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Fix GPM IMERG reader. #2137

Merged
merged 7 commits into from Jul 7, 2022
Merged

Fix GPM IMERG reader. #2137

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bd26450
Fix GPM IMERG reader.
simonrp84 Jul 6, 2022
d0d1b90
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Jul 6, 2022
887174e
Further fixes for GPM IMERG reader.
simonrp84 Jul 6, 2022
fd7cfa6
Merge remote-tracking branch 'origin/imerg_fix' into imerg_fix
simonrp84 Jul 6, 2022
9c8185c
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Jul 6, 2022
b5f9a1e
Update GPM tests.
simonrp84 Jul 6, 2022
345336d
Merge remote-tracking branch 'origin/imerg_fix' into imerg_fix
simonrp84 Jul 6, 2022
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15 changes: 10 additions & 5 deletions satpy/readers/gpm_imerg.py
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Expand Up @@ -26,6 +26,7 @@
import logging
from datetime import datetime

import dask.array as da
import h5py
import numpy as np
from pyresample.geometry import AreaDefinition
Expand Down Expand Up @@ -69,18 +70,22 @@ def get_dataset(self, dataset_id, ds_info):
"""Load a dataset."""
file_key = ds_info.get('file_key', dataset_id['name'])
dsname = 'Grid/' + file_key
data = self[dsname].squeeze().transpose()
data.values = np.flipud(data.values)
data = self.get(dsname)
data = data.squeeze().transpose()
if data.ndim >= 2:
data = data.rename({data.dims[-2]: 'y', data.dims[-1]: 'x'})
data.data = da.flip(data.data, axis=0)

fill = data.attrs['_FillValue']
pts = (data.values == fill).nonzero()
data.values[pts] = np.nan
data = data.where(data != fill)

for key in list(data.attrs.keys()):
val = data.attrs[key]
if isinstance(val, h5py.h5r.Reference):
del data.attrs[key]

if isinstance(val, np.ndarray):
if isinstance(val[0][0], h5py.h5r.Reference):
del data.attrs[key]
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return data

def get_area_def(self, dsid):
Expand Down
5 changes: 4 additions & 1 deletion satpy/tests/reader_tests/test_gpm_imerg.py
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Expand Up @@ -23,6 +23,7 @@
from unittest import mock

import dask.array as da
import h5py
import numpy as np
import xarray as xr

Expand Down Expand Up @@ -55,12 +56,14 @@ def _get_precip_data(self, num_rows, num_cols):
selection = {
'Grid/IRprecipitation':
xr.DataArray(
da.ones((1, num_rows, num_cols), chunks=1024,
da.ones((1, num_cols, num_rows), chunks=1024,
dtype=np.float32),
attrs={
'_FillValue': -9999.9,
'units': 'mm/hr',
'Units': 'mm/hr',
'badval': h5py.h5r.Reference,
'badvals': np.array([[h5py.h5r.Reference]])
},
dims=('time', 'lon', 'lat')),
}
Expand Down