interp() now accepts date strings as desired co-ordinate locations

Fixes pydata#2284

Author: dcherian

doc/interpolation.rst

@@ -49,14 +49,14 @@ array-like, which gives the interpolated result as an array.
     da.interp(time=[2.5, 3.5])
 
 
-To interpolate data with a :py:func:`numpy.datetime64` coordinate you have to 
-wrap it explicitly in a :py:func:`numpy.datetime64` object.
+To interpolate data with a :py:func:`numpy.datetime64` coordinate you can either
+pass :py:func:`numpy.datetime64` objects or a date-string.
 
 .. ipython:: python
 
     da_dt64 = xr.DataArray([1, 3],
                            [('time', pd.date_range('1/1/2000', '1/3/2000', periods=2))])
-    da_dt64.interp(time=np.datetime64('2000-01-02'))
+    da_dt64.interp(time='2000-01-02')
 
 The interpolated data can be merged into the original :py:class:`~xarray.DataArray` 
 by specifing the time periods required.

xarray/core/dataset.py

@@ -1308,6 +1308,8 @@ def _validate_indexers(self, indexers):
         """ Here we make sure
         + indexer has a valid keys
         + indexer is in a valid data type
+        * string indexers are cast to datetime64
+          if associated index is DatetimeIndex
         """
         from .dataarray import DataArray
 
@@ -1328,6 +1330,12 @@ def _validate_indexers(self, indexers):
                 raise TypeError('cannot use a Dataset as an indexer')
             else:
                 v = np.asarray(v)
+
+                if (v.dtype.kind == 'U'
+                    and isinstance(self.coords[k].to_index(),
+                                 pd.DatetimeIndex)):
+                    v = v.astype('datetime64[ns]')
+
                 if v.ndim == 0:
                     v = as_variable(v)
                 elif v.ndim == 1:

xarray/tests/test_interp.py

@@ -478,3 +478,11 @@ def test_datetime():
                     0.5 * (da.isel(time=0) + da.isel(time=1)))
     assert_allclose(actual.isel(time=1).drop('time'),
                     0.5 * (da.isel(time=1) + da.isel(time=2)))
+
+    x_new = np.array(['2000-01-01T12:00',
+                      '2000-01-02T12:00'])
+    actual = da.interp(time=x_new)
+    assert_allclose(actual.isel(time=0).drop('time'),
+                    0.5 * (da.isel(time=0) + da.isel(time=1)))
+    assert_allclose(actual.isel(time=1).drop('time'),
+                    0.5 * (da.isel(time=1) + da.isel(time=2)))