matplotlib.colors.PowerNorm

class matplotlib.colors.PowerNorm(gamma, vmin=None, vmax=None, clip=False) [source]

Bases: matplotlib.colors.Normalize

Linearly map a given value to the 0-1 range and then apply a power-law normalization over that range.

Parameters:
vmin, vmaxfloat or None

If vmin and/or vmax is not given, they are initialized from the minimum and maximum value, respectively, of the first input processed; i.e., __call__(A) calls autoscale_None(A).

clipbool, default: False

If True values falling outside the range [vmin, vmax], are mapped to 0 or 1, whichever is closer, and masked values are set to 1. If False masked values remain masked.

Clipping silently defeats the purpose of setting the over, under, and masked colors in a colormap, so it is likely to lead to surprises; therefore the default is clip=False.

Notes

Returns 0 if vmin == vmax.

__call__(self, value, clip=None) [source]

Normalize value data in the [vmin, vmax] interval into the [0.0, 1.0] interval and return it.

Parameters:
value

Data to normalize.

clipbool

If None, defaults to self.clip (which defaults to False).

Notes

If not already initialized, self.vmin and self.vmax are initialized using self.autoscale_None(value).

__init__(self, gamma, vmin=None, vmax=None, clip=False) [source]
Parameters:
vmin, vmaxfloat or None

If vmin and/or vmax is not given, they are initialized from the minimum and maximum value, respectively, of the first input processed; i.e., __call__(A) calls autoscale_None(A).

clipbool, default: False

If True values falling outside the range [vmin, vmax], are mapped to 0 or 1, whichever is closer, and masked values are set to 1. If False masked values remain masked.

Clipping silently defeats the purpose of setting the over, under, and masked colors in a colormap, so it is likely to lead to surprises; therefore the default is clip=False.

Notes

Returns 0 if vmin == vmax.

__module__ = 'matplotlib.colors'
__slotnames__ = []
inverse(self, value) [source]

Examples using matplotlib.colors.PowerNorm

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Licensed under the Matplotlib License Agreement.
https://matplotlib.org/3.3.3/api/_as_gen/matplotlib.colors.PowerNorm.html