Remove PR old association #63
GitHub Actions / Regression test results for ops
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Sep 19, 2024 in 0s
15 errors, 50 fail, 523 pass in 1h 33m 4s
588 tests 523 ✅ 1h 33m 4s ⏱️
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1 files 50 ❌ 15 🔥
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Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1918209846-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 58s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C1918209846-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1918209846-GES_DISC', 'concept-id': 'G3243059190-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1918209846-GES_DISC'}]}, 'meta': {'association-details': {'collect...tracted from _FillValue metadata attribute', 'Type': 'SCIENCE_FILLVALUE', 'Value': 9.969209968386869e+36}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw1/test_spatial_subset_C1918209840')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f77baf2b240>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f77baf2ac40>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7f77baf2ab40>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G3243059190-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1918209846-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.2593%3A-67.37270000000001%29&subset=lon%28-167.512925%3A153.855925%29&granuleId=G3243059190-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job 735be73f-a804-480d-829b-a9df2e23562b
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw1/test_spatial_subset_C1918209840/77291074_S5P_OFFL_L2_O3_20240917T081741_20240917T095911_35908_03_020601_20240919T001255_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1627516298-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 1m 7s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C1627516298-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1627516298-GES_DISC', 'concept-id': 'G2087797426-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1627516298-GES_DISC'}]}, 'meta': {'association-details': {'collect..., 'Version': '1.9.0'}, 'Name': 'METADATA/QA_STATISTICS/nitrogendioxide_tropospheric_column_histogram_axis', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw6/test_spatial_subset_C1627516290')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7fe1519d0440>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7fe1519d2240>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7fe1519d2140>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G2087797426-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1627516298-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-76.82889999999999%3A-59.7251%29&subset=lon%28-77.22455%3A-1.6634499999999974%29&granuleId=G2087797426-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job 3219a585-c73a-47e0-9b86-d92233ba3a86
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw6/test_spatial_subset_C1627516290/77291098_S5P_OFFL_L2_NO2_20210701T170324_20210701T184453_19257_01_010400_20210703T102341_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2832224417-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 54s]
Raw output
Failed: Unable to find latitude and longitude variables.
collection_concept_id = 'C2832224417-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2832224417-POCLOUD', 'concept-id': 'G3242889404-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2832224417-POCLOUD'}]}, 'meta': {'association-details': {'collecti...me': 'look', 'Size': 2, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -9999.0}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw2/test_spatial_subset_C2832224410')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
> lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
verify_collection.py:406:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
dataset = <xarray.Dataset> Size: 232B
Dimensions: (ydim_grid: 1, xdim_grid: 1, look: 1,
... -0.43
history_json: [{"date_time": "2024-...
file_to_subset = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw2/test_spatial_subset_C2832224410/77291100_RSS_SMAP_SSS_L2C_r51457_20240918T230141_2024262_NRT_V06.0_001.nc4')
collection_variable_list = [{'associations': {'collections': [{'concept-id': 'C2832224417-POCLOUD'}]}, 'meta': {'association-details': {'collecti...me': 'look', 'Size': 2, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -9999.0}], ...}}, ...]
collection_concept_id = 'C2832224417-POCLOUD'
def get_lat_lon_var_names(dataset: xarray.Dataset, file_to_subset: str, collection_variable_list: List[Dict], collection_concept_id: str):
# Try getting it from UMM-Var first
lat_var_json, lon_var_json, _ = get_coordinate_vars_from_umm(collection_variable_list)
lat_var_name = get_variable_name_from_umm_json(lat_var_json)
lon_var_name = get_variable_name_from_umm_json(lon_var_json)
if lat_var_name and lon_var_name:
return lat_var_name, lon_var_name
logging.warning("Unable to find lat/lon vars in UMM-Var")
# If that doesn't work, try using cf-xarray to infer lat/lon variable names
try:
latitude = [lat for lat in dataset.cf.coordinates['latitude']
if lat.lower() in VALID_LATITUDE_VARIABLE_NAMES][0]
longitude = [lon for lon in dataset.cf.coordinates['longitude']
if lon.lower() in VALID_LONGITUDE_VARIABLE_NAMES][0]
return latitude, longitude
except:
logging.warning("Unable to find lat/lon vars using cf_xarray")
# If that still doesn't work, try using l2ss-py directly
try:
# file not able to be flattened unless locally downloaded
filename = f'my_copy_file_{collection_concept_id}.nc'
shutil.copy(file_to_subset, filename)
nc_dataset = netCDF4.Dataset(filename, mode='r+')
# flatten the dataset
nc_dataset_flattened = podaac.subsetter.group_handling.transform_grouped_dataset(nc_dataset, filename)
args = {
'decode_coords': False,
'mask_and_scale': False,
'decode_times': False
}
with xarray.open_dataset(
xarray.backends.NetCDF4DataStore(nc_dataset_flattened),
**args
) as flat_dataset:
# use l2ss-py to find lat and lon names
lat_var_names, lon_var_names = podaac.subsetter.subset.compute_coordinate_variable_names(flat_dataset)
os.remove(filename)
if lat_var_names and lon_var_names:
lat_var_name = lat_var_names.split('__')[-1] if isinstance(lat_var_names, str) else lat_var_names[0].split('__')[-1]
lon_var_name = lon_var_names.split('__')[-1] if isinstance(lon_var_names, str) else lon_var_names[0].split('__')[-1]
return lat_var_name, lon_var_name
except ValueError:
logging.warning("Unable to find lat/lon vars using l2ss-py")
# Still no dice, try using the 'units' variable attribute
for coord_name, coord in dataset.coords.items():
if 'units' not in coord.attrs:
continue
if coord.attrs['units'] == 'degrees_north' and lat_var_name is None:
lat_var_name = coord_name
if coord.attrs['units'] == 'degrees_east' and lon_var_name is None:
lon_var_name = coord_name
if lat_var_name and lon_var_name:
return lat_var_name, lon_var_name
else:
logging.warning("Unable to find lat/lon vars using 'units' attribute")
# Out of options, fail the test because we couldn't determine lat/lon variables
> pytest.fail(f"Unable to find latitude and longitude variables.")
