smpl.plot.Normalize¶
- class smpl.plot.Normalize(vmin=None, vmax=None, clip=False)[source]¶
Bases:
objectA class which, when called, linearly normalizes data into the
[0.0, 1.0]interval.- __init__(vmin=None, vmax=None, clip=False)[source]¶
Parameters¶
- vmin, vmaxfloat or None
If vmin and/or vmax is not given, they are initialized from the minimum and maximum value, respectively, of the first input processed; i.e.,
__call__(A)callsautoscale_None(A).- clipbool, default: False
If
Truevalues falling outside the range[vmin, vmax], are mapped to 0 or 1, whichever is closer, and masked values are set to 1. IfFalsemasked values remain masked.Clipping silently defeats the purpose of setting the over, under, and masked colors in a colormap, so it is likely to lead to surprises; therefore the default is
clip=False.
Notes¶
Returns 0 if
vmin == vmax.
Methods
__init__([vmin, vmax, clip])Parameters vmin, vmax float or None If vmin and/or vmax is not given, they are initialized from the minimum and maximum value, respectively, of the first input processed; i.e., __call__(A) calls autoscale_None(A).
autoscale(A)Set vmin, vmax to min, max of A.
If vmin or vmax are not set, use the min/max of A to set them.
inverse(value)process_value(value)Homogenize the input value for easy and efficient normalization.
scaled()Return whether vmin and vmax are set.
Attributes
clipvmaxvmin- static process_value(value)[source]¶
Homogenize the input value for easy and efficient normalization.
value can be a scalar or sequence.
Returns¶
- resultmasked array
Masked array with the same shape as value.
- is_scalarbool
Whether value is a scalar.
Notes¶
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 in-place operations, greatly improves speed for large arrays.