From 6edf43553a2a1ea2a63ca77658c2cdf52db24116 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Thu, 6 Oct 2022 15:28:01 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/srcnn_l1b_l2.py | 4 +++-
1 file changed, 3 insertions(+), 1 deletion(-)
diff --git a/modules/deeplearning/srcnn_l1b_l2.py b/modules/deeplearning/srcnn_l1b_l2.py
index 377e8608..bfd88fd6 100644
--- a/modules/deeplearning/srcnn_l1b_l2.py
+++ b/modules/deeplearning/srcnn_l1b_l2.py
@@ -237,6 +237,7 @@ class SRCNN:
data_norm.append(tmp)
# --------
tmp = input_data[:, label_idx, 3:131:2, 3:131:2]
+ tmp = np.where(np.isnan(tmp), 0, tmp)
tmp = resample_2d_linear(x_64, y_64, tmp, t, s)
data_norm.append(tmp)
# ---------
@@ -245,6 +246,7 @@ class SRCNN:
# label = input_data[:, label_idx, 3:131:2, 3:131:2]
label = input_data[:, label_idx, 3:131, 3:131]
+ label = np.where(np.isnan(label), 0, label)
label = np.expand_dims(label, axis=3)
if label_param != 'cloud_fraction':
label = normalize(label, label_param, mean_std_dct)
@@ -650,7 +652,7 @@ class SRCNN:
self.do_training()
def run_restore(self, directory, ckpt_dir):
- valid_data_files = glob.glob(directory + 'data_valid*.npy')
+ valid_data_files = glob.glob(directory + 'data_*.npy')
self.num_data_samples = 1000
self.setup_test_pipeline(valid_data_files)
self.build_model()
--
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