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Commit d2fdfcfd authored by tomrink's avatar tomrink
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...@@ -10,6 +10,7 @@ import pickle ...@@ -10,6 +10,7 @@ import pickle
import h5py import h5py
import xarray as xr import xarray as xr
import gc import gc
import time
AUTOTUNE = tf.data.AUTOTUNE AUTOTUNE = tf.data.AUTOTUNE
...@@ -825,6 +826,7 @@ class SRCNN: ...@@ -825,6 +826,7 @@ class SRCNN:
def run_inference_full_disk(self, in_file, out_file): def run_inference_full_disk(self, in_file, out_file):
gc.collect() gc.collect()
t0 = time.time()
h5f = h5py.File(in_file, 'r') h5f = h5py.File(in_file, 'r')
bt = get_grid_values_all(h5f, 'temp_11_0um_nom') bt = get_grid_values_all(h5f, 'temp_11_0um_nom')
...@@ -835,6 +837,8 @@ class SRCNN: ...@@ -835,6 +837,8 @@ class SRCNN:
refl_hi = get_grid_values_all(h5f, 'refl_0_65um_nom_max_sub') 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') refl_std = get_grid_values_all(h5f, 'refl_0_65um_nom_stddev_sub')
cp = get_grid_values_all(h5f, label_param) cp = get_grid_values_all(h5f, label_param)
t1 = time.time()
print(' read time:', (t1-t0))
# lons = get_grid_values_all(h5f, 'longitude') # lons = get_grid_values_all(h5f, 'longitude')
# lats = get_grid_values_all(h5f, 'latitude') # lats = get_grid_values_all(h5f, 'latitude')
...@@ -852,9 +856,11 @@ class SRCNN: ...@@ -852,9 +856,11 @@ class SRCNN:
refl_std_sh = refl_std[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, :] cp_sh = cp[h_y_len - 1:y_len, :]
t0 = time.time()
cld_frac_nh = self.run_inference_(bt_nh, refl_nh, refl_lo_nh, refl_hi_nh, refl_std_nh, cp_nh) cld_frac_nh = self.run_inference_(bt_nh, refl_nh, refl_lo_nh, refl_hi_nh, refl_std_nh, cp_nh)
cld_frac_sh = self.run_inference_(bt_sh, refl_sh, refl_lo_sh, refl_hi_sh, refl_std_sh, cp_sh) cld_frac_sh = self.run_inference_(bt_sh, refl_sh, refl_lo_sh, refl_hi_sh, refl_std_sh, cp_sh)
t1 = time.time()
print(' inference time: ', (t1-t0))
cld_frac_out = np.zeros((y_len, x_len), dtype=np.int8) cld_frac_out = np.zeros((y_len, x_len), dtype=np.int8)
border = int((KERNEL_SIZE - 1) / 2) border = int((KERNEL_SIZE - 1) / 2)
......
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