generated/cellestial.single.core.distribution.boxplot.html deleted file mode 100644 index c71c47f..0000000 --- a/docs/_build/generated/cellestial.single.core.distribution.boxplot.html +++ /dev/null @@ -1,540 +0,0 @@ - - - - - - - - - - - cellestial.single.core.distribution.boxplot - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.core.distribution.boxplot#

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-boxplot(data: AnnData, key: str | Sequence[str], *, mapping: FeatureSpec | None = None, axis: Literal[0, 1] | None = None, color: str | None = None, fill: str | None = None, add_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, geom_fill: str | None = '#FF00FF', geom_color: str | None = '#2f2f2f', point_color: str = '#1f1f1f', point_alpha: float = 0.7, point_size: float = 0.5, point_geom: Literal['jitter', 'point', 'sina'] = 'jitter', observations_name: str = 'Barcode', variables_name: str = 'Variable', show_points: bool = True, interactive: bool = False, value_column: str = 'value', variable_column: str = 'variable', point_kwargs: dict[str, Any] | None = None, **geom_kwargs) → PlotSpec[source]#
-

Boxplot.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • key (str | Sequence[str]) – The key(s) to get the values (numerical). -e.g., ‘total_counts’ or a gene name.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • axis (Literal[0,1] | None, default None) – axis of the data, 0 for observations and 1 for variables.

    • -

  • color (str | None, default None) – Color aesthetic to split the boxplot (categorical). -e,g., ‘cell_type’ or ‘leiden’.

    • -

  • fill (str | None, default None) – Fill aesthetic to split the boxplot (categorical). -e,g., ‘cell_type’ or ‘leiden’.

    • -

  • add_keys (Sequence[str] | str | None, default None) – Additional keys to include in the dataframe.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • geom_fill (str | None, default '#FF00FF') –

    Fill color for all boxplots in the boxplot. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -

    • -

  • geom_color (str | None, default '#2f2f2f') –

    Border color for all boxplots in the boxplot. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -

    • -

  • point_color (str, default '#1f1f1f') –

    Color for the points in the boxplot. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -

    • -

  • point_alpha (float, default 0.7) – Alpha (transparency) for the points in the boxplot.

    • -

  • point_size (float, default 0.5) – Size for the points in the boxplot.

    • -

  • point_geom (Literal[``’jitter’:py:class:`,`’point’:py:class:`,`’sina’:py:class:`]`, *default* is ``'jitter',) – Geom type of the points, default is geom_jitter.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • variables_name (str, default 'Variable') – The name to give to variable index column in the dataframe.

    • -

  • show_points (bool, default True) – Whether to show points.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • variable_column (str, default 'variable') – The name of the variable column in the dataframe.

    • -

  • value_column (str, default 'value') – The name of the value column in the dataframe.

    • -

  • point_kwargs (dict[str, Any] | None, default None) – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -

  • **geom_kwargs – Additional parameters for the geom_boxplot layer. -For more information on geom_boxplot parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_boxplot.html

    • -
-
-
Returns:
-

PlotSpec – Boxplot.

-
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- - - - -
- - -
-
- On this page -
-
- -
- - -
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- -
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-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.core.distribution.violin.html b/docs/_build/generated/cellestial.single.core.distribution.violin.html deleted file mode 100644 index 298b0f2..0000000 --- a/docs/_build/generated/cellestial.single.core.distribution.violin.html +++ /dev/null @@ -1,540 +0,0 @@ - - - - - - - - - - - cellestial.single.core.distribution.violin - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.core.distribution.violin#

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-violin(data: AnnData, key: str | Sequence[str], *, mapping: FeatureSpec | None = None, axis: Literal[0, 1] | None = None, color: str | None = None, fill: str | None = None, add_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, geom_fill: str | None = '#FF00FF', geom_color: str | None = '#2f2f2f', point_color: str = '#1f1f1f', point_alpha: float = 0.7, point_size: float = 0.5, point_geom: Literal['jitter', 'point', 'sina'] = 'jitter', observations_name: str = 'Barcode', variables_name: str = 'Variable', show_points: bool = True, interactive: bool = False, value_column: str = 'value', variable_column: str = 'variable', point_kwargs: dict[str, Any] | None = None, **geom_kwargs) → PlotSpec[source]#
-

Violin Plot.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • key (str | Sequence[str]) – The key(s) to get the values (numerical). -e.g., ‘total_counts’ or a gene name.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • axis (Literal[0,1] | None, default None) – axis of the data, 0 for observations and 1 for variables.

    • -

  • color (str | None, default None) – Color aesthetic to split the violin plot (categorical). -e,g., ‘cell_type’ or ‘leiden’.

    • -

  • fill (str | None, default None) – Fill aesthetic to split the violin plot (categorical). -e,g., ‘cell_type’ or ‘leiden’.

    • -

  • add_keys (Sequence[str] | str | None, default None) – Additional keys to include in the dataframe.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • geom_fill (str | None, default '#FF00FF') –

    Fill color for all violins in the violin plot. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -

    • -

  • geom_color (str | None, default '#2f2f2f') –

    Border color for all violins in the violin plot. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -

    • -

  • point_color (str, default '#1f1f1f') –

    Color for the points in the violin plot. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -

    • -

  • point_alpha (float, default 0.7) – Alpha (transparency) for the points in the violin plot.

    • -

  • point_size (float, default 0.5) – Size for the points in the violin plot.

    • -

  • point_geom (Literal[``’jitter’:py:class:`,`’point’:py:class:`,`’sina’:py:class:`]`, *default* is ``'jitter',) – Geom type of the points, default is geom_jitter.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • variables_name (str, default 'Variable') – The name to give to variable index column in the dataframe.

    • -

  • show_points (bool, default True) – Whether to show points.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • variable_column (str, default 'variable') – The name of the variable column in the dataframe.

    • -

  • value_column (str, default 'value') – The name of the value column in the dataframe.

    • -

  • point_kwargs (dict[str, Any] | None, default None) – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -

  • **geom_kwargs – Additional parameters for the geom_violin layer. -For more information on geom_violin parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_violin.html

    • -
-
-
Returns:
-

PlotSpec – Violin plot.

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- - -
-
- On this page -
-
- -
- - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.core.distributions.boxplots.html b/docs/_build/generated/cellestial.single.core.distributions.boxplots.html deleted file mode 100644 index 387e879..0000000 --- a/docs/_build/generated/cellestial.single.core.distributions.boxplots.html +++ /dev/null @@ -1,580 +0,0 @@ - - - - - - - - - - - cellestial.single.core.distributions.boxplots - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.core.distributions.boxplots#

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-boxplots(data: AnnData, keys: Sequence[str], *, mapping: FeatureSpec | None = None, axis: Literal[0, 1] | None = None, color: str | None = None, fill: str | None = None, add_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, geom_fill: str = '#FF00FF', geom_color: str = '#2f2f2f', point_color: str = '#1f1f1f', point_alpha: float = 0.7, point_size: float = 0.5, point_geom: Literal['jitter', 'point', 'sina'] = 'jitter', observations_name: str = 'Barcode', variables_name: str = 'Variable', show_points: bool = True, interactive: bool = False, value_column: str = 'value', variable_column: str = 'variable', share_axis: bool = False, share_ticks: bool = False, layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None, ncol: int | None = None, sharex: str | None = None, sharey: str | None = None, widths: list | None = None, heights: list | None = None, hspace: float | None = None, vspace: float | None = None, fit: bool | None = None, align: bool | None = None, guides: str = 'auto', point_kwargs: dict[str, Any] | None = None, **geom_kwargs) → SupPlotsSpec[source]#
-

Boxplots.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • keys (list[str] | tuple[str] | Sequence[str]) – The keys to get the values (numerical). -e.g., [‘total_counts’, ‘pct_counts_in_top_50_genes’] or a list of gene names.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • axis (Literal[0,1] | None, default None) – axis of the data, 0 for observations and 1 for variables.

    • -

  • color (str | None, default None) – Color aesthetic to split the boxplot (categorical). -e,g., ‘cell_type’ or ‘leiden’.

    • -

  • fill (str | None, default None) – Fill aesthetic to split the boxplot (categorical). -e,g., ‘cell_type’ or ‘leiden’.

    • -

  • add_keys (Sequence[str] | str | None, default None) – Additional keys to include in the dataframe.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • geom_fill (str, default '#FF00FF') –

    Fill color for all boxplots in the boxplot. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -

    • -

  • geom_color (str, default '#2f2f2f') –

    Border color for all boxplots in the boxplot. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -

    • -

  • point_color (str, default '#1f1f1f') –

    Color for the points in the boxplot. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -

    • -

  • point_alpha (float, default 0.7) – Alpha (transparency) for the points in the boxplot.

    • -

  • point_size (float, default 0.5) – Size for the points in the boxplot.

    • -

  • point_geom (Literal[``’jitter’:py:class:`,`’point’:py:class:`,`’sina’:py:class:`]`, *default* is ``'jitter',) – Geom type of the points, default is geom_jitter.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • variables_name (str, default 'Gene') – The name to give to variable index column in the dataframe.

    • -

  • show_points (bool, default True) – Whether to show points.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • share_ticks (bool, default True) – Whether to share the labels across all plots. -If True, only X tick texts on bottom row and Y tick text on left column are shown.

    • -

  • share_axis (bool, default False) – Whether to share the axis across all plots. -If True, only X axis on bottom row and Y axis on left column is shown.

    • -

  • layers (Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None, default None) – Additional layers to add to the plot.

    • -

  • variable_column (str, default 'variable') – The name of the variable column in the dataframe.

    • -

  • value_column (str, default 'value') – The name of the value column in the dataframe.

    • -

  • ncol (int, default None) – Number of columns in grid. If not specified, shows plots horizontally, in one row.

    • -

  • sharex (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • sharey (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • widths (list[float], default None) – Relative width of each column of grid, left to right.

    • -

  • heights (list[float], default None) – Relative height of each row of grid, top-down.

