neuralib.plot.colormap

class neuralib.plot.colormap.DiscreteColorMapper

map color to iterable object

Example of a ``dict`` palette

>>> palette = {3: ('#3182bd', '#6baed6', '#9ecae1'),
...            5: ('#a1d99b', '#c7e9c0', '#756bb1', '#9e9ac8', '#bcbddc')}
>>> cmapper = DiscreteColorMapper(palette, 5)
>>> x = ['1', '2', '3']
>>> color_list = [cmapper[i] for i in x]

Example of a mpl ``str`` palette

>>> cmapper = DiscreteColorMapper('viridis', 20)
>>> regions = ['rsc', 'vis', 'hpc']
>>> color_list = [cmapper[r] for r in regions]

__init__(palette, number)

Parameters:

• palette (dict[int, tuple[str, ...]] | str) – A custom dictionary color palette or a Matplotlib colormap name

• number (int) – Number of colors to cycle through in the palette or colormap

neuralib.plot.colormap.get_customized_cmap(name, value, numbers, endpoint=True)

Generate gradient color map array. N = number of color

Parameters:

• name (str) – name of cmap

• value (tuple[float, float]) – value range, could be 0-1

• numbers (int) – N

• endpoint (bool) – If cyclic colormap, then used False

Returns:

RGBA. Array[float, [N, 4]]

Return type:

ndarray

neuralib.plot.colormap.insert_colorbar(ax, im, **kwargs)

Insert colormap

Parameters:

• ax (Axes) – Axes

• im (_ScalarMappable) – ScalarMappable

• kwargs – Additional args pass to ax.figure.colorbar

Returns:

Return type:

Colorbar

neuralib.plot.colormap.insert_cyclic_colorbar(ax, im, *, num_colors=12, num_labels=4, width=0.6, inner_diameter=0.6, vmin=None, vmax=None)

Insert cyclic colormap in inset_axes

Parameters:

• ax (Axes) – Axes

• im (_ScalarMappable) – ScalarMappable

• num_colors (int) – Number of color in the cyclic colorbar

• num_labels (int) – Number of labels in the cyclic colorbar

• width (float) – Width of the each color

• inner_diameter (float) – The size of the inner circle

• vmin (float | None) – Min value of the colormap, equal to vmax in cyclic data

• vmax (float | None) – Max value of the colormap, equal to vmin in cyclic data

Return type:

None