snapshot...

modules/deeplearning/cloud_fraction_fcn_abi.py

@@ -778,7 +778,6 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
 
     bt = get_grid_values_all(h5f, 'temp_11_0um_nom')
     y_len, x_len = bt.shape
-    print(y_len, x_len)
     h_y_len = int(y_len/2)
     refl = get_grid_values_all(h5f, 'refl_0_65um_nom')
     refl_lo = get_grid_values_all(h5f, 'refl_0_65um_nom_min_sub')
@@ -794,7 +793,6 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
     refl_hi_nh = refl_hi[0:h_y_len+1, :]
     refl_std_nh = refl_std[0:h_y_len+1, :]
     cp_nh = cp[0:h_y_len+1, :]
-    print(cp_nh.shape)
 
     bt_sh = bt[h_y_len-1:y_len, :]
     refl_sh = refl[h_y_len-1:y_len, :]
@@ -802,15 +800,12 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
     refl_hi_sh = refl_hi[h_y_len-1:y_len, :]
     refl_std_sh = refl_std[h_y_len-1:y_len, :]
     cp_sh = cp[h_y_len-1:y_len, :]
-    print(bt_sh.shape)
 
     h5f.close()
 
     cld_frac_nh = run_evaluate_static_(bt_nh, refl_nh, refl_lo_nh, refl_hi_nh, refl_std_nh, cp_nh, ckpt_dir)
-    print(cld_frac_nh.shape)
 
     cld_frac_sh = run_evaluate_static_(bt_sh, refl_sh, refl_lo_sh, refl_hi_sh, refl_std_sh, cp_sh, ckpt_dir)
-    print(cld_frac_sh.shape)
 
     cld_frac_out = np.zeros((y_len, x_len), dtype=np.int8)
     border = int((KERNEL_SIZE - 1)/2)