matplotlib.colors.LogNorm

class matplotlib.colors.LogNorm(vmin=None, vmax=None, clip=False)

Bases: Normalize

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)

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).

autoscale(A)

Set vmin, vmax to min, max of A.

autoscale_None(A)

If vmin or vmax are not set, use the min/max of A to set them.

inverse(value)

Examples using matplotlib.colors.LogNorm

Colormap Normalizations

Colormap Normalizations

Pcolor Demo

Pcolor Demo

Histograms

Histograms

Time Series Histogram

Time Series Histogram

Quick start guide

Quick start guide

Colormap Normalization

Colormap Normalization