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Commit 4ab3264e authored by tomrink's avatar tomrink
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modules/util/abi_surfrad.py
+ 22
− 16
View file @ 4ab3264e
...@@ -3,9 +3,9 @@ import h5py ...@@ -3,9 +3,9 @@ import h5py
from util.util import get_grid_values, is_day from util.util import get_grid_values, is_day
import glob import glob
# target_param = 'cloud_probability' target_param = 'cloud_probability'
# target_param = 'cld_opd_dcomp' # target_param = 'cld_opd_dcomp'
target_param = 'cld_opd_dcomp_1' # target_param = 'cld_opd_dcomp_1'
# target_param = 'cld_opd_dcomp_2' # target_param = 'cld_opd_dcomp_2'
# target_param = 'cld_opd_dcomp_3' # target_param = 'cld_opd_dcomp_3'
...@@ -15,15 +15,17 @@ group_name_m = 'orig/' ...@@ -15,15 +15,17 @@ group_name_m = 'orig/'
solzen_name = group_name_m + 'solar_zenith' solzen_name = group_name_m + 'solar_zenith'
snow_class_name = group_name_m + 'snow_class' snow_class_name = group_name_m + 'snow_class'
# params_i = [group_name_i+'temp_ch38', group_name_i+'refl_ch01', group_name_i+target_param] params_i = [group_name_i+'temp_ch38', group_name_i+'refl_ch01', group_name_i+target_param]
params_i = [group_name_i+'temp_ch38', group_name_i+'refl_ch01', group_name_i+'temp_stddev3x3_ch31', group_name_i+'refl_stddev3x3_ch01', group_name_i+target_param] # params_i = [group_name_i+'temp_ch38', group_name_i+'refl_ch01', group_name_i+'temp_stddev3x3_ch31', group_name_i+'refl_stddev3x3_ch01', group_name_i+target_param]
# params_m = [group_name_m+'temp_ch38', group_name_m+'refl_ch01', group_name_m+'refl_submin_ch01', group_name_m+'refl_submax_ch01', group_name_m+'refl_substddev_ch01', group_name_m+target_param] params_m = [group_name_m+'temp_ch38', group_name_m+'refl_ch01', group_name_m+'refl_submin_ch01', group_name_m+'refl_submax_ch01', group_name_m+'refl_substddev_ch01', group_name_m+target_param]
params_m = [group_name_m+'temp_ch38', group_name_m+'refl_ch01', group_name_m+'refl_submin_ch01', group_name_m+'refl_submax_ch01', group_name_m+'refl_substddev_ch01', group_name_m+'temp_stddev3x3_ch31', group_name_m+'refl_stddev3x3_ch01', group_name_m+target_param] # params_m = [group_name_m+'temp_ch38', group_name_m+'refl_ch01', group_name_m+'refl_submin_ch01', group_name_m+'refl_submax_ch01', group_name_m+'refl_substddev_ch01', group_name_m+'temp_stddev3x3_ch31', group_name_m+'refl_stddev3x3_ch01', group_name_m+target_param]
param_idx_m = params_m.index(group_name_m + target_param) param_idx_m = params_m.index(group_name_m + target_param)
param_idx_i = params_i.index(group_name_i + target_param) param_idx_i = params_i.index(group_name_i + target_param)
DO_WRITE_OUTFILE = False
def snow_covered(tile): def snow_covered(tile):
return np.any(tile > 1) return np.any(tile > 1)
...@@ -142,8 +144,8 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st ...@@ -142,8 +144,8 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st
try: try:
num_not_missing, num_snow_covered = \ num_not_missing, num_snow_covered = \
run(h5f, params_m, data_tiles_m, params_i, data_tiles_i, run(h5f, params_m, data_tiles_m, params_i, data_tiles_i,
# tile_width=16, kernel_size=4, factor=4, tile_width=32, kernel_size=5, factor=4,
tile_width=64, kernel_size=7, factor=2, # tile_width=64, kernel_size=7, factor=2,
day_night=day_night, is_snow_covered=is_snow_covered) day_night=day_night, is_snow_covered=is_snow_covered)
except Exception as e: except Exception as e:
print(e) print(e)
...@@ -163,6 +165,7 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st ...@@ -163,6 +165,7 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st
if len(data_tiles_m) > 0: if len(data_tiles_m) > 0:
valid_i = np.stack(data_tiles_i) valid_i = np.stack(data_tiles_i)
valid_m = np.stack(data_tiles_m) valid_m = np.stack(data_tiles_m)
if DO_WRITE_OUTFILE:
np.save(out_directory + 'valid_mres_' + str(cnt), valid_m) np.save(out_directory + 'valid_mres_' + str(cnt), valid_m)
np.save(out_directory + 'valid_ires_' + str(cnt), valid_i) np.save(out_directory + 'valid_ires_' + str(cnt), valid_i)
num_valid_samples = valid_m.shape[0] num_valid_samples = valid_m.shape[0]
...@@ -184,6 +187,7 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st ...@@ -184,6 +187,7 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st
if len(data_tiles_m) > 0: if len(data_tiles_m) > 0:
valid_i = np.stack(data_tiles_i) valid_i = np.stack(data_tiles_i)
valid_m = np.stack(data_tiles_m) valid_m = np.stack(data_tiles_m)
if DO_WRITE_OUTFILE:
np.save(out_directory + 'valid_mres_' + str(cnt), valid_m) np.save(out_directory + 'valid_mres_' + str(cnt), valid_m)
np.save(out_directory + 'valid_ires_' + str(cnt), valid_i) np.save(out_directory + 'valid_ires_' + str(cnt), valid_i)
num_valid_samples = valid_m.shape[0] num_valid_samples = valid_m.shape[0]
...@@ -233,6 +237,7 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st ...@@ -233,6 +237,7 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st
if len(data_tiles_m) > 0: if len(data_tiles_m) > 0:
train_i = np.stack(data_tiles_i) train_i = np.stack(data_tiles_i)
train_m = np.stack(data_tiles_m) train_m = np.stack(data_tiles_m)
if DO_WRITE_OUTFILE:
np.save(out_directory + 'train_ires_' + str(cnt), train_i) np.save(out_directory + 'train_ires_' + str(cnt), train_i)
np.save(out_directory + 'train_mres_' + str(cnt), train_m) np.save(out_directory + 'train_mres_' + str(cnt), train_m)
num_train_samples = train_m.shape[0] num_train_samples = train_m.shape[0]
...@@ -254,6 +259,7 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st ...@@ -254,6 +259,7 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st
if len(data_tiles_m) > 0: if len(data_tiles_m) > 0:
train_i = np.stack(data_tiles_i) train_i = np.stack(data_tiles_i)
train_m = np.stack(data_tiles_m) train_m = np.stack(data_tiles_m)
if DO_WRITE_OUTFILE:
np.save(out_directory + 'train_ires_' + str(cnt), train_i) np.save(out_directory + 'train_ires_' + str(cnt), train_i)
np.save(out_directory + 'train_mres_' + str(cnt), train_m) np.save(out_directory + 'train_mres_' + str(cnt), train_m)
num_train_samples = train_m.shape[0] num_train_samples = train_m.shape[0]
... ...
......
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