Bases: BoundaryNorm
Meta-normalizer that discretizes the possible color values returned by arbitrary continuous normalizers given a sequence of level boundaries.
levels (sequence of float) – The level boundaries. Must be monotonically increasing or decreasing. If the latter then descending is set to True and the colorbar axis drawn with this normalizer will be reversed.
norm (Normalize, optional) – The normalizer used to transform levels and data values passed to __call__ before discretization. The vmin and vmax of the normalizer are set to the minimum and maximum values in levels.
unique ({'neither', 'both', 'min', 'max'}, optional) – Which out-of-bounds regions should be assigned unique colormap colors. Possible values are equivalent to the extend values. Internally, ultraplot sets this depending on the user-input extend, whether the colormap is cyclic, and whether set_under or set_over were called for the colormap.
step (float, optional) – The intensity of the transition to out-of-bounds colors as a fraction of the adjacent step between in-bounds colors. Internally, ultraplot sets this to 0.5 for cyclic colormaps and 1 for all other colormaps. This only has an effect on lower colors when unique is 'min' or 'both', and on upper colors when unique is 'max' or 'both'.
clip (bool, optional) – Whether to clip values falling outside of the level bins. This only has an effect on lower colors when unique is 'min' or 'both', and on upper colors when unique is 'max' or 'both'.
ticks (array-like, default: levels) – Default tick values to use for colorbars drawn with this normalizer. This is set to the level centers when values is passed to a plotting command.
labels (array-like, optional) – Default tick labels to use for colorbars drawn with this normalizer. This is set to values when drawing on-the-fly colorbars.
Note
This normalizer makes sure that levels always span the full range of colors in the colormap, whether extend is set to 'min', 'max', 'neither', or 'both'. In matplotlib, when extend is not 'both', the most intense colors are cut off (reserved for “out of bounds” data), even though they are not being used.
Attributes Summary
Boolean indicating whether the levels are descending.
Methods Summary
__call__(value[, clip])
Normalize data values to 0-1.
inverse(value)
Raise an error.
Attributes Documentation
Boolean indicating whether the levels are descending.
Methods Documentation
Normalize data values to 0-1.
value (numeric) – The data to be normalized.
clip (bool, default: self.clip) – Whether to clip values falling outside of the level bins.
Raise an error.
ValueError – Inversion after discretization is impossible.
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