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IR/gen_meta_file.py

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+import os
+import sys
+import json
+import pandas as pd
+import numpy as np
+from tqdm import tqdm
+
+import rdkit
+from rdkit import Chem
+from rdkit.Chem import AllChem
+
+sys.path.append("../../")
+from utils.compound_tools import mol_to_geognn_graph_data_MMFF3d
+
+
+def GetIRMetaFile():
+    # get dataset_all, smiles_all, index_all from SMILES in IR dataset
+
+    raw_smiles_all, raw_index_all = [], []
+    max_len = -1
+    ir_filelist = os.listdir("./qm9_ir_spec/")
+    for filename in tqdm(ir_filelist[:max_len]):
+        mol_info = json.load(open(os.path.join("./qm9_ir_spec/", filename), "r"))
+        raw_smiles_all.append(mol_info['smiles'])
+        raw_index_all.append(filename.split('.')[0])
+
+    dataset_all, smiles_all, index_all = [], [], []
+    
+    for i in tqdm(range(len(raw_smiles_all))): 
+        mol = AllChem.MolFromSmiles(raw_smiles_all[i])
+        mol = Chem.AddHs(mol)
+        AllChem.EmbedMolecule(mol)
+        try: 
+            data = mol_to_geognn_graph_data_MMFF3d(mol)
+            dataset_all.append(data); smiles_all.append(raw_smiles_all[i])
+            index_all.append(raw_index_all[i])
+        except ValueError:
+            print("error in {}".format(i))
+    
+    result_dict = dict(
+        smiles_all=smiles_all, index_all=index_all,
+        dataset_all=dataset_all, 
+    )
+    np.save(f"ir_column_charity_all.npy", result_dict)
+
+if __name__ == "__main__":
+    GetIRMetaFile()

IR/ir_column_charity_100.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b55c598dda0547cac6e919284a8bffaa0454df77a00694af9d82a902a6413906
+size 1195616

IR/ir_column_charity_10000.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ce423c6832347e54342ed210de190f6bebc957ca164056b0707f966fe6a7f63f
+size 129309557

IR/ir_column_charity_all.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:82492d0812a79ad38394c07fc59be940676a865237bec4a69f98375c20d30991
+size 1528483538

IR/readme.txt

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+gen_meta_file.py
+    用于根据IR数据集的smiles值生成 GeoGNN 能够处理的分子feature