E Failed: Unable to find latitude and longitude variables.
verify_collection.py:359: Failed
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G3242889404-POCLOUD for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C2832224417-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-82.70845%3A65.24645000000001%29&subset=lon%284.511700000000005%3A175.50029999999998%29&granuleId=G3242889404-POCLOUD
INFO root:verify_collection.py:393 Submitted harmony job 9bfa2ebf-9aef-4836-9579-ac34571f2c1e
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw2/test_spatial_subset_C2832224410/77291100_RSS_SMAP_SSS_L2C_r51457_20240918T230141_2024262_NRT_V06.0_001.nc4
WARNING root:verify_collection.py:302 Unable to find lat/lon vars in UMM-Var
WARNING root:verify_collection.py:312 Unable to find lat/lon vars using cf_xarray
WARNING root:verify_collection.py:343 Unable to find lat/lon vars using l2ss-py
WARNING root:verify_collection.py:356 Unable to find lat/lon vars using 'units' attribute
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1729925806-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 50s]
Raw output
assert False
collection_concept_id = 'C1729925806-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1729925806-GES_DISC', 'concept-id': 'G3242926920-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1729925806-GES_DISC'}]}, 'meta': {'association-details': {'collect...': [{'Type': 'SCIENCE_FILLVALUE', 'Value': 513}], 'LongName': 'HDFEOS/SWATHS/O3 column/Data Fields/Status', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C1729925800')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
group_walk(f.groups, f, '')
assert lat_var_name and lon_var_name
var_ds = None
msk = None
science_vars = get_science_vars(collection_variables)
if science_vars:
for var in science_vars:
science_var_name = var['umm']['Name']
var_ds = find_variable(subsetted_ds_new, science_var_name)
if var_ds is not None:
try:
msk = np.logical_not(np.isnan(var_ds.data.squeeze()))
break
except Exception:
continue
else:
var_ds, msk = None, None
else:
for science_var_name in subsetted_ds_new.variables:
if (str(science_var_name) not in lat_var_name and
str(science_var_name) not in lon_var_name and
'time' not in str(science_var_name)):
var_ds = find_variable(subsetted_ds_new, science_var_name)
if var_ds is not None:
try:
msk = np.logical_not(np.isnan(var_ds.data.squeeze()))
break
except Exception:
continue
else:
var_ds, msk = None, None
if var_ds is None or msk is None:
pytest.fail("Unable to find variable from umm-v to use as science variable.")
try:
msk = np.logical_not(np.isnan(var_ds.data.squeeze()))
llat = subsetted_ds_new[lat_var_name].where(msk)
llon = subsetted_ds_new[lon_var_name].where(msk)
except ValueError:
llat = subsetted_ds_new[lat_var_name]
llon = subsetted_ds_new[lon_var_name]
lat_max = llat.max()
lat_min = llat.min()
lon_min = llon.min()
lon_max = llon.max()
lon_min = (lon_min + 180) % 360 - 180
lon_max = (lon_max + 180) % 360 - 180
lat_var_fill_value = subsetted_ds_new[lat_var_name].encoding.get('_FillValue')
lon_var_fill_value = subsetted_ds_new[lon_var_name].encoding.get('_FillValue')
if lat_var_fill_value:
if (lat_max <= north or np.isclose(lat_max, north)) and (lat_min >= south or np.isclose(lat_min, south)):
logging.info("Successful Latitude subsetting")
elif np.isnan(lat_max) and np.isnan(lat_min):
logging.info("Partial Lat Success - no Data")
else:
assert False
if lon_var_fill_value:
if (lon_max <= east or np.isclose(lon_max, east)) and (lon_min >= west or np.isclose(lon_min, west)):
logging.info("Successful Longitude subsetting")
elif np.isnan(lon_max) and np.isnan(lon_min):
logging.info("Partial Lon Success - no Data")
else:
> assert False
E assert False
verify_collection.py:522: AssertionError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G3242926920-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1729925806-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.5%3A85.5%29&subset=lon%28-171.0%3A171.0%29&granuleId=G3242926920-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job 2f4d27e3-8a59-44ec-a539-9ab23fb8f0d4
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C1729925800/77291108_MLS-Aura_L2GP-O3_v05-03-c01_2024d261_subsetted.nc4
INFO root:verify_collection.py:510 Successful Latitude subsetting
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2601581863-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 3s]
Raw output
Exception: ('Unprocessable Entity', 'Error: the requested combination of operations: spatial subsetting on C2601581863-POCLOUD is unsupported')
collection_concept_id = 'C2601581863-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2601581863-POCLOUD', 'concept-id': 'G2816589710-POCLOUD', 'concept-type': 'granul...122T003749_PIC0_02.nc', 'SWOT_L2_LR_PreCalSSH_WindWave_006_545_20231121T234622_20231122T003750_PIC0_02.nc', ...], ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2601581863-POCLOUD'}]}, 'meta': {'association-details': {'collecti...pixels', 'Size': 71, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': 2147483647}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw0/test_spatial_subset_C2601581860')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
> job_id = harmony_client.submit(harmony_request)
verify_collection.py:392:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:851: in submit
self._handle_error_response(response)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7f39a44b6f20>
response = <Response [422]>
def _handle_error_response(self, response: Response):
"""Raises the appropriate exception based on the response
received from Harmony. Tries to pull out an error message
from a Harmony JSON response when possible.
