Recursive filter mask zeros modifications

improver/cli/recursive_filter.py

@@ -16,6 +16,7 @@ def process(
     *,
     iterations: int = 1,
     variable_mask: bool = False,
+    mask_zeros: bool = False,
 ):
     """Module to apply a recursive filter to neighbourhooded data.
 
@@ -50,6 +51,11 @@ def process(
             different mask. If False and cube is masked, a check will be made that
             the same mask is present on each spatial slice. If True, each spatial
             slice of cube may contain a different spatial mask.
+        mask_zeros (bool):
+            If set true all of the values of 0 in the cube will be masked,
+            stopping the recursive filter from spreading values into these areas.
+            They will then be unmasked later on. If the input cube was masked
+            this mask will be reapplied to the output at the end.
 
     Returns:
         iris.cube.Cube:
@@ -59,5 +65,8 @@ def process(
 
     plugin = RecursiveFilter(iterations=iterations)
     return plugin(
-        cube, smoothing_coefficients=smoothing_coefficients, variable_mask=variable_mask
+        cube,
+        smoothing_coefficients=smoothing_coefficients,
+        variable_mask=variable_mask,
+        mask_zeros=mask_zeros,
     )

improver/nbhood/recursive_filter.py

@@ -382,10 +382,6 @@ def process(
         else:
             cube_mask = None
 
-        if mask_zeros:
-            cube.data = np.ma.masked_where(cube.data == 0.0, cube.data, copy=False)
-            # This masks any array element that is zero
-
         cube_format = next(cube.slices([cube.coord(axis="y"), cube.coord(axis="x")]))
         coeffs_x, coeffs_y = self._validate_coefficients(
             cube_format, smoothing_coefficients
@@ -402,6 +398,11 @@ def process(
                         "Input cube contains spatial slices with different masks."
                     )
 
+        # This masks any array element that is zero. Performed after variable array
+        # check as zeros may not be located consistently across slices.
+        if mask_zeros:
+            cube.data = np.ma.masked_where(cube.data == 0.0, cube.data, copy=False)
+
         recursed_cube = iris.cube.CubeList()
         for cslice in cube.slices([cube.coord(axis="y"), cube.coord(axis="x")]):
             padded_cube = pad_cube_with_halo(

improver_tests/acceptance/SHA256SUMS

@@ -839,9 +839,11 @@ f69103cececd76e27bbff5a96e9c74c0e708dcb7f18459ade3eb448639992b34  ./precipitatio
 ae048c636992e80b79c6cbb44b36339b30ea8d0ef1db72cd3f4de8766346fa1d  ./recursive-filter/input.nc
 b6cdb8bf877bb0b3b78ad224b50b9272b65732bf9e39a88df704209e228bf4c0  ./recursive-filter/input_masked.nc
 11c428f6fb0202ab0f975e58e52d17342c50f607aee4fd0e387a2a62c188790e  ./recursive-filter/input_variable_masked.nc
+ce0ff757524da235a94421a3e2a254958811c562c739a7a73c3fa9cd4d00ddb5  ./recursive-filter/input_with_zeros.nc
 b4f7acb4fb95640f50a11cdb02038a1e66f2bc02d65b87230ff5a1dab649f141  ./recursive-filter/kgo_basic.nc
 0f5ae62721603eb258cd54b195673be0fde0effbecbae7bf88100913a603bd38  ./recursive-filter/kgo_internal_mask_with_re_mask.nc
 6e77a397bea8fd914a182ed9152b9b75b9e751968c432d1d45ffe971c6f8a815  ./recursive-filter/kgo_variable_internal_mask_with_re_mask.nc
+a0660ea5d5540b9476e8b77d5f488db2f36842c0da3a1d068d52986353fe445f  ./recursive-filter/kgo_with_zeros.nc
 49497750007d283c609d8d1e1415f9a8be1f1c8b9f4c5c74e3b741ab3c3f681e  ./recursive-filter/smoothing_coefficients.nc
 f4128d6ea8da41f46eb3b86f49cd6a60a0c81dabced89f1016372c20230fd85d  ./regrid/basic/kgo.nc
 b431242e8abec923d1ad6d54022e3602511274e8b35bab81fa63a2383a9020b4  ./regrid/bilinear_2/kgo_multi_realization.nc

improver_tests/acceptance/test_recursive_filter.py

@@ -55,3 +55,21 @@ def test_variable_internal_mask(tmp_path):
     ]
     run_cli(args)
     acc.compare(output_path, kgo_path)
+
+
+def test_zero_masking(tmp_path):
+    """Test recursive filter with zero masking preserves areas of zeros."""
+    kgo_dir = acc.kgo_root() / "recursive-filter"
+    kgo_path = kgo_dir / "kgo_with_zeros.nc"
+    input_path = kgo_dir / "input_with_zeros.nc"
+    smoothing_coefficients_path = kgo_dir / "smoothing_coefficients.nc"
+    output_path = tmp_path / "output.nc"
+    args = [
+        input_path,
+        smoothing_coefficients_path,
+        "--mask-zeros",
+        "--output",
+        output_path,
+    ]
+    run_cli(args)
+    acc.compare(output_path, kgo_path)