    • -

  • hspace (float | None = None) – Cell horizontal spacing in px.

    • -

  • vspace (float | None = None) – Cell vertical spacing in px.

    • -

  • fit (bool, default True) – Whether to stretch each plot to match the aspect ratio of its cell (fit=True), -or to preserve the original aspect ratio of plots (fit=False).

    • -

  • align (bool, default False) – If True, align inner areas (i.e. “geom” bounds) of plots. -However, cells containing other (sub)grids are not participating -in the plot “inner areas” layouting.

    • -

  • guides (str, default 'auto') –

    -
    Specifies how guides (legends and colorbars) should be treated in the layout.
      -

    • ’collect’ collect guides from all subplots, removing duplicates.

      • -

    • ’keep’ keep guides in their original subplots; do not collect at this level.

      • -

    • ’auto’ allow guides to be collected if an upper-level layout uses guides=’collect’;

      • -
    -
    -
    -

    otherwise, keep them in subplots. -Duplicates are identified by comparing visual properties: -For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.). -For colorbars: title, domain limits, breaks, and color gradient.

    -

    For more information on gggrid parameters: -https://lets-plot.org/python/pages/api/lets_plot.gggrid.html

    -

    • -

  • point_kwargs (dict[str, Any] | None, default None) – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -

  • **geom_kwargs – Additional parameters for the geom_boxplot layer. -For more information on geom_boxplot parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_boxplot.html

    • -
-
-
Returns:
-

SupPlotsSpec – Boxplots.

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- - © Copyright 2026, datavil. -
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- Created using Sphinx 9.1.0. -
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- - Built with the PyData Sphinx Theme 0.16.1. -

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cellestial.single.core.distributions.violins#

-
-
-violins(data: AnnData, keys: Sequence[str], *, mapping: FeatureSpec | None = None, axis: Literal[0, 1] | None = None, color: str | None = None, fill: str | None = None, add_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, geom_fill: str = '#FF00FF', geom_color: str = '#2f2f2f', point_color: str = '#1f1f1f', point_alpha: float = 0.7, point_size: float = 0.5, point_geom: Literal['jitter', 'point', 'sina'] = 'jitter', observations_name: str = 'Barcode', variables_name: str = 'Variable', show_points: bool = True, interactive: bool = False, value_column: str = 'value', variable_column: str = 'variable', share_axis: bool = False, share_ticks: bool = False, layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None, ncol: int | None = None, sharex: str | None = None, sharey: str | None = None, widths: list | None = None, heights: list | None = None, hspace: float | None = None, vspace: float | None = None, fit: bool | None = None, align: bool | None = None, guides: str = 'auto', point_kwargs: dict[str, Any] | None = None, **geom_kwargs) → SupPlotsSpec[source]#
-

Violin Plots.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • keys (list[str] | tuple[str] | Sequence[str]) – The keys to get the values (numerical). -e.g., [‘total_counts’, ‘pct_counts_in_top_50_genes’] or a list of gene names.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • axis (Literal[0,1] | None, default None) – axis of the data, 0 for observations and 1 for variables.

    • -

  • color (str | None, default None) – Color aesthetic to split the violin plot (categorical). -e,g., ‘cell_type’ or ‘leiden’.

    • -

  • fill (str | None, default None) – Fill aesthetic to split the violin plot (categorical). -e,g., ‘cell_type’ or ‘leiden’.

    • -

  • add_keys (Sequence[str] | str | None, default None) – Additional keys to include in the dataframe.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • geom_fill (str, default '#FF00FF') –

    Fill color for all violins in the violin plot. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -

    • -

  • geom_color (str, default '#2f2f2f') –

    Border color for all violins in the violin plot. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -

    • -

  • point_color (str, default '#1f1f1f') –

    Color for the points in the violin plot. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -

    • -

  • point_alpha (float, default 0.7) – Alpha (transparency) for the points in the violin plot.

    • -

  • point_size (float, default 0.5) – Size for the points in the violin plot.

    • -

  • point_geom (Literal[``’jitter’:py:class:`,`’point’:py:class:`,`’sina’:py:class:`]`, *default* is ``'jitter',) – Geom type of the points, default is geom_jitter.

    • -

  • trim (bool, default False) – Whether to trim the violin plot.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • variables_name (str, default 'Gene') – The name to give to variable index column in the dataframe.

    • -

  • show_points (bool, default True) – Whether to show points.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • share_ticks (bool, default True) – Whether to share the labels across all plots. -If True, only X tick texts on bottom row and Y tick text on left column are shown.

    • -

  • share_axis (bool, default False) – Whether to share the axis across all plots. -If True, only X axis on bottom row and Y axis on left column is shown.

    • -

  • layers (Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None, default None) – Additional layers to add to the plot.

    • -

  • variable_column (str, default 'variable') – The name of the variable column in the dataframe.

    • -

  • value_column (str, default 'value') – The name of the value column in the dataframe.

    • -

  • ncol (int, default None) – Number of columns in grid. If not specified, shows plots horizontally, in one row.

    • -

  • sharex (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • sharey (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • widths (list[float], default None) – Relative width of each column of grid, left to right.

    • -

  • heights (list[float], default None) – Relative height of each row of grid, top-down.

    • -

  • hspace (float | None = None) – Cell horizontal spacing in px.

    • -

  • vspace (float | None = None) – Cell vertical spacing in px.

    • -

  • fit (bool, default True) – Whether to stretch each plot to match the aspect ratio of its cell (fit=True), -or to preserve the original aspect ratio of plots (fit=False).

    • -

  • align (bool, default False) – If True, align inner areas (i.e. “geom” bounds) of plots. -However, cells containing other (sub)grids are not participating -in the plot “inner areas” layouting.

    • -

  • guides (str, default 'auto') –

    -
    Specifies how guides (legends and colorbars) should be treated in the layout.
      -

    • ’collect’ collect guides from all subplots, removing duplicates.

      • -

    • ’keep’ keep guides in their original subplots; do not collect at this level.

      • -

    • ’auto’ allow guides to be collected if an upper-level layout uses guides=’collect’;

      • -
    -
    -
    -

    otherwise, keep them in subplots. -Duplicates are identified by comparing visual properties: -For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.). -For colorbars: title, domain limits, breaks, and color gradient.

    -

    For more information on gggrid parameters: -https://lets-plot.org/python/pages/api/lets_plot.gggrid.html

    -

    • -

  • point_kwargs (dict[str, Any] | None, default None) – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -

  • **geom_kwargs – Additional parameters for the geom_violin layer. -For more information on geom_violin parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_violin.html

    • -
-
-
Returns:
-

SupPlotsSpec – Violin Plots.

-
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- - - - - -
- - - - -
- - -
-
- On this page -
-
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- - -
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- -
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-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.core.subdimensional.expression.html b/docs/_build/generated/cellestial.single.core.subdimensional.expression.html deleted file mode 100644 index 5691c59..0000000 --- a/docs/_build/generated/cellestial.single.core.subdimensional.expression.html +++ /dev/null @@ -1,574 +0,0 @@ - - - - - - - - - - - cellestial.single.core.subdimensional.expression - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.core.subdimensional.expression#

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-
-expression(data: AnnData, key: str, *, mapping: FeatureSpec | None = None, dimensions: Literal['umap', 'pca', 'tsne'] = 'umap', use_key: str | None = None, xy: tuple[int, int] | Sequence[int] = (1, 2), size: float = 0.8, variable_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, observations_name: str = 'Barcode', color_low: str = '#e6e6e6', color_mid: str | None = None, color_high: str = '#377eb8', mid_point: Literal['mean', 'median', 'mid'] | float = 'median', axis_type: Literal['axis', 'arrow'] | None = 'arrow', arrow_length: float = 0.25, arrow_size: float = 1, arrow_color: str = '#3f3f3f', arrow_angle: float = 10, legend_ondata: bool = False, ondata_size: float = 12, ondata_color: str = '#3f3f3f', ondata_fontface: str = 'bold', ondata_family: str = 'sans', ondata_alpha: float = 1, ondata_weighted: bool = True, **point_kwargs) → PlotSpec[source]#
-

Dimensionality reduction plot of expression data.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • key (str) – The key (gene names) to color the points by.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • dimensions (Literal[``’umap’, ``'pca', 'tsne'], default 'umap') – The dimensional reduction method to use. -e.g., ‘umap’ or ‘pca’ or ‘tsne’.

    • -

  • use_key (str, default None) – The specific key to use for the desired dimensions. -e.g., ‘X_umap_2d’ or ‘X_pca_2d’. -Otherwise, the function will decide on the key based on the dimensions.

    • -

  • xy (tuple[int, int] | Sequence[int], default (1, 2)) – The x and y axes to use for the plot. -e.g., (1, 2) for UMAP1 and UMAP2.

    • -

  • size (float, default 0.8) – The size of the points.

    • -

  • variable_keys (str | Sequence[str] | None, default None) – Variable keys to add to the DataFrame. If None, no additional keys are added.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • color_low (str, default '#e6e6e6') –

    The color to use for the low end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_mid (str, default None) –

    The color to use for the middle part of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_high (str, default '#377EB8') –

    The color to use for the high end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • mid_point (Literal[``’mean’, ``'median', 'mid'] | float, default 'median') – The midpoint (in data value) of the color gradient. -Can be ‘mean’, ‘median’ and ‘mid’ or a number (float or int). -- If ‘mean’, the midpoint is the mean of the data. -- If ‘median’, the midpoint is the median of the data. -- If ‘mid’, the midpoint is the mean of ‘min’ and ‘max’ of the data.

    • -

  • axis_type (Literal[``’axis’, ``'arrow'] | None) – Whether to use regular axis or arrows as the axis.

    • -

  • arrow_length (float, default 0.25) – Length of the arrow head (px).

    • -

  • arrow_size (float, default 1) – Size of the arrow.

