Metadata-Version: 2.1
Name: deepqmc
Version: 0.1.1
Summary: Deep-learning quantum Monte Carlo for electrons in real space
Home-page: https://github.com/deepqmc/deepqmc
License: MIT
Author: Jan Hermann
Author-email: jan.hermann@fu-berlin.de
Requires-Python: >=3.7,<4.0
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Environment :: GPU :: NVIDIA CUDA
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Physics
Provides-Extra: all
Provides-Extra: cli
Provides-Extra: doc
Provides-Extra: test
Provides-Extra: train
Provides-Extra: wf
Requires-Dist: Pillow (>=7,<8); extra == "train" or extra == "all"
Requires-Dist: click (>=7.0,<8.0); extra == "cli" or extra == "all"
Requires-Dist: coverage (>=4.5,<5.0); extra == "test" or extra == "all"
Requires-Dist: h5py (>=2.10.0,<3.0.0); extra == "train" or extra == "all"
Requires-Dist: numpy (>=1.16,<2.0)
Requires-Dist: pyscf (>=1.6,<2.0); extra == "wf" or extra == "all"
Requires-Dist: pytest (>=4.4,<5.0); extra == "test" or extra == "all"
Requires-Dist: scipy (>=1.2,<2.0); extra == "wf" or extra == "all"
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Requires-Dist: sphinxcontrib-katex (>=0.5.1,<0.6.0); extra == "doc"
Requires-Dist: tensorboard (>=2.0,<3.0); extra == "train" or extra == "all"
Requires-Dist: toml (>=0.10.0,<0.11.0)
Requires-Dist: torch (>=1.2,<2.0)
Requires-Dist: tqdm (>=4.31,<5.0); extra == "train" or extra == "all"
Requires-Dist: uncertainties (>=3.1.2,<4.0.0)
Project-URL: Documentation, https://deepqmc.github.io
Project-URL: Repository, https://github.com/deepqmc/deepqmc
Description-Content-Type: text/markdown

# DeepQMC

[![build](https://img.shields.io/travis/deepqmc/deepqmc/master.svg)](https://travis-ci.com/deepqmc/deepqmc)
[![coverage](https://img.shields.io/codecov/c/github/deepqmc/deepqmc.svg)](https://codecov.io/gh/deepqmc/deepqmc)
![python](https://img.shields.io/pypi/pyversions/deepqmc.svg)
[![release](https://img.shields.io/github/release/deepqmc/deepqmc.svg)](https://github.com/deepqmc/deepqmc/releases)
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[![commits since](https://img.shields.io/github/commits-since/deepqmc/deepqmc/latest.svg)](https://github.com/deepqmc/deepqmc/releases)
[![last commit](https://img.shields.io/github/last-commit/deepqmc/deepqmc.svg)](https://github.com/deepqmc/deepqmc/commits/master)
[![license](https://img.shields.io/github/license/deepqmc/deepqmc.svg)](https://github.com/deepqmc/deepqmc/blob/master/LICENSE)
[![code style](https://img.shields.io/badge/code%20style-black-202020.svg)](https://github.com/ambv/black)

DeepQMC implements variational quantum Monte Carlo for electrons in molecules, using deep neural networks written in [PyTorch](https://pytorch.org) as trial wave functions. Besides the core functionality, it contains implementations of the following ansatzes:

- PauliNet: https://arxiv.org/abs/1909.08423

## Installing

Install and update using [Pip](https://pip.pypa.io/en/stable/quickstart/).

```
pip install -U deepqmc[wf,train]
```

## A simple example

```python
from deepqmc import Molecule, evaluate, train
from deepqmc.wf import PauliNet

mol = Molecule.from_name('LiH')
net = PauliNet.from_hf(mol).cuda()
train(net)
evaluate(net)
```

## Links

- Documentation: https://deepqmc.github.io

