Metadata-Version: 1.1
Name: cctk
Version: v0.1.3
Summary: computational chemistry toolkit
Home-page: https://github.com/ekwan/cctk
Author: Corin Wagen and Eugene Kwan
Author-email: corin.wagen@gmail.com
License: Apache 2.O
Download-URL: https://github.com/ekwan/cctk/archive/v0.1.3.tar.gz
Description: # 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:
        
        The documentation for *cctk* can be found on [Read the Docs](https://cctk.readthedocs.io). 
        
        ## 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&ndash;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 `cwagen@g.harvard.edu` 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](https://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*
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
