Merge pull request #81 from oberonia78/fix_calval_metadata

Fix bugs/issues in calval point (0.4.1)

src/dswx_sar/dswx_sar_util.py

@@ -252,8 +252,11 @@ def save_dswx_product(wtr, output_file, geotransform,
         print(msg)
 
     band_value_dict = band_assign_value_dict
+    sorted_band_keys = sorted(
+        band_value_dict.keys(),
+        key=lambda x: x.lower() == 'inundated_vegetation')
 
-    for band_key in band_value_dict.keys():
+    for band_key in sorted_band_keys:
         if band_key.lower() in dswx_processed_bands_keys:
             dswx_product_value = band_value_dict[band_key]
             wtr[dswx_processed_bands[band_key.lower()] == 1] = \
@@ -890,7 +893,7 @@ def write_raster_block(out_raster, data,
     number_band = 1 if ndim < 3 else data.shape[0]
 
     data_start_without_pad = block_param.write_start_line - \
-        block_param.read_start_line
+        block_param.read_start_line + block_param.block_pad[0][0]
     data_end_without_pad = data_start_without_pad + \
         block_param.block_length
 

src/dswx_sar/metadata.py

@@ -283,16 +283,14 @@ def compute_spatial_coverage(data_array):
     return round(valid_pixels / total_pixels * 100, 4)
 
 
-def compute_layover_shadow_coverage(data_array, spatial_coverage):
+def compute_layover_shadow_coverage(data_array):
     """
     Compute the layover-shadow coverage.
 
     Parameters
     ----------
     data_array : np.array
         The 2D numpy array representation of the GeoTIFF.
-    spatial_coverage : float
-        Spatial coverage as a percentage.
 
     Returns
     -------
@@ -301,12 +299,16 @@ def compute_layover_shadow_coverage(data_array, spatial_coverage):
     """
     layover_shadow_pixels = np.sum(
         data_array == band_assign_value_dict['layover_shadow_mask'])
+    total_pixels = data_array.size
+    invalid_pixels = np.sum(
+        data_array == band_assign_value_dict['no_data'])
+    valid_pixels = total_pixels - invalid_pixels
 
-    if spatial_coverage > 0:
+    if valid_pixels > 0:
         return round(layover_shadow_pixels /
-                     (spatial_coverage * data_array.size), 4)
+                     valid_pixels * 100, 4)
     else:
-        return np.nan
+        return 0.0
 
 
 def _populate_statics_metadata_datasets(dswx_metadata_dict, dswx_geotiff):
@@ -326,7 +328,7 @@ def _populate_statics_metadata_datasets(dswx_metadata_dict, dswx_geotiff):
 
         spatial_cov = compute_spatial_coverage(dswx_data)
         layover_shadow_cov = compute_layover_shadow_coverage(
-            dswx_data, spatial_cov)
+            dswx_data)
 
         dswx_metadata_dict['SPATIAL_COVERAGE'] = spatial_cov
         dswx_metadata_dict['LAYOVER_SHADOW_COVERAGE'] = layover_shadow_cov

src/dswx_sar/refine_with_bimodality.py

@@ -909,7 +909,7 @@ def remove_false_water_bimodality_parallel(water_mask_path,
 
             # save the water label into file
             water_label_str = os.path.join(
-                outputdir, f'false_water_label_{pol_str}.tif')
+                outputdir, f'false_water_label_{pol_str}_{block_iter}.tif')
             dswx_sar_util.write_raster_block(
                 water_label_str,
                 output_water,
@@ -1034,7 +1034,9 @@ def remove_false_water_bimodality_parallel(water_mask_path,
                         ref_land_portion_image = ref_land_portion_output[
                             index_array_to_image]
                         dswx_sar_util.write_raster_block(
-                            os.path.join(outputdir, f'land_portion_{pol}.tif'),
+                            os.path.join(
+                                outputdir,
+                                f'land_portion_{pol}_{block_iter}.tif'),
                             ref_land_portion_image,
                             block_param,
                             geotransform=meta_info['geotransform'],
@@ -1044,11 +1046,11 @@ def remove_false_water_bimodality_parallel(water_mask_path,
                             scratch_dir=outputdir)
 
                         metric_detail_name = [
-                            f'binary_ahman_{pol}.tif',
-                            f'binary_bhc_{pol}.tif',
-                            f'binary_asurface_ratio_{pol}.tif',
-                            f'binary_bm_coeff_{pol}.tif',
-                            f'binary_bc_coeff_{pol}.tif']
+                            f'binary_ahman_{pol}_{block_iter}.tif',
+                            f'binary_bhc_{pol}_{block_iter}.tif',
+                            f'binary_asurface_ratio_{pol}_{block_iter}.tif',
+                            f'binary_bm_coeff_{pol}_{block_iter}.tif',
+                            f'binary_bc_coeff_{pol}_{block_iter}.tif']
 
                         metric_output = np.insert(metric_output,
                                                   0,
@@ -1498,7 +1500,7 @@ def run(cfg):
         merged_layer_path=bright_water_path,
         lines_per_block=lines_per_block,
         mode='or', cog_flag=True,
-        scratch_dir='.')
+        scratch_dir=outputdir)
 
     fill_gap_bindary_path = \
         fill_gap_water_bimodality_parallel(
@@ -1521,7 +1523,7 @@ def run(cfg):
         lines_per_block=lines_per_block,
         mode='or',
         cog_flag=True,
-        scratch_dir='.')
+        scratch_dir=outputdir)
 
     t_time_end = time.time()
     t_all_elapsed = t_time_end - t_all

src/dswx_sar/save_mgrs_tiles.py

@@ -661,13 +661,25 @@ def run(cfg):
     else:
         pol_set1 = pol_list
         pol_set2 = []
-        count_pols = [len(glob.glob(f'{input_dir}/*{pol_candidate}*.tif'))
-                      for pol_candidate in pol_list]
+        count_pols = []
+        for input_dir in input_list:
+            pol_types = DSWX_S1_POL_DICT['DV_POL'] + \
+                        DSWX_S1_POL_DICT['DH_POL']
+            # Initialize count
+            count_pol = 0
+            # Count files for each polarization type
+            for target_pol in pol_types:
+                pol_files = glob.glob(
+                    os.path.join(input_dir, f'*{target_pol}*.tif'))
+                count_pol += len(pol_files)
+            count_pols.append(count_pol)
+        all_match_first = all(count == count_pols[0]
+                              for count in count_pols)
 
         # count_pols is list of number of the available pols.
         # count_pols[0] is always copol because
         # Co-pol proceed before cross-pol.
-        if len(pol_list) > 1 and np.any(count_pols != count_pols[0]):
+        if len(pol_list) > 1 and not all_match_first:
             # get first character from polarization (V or H)
             pol_id = pol_list[0][0]
             pol_mode = f'MIX_DUAL_{pol_id}_SINGLE_{pol_id}_POL'

src/dswx_sar/schemas/dswx_s1.yaml

@@ -69,7 +69,7 @@ runconfig:
             # according to proper file naming conventions.
             sas_output_path: str()
 
-            product_version: num(required=False)
+            product_version: str(required=False)
 
             # DSWx-S1 product format (default is 'COG')
             output_imagery_format: enum('GTiff', 'COG', required=False)