diff --git a/src/bathymetric_adjustment.py b/src/bathymetric_adjustment.py index d6fff27f..75b6425c 100644 --- a/src/bathymetric_adjustment.py +++ b/src/bathymetric_adjustment.py @@ -190,8 +190,8 @@ def correct_rating_for_ai_based_bathymetry(fim_dir, huc, strm_order, bathy_file_ aib_df0 = aib_bathy_data_df[ ['feature_id', 'missing_xs_area_m2', 'missing_wet_perimeter_m', 'Bathymetry_source'] ] - #test = aib_df[aib_df.duplicated(subset='feature_id', keep=False)] - aib_df = aib_df0.drop_duplicates(subset=['feature_id'], keep = 'first') + # test = aib_df[aib_df.duplicated(subset='feature_id', keep=False)] + aib_df = aib_df0.drop_duplicates(subset=['feature_id'], keep='first') aib_df.index = range(len(aib_df)) # Get src_full from each branch @@ -214,7 +214,7 @@ def correct_rating_for_ai_based_bathymetry(fim_dir, huc, strm_order, bathy_file_ # Merge in missing bathy data and fill Nans if "missing_xs_area_m2" not in src_df.columns: src_df.drop(columns=["Bathymetry_source"], inplace=True) - src_df = src_df.merge(aib_df, on='feature_id', how='left', validate='many_to_one') + src_df = src_df.merge(aib_df, on='feature_id', how='left', validate='many_to_one') # print([src,src_df.columns]) src_df.Bathymetry_source else: src_df = pd.read_csv(src, low_memory=False) @@ -299,7 +299,7 @@ def apply_src_adjustment_for_bathymetry( log_text = "" try: if os.path.exists(bathy_file_ehydro): - msg = f"correcting rating curve for ehydro bathy for huc : {huc}" + msg = f"Correcting rating curve for ehydro bathy for huc : {huc}" log_text += msg + '\n' print(msg) log_text += correct_rating_for_ehydro_bathymetry(fim_dir, huc, bathy_file_ehydro, verbose) @@ -319,7 +319,7 @@ def apply_src_adjustment_for_bathymetry( log_text = "" try: if os.path.exists(bathy_file_aibased): - msg = f"correcting rating curve for AI-based bathy for huc : {huc}" + msg = f"Correcting rating curve for AI-based bathy for huc : {huc}" log_text += msg + '\n' print(msg + '\n')