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Computational Autonomy for Materials Discovery (CAMD)

Installation

Note that, since qmpy is currently only python 2.7 compatible, CAMD python 3 compatibility depends on a custom fork of qmpy here, which is installed using the setup.py procedure.

We recommend using Anaconda python, and creating a fresh conda environment for the install (e. g. conda create -n MY_ENV_NAME).

Linux

Update packages via apt and set pathing for MySQL dependency:

apt-get update
apt install -y default-libmysqlclient-dev gcc
export PATH=$PATH:/usr/local/mysql/bin

Install numpy/Django via pip first, since the build depends on this and numpy has some difficulty recognizing its own install:

pip install numpy
pip install Django

Then use the included setup.py procedure, from the cloned directory.

python setup.py develop

Mac OSX

First dependencies via homebrew. Thanks to the contributors to this stack exchange thread.

$ brew install mysql
$ brew install postgresql
$ brew install gcc

Install numpy/Django via pip first, since the build depends on these and numpy has some difficulty recognizing its own install:

pip install numpy
pip install Django

Then use the included setup.py procedure, from the cloned directory.

python setup.py develop

Data download

Datasets for featurized OQMD entries for after-the-fact testing can be downloaded at data.matr.io/3

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  • Python 70.2%
  • Jupyter Notebook 29.8%