switch to total column prediction for now - need more R&D

modules/deeplearning/icing_cnn.py

@@ -1050,7 +1050,7 @@ def run_restore_static(filename_l1b, filename_l2, ckpt_dir_s_path, day_night='DA
     return labels, prob_avg, cm_avg
 
 
-def run_evaluate_static(data_dct, ll, cc, ckpt_dir_s_path, flight_level=4, prob_thresh=0.5, satellite='GOES16', domain='FD'):
+def run_evaluate_static(data_dct, ll, cc, ckpt_dir_s_path, day_night='DAY', flight_level=4, prob_thresh=0.5, satellite='GOES16', domain='FD'):
     num_elems = len(cc)
     num_lines = len(ll)
     cc = np.array(cc)
@@ -1065,7 +1065,7 @@ def run_evaluate_static(data_dct, ll, cc, ckpt_dir_s_path, flight_level=4, prob_
         ckpt_dir = ckpt_dir_s_path + ckpt
         if not os.path.isdir(ckpt_dir):
             continue
-        nn = IcingIntensityNN()
+        nn = IcingIntensityNN(day_night=day_night)
         nn.flight_level = flight_level
         nn.setup_eval_pipeline(data_dct, num_lines * num_elems)
         nn.build_model()