lisc.plts.counts.plot_clustermap

lisc.plts.counts.plot_clustermap(data, x_labels=None, y_labels=None, attribute='score', transpose=False, method='complete', metric='cosine', cmap='purple', **kwargs)

Plot a clustermap of the given data.

Parameters:

dataCounts or 2d array

Data to plot, as a clustermap.

x_labelslist of str, optional

Labels for the x-axis.

y_labelslist of str, optional

Labels for the y-axis.

attribute{‘score’, ‘counts’}, optional

Which data attribute from the counts object to plot the data for. Only used if the data input is a Counts object.

transposebool, optional, default: False

Whether to transpose the data before plotting.

methodstr, optional, default: ‘complete’

The linkage algorithm to use. See scipy.cluster.hierarchy.linkage for options.

metricstr or function, optional, default: ‘cosine’

The distance metric to use. See scipy.spatial.distance.pdist for options.

cmap{‘purple’, ‘blue’} or matplotlib.cmap

Colormap to use for the plot. If string, uses a sequential palette of the specified color.

**kwargs

Additional keyword arguments to pass through to seaborn.clustermap.

Notes

This function is a wrapper of the seaborn.clustermap plot function.

Examples

See the example for the compute_score() method of the Counts class.

Examples using lisc.plts.counts.plot_clustermap

Tutorial 05: Counts Analysis

Tutorial 05: Counts Analysis