interp() now accepts date strings as desired co-ordinate locations (#2325)

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

Fixes #2284

* Consolidated tests.

* Update condition for python 2

* Add additional test.

* Add decorator.

Author: dcherian

doc/interpolation.rst

@@ -48,15 +48,13 @@ array-like, which gives the interpolated result as an array.
     # interpolation
     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 pass a 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.

doc/whats-new.rst

@@ -41,6 +41,10 @@ Enhancements
   (:issue:`1186`)
   By `Seth P <https://github.com/seth-p>`_.
 
+- When interpolating over a ``datetime64`` axis, you can now provide a datetime string instead of a ``datetime64`` object. E.g. ``da.interp(time='1991-02-01')``
+  (:issue:`2284`)
+  By `Deepak Cherian <https://github.com/dcherian>`_.
+
 
 Bug fixes
 ~~~~~~~~~

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' or v.dtype.kind == 'S')
+                    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

@@ -462,19 +462,31 @@ def test_interp_like():
 
 
 @requires_scipy
-def test_datetime():
-    da = xr.DataArray(np.random.randn(24), dims='time',
+@pytest.mark.parametrize('x_new, expected', [
+    (pd.date_range('2000-01-02', periods=3), [1, 2, 3]),
+    (np.array([np.datetime64('2000-01-01T12:00'),
+               np.datetime64('2000-01-02T12:00')]), [0.5, 1.5]),
+    (['2000-01-01T12:00', '2000-01-02T12:00'], [0.5, 1.5]),
+    (['2000-01-01T12:00'], 0.5),
+    pytest.param('2000-01-01T12:00', 0.5, marks=pytest.mark.xfail)
+])
+def test_datetime(x_new, expected):
+    da = xr.DataArray(np.arange(24), dims='time',
                       coords={'time': pd.date_range('2000-01-01', periods=24)})
 
-    x_new = pd.date_range('2000-01-02', periods=3)
     actual = da.interp(time=x_new)
-    expected = da.isel(time=[1, 2, 3])
-    assert_allclose(actual, expected)
+    expected_da = xr.DataArray(np.atleast_1d(expected), dims=['time'],
+                               coords={'time': (np.atleast_1d(x_new)
+                                                .astype('datetime64[ns]'))})
 
-    x_new = np.array([np.datetime64('2000-01-01T12:00'),
-                      np.datetime64('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)))
+    assert_allclose(actual, expected_da)
+
+
+@requires_scipy
+def test_datetime_single_string():
+    da = xr.DataArray(np.arange(24), dims='time',
+                      coords={'time': pd.date_range('2000-01-01', periods=24)})
+    actual = da.interp(time='2000-01-01T12:00')
+    expected = xr.DataArray(0.5)
+
+    assert_allclose(actual.drop('time'), expected)