File size: 1,007 Bytes
46276cb |
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 |
import pandas as pd
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
from molfeat.calc import FPCalculator
from molfeat.trans import MoleculeTransformer
calc = FPCalculator("ecfp")
mol_transf = MoleculeTransformer(calc, n_jobs=5)
data_train_moldata = pq.read_table("intermediate_data/data_train.parquet").to_pandas()
data_train_features = mol_transf(data_train_moldata["SMILES"].values)
data_train_features = np.stack(data_train_features)
data_train_features = pd.DataFrame(data_train_features)
pq.write_table(
pa.Table.from_pandas(data_train_features),
"intermediate_data/data_train_features.parquet")
data_test_moldata = pq.read_table("intermediate_data/data_test.parquet").to_pandas()
data_test_features = mol_transf(data_test_moldata['SMILES'].values)
data_test_features = np.stack(data_test_features)
data_test_features = pd.DataFrame(data_test_features)
pq.write_table(
pa.Table.from_pandas(data_test_features),
"intermediate_data/data_test_features.parquet")
|