pie

pie ¶

pie(
    data,
    phenotype="phenotype",
    groupBy="imageid",
    ncols=None,
    subsetPhenotype=None,
    subsetGroupBy=None,
    label="auto",
    title="auto",
    colors=None,
    autopct="%1.1f%%",
    legend=False,
    legendLoc="upper right",
    wedgeprops=None,
    fileName="pie.pdf",
    outputDir=None,
    saveDir=None,
    show=True,
    returnData=False,
    returnFig=False,
    dpi=300,
    transparent=False,
    sdataTable=None,
    **kwargs
)

Cell-type proportions as a grid of pie charts.

One pie per category of groupBy, with wedges for each category of phenotype. The counts behind the plot are a pandas.crosstab of the two columns, which returnData=True hands back.

Parameters:

Name	Type	Description	Default
`data`	`(AnnData \| SpatialData \| str, required)`	The cell table. An `AnnData`, a path to an `.h5ad` file, a `SpatialData` object, or a path to a `.zarr` SpatialData store.	required
`phenotype`	`str`	Column in `obs` that supplies the wedges.	`'phenotype'`
`groupBy`	`str`	Column in `obs` that supplies the panels. One pie per value.	`'imageid'`
`ncols`	`int`	Panels per row. Defaults to `min(3, number of groups)`.	`None`
`subsetPhenotype`	`list`	Keep only these phenotypes.	`None`
`subsetGroupBy`	`list`	Keep only these groups.	`None`
`label`	`str`	`'auto'` labels the wedges with the phenotype names; anything else suppresses the labels.	`'auto'`
`title`	`str`	`'auto'` titles each panel with its group name; any other string is used verbatim for every panel.	`'auto'`
`colors`	`list`	Explicit wedge colours, in the order the phenotypes appear.	`None`
`autopct`	`str`	Percentage format string passed to Matplotlib, or `None` for no percentages.	`'%1.1f%%'`
`legend`	`bool`	Draw a legend on each panel instead of relying on wedge labels.	`False`
`legendLoc`	`str`	Matplotlib legend location.	`'upper right'`
`wedgeprops`	`dict`	Passed through to `Axes.pie`, e.g. `{"width": 0.4}` for a donut.	`None`
`outputDir`	`str`	Directory to save the figure in. When `None` nothing is written.	`None`
`fileName`	`str`	File name for the saved figure. The extension decides the format.	`'pie.pdf'`
`saveDir`	`str`	Deprecated alias for `outputDir`, kept for scripts carried over from scimap. `outputDir` wins when both are given.	`None`
`show`	`bool`	Call `plt.show()` before returning. Set `False` in scripts and notebooks that save rather than display.	`True`
`returnData`	`bool`	Return the `DataFrame` behind the plot instead of drawing it.	`False`
`returnFig`	`bool`	Return `(fig, axes)`. With `returnData` as well, returns `(fig, axes, plotData)`.	`False`
`dpi`	`int`	Resolution of the saved figure.	`300`
`transparent`	`bool`	Save with a transparent background.	`False`
`sdataTable`	`str`	Which `SpatialData` table to read. Ignored for `AnnData` input, and optional when the store has exactly one table.	`None`

Returns:

Name	Type	Description
`result`	`None \| DataFrame \| tuple`	`None` by default; the group x phenotype count table with `returnData=True`; `(fig, axes)` with `returnFig=True`.

Example

# One pie per image.
sp.pl.pie(adata, phenotype="phenotype")

# Donut charts for two cell types across selected samples.
sp.pl.pie(
    adata,
    phenotype="phenotype",
    subsetPhenotype=["Treg", "NK cells"],
    subsetGroupBy=["sample_1", "sample_2"],
    wedgeprops={"width": 0.4},
    outputDir="figures",
    show=False,
)