Metadata-Version: 2.1
Name: doped
Version: 0.0.8
Summary: Collection of Python modules & functions to perform and process solid-state defect calculations
Home-page: https://github.com/kavanase/doped
Author: Seán Kavanagh
Author-email: sean.kavanagh.19@ucl.ac.uk
Maintainer: Seán Kavanagh
Maintainer-email: sean.kavanagh.19@ucl.ac.uk
License: MIT
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
License-File: LICENSE

# **D**efect **O**riented **P**ython **E**nvironment **D**istribution (DOPED)
This is a (mid-development) Python package for managing solid-state defect calculations,
geared toward VASP. Much of it is a modified version of the excellent [PyCDT](https://bitbucket.org/mbkumar/pycdt).  
See [this link](https://www.sciencedirect.com/science/article/pii/S0010465518300079) for the original PyCDT paper.

Defect formation energy plots are templated from [AIDE](https://github.com/SMTG-UCL/aide) and follow the aesthetics
philosopy of [sumo](https://smtg-ucl.github.io/sumo/), both developed by the dynamic duo Adam Jackson and Alex Ganose.

This code is still being customised, so in the spirit of efficiency 
and avoiding redundant work, there are example 
Jupyter notebooks (the `.ipynb` files) provided to show the code functionality and usage.
(Better to open in Jupyter, after installing, rather than with GitHub preview).

## Requirements
`doped` requires pymatgen (and its dependencies).

## Installation
1.  Download the `doped` source code using the command:
```bash
  git clone https://github.com/SMTG-UCL/doped
```
2.  Navigate to root directory:
```bash
  cd doped
```
3.  Install the code, using the command:
```bash
  pip install -e .
```
This command tries to obtain the required packages and their dependencies and install them automatically.
Access to root may be needed if ``virtualenv`` is not used.

4.  (If not set) Set the VASP pseudopotential directory in `$HOME/.pmgrc.yaml` as follows::
```bash
  PMG_VASP_PSP_DIR: <Path to VASP pseudopotential top directory>
```
Within your `VASP pseudopotential top directory`, you should have a folder named `POT_GGA_PAW_PBE` which contains the `POTCAR.X(.gz)` files (in this case for PBE `POTCAR`s).

(Necessary to generate `POTCAR` files, auto-determine `INCAR` settings such as `NELECT` for charged defects...)

5.  (Optional) Set the Materials Project API key in `$HOME/.pmgrc.yaml` as follows::
```bash
  MAPI_KEY: <Your mapi key obtained from www.materialsproject.org>
```
(For pulling structures and comparing properties with the Materials Project database).


## Word of Caution
There is quite possibly a couple of bugs in this code, as it is very much still experimental and in development.
If you find any, please let us know!