    • -

  • arrow_color (str, default '#3f3f3f') –

    Color of the arrows. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • arrow_angle (float, default 10) – Angle of the arrow head in degrees.

    • -

  • legend_ondata (bool, default False) – whether to show legend on data

    • -

  • ondata_size (float, default 12) – size of the legend (text) on data.

    • -

  • ondata_color (str, default '#3f3f3f') – color of the legend (text) on data

    • -

  • ondata_fontface (str, default 'bold') – fontface of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-face

    • -

  • ondata_family (str, default 'sans') – family of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-family

    • -

  • ondata_alpha (float, default 1) – alpha (transparency) of the legend on data.

    • -

  • ondata_weighted (bool, default True) – whether to use weighted mean for the legend on data. -If True, the weighted mean of the group means is used. -If False, the arithmetic mean of the group means is used.

    • -

  • **point_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -
-
-
Returns:
-

PlotSpec – Dimensional reduction plot.

-
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- - © Copyright 2026, datavil. -
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-
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- Created using Sphinx 9.1.0. -
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- - Built with the PyData Sphinx Theme 0.16.1. -

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- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.core.subdimensional.pca.html b/docs/_build/generated/cellestial.single.core.subdimensional.pca.html deleted file mode 100644 index 3ba844d..0000000 --- a/docs/_build/generated/cellestial.single.core.subdimensional.pca.html +++ /dev/null @@ -1,573 +0,0 @@ - - - - - - - - - - - cellestial.single.core.subdimensional.pca - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.core.subdimensional.pca#

-
-
-pca(data: AnnData, key: str | None = None, *, mapping: FeatureSpec | None = None, use_key: str | None = None, xy: tuple[int, int] | Sequence[int] = (1, 2), size: float = 0.8, variable_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, observations_name: str = 'Barcode', color_low: str = '#e6e6e6', color_mid: str | None = None, color_high: str = '#377eb8', mid_point: Literal['mean', 'median', 'mid'] | float = 'median', axis_type: Literal['axis', 'arrow'] | None = None, arrow_length: float = 0.25, arrow_size: float = 1, arrow_color: str = '#3f3f3f', arrow_angle: float = 10, legend_ondata: bool = False, ondata_size: float = 12, ondata_color: str = '#3f3f3f', ondata_fontface: str = 'bold', ondata_family: str = 'sans', ondata_alpha: float = 1, ondata_weighted: bool = True, **point_kwargs) → PlotSpec[source]#
-

PCA Dimensionality reduction plot.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • key (str, default None) – The key (cell feature) to color the points by. -e.g., ‘leiden’ or ‘louvain’ to color by clusters or gene name for expression.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • use_key (str, default None) – The specific key to use for the desired dimensions. -e.g., ‘X_umap_2d’ or ‘X_pca_2d’. -Otherwise, the function will decide on the key based on the dimensions.

    • -

  • xy (tuple[int, int] | Sequence[int], default (1, 2)) – The x and y axes to use for the plot. -e.g., (1, 2) for UMAP1 and UMAP2.

    • -

  • size (float, default 0.8) – The size of the points.

    • -

  • variable_keys (str | Sequence[str] | None, default None) – Variable keys to add to the DataFrame. If None, no additional keys are added.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • color_low (str, default '#e6e6e6') –

    The color to use for the low end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_mid (str, default None) –

    The color to use for the middle part of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_high (str, default '#377EB8') –

    The color to use for the high end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • mid_point (Literal[``’mean’, ``'median', 'mid'] | float, default 'median') – The midpoint (in data value) of the color gradient. -Can be ‘mean’, ‘median’ and ‘mid’ or a number (float or int). -- If ‘mean’, the midpoint is the mean of the data. -- If ‘median’, the midpoint is the median of the data. -- If ‘mid’, the midpoint is the mean of ‘min’ and ‘max’ of the data.

    • -

  • axis_type (Literal[``’axis’, ``'arrow'] | None) – Whether to use regular axis or arrows as the axis.

    • -

  • arrow_length (float, default 0.25) – Length of the arrow head (px).

    • -

  • arrow_size (float, default 1) – Size of the arrow.

    • -

  • arrow_color (str, default '#3f3f3f') –

    Color of the arrows. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • arrow_angle (float, default 10) – Angle of the arrow head in degrees.

    • -

  • legend_ondata (bool, default False) – whether to show legend on data

    • -

  • ondata_size (float, default 12) – size of the legend (text) on data.

    • -

  • ondata_color (str, default '#3f3f3f') – color of the legend (text) on data

    • -

  • ondata_fontface (str, default 'bold') – fontface of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-face

    • -

  • ondata_family (str, default 'sans') – family of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-family

    • -

  • ondata_alpha (float, default 1) – alpha (transparency) of the legend on data.

    • -

  • ondata_weighted (bool, default True) – whether to use weighted mean for the legend on data. -If True, the weighted mean of the group means is used. -If False, the arithmetic mean of the group means is used.

    • -

  • **point_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -
-
-
Returns:
-

PlotSpec – Dimensional reduction plot.

-
-
-
- -
- - -
- - - - - -
- - - - -
- - -
-
- On this page -
-
- -
- - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.core.subdimensional.tsne.html b/docs/_build/generated/cellestial.single.core.subdimensional.tsne.html deleted file mode 100644 index c6156de..0000000 --- a/docs/_build/generated/cellestial.single.core.subdimensional.tsne.html +++ /dev/null @@ -1,573 +0,0 @@ - - - - - - - - - - - cellestial.single.core.subdimensional.tsne - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.core.subdimensional.tsne#

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-
-tsne(data: AnnData, key: str | None = None, *, mapping: FeatureSpec | None = None, use_key: str | None = None, xy: tuple[int, int] | Sequence[int] = (1, 2), size: float = 0.8, variable_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, observations_name: str = 'Barcode', color_low: str = '#e6e6e6', color_mid: str | None = None, color_high: str = '#377eb8', mid_point: Literal['mean', 'median', 'mid'] | float = 'median', axis_type: Literal['axis', 'arrow'] | None = None, arrow_length: float = 0.25, arrow_size: float = 1, arrow_color: str = '#3f3f3f', arrow_angle: float = 10, legend_ondata: bool = False, ondata_size: float = 12, ondata_color: str = '#3f3f3f', ondata_fontface: str = 'bold', ondata_family: str = 'sans', ondata_alpha: float = 1, ondata_weighted: bool = True, **point_kwargs) → PlotSpec[source]#
-

tSNE Dimensionality reduction plot.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • key (str, default None) – The key (cell feature) to color the points by. -e.g., ‘leiden’ or ‘louvain’ to color by clusters or gene name for expression.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • use_key (str, default None) – The specific key to use for the desired dimensions. -e.g., ‘X_umap_2d’ or ‘X_pca_2d’. -Otherwise, the function will decide on the key based on the dimensions.

    • -

  • xy (tuple[int, int] | Sequence[int], default (1, 2)) – The x and y axes to use for the plot. -e.g., (1, 2) for UMAP1 and UMAP2.

    • -

  • size (float, default 0.8) – The size of the points.

    • -

  • variable_keys (str | Sequence[str] | None, default None) – Variable keys to add to the DataFrame. If None, no additional keys are added.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • color_low (str, default '#e6e6e6') –

    The color to use for the low end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_mid (str, default None) –

    The color to use for the middle part of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_high (str, default '#377EB8') –

    The color to use for the high end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • mid_point (Literal[``’mean’, ``'median', 'mid'] | float, default 'median') – The midpoint (in data value) of the color gradient. -Can be ‘mean’, ‘median’ and ‘mid’ or a number (float or int). -- If ‘mean’, the midpoint is the mean of the data. -- If ‘median’, the midpoint is the median of the data. -- If ‘mid’, the midpoint is the mean of ‘min’ and ‘max’ of the data.

    • -

  • axis_type (Literal[``’axis’, ``'arrow'] | None) – Whether to use regular axis or arrows as the axis.

    • -

  • arrow_length (float, default 0.25) – Length of the arrow head (px).

    • -

  • arrow_size (float, default 1) – Size of the arrow.

    • -

  • arrow_color (str, default '#3f3f3f') –

    Color of the arrows. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • arrow_angle (float, default 10) – Angle of the arrow head in degrees.

    • -

  • legend_ondata (bool, default False) – whether to show legend on data

    • -

  • ondata_size (float, default 12) – size of the legend (text) on data.

    • -

  • ondata_color (str, default '#3f3f3f') – color of the legend (text) on data

    • -

  • ondata_fontface (str, default 'bold') – fontface of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-face

    • -

  • ondata_family (str, default 'sans') – family of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-family

    • -

  • ondata_alpha (float, default 1) – alpha (transparency) of the legend on data.

    • -

  • ondata_weighted (bool, default True) – whether to use weighted mean for the legend on data. -If True, the weighted mean of the group means is used. -If False, the arithmetic mean of the group means is used.

    • -

  • **point_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -
-
-
Returns:
-

PlotSpec – Dimensional reduction plot.

-
-
-
- -
- - -
- - - - - -
- - - - -
- - -
-
- On this page -
-
- -
- - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.core.subdimensional.umap.html b/docs/_build/generated/cellestial.single.core.subdimensional.umap.html deleted file mode 100644 index 18b32bd..0000000 --- a/docs/_build/generated/cellestial.single.core.subdimensional.umap.html +++ /dev/null @@ -1,573 +0,0 @@ - - - - - - - - - - - cellestial.single.core.subdimensional.umap - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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- - - Ctrl+K -
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cellestial.single.core.subdimensional.umap#

-
-
-umap(data: AnnData, key: str | None = None, *, mapping: FeatureSpec | None = None, use_key: str | None = None, xy: tuple[int, int] | Sequence[int] = (1, 2), size: float = 0.8, variable_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, observations_name: str = 'Barcode', color_low: str = '#e6e6e6', color_mid: str | None = None, color_high: str = '#377eb8', mid_point: Literal['mean', 'median', 'mid'] | float = 'median', axis_type: Literal['axis', 'arrow'] | None = None, arrow_length: float = 0.25, arrow_size: float = 1, arrow_color: str = '#3f3f3f', arrow_angle: float = 10, legend_ondata: bool = False, ondata_size: float = 12, ondata_color: str = '#3f3f3f', ondata_fontface: str = 'bold', ondata_family: str = 'sans', ondata_alpha: float = 1, ondata_weighted: bool = True, **point_kwargs) → PlotSpec[source]#
-

UMAP Dimensionality reduction plot.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • key (str, default None) – The key (cell feature) to color the points by. -e.g., ‘leiden’ or ‘louvain’ to color by clusters or gene name for expression.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • use_key (str, default None) – The specific key to use for the desired dimensions. -e.g., ‘X_umap_2d’ or ‘X_pca_2d’. -Otherwise, the function will decide on the key based on the dimensions.

