matplotlib.colors.FuncNorm#
- classmatplotlib.colors.FuncNorm(functions,vmin=None,vmax=None,clip=False)[source]#
Bases:
FuncNormArbitrary normalization using functions for the forward and inverse.
- Parameters:
- functions(callable, callable)
two-tuple of the forward and inverse functions for the normalization.The forward function must be monotonic.
Both functions must have the signature
defforward(values:array-like)->array-like
- vmin, vmaxfloat or None
Ifvmin and/orvmax is not given, they are initialized from theminimum and maximum value, respectively, of the first inputprocessed; i.e.,
__call__(A)callsautoscale_None(A).- clipbool, default: False
Determines the behavior for mapping values outside the range
[vmin,vmax].If clipping is off, values outside the range
[vmin,vmax]are alsotransformed by the function, resulting in values outside[0,1].This behavior is usually desirable, as colormaps can mark theseunderandover values with specific colors.If clipping is on, values belowvmin are mapped to 0 and values abovevmax are mapped to 1. Such values become indistinguishable fromregular boundary values, which may cause misinterpretation of the data.
- 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
If
vmin==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 in
Normalize.If
None, defaults toself.clip(which defaults toFalse).
Notes
If not already initialized,
self.vminandself.vmaxareinitialized usingself.autoscale_None(value).