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import os
import pytest
import xarray
from numpy import nansum
from numpy.testing import assert_almost_equal
from rioxarray import open_rasterio
from rioxarray.merge import merge_arrays, merge_datasets
from test.conftest import TEST_INPUT_DATA_DIR
@pytest.mark.parametrize("squeeze", [True, False])
def test_merge_arrays(squeeze):
dem_test = os.path.join(TEST_INPUT_DATA_DIR, "MODIS_ARRAY.nc")
with open_rasterio(dem_test) as rds:
rds.attrs = {
"_FillValue": rds.rio.nodata,
}
arrays = [
rds.isel(x=slice(100), y=slice(100)),
rds.isel(x=slice(100, 200), y=slice(100, 200)),
rds.isel(x=slice(100), y=slice(100, 200)),
rds.isel(x=slice(100, 200), y=slice(100)),
]
if squeeze:
arrays = [array.squeeze() for array in arrays]
merged = merge_arrays(arrays)
assert_almost_equal(
merged.rio.bounds(),
(-7274009.6494863, 5003777.3385, -7227678.3778335, 5050108.6101528),
)
assert merged.rio.shape == (200, 200)
assert_almost_equal(merged.sum(), 22865733)
assert_almost_equal(
tuple(merged.rio.transform()),
(
231.6563582639536,
0.0,
-7274009.649486291,
0.0,
-231.65635826374404,
5050108.61015275,
0.0,
0.0,
1.0,
),
)
assert merged.rio._cached_transform() == merged.rio.transform()
assert sorted(merged.coords) == sorted(rds.coords)
assert merged.coords["band"].values == [1]
assert merged.rio.crs == rds.rio.crs
assert merged.attrs == rds.attrs
assert merged.encoding["grid_mapping"] == "spatial_ref"
@pytest.mark.parametrize("dataset", [True, False])
def test_merge__different_crs(dataset):
dem_test = os.path.join(TEST_INPUT_DATA_DIR, "MODIS_ARRAY.nc")
with (
xarray.open_dataset(dem_test, mask_and_scale=False)
if dataset
else xarray.open_dataarray(dem_test, mask_and_scale=False)
) as rds:
crs = rds.rio.crs
arrays = [
rds.isel(x=slice(100), y=slice(100)).rio.reproject("EPSG:3857"),
rds.isel(x=slice(100, 200), y=slice(100, 200)),
rds.isel(x=slice(100), y=slice(100, 200)),
rds.isel(x=slice(100, 200), y=slice(100)),
]
if dataset:
merged = merge_datasets(arrays, crs=crs)
else:
merged = merge_arrays(arrays, crs=crs)
if dataset:
test_sum = merged[merged.rio.vars[0]].sum()
else:
test_sum = merged.sum()
assert_almost_equal(
merged.rio.bounds(),
(-7300984.0238134, 5003618.5908794, -7224054.1109682, 5050108.6101528),
)
assert merged.rio.shape == (84, 139)
assert_almost_equal(test_sum, -131734881)
assert_almost_equal(
tuple(merged.rio.transform()),
(
553.4526103969893,
0.0,
-7300984.023813409,
0.0,
-553.4526103969796,
5050108.610152751,
0.0,
0.0,
1.0,
),
)
assert sorted(merged.coords) == sorted(list(rds.coords) + ["spatial_ref"])
assert merged.rio.crs == rds.rio.crs
if not dataset:
assert merged.attrs == {
"_FillValue": -28672,
}
assert merged.encoding["grid_mapping"] == "spatial_ref"
def test_merge_arrays__res():
dem_test = os.path.join(TEST_INPUT_DATA_DIR, "MODIS_ARRAY.nc")
with open_rasterio(dem_test, masked=True) as rds:
arrays = [
rds.isel(x=slice(100), y=slice(100)),
rds.isel(x=slice(100, 200), y=slice(100, 200)),
rds.isel(x=slice(100), y=slice(100, 200)),
rds.isel(x=slice(100, 200), y=slice(100)),
]
merged = merge_arrays(arrays, res=(300, 300))
assert_almost_equal(
merged.rio.bounds(),
(-7274009.6494863, 5003608.6101528, -7227509.6494863, 5050108.6101528),
)
assert merged.rio.shape == (155, 155)
assert_almost_equal(
tuple(merged.rio.transform()),
(
300.0,
0.0,
-7274009.649486291,
0.0,
-300.0,
5050108.61015275,
0.0,
0.0,
1.0,
),
)
assert merged.rio._cached_transform() == merged.rio.transform()
assert sorted(merged.coords) == sorted(rds.coords)
assert merged.coords["band"].values == [1]
assert merged.rio.crs == rds.rio.crs
assert_almost_equal(merged.rio.nodata, rds.rio.nodata)
assert_almost_equal(merged.rio.encoded_nodata, rds.rio.encoded_nodata)
assert merged.encoding["grid_mapping"] == "spatial_ref"
assert_almost_equal(nansum(merged), 13760565)
@pytest.mark.xfail(os.name == "nt", reason="On windows the merged data is different.")
