snapshot...

modules/deeplearning/icing_fcn.py

@@ -572,7 +572,7 @@ class IcingIntensityFCN:
 
     def setup_eval_pipeline(self, data_dct, num_tiles=1):
         self.data_dct = data_dct
-        # self.cth_max = data_dct.get('cth_high_avg', None)
+        self.cth_max = data_dct.get('cth_high_avg', None)
         idxs = np.arange(num_tiles)
         self.num_data_samples = idxs.shape[0]
 
@@ -1157,13 +1157,7 @@ def run_evaluate_static(data_dct, num_tiles, ckpt_dir_s_path, day_night='DAY', l
     return preds_dct, probs_dct
 
 
-def run_evaluate_static_2(model, data_dct, num_tiles, prob_thresh=0.5, flight_levels=[0, 1, 2, 3, 4],
-                          use_flight_altitude=False, use_max_cth_level=False):
-    model.cth_max = None
-    flight_levels = flight_levels.copy()
-
-    if not use_flight_altitude:
-        flight_levels = [0]
+def run_evaluate_static_2(model, data_dct, num_tiles, prob_thresh=0.5, flight_levels=[0, 1, 2, 3, 4]):
 
     probs_dct = {flvl: None for flvl in flight_levels}
     preds_dct = {flvl: None for flvl in flight_levels}
@@ -1176,16 +1170,6 @@ def run_evaluate_static_2(model, data_dct, num_tiles, prob_thresh=0.5, flight_le
         probs_dct[flvl] = model.test_probs.flatten()
         preds_dct[flvl] = model.test_preds.flatten()
 
-    if use_max_cth_level:
-        flvl = 5
-        model.cth_max = data_dct.get('cth_high_avg', None)
-        model.flight_level = flvl
-        model.setup_eval_pipeline(data_dct, num_tiles)
-        model.do_evaluate(prob_thresh=prob_thresh)
-
-        probs_dct[flvl] = model.test_probs.flatten()
-        preds_dct[flvl] = model.test_preds.flatten()
-
     return preds_dct, probs_dct