def test_C3STs_tcdr_passive_decadal():
file = os.path.join(
os.path.join(
os.path.dirname(__file__), 'c3s_sm-test-data', 'img', 'TCDR',
'062_dekadalImages', 'passive',
'C3S-SOILMOISTURE-L3S-SSMV-PASSIVE-DEKADAL-20140101000000-TCDR-v201801.0.0.nc'
))
ds = C3SImg(file,
mode='r',
flatten=False,
fillval={
'nobs': -1,
'sm': np.nan
},
subgrid=SMECV_Grid_v052('landcover_class',
subset_value=[10, 11, 60,
70]).subgrid_from_bbox(
-14, 30, 44, 73))
image = ds.read()
test_loc_lonlat = (16.125, 48.125)
row, col = np.where((image.lon == test_loc_lonlat[0])
& (image.lat == test_loc_lonlat[1]))
assert image['nobs'].min() == -1
assert np.any(np.isnan(image['sm']))
nptest.assert_almost_equal(image['sm'][row, col], 0.50875, 4)
assert (image.metadata['sm']['long_name'] == 'Volumetric Soil Moisture')
def test_C3STs_tcdr_active_monthly():
file = os.path.join(
os.path.join(
os.path.dirname(__file__), 'c3s_sm-test-data', 'img', 'TCDR',
'061_monthlyImages', 'active',
'C3S-SOILMOISTURE-L3S-SSMS-ACTIVE-MONTHLY-20140101000000-TCDR-v201801.0.0.nc'
))
ds = C3SImg(file,
mode='r',
parameters='sm',
flatten=False,
fillval=None,
subgrid=SMECV_Grid_v052(None).subgrid_from_bbox(
-181, -91, 181, 91))
image = ds.read()
test_loc_lonlat = (16.375, 48.125)
row, col = np.where((image.lon == test_loc_lonlat[0])
& (image.lat == test_loc_lonlat[1]))
assert image.data['sm'].shape == (720, 1440)
nptest.assert_almost_equal(image.data['sm'][row, col], 47.69982, 4)
assert (image.metadata['sm']['_FillValue'] == -9999.)
assert image.data['sm'].min() == image.metadata['sm']['_FillValue']
assert (image.metadata['sm']['long_name'] ==
'Percent of Saturation Soil Moisture')
def test_1Dreading(subgrid):
# Test 1D reading with and without land grid, and if the results are the same
file = os.path.join(
os.path.join(
os.path.dirname(__file__), 'c3s_sm-test-data', 'img', 'ICDR',
'060_dailyImages', 'combined', '2017',
'C3S-SOILMOISTURE-L3S-SSMV-COMBINED-DAILY-20170701000000-ICDR-v201706.0.0.nc'
))
ds = C3SImg(file, mode='r', parameters=None, flatten=True, subgrid=subgrid)
image = ds.read()
test_loc_lonlat = (75.625, 14.625)
idx = np.where((image.lon == test_loc_lonlat[0])
& (image.lat == test_loc_lonlat[1]))[0]
assert ds.subgrid.find_nearest_gpi(*test_loc_lonlat) == (602942, 0)
ref_sm = image.data['sm'][idx]
ref_lat = image.lat[idx]
ref_lon = image.lon[idx]
assert ref_lat == test_loc_lonlat[1]
assert ref_lon == test_loc_lonlat[0]
nptest.assert_almost_equal(ref_sm, 0.360762, 5)
assert (image.metadata['sm']['long_name'] == 'Volumetric Soil Moisture')
def test_1Dreading():
''' Test 1D reading with and without land grid, and if the results are the same'''
file = os.path.join(
os.path.join(
os.path.dirname(__file__), 'c3s_sm-test-data', 'img', 'ICDR',
'060_dailyImages', 'combined', '2017',
'C3S-SOILMOISTURE-L3S-SSMV-COMBINED-DAILY-20170701000000-ICDR-v201706.0.0.nc'
))
ds = C3SImg(file, mode='r', parameters='sm', array_1D=True)
image = ds.read()
assert ds.grid.find_nearest_gpi(75.625, 14.625) == (602942, 0)
ref_sm = image.data['sm'][434462]
ref_lat = image.lat[434462]
ref_lon = image.lon[434462]
assert ref_lat == 14.625
assert ref_lon == 75.625
nptest.assert_almost_equal(ref_sm, 0.360762, 5)
assert (image.metadata['sm']['long_name'] == 'Volumetric Soil Moisture')
land_grid = C3SLandGrid()
ds = C3SImg(file,
mode='r',
parameters='sm',
array_1D=True,
subgrid=land_grid)
image = ds.read()
assert ds.grid.find_nearest_gpi(75.625, 14.625) == (602942, 0)
sm = image.data['sm'][177048]
lat = image.lat[177048]
lon = image.lon[177048]
assert ref_lat == lat
assert ref_lon == lon
nptest.assert_almost_equal(ref_sm, sm, 5)
assert (image.metadata['sm']['long_name'] == 'Volumetric Soil Moisture')
def test_C33Ts_icdr_passive_decadal():
file = os.path.join(
os.path.join(
os.path.dirname(__file__), 'c3s_sm-test-data', 'img', 'ICDR',
'062_dekadalImages', 'passive',
