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| id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 516306758 | MDU6SXNzdWU1MTYzMDY3NTg= | 3476 | Error when writing string coordinate variables to zarr | jsadler2 6943441 | open | 0 | 16 | 2019-11-01T19:32:29Z | 2024-01-25T17:39:42Z | NONE | I saved an xarray dataset to zarr using MCVE Code Sample```python import xarray as xr sm_from_zarr = xr.open_zarr('test_sm_zarr') sm_from_zarr.to_zarr('test_sm_zarr_from', mode='w') ``` Expected OutputNo error Problem DescriptionI get this error:
sm_from_zarr = xr.open_zarr('test_sm_zarr') sm_from_zarr['site_code'] = sm_from_zarr.site_code.astype('str') sm_from_zarr.to_zarr('test_sm_zarr_from', mode='w')
Output of
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xarray 13221727 | issue | ||||||||
| 502720385 | MDU6SXNzdWU1MDI3MjAzODU= | 3374 | Key error in to_netcdf | jsadler2 6943441 | closed | 0 | 5 | 2019-10-04T16:04:30Z | 2023-03-14T21:14:33Z | 2023-03-14T21:14:33Z | NONE | MCVE Code Sample```python import xarray as xr p = range(10) ds = xr.Dataset({'precip': (['time'], p)}, coords={'time': range(10)}) ds.attrs['Conventions'] = ['COARDS', 'GrADS'] ds.to_netcdf('a.nc') ``` Expected OutputSaves data to Problem DescriptionIn version
If instead the attribute is saved as as string instead of a list, it works: ```python import xarray as xr p = range(10) ds = xr.Dataset({'precip': (['time'], p)}, coords={'time': range(10)}) ds.attrs['Conventions'] = "['COARDS', 'GrADS']" ds.to_netcdf('a.nc') ``` Output of
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completed | xarray 13221727 | issue | ||||||
| 861684673 | MDU6SXNzdWU4NjE2ODQ2NzM= | 5189 | KeyError pulling from Nasa server with Pydap | jsadler2 6943441 | open | 0 | 12 | 2021-04-19T18:41:11Z | 2021-06-17T09:49:48Z | NONE | What happened: I'm trying to pull data from this NASA server: https://hydro1.gesdisc.eosdis.nasa.gov/dods/NLDAS_FORA0125_H.002?. Through pydap, I can create a DataSet representing the data, but when I try to get the data I get this error: ```python-tracebackKeyError Traceback (most recent call last) ~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in _getitem_string(self, key) 403 try: --> 404 return self._dict[quote(key)] 405 except KeyError: KeyError: 'tmp2m%2Etmp2m' During handling of the above exception, another exception occurred: IndexError Traceback (most recent call last) <ipython-input-17-3efbb8f7b71f> in <module> ----> 1 ds['tmp2m'].isel(time=0).values ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/dataarray.py in values(self) 632 def values(self) -> np.ndarray: 633 """The array's data as a numpy.ndarray""" --> 634 return self.variable.values 635 636 @values.setter ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/variable.py in values(self) 552 def values(self): 553 """The variable's data as a numpy.ndarray""" --> 554 return _as_array_or_item(self._data) 555 556 @values.setter ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/variable.py in _as_array_or_item(data) 285 data = data.get() 286 else: --> 287 data = np.asarray(data) 288 if data.ndim == 0: 289 if data.dtype.kind == "M": ~/my-conda-envs/nwm/lib/python3.7/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order, like) 100 return _asarray_with_like(a, dtype=dtype, order=order, like=like) 101 --> 102 return array(a, dtype, copy=False, order=order) 103 104 ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/indexing.py in array(self, dtype) 691 692 def array(self, dtype=None): --> 693 self._ensure_cached() 694 return np.asarray(self.array, dtype=dtype) 695 ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/indexing.py in _ensure_cached(self) 688 def _ensure_cached(self): 689 if not isinstance(self.array, NumpyIndexingAdapter): --> 690 self.array = NumpyIndexingAdapter(np.asarray(self.array)) 691 692 def array(self, dtype=None): ~/my-conda-envs/nwm/lib/python3.7/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order, like) 100 return _asarray_with_like(a, dtype=dtype, order=order, like=like) 101 --> 102 return array(a, dtype, copy=False, order=order) 103 104 ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/indexing.py in array(self, dtype) 661 662 def array(self, dtype=None): --> 663 return np.asarray(self.array, dtype=dtype) 664 665 def getitem(self, key): ~/my-conda-envs/nwm/lib/python3.7/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order, like) 100 return _asarray_with_like(a, dtype=dtype, order=order, like=like) 101 --> 102 return array(a, dtype, copy=False, order=order) 103 104 ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/indexing.py in array(self, dtype) 566 def array(self, dtype=None): 567 array = as_indexable(self.array) --> 568 return np.asarray(array[self.key], dtype=None) 569 570 def transpose(self, order): ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/conventions.py in getitem(self, key) 60 61 def getitem(self, key): ---> 62 return np.asarray(self.array[key], dtype=self.dtype) 63 64 ~/my-conda-envs/nwm/lib/python3.7/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order, like) 100 return _asarray_with_like(a, dtype=dtype, order=order, like=like) 101 --> 102 return array(a, dtype, copy=False, order=order) 103 104 ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/coding/variables.py in