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Linear interp with NaNs in nd indexer #4233

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merged 10 commits into from
Aug 27, 2020
Merged

Linear interp with NaNs in nd indexer #4233

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9d52010
Added test for nd interpolation with nan
jenssss Jul 17, 2020
47886ce
Now ignoring NaNs in missing._localize
jenssss Jul 17, 2020
5daa841
Added `@requires_scipy` to test. Also updated what's new.
jenssss Jul 17, 2020
2929491
Merge remote-tracking branch 'upstream/master' into NaNs-in-linear-in…
jenssss Aug 23, 2020
2152fb8
Added numpy>=1.18 checks with `LooseVersion`
jenssss Aug 23, 2020
484052f
Added checks for np.datetime64 type
jenssss Aug 24, 2020
80e07cb
Merge remote-tracking branch 'upstream/master' into NaNs-in-linear-in…
jenssss Aug 24, 2020
8313c3e
Removed `raise ValueError` from previous commit
jenssss Aug 25, 2020
6b59771
Added datetime `NaT` test.
jenssss Aug 25, 2020
d187ba6
Merge remote-tracking branch 'upstream/master' into NaNs-in-linear-in…
jenssss Aug 25, 2020
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4 changes: 2 additions & 2 deletions xarray/core/missing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -560,8 +560,8 @@ def _localize(var, indexes_coords):
indexes = {}
for dim, [x, new_x] in indexes_coords.items():
index = x.to_index()
imin = index.get_loc(np.min(new_x.values), method="nearest")
imax = index.get_loc(np.max(new_x.values), method="nearest")
imin = index.get_loc(np.nanmin(new_x.values), method="nearest")
imax = index.get_loc(np.nanmax(new_x.values), method="nearest")
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It looks that np.nanmin (and nanmax) supports np.datetime-dtype only with numpy>=1.18.
We can copy np.nanmin to our core/npcompat.py and call this function here.

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I think they added some low level loops to fix this (numpy/numpy#14841) so guess we cannot copy nanmin over and have to use if LooseVersion(np. __version__) < LooseVersion("1.18") (or similar).

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I added some LooseVersion checks for numpy>=1.18 in the d044142 commit to the missing._localize function and to the test. Would this do?


indexes[dim] = slice(max(imin - 2, 0), imax + 2)
indexes_coords[dim] = (x[indexes[dim]], new_x)
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19 changes: 19 additions & 0 deletions xarray/tests/test_interp.py
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Expand Up @@ -274,6 +274,25 @@ def test_interpolate_nd_nd():
da.interp(a=ia)


def test_interpolate_nd_with_nan():
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"""Interpolate an array with an nd indexer."""

# Create indexer into `a` with dimensions (y, x)
x = [0, 1, 2]
y = [10, 20]
c = {"x": x, "y": y}
a = np.arange(6, dtype=float).reshape(2, 3)
a[0, 1] = np.nan
ia = xr.DataArray(a, dims=("y", "x"), coords=c)

da = xr.DataArray([1, 2, 2], dims=("a"), coords={"a": [0, 2, 4]})
out = da.interp(a=ia)
expected = xr.DataArray(
[[1.0, np.nan, 2.0], [2.0, 2.0, np.nan]], dims=("y", "x"), coords=c
)
xr.testing.assert_allclose(out.drop_vars("a"), expected)


@pytest.mark.parametrize("method", ["linear"])
@pytest.mark.parametrize("case", [0, 1])
def test_interpolate_scalar(method, case):
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