snapshot...

modules/deeplearning/cloud_opd_srcnn_abi.py

@@ -263,7 +263,7 @@ class SRCNN:
             idx = params.index(param)
             tmp = input_data[:, idx, :, :]
             tmp = tmp[:, self.slc_y_m, self.slc_x_m]
-            tmp = self.upsample_nearest(tmp)
+            tmp = upsample_nearest(tmp)
             if param != 'refl_substddev_ch01':
                 tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
             else:
@@ -683,16 +683,16 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
 
     h5f = h5py.File(in_file, 'r')
 
-    refl = get_grid_values_all(h5f, 'super/refl_0_65um')
+    refl = get_grid_values_all(h5f, 'refl_0_65um_nom')
     ylen, xlen = refl.shape
     refl = refl[int(ylen/2):ylen, :]
     LEN_Y, LEN_X = refl.shape
 
-    bt = get_grid_values_all(h5f, 'orig/temp_11_0um')
+    bt = get_grid_values_all(h5f, 'temp_11_0um_nom')
     ylen, xlen = bt.shape
     bt = bt[int(ylen/2):ylen, :]
 
-    cld_opd = get_grid_values_all(h5f, 'super/' + label_param)
+    cld_opd = get_grid_values_all(h5f, label_param)
     ylen, xlen = cld_opd.shape
     cld_opd = cld_opd[int(ylen/2):ylen, :]
     cld_opd_hres = cld_opd.copy()