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pydata / xarray

N-D labeled arrays and datasets in Python
https://xarray.dev
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NotImplementedError: Don't yet support nd fancy indexing #6490

Closed javedali99 closed 2 years ago

javedali99 commented 2 years ago

What is your issue?

Hi, I am trying to use isel method from xarray to subset netCDF file using boundary coordinates. But, I am getting the following error:

NotImplementedError: Don't yet support nd fancy indexing

Could you please help me with how to solve this issue?

Detail information on error:

---------------------------------------------------------------------------
NotImplementedError                       Traceback (most recent call last)
Input In [21], in <cell line: 1>()
----> 1 ds_sel = ds2011_2014.isel(lon=(ds2011_2014.lon >= left) & (ds2011_2014.lon <= right),
      2                           lat=(ds2011_2014.lat >= bottom) & (ds2011_2014.lat <= top),
      3                           )
      5 ds_sel_avg = ds_sel.mean(dim=['lat','lon'])

File ~/miniforge3/lib/python3.9/site-packages/xarray/core/dataset.py:2352, in Dataset.isel(self, indexers, drop, missing_dims, **indexers_kwargs)
   2350 indexers = either_dict_or_kwargs(indexers, indexers_kwargs, "isel")
   2351 if any(is_fancy_indexer(idx) for idx in indexers.values()):
-> 2352     return self._isel_fancy(indexers, drop=drop, missing_dims=missing_dims)
   2354 # Much faster algorithm for when all indexers are ints, slices, one-dimensional
   2355 # lists, or zero or one-dimensional np.ndarray's
   2356 indexers = drop_dims_from_indexers(indexers, self.dims, missing_dims)

File ~/miniforge3/lib/python3.9/site-packages/xarray/core/dataset.py:2416, in Dataset._isel_fancy(self, indexers, drop, missing_dims)
   2414         indexes[name] = new_index
   2415 elif var_indexers:
-> 2416     new_var = var.isel(indexers=var_indexers)
   2417 else:
   2418     new_var = var.copy(deep=False)

File ~/miniforge3/lib/python3.9/site-packages/xarray/core/variable.py:1186, in Variable.isel(self, indexers, missing_dims, **indexers_kwargs)
   1183 indexers = drop_dims_from_indexers(indexers, self.dims, missing_dims)
   1185 key = tuple(indexers.get(dim, slice(None)) for dim in self.dims)
-> 1186 return self[key]

File ~/miniforge3/lib/python3.9/site-packages/xarray/core/variable.py:779, in Variable.__getitem__(self, key)
    766 """Return a new Variable object whose contents are consistent with
    767 getting the provided key from the underlying data.
    768 
   (...)
    776 array `x.values` directly.
    777 """
    778 dims, indexer, new_order = self._broadcast_indexes(key)
--> 779 data = as_indexable(self._data)[indexer]
    780 if new_order:
    781     data = np.moveaxis(data, range(len(new_order)), new_order)

File ~/miniforge3/lib/python3.9/site-packages/xarray/core/indexing.py:1161, in NumpyIndexingAdapter.__getitem__(self, key)
   1159 def __getitem__(self, key):
   1160     array, key = self._indexing_array_and_key(key)
-> 1161     return array[key]

File ~/miniforge3/lib/python3.9/site-packages/dask/array/core.py:1904, in Array.__getitem__(self, index)
   1901     return self
   1903 out = "getitem-" + tokenize(self, index2)
-> 1904 dsk, chunks = slice_array(out, self.name, self.chunks, index2, self.itemsize)
   1906 graph = HighLevelGraph.from_collections(out, dsk, dependencies=[self])
   1908 meta = meta_from_array(self._meta, ndim=len(chunks))

File ~/miniforge3/lib/python3.9/site-packages/dask/array/slicing.py:174, in slice_array(out_name, in_name, blockdims, index, itemsize)
    171 index += (slice(None, None, None),) * missing
    173 # Pass down to next function
--> 174 dsk_out, bd_out = slice_with_newaxes(out_name, in_name, blockdims, index, itemsize)
    176 bd_out = tuple(map(tuple, bd_out))
    177 return dsk_out, bd_out

