matplotlib.colors.DivergingNorm

class matplotlib.colors.DivergingNorm(**kwargs) [source]

Bases: matplotlib.colors.TwoSlopeNorm

[Deprecated]

Notes

Deprecated since version 3.2:

Normalize data with a set center.

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

Parameters:	vcenterfloat The data value that defines 0.5 in the normalization. vminfloat, optional The data value that defines 0.0 in the normalization. Defaults to the min value of the dataset. vmaxfloat, optional The data value that defines 1.0 in the normalization. Defaults to the the max value of the dataset.

Examples

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

>>> import matplotlib.colors as mcolors
>>> 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])