Metadata-Version: 2.1
Name: ptmcmcsampler
Version: 2.1.0
Summary: Parallel tempering MCMC sampler written in Python
Home-page: https://github.com/jellis18/PTMCMCSampler
Author: Justin A. Ellis
Author-email: justin.ellis18@gmail.com
License: MIT
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: mpi
License-File: LICENSE

# PTMCMCSampler

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[![DOI](https://zenodo.org/badge/32821232.svg)](https://zenodo.org/badge/latestdoi/32821232)
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MPI enabled Parallel Tempering MCMC code written in Python.

See the [examples](https://github.com/jellis18/PTMCMCSampler/tree/master/examples) for some simple use cases.

For MPI support you will need A functional MPI 1.x/2.x/3.x implementation like:

- [MPICH](http://www.mpich.org/)

  ```bash
  # mac
  brew install mpich

  # debian
  sudo apt install mpich
  ```

- [Open MPI](http://www.open-mpi.org/)

  ```bash
  # mac
  brew install open-mpi

  # debian
  sudo apt install libopenmpi-dev
  ```

To run with MPI support you can run your script containing a sampler with:

```bash
mpirun -np <number of temperature chains> script.py
```

This will kick off `np` chains running at different temperatures. The temperature ladder and sampling schemes can be set in the `PTMCMCSampler.sample()` method.

## Installation

### Development

For development clone this repo and run:

```bash
make init
source venv/bin/activate
```

### Via pip

```bash
pip install ptmcmcsampler
```

for MPI support use

```bash
pip install ptmcmcsampler[mpi]
```

### Via conda

```bash
conda install -c conda-forge ptmcmcsampler
```

for MPI support use

```bash
conda install -c conda-forge ptmcmcsampler mpi4py
```

## Attribution

If you make use of this code, please cite:

```
@misc{justin_ellis_2017_1037579,
  author       = {Justin Ellis and
                  Rutger van Haasteren},
  title        = {jellis18/PTMCMCSampler: Official Release},
  month        = oct,
  year         = 2017,
  doi          = {10.5281/zenodo.1037579},
  url          = {https://doi.org/10.5281/zenodo.1037579}
}
```

### Correlation Length

In order for the sampler to run correctly using `acor` with Python 3 kernels the GitHub version of acor needs to be installed. (Currently the PyPI version is behind the GitHub version.) It can be easily installed with:

```
pip install git+https://github.com/dfm/acor.git@master
```

> Note that `acor` is not required to run the sampler, it simply calculates the effective chain length for output in the chain file.


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