matplotlib.colors.TwoSlopeNorm#

classmatplotlib.colors.TwoSlopeNorm(vcenter,vmin=None,vmax=None)[source]#

Bases:Normalize

Normalize data with a set center.

Useful when mapping data with an unequal rates of change around aconceptual center, e.g., data that range from -2 to 4, with 0 asthe midpoint.

Parameters:

vcenterfloat

The data value that defines0.5 in the normalization.

vminfloat, optional

The data value that defines0.0 in the normalization.Defaults to the min value of the dataset.

vmaxfloat, optional

The data value that defines1.0 in the normalization.Defaults to the max value of the dataset.

Examples

This maps data value -4000 to 0., 0 to 0.5, and +10000 to 1.0; databetween is linearly interpolated:

>>>importmatplotlib.colorsasmcolors>>>offset=mcolors.TwoSlopeNorm(vmin=-4000.,...vcenter=0.,vmax=10000)>>>data=[-4000.,-2000.,0.,2500.,5000.,7500.,10000.]>>>offset(data)array([0., 0.25, 0.5, 0.625, 0.75, 0.875, 1.0])

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

Map value to the interval [0, 1]. Theclip argument is unused.

autoscale_None(A)[source]#

Get vmin and vmax.

If vcenter isn't in the range [vmin, vmax], either vmin or vmaxis expanded so that vcenter lies in the middle of the modified range[vmin, vmax].

inverse(value)[source]#

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

Parameters:

value

Normalized value.

propertyvcenter#

Examples usingmatplotlib.colors.TwoSlopeNorm#

Colormap normalization

Colormap normalization