snapshot...

modules/deeplearning/cloud_fraction_fcn_abi.py

@@ -817,8 +817,6 @@ class SRCNN:
         refl_hi = get_grid_values_all(h5f, 'refl_0_65um_nom_max_sub')
         refl_std = get_grid_values_all(h5f, 'refl_0_65um_nom_stddev_sub')
         cp = get_grid_values_all(h5f, label_param)
-        # lons = get_grid_values_all(h5f, 'longitude')
-        # lats = get_grid_values_all(h5f, 'latitude')
 
         cld_frac = self.run_inference_(bt, refl, refl_lo, refl_hi, refl_std, cp)
 
@@ -923,10 +921,11 @@ class SRCNN:
         refl = normalize(refl, 'refl_0_65um_nom', mean_std_dct)
         refl_lo = normalize(refl_lo, 'refl_0_65um_nom', mean_std_dct)
         refl_hi = normalize(refl_hi, 'refl_0_65um_nom', mean_std_dct)
+        refl_rng = refl_hi - refl_lo
         refl_std = np.where(np.isnan(refl_std), 0, refl_std)
         cp = np.where(np.isnan(cp), 0, cp)
 
-        data = np.stack([bt, refl, refl_lo, refl_hi, refl_std, cp], axis=2)
+        data = np.stack([bt, refl, refl_rng, refl_std, cp], axis=2)
         data = np.expand_dims(data, axis=0)
         probs = self.do_inference(data)
         cld_frac = probs.argmax(axis=3)