cmap_builder.PiecewiseNorm
- class cmap_builder.PiecewiseNorm(data_points, clip=False)
Piecewise linear Norm.
Normalizes data into the [0.0, 1.0] interval by performing a piecewise linear interpolation a non-uniform sequence of N data points over the [0-1] interval.
The non-uniform data intervals are mapped to evenly-spaced intervals in the [0-1] interval using piecewise interpolation.
(Class adapted from the matplotlib.colors.Normalize class).
- __init__(data_points, clip=False)
Constructor
- Parameters
- data_points: array-like (1D)
Sequence of data points indicating the data segments to map.
- clip: bool
If True values falling outside the data_points range are mapped to 0 or 1, whichever is closer, and masked values are set to 1. If False masked 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.
Methods
__init__(data_points[, clip])Constructor
autoscale(A)Set vmin, vmax to min, max of A.
autoscale_None(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