def test_merge_datasets():
dem_test = os.path.join(
TEST_INPUT_DATA_DIR, "MOD09GA.A2008296.h14v17.006.2015181011753.hdf"
)
with open_rasterio(dem_test, group="MODIS_Grid_500m_2D") as rds:
datasets = [
rds.isel(x=slice(600), y=slice(600)),
rds.isel(x=slice(600, None), y=slice(600, None)),
rds.isel(x=slice(600), y=slice(600, None)),
rds.isel(x=slice(600, None), y=slice(600)),
]
merged = merge_datasets(datasets)
data_vars = sorted(merged.data_vars)
assert data_vars == [
"QC_500m_1",
"iobs_res_1",
"num_observations_500m",
"obscov_500m_1",
"sur_refl_b01_1",
"sur_refl_b02_1",
"sur_refl_b03_1",
"sur_refl_b04_1",
"sur_refl_b05_1",
"sur_refl_b06_1",
"sur_refl_b07_1",
]
data_var = data_vars[0]
assert_almost_equal(
merged[data_var].rio.bounds(),
(-4447802.078667, -10007554.677, -3335851.559, -8895604.157333),
)
assert merged.rio.shape == (2400, 2400)
assert_almost_equal(
tuple(merged[data_var].rio.transform()),
(
463.3127165279158,
0.0,
-4447802.078667,
0.0,
-463.3127165279151,
-8895604.157333,
0.0,
0.0,
1.0,
),
)
assert sorted(merged.coords) == sorted(rds.coords)
assert merged.coords["band"].values == [1]
assert merged.rio.crs == rds.rio.crs
assert merged.attrs == rds.attrs
assert merged.encoding["grid_mapping"] == "spatial_ref"
assert_almost_equal(merged[data_var].sum(), 4539666606551516)
@pytest.mark.xfail(os.name == "nt", reason="On windows the merged data is different.")
def test_merge_datasets__res():
dem_test = os.path.join(
TEST_INPUT_DATA_DIR, "MOD09GA.A2008296.h14v17.006.2015181011753.hdf"
)
with open_rasterio(dem_test, group="MODIS_Grid_500m_2D") as rds:
datasets = [
rds.isel(x=slice(1200), y=slice(1200)),
rds.isel(x=slice(1200, None), y=slice(1200, None)),
rds.isel(x=slice(1200), y=slice(1200, None)),
rds.isel(x=slice(1200, None), y=slice(1200)),
]
merged = merge_datasets(datasets, res=1000)
data_vars = sorted(merged.data_vars)
assert data_vars == [
"QC_500m_1",
"iobs_res_1",
"num_observations_500m",
"obscov_500m_1",
"sur_refl_b01_1",
"sur_refl_b02_1",
"sur_refl_b03_1",
"sur_refl_b04_1",
"sur_refl_b05_1",
"sur_refl_b06_1",
"sur_refl_b07_1",
]
data_var = data_vars[0]
assert_almost_equal(
merged[data_var].rio.bounds(),
(-4447802.078667, -10007604.157333, -3335802.078667, -8895604.157333),
)
assert_almost_equal(
tuple(merged[data_var].rio.transform()),
(
1000.0,
0.0,
-4447802.078667,
0.0,
-1000.0,
-8895604.157333,
0.0,
0.0,
1.0,
),
)
assert merged.rio.shape == (1112, 1112)
assert merged.coords["band"].values == [1]
assert sorted(merged.coords) == sorted(rds.coords)
assert merged.rio.crs == rds.rio.crs
assert merged.attrs == rds.attrs
assert merged.encoding["grid_mapping"] == "spatial_ref"
assert_almost_equal(merged[data_var].sum(), 974566547463955)
@pytest.mark.parametrize("mask_and_scale", [True, False])
def test_merge_datasets__mask_and_scale(mask_and_scale):
test_file = os.path.join(TEST_INPUT_DATA_DIR, "tmmx_20190121.nc")
with open_rasterio(test_file, mask_and_scale=mask_and_scale) as rds:
rds = rds.to_dataset()
datasets = [
rds.isel(x=slice(100), y=slice(100)),
rds.isel(x=slice(100, None), y=slice(100, None)),
rds.isel(x=slice(100), y=slice(100, None)),
rds.isel(x=slice(100, None), y=slice(100)),
]
merged = merge_datasets(datasets)
assert sorted(merged.coords) == sorted(list(rds.coords))
total = merged.air_temperature.sum()
if mask_and_scale:
assert_almost_equal(total, 133376696)
else:
assert_almost_equal(total, 10981781386)
def test_merge_datasets__preserve_dimension_names():
sentinel_2_geographic = os.path.join(
TEST_INPUT_DATA_DIR, "sentinel_2_L1C_geographic.nc"
)
with xarray.open_dataset(sentinel_2_geographic) as mda:
merged = merge_datasets([mda])
assert sorted(merged.coords) == sorted(mda.coords)
for data_var in mda.data_vars:
assert_almost_equal(merged[data_var].sum(), mda[data_var].sum())
assert merged.rio.crs == mda.rio.crs
|
