matplotlib.colors.AsinhNorm#
- classmatplotlib.colors.AsinhNorm(linear_width=1,vmin=None,vmax=None,clip=False)[source]#
Bases:
AsinhNormThe inverse hyperbolic sine scale is approximately linear nearthe origin, but becomes logarithmic for larger positiveor negative values. Unlike the
SymLogNorm, the transition betweenthese linear and logarithmic regions is smooth, which may reducethe risk of visual artifacts.Note
This API is provisional and may be revised in the futurebased on early user feedback.
- Parameters:
- linear_widthfloat, default: 1
The effective width of the linear region, beyond whichthe transformation becomes asymptotically logarithmic
- Parameters:
- vmin, vmaxfloat or None
Values within the range
[vmin,vmax]from the input data will belinearly mapped to[0,1]. If eithervmin orvmax is notprovided, they default to the minimum and maximum values of the input,respectively.- clipbool, default: False
Determines the behavior for mapping values outside the range
[vmin,vmax].If clipping is off, values outside the range
[vmin,vmax]arealso transformed, resulting in values outside[0,1]. Thisbehavior is usually desirable, as colormaps can mark theseunderandover values with specific colors.If clipping is on, values belowvmin are mapped to 0 and valuesabovevmax are mapped to 1. Such values become indistinguishablefrom regular boundary values, which may cause misinterpretation ofthe data.
Notes
If
vmin==vmax, input data will be mapped to 0.- __call__(value,clip=None)[source]#
Normalize the data and return the normalized data.
- Parameters:
- value
Data to normalize.
- clipbool, optional
See the description of the parameterclip in
Normalize.If
None, defaults toself.clip(which defaults toFalse).
Notes
If not already initialized,
self.vminandself.vmaxareinitialized usingself.autoscale_None(value).
