issues: 529644880

MCVE Code Sample

```python import xarray as xr xr.show_versions()

url = 'http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME/NCEP-CFSv2/.HINDCAST/.MONTHLY/.sst/dods' fullda = xr.open_dataset(url, decode_times=False,chunks={'S': 'auto', 'L': 'auto', 'M':'auto','X':'auto','Y':'auto'}) print(fullda) print(fullda['sst'][:10,0,0,0,0].values)

```

Expected Output

python <xarray.Dataset> Dimensions: (L: 10, M: 24, S: 348, X: 360, Y: 181) Coordinates: * X (X) float32 0.0 1.0 2.0 3.0 4.0 ... 355.0 356.0 357.0 358.0 359.0 * L (L) float32 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 * S (S) float32 264.0 265.0 266.0 267.0 ... 608.0 609.0 610.0 611.0 * M (M) float32 1.0 2.0 3.0 4.0 5.0 6.0 ... 20.0 21.0 22.0 23.0 24.0 * Y (Y) float32 -90.0 -89.0 -88.0 -87.0 -86.0 ... 87.0 88.0 89.0 90.0 Data variables: sst (S, L, M, Y, X) float32 dask.array<chunksize=(29, 10, 24, 51, 45), meta=np.ndarray> Attributes: Conventions: IRIDL [-25.652588 -35.577393 -48.702896 -51.3853 -50.687195 -50.341995 -50.407593 -54.955994 -52.052994 -47.31279 ]

Problem Description

This should return the array’s data as a numpy.ndarray according to the documentation and as shown above. I tested this with various versions of netcdf4 and I get the error below for netcdf4 versions 1.5.1, 1.5.1.2, 1.5.3 (latest version). If I use netcdf4 version 1.5.1, I get the expected output as above.

``` python <xarray.Dataset> Dimensions: (L: 10, M: 24, S: 348, X: 360, Y: 181) Coordinates: * X (X) float32 0.0 1.0 2.0 3.0 4.0 ... 355.0 356.0 357.0 358.0 359.0 * L (L) float32 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 * S (S) float32 264.0 265.0 266.0 267.0 ... 608.0 609.0 610.0 611.0 * M (M) float32 1.0 2.0 3.0 4.0 5.0 6.0 ... 20.0 21.0 22.0 23.0 24.0 * Y (Y) float32 -90.0 -89.0 -88.0 -87.0 -86.0 ... 87.0 88.0 89.0 90.0 Data variables: sst (S, L, M, Y, X) float32 dask.array<chunksize=(29, 10, 24, 51, 45), meta=np.ndarray> Attributes: Conventions: IRIDL Traceback (most recent call last): File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/xarray/backends/netCDF4_.py", line 84, in _getitem array = getitem(original_array, key) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/xarray/backends/common.py", line 54, in robust_getitem return array[key] File "netCDF4/_netCDF4.pyx", line 4408, in netCDF4._netCDF4.Variable.getitem File "netCDF4/_netCDF4.pyx", line 5350, in netCDF4._netCDF4.Variable._get IndexError: index exceeds dimension bounds

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "testpython.py", line 7, in <module> print(fullda['sst'][:10,0,0,0,0].values) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/xarray/core/dataarray.py", line 567, in values return self.variable.values File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/xarray/core/variable.py", line 448, in values return as_array_or_item(self._data) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/xarray/core/variable.py", line 254, in _as_array_or_item data = np.asarray(data) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/numpy/core/_asarray.py", line 85, in asarray return array(a, dtype, copy=False, order=order) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/dask/array/core.py", line 1314, in __array__ x = self.compute() File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/dask/base.py", line 165, in compute (result,) = compute(self, traverse=False, kwargs) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/dask/base.py", line 436, in compute results = schedule(dsk, keys, kwargs) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/dask/threaded.py", line 81, in get *kwargs File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/dask/local.py", line 486, in get_async raise_exception(exc, tb) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/dask/local.py", line 316, in reraise raise exc File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/dask/local.py", line 222, in execute_task result = _execute_task(task, data) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/dask/core.py", line 119, in _execute_task return func(args2) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/dask/array/core.py", line 106, in getter c = np.asarray(c) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/numpy/core/_asarray.py", line 85, in asarray return array(a, dtype, copy=False, order=order) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/xarray/core/indexing.py", line 481, in array return np.asarray(self.array, dtype=dtype) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/numpy/core/_asarray.py", line 85, in asarray return array(a, dtype, copy=False, order=order) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/xarray/core/indexing.py", line 643, in array return np.asarray(self.array, dtype=dtype) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/numpy/core/_asarray.py", line 85, in asarray return array(a, dtype, copy=False, order=order) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/xarray/core/indexing.py", line 547, in array return np.asarray(array[self.key], dtype=None) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/xarray/backends/netCDF4.py", line 72, in getitem key, self.shape, indexing.IndexingSupport.OUTER, self.getitem File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/xarray/core/indexing.py", line 827, in explicit_indexing_adapter result = raw_indexing_method(raw_key.tuple) File "/homes/kpegion/.conda/envs/testenv3-dev/lib/python3.6/site-packages/xarray/backends/netCDF4.py", line 94, in _getitem raise IndexError(msg) IndexError: The indexing operation you are attempting to perform is not valid on netCDF4.Variable object. Try loading your data into memory first by calling .load(). ```

Output of xr.show_versions()