    • -

  • xy (tuple[int, int] | Sequence[int], default (1, 2)) – The x and y axes to use for the plot. -e.g., (1, 2) for UMAP1 and UMAP2.

    • -

  • size (float, default 0.8) – The size of the points.

    • -

  • variable_keys (str | Sequence[str] | None, default None) – Variable keys to add to the DataFrame. If None, no additional keys are added.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • color_low (str, default '#e6e6e6') –

    The color to use for the low end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_mid (str, default None) –

    The color to use for the middle part of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_high (str, default '#377EB8') –

    The color to use for the high end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • mid_point (Literal[``’mean’, ``'median', 'mid'] | float, default 'median') – The midpoint (in data value) of the color gradient. -Can be ‘mean’, ‘median’ and ‘mid’ or a number (float or int). -- If ‘mean’, the midpoint is the mean of the data. -- If ‘median’, the midpoint is the median of the data. -- If ‘mid’, the midpoint is the mean of ‘min’ and ‘max’ of the data.

    • -

  • axis_type (Literal[``’axis’, ``'arrow'] | None) – Whether to use regular axis or arrows as the axis.

    • -

  • arrow_length (float, default 0.25) – Length of the arrow head (px).

    • -

  • arrow_size (float, default 1) – Size of the arrow.

    • -

  • arrow_color (str, default '#3f3f3f') –

    Color of the arrows. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • arrow_angle (float, default 10) – Angle of the arrow head in degrees.

    • -

  • legend_ondata (bool, default False) – whether to show legend on data

    • -

  • ondata_size (float, default 12) – size of the legend (text) on data.

    • -

  • ondata_color (str, default '#3f3f3f') – color of the legend (text) on data

    • -

  • ondata_fontface (str, default 'bold') – fontface of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-face

    • -

  • ondata_family (str, default 'sans') – family of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-family

    • -

  • ondata_alpha (float, default 1) – alpha (transparency) of the legend on data.

    • -

  • ondata_weighted (bool, default True) – whether to use weighted mean for the legend on data. -If True, the weighted mean of the group means is used. -If False, the arithmetic mean of the group means is used.

    • -

  • **point_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -
-
-
Returns:
-

PlotSpec – Dimensional reduction plot.

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- - © Copyright 2026, datavil. -
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- Created using Sphinx 9.1.0. -
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-
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- - Built with the PyData Sphinx Theme 0.16.1. -

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cellestial.single.core.subdimensionals.dimensionals#

-
-
-dimensionals(data: AnnData, keys: Sequence[str], *, mapping: FeatureSpec | None = None, dimensions: Literal['umap', 'pca', 'tsne'] = 'umap', use_key: str | None = None, xy: tuple[int, int] | Sequence[int] = (1, 2), size: float = 0.8, variable_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, observations_name: str = 'Barcode', color_low: str = '#e6e6e6', color_mid: str | None = None, color_high: str = '#377eb8', mid_point: Literal['mean', 'median', 'mid'] | float = 'median', axis_type: Literal['axis', 'arrow'] | None = None, arrow_length: float = 0.25, arrow_size: float = 1, arrow_color: str = '#3f3f3f', arrow_angle: float = 10, legend_ondata: bool = False, ondata_size: float = 12, ondata_color: str = '#3f3f3f', ondata_fontface: str = 'bold', ondata_family: str = 'sans', ondata_alpha: float = 1, ondata_weighted: bool = True, share_labels: bool = True, share_axis: bool = False, layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None, ncol: int | None = None, sharex: str | None = None, sharey: str | None = None, widths: list[float] | None = None, heights: list[float] | None = None, hspace: float | None = None, vspace: float | None = None, fit: bool | None = None, align: bool | None = None, guides: str = 'auto', **point_kwargs) → SupPlotsSpec[source]#
-

Grid of dimensionality reduction plots.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • keys (list[str] | tuple[str] | Sequence[str]) – The keys (cell features) to color the points by. -e.g., ‘leiden’ or ‘louvain’ to color by clusters or gene name for expression.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • dimensions (Literal[``’umap’, ``'pca', 'tsne'], default 'umap') – The dimensional reduction method to use. -e.g., ‘umap’ or ‘pca’ or ‘tsne’.

    • -

  • xy (tuple[int, int] | Sequence[int], default (1, 2)) – The x and y axes to use for the plot. -e.g., (1, 2) for UMAP1 and UMAP2.

    • -

  • use_key (str, default None) – The specific key to use for the desired dimensions. -e.g., ‘X_umap_2d’ or ‘X_pca_2d’. -Otherwise, the function will decide on the key based on the dimensions.

    • -

  • size (float, default 0.8) – The size of the points.

    • -

  • variable_keys (str | Sequence[str] | None, default None) – Variable keys to add to the DataFrame. If None, no additional keys are added.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • cluster_name (str, default 'Cluster') – The name to overwrite the clustering key in the dataframe and the plot.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • color_low (str, default '#e6e6e6') –

    The color to use for the low end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_mid (str, default None) –

    The color to use for the middle part of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_high (str, default '#377EB8') –

    The color to use for the high end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • mid_point (Literal[``’mean’, ``'median', 'mid'] | float, default 'median') – The midpoint (in data value) of the color gradient. -Can be ‘mean’, ‘median’ and ‘mid’ or a number (float or int). -- If ‘mean’, the midpoint is the mean of the data. -- If ‘median’, the midpoint is the median of the data. -- If ‘mid’, the midpoint is the mean of ‘min’ and ‘max’ of the data.

    • -

  • axis_type (Literal[``’axis’, ``'arrow'] | None) – Whether to use regular axis or arrows as the axis.

    • -

  • arrow_length (float, default 0.25) – Length of the arrow head (px).

    • -

  • arrow_size (float, default 1) – Size of the arrow.

    • -

  • arrow_color (str, default '#3f3f3f') –

    Color of the arrows. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • arrow_angle (float, default 10) – Angle of the arrow head in degrees.

    • -

  • legend_ondata (bool, default False) – whether to show legend on data

    • -

  • ondata_size (float, default 12) – size of the legend (text) on data.

    • -

  • ondata_color (str, default '#3f3f3f') – color of the legend (text) on data

    • -

  • ondata_fontface (str, default 'bold') – fontface of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-face

    • -

  • ondata_family (str, default 'sans') – family of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-family

    • -

  • ondata_alpha (float, default 1) – alpha (transparency) of the legend on data.

    • -

  • ondata_weighted (bool, default True) – whether to use weighted mean for the legend on data. -If True, the weighted mean of the group means is used. -If False, the arithmetic mean of the group means is used.

    • -

  • share_labels (bool, default True) – Whether to share the labels across all plots. -If True, only X labels on bottom row and Y labels on left column are shown.

    • -

  • share_axis (bool, default False) – Whether to share the axis across all plots. -If True, only X axis on bottom row and Y axis on left column is shown.

    • -

  • layers (Sequence[FeatureSpec|LayerSpec] | FeatureSpec | LayerSpec | None, default None) – Layers to add to all the plots in the grid.

    • -

  • ncol (int, default None) – Number of columns in grid. If not specified, shows plots horizontally, in one row.

    • -

  • sharex (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • sharey (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • widths (list[float], default None) – Relative width of each column of grid, left to right.

    • -

  • heights (list[float], default None) – Relative height of each row of grid, top-down.

    • -

  • hspace (float | None = None) – Cell horizontal spacing in px.

    • -

  • vspace (float | None = None) – Cell vertical spacing in px.

    • -

  • fit (bool, default True) – Whether to stretch each plot to match the aspect ratio of its cell (fit=True), -or to preserve the original aspect ratio of plots (fit=False).

    • -

  • align (bool, default False) – If True, align inner areas (i.e. “geom” bounds) of plots. -However, cells containing other (sub)grids are not participating -in the plot “inner areas” layouting.

    • -

  • guides (str, default 'auto') –

    -
    Specifies how guides (legends and colorbars) should be treated in the layout.
      -

    • ’collect’ collect guides from all subplots, removing duplicates.

      • -

    • ’keep’ keep guides in their original subplots; do not collect at this level.

      • -

    • ’auto’ allow guides to be collected if an upper-level layout uses guides=’collect’;

      • -
    -
    -
    -

    otherwise, keep them in subplots. -Duplicates are identified by comparing visual properties: -For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.). -For colorbars: title, domain limits, breaks, and color gradient.

    -

    For more information on gggrid parameters: -https://lets-plot.org/python/pages/api/lets_plot.gggrid.html

    -

    • -

  • **point_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -
-
-
Returns:
-

SupPlotsSpec – Grid of dimensionality reduction plots.

