matplotlib.colors.NoNorm#

classmatplotlib.colors.NoNorm(vmin=None,vmax=None,clip=False)[source]#

Bases:Normalize

Dummy replacement forNormalize, for the case where we want to useindices directly in aScalarMappable.

Parameters:

vmin, vmaxfloat or None

Values within the range[vmin,vmax] from the input data will belinearly mapped to[0,1]. If eithervmin orvmax is notprovided, they default to the minimum and maximum values of the input,respectively.

clipbool, default: False

Determines the behavior for mapping values outside the range[vmin,vmax].

If clipping is off, values outside the range[vmin,vmax] arealso transformed, resulting in values outside[0,1]. Thisbehavior is usually desirable, as colormaps can mark theseunderandover values with specific colors.

If clipping is on, values belowvmin are mapped to 0 and valuesabovevmax are mapped to 1. Such values become indistinguishablefrom regular boundary values, which may cause misinterpretation ofthe data.

Notes

Ifvmin==vmax, input data will be mapped to 0.

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

Normalize the data and return the normalized data.

Parameters:

value

Data to normalize.

clipbool, optional

See the description of the parameterclip inNormalize.

IfNone, defaults toself.clip (which defaults toFalse).

Notes

If not already initialized,self.vmin andself.vmax areinitialized usingself.autoscale_None(value).

inverse(value)[source]#

Maps the normalized value (i.e., index in the colormap) back to imagedata value.

Parameters:

value

Normalized value.