Args:
response: The Response from Harmony
Raises:
Exception with a Harmony error message or a more generic
HTTPError
"""
if 'application/json' in response.headers.get('Content-Type', ''):
exception_message = None
try:
response_json = response.json()
if hasattr(response_json, 'get'):
exception_message = response_json.get('description')
if not exception_message:
exception_message = response_json.get('error')
except JSONDecodeError:
pass
if exception_message:
> raise Exception(response.reason, exception_message)
E Exception: ('Unprocessable Entity', 'Error: the requested combination of operations: spatial subsetting on C2601581863-POCLOUD is unsupported')
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:784: Exception
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G2816589710-POCLOUD for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C2601581863-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.5%3A85.5%29&subset=lon%28-171.0%3A171.0%29&granuleId=G2816589710-POCLOUD
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2601584109-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 8s]
Raw output
Exception: ('Unprocessable Entity', 'Error: the requested combination of operations: spatial subsetting on C2601584109-POCLOUD is unsupported')
collection_concept_id = 'C2601584109-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2601584109-POCLOUD', 'concept-id': 'G2816589757-POCLOUD', 'concept-type': 'granul...122T003749_PIC0_02.nc', 'SWOT_L2_LR_PreCalSSH_WindWave_006_545_20231121T234622_20231122T003750_PIC0_02.nc', ...], ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2601584109-POCLOUD'}]}, 'meta': {'association-details': {'collecti...'num_pixels', 'Size': 71, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': 32767}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw7/test_spatial_subset_C2601584100')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
> job_id = harmony_client.submit(harmony_request)
verify_collection.py:392:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:851: in submit
self._handle_error_response(response)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7f3a7da64880>
response = <Response [422]>
def _handle_error_response(self, response: Response):
"""Raises the appropriate exception based on the response
received from Harmony. Tries to pull out an error message
from a Harmony JSON response when possible.
Args:
response: The Response from Harmony
Raises:
Exception with a Harmony error message or a more generic
HTTPError
"""
if 'application/json' in response.headers.get('Content-Type', ''):
exception_message = None
try:
response_json = response.json()
if hasattr(response_json, 'get'):
exception_message = response_json.get('description')
if not exception_message:
exception_message = response_json.get('error')
except JSONDecodeError:
pass
if exception_message:
> raise Exception(response.reason, exception_message)
E Exception: ('Unprocessable Entity', 'Error: the requested combination of operations: spatial subsetting on C2601584109-POCLOUD is unsupported')
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:784: Exception
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G2816589757-POCLOUD for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C2601584109-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.5%3A85.5%29&subset=lon%28-171.0%3A171.0%29&granuleId=G2816589757-POCLOUD
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1627516292-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 2m 12s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C1627516292-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1627516292-GES_DISC', 'concept-id': 'G1898261144-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1627516292-GES_DISC'}]}, 'meta': {'association-details': {'collect... 'URL': 'https://cdn.earthdata.nasa.gov/umm/variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/layer', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw0/test_spatial_subset_C1627516290')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f39a45b0040>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f39a469b840>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7f39a469b740>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G1898261144-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1627516292-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-78.0453%3A-60.6907%29&subset=lon%28-164.82465%3A-84.66935000000001%29&granuleId=G1898261144-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job a84fda81-6250-44bf-9292-b780c8f6ed70
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw0/test_spatial_subset_C1627516290/77291132_S5P_OFFL_L2_HCHO_20200712T224601_20200713T002730_14238_01_010108_20200715T122623_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2601583089-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 3s]
Raw output
Exception: ('Unprocessable Entity', 'Error: the requested combination of operations: spatial subsetting on C2601583089-POCLOUD is unsupported')
collection_concept_id = 'C2601583089-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2601583089-POCLOUD', 'concept-id': 'G2816589876-POCLOUD', 'concept-type': 'granul...122T003749_PIC0_02.nc', 'SWOT_L2_LR_PreCalSSH_WindWave_006_545_20231121T234622_20231122T003750_PIC0_02.nc', ...], ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2601583089-POCLOUD'}]}, 'meta': {'association-details': {'collecti...pixels', 'Size': 71, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': 2147483647}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw5/test_spatial_subset_C2601583080')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
> job_id = harmony_client.submit(harmony_request)
verify_collection.py:392:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:851: in submit
self._handle_error_response(response)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7efe28236bf0>
response = <Response [422]>
def _handle_error_response(self, response: Response):
"""Raises the appropriate exception based on the response
received from Harmony. Tries to pull out an error message
from a Harmony JSON response when possible.
Args:
response: The Response from Harmony
Raises:
Exception with a Harmony error message or a more generic
HTTPError
"""
if 'application/json' in response.headers.get('Content-Type', ''):
exception_message = None
try:
response_json = response.json()
if hasattr(response_json, 'get'):
exception_message = response_json.get('description')
if not exception_message:
exception_message = response_json.get('error')
except JSONDecodeError:
pass
if exception_message:
> raise Exception(response.reason, exception_message)
E Exception: ('Unprocessable Entity', 'Error: the requested combination of operations: spatial subsetting on C2601583089-POCLOUD is unsupported')
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:784: Exception
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G2816589876-POCLOUD for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C2601583089-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.5%3A85.5%29&subset=lon%28-171.0%3A171.0%29&granuleId=G2816589876-POCLOUD
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2936721448-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 1m 32s]
Raw output
Failed: Unable to find latitude and longitude variables.
collection_concept_id = 'C2936721448-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2936721448-POCLOUD', 'concept-id': 'G3062447313-POCLOUD', 'concept-type': 'granul...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2936721448-POCLOUD'}]}, 'meta': {'association-details': {'collecti...rization_2', 'Size': 2, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -9999.0}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw6/test_spatial_subset_C2936721440')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
> lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
verify_collection.py:406:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
dataset = <xarray.Dataset> Size: 240B
Dimensions: (ydim_grid: 1, xdim_grid: 1, look: 1,
... -0.43
history_json: [{"date_time": "2...
file_to_subset = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw6/test_spatial_subset_C2936721440/77291160_RSS_SMAP_SSS_L2C_r47700_20240106T014035_2024006_FNL_V05.3.nc4')
collection_variable_list = [{'associations': {'collections': [{'concept-id': 'C2936721448-POCLOUD'}]}, 'meta': {'association-details': {'collecti...rization_2', 'Size': 2, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': -9999.0}], ...}}, ...]
