| Name | qmllib JSON |
| Version |
1.0.1
JSON |
| download |
| home_page | None |
| Summary | Python/Fortran toolkit for representation of molecules and solids for machine learning of properties of molecules and solids. |
| upload_time | 2024-03-29 20:19:01 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | None |
| keywords |
qml
quantum chemistry
machine learning
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
====
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
.. code-block:: bash
pip install git+https://github.com/qmlcode/qmllib
or if you want a specific feature branch
.. code-block:: bash
pip install git+https://github.com/qmlcode/qmllib@feature_branch
=================
How to contribute
=================
Know a issue and want to get started developing?
.. code-block:: bash
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
.. code-block:: bash
make test
happy developing
==========
How to use
==========
.. code-block:: python
raise NotImplementedError
===========
How to cite
===========
.. code-block:: python
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)
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