'C3S-SOILMOISTURE-L3S-SSMV-PASSIVE-DEKADAL-20170701000000-ICDR-v201706.0.0.nc'
))
ds = C3SImg(file, mode='r', parameters='sm', array_1D=False)
image = ds.read()
nptest.assert_almost_equal(image.data['sm'][167, 785], 0.21000, 4)
assert (image.metadata['sm']['long_name'] == 'Volumetric Soil Moisture')
def test_C33Ts_tcdr_combined_daily():
file = os.path.join(
os.path.join(
os.path.dirname(__file__), 'c3s_sm-test-data', 'img', 'TCDR',
'060_dailyImages', 'combined', '2014',
'C3S-SOILMOISTURE-L3S-SSMV-COMBINED-DAILY-20140101000000-TCDR-v201801.0.0.nc'
))
ds = C3SImg(file, mode='r', parameters='sm', array_1D=False)
image = ds.read()
nptest.assert_almost_equal(image.data['sm'][167, 785], 0.34659, 4)
assert (image.metadata['sm']['long_name'] == 'Volumetric Soil Moisture')
def test_C33Ts_icdr_active_monthly():
file = os.path.join(
os.path.join(
os.path.dirname(__file__), 'c3s_sm-test-data', 'img', 'ICDR',
'061_monthlyImages', 'active',
'C3S-SOILMOISTURE-L3S-SSMS-ACTIVE-MONTHLY-20170701000000-ICDR-v201706.0.0.nc'
))
ds = C3SImg(file, mode='r', parameters='sm', array_1D=False)
image = ds.read()
nptest.assert_almost_equal(image.data['sm'][167, 785], 65.00162, 4)
assert (image.metadata['sm']['_FillValue'] == -9999.)
assert (image.metadata['sm']['long_name'] ==
'Percent of Saturation Soil Moisture')
def test_C3STs_icdr_passive_decadal():
file = os.path.join(
os.path.join(
os.path.dirname(__file__), 'c3s_sm-test-data', 'img', 'ICDR',
'062_dekadalImages', 'passive',
'C3S-SOILMOISTURE-L3S-SSMV-PASSIVE-DEKADAL-20170701000000-ICDR-v201706.0.0.nc'
))
ds = C3SImg(file, mode='r', parameters='sm', flatten=False, fillval=np.nan)
image = ds.read()
test_loc_lonlat = (16.375, 48.125)
row, col = np.where((image.lon == test_loc_lonlat[0])
& (image.lat == test_loc_lonlat[1]))
nptest.assert_almost_equal(image.data['sm'][row, col], 0.21000, 4)
assert (image.metadata['sm']['long_name'] == 'Volumetric Soil Moisture')
def test_C3STs_icdr_combined_daily():
file = os.path.join(
os.path.join(
os.path.dirname(__file__), 'c3s_sm-test-data', 'img', 'ICDR',
'060_dailyImages', 'combined', '2017',
'C3S-SOILMOISTURE-L3S-SSMV-COMBINED-DAILY-20170701000000-ICDR-v201706.0.0.nc'
))
ds = C3SImg(file,
mode='r',
parameters=['sm', 't0'],
flatten=False,
subgrid=SMECV_Grid_v052('land'))
image = ds.read()
test_loc_lonlat = (16.375, 48.125)
row, col = np.where((image.lon == test_loc_lonlat[0])
& (image.lat == test_loc_lonlat[1]))
nptest.assert_almost_equal(image.data['sm'][row, col], 0.14548, 4)
assert (image.metadata['t0']['long_name'] == 'Observation Timestamp')
def test_C3STs_tcdr_combined_daily():
file = os.path.join(
os.path.join(
os.path.dirname(__file__), 'c3s_sm-test-data', 'img', 'TCDR',
'060_dailyImages', 'combined', '2014',
'C3S-SOILMOISTURE-L3S-SSMV-COMBINED-DAILY-20140101000000-TCDR-v201801.0.0.nc'
))
ds = C3SImg(file,
mode='r',
parameters=None,
flatten=False,
fillval={'sm': np.nan})
image = ds.read()
test_loc_lonlat = (16.375, 48.125)
row, col = np.where((image.lon == test_loc_lonlat[0])
& (image.lat == test_loc_lonlat[1]))
nptest.assert_almost_equal(image.data['sm'][row, col], 0.34659, 4)
assert (image.metadata['sm']['long_name'] == 'Volumetric Soil Moisture')
def test_C3STs_icdr_active_monthly():
file = os.path.join(
os.path.join(
os.path.dirname(__file__), 'c3s_sm-test-data', 'img', 'ICDR',
'061_monthlyImages', 'active',
'C3S-SOILMOISTURE-L3S-SSMS-ACTIVE-MONTHLY-20170701000000-ICDR-v201706.0.0.nc'
))
ds = C3SImg(file,
mode='r',
parameters=['sm', 'sensor'],
flatten=False,
fillval=-1)
image = ds.read()
assert image['sensor'].min() == image['sm'].min() == -1
test_loc_lonlat = (16.375, 48.125)
row, col = np.where((image.lon == test_loc_lonlat[0])
& (image.lat == test_loc_lonlat[1]))
nptest.assert_almost_equal(image.data['sm'][row, col], 65.00162, 4)
assert (image.metadata['sm']['_FillValue'] == -9999.)
assert (image.metadata['sm']['long_name'] ==
'Percent of Saturation Soil Moisture')