| import argparse | |
| def m_b_A(output_path, AA_list, bias_list): | |
| import numpy as np | |
| import json | |
| bias_list = [float(item) for item in bias_list.split()] | |
| AA_list = [str(item) for item in AA_list.split()] | |
| my_dict = dict(zip(AA_list, bias_list)) | |
| with open(output_path, 'w') as f: | |
| f.write(json.dumps(my_dict) + '\n') | |
| return output_path | |
| # if __name__ == "__main__": | |
| # argparser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) | |
| # argparser.add_argument("--output_path", type=str, help="Path to the output dictionary") | |
| # argparser.add_argument("--AA_list", type=str, default='', help="List of AAs to be biased") | |
| # argparser.add_argument("--bias_list", type=str, default='', help="AA bias strengths") | |
| # | |
| # args = argparser.parse_args() | |
| # main(args) | |
| #e.g. output | |
| #{"A": -0.01, "G": 0.02} | |