Not able to slice dataset using its own coordinate value

[rafa-guedes]

Code Sample, a copy-pastable example if possible

In [1]: import xarray as xr
In [2]: ds = xr.open_dataset('test.nc')
In [3]: ds.sel(time=ds.time[0]) #works
In [4]: ds.sel(time=ds.time[1], method='nearest') #works
In [5]: ds.sel(time=ds.time[1]) #does not work

In [6]: ds.time[0]
Out[6]: 
<xarray.DataArray 'time' ()>
array('2018-02-12T06:00:00.000000000', dtype='datetime64[ns]')
Coordinates:
    time     datetime64[ns] 2018-02-12T06:00:00
    site     float64 ...
Attributes:
    standard_name:  time

In [7]: ds.time[1]
Out[7]: 
<xarray.DataArray 'time' ()>
array('2018-02-12T06:59:59.999986000', dtype='datetime64[ns]')
Coordinates:
    time     datetime64[ns] 2018-02-12T06:59:59.999986
    site     float64 ...
Attributes:
    standard_name:  time

Problem description

xarray sometimes fails to slice using its own coordinate values. It looks like it may have to do with precision. Traceback below, test file attached.

In [7]: ds.sel(time=ds.time[1])
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-7-371d2f896b4a> in <module>()
----> 1 ds.sel(time=ds.time[1])

/usr/lib/python2.7/site-packages/xarray/core/dataset.pyc in sel(self, method, tolerance, drop, **indexers)
   1444 
   1445         pos_indexers, new_indexes = indexing.remap_label_indexers(
-> 1446             self, v_indexers, method=method, tolerance=tolerance
   1447         )
   1448         # attach indexer's coordinate to pos_indexers

/usr/lib/python2.7/site-packages/xarray/core/indexing.pyc in remap_label_indexers(data_obj, indexers, method, tolerance)
    234         else:
    235             idxr, new_idx = convert_label_indexer(index, label,
--> 236                                                   dim, method, tolerance)
    237             pos_indexers[dim] = idxr
    238             if new_idx is not None:

/usr/lib/python2.7/site-packages/xarray/core/indexing.pyc in convert_label_indexer(index, label, index_name, method, tolerance)
    163                 indexer, new_index = index.get_loc_level(label.item(), level=0)
    164             else:
--> 165                 indexer = get_loc(index, label.item(), method, tolerance)
    166         elif label.dtype.kind == 'b':
    167             indexer = label

/usr/lib/python2.7/site-packages/xarray/core/indexing.pyc in get_loc(index, label, method, tolerance)
     93 def get_loc(index, label, method=None, tolerance=None):
     94     kwargs = _index_method_kwargs(method, tolerance)
---> 95     return index.get_loc(label, **kwargs)
     96 
     97 

/usr/lib/python2.7/site-packages/pandas/core/indexes/datetimes.pyc in get_loc(self, key, method, tolerance)
   1444                 return Index.get_loc(self, stamp, method, tolerance)
   1445             except KeyError:
-> 1446                 raise KeyError(key)
   1447             except ValueError as e:
   1448                 # list-like tolerance size must match target index size

KeyError: 1518418799999986000L

Expected Output

Output of xr.show_versions()

In [9]: xr.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.14.final.0
python-bits: 64
OS: Linux
OS-release: 4.14.15-1-ARCH
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: en_NZ.UTF-8
LOCALE: en_NZ.UTF-8

xarray: 0.10.0
pandas: 0.22.0
numpy: 1.14.0
scipy: 0.17.1
netCDF4: 1.2.9
h5netcdf: None
Nio: None
bottleneck: None
cyordereddict: None
dask: 0.11.1
matplotlib: 2.1.0
cartopy: 0.14.2
seaborn: None
setuptools: 34.2.0
pip: 9.0.1
conda: None
pytest: 3.3.1
IPython: 5.2.2
sphinx: None

test.zip

[fujiisoup]

@rafa-guedes , thank you for reporting this.
This reproduces also in my environment.

As we use pandas index under the hood, I thought it was pandas' issue.
But I confirmed that this works with pandas

import xarray as xr
ds = xr.open_dataset('test.nc')
se = ds['wdir'].to_series()
se.loc[se.index[0]]  # works
se.loc[se.index[1]]  # also works

It looks our issue.

[fujiisoup]

I found the discrepancy between ds['time'][1] and ds.get_index('time')[1]

In [13]: ds.get_index('time')[1]
Out[13]: Timestamp('2018-02-12 06:59:59.999986560')

In [14]: ds['time'][1].values
Out[14]: numpy.datetime64('2018-02-12T06:59:59.999986000')

Last three digits are different.