collection_concept_id = 'C2936721448-POCLOUD'
def get_lat_lon_var_names(dataset: xarray.Dataset, file_to_subset: str, collection_variable_list: List[Dict], collection_concept_id: str):
# Try getting it from UMM-Var first
lat_var_json, lon_var_json, _ = get_coordinate_vars_from_umm(collection_variable_list)
lat_var_name = get_variable_name_from_umm_json(lat_var_json)
lon_var_name = get_variable_name_from_umm_json(lon_var_json)
if lat_var_name and lon_var_name:
return lat_var_name, lon_var_name
logging.warning("Unable to find lat/lon vars in UMM-Var")
# If that doesn't work, try using cf-xarray to infer lat/lon variable names
try:
latitude = [lat for lat in dataset.cf.coordinates['latitude']
if lat.lower() in VALID_LATITUDE_VARIABLE_NAMES][0]
longitude = [lon for lon in dataset.cf.coordinates['longitude']
if lon.lower() in VALID_LONGITUDE_VARIABLE_NAMES][0]
return latitude, longitude
except:
logging.warning("Unable to find lat/lon vars using cf_xarray")
# If that still doesn't work, try using l2ss-py directly
try:
# file not able to be flattened unless locally downloaded
filename = f'my_copy_file_{collection_concept_id}.nc'
shutil.copy(file_to_subset, filename)
nc_dataset = netCDF4.Dataset(filename, mode='r+')
# flatten the dataset
nc_dataset_flattened = podaac.subsetter.group_handling.transform_grouped_dataset(nc_dataset, filename)
args = {
'decode_coords': False,
'mask_and_scale': False,
'decode_times': False
}
with xarray.open_dataset(
xarray.backends.NetCDF4DataStore(nc_dataset_flattened),
**args
) as flat_dataset:
# use l2ss-py to find lat and lon names
lat_var_names, lon_var_names = podaac.subsetter.subset.compute_coordinate_variable_names(flat_dataset)
os.remove(filename)
if lat_var_names and lon_var_names:
lat_var_name = lat_var_names.split('__')[-1] if isinstance(lat_var_names, str) else lat_var_names[0].split('__')[-1]
lon_var_name = lon_var_names.split('__')[-1] if isinstance(lon_var_names, str) else lon_var_names[0].split('__')[-1]
return lat_var_name, lon_var_name
except ValueError:
logging.warning("Unable to find lat/lon vars using l2ss-py")
# Still no dice, try using the 'units' variable attribute
for coord_name, coord in dataset.coords.items():
if 'units' not in coord.attrs:
continue
if coord.attrs['units'] == 'degrees_north' and lat_var_name is None:
lat_var_name = coord_name
if coord.attrs['units'] == 'degrees_east' and lon_var_name is None:
lon_var_name = coord_name
if lat_var_name and lon_var_name:
return lat_var_name, lon_var_name
else:
logging.warning("Unable to find lat/lon vars using 'units' attribute")
# Out of options, fail the test because we couldn't determine lat/lon variables
> pytest.fail(f"Unable to find latitude and longitude variables.")
E Failed: Unable to find latitude and longitude variables.
verify_collection.py:359: Failed
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G3062447313-POCLOUD for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C2936721448-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-82.29044999999999%3A82.08044999999998%29&subset=lon%284.51755%3A175.50045%29&granuleId=G3062447313-POCLOUD
INFO root:verify_collection.py:393 Submitted harmony job 4f2cf09a-dd8e-423b-b028-82ab2f698c79
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw6/test_spatial_subset_C2936721440/77291160_RSS_SMAP_SSS_L2C_r47700_20240106T014035_2024006_FNL_V05.3.nc4
WARNING root:verify_collection.py:302 Unable to find lat/lon vars in UMM-Var
WARNING root:verify_collection.py:312 Unable to find lat/lon vars using cf_xarray
WARNING root:verify_collection.py:343 Unable to find lat/lon vars using l2ss-py
WARNING root:verify_collection.py:356 Unable to find lat/lon vars using 'units' attribute
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1918209669-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 2m 5s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C1918209669-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1918209669-GES_DISC', 'concept-id': 'G3243096359-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1918209669-GES_DISC'}]}, 'meta': {'association-details': {'collect...tracted from _FillValue metadata attribute', 'Type': 'SCIENCE_FILLVALUE', 'Value': 9.969209968386869e+36}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw9/test_spatial_subset_C1918209660')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7fd923bb7440>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7fd923bb7b40>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7fd923bb7c40>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G3243096359-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1918209669-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.16425%3A-67.35175%29&subset=lon%28-99.89144999999999%3A171.82944999999998%29&granuleId=G3243096359-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job abef0398-e5ff-4ec5-9864-ce38b283c800
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw9/test_spatial_subset_C1918209660/77291168_S5P_OFFL_L2_CLOUD_20240917T150339_20240917T164509_35912_03_020601_20240919T062017_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1627516285-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 2m 17s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C1627516285-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1627516285-GES_DISC', 'concept-id': 'G2084435970-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1627516285-GES_DISC'}]}, 'meta': {'association-details': {'collect.../variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'METADATA/QA_STATISTICS/aerosol_index_354_388_histogram_bounds'}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw8/test_spatial_subset_C1627516280')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7feffe668440>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7feffe669240>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7feffe669140>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G2084435970-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1627516285-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-76.82889999999999%3A-59.7251%29&subset=lon%28-77.22455%3A-1.6634499999999974%29&granuleId=G2084435970-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job 0a9c1d13-4311-4a44-a21b-c89dfadf9b73
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw8/test_spatial_subset_C1627516280/77291190_S5P_OFFL_L2_AER_AI_20210701T170324_20210701T184453_19257_01_010400_20210703T065109_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1627516300-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 2m 18s]
Raw output
OSError: [Errno group not found: PRODUCT] 'PRODUCT'
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7efe28271d40>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7efe30af9fc0>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
> ds = ds.groups[key]
E KeyError: 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:190: KeyError
During handling of the above exception, another exception occurred:
