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).

Metadata

Release files for jtnnencoder 0.1

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Source distribution for jtnnencoder 0.1
File	Size	Uploaded	Provenance	Actions
jtnnencoder-0.1.tar.gz	19.0 MB	Oct 24, 2020	Without provenance	Details for jtnnencoder-0.1.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for jtnnencoder 0.1
File	Interpreter	ABI	Platform	Actions Reset
jtnnencoder-0.1-py3-none-any.whl 19.0 MB Oct 24, 2020 Without provenance	Python 3	none	any	Details for jtnnencoder-0.1-py3-none-any.whl

Total release size: 38.0 MB

Release files / jtnnencoder-0.1.tar.gz

Download URL	jtnnencoder-0.1.tar.gz
Size	19.0 MB
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Download URL	jtnnencoder-0.1-py3-none-any.whl
Size	19.0 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`e7f7868a7e58bc8841a3430c35c5314a6b35fce491166b96bd6a549b5aab8654`
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Uploaded via	`twine/3.2.0 pkginfo/1.6.0 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.7.8`

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0.1 This release

Oct 24, 2020 2 release files No provenance

jtnnencoder 0.1