Fixed ndfilters.mean_filter() to support instances of astropy.units.Quantity.

ndfilters/_mean.py

@@ -91,6 +91,7 @@ def _mean_filter_1d(
         array=array,
         size=size,
         where=where,
+        out=np.empty_like(array),
     )
 
     result = result.reshape(shape)
@@ -105,9 +106,9 @@ def _mean_filter_1d_numba(
     array: np.ndarray,
     size: int,
     where: np.ndarray,
+    out: np.ndarray,
 ) -> np.ndarray:
 
-    result = np.empty_like(array)
     num_t, num_x = array.shape
 
     halfsize = size // 2
@@ -132,6 +133,6 @@ def _mean_filter_1d_numba(
                     sum += array[t, k]
                     count += 1
 
-            result[t, i] = sum / count
+            out[t, i] = sum / count
 
-    return result
+    return out

ndfilters/_tests/test_mean.py

@@ -2,6 +2,7 @@
 import numpy as np
 import scipy.ndimage
 import scipy.stats
+import astropy.units as u
 import ndfilters
 
 
@@ -10,7 +11,7 @@
     argvalues=[
         np.random.random(5),
         np.random.random((5, 6)),
-        np.random.random((5, 6, 7)),
+        np.random.random((5, 6, 7)) * u.mm,
     ],
 )
 @pytest.mark.parametrize(
@@ -75,9 +76,13 @@ def test_mean_filter(
         size=size_scipy,
         mode="constant",
     ) / scipy.ndimage.uniform_filter(
-        input=np.ones_like(array),
+        input=np.ones(array.shape),
         size=size_scipy,
         mode="constant",
     )
 
-    assert np.allclose(result, expected)
+    if isinstance(result, u.Quantity):
+        assert np.allclose(result.value, expected)
+        assert result.unit == array.unit
+    else:
+        assert np.allclose(result, expected)

pyproject.toml

@@ -23,6 +23,7 @@ dynamic = ["version"]
 test = [
     "pytest",
     "scipy",
+    "astropy",
 ]
 doc = [
     "pytest",