matplotlib.colors.LogNorm

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

Bases: matplotlib.colors.LogNorm

Normalize a given value to the 0-1 range on a log scale.

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__(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).

inverse(value)[source]

Examples using matplotlib.colors.LogNorm