Use nearest for llm with vis06

Use nearest neighbour when combining with cloud mask
gerritholl · Jan 24, 2025 · 2e48efe · 2e48efe
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Showing 3 changed files with 16 additions and 14 deletions.
diff --git a/satpy/tests/behave/features/image_comparison.feature b/satpy/tests/behave/features/image_comparison.feature
@@ -2,16 +2,16 @@ Feature: Image Comparison
 
   Scenario Outline: Compare generated image with reference image
     Given I have a <composite> reference image file from <satellite> resampled to <area>
-    When I generate a new <composite> image file from <satellite> case <case> with <reader> for <area> with clipping <clip>
+    When I generate a new <composite> image file from <satellite> case <case> with <reader> for <area> resampling with <resampler> with clipping <clip>
     Then the generated image should be the same as the reference image
 
     Examples:
-      |satellite | case | composite  | reader | area | clip |
-      |Meteosat-12 | scan_night | cloudtop | fci_l1c_nc | sve | True |
-      |Meteosat-12 | scan_night | night_microphysics | fci_l1c_nc | sve | True |
-      |Meteosat-12 | mali_day | essl_colorized_low_level_moisture | fci_l1c_nc | mali | False |
-      |Meteosat-12 | spain_day | colorized_low_level_moisture_with_vis06 | fci_l1c_nc,fci_l2_nc | spain | False |
-      |GOES17   | americas_night | airmass  | abi_l1b | null | null |
-      |GOES16   | americas_night | airmass  | abi_l1b | null | null |
-      |GOES16   | americas_night | ash      | abi_l1b | null | null |
-      |GOES17   | americas_night | ash      | abi_l1b | null | null |
+      |satellite | case | composite  | reader | area | resampler | clip |
+      |Meteosat-12 | scan_night | cloudtop | fci_l1c_nc | sve | gradient_search | True |
+      |Meteosat-12 | scan_night | night_microphysics | fci_l1c_nc | sve | gradient_search | True |
+      |Meteosat-12 | mali_day | essl_colorized_low_level_moisture | fci_l1c_nc | mali | gradient_search | False |
+      |Meteosat-12 | spain_day | colorized_low_level_moisture_with_vis06 | fci_l1c_nc,fci_l2_nc | nearest | spain | False |
+      |GOES17   | americas_night | airmass  | abi_l1b | null | null | null |
+      |GOES16   | americas_night | airmass  | abi_l1b | null | null | null |
+      |GOES16   | americas_night | ash      | abi_l1b | null | null | null |
+      |GOES17   | americas_night | ash      | abi_l1b | null | null | null |
diff --git a/satpy/tests/behave/features/steps/image_comparison.py b/satpy/tests/behave/features/steps/image_comparison.py
@@ -65,8 +65,8 @@ def step_given_reference_image(context, composite, satellite, area):
 
 
 @when("I generate a new {composite} image file from {satellite} case {case} "
-      "with {reader} for {area} with clipping {clip}")
-def step_when_generate_image(context, composite, satellite, case, reader, area, clip):
+      "with {reader} for {area} resampling with {resampler} with clipping {clip}")
+def step_when_generate_image(context, composite, satellite, case, reader, area, resampler,clip):
     """Generate test images."""
     os.environ["OMP_NUM_THREADS"] = os.environ["MKL_NUM_THREADS"] = "2"
     os.environ["PYTROLL_CHUNK_SIZE"] = "1024"
@@ -86,7 +86,7 @@ def step_when_generate_image(context, composite, satellite, case, reader, area,
     if area == "null":
         ls = scn
     else:
-        ls = scn.resample(area, resampler="gradient_search")
+        ls = scn.resample(area, resampler=resampler)
 
     # Save the generated image in the generated folder
     generated_image_path = os.path.join(context.test_results_dir, "generated",

diff --git a/utils/create_reference.py b/utils/create_reference.py
@@ -47,15 +47,17 @@ def generate_images(props):
 
     if "," in props.reader:
         reader = props.reader.split(",")
+        resampler = "nearest"  # use nearest when combining with cloud mask
     else:
         reader = props.reader
+        resampler = "gradient_search"
     scn = Scene(reader=reader, filenames=filenames)
 
     scn.load(props.composites)
     if props.area == "native":
         ls = scn.resample(resampler="native")
     elif props.area is not None:
-        ls = scn.resample(props.area, resampler="gradient_search")
+        ls = scn.resample(props.area, resampler=resampler)
     else:
         ls = scn