AIRS/OpenMol/Geo2Seq/process_data_qm9.py at main · divelab/AIRS · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
import numpy as np
from tqdm import tqdm
import torch
from rdkit import Chem
from rdkit.Chem import rdDetermineBonds

def nan_to_num(vec, num=0.0):
    idx = np.isnan(vec)
    vec[idx] = num
    return vec

def _normalize(vec, axis=-1):
    return nan_to_num(
        np.divide(vec, np.linalg.norm(vec, axis=axis, keepdims=True)))

def write_xyz_file(atom_types, atom_coordinates, file_path):
    with open(file_path, 'w') as file:
        num_atoms = len(atom_types)
        file.write(f"{num_atoms}\n")
        file.write('\n')

        for atom_type, coords in zip(atom_types, atom_coordinates):
            x, y, z = coords
            file.write(f"{atom_type} {np.format_float_positional(x)} {np.format_float_positional(y)} {np.format_float_positional(z)}\n")


dict_qm9 = {1:'H', 6:'C', 7:'N', 8:'O', 9:'F'}


def write_qm9_to_seq(raw_path='data/QM9Gen/processed_edm/',
                     write_path='QM9_seq/',
                     split='train',
                     order_type='order',
                     remove_h=False,
                     sample=False):

    write_name_ori_coord = f"{order_type}{'_ori_cord'}{'_noH' if remove_h else '_adH'}{'_sample' if sample else ''}{'_seq'}"
    write_name_invariant = f"{order_type}{'_invariant_cord'}{'_noH' if remove_h else '_adH'}{'_sample' if sample else ''}{'_seq'}"
    write_name_spherical = f"{order_type}{'_spherical_cord'}{'_noH' if remove_h else '_adH'}{'_sample' if sample else ''}{'_seq'}"

    write_path_ori_coord = write_path + write_name_ori_coord + '.txt'
    write_path_invariant = write_path + write_name_invariant + '.txt'
    write_path_spherical = write_path + write_name_spherical + '.txt'


    if split == 'train':
        raw_file = raw_path + 'train.npz'
    elif split == 'valid':
        raw_file = raw_path + 'valid.npz'
    else:
        print('!!! split not supported !!!')
        exit()

    smiles_seq = []
    atom_seq = []
    coords_seq = []
    invariant_coords_seq = []
    spherical_coords_seq = []

    all_data = np.load(raw_file)
    keys = all_data.files

    ############### all files ################
    # 'num_atoms', 'charges', 'positions',
    # 'index',
    # properties: 'A', 'B', 'C', 'mu', 'alpha', 'homo', 'lumo', 'gap', 'r2', 'zpve',
    # properties: 'U0', 'U', 'H', 'G', 'Cv', 'omega1', 'zpve_thermo', 'U0_thermo', 'U_thermo', 'H_thermo', 'G_thermo', 'Cv_thermo'
    # need to change units:
    # qm9_to_eV = {'U0': 27.2114, 'U': 27.2114, 'G': 27.2114, 'H': 27.2114, 'zpve': 27211.4,
    # 'gap': 27.2114, 'homo': 27.2114, 'lumo': 27.2114}

    if not sample:
        num_mol = len(all_data[keys[0]])
    else:
        num_mol = 5

    all_num_atoms = all_data['num_atoms']
    all_charges = all_data['charges']
    all_positions = all_data['positions']

    for i in tqdm(range(num_mol)):
        num_atom = all_num_atoms[i]
        file_path = 'Molecule3D/example.xyz'
        ori_z = all_charges[i][:num_atom]
        ori_coords = all_positions[i][:num_atom]

        write_xyz_file([dict_qm9[key] for key in ori_z], ori_coords, file_path)
        raw_mol = Chem.MolFromXYZFile(file_path)
        mol = Chem.Mol(raw_mol)
        try:
            rdDetermineBonds.DetermineBonds(mol)
        except:
            pass
        smiles = Chem.MolToSmiles(mol)

        order = mol.GetPropsAsDict(includePrivate=True, includeComputed=True)['_smilesAtomOutputOrder']
        reorder_mol = Chem.RenumberAtoms(mol,order)
        atom_type = np.array([atom.GetSymbol() for atom in reorder_mol.GetAtoms()])
        coords = reorder_mol.GetConformer().GetPositions()

        if remove_h:
            mask = atom_type != 'H'
            atom_type = atom_type[mask]
            coords = coords[mask]
            num_atom = len(atom_type)

        centered_coords = coords - coords[0]
        invariant_coords = np.zeros_like(coords)
        spherical_coords = np.zeros_like(coords)

        # we have to select three nodes to build a global frame
        flag = False

        if num_atom == 1:
            pass
        elif num_atom == 2:
            d = np.linalg.norm(coords[1] - coords[0], axis=-1)
            invariant_coords[1,0] = d
            spherical_coords[1,0] = d
        else:
            v1 = centered_coords[1] - centered_coords[0]
            for i in range(2, num_atom):
                v2 = centered_coords[i] - centered_coords[0]
                if np.linalg.norm(np.cross(v1, v2)) != 0:
                    flag = True # # can find the third node that is not on the same line as the first two nodes
                    break
            if flag == False and i == num_atom - 1: # cannot find the third node that is not on the same line as the first two nodes
                invariant_coords = centered_coords
            else:
                # build a global frame (xyz axis)
                x = _normalize(v1)
                y = _normalize(np.cross(v1, v2))
                z = np.cross(x, y)
                # invariant coords
                invariant_coords = np.dot(centered_coords, np.stack((x, y, z)).T)
            d = np.linalg.norm(invariant_coords, axis=-1)
            theta = np.zeros_like(d)
            theta[1:] = np.arccos(invariant_coords[1:,2]/d[1:])
            phi = np.arctan2(invariant_coords[:,1], invariant_coords[:,0])
            # invariant_spherical_coords
            spherical_coords = np.stack((d, theta, phi)).T


        coords = np.array([["{:.2f}".format(value) for value in row] for row in coords])
        invariant_coords = np.array([["{:.2f}".format(value) for value in row] for row in invariant_coords])
        spherical_coords = np.array([["{:.2f}".format(value) for value in row] for row in spherical_coords])
        coords_seq.append(coords)
        invariant_coords_seq.append(invariant_coords)
        spherical_coords_seq.append(spherical_coords)

        smiles_seq.append(smiles)
        atom_seq.append(atom_type)


    with open(write_path_ori_coord, 'w') as file:
        for i in range(len(atom_seq)):
            for j in range(len(atom_seq[i])):
                file.write(atom_seq[i][j])
                file.write(' ')
                file.write(str(coords_seq[i][j][0]) + ' ' + str(coords_seq[i][j][1]) + ' ' + str(coords_seq[i][j][2]) + ' ')
            file.write('\n')

    with open(write_path_invariant, 'w') as file:
        for i in range(len(atom_seq)):
            for j in range(len(atom_seq[i])):
                file.write(atom_seq[i][j])
                file.write(' ')
                file.write(str(invariant_coords_seq[i][j][0]) + ' ' + str(invariant_coords_seq[i][j][1]) + ' ' + str(invariant_coords_seq[i][j][2]) + ' ')
            file.write('\n')

    with open(write_path_spherical, 'w') as file:
        for i in range(len(atom_seq)):
            for j in range(len(atom_seq[i])):
                file.write(atom_seq[i][j])
                file.write(' ')
                file.write(str(spherical_coords_seq[i][j][0]) + ' ' + str(spherical_coords_seq[i][j][1]) + '° ' + str(spherical_coords_seq[i][j][2]) + '° ')
            file.write('\n')