Bases: matplotlib.colors.Normalize
Dummy replacement for Normalize
, for the case where we want to use indices directly in a ScalarMappable
.
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)
.
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
.
Returns 0 if vmin == vmax
.
Normalize value data in the [vmin, vmax]
interval into the [0.0, 1.0]
interval and return it.
Data to normalize.
If None
, defaults to self.clip
(which defaults to False
).
If not already initialized, self.vmin
and self.vmax
are initialized using self.autoscale_None(value)
.
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https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.colors.NoNorm.html