fix some cf issues

modules/icing/util.py

@@ -3,7 +3,7 @@ import deeplearning.icing_fcn as icing_fcn
 import deeplearning.icing_cnn as icing_cnn
 from icing.pirep_goes import setup, time_filter_3
 from icing.moon_phase import moon_phase
-from util.util import get_time_tuple_utc, is_day, check_oblique, get_average, homedir, write_icing_file_nc4,\
+from util.util import get_time_tuple_utc, is_day, check_oblique, get_median, homedir, write_icing_file_nc4,\
     write_icing_file_nc4_viirs,\
     make_for_full_domain_predict, make_for_full_domain_predict_viirs_clavrx, prepare_evaluate
 from util.plot import make_icing_image
@@ -130,7 +130,7 @@ def run_icing_predict(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output_dir=h
         for j in range(num_lines):
             for i in range(num_elems):
                 k = i + j*num_elems
-                avg_bt.append(get_average(bt_10_4[k]))
+                avg_bt.append(get_median(bt_10_4[k]))
 
                 if not check_oblique(satzen[k]):
                     continue
@@ -155,8 +155,8 @@ def run_icing_predict(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output_dir=h
             preds_2d_dct[flvl] = fd_preds
             probs_2d_dct[flvl] = fd_probs
 
-        if (day_night == 'AUTO' or day_night == 'DAY') and num_day_tiles > 0:
-
+        if day_night == 'AUTO' or day_night == 'DAY':
+            if num_day_tiles > 0:
                 day_data_dct = {name: [] for name in day_train_params}
                 for name in day_train_params:
                     for k in day_idxs:
@@ -179,10 +179,9 @@ def run_icing_predict(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output_dir=h
                     fd_preds[day_idxs] = day_preds[:]
                     fd_probs[day_idxs] = day_probs[:]
 
-        if (day_night == 'AUTO' or day_night == 'NIGHT') and num_nght_tiles > 0:
-            model_path = night_model_path
-
+            if num_nght_tiles > 0:
                 mode = 'NIGHT'
+                model_path = night_model_path
                 if use_dnb and lunar_illuminated:
                     model_path = day_model_path
                     mode = 'DAY'
@@ -196,8 +195,10 @@ def run_icing_predict(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output_dir=h
                 for ds_name in nght_train_params:
                     nght_grd_dct[ds_name] = np.stack(nght_data_dct[ds_name])
 
-            preds_nght_dct, probs_nght_dct = model_module.run_evaluate_static(nght_grd_dct, num_nght_tiles, model_path,
-                                                                              day_night=mode, l1b_or_l2=l1b_andor_l2,
+                preds_nght_dct, probs_nght_dct = model_module.run_evaluate_static(nght_grd_dct, num_nght_tiles,
+                                                                                  model_path,
+                                                                                  day_night=mode,
+                                                                                  l1b_or_l2=l1b_andor_l2,
                                                                                   prob_thresh=prob_thresh,
                                                                                   use_flight_altitude=use_flight_altitude,
                                                                                   flight_levels=flight_levels)
@@ -210,6 +211,38 @@ def run_icing_predict(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output_dir=h
                     fd_preds[nght_idxs] = nght_preds[:]
                     fd_probs[nght_idxs] = nght_probs[:]
 
+        elif day_night == 'NIGHT':
+            model_path = night_model_path
+            all_idxs = np.arange(num_lines * num_elems)
+
+            mode = 'NIGHT'
+            if use_dnb and lunar_illuminated:
+                model_path = day_model_path
+                mode = 'DAY'
+                nght_train_params = train_params_dnb
+
+            nght_data_dct = {name: [] for name in nght_train_params}
+            for name in nght_train_params:
+                for k in all_idxs:
+                    nght_data_dct[name].append(data_dct[name][k])
+            nght_grd_dct = {name: None for name in nght_train_params}
+            for ds_name in nght_train_params:
+                nght_grd_dct[ds_name] = np.stack(nght_data_dct[ds_name])
+
+            preds_nght_dct, probs_nght_dct = model_module.run_evaluate_static(nght_grd_dct, num_nght_tiles, model_path,
+                                                                              day_night=mode, l1b_or_l2=l1b_andor_l2,
+                                                                              prob_thresh=prob_thresh,
+                                                                              use_flight_altitude=use_flight_altitude,
+                                                                              flight_levels=flight_levels)
+            for flvl in flight_levels:
+                nght_preds = preds_nght_dct[flvl]
+                nght_probs = probs_nght_dct[flvl]
+                fd_preds = preds_2d_dct[flvl]
+                fd_probs = probs_2d_dct[flvl]
+                fd_preds[all_idxs] = nght_preds[:]
+                fd_probs[all_idxs] = nght_probs[:]
+
+        # combine day and night into full grid  ------------------------------------------
         for flvl in flight_levels:
             fd_preds = preds_2d_dct[flvl]
             fd_probs = probs_2d_dct[flvl]