File ~/miniforge3/lib/python3.9/site-packages/dask/array/slicing.py:196, in slice_with_newaxes(out_name, in_name, blockdims, index, itemsize)
    193         where_none[i] -= n
    195 # Pass down and do work
--> 196 dsk, blockdims2 = slice_wrap_lists(out_name, in_name, blockdims, index2, itemsize)
    198 if where_none:
    199     expand = expander(where_none)

File ~/miniforge3/lib/python3.9/site-packages/dask/array/slicing.py:242, in slice_wrap_lists(out_name, in_name, blockdims, index, itemsize)
    238 where_list = [
    239     i for i, ind in enumerate(index) if is_arraylike(ind) and ind.ndim > 0
    240 ]
    241 if len(where_list) > 1:
--> 242     raise NotImplementedError("Don't yet support nd fancy indexing")
    243 # Is the single list an empty list? In this case just treat it as a zero
    244 # length slice
    245 if where_list and not index[where_list[0]].size:

NotImplementedError: Don't yet support nd fancy indexing
Environment information ``` python active environment : base active env location : /Users/javedali/miniforge3 shell level : 1 user config file : /Users/javedali/.condarc populated config files : /Users/javedali/miniforge3/.condarc /Users/javedali/.condarc conda version : 4.12.0 conda-build version : not installed python version : 3.9.10.final.0 virtual packages : __osx=12.3.1=0 __unix=0=0 __archspec=1=arm64 base environment : /Users/javedali/miniforge3 (writable) conda av data dir : /Users/javedali/miniforge3/etc/conda conda av metadata url : None channel URLs : https://conda.anaconda.org/conda-forge/osx-arm64 https://conda.anaconda.org/conda-forge/noarch package cache : /Users/javedali/miniforge3/pkgs /Users/javedali/.conda/pkgs envs directories : /Users/javedali/miniforge3/envs /Users/javedali/.conda/envs platform : osx-arm64 user-agent : conda/4.12.0 requests/2.27.1 CPython/3.9.10 Darwin/21.4.0 OSX/12.3.1 UID:GID : 501:20 netrc file : None offline mode : False ```
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tiledb 2.7.1 h29b8279_0 conda-forge tk 8.6.12 he1e0b03_0 conda-forge tldextract 3.2.0 pyhd8ed1ab_0 conda-forge toolz 0.11.2 pyhd8ed1ab_0 conda-forge tornado 6.1 py39h5161555_2 conda-forge tqdm 4.63.0 pyhd8ed1ab_0 conda-forge traitlets 5.1.1 pyhd8ed1ab_0 conda-forge typing_extensions 4.1.1 pyha770c72_0 conda-forge tzcode 2022a h1c322ee_0 conda-forge tzdata 2022a h191b570_0 conda-forge unicodedata2 14.0.0 py39h5161555_0 conda-forge urllib3 1.26.9 pyhd8ed1ab_0 conda-forge watchdog 2.1.6 py39h5161555_1 conda-forge wcwidth 0.2.5 pyh9f0ad1d_2 conda-forge webencodings 0.5.1 py_1 conda-forge websocket-client 1.3.1 pyhd8ed1ab_0 conda-forge wget 1.20.3 hb616509_1 conda-forge wheel 0.37.1 pyhd8ed1ab_0 conda-forge widgetsnbextension 3.6.0 py39h2804cbe_0 conda-forge xarray 2022.3.0 pyhd8ed1ab_0 conda-forge xerces-c 3.2.3 hff64b9e_4 conda-forge xlrd 2.0.1 pypi_0 pypi xorg-libxau 1.0.9 h27ca646_0 conda-forge xorg-libxdmcp 1.1.3 h27ca646_0 conda-forge xyzservices 2022.3.0 pyhd8ed1ab_0 conda-forge xz 5.2.5 h642e427_1 conda-forge yaml 0.2.5 h3422bc3_2 conda-forge zeromq 4.3.4 hbdafb3b_1 conda-forge zict 2.1.0 pyhd8ed1ab_0 conda-forge zipp 3.7.0 pyhd8ed1ab_1 conda-forge zlib 1.2.11 hee7b306_1013 conda-forge zstd 1.5.2 h861e0a7_0 conda-forge ```
max-sixty commented 2 years ago

