From 08bb6f671877cf286bb75f873aa860ffe801b3ed Mon Sep 17 00:00:00 2001
From: "b.gong" <b.gong@fz-juelich.de>
Date: Mon, 18 May 2020 12:22:35 +0200
Subject: [PATCH] update generate_transfer_learning_finetune.py
---
.../generate_transfer_learning_finetune.py | 41 ++++++++++---------
1 file changed, 21 insertions(+), 20 deletions(-)
diff --git a/scripts/generate_transfer_learning_finetune.py b/scripts/generate_transfer_learning_finetune.py
index 662a415d..c4fa8315 100644
--- a/scripts/generate_transfer_learning_finetune.py
+++ b/scripts/generate_transfer_learning_finetune.py
@@ -214,6 +214,8 @@ def main():
print("Sample id", sample_ind)
if sample_ind <= 24:
pass
+ elif sample_ind >= len(X_test):
+ break
else:
gen_images_stochastic = []
if args.num_samples and sample_ind >= args.num_samples:
@@ -239,7 +241,6 @@ def main():
#bing:20200417
t_stampe = test_temporal_pkl[sample_ind+i]
print("timestamp:",type(t_stampe))
-
persistent_ts = np.array(t_stampe) - datetime.timedelta(days=1)
print ("persistent ts",persistent_ts)
persistent_idx = list(test_temporal_pkl).index(np.array(persistent_ts))
@@ -323,25 +324,25 @@ def main():
plt.savefig(os.path.join(args.output_png_dir, "Persistent_Sample_" + str(name) + ".jpg"))
plt.clf()
-##
-## with open(os.path.join(args.output_png_dir, "persistent_images_all.pkl"), "wb") as input_files:
-## pickle.dump(list(persistent_images_all), input_files)
-## print ("Save persistent all")
-## if is_first:
-## gen_images_all = gen_images_stochastic
-## is_first = False
-## else:
-## gen_images_all = np.concatenate((np.array(gen_images_all), np.array(gen_images_stochastic)), axis=1)
-##
-## if args.num_stochastic_samples == 1:
-## with open(os.path.join(args.output_png_dir, "gen_images_all.pkl"), "wb") as gen_files:
-## pickle.dump(list(gen_images_all[0]), gen_files)
-## print ("Save generate all")
-## else:
-## with open(os.path.join(args.output_png_dir, "gen_images_sample_id_" + str(sample_ind)),"wb") as gen_files:
-## pickle.dump(list(gen_images_stochastic), gen_files)
-## with open(os.path.join(args.output_png_dir, "gen_images_all_stochastic"), "wb") as gen_files:
-## pickle.dump(list(gen_images_all), gen_files)
+
+ with open(os.path.join(args.output_png_dir, "persistent_images_all.pkl"), "wb") as input_files:
+ pickle.dump(list(persistent_images_all), input_files)
+ print ("Save persistent all")
+ if is_first:
+ gen_images_all = gen_images_stochastic
+ is_first = False
+ else:
+ gen_images_all = np.concatenate((np.array(gen_images_all), np.array(gen_images_stochastic)), axis=1)
+
+ if args.num_stochastic_samples == 1:
+ with open(os.path.join(args.output_png_dir, "gen_images_all.pkl"), "wb") as gen_files:
+ pickle.dump(list(gen_images_all[0]), gen_files)
+ print ("Save generate all")
+ else:
+ with open(os.path.join(args.output_png_dir, "gen_images_sample_id_" + str(sample_ind)),"wb") as gen_files:
+ pickle.dump(list(gen_images_stochastic), gen_files)
+ with open(os.path.join(args.output_png_dir, "gen_images_all_stochastic"), "wb") as gen_files:
+ pickle.dump(list(gen_images_all), gen_files)
##
##
## # fig = plt.figure()
--
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