plots.styles.levels

Classes

Levels

Class defining levels to use with a mapping style.

Functions

`auto_range`(data[, divergence_point, n_levels])	Generate a suitable range of levels for arbitrary input data.
`categorical_range`(values)	Generate a range of levels for categorical data.
`step_range`(data, step[, reference])	Generate a range of levels for some data based on a level step and multiple.

Module Contents

class plots.styles.levels.Levels(levels=None, step=None, reference=None, divergence_point=None, categorical=False)

Class defining levels to use with a mapping style.

Parameters:

levels (list, optional) – A static list of levels to always use, no matter the input data.
step (float, optional) – The step/difference between each level in the desired level range.
reference (float, optional) – The reference point around which to calibrate the level range. For example, if a step of 4 is used and a reference of 2 is used, then the generated levels will be generated as steps of 4 above and below the number 2.
divergence_point (float, optional) – If provided, force the levels to be centred on this point. This is mostly useful for parameters which use diverging colors in their style, such as anomalies.

apply(data)

Generate levels specific to some data.

Parameters:: data (numpy.ndarray or xarray.DataArray or earthkit.data.core.Base) – The data for which to generate a list of levels.
Return type:: list

classmethod from_config(config)

plots.styles.levels.auto_range(data, divergence_point=None, n_levels=schema.default_style_levels)

Generate a suitable range of levels for arbitrary input data.

Parameters:

data (numpy.ndarray or xarray.DataArray or earthkit.data.core.Base) – The data for which to generate a list of levels.
divergence_point (float, optional) – If provided, force the levels to be centered on this point. Useful for parameters that use diverging colors in their style, such as anomalies.
n_levels (int, optional) – The target number of levels to generate (default is 10).

Returns:

A list of levels spaced across the data range with easy-to-interpret intervals.

Return type:

list

plots.styles.levels.categorical_range(values)

Generate a range of levels for categorical data.

This can be necessary to make sure that categorical data falls inside the correct bins, as values at the edge of a bin may not be included in the bin.

Parameters:: values (numpy.ndarray or xarray.DataArray or earthkit.data.core.Base) – The data for which to generate a list of levels.
Return type:: list

plots.styles.levels.step_range(data, step, reference=None)

Generate a range of levels for some data based on a level step and multiple.

Parameters:

data (numpy.ndarray or xarray.DataArray or earthkit.data.core.Base) – The data for which to generate a list of levels.
step (float) – The step/difference between each level in the desired level range.
reference (float, optional) – The reference point around which to calibrate the level range. For example, if a step of 4 is used and a reference of 2 is used, then the generated levels will be generated as steps of 4 above and below the number 2.

Return type:

list