What

qmllib is a Python/Fortran toolkit for representation of molecules and solids for machine learning of properties of molecules and solids. The library is not a high-level framework where you can do model.train(), but supplies the building blocks to carry out efficient and accurate machine learning. As such, the goal is to provide usable and efficient implementations of concepts such as representations and kernels.

QML or QMLLib?

qmllib represents the core library functionality derived from the original QML package, providing a powerful toolkit for quantum machine learning applications, but without the high-level abstraction, for example SKLearn.

This package is and should stay free-function design oriented.

Breaking changes from qml:

• FCHL representations callable interface to be consistent with other representations (e.i. atoms, coordinates)

How to install

A proper pip-package is on the way, for now

pip install git+https://github.com/qmlcode/qmllib

or if you want a specific feature branch

pip install git+https://github.com/qmlcode/qmllib@feature_branch

How to contribute

Know a issue and want to get started developing?

git clone repo.url qmllib.git
cd qmllib.git
make # setup env
make compile # compile

You know have a conda environment in ./env and are ready to run

make test

happy developing

How to use

raise NotImplementedError

How to cite

raise NotImplementedError

What TODO

• Setup ifort flags
• Setup based on FCC env variable or --global-option flags
• Find MKL from env (for example conda)
• Find what numpy has been linked too (lapack or mkl)