-
-
-
- -
- - -
- - - - - -
- - - - -
- - -
-
- On this page -
-
- -
- - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.core.subdimensionals.expressions.html b/docs/_build/generated/cellestial.single.core.subdimensionals.expressions.html deleted file mode 100644 index c086c80..0000000 --- a/docs/_build/generated/cellestial.single.core.subdimensionals.expressions.html +++ /dev/null @@ -1,615 +0,0 @@ - - - - - - - - - - - cellestial.single.core.subdimensionals.expressions - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.core.subdimensionals.expressions#

-
-
-expressions(data: AnnData, keys: Sequence[str], *, mapping: FeatureSpec | None = None, dimensions: Literal['umap', 'pca', 'tsne'] = 'umap', use_key: str | None = None, xy: tuple[int, int] | Sequence[int] = (1, 2), size: float = 0.8, variable_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, observations_name: str = 'Barcode', color_low: str = '#e6e6e6', color_mid: str | None = None, color_high: str = '#377eb8', mid_point: Literal['mean', 'median', 'mid'] | float = 'median', axis_type: Literal['axis', 'arrow'] | None = None, arrow_length: float = 0.25, arrow_size: float = 1, arrow_color: str = '#3f3f3f', arrow_angle: float = 10, legend_ondata: bool = False, ondata_size: float = 12, ondata_color: str = '#3f3f3f', ondata_fontface: str = 'bold', ondata_family: str = 'sans', ondata_alpha: float = 1, ondata_weighted: bool = True, share_labels: bool = True, share_axis: bool = False, layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None, ncol: int | None = None, sharex: str | None = None, sharey: str | None = None, widths: list[float] | None = None, heights: list[float] | None = None, hspace: float | None = None, vspace: float | None = None, fit: bool | None = None, align: bool | None = None, guides: str = 'auto', **point_kwargs) → SupPlotsSpec[source]#
-

Grid of dimensionality reduction plots.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • keys (list[str] | tuple[str] | Sequence[str]) – The keys (gene names) to color the points by.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • dimensions (Literal[``’umap’, ``'pca', 'tsne'], default 'umap') – The dimensional reduction method to use. -e.g., ‘umap’ or ‘pca’ or ‘tsne’.

    • -

  • xy (tuple[int, int] | Sequence[int], default (1, 2)) – The x and y axes to use for the plot. -e.g., (1, 2) for UMAP1 and UMAP2.

    • -

  • use_key (str, default None) – The specific key to use for the desired dimensions. -e.g., ‘X_umap_2d’ or ‘X_pca_2d’. -Otherwise, the function will decide on the key based on the dimensions.

    • -

  • size (float, default 0.8) – The size of the points.

    • -

  • variable_keys (str | Sequence[str] | None, default None) – Variable keys to add to the DataFrame. If None, no additional keys are added.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • cluster_name (str, default 'Cluster') – The name to overwrite the clustering key in the dataframe and the plot.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • color_low (str, default '#e6e6e6') –

    The color to use for the low end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_mid (str, default None) –

    The color to use for the middle part of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_high (str, default '#377EB8') –

    The color to use for the high end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • mid_point (Literal[``’mean’, ``'median', 'mid'] | float, default 'median') – The midpoint (in data value) of the color gradient. -Can be ‘mean’, ‘median’ and ‘mid’ or a number (float or int). -- If ‘mean’, the midpoint is the mean of the data. -- If ‘median’, the midpoint is the median of the data. -- If ‘mid’, the midpoint is the mean of ‘min’ and ‘max’ of the data.

    • -

  • axis_type (Literal[``’axis’, ``'arrow'] | None) – Whether to use regular axis or arrows as the axis.

    • -

  • arrow_length (float, default 0.25) – Length of the arrow head (px).

    • -

  • arrow_size (float, default 1) – Size of the arrow.

    • -

  • arrow_color (str, default '#3f3f3f') –

    Color of the arrows. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • arrow_angle (float, default 10) – Angle of the arrow head in degrees.

    • -

  • legend_ondata (bool, default False) – whether to show legend on data

    • -

  • ondata_size (float, default 12) – size of the legend (text) on data.

    • -

  • ondata_color (str, default '#3f3f3f') – color of the legend (text) on data

    • -

  • ondata_fontface (str, default 'bold') – fontface of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-face

    • -

  • ondata_family (str, default 'sans') – family of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-family

    • -

  • ondata_alpha (float, default 1) – alpha (transparency) of the legend on data.

    • -

  • ondata_weighted (bool, default True) – whether to use weighted mean for the legend on data. -If True, the weighted mean of the group means is used. -If False, the arithmetic mean of the group means is used.

    • -

  • share_labels (bool, default True) – Whether to share the labels across all plots. -If True, only X labels on bottom row and Y labels on left column are shown.

    • -

  • share_axis (bool, default False) – Whether to share the axis across all plots. -If True, only X axis on bottom row and Y axis on left column is shown.

    • -

  • layers (Sequence[FeatureSpec|LayerSpec] | FeatureSpec | LayerSpec | None, default None) – Layers to add to all the plots in the grid.

    • -

  • ncol (int, default None) – Number of columns in grid. If not specified, shows plots horizontally, in one row.

    • -

  • sharex (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • sharey (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • widths (list[float], default None) – Relative width of each column of grid, left to right.

    • -

  • heights (list[float], default None) – Relative height of each row of grid, top-down.

    • -

  • hspace (float | None = None) – Cell horizontal spacing in px.

    • -

  • vspace (float | None = None) – Cell vertical spacing in px.

    • -

  • fit (bool, default True) – Whether to stretch each plot to match the aspect ratio of its cell (fit=True), -or to preserve the original aspect ratio of plots (fit=False).

    • -

  • align (bool, default False) – If True, align inner areas (i.e. “geom” bounds) of plots. -However, cells containing other (sub)grids are not participating -in the plot “inner areas” layouting.

    • -

  • guides (str, default 'auto') –

    -
    Specifies how guides (legends and colorbars) should be treated in the layout.
      -

    • ’collect’ collect guides from all subplots, removing duplicates.

      • -

    • ’keep’ keep guides in their original subplots; do not collect at this level.

      • -

    • ’auto’ allow guides to be collected if an upper-level layout uses guides=’collect’;

      • -
    -
    -
    -

    otherwise, keep them in subplots. -Duplicates are identified by comparing visual properties: -For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.). -For colorbars: title, domain limits, breaks, and color gradient.

    -

    For more information on gggrid parameters: -https://lets-plot.org/python/pages/api/lets_plot.gggrid.html

    -

    • -

  • **point_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -
-
-
Returns:
-

SupPlotsSpec – Grid of dimensionality reduction plots.

-
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- On this page -
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- - - - - -
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- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.core.subdimensionals.pcas.html b/docs/_build/generated/cellestial.single.core.subdimensionals.pcas.html deleted file mode 100644 index ed06445..0000000 --- a/docs/_build/generated/cellestial.single.core.subdimensionals.pcas.html +++ /dev/null @@ -1,614 +0,0 @@ - - - - - - - - - - - cellestial.single.core.subdimensionals.pcas - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.core.subdimensionals.pcas#

-
-
-pcas(data: AnnData, keys: Sequence[str], *, mapping: FeatureSpec | None = None, use_key: str | None = None, xy: tuple[int, int] | Sequence[int] = (1, 2), size: float = 0.8, variable_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, observations_name: str = 'Barcode', color_low: str = '#e6e6e6', color_mid: str | None = None, color_high: str = '#377eb8', mid_point: Literal['mean', 'median', 'mid'] | float = 'median', axis_type: Literal['axis', 'arrow'] | None = None, arrow_length: float = 0.25, arrow_size: float = 1, arrow_color: str = '#3f3f3f', arrow_angle: float = 10, legend_ondata: bool = False, ondata_size: float = 12, ondata_color: str = '#3f3f3f', ondata_fontface: str = 'bold', ondata_family: str = 'sans', ondata_alpha: float = 1, ondata_weighted: bool = True, share_labels: bool = True, share_axis: bool = False, layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None, ncol: int | None = None, sharex: str | None = None, sharey: str | None = None, widths: list[float] | None = None, heights: list[float] | None = None, hspace: float | None = None, vspace: float | None = None, fit: bool | None = None, align: bool | None = None, guides: str = 'auto', **point_kwargs) → SupPlotsSpec[source]#
-

Grid of dimensionality reduction plots.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • keys (list[str] | tuple[str] | Sequence[str]) – The keys (cell features) to color the points by. -e.g., ‘leiden’ or ‘louvain’ to color by clusters or gene name for expression.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • xy (tuple[int, int] | Sequence[int], default (1, 2)) – The x and y axes to use for the plot. -e.g., (1, 2) for UMAP1 and UMAP2.

    • -

  • use_key (str, default None) – The specific key to use for the desired dimensions. -e.g., ‘X_umap_2d’ or ‘X_pca_2d’. -Otherwise, the function will decide on the key based on the dimensions.

    • -

  • size (float, default 0.8) – The size of the points.

    • -

  • variable_keys (str | Sequence[str] | None, default None) – Variable keys to add to the DataFrame. If None, no additional keys are added.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • cluster_name (str, default 'Cluster') – The name to overwrite the clustering key in the dataframe and the plot.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • color_low (str, default '#e6e6e6') –

    The color to use for the low end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_mid (str, default None) –

    The color to use for the middle part of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_high (str, default '#377EB8') –

    The color to use for the high end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • mid_point (Literal[``’mean’, ``'median', 'mid'] | float, default 'median') – The midpoint (in data value) of the color gradient. -Can be ‘mean’, ‘median’ and ‘mid’ or a number (float or int). -- If ‘mean’, the midpoint is the mean of the data. -- If ‘median’, the midpoint is the median of the data. -- If ‘mid’, the midpoint is the mean of ‘min’ and ‘max’ of the data.

    • -

  • axis_type (Literal[``’axis’, ``'arrow'] | None) – Whether to use regular axis or arrows as the axis.

    • -

  • arrow_length (float, default 0.25) – Length of the arrow head (px).

    • -

  • arrow_size (float, default 1) – Size of the arrow.

    • -

  • arrow_color (str, default '#3f3f3f') –

    Color of the arrows. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • arrow_angle (float, default 10) – Angle of the arrow head in degrees.

    • -

  • legend_ondata (bool, default False) – whether to show legend on data

    • -

  • ondata_size (float, default 12) – size of the legend (text) on data.

