Fixes from last commit

Author: chantreux

scripts/derived/reanalysis-cerra-land_accumulation.py

@@ -142,7 +142,7 @@ def accumulation(ds,var):
         mask_var = (df_parameters['filename_variable'] == var) & (df_parameters['product_type'] == 'derived')
         var_row = require_single_row(df_parameters, mask_var, f"{var}/derived")
         # Use utility function to load input path
-        var_download_path = load_output_path_from_row(input_row], dataset)
+        var_download_path = load_output_path_from_row(input_row, dataset)
         var_files = np.sort(glob.glob(f"{var_download_path}/*.nc"))
         print(f"{var_download_path}/*.nc")
         logging.info(f"List of file variables: {var_files}")

scripts/derived/reanalysis-era5-single-levels.py

@@ -19,9 +19,6 @@ def main():
     derived_variables_list = derived_variables.tolist()
     for var in derived_variables_list:
         logging.info(f"Calculating {var}")
-        mask_input = (df_parameters['filename_variable'] == var) & (df_parameters['product_type'] == 'raw')
-        input_row = require_single_row(df_parameters, mask_input, f"{var}/raw")
-
         mask_var = (df_parameters['filename_variable'] == var) & (df_parameters['product_type'] == 'derived')
         var_row = require_single_row(df_parameters, mask_var, f"{var}/derived")
 
@@ -52,7 +49,7 @@ def main():
                 ds_merge = xr.merge([ds_u, ds_v])
                 sfcwind = operations.sfcwind_from_u_v(ds_merge)
                 sfcwind_daily = operations.resample_to_daily(sfcwind,"valid_time")
-                
+
                 logging.info(f"Saving calculated sfcwind to {dest_dir}")
                 sfcwind_daily.to_netcdf(output_file)
 

scripts/interpolation/reanalysis-cerra-single-levels.py

@@ -36,8 +36,9 @@ def main():
     variables_file_path = f"../../requests/{dataset}.csv"
     df_parameters = pd.read_csv(variables_file_path)
 
-    mask_ref = (df_parameters['interpolation'] != 'native') & (df_parameters['product_type'] == 'derived')
-    interpolated_row = require_single_row(df_parameters, mask_ref, "interpolated/derived reference row")
+    #Take first row with interpolation not native and product_type derived as reference for loading the reference grid
+    interpolated_row = df_parameters[(df_parameters['interpolation'] != 'native') & (df_parameters['product_type'] == 'derived')].iloc[0]
+
 
     interpolation_file = interpolated_row.get('interpolation_file', 'land_sea_mask_0.0625degree.nc4')
     ds_ref=xr.open_dataset(f"/lustre/gmeteo/WORK/chantreuxa/cica/data/resources/reference-grids/{interpolation_file}")