9347528555

Committed 03 Jun 2024 09:16AM UTC coverage: 92.866% (+5.0%) from 87.87%

Build # 9347528555

Build Type

push

github

Committed by

ghiggi

Commit Message

Generalize checks defaults

Run Details

10 of 10 new or added lines in 1 file covered. (100.0%)

266 existing lines in 25 files now uncovered.

13199 of 14213 relevant lines covered (92.87%)

0.93 hits per line

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96.0

/gpm/dataset/decoding/utils.py

# -----------------------------------------------------------------------------.
# MIT License

# Copyright (c) 2024 GPM-API developers
#
# This file is part of GPM-API.

# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.

# -----------------------------------------------------------------------------.
"""This module contains utilities for the decoding of GPM product variables."""
import dask.array
import numpy as np


def is_dataarray_decoded(da):
    """Check if a `xarray.DataArray` has been decoded by GPM-API."""
    return da.attrs.get("gpm_api_decoded", "no") == "yes"


def add_decoded_flag(ds, variables):
    """Add gpm_api_decoded flag to GPM-API decoded variables."""
    for var in variables:
        if var in ds:
            ds[var].attrs["gpm_api_decoded"] = "yes"
    return ds


# def _np_remap_numeric_array1(arr, remapping_dict, fill_value=np.nan):
#     # VERY SLOW ALTERNATIVE
#     isna = np.isnan(arr)
#     arr[isna] = -1 # dummy
#     unique_values = np.unique(arr[~np.isnan(arr)])
#     _ = [remapping_dict.setdefault(value, fill_value) for value in unique_values if value not in remapping_dict]
#     remapping_dict = {float(k): float(v) for k, v in remapping_dict.items()}
#     new_arr = np.vectorize(remapping_dict.__getitem__)(arr)
#     new_arr[isna] = np.nan
#     return new_arr


def _np_remap_numeric_array(arr, remapping_dict, fill_value=np.nan):
    # Define conditions
    conditions = [arr == i for i in remapping_dict]
    # Define choices corresponding to conditions
    choices = remapping_dict.values()
    # Apply np.select to transform the array
    return np.select(conditions, choices, default=fill_value)


def _dask_remap_numeric_array(arr, remapping_dict, fill_value=np.nan):
    return dask.array.map_blocks(_np_remap_numeric_array, arr, remapping_dict, fill_value, dtype=arr.dtype)


def remap_numeric_array(arr, remapping_dict, fill_value=np.nan):
    """Remap the values of a numeric array."""
    if hasattr(arr, "chunks"):
        return _dask_remap_numeric_array(arr, remapping_dict, fill_value=fill_value)
    return _np_remap_numeric_array(arr, remapping_dict, fill_value=fill_value)


def ceil_dataarray(da):
    """Ceil a `xarray.DataArray`."""
    data = da.data
    data = np.ceil(data) if hasattr(data, "chunks") else dask.array.ceil(data)
    da.data = data
    return da

1	# -----------------------------------------------------------------------------.
2	# MIT License
3
4	# Copyright (c) 2024 GPM-API developers
5	#
6	# This file is part of GPM-API.
7
8	# Permission is hereby granted, free of charge, to any person obtaining a copy
9	# of this software and associated documentation files (the "Software"), to deal
10	# in the Software without restriction, including without limitation the rights
11	# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
12	# copies of the Software, and to permit persons to whom the Software is
13	# furnished to do so, subject to the following conditions:
14	#
15	# The above copyright notice and this permission notice shall be included in all
16	# copies or substantial portions of the Software.
17	#
18	# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
19	# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
20	# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
21	# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
22	# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
23	# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
24	# SOFTWARE.
25
26	# -----------------------------------------------------------------------------.
27	"""This module contains utilities for the decoding of GPM product variables."""	1✔
28	import dask.array	1✔
29	import numpy as np	1✔
30
31
32	def is_dataarray_decoded(da):	1✔
33	"""Check if a `xarray.DataArray` has been decoded by GPM-API."""
34	return da.attrs.get("gpm_api_decoded", "no") == "yes"	1✔
35
36
37	def add_decoded_flag(ds, variables):	1✔
38	"""Add gpm_api_decoded flag to GPM-API decoded variables."""
39	for var in variables:	1✔
40	if var in ds:	1✔
41	ds[var].attrs["gpm_api_decoded"] = "yes"	1✔
42	return ds	1✔
43
44
45	# def _np_remap_numeric_array1(arr, remapping_dict, fill_value=np.nan):
46	# # VERY SLOW ALTERNATIVE
47	# isna = np.isnan(arr)
48	# arr[isna] = -1 # dummy
49	# unique_values = np.unique(arr[~np.isnan(arr)])
50	# _ = [remapping_dict.setdefault(value, fill_value) for value in unique_values if value not in remapping_dict]
51	# remapping_dict = {float(k): float(v) for k, v in remapping_dict.items()}
52	# new_arr = np.vectorize(remapping_dict.__getitem__)(arr)
53	# new_arr[isna] = np.nan
54	# return new_arr
55
56
57	def _np_remap_numeric_array(arr, remapping_dict, fill_value=np.nan):	1✔
58	# Define conditions
59	conditions = [arr == i for i in remapping_dict]	1✔
60	# Define choices corresponding to conditions
61	choices = remapping_dict.values()	1✔
62	# Apply np.select to transform the array
63	return np.select(conditions, choices, default=fill_value)	1✔
64
65
66	def _dask_remap_numeric_array(arr, remapping_dict, fill_value=np.nan):	1✔
67	return dask.array.map_blocks(_np_remap_numeric_array, arr, remapping_dict, fill_value, dtype=arr.dtype)	1✔
68
69
70	def remap_numeric_array(arr, remapping_dict, fill_value=np.nan):	1✔
71	"""Remap the values of a numeric array."""
72	if hasattr(arr, "chunks"):	1✔
73	return _dask_remap_numeric_array(arr, remapping_dict, fill_value=fill_value)	1✔
UNCOV 74	return _np_remap_numeric_array(arr, remapping_dict, fill_value=fill_value)	×
75
76
77	def ceil_dataarray(da):	1✔
78	"""Ceil a `xarray.DataArray`."""
79	data = da.data	1✔
80	data = np.ceil(data) if hasattr(data, "chunks") else dask.array.ceil(data)	1✔
81	da.data = data	1✔
82	return da	1✔

ghiggi / gpm_api / 9347528555

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