array(self, dtype) 68 69 def array(self, dtype=None): ---> 70 return self.func(self.array) 71 72 def repr(self): ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/coding/variables.py in _apply_mask(data, encoded_fill_values, decoded_fill_value, dtype) 136 ) -> np.ndarray: 137 """Mask all matching values in a NumPy arrays.""" --> 138 data = np.asarray(data, dtype=dtype) 139 condition = False 140 for fv in encoded_fill_values: ~/my-conda-envs/nwm/lib/python3.7/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order, like) 100 return _asarray_with_like(a, dtype=dtype, order=order, like=like) 101 --> 102 return array(a, dtype, copy=False, order=order) 103 104 ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/indexing.py in array(self, dtype) 566 def array(self, dtype=None): 567 array = as_indexable(self.array) --> 568 return np.asarray(array[self.key], dtype=None) 569 570 def transpose(self, order): ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/backends/pydap_.py in getitem(self, key) 36 def getitem(self, key): 37 return indexing.explicit_indexing_adapter( ---> 38 key, self.shape, indexing.IndexingSupport.BASIC, self._getitem 39 ) 40 ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/indexing.py in explicit_indexing_adapter(key, shape, indexing_support, raw_indexing_method) 851 """ 852 raw_key, numpy_indices = decompose_indexer(key, shape, indexing_support) --> 853 result = raw_indexing_method(raw_key.tuple) 854 if numpy_indices.tuple: 855 # index the loaded np.ndarray ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/backends/pydap_.py in _getitem(self, key) 43 # downloading coordinate data twice 44 array = getattr(self.array, "array", self.array) ---> 45 result = robust_getitem(array, key, catch=ValueError) 46 # in some cases, pydap doesn't squeeze axes automatically like numpy 47 axis = tuple(n for n, k in enumerate(key) if isinstance(k, integer_types)) ~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/backends/common.py in robust_getitem(array, key, catch, max_retries, initial_delay) 51 for n in range(max_retries + 1): 52 try: ---> 53 return array[key] 54 except catch: 55 if n == max_retries: ~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in getitem(self, index) 318 def getitem(self, index): 319 out = copy.copy(self) --> 320 out.data = self._get_data_index(index) 321 return out 322 ~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in _get_data_index(self, index) 347 return np.vectorize(decode_np_strings)(self._data[index]) 348 else: --> 349 return self._data[index] 350 351 def _get_data(self): ~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/handlers/dap.py in getitem(self, index) 147 dataset = build_dataset(dds) 148 dataset.data = unpack_data(BytesReader(data), dataset) --> 149 return dataset[self.id].data 150 151 def len(self): ~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in getitem(self, key) 423 def getitem(self, key): 424 if isinstance(key, string_types): --> 425 return self._getitem_string(key) 426 elif (isinstance(key, tuple) and 427 all(isinstance(name, string_types) ~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in _getitem_string(self, key) 407 if len(splitted) > 1: 408 try: --> 409 return self[splitted[0]]['.'.join(splitted[1:])] 410 except KeyError: 411 return self['.'.join(splitted[1:])] ~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in getitem(self, index) 318 def getitem(self, index): 319 out = copy.copy(self) --> 320 out.data = self._get_data_index(index) 321 return out 322 ~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in _get_data_index(self, index) 347 return np.vectorize(decode_np_strings)(self._data[index]) 348 else: --> 349 return self._data[index] 350 351 def _get_data(self): IndexError: only integers, slices ( ``` What you expected to happen: I should be able to select the data w/o error. Minimal Complete Verifiable Example: (a nasa username and password are required): ```python from pydap.client import open_url from pydap.cas.urs import setup_session import xarray as xr base_url = "https://hydro1.gesdisc.eosdis.nasa.gov/dods/NLDAS_FORA0125_H.002?" session = setup_session("USER", "PASSWORD", check_url=base_url) store = xr.backends.PydapDataStore.open(base_url, session=session) ds = xr.open_dataset(store) ds['tmp2m'].isel(time=0, lat=0, lon=0).values ``` Anything else we need to know?: Environment: Output of <tt>xr.show_versions()</tt>INSTALLED VERSIONS ------------------ commit: None python: 3.7.10 | packaged by conda-forge | (default, Feb 19 2021, 16:07:37) [GCC 9.3.0] python-bits: 64 OS: Linux OS-release: 4.14.219-164.354.amzn2.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: C.UTF-8 LANG: C.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.17.0 pandas: 1.2.3 numpy: 1.20.1 scipy: 1.6.0 netCDF4: 1.5.6 pydap: installed h5netcdf: None h5py: None Nio: None zarr: 2.6.1 cftime: 1.4.1 nc_time_axis: None PseudoNetCDF: None rasterio: 1.2.1 cfgrib: None iris: None bottleneck: None dask: 2021.02.0 distributed: 2021.02.0 matplotlib: 3.3.4 cartopy: None seaborn: None numbagg: None pint: None setuptools: 49.6.0.post20210108 pip: 21.0.1 conda: None pytest: None IPython: 7.21.0 sphinx: None |
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xarray 13221727 | issue |
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