bug fix

modules/deeplearning/icing_cnn.py

@@ -951,6 +951,9 @@ class IcingIntensityNN:
 def run_restore_static(filename_l1b, filename_l2, ckpt_dir_s_path):
     ckpt_dir_s = os.listdir(ckpt_dir_s_path)
     cm_s = []
+    prob_s = []
+    labels = None
+
     for ckpt in ckpt_dir_s:
         ckpt_dir = ckpt_dir_s_path + ckpt
         if not os.path.isdir(ckpt_dir):
@@ -958,13 +961,20 @@ def run_restore_static(filename_l1b, filename_l2, ckpt_dir_s_path):
         nn = IcingIntensityNN()
         nn.run_restore(filename_l1b, filename_l2, ckpt_dir)
         cm_s.append(tf.math.confusion_matrix(nn.test_labels.flatten(), nn.test_preds.flatten()))
+        prob_s.append(nn.test_probs.flatten())
+        if labels is None:  # These should be the same
+            labels = nn.test_labels.flatten()
+
     num = len(cm_s)
     cm_avg = cm_s[0]
+    prob_avg = prob_s[0]
     for k in range(num-1):
         cm_avg += cm_s[k+1]
+        prob_avg += prob_s[k+1]
     cm_avg /= num
+    prob_avg /= num
 
-    return cm_avg
+    return labels, prob_avg, cm_avg
 
 
 def run_evaluate_static(h5f, ckpt_dir_s_path, prob_thresh=0.5, satellite='GOES16', domain='FD'):