Use complex nan by default when interpolating out of bounds (#6019)

* use complex nan by default when interpolating out of bounds

* update whats-new.rst

* remove unecessary complexity

* analyse `dtype.kind` instead of using `np.iscomplexobj`

Co-authored-by: Alexandre Poux <work@alexandrepoux.fr>

doc/whats-new.rst

@@ -26,7 +26,8 @@ New Features
 
 Breaking changes
 ~~~~~~~~~~~~~~~~
-
+- Use complex nan when interpolating complex values out of bounds by default (instead of real nan) (:pull:`6019`).
+  By `Alexandre Poux <https://github.com/pums974>`_.
 
 Deprecations
 ~~~~~~~~~~~~

xarray/core/missing.py

@@ -82,9 +82,11 @@ def __init__(self, xi, yi, method="linear", fill_value=None, period=None):
         self._xi = xi
         self._yi = yi
 
+        nan = np.nan if yi.dtype.kind != "c" else np.nan + np.nan * 1j
+
         if fill_value is None:
-            self._left = np.nan
-            self._right = np.nan
+            self._left = nan
+            self._right = nan
         elif isinstance(fill_value, Sequence) and len(fill_value) == 2:
             self._left = fill_value[0]
             self._right = fill_value[1]
@@ -143,10 +145,12 @@ def __init__(
         self.cons_kwargs = kwargs
         self.call_kwargs = {}
 
+        nan = np.nan if yi.dtype.kind != "c" else np.nan + np.nan * 1j
+
         if fill_value is None and method == "linear":
-            fill_value = np.nan, np.nan
+            fill_value = nan, nan
         elif fill_value is None:
-            fill_value = np.nan
+            fill_value = nan
 
         self.f = interp1d(
             xi,

xarray/tests/test_interp.py

@@ -907,3 +907,16 @@ def test_coord_attrs(x, expect_same_attrs):
 
     has_same_attrs = ds.interp(x=x).x.attrs == base_attrs
     assert expect_same_attrs == has_same_attrs
+
+
+@requires_scipy
+def test_interp1d_complex_out_of_bounds():
+    """Ensure complex nans are used by default"""
+    da = xr.DataArray(
+        np.exp(0.3j * np.arange(4)),
+        [("time", np.arange(4))],
+    )
+
+    expected = da.interp(time=3.5, kwargs=dict(fill_value=np.nan + np.nan * 1j))
+    actual = da.interp(time=3.5)
+    assert_identical(actual, expected)

xarray/tests/test_missing.py

@@ -687,3 +687,25 @@ def test_interpolate_na_2d(coords):
         coords=coords,
     )
     assert_equal(actual, expected_x)
+
+
+@requires_scipy
+def test_interpolators_complex_out_of_bounds():
+    """Ensure complex nans are used for complex data"""
+
+    xi = np.array([-1, 0, 1, 2, 5], dtype=np.float64)
+    yi = np.exp(1j * xi)
+    x = np.array([-2, 1, 6], dtype=np.float64)
+
+    expected = np.array(
+        [np.nan + np.nan * 1j, np.exp(1j), np.nan + np.nan * 1j], dtype=yi.dtype
+    )
+
+    for method, interpolator in [
+        ("linear", NumpyInterpolator),
+        ("linear", ScipyInterpolator),
+    ]:
+
+        f = interpolator(xi, yi, method=method)
+        actual = f(x)
+        assert_array_equal(actual, expected)