collection_concept_id = 'C1627516300-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1627516300-GES_DISC', 'concept-id': 'G1902371249-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1627516300-GES_DISC'}]}, 'meta': {'association-details': {'collect...asa.gov/umm/variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/ozone_total_vertical_column_precision', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw5/test_spatial_subset_C1627516300')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
verify_collection.py:431: in group_walk
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/api.py:571: in open_dataset
backend_ds = backend.open_dataset(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:646: in open_dataset
store = NetCDF4DataStore.open(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:409: in open
return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:356: in __init__
self.format = self.ds.data_model
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:418: in ds
return self._acquire()
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:413: in _acquire
ds = _nc4_require_group(root, self._group, self._mode)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7efe28271d40>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7efe30af9fc0>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
ds = ds.groups[key]
except KeyError as e:
if mode != "r":
ds = create_group(ds, key)
else:
# wrap error to provide slightly more helpful message
> raise OSError(f"group not found: {key}", e)
E OSError: [Errno group not found: PRODUCT] 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:196: OSError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G1902371249-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1627516300-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-78.0453%3A-60.6907%29&subset=lon%28-164.82465%3A-84.66935000000001%29&granuleId=G1902371249-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job 96a9de52-f962-4b4a-88b7-c8e6b3b93057
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw5/test_spatial_subset_C1627516300/77291200_S5P_OFFL_L2_O3_20200712T224601_20200713T002730_14238_01_010108_20200715T122623_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1627516296-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 1m 37s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C1627516296-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1627516296-GES_DISC', 'concept-id': 'G1902371245-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1627516296-GES_DISC'}]}, 'meta': {'association-details': {'collect...umm/variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/sulfurdioxide_total_vertical_column_precision', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw4/test_spatial_subset_C1627516290')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7fd11ada7b40>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7fd1199e7940>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7fd1199e4040>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G1902371245-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1627516296-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-78.0453%3A-60.6907%29&subset=lon%28-164.82465%3A-84.66935000000001%29&granuleId=G1902371245-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job 5ea13d62-db28-452f-af76-df233d4d760e
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw4/test_spatial_subset_C1627516290/77291251_S5P_OFFL_L2_SO2_20200712T224601_20200713T002730_14238_01_010108_20200715T211427_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1627516287-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 1m 34s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C1627516287-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1627516287-GES_DISC', 'concept-id': 'G2084463561-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1627516287-GES_DISC'}]}, 'meta': {'association-details': {'collect...'URL': 'https://cdn.earthdata.nasa.gov/umm/variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/corner', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw7/test_spatial_subset_C1627516280')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f3a7d78d440>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f3a7d78d940>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7f3a7d78da40>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G2084463561-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1627516287-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-76.99937499999999%3A-59.951625%29&subset=lon%28-76.6214%3A-1.5866000000000042%29&granuleId=G2084463561-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job c40f6c67-fcbd-4bf8-a3ff-31d9092a2ae4
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw7/test_spatial_subset_C1627516280/77291266_S5P_OFFL_L2_CO_20210701T170324_20210701T184453_19257_01_010400_20210703T065107_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1266136113-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 10m 0s]
Raw output
Failed: Timeout >600.0s
collection_concept_id = 'C1266136113-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1266136113-GES_DISC', 'concept-id': 'G3242538322-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1266136113-GES_DISC'}]}, 'meta': {'association-details': {'collect...acted from _FillValue metadata attribute', 'Type': 'SCIENCE_FILLVALUE', 'Value': -1.2676506002282294e+30}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw0/test_spatial_subset_C1266136110')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
> harmony_client.wait_for_processing(job_id, show_progress=True)
verify_collection.py:394:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7f39a445ada0>
job_id = '268d924f-ae56-4159-b92a-c09fa9113f7f', show_progress = True
def wait_for_processing(self, job_id: str, show_progress: bool = False) -> None:
"""Retrieve a submitted job's completion status in percent.
Args:
job_id: UUID string for the job you wish to interrogate.
Returns:
The job's processing progress as a percentage.
:raises
Exception: This can happen if an invalid job_id is provided or Harmony services
can't be reached.
"""
# How often to refresh the screen for progress updates and animating spinners.
ui_update_interval = 0.33 # in seconds
running_w_errors_logged = False
intervals = round(self.check_interval / ui_update_interval)
if show_progress:
with progressbar.ProgressBar(max_value=100, widgets=progressbar_widgets) as bar:
progress = 0
while progress < 100:
progress, status, message = self.progress(job_id)
if status == 'failed':
raise ProcessingFailedException(job_id, message)
if status == 'canceled':
print('Job has been canceled.')
break
if status == 'paused':
print('\nJob has been paused. Call `resume()` to resume.', file=sys.stderr)
break
if (not running_w_errors_logged and status == 'running_with_errors'):
print('\nJob is running with errors.', file=sys.stderr)