@javedali99 please could you supply an MVCE?

javedali99 commented 2 years ago

@javedali99 please could you supply an MVCE?

# download data
for yr in range(2011,2015): 
    url = f'https://downloads.psl.noaa.gov/Datasets/cpc_us_precip/RT/precip.V1.0.{yr}.nc'
    savename = url.split('/')[-1]
    urllib.request.urlretrieve(url,savename)

# combine netcdf files
ds2011_2014 = xr.open_mfdataset('precip.V1.0.*.nc', concat_dim='time', combine='nested')

# coordinates
top = 40
bottom = 37
left = 258
right = 265.4 

# subsetting the data based on boundary coordinates
ds_sel = ds2011_2014.isel(lon=(ds2011_2014.lon >= left) & (ds2011_2014.lon <= right),
                          lat=(ds2011_2014.lat >= bottom) & (ds2011_2014.lat <= top),
                          )
max-sixty commented 2 years ago

I'm getting a different error around the encoding — please could the MVCE not use external data? Check out the link on the label, or the issue template, for more tips. Thanks

```python --------------------------------------------------------------------------- KeyError Traceback (most recent call last) File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/file_manager.py:199, in CachingFileManager._acquire_with_cache_info(self, needs_lock) 198 try: --> 199 file = self._cache[self._key] 200 except KeyError: File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/lru_cache.py:53, in LRUCache.__getitem__(self, key) 52 with self._lock: ---> 53 value = self._cache[key] 54 self._cache.move_to_end(key) KeyError: [, ('/home/jovyan/precip.V1.0.2014.nc',), 'r', (('clobber', True), ('diskless', False), ('format', 'NETCDF4'), ('persist', False))] During handling of the above exception, another exception occurred: OSError Traceback (most recent call last) Input In [5], in 1 # combine netcdf files ----> 2 ds2011_2014 = xr.open_mfdataset('precip.V1.0.*.nc', concat_dim='time', combine='nested', engine='netcdf4') File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/api.py:908, in open_mfdataset(paths, chunks, concat_dim, compat, preprocess, engine, data_vars, coords, combine, parallel, join, attrs_file, combine_attrs, **kwargs) 905 open_ = open_dataset 906 getattr_ = getattr --> 908 datasets = [open_(p, **open_kwargs) for p in paths] 909 closers = [getattr_(ds, "_close") for ds in datasets] 910 if preprocess is not None: File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/api.py:908, in (.0) 905 open_ = open_dataset 906 getattr_ = getattr --> 908 datasets = [open_(p, **open_kwargs) for p in paths] 909 closers = [getattr_(ds, "_close") for ds in datasets] 910 if preprocess is not None: File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/api.py:495, in open_dataset(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, backend_kwargs, *args, **kwargs) 483 decoders = _resolve_decoders_kwargs( 484 decode_cf, 485 open_backend_dataset_parameters=backend.open_dataset_parameters, (...) 491 decode_coords=decode_coords, 492 ) 494 overwrite_encoded_chunks = kwargs.pop("overwrite_encoded_chunks", None) --> 495 backend_ds = backend.open_dataset( 496 filename_or_obj, 497 drop_variables=drop_variables, 498 **decoders, 499 **kwargs, 500 ) 501 ds = _dataset_from_backend_dataset( 502 backend_ds, 503 filename_or_obj, (...) 510 **kwargs, 511 ) 512 return ds File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/netCDF4_.py:553, in NetCDF4BackendEntrypoint.open_dataset(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, group, mode, format, clobber, diskless, persist, lock, autoclose) 532 def open_dataset( 533 self, 534 filename_or_obj, (...) 