snapshot...

modules/contrail/util.py

@@ -96,6 +96,7 @@ def extract(mask_image, image_ts, clavrx_path):
 
     all_list = []
     levels_dict = {press_bins[key]: [] for key in bins_dict.keys()}
+    levels_dict_cidx = {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)
@@ -116,6 +117,7 @@ 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')
 
+            levels_dict_cidx[press_level].append(c_idx)
             levels_dict[press_level].append((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))
 
@@ -128,6 +130,14 @@ def extract(mask_image, image_ts, clavrx_path):
                                    "horz_shear_deform", "static_stability", "horz_wind_speed", "vert_wind_shear"])
         levels_dict_df[k] = df
 
+    # Create a contrail location image for each pressure layer
+    levels_dict_image = {}
+    for k, v in levels_dict_cidx.items():
+        cidx_nda = np.array(v)
+        flat_image = np.zeros(5424*5424)
+        flat_image[cidx_nda] = 1
+        levels_dict_image[k] = flat_image.reshape(5424, 5424)
+
     # Create a DataFrame for all tuples
     all_df = pd.DataFrame(all_list,
                           columns=["pressure_level", "pressure", "lat", "lon", "temperature", "relative_humidity",