From 9bb4fb513f66d7e21a076f07743199c5ef1d46d0 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Thu, 1 Jun 2023 11:37:09 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/cloud_opd_srcnn_abi.py | 22 ++++++++++-----------
1 file changed, 11 insertions(+), 11 deletions(-)
diff --git a/modules/deeplearning/cloud_opd_srcnn_abi.py b/modules/deeplearning/cloud_opd_srcnn_abi.py
index dc2b62d2..94064599 100644
--- a/modules/deeplearning/cloud_opd_srcnn_abi.py
+++ b/modules/deeplearning/cloud_opd_srcnn_abi.py
@@ -206,7 +206,7 @@ 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 = 6
self.X_img = tf.keras.Input(shape=(None, None, self.n_chans))
@@ -265,16 +265,16 @@ 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[:, self.slc_y_m, self.slc_x_m]
- # tmp = upsample_nearest(tmp)
- # 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[:, self.slc_y_m, self.slc_x_m]
+ tmp = upsample_nearest(tmp)
+ 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 data_params_full:
# idx = params_i.index(param)
--
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