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Commit f4dbbaef authored by tomrink's avatar tomrink
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parent 39b58be8
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......@@ -3,7 +3,7 @@ import tensorflow as tf
from util.plot_cm import confusion_matrix_values
from util.augment import augment_image
from util.setup_cloud_fraction import logdir, modeldir, now, ancillary_path
from util.util import EarlyStop, normalize, denormalize, get_grid_values_all, make_tf_callable_generator
from util.util import EarlyStop, normalize, denormalize, scale2, get_grid_values_all, make_tf_callable_generator
import glob
import os, datetime
import numpy as np
......@@ -289,8 +289,7 @@ class SRCNN:
self.test_data_files = None
self.test_label_files = None
# self.n_chans = len(data_params_half) + len(data_params_full) + 1
self.n_chans = 6
self.n_chans = 5
self.X_img = tf.keras.Input(shape=(None, None, self.n_chans))
......@@ -327,15 +326,30 @@ class SRCNN:
tmp = normalize(tmp, param, mean_std_dct)
data_norm.append(tmp)
for param in sub_fields:
idx = params.index(param)
tmp = input_data[:, idx, :, :]
tmp = tmp[:, slc_y, slc_x]
if param != 'refl_substddev_ch01':
tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
else:
tmp = np.where(np.isnan(tmp), 0, tmp)
data_norm.append(tmp)
# for param in sub_fields:
# idx = params.index(param)
# tmp = input_data[:, idx, :, :]
# tmp = tmp[:, slc_y, slc_x]
# if param != 'refl_substddev_ch01':
# tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
# else:
# tmp = np.where(np.isnan(tmp), 0, tmp)
# data_norm.append(tmp)
rlo = input_data[:, params.index('refl_submin_ch01'), :, :]
rlo = rlo[:, slc_y, slc_x]
rlo = normalize(rlo, 'refl_0_65um_nom', mean_std_dct)
rhi = input_data[:, params.index('refl_submax_ch01'), :, :]
rhi = rhi[:, slc_y, slc_x]
rhi = normalize(rhi, 'refl_0_65um_nom', mean_std_dct)
refl_rng = rhi - rlo
data_norm.append(refl_rng)
rstd = input_data[:, params.index('refl_substddev_ch01'), :, :]
rstd = rstd[:, slc_y, slc_x]
rstd = scale2(rstd, 0.0, 20.0)
data_norm.append(rstd)
tmp = input_label[:, label_idx_i, :, :]
tmp = get_grid_cell_mean(tmp)
......
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