    • -

  • ondata_color (str, default '#3f3f3f') – color of the legend (text) on data

    • -

  • ondata_fontface (str, default 'bold') – fontface of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-face

    • -

  • ondata_family (str, default 'sans') – family of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-family

    • -

  • ondata_alpha (float, default 1) – alpha (transparency) of the legend on data.

    • -

  • ondata_weighted (bool, default True) – whether to use weighted mean for the legend on data. -If True, the weighted mean of the group means is used. -If False, the arithmetic mean of the group means is used.

    • -

  • share_labels (bool, default True) – Whether to share the labels across all plots. -If True, only X labels on bottom row and Y labels on left column are shown.

    • -

  • share_axis (bool, default False) – Whether to share the axis across all plots. -If True, only X axis on bottom row and Y axis on left column is shown.

    • -

  • layers (Sequence[FeatureSpec|LayerSpec] | FeatureSpec | LayerSpec | None, default None) – Layers to add to all the plots in the grid.

    • -

  • ncol (int, default None) – Number of columns in grid. If not specified, shows plots horizontally, in one row.

    • -

  • sharex (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • sharey (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • widths (list[float], default None) – Relative width of each column of grid, left to right.

    • -

  • heights (list[float], default None) – Relative height of each row of grid, top-down.

    • -

  • hspace (float | None = None) – Cell horizontal spacing in px.

    • -

  • vspace (float | None = None) – Cell vertical spacing in px.

    • -

  • fit (bool, default True) – Whether to stretch each plot to match the aspect ratio of its cell (fit=True), -or to preserve the original aspect ratio of plots (fit=False).

    • -

  • align (bool, default False) – If True, align inner areas (i.e. “geom” bounds) of plots. -However, cells containing other (sub)grids are not participating -in the plot “inner areas” layouting.

    • -

  • guides (str, default 'auto') –

    -
    Specifies how guides (legends and colorbars) should be treated in the layout.
      -

    • ’collect’ collect guides from all subplots, removing duplicates.

      • -

    • ’keep’ keep guides in their original subplots; do not collect at this level.

      • -

    • ’auto’ allow guides to be collected if an upper-level layout uses guides=’collect’;

      • -
    -
    -
    -

    otherwise, keep them in subplots. -Duplicates are identified by comparing visual properties: -For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.). -For colorbars: title, domain limits, breaks, and color gradient.

    -

    For more information on gggrid parameters: -https://lets-plot.org/python/pages/api/lets_plot.gggrid.html

    -

    • -

  • **point_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -
-
-
Returns:
-

SupPlotsSpec – Grid of dimensionality reduction plots.

-
-
-
- -
- - -
- - - - - -
- - - - -
- - -
-
- On this page -
-
- -
- - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
- -
- -

- Created using Sphinx 9.1.0. -
-

-
- -
- - -
- -
-

- - Built with the PyData Sphinx Theme 0.16.1. -

- -
- -
- -
- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.core.subdimensionals.tsnes.html b/docs/_build/generated/cellestial.single.core.subdimensionals.tsnes.html deleted file mode 100644 index f8b66eb..0000000 --- a/docs/_build/generated/cellestial.single.core.subdimensionals.tsnes.html +++ /dev/null @@ -1,614 +0,0 @@ - - - - - - - - - - - cellestial.single.core.subdimensionals.tsnes - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.core.subdimensionals.tsnes#

-
-
-tsnes(data: AnnData, keys: Sequence[str], *, mapping: FeatureSpec | None = None, use_key: str | None = None, xy: tuple[int, int] | Sequence[int] = (1, 2), size: float = 0.8, variable_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, observations_name: str = 'Barcode', color_low: str = '#e6e6e6', color_mid: str | None = None, color_high: str = '#377eb8', mid_point: Literal['mean', 'median', 'mid'] | float = 'median', axis_type: Literal['axis', 'arrow'] | None = None, arrow_length: float = 0.25, arrow_size: float = 1, arrow_color: str = '#3f3f3f', arrow_angle: float = 10, legend_ondata: bool = False, ondata_size: float = 12, ondata_color: str = '#3f3f3f', ondata_fontface: str = 'bold', ondata_family: str = 'sans', ondata_alpha: float = 1, ondata_weighted: bool = True, share_labels: bool = True, share_axis: bool = False, layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None, ncol: int | None = None, sharex: str | None = None, sharey: str | None = None, widths: list[float] | None = None, heights: list[float] | None = None, hspace: float | None = None, vspace: float | None = None, fit: bool | None = None, align: bool | None = None, guides: str = 'auto', **point_kwargs) → SupPlotsSpec[source]#
-

Grid of dimensionality reduction plots.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • keys (list[str] | tuple[str] | Sequence[str]) – The keys (cell features) to color the points by. -e.g., ‘leiden’ or ‘louvain’ to color by clusters or gene name for expression.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • xy (tuple[int, int] | Sequence[int], default (1, 2)) – The x and y axes to use for the plot. -e.g., (1, 2) for UMAP1 and UMAP2.

    • -

  • use_key (str, default None) – The specific key to use for the desired dimensions. -e.g., ‘X_umap_2d’ or ‘X_pca_2d’. -Otherwise, the function will decide on the key based on the dimensions.

    • -

  • size (float, default 0.8) – The size of the points.

    • -

  • variable_keys (str | Sequence[str] | None, default None) – Variable keys to add to the DataFrame. If None, no additional keys are added.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • cluster_name (str, default 'Cluster') – The name to overwrite the clustering key in the dataframe and the plot.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

    • -

  • color_low (str, default '#e6e6e6') –

    The color to use for the low end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_mid (str, default None) –

    The color to use for the middle part of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • color_high (str, default '#377EB8') –

    The color to use for the high end of the color gradient. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • mid_point (Literal[``’mean’, ``'median', 'mid'] | float, default 'median') – The midpoint (in data value) of the color gradient. -Can be ‘mean’, ‘median’ and ‘mid’ or a number (float or int). -- If ‘mean’, the midpoint is the mean of the data. -- If ‘median’, the midpoint is the median of the data. -- If ‘mid’, the midpoint is the mean of ‘min’ and ‘max’ of the data.

    • -

  • axis_type (Literal[``’axis’, ``'arrow'] | None) – Whether to use regular axis or arrows as the axis.

    • -

  • arrow_length (float, default 0.25) – Length of the arrow head (px).

    • -

  • arrow_size (float, default 1) – Size of the arrow.

    • -

  • arrow_color (str, default '#3f3f3f') –

    Color of the arrows. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
    -
    -
      -

    • Applies to continuous (non-categorical) data.

      • -
    -

    • -

  • arrow_angle (float, default 10) – Angle of the arrow head in degrees.

    • -

  • legend_ondata (bool, default False) – whether to show legend on data

    • -

  • ondata_size (float, default 12) – size of the legend (text) on data.

    • -

  • ondata_color (str, default '#3f3f3f') – color of the legend (text) on data

    • -

  • ondata_fontface (str, default 'bold') – fontface of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-face

    • -

  • ondata_family (str, default 'sans') – family of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-family

    • -

  • ondata_alpha (float, default 1) – alpha (transparency) of the legend on data.

    • -

  • ondata_weighted (bool, default True) – whether to use weighted mean for the legend on data. -If True, the weighted mean of the group means is used. -If False, the arithmetic mean of the group means is used.

    • -

  • share_labels (bool, default True) – Whether to share the labels across all plots. -If True, only X labels on bottom row and Y labels on left column are shown.

    • -

  • share_axis (bool, default False) – Whether to share the axis across all plots. -If True, only X axis on bottom row and Y axis on left column is shown.

    • -

  • layers (Sequence[FeatureSpec|LayerSpec] | FeatureSpec | LayerSpec | None, default None) – Layers to add to all the plots in the grid.

    • -

  • ncol (int, default None) – Number of columns in grid. If not specified, shows plots horizontally, in one row.

    • -

  • sharex (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • sharey (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • widths (list[float], default None) – Relative width of each column of grid, left to right.

    • -

  • heights (list[float], default None) – Relative height of each row of grid, top-down.

    • -

  • hspace (float | None = None) – Cell horizontal spacing in px.

    • -

  • vspace (float | None = None) – Cell vertical spacing in px.

    • -

  • fit (bool, default True) – Whether to stretch each plot to match the aspect ratio of its cell (fit=True), -or to preserve the original aspect ratio of plots (fit=False).

    • -

  • align (bool, default False) – If True, align inner areas (i.e. “geom” bounds) of plots. -However, cells containing other (sub)grids are not participating -in the plot “inner areas” layouting.

    • -

  • guides (str, default 'auto') –

    -
    Specifies how guides (legends and colorbars) should be treated in the layout.
      -

    • ’collect’ collect guides from all subplots, removing duplicates.

      • -

    • ’keep’ keep guides in their original subplots; do not collect at this level.

      • -

    • ’auto’ allow guides to be collected if an upper-level layout uses guides=’collect’;

      • -
    -
    -
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    otherwise, keep them in subplots. -Duplicates are identified by comparing visual properties: -For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.). -For colorbars: title, domain limits, breaks, and color gradient.

    -

    For more information on gggrid parameters: -https://lets-plot.org/python/pages/api/lets_plot.gggrid.html

    -

    • -

  • **point_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -
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SupPlotsSpec – Grid of dimensionality reduction plots.

