use meshgrid

modules/deeplearning/icing_cnn.py

@@ -1006,8 +1006,9 @@ def run_evaluate_static(h5f, ckpt_dir_s_path, prob_thresh=0.5, satellite='GOES16
     else:
         preds = np.argmax(probs, axis=1)
 
-    cc = np.array(cc)
-    ll = np.array(ll)
+    ll, cc = np.meshgrid(ll, cc, indexing='ij')
+    #cc = np.array(cc)
+    #ll = np.array(ll)
     ice_mask = preds == 1
     print(cc.shape, ll.shape, ice_mask.shape)
     ice_cc = cc[ice_mask]