File size: 1,797 Bytes
f555e1d | 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 | import os
import pickle
import lmdb
from tqdm import tqdm, trange
def read_lmdb(lmdb_path):
env = lmdb.open(
lmdb_path,
subdir=False,
readonly=True,
lock=False,
readahead=False,
meminit=False,
max_readers=256,
)
txn = env.begin()
keys = list(txn.cursor().iternext(values=False))
out_list = []
for idx in tqdm(keys):
datapoint_pickled = txn.get(idx)
data = pickle.loads(datapoint_pickled)
out_list.append(data)
#print(len(data["coordinates"]))
env.close()
return out_list
def write_lmdb(out_list, save_path):
env = lmdb.open(
save_path,
subdir=False,
lock=False,
readahead=False,
meminit=False,
max_readers=64,
map_size=1099511627776
)
with env.begin(write=True) as lmdb_txn:
for i in tqdm(range(len(out_list))):
lmdb_txn.put(str(i).encode('ascii'), pickle.dumps(out_list[i]))
if __name__ == "__main__":
# Example usage
# Read LMDB
lmdb_path = "/HOME/nsccgz_ywang/nsccgz_ywang_wzh/HDD_POOL/qiaoaj/DrugCLIP/data/train_no_test_af/train.lmdb"
data = read_lmdb(lmdb_path)
print(len(data))
print(data[0].keys())
#print(len(data[1]["coordinates"]))
dic = {
"atoms": "atom types for each atom in the ligand",
"coordinates": "3D coordinates for each atom in the ligand generated by RDKit. Max number of conformations is 10",
"pocket_atoms": "atom types for each atom in the pocket",
"pocket_coordinates": "3D coordinates for each atom in the pocket",
"mol": "RDKit molecule object for the ligand",
"smi": "SMILES string for the ligand",
"pocket": "pdbid of the pocket",
}
|