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- - © Copyright 2026, datavil. -
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- - Built with the PyData Sphinx Theme 0.16.1. -

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- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.core.subdimensionals.umaps.html b/docs/_build/generated/cellestial.single.core.subdimensionals.umaps.html deleted file mode 100644 index 5283c22..0000000 --- a/docs/_build/generated/cellestial.single.core.subdimensionals.umaps.html +++ /dev/null @@ -1,614 +0,0 @@ - - - - - - - - - - - cellestial.single.core.subdimensionals.umaps - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.core.subdimensionals.umaps#

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-umaps(data: AnnData, keys: Sequence[str], *, mapping: FeatureSpec | None = None, use_key: str | None = None, xy: tuple[int, int] | Sequence[int] = (1, 2), size: float = 0.8, variable_keys: Sequence[str] | str | None = None, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, observations_name: str = 'Barcode', color_low: str = '#e6e6e6', color_mid: str | None = None, color_high: str = '#377eb8', mid_point: Literal['mean', 'median', 'mid'] | float = 'median', axis_type: Literal['axis', 'arrow'] | None = None, arrow_length: float = 0.25, arrow_size: float = 1, arrow_color: str = '#3f3f3f', arrow_angle: float = 10, legend_ondata: bool = False, ondata_size: float = 12, ondata_color: str = '#3f3f3f', ondata_fontface: str = 'bold', ondata_family: str = 'sans', ondata_alpha: float = 1, ondata_weighted: bool = True, share_labels: bool = True, share_axis: bool = False, layers: Sequence[FeatureSpec | LayerSpec] | FeatureSpec | LayerSpec | None = None, ncol: int | None = None, sharex: str | None = None, sharey: str | None = None, widths: list[float] | None = None, heights: list[float] | None = None, hspace: float | None = None, vspace: float | None = None, fit: bool | None = None, align: bool | None = None, guides: str = 'auto', **point_kwargs) → SupPlotsSpec[source]#
-

Grid of dimensionality reduction plots.

-
-
Parameters:
-
    -

  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • keys (list[str] | tuple[str] | Sequence[str]) – The keys (cell features) to color the points by. -e.g., ‘leiden’ or ‘louvain’ to color by clusters or gene name for expression.

    • -

  • mapping (FeatureSpec | None, default None) – Additional aesthetic mappings for the plot, the result of aes().

    • -

  • xy (tuple[int, int] | Sequence[int], default (1, 2)) – The x and y axes to use for the plot. -e.g., (1, 2) for UMAP1 and UMAP2.

    • -

  • use_key (str, default None) – The specific key to use for the desired dimensions. -e.g., ‘X_umap_2d’ or ‘X_pca_2d’. -Otherwise, the function will decide on the key based on the dimensions.

    • -

  • size (float, default 0.8) – The size of the points.

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  • variable_keys (str | Sequence[str] | None, default None) – Variable keys to add to the DataFrame. If None, no additional keys are added.

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  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

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  • cluster_name (str, default 'Cluster') – The name to overwrite the clustering key in the dataframe and the plot.

    • -

  • observations_name (str, default 'Barcode') – The name to give to barcode (or index) column in the dataframe.

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  • color_low (str, default '#e6e6e6') –

    The color to use for the low end of the color gradient. -- Accepts:

    -
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    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

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      • -
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    The color to use for the middle part of the color gradient. -- Accepts:

    -
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    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

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    The color to use for the high end of the color gradient. -- Accepts:

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    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

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      • -
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  • mid_point (Literal[``’mean’, ``'median', 'mid'] | float, default 'median') – The midpoint (in data value) of the color gradient. -Can be ‘mean’, ‘median’ and ‘mid’ or a number (float or int). -- If ‘mean’, the midpoint is the mean of the data. -- If ‘median’, the midpoint is the median of the data. -- If ‘mid’, the midpoint is the mean of ‘min’ and ‘max’ of the data.

    • -

  • axis_type (Literal[``’axis’, ``'arrow'] | None) – Whether to use regular axis or arrows as the axis.

    • -

  • arrow_length (float, default 0.25) – Length of the arrow head (px).

    • -

  • arrow_size (float, default 1) – Size of the arrow.

    • -

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    Color of the arrows. -- Accepts:

    -
    -
      -

    • hex code e.g. ‘#f1f1f1’

      • -

    • color name (of a limited set of colors).

      • -

    • RGB/RGBA e.g. ‘rgb(0, 0, 255)’, ‘rgba(0, 0, 255, 0.5)’.

      • -
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    -
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      • -
    -

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  • arrow_angle (float, default 10) – Angle of the arrow head in degrees.

    • -

  • legend_ondata (bool, default False) – whether to show legend on data

    • -

  • ondata_size (float, default 12) – size of the legend (text) on data.

    • -

  • ondata_color (str, default '#3f3f3f') – color of the legend (text) on data

    • -

  • ondata_fontface (str, default 'bold') – fontface of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-face

    • -

  • ondata_family (str, default 'sans') – family of the legend (text) on data. -https://lets-plot.org/python/pages/aesthetics.html#font-family

    • -

  • ondata_alpha (float, default 1) – alpha (transparency) of the legend on data.

    • -

  • ondata_weighted (bool, default True) – whether to use weighted mean for the legend on data. -If True, the weighted mean of the group means is used. -If False, the arithmetic mean of the group means is used.

    • -

  • share_labels (bool, default True) – Whether to share the labels across all plots. -If True, only X labels on bottom row and Y labels on left column are shown.

    • -

  • share_axis (bool, default False) – Whether to share the axis across all plots. -If True, only X axis on bottom row and Y axis on left column is shown.

    • -

  • layers (Sequence[FeatureSpec|LayerSpec] | FeatureSpec | LayerSpec | None, default None) – Layers to add to all the plots in the grid.

    • -

  • ncol (int, default None) – Number of columns in grid. If not specified, shows plots horizontally, in one row.

    • -

  • sharex (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

  • sharey (bool, default None) – Controls sharing of axis limits between subplots in the grid. -all/True - share limits between all subplots. -none/False - do not share limits between subplots. -row - share limits between subplots in the same row. -col - share limits between subplots in the same column.

    • -

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    • -

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    • -

  • hspace (float | None = None) – Cell horizontal spacing in px.

    • -

  • vspace (float | None = None) – Cell vertical spacing in px.

    • -

  • fit (bool, default True) – Whether to stretch each plot to match the aspect ratio of its cell (fit=True), -or to preserve the original aspect ratio of plots (fit=False).

    • -

  • align (bool, default False) – If True, align inner areas (i.e. “geom” bounds) of plots. -However, cells containing other (sub)grids are not participating -in the plot “inner areas” layouting.

    • -

  • guides (str, default 'auto') –

    -
    Specifies how guides (legends and colorbars) should be treated in the layout.
      -

    • ’collect’ collect guides from all subplots, removing duplicates.

      • -

    • ’keep’ keep guides in their original subplots; do not collect at this level.

      • -

    • ’auto’ allow guides to be collected if an upper-level layout uses guides=’collect’;

      • -
    -
    -
    -

    otherwise, keep them in subplots. -Duplicates are identified by comparing visual properties: -For legends: title, labels, and all aesthetic values (colors, shapes, sizes, etc.). -For colorbars: title, domain limits, breaks, and color gradient.

    -

    For more information on gggrid parameters: -https://lets-plot.org/python/pages/api/lets_plot.gggrid.html

    -

    • -

  • **point_kwargs – Additional parameters for the geom_point layer. -For more information on geom_point parameters, see: -https://lets-plot.org/python/pages/api/lets_plot.geom_point.html

    • -
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Returns:
-

SupPlotsSpec – Grid of dimensionality reduction plots.

-
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- -
- - -
- - - - - -
- - - - -
- - -
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- On this page -
-
- -
- - -
-
- -
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- - - - - -
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- -

- - © Copyright 2026, datavil. -
- -

-
- -
- - -
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- Created using Sphinx 9.1.0. -
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-
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- - Built with the PyData Sphinx Theme 0.16.1. -

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- - \ No newline at end of file diff --git a/docs/_build/generated/cellestial.single.special.dotplot.dotplot.html b/docs/_build/generated/cellestial.single.special.dotplot.dotplot.html deleted file mode 100644 index 041a9d3..0000000 --- a/docs/_build/generated/cellestial.single.special.dotplot.dotplot.html +++ /dev/null @@ -1,501 +0,0 @@ - - - - - - - - - - - cellestial.single.special.dotplot.dotplot - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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cellestial.single.special.dotplot.dotplot#

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-dotplot(data: AnnData, keys: Sequence[str], group_by: str, *, threshold: float = 0, variables_name: str = 'gene', value_name: str = 'expression', color_low: str = '#e6e6e6', color_high: str = '#D2042D', fill: bool = False, sort_by: str | Sequence[str] | None = None, sort_order: Literal['ascending', 'descending'] = 'descending', percentage_key: str = 'pct_exp', mean_key: str = 'avg_exp', tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, **geom_kwargs) → PlotSpec[source]#
-

Dotplot.

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  • data (AnnData) – The AnnData object of the single cell data.

    • -

  • keys (Sequence[str]) – The variable keys or names to include in the dotplot.

    • -

  • group_by (str) – The key to group the data by.

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    • -

  • variables_name (str, default 'gene') – The name of the variable column in the long format.

    • -

  • value_name (str, default 'expression') – The name of the value column in the long format.

    • -

  • color_low (str, default '#e6e6e6') – The low color for the gradient.

    • -

  • color_high (str, default '#D2042D') – The high color for the gradient.

    • -

  • fill (bool, optional) – Whether to use fill aesthetic instead of color, by default False.

    • -

  • sort_by (str | None) – The column to sort the results by, by default None.

    • -

  • sort_order (str, default 'descending') – The sort order, either ‘ascending’ or ‘descending’.

    • -

  • percentage_key (str, default 'pct_exp') – The name of the percentage column.

    • -

  • mean_key (str, default 'avg_exp') – The name of the mean expression column.

    • -

  • tooltips (Literal[``’none’``] | Sequence[str] | FeatureSpec | None, default None) – Tooltips to show when hovering over the geom. -Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. -Use ‘none’ to disable tooltips.

    • -

  • show_tooltips (bool, default True) – Whether to show tooltips.

    • -

  • interactive (bool, default False) – Whether to make the plot interactive.

    • -

  • **geom_kwargs (Any) – Additional keyword arguments for the geom_point layer.

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PlotSpec – Dotplot.

