From 0db423b2bfe06cdd0f5037e5f7762156904d02a6 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 21 Jun 2023 15:56:46 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/cloud_opd_srcnn_abi.py | 28 ++++++++++-----------
1 file changed, 14 insertions(+), 14 deletions(-)
diff --git a/modules/deeplearning/cloud_opd_srcnn_abi.py b/modules/deeplearning/cloud_opd_srcnn_abi.py
index 8fac5c4b..33022629 100644
--- a/modules/deeplearning/cloud_opd_srcnn_abi.py
+++ b/modules/deeplearning/cloud_opd_srcnn_abi.py
@@ -57,7 +57,7 @@ params_i = ['temp_11_0um_nom', 'refl_0_65um_nom', 'temp_stddev3x3_ch31', 'refl_s
data_params_half = ['temp_11_0um_nom', 'refl_0_65um_nom']
data_params_full = ['refl_0_65um_nom']
# sub_fields = ['refl_submin_ch01', 'refl_submax_ch01', 'refl_substddev_ch01']
-sub_fields = ['temp_stddev3x3_ch31', 'refl_stddev3x3_ch01']
+sub_fields = ['refl_stddev3x3_ch01']
label_idx_i = params_i.index(label_param)
label_idx = params.index(label_param)
@@ -207,7 +207,7 @@ class SRCNN:
self.test_label_files = None
# self.n_chans = len(data_params_half) + len(data_params_full) + 1
- self.n_chans = 3
+ self.n_chans = 4
self.X_img = tf.keras.Input(shape=(None, None, self.n_chans))
@@ -266,18 +266,18 @@ 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 = np.where(np.isnan(tmp), 0.0, tmp)
- # tmp = tmp[:, self.slc_y_m, self.slc_x_m]
- # tmp = self.upsample(tmp)
- # # if param != 'refl_substddev_ch01':
- # if False:
- # tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
- # else:
- # tmp = np.where(np.isnan(tmp), 0.0, tmp)
- # data_norm.append(tmp)
+ for param in sub_fields:
+ idx = params.index(param)
+ tmp = input_data[:, idx, :, :]
+ tmp = np.where(np.isnan(tmp), 0.0, tmp)
+ tmp = tmp[:, self.slc_y_m, self.slc_x_m]
+ tmp = self.upsample(tmp)
+ # if param != 'refl_substddev_ch01':
+ if False:
+ tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
+ else:
+ tmp = np.where(np.isnan(tmp), 0.0, tmp)
+ data_norm.append(tmp)
# for param in sub_fields:
# idx = params.index(param)
--
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