running_w_errors_logged = True
# This gets around an issue with progressbar. If we update() with 0, the
# output shows up as "N/A". If we update with, e.g. 0.1, it rounds down or
# truncates to 0 but, importantly, actually displays that.
if progress == 0:
progress = 0.1
for _ in range(intervals):
bar.update(progress) # causes spinner to rotate even when no data change
sys.stdout.flush() # ensures correct behavior in Jupyter notebooks
if progress >= 100:
break
else:
> time.sleep(ui_update_interval)
E Failed: Timeout >600.0s
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:1009: Failed
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G3242538322-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1266136113-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.5%3A85.5%29&subset=lon%28-171.0%3A171.0%29&granuleId=G3242538322-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job 268d924f-ae56-4159-b92a-c09fa9113f7f
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1918210023-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 4m 45s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C1918210023-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1918210023-GES_DISC', 'concept-id': 'G3243059376-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1918210023-GES_DISC'}]}, 'meta': {'association-details': {'collect...RL': 'https://cdn.earthdata.nasa.gov/umm/variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/qa_value', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw7/test_spatial_subset_C1918210020')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f3a7d9ce340>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f3a7d9cdc40>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7f3a7d9cdb40>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G3243059376-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1918210023-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.15780000000001%3A-67.36619999999999%29&subset=lon%28-148.967775%3A101.308775%29&granuleId=G3243059376-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job 37254430-7895-4a21-a0e2-1394ac2d443b
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw7/test_spatial_subset_C1918210020/77291320_S5P_OFFL_L2_HCHO_20240917T132210_20240917T150339_35911_03_020601_20240919T052540_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2087216530-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 2m 42s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C2087216530-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2087216530-GES_DISC', 'concept-id': 'G3243095127-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2087216530-GES_DISC'}]}, 'meta': {'association-details': {'collect...Var', 'URL': 'https://cdn.earthdata.nasa.gov/umm/variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/layer'}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C2087216530')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f1a56a41a40>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f1a56a41840>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7f1a556ccd40>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G3243095127-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C2087216530-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.36149999999999%3A-67.4825%29&subset=lon%28-150.23684999999998%3A101.74685%29&granuleId=G3243095127-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job c732c4cf-9ce7-4990-aad5-19acff93effe
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C2087216530/77291370_S5P_OFFL_L2_CH4_20240917T132210_20240917T150339_35911_03_020701_20240919T052540_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1627516288-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 2m 39s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C1627516288-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1627516288-GES_DISC', 'concept-id': 'G2085128317-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1627516288-GES_DISC'}]}, 'meta': {'association-details': {'collect... 'https://cdn.earthdata.nasa.gov/umm/variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/ground_pixel', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C1627516280')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f1a56a43940>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f1a56a43440>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7f1a56a43340>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G2085128317-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1627516288-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-76.99937499999999%3A-59.951625%29&subset=lon%28-76.6214%3A-1.5866000000000042%29&granuleId=G2085128317-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job b9bc5ffb-09a8-4e87-b95a-690da654542b
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C1627516280/77291488_S5P_OFFL_L2_CH4_20210701T170324_20210701T184453_19257_01_010400_20210703T102338_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2746966926-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 3s]
Raw output
Exception: ('Unprocessable Entity', 'Error: the requested combination of operations: spatial subsetting on C2746966926-POCLOUD is unsupported')
collection_concept_id = 'C2746966926-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2746966926-POCLOUD', 'concept-id': 'G2816914994-POCLOUD', 'concept-type': 'granul..._XOverCal_20230709T115434_20230710T082110_PIB0_01.nc', 'SWOT_GranulePolygons_Cal_20230213T142800_v05.json', ...], ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2746966926-POCLOUD'}]}, 'meta': {'association-details': {'collecti...pixels', 'Size': 69, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': 2147483647}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw9/test_spatial_subset_C2746966920')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
> job_id = harmony_client.submit(harmony_request)
verify_collection.py:392:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:851: in submit
self._handle_error_response(response)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7fd923937df0>
response = <Response [422]>
def _handle_error_response(self, response: Response):
"""Raises the appropriate exception based on the response
received from Harmony. Tries to pull out an error message
from a Harmony JSON response when possible.
Args:
response: The Response from Harmony
Raises:
Exception with a Harmony error message or a more generic
HTTPError
"""
if 'application/json' in response.headers.get('Content-Type', ''):
exception_message = None
try:
response_json = response.json()
if hasattr(response_json, 'get'):
exception_message = response_json.get('description')
if not exception_message:
exception_message = response_json.get('error')
except JSONDecodeError:
pass
if exception_message:
> raise Exception(response.reason, exception_message)
E Exception: ('Unprocessable Entity', 'Error: the requested combination of operations: spatial subsetting on C2746966926-POCLOUD is unsupported')
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:784: Exception
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G2816914994-POCLOUD for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C2746966926-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.5%3A85.5%29&subset=lon%28-171.0%3A171.0%29&granuleId=G2816914994-POCLOUD
