n0w0f/superionic_ai_flyte

A computational workflow for screening superionic conductors managed by flyte

Superionic_ai [FLYTE]

A heirarchical screening workflow to discover superionic conductors managed by flyte

Local Installation

The following steps assume that you use MacOS or some Linux flavor. If you use Windows, we recommend that you first install the Windows Subsystem for Linux (WSL).

We recommend that you create a virtual conda environment on your computer in which you install the dependencies for this exercise. To do so head over to Miniconda and follow the installation instructions there.

Then, use

conda env create -f environment.yml -n superionic_ai

You can activate this environment using

conda activate superionic_ai

Create a new folder and clone this repository (you need git for this, if you get a missing command error for git you can install it with sudo apt-get install git)

git clone https://github.com/n0w0f/superionic_ai.git
cd superionic_ai
pip install -e .

💪 Getting Started

cd src
python3 main.py

Project Organization

├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`  #TODO
├── README.md          <- The top-level README for developers using this project.
|
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details  #TODO
│
├── models             <- Trained and serialized model checkpoints will be loaded while running src 
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials.  #TODO
│
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported   #TODO
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   │
│   ├── data            <- all data prepared or developed using the app will reside here
|   |   |──          
│   │   └── start_mat.yaml  
│   │
│   ├── data_prep                     <- Scripts to turn raw data into features , query structures, build structures , anything related to data !!
|   |   |──  mp_query.py              <- anything relater to materials project api, query
|   |   |──  structure_builder.py     <- anythin related to playing with strucututres
│   │   └──  pymatgen_action.py       <- anything related to pymatgen 
│   │
|   ├── utils                <-  All helper function
|   |   |──  read_yaml.py    <-  reading yamls
│   │   └── manage_files.py  <-  create folders save files 
│   │
│   ├── models         <- Scripts to use models in workflows
│   │   │                 
│   │   ├── dynamics.py   <- anything realted to md
│   │   ├── dynamics.py   <- anything realted to screening
│   │   └── m3gnet.py     <- property prediction, relax
│   │
│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
│       └── visualize.py
│
└── tox.ini            <- tox file with settings for running tox; see tox.readthedocs.io  #TODO

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Project based on the cookiecutter data science project template. #cookiecutterdatascience