Added numpy>=1.18 checks with LooseVersion

doc/whats-new.rst

@@ -74,7 +74,7 @@ Bug fixes
 - Fixed overflow issue causing incorrect results in computing means of :py:class:`cftime.datetime`
   arrays (:issue:`4341`). By `Spencer Clark <https://github.com/spencerkclark>`_.
 - Fix `KeyError` when doing linear interpolation to an nd `DataArray`
-  that contains NaNs (:pull:`4233`).
+  that contains NaNs (:pull:`4233`). Requires `numpy` version `1.18` or newer.
   By `Jens Svensmark <https://github.com/jenssss>`_
 
 

xarray/core/missing.py

@@ -1,5 +1,6 @@
 import datetime as dt
 import warnings
+from distutils.version import LooseVersion
 from functools import partial
 from numbers import Number
 from typing import Any, Callable, Dict, Hashable, Sequence, Union
@@ -551,8 +552,14 @@ def _localize(var, indexes_coords):
     indexes = {}
     for dim, [x, new_x] in indexes_coords.items():
         index = x.to_index()
-        imin = index.get_loc(np.nanmin(new_x.values), method="nearest")
-        imax = index.get_loc(np.nanmax(new_x.values), method="nearest")
+        if LooseVersion(np.__version__) >= LooseVersion("1.18"):
+            imin = index.get_loc(np.nanmin(new_x.values), method="nearest")
+            imax = index.get_loc(np.nanmax(new_x.values), method="nearest")
+        else:
+            imin = index.get_loc(np.min(new_x.values), method="nearest")
+            imax = index.get_loc(np.max(new_x.values), method="nearest")
+        # imin=0
+        # imax=0
 
         indexes[dim] = slice(max(imin - 2, 0), imax + 2)
         indexes_coords[dim] = (x[indexes[dim]], new_x)

xarray/tests/test_interp.py

@@ -6,6 +6,7 @@
 
 import xarray as xr
 from xarray.tests import (
+    LooseVersion,
     assert_allclose,
     assert_equal,
     assert_identical,
@@ -277,9 +278,13 @@ def test_interpolate_nd_nd():
         da.interp(a=ia)
 
 
+@pytest.mark.skipif(
+    LooseVersion(np.__version__) < "1.18",
+    reason="only in numpy>=1.18 does np.nanmin/max support np.datatime-dtype",
+)
 @requires_scipy
 def test_interpolate_nd_with_nan():
-    """Interpolate an array with an nd indexer."""
+    """Interpolate an array with an nd indexer and `NaN` values."""
 
     # Create indexer into `a` with dimensions (y, x)
     x = [0, 1, 2]