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# Copyright (c) 2018-2025 by xcube team and contributors
# Permissions are hereby granted under the terms of the MIT License:
# https://opensource.org/licenses/MIT.
import unittest
import numpy as np
import xarray as xr
from xcube_resampling.gridmapping import CRS_WGS84, GridMapping
from xcube_resampling.spatial import resample_in_space
from .sampledata import (
create_2x2_dataset_with_irregular_coords,
create_4x4_dataset_with_irregular_coords,
create_5x5_dataset_regular_utm,
create_8x6_dataset_with_regular_coords,
)
nan = np.nan
# noinspection PyMethodMayBeStatic
class ResampleInSpaceTest(unittest.TestCase):
def test_affine_transform_dataset(self):
source_ds = create_8x6_dataset_with_regular_coords()
source_gm = GridMapping.from_dataset(source_ds)
target_gm = GridMapping.regular((3, 3), (50.05, 10.05), 0.1, source_gm.crs)
target_ds = resample_in_space(
source_ds,
target_gm=target_gm,
interp_methods=1,
)
self.assertIsInstance(target_ds, xr.Dataset)
self.assertEqual(
set(source_ds.variables).union(["spatial_ref"]),
set(target_ds.variables),
)
self.assertEqual((3, 3), target_ds.refl.shape)
np.testing.assert_almost_equal(
target_ds.refl.values,
np.array(
[
[1, 0, 2],
[0, 3, 0],
[4, 0, 1],
]
),
)
def test_rectify_and_downscale_dataset(self):
source_ds = create_4x4_dataset_with_irregular_coords()
# nearest neighbour interpolation
target_gm = GridMapping.regular(
size=(2, 2), xy_min=(0, 52), xy_res=2, crs=CRS_WGS84
)
target_ds = resample_in_space(source_ds, target_gm=target_gm, interp_methods=0)
np.testing.assert_almost_equal(
target_ds.rad.values,
np.array(
[
[5, 2],
[10, 7],
],
dtype=target_ds.rad.dtype,
),
)
# bi-linear interpolation
target_ds = resample_in_space(source_ds, target_gm=target_gm, interp_methods=1)
np.testing.assert_almost_equal(
target_ds.rad.values,
np.array(
[
[7.5, 4.5],
[12.5, 9.5],
],
dtype=target_ds.rad.dtype,
),
)
# shifted target grid
target_gm = GridMapping.regular(
size=(2, 2), xy_min=(0, 50), xy_res=2, crs=CRS_WGS84
)
target_ds = resample_in_space(source_ds, target_gm=target_gm, interp_methods=0)
np.testing.assert_almost_equal(
target_ds.rad.values,
np.array(
[
[10, 7],
[nan, nan],
],
dtype=target_ds.rad.dtype,
),
)
def test_rectify_and_upscale_dataset(self):
source_ds = create_2x2_dataset_with_irregular_coords()
target_gm = GridMapping.regular(
size=(4, 4), xy_min=(0, 50), xy_res=2, crs=CRS_WGS84
)
target_ds = resample_in_space(source_ds, target_gm=target_gm, interp_methods=0)
np.testing.assert_almost_equal(
target_ds.rad.values,
np.array(
[
[nan, nan, nan, nan],
[nan, 1.0, 2.0, nan],
[3.0, 3.0, 2.0, nan],
[nan, 4.0, nan, nan],
],
dtype=target_ds.rad.dtype,
),
)
def test_reproject_dataset(self):
source_ds = create_5x5_dataset_regular_utm()
# test projected CRS similar resolution
target_gm = GridMapping.regular(
size=(5, 5), xy_min=(4320120, 3382520), xy_res=80, crs="epsg:3035"
)
target_ds = resample_in_space(source_ds, target_gm=target_gm, interp_methods=0)
np.testing.assert_almost_equal(
target_ds.band_1.values,
np.array(
[
[1, 1, 2, 3, 4],
[6, 6, 7, 8, 9],
[11, 12, 12, 13, 14],
[16, 17, 17, 18, 19],
[21, 17, 17, 18, 19],
],
dtype=target_ds.band_1.dtype,
),
)
# test projected CRS finer resolution
# test if subset calculation works as expected
target_gm = GridMapping.regular(
size=(5, 5), xy_min=(4320090, 3382490), xy_res=20, crs="epsg:3035"
)
target_ds = resample_in_space(source_ds, target_gm=target_gm, interp_methods=0)
np.testing.assert_almost_equal(
target_ds.band_1.values,
np.array(
[
[15, 16, 16, 16, 16],
[15, 16, 16, 16, 16],
[15, 16, 16, 16, 16],
[20, 21, 21, 21, 21],
[20, 21, 21, 21, 21],
],
dtype=target_ds.band_1.dtype,
),
)
# test geographic CRS with similar resolution
target_gm = GridMapping.regular(
size=(5, 5), xy_min=(9.9889, 53.5502), xy_res=0.0006, crs=CRS_WGS84
)
target_ds = resample_in_space(source_ds, target_gm=target_gm, interp_methods=0)
np.testing.assert_almost_equal(
target_ds.band_1.values,
np.array(
[
[7, 8, 8, 8, 9],
[12, 13, 13, 13, 14],
[12, 13, 13, 13, 14],
[17, 18, 18, 18, 19],
[22, 23, 23, 23, 24],
],
dtype=target_ds.band_1.dtype,
),
)
# test geographic CRS with 1/2 resolution
# test if subset calculation works as expected
target_gm = GridMapping.regular(
size=(5, 5), xy_min=(9.98875, 53.55005), xy_res=0.0003, crs=CRS_WGS84
)
target_ds = resample_in_space(source_ds, target_gm=target_gm, interp_methods=0)
np.testing.assert_almost_equal(
target_ds.band_1.values,
np.array(
[
[12, 12, 12, 13, 13],
[17, 17, 17, 18, 18],
[17, 17, 17, 18, 18],
[22, 17, 17, 18, 18],
[22, 22, 22, 23, 23],
],
dtype=target_ds.band_1.dtype,
),
)
def test_resample_in_space_raise_logs(self):
source_ds = create_5x5_dataset_regular_utm()
with self.assertLogs("xcube.resampling", level="WARNING") as cm:
_ = resample_in_space(source_ds)
self.assertIn(
"If source grid mapping is regular `target_gm` must be given. "
"Source dataset is returned.",
cm.output[0],
)
def test_resample_in_space_return_input_dataset(self):
source_ds = create_5x5_dataset_regular_utm()
target_gm = GridMapping.from_dataset(source_ds)
target_ds = resample_in_space(source_ds, target_gm=target_gm)
xr.testing.assert_equal(target_ds, source_ds)
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