snapshot...

modules/icing/util.py

@@ -1560,6 +1560,7 @@ def run_icing_predict_image_1x1(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', ou
         varX_ngth, solzen, satzen, cldmsk, ll, cc = prepare_evaluate1x1(h5f, name_list=nght_train_params, satellite=satellite, domain=domain, offset=8)
         num_elems = len(cc)
         num_lines = len(ll)
+        print('num_lines, num_elems: ', num_lines, num_elems)
 
         day_idxs = solzen < 80.0
         num_day_tiles = np.sum(day_idxs)
@@ -1579,15 +1580,15 @@ def run_icing_predict_image_1x1(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', ou
 
             varX_std = stdSclr_day.transform(varX_day)
             varX_std = np.where(np.isnan(varX_std), 0, varX_std)
-            probs = day_model.predict_proba(varX_std)
-            fd_probs[:] = probs[day_idxs]
+            probs = day_model.predict_proba(varX_std)[:, 1]
+            fd_probs[day_idxs] = probs[day_idxs]
 
         if (day_night == 'AUTO' or day_night == 'NIGHT') and num_nght_tiles > 0:
 
             varX_std = stdSclr_nght.transform(varX_ngth)
             varX_std = np.where(np.isnan(varX_std), 0, varX_std)
-            probs = nght_model.predict_proba(varX_std)
-            fd_probs[:] = probs[nght_idxs]
+            probs = nght_model.predict_proba(varX_std)[:, 1]
+            fd_probs[nght_idxs] = probs[nght_idxs]
 
         max_prob = fd_probs.reshape((num_lines, num_elems))