From 3f4ade5f0c60e2825146096ef9b4f1fb13528d0a Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 4 Jan 2023 09:58:26 -0600
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 caf873de..343502bd 100644
--- a/modules/deeplearning/srcnn_l1b_l2.py
+++ b/modules/deeplearning/srcnn_l1b_l2.py
@@ -831,13 +831,12 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
grd_c = grd_c[slc_y_2, slc_x_2]
grd_c = resample_2d_linear_one(x_2, y_2, grd_c, t, s)
grd_c = grd_c[y_k, x_k]
-
if label_param != 'cloud_probability':
grd_c = normalize(grd_c, label_param, mean_std_dct)
# data = np.stack([grd_a, grd_b, grd_c], axis=2)
- # data = np.stack([grd_a, grd_c], axis=2)
- data = np.stack([grd_c], axis=2)
+ data = np.stack([grd_a, grd_c], axis=2)
+ # data = np.stack([grd_c], axis=2)
data = np.expand_dims(data, axis=0)
h5f.close()
@@ -845,9 +844,9 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
nn = SRCNN()
out_sr = nn.run_evaluate(data, ckpt_dir)
if out_file is not None:
- np.save(out_file, (out_sr[0, :, :, 0], hr_grd_c))
+ np.save(out_file, (out_sr[0, :, :, 0], hr_grd_a, hr_grd_c))
else:
- return out_sr, hr_grd_c
+ return out_sr, hr_grd_a, hr_grd_c
if __name__ == "__main__":
--
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