Source code for improver.between_thresholds
# (C) Crown Copyright, Met Office. All rights reserved.
#
# This file is part of 'IMPROVER' and is released under the BSD 3-Clause license.
# See LICENSE in the root of the repository for full licensing details.
"""Plugin to calculate probabilities of occurrence between specified thresholds"""
from typing import List
import iris
import numpy as np
from cf_units import Unit
from iris.cube import Cube
from iris.exceptions import CoordinateNotFoundError
from improver import PostProcessingPlugin
from improver.metadata.probabilistic import (
find_threshold_coordinate,
probability_is_above_or_below,
)
[docs]
class OccurrenceBetweenThresholds(PostProcessingPlugin):
"""Calculate the probability of occurrence between thresholds"""
[docs]
def __init__(
self, threshold_ranges: List[List[float]], threshold_units: str
) -> None:
"""
Initialise the class. Threshold ranges must be specified in a unit
that is NOT sensitive to differences at the 1e-5 (float32) precision
level.
Args:
threshold_ranges:
List of 2-item iterables specifying thresholds between which
probabilities should be calculated
threshold_units:
Units in which the thresholds are specified
Raises:
ValueError:
If any of the specified thresholds are indistinguishable at the
1e-5 (float32) precision level
"""
threshold_diffs = np.diff(threshold_ranges)
if any(diff < 1e-5 for diff in threshold_diffs):
raise ValueError(
"Plugin cannot distinguish between thresholds at {} {}".format(
threshold_ranges, threshold_units
)
)
self.threshold_ranges = threshold_ranges
self.threshold_units = threshold_units
[docs]
def _slice_cube(self) -> List[List[Cube]]:
"""
Extract required slices from input cube
Returns:
List of 2-item lists containing lower and upper
threshold cubes
Raises:
ValueError:
If any of the required constraints returns None
"""
thresh_coord = self.cube.coord(self.thresh_coord.name())
error_string = (
f"{thresh_coord.name()} threshold {{}} {self.threshold_units} "
"is not available\n"
)
error_msg = ""
cubes = []
for t_range in self.threshold_ranges:
t_range.sort()
lower_constraint = iris.Constraint(
coord_values={
thresh_coord: lambda t: np.isclose(t.point, t_range[0], atol=1e-5)
}
)
lower_cube = self.cube.extract(lower_constraint)
if lower_cube is None:
error_msg += error_string.format(t_range[0])
upper_constraint = iris.Constraint(
coord_values={
thresh_coord: lambda t: np.isclose(t.point, t_range[1], atol=1e-5)
}
)
upper_cube = self.cube.extract(upper_constraint)
if upper_cube is None:
error_msg += error_string.format(t_range[1])
cubes.append([lower_cube, upper_cube])
if error_msg:
# if any thresholds were unavailable, raise errors together here
raise ValueError(error_msg)
return cubes
[docs]
def _get_multiplier(self) -> np.float32:
"""
Check whether the cube contains "above" or "below" threshold
probabilities. For "above", the probability of occurrence between
thresholds is the difference between probabilities at the lower
and higher thresholds: P(lower) - P(higher). For "below" it is the
inverse of this: P(higher) - P(lower), which is implemented by
multiplying the difference by -1.
Returns:
1. or -1.
Raises:
ValueError: If the spp__relative_to_threshold attribute is
not recognised
"""
relative_to_threshold = probability_is_above_or_below(self.cube)
if relative_to_threshold == "above":
multiplier = 1.0
elif relative_to_threshold == "below":
multiplier = -1.0
else:
raise ValueError(
"Input cube must contain probabilities of "
"occurrence above or below threshold"
)
return np.float32(multiplier)
[docs]
def _calculate_probabilities(self) -> Cube:
"""
Calculate between_threshold probabilities cube
Returns:
Merged cube containing recalculated probabilities
"""
multiplier = self._get_multiplier()
thresh_name = self.thresh_coord.name()
cubelist = iris.cube.CubeList([])
for lower_cube, upper_cube in self.cube_slices:
# construct difference cube
between_thresholds_data = (lower_cube.data - upper_cube.data) * multiplier
between_thresholds_cube = upper_cube.copy(between_thresholds_data)
# add threshold coordinate bounds
lower_threshold = lower_cube.coord(thresh_name).points[0]
upper_threshold = upper_cube.coord(thresh_name).points[0]
between_thresholds_cube.coord(thresh_name).bounds = [
lower_threshold,
upper_threshold,
]
cubelist.append(between_thresholds_cube)
return cubelist.merge_cube()
[docs]
def process(self, cube: Cube) -> Cube:
"""
Calculate probabilities between thresholds for the input cube
Args:
cube:
Probability cube containing thresholded data (above or below)
Returns:
Cube containing probability of occurrence between thresholds
"""
# if cube has no threshold-type coordinate, raise an error
try:
self.thresh_coord = find_threshold_coordinate(cube)
except CoordinateNotFoundError:
raise ValueError(
"Input is not a probability cube (has no threshold-type coordinate)"
)
self.cube = cube.copy()
# check input cube units and convert if needed
original_units = self.thresh_coord.units
if original_units != self.threshold_units:
self.cube.coord(self.thresh_coord).convert_units(self.threshold_units)
# extract suitable cube slices
self.cube_slices = self._slice_cube()
# generate "between thresholds" probabilities
output_cube = self._calculate_probabilities()
self._update_metadata(output_cube, original_units)
return output_cube
