Metadata-Version: 2.3
Name: chytorch-rxnmap-synplan
Version: 1.6
Summary: 
License: LGPL-3.0-or-later
Keywords: scientific engineering,chemistry,information analysis,software development,libraries
Author: Dr. Ramil Nugmanov
Author-email: nougmanoff@protonmail.com
Requires-Python: >=3.10
Classifier: Environment :: Plugins
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Dist: chytorch-synplan (>=1.69)
Project-URL: Homepage, https://github.com/chython/chytorch-rxnmap
Project-URL: Repository, https://github.com/chython/chytorch-rxnmap
Description-Content-Type: text/markdown

Chytorch RxnMap
---------------

Semisupervised Model trained on USPTO and Pistachio datasets.

[Publication](https://pubs.acs.org/doi/10.1021/acs.jcim.2c00344) ([Preprint](https://doi.org/10.26434/chemrxiv-2022-bn5nt)) with details.

Installation
------------

Use `pip install chytorch-rxnmap` to install release version.

Or `pip install .` in source code directory to install DEV version.

Perform Atom-to-atom mapping
----------------------------

AAM integrated into `chython` package and available as reaction object method. See `chython` documentation [here](https://chython.readthedocs.io).

    from chython import smiles

    r = smiles('OC(=O)C(=C)C=C.C=CC#N>>OC(=O)C1=CCCC(C1)C#N')
    r.reset_mapping()
    print(format(r, 'm'))
    >> [C:2]([C:4](=[CH2:5])[CH:6]=[CH2:7])(=[O:3])[OH:1].[CH2:8]=[CH:9][C:10]#[N:11]>>[O:3]=[C:2]([OH:1])[C:4]=1[CH2:5][CH:9]([C:10]#[N:11])[CH2:8][CH2:7][CH:6]=1