549 autoclose=False, 550 ): 552 filename_or_obj = _normalize_path(filename_or_obj) --> 553 store = NetCDF4DataStore.open( 554 filename_or_obj, 555 mode=mode, 556 format=format, 557 group=group, 558 clobber=clobber, 559 diskless=diskless, 560 persist=persist, 561 lock=lock, 562 autoclose=autoclose, 563 ) 565 store_entrypoint = StoreBackendEntrypoint() 566 with close_on_error(store): File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/netCDF4_.py:382, in NetCDF4DataStore.open(cls, filename, mode, format, group, clobber, diskless, persist, lock, lock_maker, autoclose) 376 kwargs = dict( 377 clobber=clobber, diskless=diskless, persist=persist, format=format 378 ) 379 manager = CachingFileManager( 380 netCDF4.Dataset, filename, mode=mode, kwargs=kwargs 381 ) --> 382 return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose) File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/netCDF4_.py:330, in NetCDF4DataStore.__init__(self, manager, group, mode, lock, autoclose) 328 self._group = group 329 self._mode = mode --> 330 self.format = self.ds.data_model 331 self._filename = self.ds.filepath() 332 self.is_remote = is_remote_uri(self._filename) File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/netCDF4_.py:391, in NetCDF4DataStore.ds(self) 389 @property 390 def ds(self): --> 391 return self._acquire() File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/netCDF4_.py:385, in NetCDF4DataStore._acquire(self, needs_lock) 384 def _acquire(self, needs_lock=True): --> 385 with self._manager.acquire_context(needs_lock) as root: 386 ds = _nc4_require_group(root, self._group, self._mode) 387 return ds File /srv/conda/envs/notebook/lib/python3.8/contextlib.py:113, in _GeneratorContextManager.__enter__(self) 111 del self.args, self.kwds, self.func 112 try: --> 113 return next(self.gen) 114 except StopIteration: 115 raise RuntimeError("generator didn't yield") from None File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/file_manager.py:187, in CachingFileManager.acquire_context(self, needs_lock) 184 @contextlib.contextmanager 185 def acquire_context(self, needs_lock=True): 186 """Context manager for acquiring a file.""" --> 187 file, cached = self._acquire_with_cache_info(needs_lock) 188 try: 189 yield file File /srv/conda/envs/notebook/lib/python3.8/site-packages/xarray/backends/file_manager.py:205, in CachingFileManager._acquire_with_cache_info(self, needs_lock) 203 kwargs = kwargs.copy() 204 kwargs["mode"] = self._mode --> 205 file = self._opener(*self._args, **kwargs) 206 if self._mode == "w": 207 # ensure file doesn't get overridden when opened again 208 self._mode = "a" File src/netCDF4/_netCDF4.pyx:2307, in netCDF4._netCDF4.Dataset.__init__() File src/netCDF4/_netCDF4.pyx:1925, in netCDF4._netCDF4._ensure_nc_success() OSError: [Errno -101] NetCDF: HDF error: b'/home/jovyan/precip.V1.0.2014.nc'
dcherian commented 2 years ago 
# subsetting the data based on boundary coordinates
ds_sel = ds2011_2014.isel(lon=(ds2011_2014.lon >= left) & (ds2011_2014.lon <= right),
                          lat=(ds2011_2014.lat >= bottom) & (ds2011_2014.lat <= top),
                          )

Please use the sel method instead of a boolean mask. This will work for this dataset because lat and lon are dimension coordinates.

See https://docs.xarray.dev/en/stable/user-guide/indexing.html

javedali99 commented 2 years ago

Thanks @dcherian @max-sixty.

I solved the issue with re-installing xarray and cfgrib individually and re-starting the kernel.

max-sixty commented 2 years ago

OK, cheers @javedali99 !