From 456712fe783cd3f9bb9389b898f07039010639df Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Tue, 27 Sep 2022 11:21:59 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/srcnn_l1b_l2.py | 9 ++++-----
1 file changed, 4 insertions(+), 5 deletions(-)
diff --git a/modules/deeplearning/srcnn_l1b_l2.py b/modules/deeplearning/srcnn_l1b_l2.py
index 9932cfbf..8dcebe73 100644
--- a/modules/deeplearning/srcnn_l1b_l2.py
+++ b/modules/deeplearning/srcnn_l1b_l2.py
@@ -202,8 +202,7 @@ class SRCNN:
f = files[k]
nda = np.load(f)
data_s.append(nda)
-
- data = np.concatenate(data_s)
+ input_data = np.concatenate(data_s)
add_noise = None
noise_scale = None
@@ -214,15 +213,15 @@ class SRCNN:
data_norm = []
for param in data_params:
idx = params.index(param)
- tmp = data[:, idx, 3:131:2, 3:131:2]
+ tmp = input_data[:, idx, 3:131:2, 3:131:2]
tmp = resample(y_64, x_64, tmp, s, t)
tmp = normalize(tmp, param, mean_std_dct, add_noise=add_noise, noise_scale=noise_scale)
data_norm.append(tmp)
data = np.stack(data_norm, axis=3)
data = data.astype(np.float32)
- # label = data[:, label_idx, 3:131:2, 3:131:2]
- label = data[:, label_idx, 3:131, 3:131]
+ # label = input_data[:, label_idx, 3:131:2, 3:131:2]
+ label = input_data[:, label_idx, 3:131, 3:131]
label = np.expand_dims(label, axis=3)
if label_param != 'cloud_fraction':
label = normalize(label, label_param, mean_std_dct)
--
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