An Easy to install version of the jtnn encoder for generation of latent molecule features.
Project description
jtnnencoder
Pip installable version of the Junction Tree Variational Autoencoder https://arxiv.org/abs/1802.04364. The original, full repository can be found here: https://github.com/wengong-jin/icml18-jtnn
Intended to be used as a simple interface for generating molecular features for molecules based on JTNN latent vectors.
Install
$ pip install jtnnencoder
$ pip install torch
You will also need rdkit:
$ conda install -c rdkit rdkit
Use
from jtnnencoder import JTNNEmbed
smiles = ['CC1(C)[C@H]2C[C@H](C/C=C\CCCC(=O)O)[C@@H](NC(=O)c3csc4ccc(O)cc34)[C@@H]1C2']
jtnn = JTNNEmbed(smiles)
features = jtnn.get_features()
features
is then a numpy ndarray of dimension (n_smiles x n_features).
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