cctk v0.1.2

computational chemistry toolkit

# cctk ## Computational Chemistry Toolkit

This is a Python 3-based library for working with computational chemistry data.

## Contents:

• [Overview](#overview)

• [Installation](#installation)

• [Contents](#contents)

• [Documentation](#documentation)

• [Technical Details](#technical-details)

• [Authors](#authors)

• [How to Cite](#how-to-cite)

• [License](#license)

## Overview:

cctk is an open-source Python package designed to automate generation and analysis of computational chemistry files.

Potential uses for cctk include:

• Monitoring one or many geometry optimizations.

• Extracting geometry from output files, changing geometric parameters, and creating new input files.

• Calculating molecular properties (e.g. NICS) along a reaction coordinate.

• Screening different functionals and basis sets.

• Generating potential energy surfaces in one or more dimensions (e.g. More O’Ferrall-Jencks plots).

For examples of how cctk can be used, refer to the [tutorials](https://github.com/ekwan/cctk/tree/master/tutorial).

### Compatible File Types:

• Gaussian 16 .out (read) and .gjf (read/write).

• .xyz (read/write)

• .mol2 (read)

• .mae (read)

• Orca .inp (write)

## Installation:

cctk requires Python 3.7+, [numpy](https://numpy.org/), and [networkx](https://networkx.github.io/). A full list of requirements can be found in env.yml.

#### Installing with a working Python 3.7+ environment:

Simply run: ` $ pip install cctk `

#### Installing without a working Python 3.7+ environment:

If you have a different version of Python (e.g. Python 2.7), you can use a conda environment to run cctk without breaking existing packages.

1. Install [conda](https://docs.conda.io/en/latest/)/[miniconda](https://docs.conda.io/en/latest/miniconda.html).

2. Use env.yml to create a Conda environment called cctk and install cctk:

` $ cd cctk $ conda env create -f env.yml `

Now, run conda activate cctk to enter the cctk Python environment (and conda deactivate to leave). (More complete guides to conda usage can be found elsewhere.)

## Contents:

• cctk/ contains the Python modules for cctk and the accompanying static data files.

• docs/ contains the code needed to generate the documentation.

• scripts/ contains pre-defined scripts that use cctk to quickly analyze and manipulate one or many output files.

• test/ contains code to test cctk and accompanying files.

• tutorial/ contains detailed tutorials on how to use cctk on complex, real-world problems.

## Documentation:

To build the documentation (which requires a few extra dependencies), run:

` cd docs/ sphinx-apidoc -o . ../cctk/ make html `

The documentation files can then be found in docs/_build/html.

## Technical Details:

### External Data:

cctk depends on some external data, stored in cctk/data/: - Atomic weights are taken from the [NIST website](https://physics.nist.gov/cgi-bin/Compositions/stand_alone.pl?ele=&all=all&ascii=ascii2&isotype=some) and stored in cctk/data/isotopes.csv. - Covalent radii are taken from [Dalton Trans. 2008, 2832–2838](https://pubs.rsc.org/en/content/articlelanding/2008/dt/b801115j#!divAbstract) and stored in cctk/data/covalent_radii.csv. (When multiple atomic types were specified, the one with longer bond distances was adopted for simplicity).

## Authors:

cctk was written by Corin Wagen and Eugene Kwan at the Department of Chemistry and Chemical Biology at Harvard University. Please email [e-mail] with any questions or bug reports; we will do our best!

## How to Cite:

Wagen, C.C.; Kwan, E.E. cctk 2020, [www.github.com/ekwan/cctk](www.github.com/ekwan/cctk).

## License:

This project is licensed under the Apache License, Version 2.0: see LICENSE for full terms and conditions.

Copyright 2020 by Corin Wagen and Eugene Kwan