Make preprocessors mask_above/below_threshold, mask_inside/outside_range lazy (#2169)

Author: joergbenke

.zenodo.json

@@ -181,6 +181,10 @@
         {
             "affiliation": "DLR, Germany",
             "name": "Bauer, Julian"
+        },
+        {
+            "affiliation": "Forschungszentrum Juelich, Germany",
+            "name": "Benke, Joerg"
         }
     ],
     "description": "ESMValCore: A community tool for pre-processing data from Earth system models in CMIP and running analysis scripts.",

CITATION.cff

@@ -190,6 +190,10 @@ authors:
     affiliation: "DLR, Germany"
     family-names: Bauer
     given-names: Julian
+  -
+    affiliation: "Forschungszentrum Juelich (FZJ), Germany"
+    family-names: Benke
+    given-names: Joerg
 
 cff-version: 1.2.0
 date-released: 2023-07-04

esmvalcore/preprocessor/_mask.py

@@ -281,8 +281,8 @@ def _mask_with_shp(cube, shapefilename, region_indices=None):
     if region_indices:
         regions = [regions[idx] for idx in region_indices]
 
-    # Create a mask for the data
-    mask = np.zeros(cube.shape, dtype=bool)
+    # Create a mask for the data (np->da)
+    mask = da.zeros(cube.shape, dtype=bool)
 
     # Create a set of x,y points from the cube
     # 1D regular grids
@@ -400,7 +400,8 @@ def mask_above_threshold(cube, threshold):
     iris.cube.Cube
         thresholded cube.
     """
-    cube.data = np.ma.masked_where(cube.data > threshold, cube.data)
+    cube.data = (da.ma.masked_where(cube.core_data() > threshold,
+                                    cube.core_data()))
     return cube
 
 
@@ -422,7 +423,8 @@ def mask_below_threshold(cube, threshold):
     iris.cube.Cube
         thresholded cube.
     """
-    cube.data = np.ma.masked_where(cube.data < threshold, cube.data)
+    cube.data = (da.ma.masked_where(cube.core_data() < threshold,
+                                    cube.core_data()))
     return cube
 
 
@@ -446,7 +448,7 @@ def mask_inside_range(cube, minimum, maximum):
     iris.cube.Cube
         thresholded cube.
     """
-    cube.data = np.ma.masked_inside(cube.data, minimum, maximum)
+    cube.data = da.ma.masked_inside(cube.core_data(), minimum, maximum)
     return cube
 
 
@@ -470,7 +472,7 @@ def mask_outside_range(cube, minimum, maximum):
     iris.cube.Cube
         thresholded cube.
     """
-    cube.data = np.ma.masked_outside(cube.data, minimum, maximum)
+    cube.data = da.ma.masked_outside(cube.core_data(), minimum, maximum)
     return cube