make_norm_from_scale(scale_cls, base_norm_cls=None, *, init=None)
After :
@make_norm_from_scale(scale_cls)
class norm_cls(Normalize):
...
norm_cls is filled with methods so that normalization computations are forwarded to scale_cls (i.e., scale_cls is the scale that would be used for the colorbar of a mappable normalized with norm_cls).
If init is not passed, then the constructor signature of norm_cls will be norm_cls(vmin=None, vmax=None, clip=False)
; these three parameters will be forwarded to the base class ( Normalize.__init__
), and a scale_cls object will be initialized with no arguments (other than a dummy axis).
If the scale_cls constructor takes additional parameters, then init should be passed to make_norm_from_scale
. It is a callable which is only used for its signature. First, this signature will become the signature of norm_cls. Second, the norm_cls constructor will bind the parameters passed to it using this signature, extract the bound vmin, vmax, and clip values, pass those to Normalize.__init__
, and forward the remaining bound values (including any defaults defined by the signature) to the scale_cls constructor.
Decorator for building a .Normalize
subclass from a ~.scale.ScaleBase
subclass.
The following pages refer to to this document either explicitly or contain code examples using this.
matplotlib.colors.make_norm_from_scale
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