Metadata-Version: 2.1
Name: mcmc-statphys
Version: 0.3.0
Summary: A library project of Monte Carlo simulation algorithms for some statistical physics models (in particular, the Ising model and its variants).
Home-page: https://github.com/uynajgi/mcmc_statphys
Author: Uynaj GI
Author-email: suquan12148@outlook.com
License: MIT license
Keywords: mcmc_statphys
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
License-File: LICENSE
License-File: AUTHORS.rst

=============
mcmc_statphys
=============


.. image:: https://img.shields.io/pypi/v/mcmc_statphys.svg
        :target: https://pypi.python.org/pypi/mcmc_statphys

.. image:: https://img.shields.io/travis/uynajgi/mcmc_statphys.svg
        :target: https://travis-ci.com/uynajgi/mcmc_statphys

.. image:: https://readthedocs.org/projects/mcmc-statphys/badge/?version=latest
        :target: https://mcmc-statphys.readthedocs.io/en/latest/?version=latest
        :alt: Documentation Status




A Python package of Monte Carlo simulation algorithms for some statistical physics models (in particular, the Ising model and its variants).


* Free software: MIT license
* Documentation: https://mcmc-statphys.readthedocs.io.


Features
--------

A simple Ising model simulation.

.. code-block:: python

    >>> import mcmc_statphys as mcsp
    >>> model = mcsp.model.Ising(12) # 12x12 Ising model
    >>> algorithm = mcsp.method.Metropolis(model) # Metropolis algorithm
    >>> uid = algorithm.equil_sample(T=1, max_iter=1000) # sample until equilibrium
    >>> fig = mcsp.draw.Plot(algorithm) 
    >>> fig.curve(uid=uid, comlumn='energy') # plot the energy curve

Install
-------

the latest version of mcmc_statphys: 

.. code-block:: console

    $ pip install mcmc_statphys

Bugs
----

Please report any bugs that you find `here`_. Or, even better, fork the repository on `GitHub`_ and create a pull request (PR). We welcome all changes, big or small, and we will help you make the PR if you are new to git (just ask on the issue and/or see `CONTRIBUTING`_).

.. _here: https://github.com/uynajgi/mcmc_statphys/issues
.. _GitHub: https://github.com/uynajgi/mcmc_statphys/
.. _CONTRIBUTING: https://mcmc-statphys.readthedocs.io/en/latest/contributing.html

Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage


=======
History
=======

All notable changes to this project will be documented in this file.

The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

[Unreleased]
------------

[0.3.0] - 2023-05-18
--------------------

Added
~~~~~

* Add `cv` in `analysis` to calculate the cv
* Add `spin2svd` in `analysis`
* Add `uid2svd` in `analysis`

[0.2.1] - 2023-05-17
--------------------

Fixed
~~~~~

* Fix the bug of saving `_get_per_magnetization` in `_save_data` in `algorithm`

Added
~~~~~

* Add moudle `analysis` to analyze the data
* Add moudle `draw` to draw the figures
* Add method `setspin` in `model`
* Add tqmd to show the progress bar

Doc
~~~

* Add documentation to README
* Add documentation to Usages

Changed
~~~~~~~

* Change the methods in the `analysis` module: removed the `Sample` and `ParameterSample` classes, added `Metropolis`, `Wolff`, `Anneal` classes and several methods

[0.1.2] - 2023-05-15
--------------------

Security
~~~~~~~~

* Add function annotations to all functions
* Add type hints to all functions
* Add type hints to all variables
* Change `mcmc_statphys.py` to `method.py`

Doc
~~~

* Add documentation to README

[0.1.1] - 2023-05-14
--------------------

* First release on PyPI.
