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librosa.display.infer_cmap

librosa.display.infer_cmap(data, *, robust=True, cmap_seq='magma', cmap_bool='gray_r', cmap_div='coolwarm', div_thresh=0.0)[source]

Get a default colormap from the given data.

If the data is boolean, use a black and white colormap.

If the data has both positive and negative values, use a diverging colormap.

Otherwise, use a sequential colormap.

Parameters:

datanp.ndarray: Input data
robustbool: If True, discard the top and bottom 2% of data when calculating range.
cmap_seqstr or matplotlib.colors.Colormap: The sequential colormap
cmap_boolstr or matplotlib.colors.Colormap: The boolean colormap
cmap_divstr or matplotlib.colors.Colormap: The diverging colormap
div_threshfloat: The threshold for determining whether to use a diverging colormap. If the data has values both above and below this threshold, then a diverging colormap is used.

Returns: