From f54b06f7241598cf2874d217c259e15d6e48b1b8 Mon Sep 17 00:00:00 2001
From: Michael <m.langguth@fz-juelich.de>
Date: Mon, 16 Nov 2020 09:37:34 +0100
Subject: [PATCH] Removed typos and smmother path_join-usage in
preprocess_data_step2.py
---
.../data_preprocess/preprocess_data_step2.py | 4 ++--
.../main_scripts/main_preprocess_data_step2.py | 2 +-
2 files changed, 3 insertions(+), 3 deletions(-)
diff --git a/video_prediction_tools/data_preprocess/preprocess_data_step2.py b/video_prediction_tools/data_preprocess/preprocess_data_step2.py
index bfd8c16b..1494d220 100644
--- a/video_prediction_tools/data_preprocess/preprocess_data_step2.py
+++ b/video_prediction_tools/data_preprocess/preprocess_data_step2.py
@@ -93,7 +93,7 @@ class ERA5Pkl2Tfrecords(ERA5Dataset):
def get_metadata(self):
"""
- This function get the meta data that generared from data_process_step1, we aim to extract the height and width informaion from it
+ This function gets the meta data that generared from data_process_step1, we aim to extract the height and width informaion from it
vars_in : list(str), must be consistent with the list from DataPreprocessing_step1
height : int, the height of the image
width : int, the width of the image
@@ -187,7 +187,7 @@ class ERA5Pkl2Tfrecords(ERA5Dataset):
month : int, the target month to save to tfrecord
"""
#Define the input_file based on the year and month
- self.input_file_year = os.path.join(os.path.join(self.input_dir, "pickle"),str(year))
+ self.input_file_year = os.path.join(self.input_dir,"pickle",str(year))
input_file = os.path.join(self.input_file_year,'X_{:02d}.pkl'.format(month))
temp_input_file = os.path.join(self.input_file_year,'T_{:02d}.pkl'.format(month))
diff --git a/video_prediction_tools/main_scripts/main_preprocess_data_step2.py b/video_prediction_tools/main_scripts/main_preprocess_data_step2.py
index 4c13ea25..a9e77a02 100644
--- a/video_prediction_tools/main_scripts/main_preprocess_data_step2.py
+++ b/video_prediction_tools/main_scripts/main_preprocess_data_step2.py
@@ -58,7 +58,7 @@ def main():
stat_obj = Calc_data_stat(nvars) # init statistic-instance
# loop over whole data set (training, dev and test set) to collect the intermediate statistics
- print("Start collecting statistics from the whole datset to be processed...")
+ print("Start collecting statistics from the whole dataset to be processed...")
for split in partition.keys():
values = partition[split]
for year in values.keys():
--
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