Rewriting results for categorical bands

polygonqueryonraster/app.py

@@ -175,6 +175,7 @@ class GeoTIFFService:
         and non-categorical data, producing different statistical measures accordingly.
 
         For categorical data, it computes statistics for each band separately, treating each band as a different category.
+        For non-categorical data, it computes standard statistical measures for each band.
 
         Args:
             combined_raster_data (numpy.ndarray): The combined raster data from all relevant tiles.
@@ -194,6 +195,9 @@ class GeoTIFFService:
             masked_band_data = band_data * polygon_mask if num_bands > 1 else band_data * polygon_mask.squeeze()
 
             if categorical:
+                # Ignore no-data value (assumed to be 0)
+                masked_band_data = masked_band_data[masked_band_data != 0]
+
                 # Compute categorical statistics for each band
                 unique, counts = np.unique(masked_band_data, return_counts=True)
                 stats_result[f'band_{band}'] = dict(zip(unique.tolist(), counts.tolist()))
@@ -214,6 +218,7 @@ class GeoTIFFService:
 
 
 
+
     @staticmethod
     def compute_entropy(x):
         """