smile_to_encoding.py

from os import environ
environ['KERAS_BACKEND'] = 'tensorflow'
from chemvae.vae_utils import VAEUtils
from chemvae import mol_utils as mu
import numpy as np
import pandas as pd
import pickle

vae = VAEUtils(directory='/home/danielcole/Documents/molecules/chemical_vae/models/zinc_properties')
focal_smiles = pd.read_csv("/home/danielcole/Documents/molecules/focal_smiles.csv",index_col=0)
focal_smiles.reset_index(drop=True, inplace=True)

smile_ohots = focal_smiles.apply(axis=1, func=lambda x: vae.smiles_to_hot(x, canonize_smiles=True))
smile_encode = smile_ohots.apply(func=lambda x: vae.encode(x))
smile_decode_ohot = smile_encode.apply(func=lambda x: vae.decode(x))
smile_decoded = smile_decode_ohot.apply(func=lambda x: vae.hot_to_smiles(x,strip=True))


pickle_data = {"focal_smiles":focal_smiles,
               "smile_onehots":smile_ohots,
               "smile_encode":smile_encode,
               "smile_decode_ohot":smile_decode_ohot,
               "smile_decoded":smile_decoded}

pickle_out = open("/home/danielcole/Documents/molecules/smile_encodings.pickle","wb")
pickle.dump(pickle_data, pickle_out)
pickle_out.close()