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  • Hierarchical clustering (scipy.cluster.hierarchy)
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scipy.cluster.hierarchy.set_link_color_palette#

scipy.cluster.hierarchy.set_link_color_palette(palette)[source]#

Set list of matplotlib color codes for use by dendrogram.

Note that this palette is global (i.e., setting it once changes the colors for all subsequent calls to dendrogram) and that it affects only the the colors below color_threshold.

Note that dendrogram also accepts a custom coloring function through its link_color_func keyword, which is more flexible and non-global.

Parameters:
palettelist of str or None

A list of matplotlib color codes. The order of the color codes is the order in which the colors are cycled through when color thresholding in the dendrogram.

If None, resets the palette to its default (which are matplotlib default colors C1 to C9).

Returns:
None

See also

dendrogram

Notes

Ability to reset the palette with None added in SciPy 0.17.0.

Examples

>>> import numpy as np
>>> from scipy.cluster import hierarchy
>>> ytdist = np.array([662., 877., 255., 412., 996., 295., 468., 268.,
...                    400., 754., 564., 138., 219., 869., 669.])
>>> Z = hierarchy.linkage(ytdist, 'single')
>>> dn = hierarchy.dendrogram(Z, no_plot=True)
>>> dn['color_list']
['C1', 'C0', 'C0', 'C0', 'C0']
>>> hierarchy.set_link_color_palette(['c', 'm', 'y', 'k'])
>>> dn = hierarchy.dendrogram(Z, no_plot=True, above_threshold_color='b')
>>> dn['color_list']
['c', 'b', 'b', 'b', 'b']
>>> dn = hierarchy.dendrogram(Z, no_plot=True, color_threshold=267,
...                           above_threshold_color='k')
>>> dn['color_list']
['c', 'm', 'm', 'k', 'k']

Now, reset the color palette to its default:

>>> hierarchy.set_link_color_palette(None)

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