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

Project description

mcmc_statphys

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

Features

A simple Ising model simulation.

>>> 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:

$ 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).

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

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.

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