From bfcddd48ee4e10f2c50e17b4cc7f2a56e256fcf6 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?K=C3=BChle=2C=20Laura=20Christine=20=28lakue103=29?=
<laura.kuehle@uni-duesseldorf.de>
Date: Wed, 5 Oct 2022 23:11:13 +0200
Subject: [PATCH] Outsourced run command for SM rule 'generate_data' into
script.
---
scripts/generate_data.py | 45 ++++++++++++++++++++++++++++++++++++++++
workflows/ANN_data.smk | 32 ++++++----------------------
2 files changed, 51 insertions(+), 26 deletions(-)
create mode 100644 scripts/generate_data.py
diff --git a/scripts/generate_data.py b/scripts/generate_data.py
new file mode 100644
index 0000000..427ec58
--- /dev/null
+++ b/scripts/generate_data.py
@@ -0,0 +1,45 @@
+# -*- coding: utf-8 -*-
+"""Script to generate training data for ANN models.
+
+@author: Laura C. Kühle
+"""
+import sys
+import numpy as np
+
+from tcd import Initial_Condition
+from tcd import ANN_Data_Generator
+
+
+def main() -> None:
+ """Generate training data for ANN models."""
+ # Set random seed if given
+ if snakemake.params['seed'] is not None:
+ np.random.seed(snakemake.params['seed'])
+
+ # Determine list of initial conditions
+ init_cond_list = []
+ for function in snakemake.params['functions']:
+ init_cond_list.append({
+ 'function': getattr(Initial_Condition, function)({}),
+ 'config': {} if snakemake.config['functions'][function] is None
+ else snakemake.config['functions'][function]
+ })
+
+ # Generate training data
+ with open(str(snakemake.log[0]), 'w', encoding='utf-8') as logfile:
+ sys.stdout = logfile
+ generator = ANN_Data_Generator.TrainingDataGenerator()
+ _ = generator.build_training_data(
+ balance=snakemake.params['balance'],
+ init_cond_list=init_cond_list,
+ directory=snakemake.params['directory'],
+ num_samples=snakemake.params['sample_number'],
+ add_reconstructions=snakemake.params['reconstruction_flag'],
+ stencil_len=snakemake.params['stencil_len'])
+
+
+if __name__ == '__main__':
+ if "snakemake" in locals():
+ main()
+ else:
+ print('Not Defined.')
diff --git a/workflows/ANN_data.smk b/workflows/ANN_data.smk
index 9d38b01..d11164d 100644
--- a/workflows/ANN_data.smk
+++ b/workflows/ANN_data.smk
@@ -1,15 +1,8 @@
-import sys
-import time
-import numpy as np
-
-from scripts.tcd import Initial_Condition
-from scripts.tcd import ANN_Data_Generator
-
configfile: 'config.yaml'
+
DIR = config['data_dir']
-if config['random_seed'] is not None:
- np.random.seed(config['random_seed'])
+
rule generate_data:
output:
@@ -22,23 +15,10 @@ rule generate_data:
stencil_len = config['stencil_length'],
sample_number = config['sample_number'],
reconstruction_flag = config['add_reconstructions'],
+ directory = DIR,
+ seed = config['random_seed'],
functions = expand('{FUNCTION}', FUNCTION=config['functions'])
log:
DIR+'/log/generate_data.log'
- run:
- init_cond_list = []
- for function in params.functions:
- init_cond_list.append({
- 'function': getattr(Initial_Condition, function)({}),
- 'config': {} if config['functions'][function] is None
- else config['functions'][function]
- })
-
- with open(str(log), 'w') as logfile:
- sys.stdout = logfile
- generator = ANN_Data_Generator.TrainingDataGenerator()
- data = generator.build_training_data(balance=params.balance,
- init_cond_list=init_cond_list, directory=DIR,
- num_samples=params.sample_number,
- add_reconstructions=params.reconstruction_flag,
- stencil_len=params.stencil_len)
\ No newline at end of file
+ script:
+ '../scripts/generate_data.py'
--
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