- matplotlib.colors.make_norm_from_scale(scale_cls, base_norm_cls=None, *, init=None)#
@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.