ehrapy.plot.matrixplot¶
- ehrapy.plot.matrixplot(adata, var_names, groupby, use_raw=None, log=False, num_categories=7, figsize=None, dendrogram=False, title=None, cmap='viridis', colorbar_title='Mean value\\n in group', gene_symbols=None, var_group_positions=None, var_group_labels=None, var_group_rotation=None, layer=None, standard_scale=None, values_df=None, swap_axes=False, show=None, save=None, ax=None, return_fig=False, vmin=None, vmax=None, vcenter=None, norm=None, **kwds)[source]¶
Creates a heatmap of the mean count per group of each var_names.
This function provides a convenient interface to the
MatrixPlot
class. If you need more flexibility, you should useMatrixPlot
directly.- Parameters:
adata (
AnnData
) – Annotated data matrix.var_names (
Union
[str
,Sequence
[str
],Mapping
[str
,Union
[str
,Sequence
[str
]]]]) – var_names should be a valid subset of adata.var_names. If var_names is a mapping, then the key is used as label to group the values (see var_group_labels). The mapping values should be sequences of valid adata.var_names. In this case either coloring or ‘brackets’ are used for the grouping of var names depending on the plot. When var_names is a mapping, then the var_group_labels and var_group_positions are set.groupby (
str
|Sequence
[str
]) – The key of the observation grouping to consider.use_raw (
bool
|None
) – Use raw attribute of adata if present.log (
bool
) – Plot on logarithmic axis.num_categories (
int
) – Only used if groupby observation is not categorical. This value determines the number of groups into which the groupby observation should be subdivided.categories_order – Order in which to show the categories. Note: add_dendrogram or add_totals can change the categories order.
figsize (
tuple
[float
,float
] |None
) – Figure size when multi_panel=True. Otherwise the rcParam[‘figure.figsize] value is used. Format is (width, height)dendrogram (
bool
|str
) – If True or a valid dendrogram key, a dendrogram based on the hierarchical clustering between the groupby categories is added. The dendrogram information is computed usingscanpy.tl.dendrogram()
. If tl.dendrogram has not been called previously the function is called with default parameters.feature_symbols – Column name in .var DataFrame that stores feature symbols. By default var_names refer to the index column of the .var DataFrame. Setting this option allows alternative names to be used.
var_group_positions (
Sequence
[tuple
[int
,int
]] |None
) – Use this parameter to highlight groups of var_names. This will draw a ‘bracket’ or a color block between the given start and end positions. If the parameter var_group_labels is set, the corresponding labels are added on top/left. E.g. var_group_positions=[(4,10)] will add a bracket between the fourth var_name and the tenth var_name. By giving more positions, more brackets/color blocks are drawn.var_group_labels (
Sequence
[str
] |None
) – Labels for each of the var_group_positions that want to be highlighted.var_group_rotation (
float
|None
) – Label rotation degrees. By default, labels larger than 4 characters are rotated 90 degrees.layer (
str
|None
) – Name of the AnnData object layer that wants to be plotted. By default adata.raw.X is plotted. If use_raw=False is set, then adata.X is plotted. If layer is set to a valid layer name, then the layer is plotted. layer takes precedence over use_raw.colorbar_title (
str
|None
) – Title for the color bar. New line character (n) can be used.standard_scale (
Literal
['var'
,'group'
]) – Whether or not to standardize the given dimension between 0 and 1, meaning for each variable or group, subtract the minimum and divide each by its maximum.swap_axes (
bool
) – By default, the x axis contains var_names (e.g. genes) and the y axis the groupby categories. By setting swap_axes then x are the groupby categories and y the var_names.return_fig (
bool
|None
) – ReturnsDotPlot
object. Useful for fine-tuning the plot. Takes precedence over show=False.show (
bool
|None
) – Whether to display the figure or return axis.save (
str
|bool
|None
) – If True or a str, save the figure. A string is appended to the default filename. Infer the filetype if ending on {‘.pdf’, ‘.png’, ‘.svg’}.ax (
_AxesSubplot
|None
) – A matplotlib axes object. Only works if plotting a single component. vmin: The value representing the lower limit of the color scale. Values smaller than vmin are plotted with the same color as vmin.vmax (
float
|None
) – The value representing the upper limit of the color scale. Values larger than vmax are plotted with the same color as vmax.vcenter (
float
|None
) – The value representing the center of the color scale. Useful for diverging colormaps.norm (
Normalize
|None
) – Custom color normalization object from matplotlib. See https://matplotlib.org/stable/tutorials/colors/colormapnorms.html for details.kwds – Are passed to
matplotlib.pyplot.pcolor()
.
- Return type:
MatrixPlot
|dict
|None
- Returns:
If return_fig is True, returns a
MatrixPlot
object, else if show is false, return axes dict
Example
import ehrapy as ep adata = ep.dt.mimic_2(encoded=True) ep.pp.knn_impute(adata) ep.pp.log_norm(adata, offset=1) ep.pp.neighbors(adata) ep.tl.leiden(adata, resolution=0.5, key_added="leiden_0_5") ep.pl.matrixplot( adata, var_names=[ "abg_count", "wbc_first", "hgb_first", "platelet_first", "sodium_first", "potassium_first", "tco2_first", "chloride_first", "bun_first", "creatinine_first", "po2_first", "pco2_first", "iv_day_1", ], groupby="leiden_0_5", )
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