genheas

genheas (Generate High Entropy Alloys Structures) is a neural evolution structures (NESs) generation methodology combining artificial neural networks (ANNs) and evolutionary algorithms (EAs) to generate High Entropy Alloys (HEAs).

Support and Documentation

see docs for documentation, reporting bugs, and getting support.

Installation

• Install poetry (https://github.com/python-poetry/poetry)

  • osx / linux / bashonwindows install instructions

  • windows powershell install instructions

other possibility

$ pip install poetry

• Once Poetry is installed you can execute the following:

$ poetry --version

$ poetry self update

• Clone the repo

$ git clone  https://github.com/CLEANit/genheas

$ cd genheas

• Create a Virtual Environment

  By default, Poetry create virtual environment in $HOME/.poetry/env or $HOME/.cache/pypoetry/virtualenvs for cahcing/sharing purpose

  • to install install dependencies to current python interpreter/virtualenv

  $genheas poetry config virtualenvs.create false --local

  • create virtual environment in default location

  $genheas poetry config virtualenvs.create

  • create virtual environment in th root directory of a Python project

  $genheas poetry config virtualenvs.in-project true

  • To change or otherwise add a new configuration setting,

  $genheas poetry config virtualenvs.path /path/to/cache/directory/virtualenvs

• install the packages

$genheas poetry install

$genheas poetry check

$genheas poetry run pytest

$genheas poetry build

• Listing the current configuration

  $genheas poetry config --list

  which will give you something similar to this

  cache-dir = "/path/to/cache/directory"
  virtualenvs.create = true
  virtualenvs.in-project = null
  virtualenvs.path = "{cache-dir}/virtualenvs"  # /path/to/cache/directory/virtualenvs

• Show Information of the Vitual Environment

  poetry env info
  
  
  Virtualenv
  Python:         3.8.5
  Implementation: CPython
  Path:           "/path/to/cache/poetry virtual environment"
  Valid:          True
  
  System
  Platform: linux
  OS:       posix
  Python:   /home/ctetsass/anaconda3

• Activate Virtual Environment

$genheas poetry shell

Usage

Here is the schematic of the workflow to generate HEAs structures:

• train.y

  use small cell to train the model

• generate.py

  use the trained model to general large cell

• Therefore, it should looks like:

  1- Train the model and generate structure

  • Edit the configuration file both training and generation part
  • copy the configuration file to the "root_dir" and edit

  • running from <workdir>

  $ cd  workdir after the activation of the virtual enviroment
  $workdir   python main.py rootdir

  • running in the <genheas/genheas> directory

  $genheas/genheas  poetry run python main.py rootdir

  2- Only train a model

  • Edit the configuration file : training part

  $root_dir vi parameters.yml

  • run

  $workdir   python train.py rootdir

  3 - Using a pre-trained model to generate cell

  • Edit the configuration file : generation part

  $root_dir vi parameters.yml

  • run

  $workdir   python  generate.py root_dir

Developing and Contributing

See contributing.md for guidelines on running tests, adding features, coding style, and updating documentation when developing in or contributing to genheas

Authors

Conrard Tetsassi