From 92de8089520a7f4a3d262ea5163b6caa4381318b Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Tue, 27 Sep 2022 10:24:31 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/srcnn_l1b_l2.py | 11 ++++-------
1 file changed, 4 insertions(+), 7 deletions(-)
diff --git a/modules/deeplearning/srcnn_l1b_l2.py b/modules/deeplearning/srcnn_l1b_l2.py
index 2c8305d1..859c4942 100644
--- a/modules/deeplearning/srcnn_l1b_l2.py
+++ b/modules/deeplearning/srcnn_l1b_l2.py
@@ -198,15 +198,12 @@ class SRCNN:
files = self.test_data_files
data_s = []
- label_s = []
for k in idxs:
f = files[k]
nda = np.load(f)
- data_s.append(nda[0:len(data_params), :, :])
- label_s.append(nda[3, :, :])
+ data_s.append(nda)
data = np.concatenate(data_s)
- label = np.concatenate(label_s)
add_noise = None
noise_scale = None
@@ -215,7 +212,7 @@ class SRCNN:
noise_scale = 0.005
data_norm = []
- for k, param in enumerate(data_params):
+ for k, param in enumerate(params):
tmp = data[:, k, 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)
@@ -223,8 +220,8 @@ class SRCNN:
data = np.stack(data_norm, axis=3)
data = data.astype(np.float32)
- # label = label[:, 3:131:2, 3:131:2]
- label = label[:, 3:131, 3:131]
+ # label = data[:, label_idx, 3:131:2, 3:131:2]
+ label = 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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