error on opening HH file #86
Description
trying to open a RCM HH file
file = "/home/datawork-cersat-public/provider/asc-csa/satellite/l1/rcm/rcm2/SCSDA/GRD/2020/051/RCM2_OK1051101_PK1052225_1_SCSDA_20200220_090253_HH_GRD"
tree = safe_rcm.open_rcm(file, chunks={})/home1/datahome/vlheureu/git/xarray-safe-rcm/safe_rcm/product/reader.py:59: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.
{"timeStamp": ds["timeStamp"].astype("datetime64")}
/home1/datahome/vlheureu/git/xarray-safe-rcm/safe_rcm/product/reader.py:68: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.
{"timeStamp": ds["timeStamp"].astype("datetime64")}
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[4], line 2
1 file = "/home/datawork-cersat-public/provider/asc-csa/satellite/l1/rcm/rcm2/SCSDA/GRD/2020/051/RCM2_OK1051101_PK1052225_1_SCSDA_20200220_090253_HH_GRD"
----> 2 tree = safe_rcm.open_rcm(file, chunks={})
File ~/git/xarray-safe-rcm/safe_rcm/api.py:98, in open_rcm(url, backend_kwargs, manifest_ignores, **dataset_kwargs)
92 if missing_files:
93 raise ExceptionGroup(
94 "not all files declared in the manifest are available",
95 [ValueError(f"{p} does not exist") for p in missing_files],
96 )
---> 98 tree = read_product(mapper, "metadata/product.xml")
100 calibration_root = "metadata/calibration"
101 lookup_table_structure = {
102 "/incidenceAngles": {
103 "path": "/imageReferenceAttributes",
(...)
136 },
137 }
File ~/git/xarray-safe-rcm/safe_rcm/product/reader.py:275, in read_product(mapper, product_path)
35 decoded = read_xml(mapper, product_path)
37 layout = {
38 "/": {
39 "path": "/",
(...)
272 },
273 }
--> 275 converted = valmap(
276 lambda x: execute(**x)(decoded),
277 layout,
278 )
279 return datatree.DataTree.from_dict(converted)
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/dicttoolz.pyx:178, in cytoolz.dicttoolz.valmap()
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/dicttoolz.pyx:203, in cytoolz.dicttoolz.valmap()
File ~/git/xarray-safe-rcm/safe_rcm/product/reader.py:276, in read_product.<locals>.<lambda>(x)
35 decoded = read_xml(mapper, product_path)
37 layout = {
38 "/": {
39 "path": "/",
(...)
272 },
273 }
275 converted = valmap(
--> 276 lambda x: execute(**x)(decoded),
277 layout,
278 )
279 return datatree.DataTree.from_dict(converted)
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/functoolz.pyx:267, in cytoolz.functoolz.curry.__call__()
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/functoolz.pyx:263, in cytoolz.functoolz.curry.__call__()
File ~/git/xarray-safe-rcm/safe_rcm/product/reader.py:31, in execute(mapping, f, path)
27 @curry
28 def execute(mapping, f, path):
29 subset = query(path, mapping)
---> 31 return compose_left(f, attach_path(path=path))(subset)
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/functoolz.pyx:516, in cytoolz.functoolz.Compose.__call__()
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/functoolz.pyx:518, in cytoolz.functoolz.Compose.__call__()
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/functoolz.pyx:735, in genexpr()
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/functoolz.pyx:735, in genexpr()
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/functoolz.pyx:518, in cytoolz.functoolz.Compose.__call__()
File ~/git/xarray-safe-rcm/safe_rcm/product/transformers.py:133, in extract_dataset(obj, dims, default_dims)
129 variables_ = keymap(lambda k: k.lstrip("@"), variables)
131 filtered_variables = valfilter(lambda x: not is_nested_dataset(x), variables_)
--> 133 data_vars = itemmap(
134 lambda item: (
135 item[0],
136 extract_entry(*item, dims=dims, default_dims=default_dims),
137 ),
138 filtered_variables,
139 )
140 return xr.Dataset(data_vars=data_vars, attrs=attrs)
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/dicttoolz.pyx:236, in cytoolz.dicttoolz.itemmap()
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/dicttoolz.pyx:261, in cytoolz.dicttoolz.itemmap()
File ~/git/xarray-safe-rcm/safe_rcm/product/transformers.py:136, in extract_dataset.<locals>.<lambda>(item)
129 variables_ = keymap(lambda k: k.lstrip("@"), variables)
131 filtered_variables = valfilter(lambda x: not is_nested_dataset(x), variables_)
133 data_vars = itemmap(
134 lambda item: (
135 item[0],
--> 136 extract_entry(*item, dims=dims, default_dims=default_dims),
137 ),
138 filtered_variables,
139 )
140 return xr.Dataset(data_vars=data_vars, attrs=attrs)
File ~/git/xarray-safe-rcm/safe_rcm/product/transformers.py:116, in extract_entry(name, obj, dims, default_dims)
114 return extract_variable(obj, dims=dims)
115 elif is_nested_array(obj):
--> 116 return extract_nested_array(obj, dims=dims).pipe(rename, name)
117 else:
118 raise ValueError(f"unknown datastructure:\n{obj}")
File ~/git/xarray-safe-rcm/safe_rcm/product/transformers.py:209, in extract_nested_array(obj, dims)
200 dims = ["$"]
202 coords = itemmap(
203 lambda it: (it[0], to_variable_tuple(*it, dims=dims)),
204 indexes,
205 )
207 arr = xr.DataArray(
208 data=preprocessed_data["$"],
--> 209 attrs=valmap(first, attrs_),
210 dims=dims,
211 coords=coords,
212 )
213 if originally_stacked:
214 return arr
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/dicttoolz.pyx:178, in cytoolz.dicttoolz.valmap()
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/dicttoolz.pyx:203, in cytoolz.dicttoolz.valmap()
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/itertoolz.pyx:549, in cytoolz.itertoolz.first()
File /home1/datawork/vlheureu/conda-env/xsar_N3/lib/python3.10/site-packages/cytoolz/itertoolz.pyx:556, in cytoolz.itertoolz.first()
TypeError: iteration over a 0-d array