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1442068509-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 1m 4s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C1442068509-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1442068509-GES_DISC', 'concept-id': 'G1628706233-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1442068509-GES_DISC'}]}, 'meta': {'association-details': {'collect... 'URL': 'https://cdn.earthdata.nasa.gov/umm/variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/level', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw8/test_spatial_subset_C1442068500')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7feffe729940>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7feffe729340>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7feffe729240>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G1628706233-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1442068509-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-82.265975%3A-63.873025000000005%29&subset=lon%28-112.057275%3A162.74827499999998%29&granuleId=G1628706233-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job e6be4d19-6a9a-4a11-a714-cdc252b015d9
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw8/test_spatial_subset_C1442068500/77291502_S5P_OFFL_L2_O3_20190806T003836_20190806T022006_09387_01_010107_20190812T015759_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1918210292-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 2m 28s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C1918210292-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1918210292-GES_DISC', 'concept-id': 'G3243059913-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1918210292-GES_DISC'}]}, 'meta': {'association-details': {'collect...v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/SUPPORT_DATA/DETAILED_RESULTS/number_of_slant_columns_win2', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw6/test_spatial_subset_C1918210290')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7fe150360740>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7fe15157e940>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7fe15157e340>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G3243059913-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1918210292-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.2593%3A-67.37270000000001%29&subset=lon%28-167.512925%3A153.855925%29&granuleId=G3243059913-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job 30362099-552b-4757-905a-4a5808b71c78
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw6/test_spatial_subset_C1918210290/77291511_S5P_OFFL_L2_SO2_20240917T081741_20240917T095911_35908_03_020601_20240919T055904_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2179081549-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 1m 36s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C2179081549-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2179081549-GES_DISC', 'concept-id': 'G3242636419-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2179081549-GES_DISC'}]}, 'meta': {'association-details': {'collect...escription': 'Extracted from _FillValue metadata attribute', 'Type': 'SCIENCE_FILLVALUE', 'Value': -9999}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C2179081540')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'Swath': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f1a56a43d40>}
nc_d = <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7f1a556cde40>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
> data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
E IndexError: list index out of range
verify_collection.py:435: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G3242636419-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C2179081549-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-66.24501225%3A-60.46643775%29&subset=lon%28-123.16097975%3A-92.89397025%29&granuleId=G3242636419-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job d7d84913-f7bf-48fd-96ab-e27ba3e1fd16
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C2179081540/77291526_2A.GPM.DPR.GPM-SLH.20240917-S211704-E225017.059941.V07C_subsetted.nc4
WARNING root:verify_collection.py:302 Unable to find lat/lon vars in UMM-Var
WARNING root:verify_collection.py:312 Unable to find lat/lon vars using cf_xarray
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C1442068508-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 2m 26s]
Raw output
IndexError: list index out of range
collection_concept_id = 'C1442068508-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C1442068508-GES_DISC', 'concept-id': 'G1628710396-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C1442068508-GES_DISC'}]}, 'meta': {'association-details': {'collect...v1.9.0', 'Version': '1.9.0'}, 'Name': 'PRODUCT/SUPPORT_DATA/DETAILED_RESULTS/fitted_radiance_squeeze_win3', ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw8/test_spatial_subset_C1442068501')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
groups = {'METADATA': <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7feffe728b40>, 'PRODUCT': <[RuntimeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7feffe639f40>}
nc_d = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Dataset object at 0x7feffe63a240>
current_group = ''
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
> sci_var = list(subsetted_ds_data.variables.keys())[0]
E IndexError: list index out of range
verify_collection.py:438: IndexError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G1628710396-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C1442068508-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-82.265975%3A-63.873025000000005%29&subset=lon%28-112.057275%3A162.74827499999998%29&granuleId=G1628710396-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job 91d2bca6-a6e4-4147-8be3-723fdae3ca81
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw8/test_spatial_subset_C1442068501/77291540_S5P_OFFL_L2_SO2_20190806T003836_20190806T022006_09387_01_010107_20190812T085130_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2087131083-GES_DISC] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 1m 43s]
Raw output
OSError: [Errno group not found: PRODUCT] 'PRODUCT'
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f1a542b2540>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7f1a5ded9bd0>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
> ds = ds.groups[key]
E KeyError: 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:190: KeyError
During handling of the above exception, another exception occurred:
collection_concept_id = 'C2087131083-GES_DISC', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2087131083-GES_DISC', 'concept-id': 'G3243096015-GES_DISC', 'concept-type': 'gran...pecification': {'Name': 'UMM-G', 'URL': 'https://cdn.earthdata.nasa.gov/umm/granule/v1.6.6', 'Version': '1.6.6'}, ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2087131083-GES_DISC'}]}, 'meta': {'association-details': {'collect.../variable/v1.9.0', 'Version': '1.9.0'}, 'Name': 'METADATA/QA_STATISTICS/aerosol_index_354_388_histogram_bounds'}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C2087131080')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
job_id = harmony_client.submit(harmony_request)
logging.info("Submitted harmony job %s", job_id)
harmony_client.wait_for_processing(job_id, show_progress=True)
subsetted_filepath = None
for filename in [file_future.result()
for file_future
in harmony_client.download_all(job_id, directory=f'{tmp_path}', overwrite=True)]:
logging.info(f'Downloaded: %s', filename)
subsetted_filepath = pathlib.Path(filename)
# Verify spatial subset worked
subsetted_ds = xarray.open_dataset(subsetted_filepath, decode_times=False)
group = None
# Try to read group in file
lat_var_name, lon_var_name = get_lat_lon_var_names(subsetted_ds, subsetted_filepath, collection_variables, collection_concept_id)
lat_var_name = lat_var_name.split('/')[-1]
lon_var_name = lon_var_name.split('/')[-1]
with netCDF4.Dataset(subsetted_filepath) as f:
group_list = []
def group_walk(groups, nc_d, current_group):
global subsetted_ds_new
subsetted_ds_new = None
# check if the top group has lat or lon variable
if lat_var_name in list(nc_d.variables.keys()):
subsetted_ds_new = subsetted_ds
else:
# if not then we'll need to keep track of the group layers
group_list.append(current_group)
# loop through the groups in the current layer
for g in groups:
