🐛 fix landsat generation - confidence mask

Author: raphaelrpl

cube_builder/utils/image.py

@@ -737,7 +737,7 @@ def linear_raster_scale(array: ArrayType,
 
 
 def get_resample_method(name: str) -> Resampling:
-    """Retrieve a resampling method from name
+    """Retrieve a resampling method from name.
 
     Note:
         This method uses ``rasterio.warp.Resampling``.

cube_builder/utils/processing.py

@@ -797,6 +797,16 @@ def blend(activity, band_map, quality_band, build_clear_observation=False, block
                 saturated = radsat_extract_bits(saturated, 1, 7).astype(numpy.bool_)
                 masked.mask[saturated] = True
 
+            # Get current observation file name
+            file_path = bandlist[order].name
+            file_date = datetime.strptime(merges_band_map[file_path], '%Y-%m-%d')
+            day_of_year = file_date.timetuple().tm_yday
+
+            if build_clear_observation and is_combined_collection:
+                datasource_block = provenance_merge_map[file_date.strftime('%Y-%m-%d')].dataset.read(1, window=window)
+                if mask_values['bits']:
+                    confidence.oli = numpy.isin(datasource_block, index_landsat_oli)
+
             if mask_values['bits']:
                 matched = get_qa_mask(masked,
                                       clear_data=clear_values,
@@ -829,16 +839,6 @@ def blend(activity, band_map, quality_band, build_clear_observation=False, block
 
             stack_total_observation[window.row_off: row_offset, window.col_off: col_offset] += copy_mask.astype(numpy.uint8)
 
-            # Get current observation file name
-            file_path = bandlist[order].name
-            file_date = datetime.strptime(merges_band_map[file_path], '%Y-%m-%d')
-            day_of_year = file_date.timetuple().tm_yday
-
-            if build_clear_observation and is_combined_collection:
-                datasource_block = provenance_merge_map[file_date.strftime('%Y-%m-%d')].dataset.read(1, window=window)
-                if mask_values['bits']:
-                    confidence.oli = datasource_block == index_landsat_oli
-
             # Find all no data in destination STACK image
             stack_raster_where_nodata = numpy.where(
                 stack_raster[window.row_off: row_offset, window.col_off: col_offset] == nodata
@@ -849,9 +849,6 @@ def blend(activity, band_map, quality_band, build_clear_observation=False, block
                                                               stack_raster[window.row_off: row_offset,
                                                               window.col_off: col_offset].shape)
 
-            if build_clear_observation and is_combined_collection:
-                datasource_block = provenance_merge_map[file_date.strftime('%Y-%m-%d')].dataset.read(1, window=window)
-
             # Find all valid/cloud in destination STACK image
             raster_where_data = numpy.where(raster != nodata)
             raster_data_pos = numpy.ravel_multi_index(raster_where_data, raster.shape)