snapshot...

modules/deeplearning/cloud_fraction_fcn.py

@@ -814,16 +814,14 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
     lats_out = np.zeros((y_len, x_len), dtype=np.float32)
     border = int((KERNEL_SIZE - 1)/2)
     cld_frac_out[border:y_len - border, border:x_len - border] = cld_frac[0, :, :]
-    lons_out[border:y_len - border, border:x_len - border] = lons[:, :]
-    lats_out[border:y_len - border, border:x_len - border] = lats[:, :]
 
     bt = denormalize(bt, 'temp_11_0um_nom', mean_std_dct)
     refl_avg = denormalize(refl_avg, 'refl_0_65um_nom', mean_std_dct)
 
     if out_file is not None:
-        np.save(out_file, (cld_frac_out, bt, refl_avg, cp))
+        np.save(out_file, (cld_frac_out, bt, refl_avg, cp, lons, lats))
     else:
-        return cld_frac_out, bt, refl_avg, cp
+        return cld_frac_out, bt, refl_avg, cp, lons, lats
 
 
 def analyze_3cat(file):