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- - © Copyright 2026, datavil. -
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cellestial.util.colors.show_colors#

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Show a grid of hand-picked colors.

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cellestial.util.get_mapping#

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-get_mapping()#
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Returns the mapping of the plot as a dict.

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- - © Copyright 2026, datavil. -
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- Created using Sphinx 9.1.0. -
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cellestial.util.utilities.get_mapping#

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Returns the mapping of the plot as a dict.

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cellestial.util.utilities.retrieve#

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-retrieve(plot: PlotSpec | SupPlotsSpec, index: int = 0) → pl.DataFrame[source]#
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Retrieves the dataframe from a PlotSpec or SupPlotsSpec using the index.

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plotPlotSpec | SupPlotsSpec

The plot to retrieve the dataframe from.

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The index of the figure to retrieve the dataframe from, by default 0

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pl.DataFrame – The dataframe utilized in the plot.

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TypeError – If the plot is not a PlotSpec or SupPlotsSpec object.

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cellestial.util.utilities.slice#

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-slice()[source]#
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Slice a ggrid (SupPlotsSpec) objects with given index.

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PlotSpec | SupPlotsSpec – The sliced grid.

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TypeError – If the grid is not a SupPlotsSpec object. - If the index is not an int or Sequence[int].

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- - © Copyright 2026, datavil. -
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+
\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from lets_plot import *\n", + "LetsPlot.setup_html()\n", + "\n", + "import cellestial as cl\n", + "import scanpy as sc\n", + "\n", + "data = sc.read_h5ad('data/pbmc3k_pped.h5ad')\n", + "\n", + "p1 = (\n", + " cl.bar(data, mapping=aes('leiden', fill='predicted_doublet'))\n", + " + scale_fill_brewer(palette='Set2', direction=-1)\n", + ")\n", + "p1" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "fbe932ed", + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-05T10:19:44.278907Z", + "iopub.status.busy": "2026-03-05T10:19:44.278767Z", + "iopub.status.idle": "2026-03-05T10:19:44.578700Z", + "shell.execute_reply": "2026-03-05T10:19:44.578306Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from lets_plot import *\n", + "LetsPlot.setup_html()\n", + "\n", + "import cellestial as cl\n", + "import scanpy as sc\n", + "\n", + "data = sc.read_h5ad('data/pbmc3k_pped.h5ad')\n", + "\n", + "p2 = (\n", + " cl.bar(data, mapping=aes('cell_type_lvl1', fill='leiden'))\n", + " + scale_fill_brewer(palette='Set2')\n", + ")\n", + "p2" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.14.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} \ No newline at end of file diff --git a/docs/jupyter_execute/generated/cellestial.bar.py b/jupyter_execute/generated/cellestial.bar.py similarity index 100% rename from docs/jupyter_execute/generated/cellestial.bar.py rename to jupyter_execute/generated/cellestial.bar.py diff --git a/jupyter_execute/generated/cellestial.plot.ipynb b/jupyter_execute/generated/cellestial.plot.ipynb new file mode 100644 index 0000000..4dad547 --- /dev/null +++ b/jupyter_execute/generated/cellestial.plot.ipynb @@ -0,0 +1,574 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "f729552c", + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-05T10:19:45.917850Z", + "iopub.status.busy": "2026-03-05T10:19:45.917602Z", + "iopub.status.idle": "2026-03-05T10:19:47.153791Z", + "shell.execute_reply": "2026-03-05T10:19:47.153433Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from lets_plot import *\n", + "LetsPlot.setup_html()\n", + "\n", + "import cellestial as cl\n", + "import scanpy as sc\n", + "\n", + "data = sc.read_h5ad('data/pbmc3k_pped.h5ad')\n", + "\n", + "p1 = (\n", + " cl.plot(data, aes(x='cell_type_lvl1', y='n_genes'))\n", + ")\n", + "p1 # plot object without layers" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "be37152f", + "metadata": { + "execution": { + "iopub.execute_input": "2026-03-05T10:19:47.154934Z", + "iopub.status.busy": "2026-03-05T10:19:47.154791Z", + "iopub.status.idle": "2026-03-05T10:19:47.613438Z", + "shell.execute_reply": "2026-03-05T10:19:47.613109Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from lets_plot import *\n", + "LetsPlot.setup_html()\n", + "\n", + "import cellestial as cl\n", + "import scanpy as sc\n", + "\n", + "data = sc.read_h5ad('data/pbmc3k_pped.h5ad')\n", + "\n", + "p2 = (\n", + " cl.plot(data, aes(x='cell_type_lvl1', y='n_genes'))\n", + " + geom_violin(aes(fill='cell_type_lvl1'), scale='width')\n", + " + geom_boxplot(width=0.2,outlier_size=0)\n", + " + scale_fill_viridis()\n", + ")\n", + "p2" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.14.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} \ No newline at end of file diff --git a/docs/jupyter_execute/generated/cellestial.plot.py b/jupyter_execute/generated/cellestial.plot.py similarity index 100% rename from docs/jupyter_execute/generated/cellestial.plot.py rename to jupyter_execute/generated/cellestial.plot.py diff --git a/docs/API.rst b/sphinx/API.rst similarity index 100% rename from docs/API.rst rename to sphinx/API.rst diff --git a/docs/_build/_static/breast_cancer_atlas_umap.png b/sphinx/_static/breast_cancer_atlas_umap.png similarity index 100% rename from docs/_build/_static/breast_cancer_atlas_umap.png rename to sphinx/_static/breast_cancer_atlas_umap.png diff --git a/docs/_build/_static/custom.css b/sphinx/_static/custom.css similarity index 100% rename from docs/_build/_static/custom.css rename to sphinx/_static/custom.css diff --git a/docs/_build/_static/custom.js b/sphinx/_static/custom.js similarity index 100% rename from docs/_build/_static/custom.js rename to 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b/sphinx/jupyter_execute/generated/cellestial.bar.py @@ -0,0 +1,38 @@ +#!/usr/bin/env python +# coding: utf-8 + +# In[1]: + + +from lets_plot import * +LetsPlot.setup_html() + +import cellestial as cl +import scanpy as sc + +data = sc.read_h5ad('data/pbmc3k_pped.h5ad') + +p1 = ( + cl.bar(data, mapping=aes('leiden', fill='predicted_doublet')) + + scale_fill_brewer(palette='Set2', direction=-1) +) +p1 + + +# In[2]: + + +from lets_plot import * +LetsPlot.setup_html() + +import cellestial as cl +import scanpy as sc + +data = sc.read_h5ad('data/pbmc3k_pped.h5ad') + +p2 = ( + cl.bar(data, mapping=aes('cell_type_lvl1', fill='leiden')) + + scale_fill_brewer(palette='Set2') +) +p2 + diff --git a/docs/jupyter_execute/generated/cellestial.plot.ipynb b/sphinx/jupyter_execute/generated/cellestial.plot.ipynb similarity index 100% rename from docs/jupyter_execute/generated/cellestial.plot.ipynb rename to sphinx/jupyter_execute/generated/cellestial.plot.ipynb diff --git a/sphinx/jupyter_execute/generated/cellestial.plot.py b/sphinx/jupyter_execute/generated/cellestial.plot.py new file mode 100644 index 0000000..ca0c759 --- /dev/null +++ b/sphinx/jupyter_execute/generated/cellestial.plot.py @@ -0,0 +1,39 @@ +#!/usr/bin/env python +# coding: utf-8 + +# In[1]: + + +from lets_plot import * +LetsPlot.setup_html() + +import cellestial as cl +import scanpy as sc + +data = sc.read_h5ad('data/pbmc3k_pped.h5ad') + +p1 = ( + cl.plot(data, aes(x='cell_type_lvl1', y='n_genes')) +) +p1 # plot object without layers + + +# In[2]: + + +from lets_plot import * +LetsPlot.setup_html() + +import cellestial as cl +import scanpy as sc + +data = sc.read_h5ad('data/pbmc3k_pped.h5ad') + +p2 = ( + cl.plot(data, aes(x='cell_type_lvl1', y='n_genes')) + + geom_violin(aes(fill='cell_type_lvl1'), scale='width') + + geom_boxplot(width=0.2,outlier_size=0) + + scale_fill_viridis() +) +p2 + diff --git a/docs/jupyter_execute/generated/cellestial.single.basic.bar.bar.ipynb b/sphinx/jupyter_execute/generated/cellestial.single.basic.bar.bar.ipynb similarity index 100% rename from docs/jupyter_execute/generated/cellestial.single.basic.bar.bar.ipynb rename to sphinx/jupyter_execute/generated/cellestial.single.basic.bar.bar.ipynb diff --git a/docs/jupyter_execute/generated/cellestial.single.basic.bar.bar.py b/sphinx/jupyter_execute/generated/cellestial.single.basic.bar.bar.py similarity index 100% rename from docs/jupyter_execute/generated/cellestial.single.basic.bar.bar.py rename to sphinx/jupyter_execute/generated/cellestial.single.basic.bar.bar.py diff --git a/docs/jupyter_execute/generated/plot.ipynb b/sphinx/jupyter_execute/generated/plot.ipynb similarity index 100% rename from docs/jupyter_execute/generated/plot.ipynb rename to sphinx/jupyter_execute/generated/plot.ipynb diff --git a/docs/jupyter_execute/generated/plot.py b/sphinx/jupyter_execute/generated/plot.py similarity index 100% rename from docs/jupyter_execute/generated/plot.py rename to sphinx/jupyter_execute/generated/plot.py diff --git a/docs/performance.rst b/sphinx/performance.rst similarity index 100% rename from docs/performance.rst rename to sphinx/performance.rst diff --git a/docs/philosophy.rst b/sphinx/philosophy.rst similarity index 100% rename from docs/philosophy.rst rename to sphinx/philosophy.rst diff --git a/docs/requirements.txt b/sphinx/requirements.txt similarity index 100% rename from docs/requirements.txt rename to sphinx/requirements.txt