iris.palette¶
Load, configure and register color map palettes and initialise color map meta-data mappings.
In this module:
-
iris.palette.auto_palette(func)[source]¶ Decorator wrapper function to control the default behaviour of the matplotlib cmap and norm keyword arguments.
Args:
- func (callable):
Callable function to be wrapped by the decorator.
- Returns
Closure wrapper function.
-
iris.palette.cmap_norm(cube)[source]¶ Determine the default
matplotlib.colors.LinearSegmentedColormapandiris.palette.SymmetricNormalizeinstances associated with the cube.Args:
- cube (
iris.cube.Cube): Source cube to generate default palette from.
- cube (
- Returns
Tuple of
matplotlib.colors.LinearSegmentedColormapandiris.palette.SymmetricNormalize
-
iris.palette.is_brewer(cmap)[source]¶ Determine whether the color map is a Cynthia Brewer color map.
Args:
- cmap:
The color map instance.
- Returns
Boolean.
Provides a symmetric normalization class around a given pivot point.
- class
iris.palette.SymmetricNormalize(pivot, *args, **kwargs)[source]¶Provides a symmetric normalization class around a given pivot point.
__call__(value, clip=None)¶Normalize value data in the
[vmin, vmax]interval into the[0.0, 1.0]interval and return it.
- Parameters
value – Data to normalize.
clip (bool) – If
None, defaults toself.clip(which defaults toFalse).Notes
If not already initialized,
self.vminandself.vmaxare initialized usingself.autoscale_None(value).
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)¶
- static
process_value(value)¶Homogenize the input value for easy and efficient normalization.
value can be a scalar or sequence.
- Returns
result (masked array) – Masked array with the same shape as value.
is_scalar (bool) – 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.
scaled()¶Return whether vmin and vmax are set.
- property
vmax¶
- property
vmin¶