Spaces:
Running
on
T4
Running
on
T4
| import argparse | |
| def main(args): | |
| import glob | |
| import random | |
| import numpy as np | |
| import json | |
| mpnn_alphabet = 'ACDEFGHIKLMNPQRSTVWYX' | |
| mpnn_alphabet_dict = {'A': 0,'C': 1,'D': 2,'E': 3,'F': 4,'G': 5,'H': 6,'I': 7,'K': 8,'L': 9,'M': 10,'N': 11,'P': 12,'Q': 13,'R': 14,'S': 15,'T': 16,'V': 17,'W': 18,'Y': 19,'X': 20} | |
| with open(args.input_path, 'r') as json_file: | |
| json_list = list(json_file) | |
| my_dict = {} | |
| for json_str in json_list: | |
| result = json.loads(json_str) | |
| all_chain_list = [item[-1:] for item in list(result) if item[:10]=='seq_chain_'] | |
| bias_by_res_dict = {} | |
| for chain in all_chain_list: | |
| chain_length = len(result[f'seq_chain_{chain}']) | |
| bias_per_residue = np.zeros([chain_length, 21]) | |
| if chain == 'A': | |
| residues = [0, 1, 2, 3, 4, 5, 11, 12, 13, 14, 15] | |
| amino_acids = [5, 9] #[G, L] | |
| for res in residues: | |
| for aa in amino_acids: | |
| bias_per_residue[res, aa] = 100.5 | |
| if chain == 'C': | |
| residues = [0, 1, 2, 3, 4, 5, 11, 12, 13, 14, 15] | |
| amino_acids = range(21)[1:] #[G, L] | |
| for res in residues: | |
| for aa in amino_acids: | |
| bias_per_residue[res, aa] = -100.5 | |
| bias_by_res_dict[chain] = bias_per_residue.tolist() | |
| my_dict[result['name']] = bias_by_res_dict | |
| with open(args.output_path, 'w') as f: | |
| f.write(json.dumps(my_dict) + '\n') | |
| if __name__ == "__main__": | |
| argparser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) | |
| argparser.add_argument("--input_path", type=str, help="Path to the parsed PDBs") | |
| argparser.add_argument("--output_path", type=str, help="Path to the output dictionary") | |
| args = argparser.parse_args() | |
| main(args) | |