snapshot...

modules/contrail/util.py

@@ -95,7 +95,7 @@ def extract(mask_image, image_ts, clavrx_path):
     vert_shear_3d = vert_shear_3d / units.hPa
 
     all_list = []
-    voxel_dict = {key: [] for key in bins_dict.keys()}
+    levels_dict = {press_bins[key]: [] for key in bins_dict.keys()}
     for key in bins_dict.keys():
         press_level = press_bins[key]
         print('working on pressure level: ', press_level)
@@ -116,12 +116,12 @@ def extract(mask_image, image_ts, clavrx_path):
             # tmp = horz_shear_3d.sel(Pressure=press, method='nearest')
             # tmp = tmp.sel(Longitude=lon, Latitude=lat, method='nearest')
 
-            voxel_dict[key].append((press_level, press, lat, lon, temp_value, rh_value, horz_shear_value, static_value, horz_wind_spd_value, vert_shear_value))
+            levels_dict[press_bins[key]].append((press_level, press, lat, lon, temp_value, rh_value, horz_shear_value, static_value, horz_wind_spd_value, vert_shear_value))
             all_list.append((press_level, press, lat, lon, temp_value, rh_value, horz_shear_value, static_value, horz_wind_spd_value, vert_shear_value))
 
     # Create pandas DataFrame for each list of tuples in voxel_dict
     voxel_dict_df = {}
-    for k, v in voxel_dict.items():
+    for k, v in levels_dict.items():
         print(k, len(v))
         df = pd.DataFrame(v,
                           columns=["pressure_level", "pressure", "lat", "lon", "temperature", "relative_humidity",