#!/usr/bin/env python
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"""Script to apply vicinity neighbourhoods to data."""
from improver import cli
[docs]@cli.clizefy
@cli.with_output
def process(cube: cli.inputcube, vicinity: cli.comma_separated_list = None):
"""Module to apply vicinity processing to data.
Calculate the maximum value within a vicinity radius about each point
in each x-y slice of the input cube.
If working with thresholded data, using this CLI to calculate a
neighbourhood maximum ensemble probability, the vicinity process must
be applied prior to averaging across the ensemble, i.e. collapsing the
realization coordinate. A typical chain might look like:
threshold --> vicinity --> realization collapse
Note that the threshold CLI can be used to perform this series of steps
in a single call without intermediate output.
Users should ensure they do not inadvertently apply vicinity processing
twice, once within the threshold CLI and then again using this CLI.
Args:
cube (iris.cube.Cube):
A cube containing data to which a vicinity is to be applied.
vicinity (list of float / int):
List of distances in metres used to define the vicinities within
which to search for an occurrence. Each vicinity provided will
lead to a different gridded field.
Returns:
iris.cube.Cube:
Cube with the vicinity processed data.
"""
from improver.utilities.spatial import OccurrenceWithinVicinity
vicinity = [float(x) for x in vicinity]
return OccurrenceWithinVicinity(radii=vicinity).process(cube)