diff --git a/modules/deeplearning/cloud_fraction_fcn_abi.py b/modules/deeplearning/cloud_fraction_fcn_abi.py index e82e3ed53b2447bc4da32f2bea95c872316832b4..f26fd28b196ecb0326e717dce701ef96a59df211 100644 --- a/modules/deeplearning/cloud_fraction_fcn_abi.py +++ b/modules/deeplearning/cloud_fraction_fcn_abi.py @@ -779,6 +779,7 @@ 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') refl_hi = get_grid_values_all(h5f, 'refl_0_65um_nom_max_sub') @@ -787,33 +788,34 @@ def run_evaluate_static(in_file, out_file, ckpt_dir): lons = get_grid_values_all(h5f, 'longitude') lats = get_grid_values_all(h5f, 'latitude') - bt_nh = bt[0:2712+1, :] - refl_nh = refl[0:2712+1, :] - refl_lo_nh = refl_lo[0:2712+1, :] - refl_hi_nh = refl_hi[0:2712+1, :] - refl_std_nh = refl_std[0:2712+1, :] - cp_nh = cp[0:2712+1, :] + bt_nh = bt[0:h_y_len+1, :] + refl_nh = refl[0:h_y_len+1, :] + refl_lo_nh = refl_lo[0:h_y_len+1, :] + 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[2712-1:y_len, :] - refl_sh = refl[2712-1:y_len, :] - refl_lo_sh = refl_lo[2712-1:y_len, :] - refl_hi_sh = refl_hi[2712-1:y_len, :] - refl_std_sh = refl_std[2712-1:y_len, :] - cp_sh = cp[2712-1:y_len, :] + bt_sh = bt[h_y_len-1:y_len, :] + refl_sh = refl[h_y_len-1:y_len, :] + refl_lo_sh = refl_lo[h_y_len-1:y_len, :] + 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) - cld_frac_out[border:2712, border:x_len - border] = cld_frac_nh[0, :, :] - cld_frac_out[2712:y_len - border, border:x_len - border] = cld_frac_sh[0, :, :] + cld_frac_out[border:h_y_len, border:x_len - border] = cld_frac_nh[0, :, :] + cld_frac_out[h_y_len:y_len - border, border:x_len - border] = cld_frac_sh[0, 1::, :] bt = denormalize(bt, 'temp_11_0um_nom', mean_std_dct) refl = denormalize(refl, 'refl_0_65um_nom', mean_std_dct)