# end the loop if we've already found latitude
if subsetted_ds_new:
break
# check if the groups have latitude, define the dataset and end the loop if found
if lat_var_name in list(nc_d.groups[g].variables.keys()):
group_list.append(g)
lat_group = '/'.join(group_list)
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
# add a science variable to the dataset if other groups are in the lat/lon group
# some GPM collections won't have any other variables in the same group as lat/lon
if len(list(nc_d.groups[g].groups.keys())) > 0:
data_group = [v for v in list(nc_d.groups[g].groups.keys()) if 'time' not in str(v).lower()][0]
g_data = lat_group+'/'+data_group
subsetted_ds_data = xarray.open_dataset(subsetted_filepath, group=g_data, decode_times=False)
sci_var = list(subsetted_ds_data.variables.keys())[0]
subsetted_ds_new['science_test'] = subsetted_ds_data[sci_var]
break
# recall the function on a group that has groups in it and didn't find latitude
# this is going 'deeper' into the groups
if len(list(nc_d.groups[g].groups.keys())) > 0:
group_walk(nc_d.groups[g].groups, nc_d.groups[g], g)
else:
continue
> group_walk(f.groups, f, '')
verify_collection.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
verify_collection.py:431: in group_walk
subsetted_ds_new = xarray.open_dataset(subsetted_filepath, group=lat_group, decode_times=False)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/api.py:571: in open_dataset
backend_ds = backend.open_dataset(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:646: in open_dataset
store = NetCDF4DataStore.open(
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:409: in open
return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose)
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:356: in __init__
self.format = self.ds.data_model
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:418: in ds
return self._acquire()
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:413: in _acquire
ds = _nc4_require_group(root, self._group, self._mode)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
ds = <[AttributeError('NetCDF: Not a valid ID') raised in repr()] Group object at 0x7f1a542b2540>
group = '/METADATA/PRODUCT', mode = 'r'
create_group = <function _netcdf4_create_group at 0x7f1a5ded9bd0>
def _nc4_require_group(ds, group, mode, create_group=_netcdf4_create_group):
if group in {None, "", "/"}:
# use the root group
return ds
else:
# make sure it's a string
if not isinstance(group, str):
raise ValueError("group must be a string or None")
# support path-like syntax
path = group.strip("/").split("/")
for key in path:
try:
ds = ds.groups[key]
except KeyError as e:
if mode != "r":
ds = create_group(ds, key)
else:
# wrap error to provide slightly more helpful message
> raise OSError(f"group not found: {key}", e)
E OSError: [Errno group not found: PRODUCT] 'PRODUCT'
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:196: OSError
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G3243096015-GES_DISC for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C2087131083-GES_DISC/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.169825%3A-67.34117499999999%29&subset=lon%28-125.68284999999999%3A146.36485%29&granuleId=G3243096015-GES_DISC
INFO root:verify_collection.py:393 Submitted harmony job c30f9468-fbd2-41a9-a584-8b0807b67257
INFO root:verify_collection.py:399 Downloaded: /tmp/pytest-of-runner/pytest-0/popen-gw3/test_spatial_subset_C2087131080/77291562_S5P_OFFL_L2_AER_AI_20240917T164509_20240917T182638_35913_03_020701_20240919T062801_subsetted.nc4
Check warning on line 0 in tests.verify_collection
github-actions / Regression test results for ops
test_spatial_subset[C2746966657-POCLOUD] (tests.verify_collection) failed
test-results/ops_test_report.xml [took 7s]
Raw output
Exception: ('Unprocessable Entity', 'Error: the requested combination of operations: spatial subsetting on C2746966657-POCLOUD is unsupported')
collection_concept_id = 'C2746966657-POCLOUD', env = 'ops'
granule_json = {'meta': {'collection-concept-id': 'C2746966657-POCLOUD', 'concept-id': 'G2816914997-POCLOUD', 'concept-type': 'granul..._XOverCal_20230709T115434_20230710T082110_PIB0_01.nc', 'SWOT_GranulePolygons_Cal_20230213T142800_v05.json', ...], ...}}
collection_variables = [{'associations': {'collections': [{'concept-id': 'C2746966657-POCLOUD'}]}, 'meta': {'association-details': {'collecti...pixels', 'Size': 69, 'Type': 'OTHER'}], 'FillValues': [{'Type': 'SCIENCE_FILLVALUE', 'Value': 2147483647}], ...}}, ...]
harmony_env = <Environment.PROD: 4>
tmp_path = PosixPath('/tmp/pytest-of-runner/pytest-0/popen-gw1/test_spatial_subset_C2746966650')
bearer_token = 'eyJ0eXAiOiJKV1QiLCJvcmlnaW4iOiJFYXJ0aGRhdGEgTG9naW4iLCJzaWciOiJlZGxqd3RwdWJrZXlfb3BzIiwiYWxnIjoiUlMyNTYifQ.eyJ0eXBlIj...Hcf0QWqtHsCuvOtj5tczYDaCn691RlCxRjaMlZBPYm2O9z5cTN31ynn1hy4h8lXYRR_I6DfCAdmdtrIdlLaMNL-ZbKOjYgx5kEqU8ClqAQnFPDVYJL29Hw'
@pytest.mark.timeout(600)
def test_spatial_subset(collection_concept_id, env, granule_json, collection_variables,
harmony_env, tmp_path: pathlib.Path, bearer_token):
test_spatial_subset.__doc__ = f"Verify spatial subset for {collection_concept_id} in {env}"
logging.info("Using granule %s for test", granule_json['meta']['concept-id'])
# Compute a box that is smaller than the granule extent bounding box
north, south, east, west = get_bounding_box(granule_json)
east, west, north, south = create_smaller_bounding_box(east, west, north, south, .95)
start_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["BeginningDateTime"]
end_time = granule_json['umm']["TemporalExtent"]["RangeDateTime"]["EndingDateTime"]
# Build harmony request
harmony_client = harmony.Client(env=harmony_env, token=bearer_token)
request_bbox = harmony.BBox(w=west, s=south, e=east, n=north)
request_collection = harmony.Collection(id=collection_concept_id)
harmony_request = harmony.Request(collection=request_collection, spatial=request_bbox,
granule_id=[granule_json['meta']['concept-id']])
logging.info("Sending harmony request %s", harmony_client.request_as_url(harmony_request))
# Submit harmony request and download result
> job_id = harmony_client.submit(harmony_request)
verify_collection.py:392:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:851: in submit
self._handle_error_response(response)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <harmony.harmony.Client object at 0x7f77b9b22920>
response = <Response [422]>
def _handle_error_response(self, response: Response):
"""Raises the appropriate exception based on the response
received from Harmony. Tries to pull out an error message
from a Harmony JSON response when possible.
Args:
response: The Response from Harmony
Raises:
Exception with a Harmony error message or a more generic
HTTPError
"""
if 'application/json' in response.headers.get('Content-Type', ''):
exception_message = None
try:
response_json = response.json()
if hasattr(response_json, 'get'):
exception_message = response_json.get('description')
if not exception_message:
exception_message = response_json.get('error')
except JSONDecodeError:
pass
if exception_message:
> raise Exception(response.reason, exception_message)
E Exception: ('Unprocessable Entity', 'Error: the requested combination of operations: spatial subsetting on C2746966657-POCLOUD is unsupported')
../../../../.cache/pypoetry/virtualenvs/l2ss-py-autotest-iYz8Sff2-py3.10/lib/python3.10/site-packages/harmony/harmony.py:784: Exception
--------------------------------- Captured Log ---------------------------------
INFO root:verify_collection.py:373 Using granule G2816914997-POCLOUD for test
INFO root:verify_collection.py:389 Sending harmony request https://harmony.earthdata.nasa.gov/C2746966657-POCLOUD/ogc-api-coverages/1.0.0/collections/all/coverage/rangeset?forceAsync=true&subset=lat%28-85.5%3A85.5%29&subset=lon%28-171.0%3A171.0%29&granuleId=G2816914997-POCLOUD
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