pairot.pl.mapping

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pairot.pl.mapping#

pairot.pl.mapping(data, width=None, height=None, zmin=None, zmax=None, colormap='Greens', sort_by_score=True, backend='plotly')#

Plot cluster mappings from pairot.tl.DatasetMap.compute_mapping.

Parameters:

  • data (DataFrame) – pd.DataFrame containing the cluster mapping scores.

  • width (int (default: None)) – Width of the plot in pixels.

  • height (int (default: None)) – Height of the plot in pixels.

  • zmin (float (default: None)) – Minimum value for color scale.

  • zmax (float (default: None)) – Maximum value for color scale.

  • colormap (str (default: 'Greens')) – Colormap to use for the heatmap.

  • sort_by_score (bool (default: True)) – Whether to sort the clusters by their maximum mapping score. If True, the strongest map for each cell type cluster appears on the diagonal of the mapping plot.

  • backend (Literal['plotly', 'matplotlib'] (default: 'plotly')) – Backend to use for plotting. Options are ‘plotly’ and ‘matplotlib’. The plotly backend allows for interactive plots, while the matplotlib backend is suitable for static plots.

Examples

>>> import pairot as pr
>>>
>>> # Get cluster mappings between query and reference dataset
>>> mapping = dataset_map.compute_mapping()
>>>
>>> # Plot the cluster mapping heatmap
>>> pr.pl.mapping(data)
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