matplotlib.colors.Normalize¶

class
matplotlib.colors.
Normalize
(vmin=None, vmax=None, clip=False)[source]¶ Bases:
object
A class which, when called, can normalize data into the
[0.0, 1.0]
interval.If vmin or vmax is not given, they are initialized from the minimum and maximum value respectively of the first input processed. That is, __call__(A) calls autoscale_None(A). If clip is True and the given value falls outside the range, the returned value will be 0 or 1, whichever is closer. Returns 0 if
vmin==vmax
Works with scalars or arrays, including masked arrays. If clip is True, masked values are set to 1; otherwise they remain masked. Clipping silently defeats the purpose of setting the over, under, and masked colors in the colormap, so it is likely to lead to surprises; therefore the default is clip = False.

static
process_value
(value)[source]¶ Homogenize the input value for easy and efficient normalization.
value can be a scalar or sequence.
Returns result, is_scalar, where result is a masked array matching value. Float dtypes are preserved; integer types with two bytes or smaller are converted to np.float32, and larger types are converted to np.float64. Preserving float32 when possible, and using inplace operations, can greatly improve speed for large arrays.
Experimental; we may want to add an option to force the use of float32.

static