#!/usr/bin/env python
# -*- coding: utf-8 -*-
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"""Script to collapse cube coordinates and calculate percentiled data."""
from improver import cli
[docs]@cli.clizefy
@cli.with_output
def process(
cube: cli.inputcube,
*,
coordinates: cli.comma_separated_list = None,
percentiles: cli.comma_separated_list = None,
ignore_ecc_bounds_exceedance=False,
):
r"""Collapses cube coordinates and calculate percentiled data.
Calculate percentiled data over a given coordinate by collapsing that
coordinate. Typically used to convert realization data into percentiled
data, but may calculate over any dimension coordinate. Alternatively
calling this with a dataset containing probabilities will convert those
to percentiles using the ensemble coupla coupling plugin. If no particular
percentiles are given at which to calculate values and no
'number of percentiles' to calculate are specified, the
following defaults will be used.
'[0, 5, 10, 20, 25, 30, 40, 50, 60, 70, 75, 80, 90, 95, 100]'
Args:
cube (iris.cube.Cube):
A Cube for processing.
coordinates (str or list):
Coordinate or coordinates over which to collapse data and
calculate percentiles; e.g. 'realization' or 'latitude,longitude'.
This argument must be provided when collapsing a coordinate or
coordinates to create percentiles, but is redundant when
converting probabilities to percentiles and may be omitted. This
coordinate(s) will be removed and replaced by a percentile
coordinate.
percentiles (list):
Optional definition of percentiles at which to calculate data.
ignore_ecc_bounds_exceedance (bool):
If True, where calculated percentiles are outside the ECC bounds
range, raises a warning rather than an exception.
Returns:
iris.cube.Cube:
The processed Cube.
Raises:
ValueError:
If the cube name does not contain 'probability_of\_' and
coordinates isn't used.
Warns:
Warning:
If 'probability_of\_' is in the cube name and coordinates is used.
"""
import warnings
import numpy as np
from improver.ensemble_copula_coupling.ensemble_copula_coupling import (
ConvertProbabilitiesToPercentiles,
)
from improver.metadata.probabilistic import is_probability
from improver.percentile import PercentileConverter
if percentiles is not None:
percentiles = [float(p) for p in percentiles]
if is_probability(cube):
result = ConvertProbabilitiesToPercentiles(
ecc_bounds_warning=ignore_ecc_bounds_exceedance
)(cube, percentiles=percentiles)
if coordinates:
warnings.warn(
"Converting probabilities to percentiles. The "
"provided COORDINATES_TO_COLLAPSE variable will "
"not be used."
)
else:
if not coordinates:
raise ValueError(
"To collapse a coordinate to calculate "
"percentiles, a coordinate or list of "
"coordinates must be provided."
)
# Switch back to use the slow scipy method if the cube contains masked
# data which the numpy method cannot handle.
fast_percentile_method = True
if np.ma.is_masked(cube.data):
# Check for masked points:
fast_percentile_method = False
elif np.ma.isMaskedArray(cube.data):
# Check if we have a masked array with an empty mask. If so,
# replace it with a non-masked array:
cube.data = cube.data.data
result = PercentileConverter(
coordinates,
percentiles=percentiles,
fast_percentile_method=fast_percentile_method,
)(cube)
return result