{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Getting Started With `mcmcplot`\n", "Author(s): Paul Miles | August 7, 2018\n", "\n", "## Introduction\n", "The [mcmcplot](https://github.com/prmiles/mcmcplot/wiki) package is designed to assist in the analysis of sampling chains gathered during a Markov Chain Monte Carlo (MCMC) simulation. This package was designed with the MCMC code [pymcmcstat](https://github.com/prmiles/pymcmcstat/wiki) in mind; however, the plotting routines are amenable to other data sets. The plotting routines use [matplotlib](https://matplotlib.org/) and [seaborn](https://seaborn.pydata.org/). User's are recommended to investigate other plotting routines available in [seaborn](https://seaborn.pydata.org/) as it is specifically designed for this sort of analysis. The routines available in [mcmcplot](https://github.com/prmiles/mcmcplot/wiki) serve as a useful wrapper function for several [seaborn](https://seaborn.pydata.org/) plots, but it is not an exhaustive demonstration.\n", "\n", "## Installation\n", "The code can be found on the [Github project page](https://github.com/prmiles/mcmcplot). The package is available on the PyPI distribution site and the latest version can be installed via\n", "```python\n", "pip install mcmcplot\n", "```\n", "The master branch typically matches the latest version on the PyPI distribution site. To install the master branch directly from Github,\n", "```python\n", "pip install git+https://github.com/prmiles/mcmcplot.git\n", "```\n", "You can also clone the repository and run `python setup.py install`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Basic Examples\n", "The following examples demonstrate how to plot a set of randomly generated chains. For physically motivated examples, see the [pymcmcstat tutorials](https://nbviewer.jupyter.org/github/prmiles/pymcmcstat/blob/master/tutorials/index.ipynb).\n", "\n", "---\n", "[](https://nbviewer.jupyter.org/github/prmiles/notebooks/blob/master/mcmcplot/matplotlib_routines/chain_panel.ipynb)\n", "## [Chain Panel](https://nbviewer.jupyter.org/github/prmiles/notebooks/blob/master/mcmcplot/matplotlib_routines/chain_panel.ipynb)\n", "Key Features:\n", "- Basic chain panel plotting.\n", "- Adding lines for mean and $\\pm$ 2 standard deviations.\n", "- Defining parameter names and editing plot appearance using settings.\n", "- Manually editing plot features.\n", "\n", "
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\n", "\n", "---\n", "[](https://nbviewer.jupyter.org/github/prmiles/notebooks/blob/master/mcmcplot/matplotlib_routines/density_panel.ipynb)\n", "## [Density Panel](https://nbviewer.jupyter.org/github/prmiles/notebooks/blob/master/mcmcplot/matplotlib_routines/density_panel.ipynb)\n", "Key Features:\n", "- Basic density panel plotting.\n", "- Adding histograms to plot.\n", "- Defining parameter names and editing plot appearance using settings.\n", "- Manually editing plot features.\n", "\n", "
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\n", "\n", "---\n", "[](https://nbviewer.jupyter.org/github/prmiles/notebooks/blob/master/mcmcplot/matplotlib_routines/pairwise_correlation_panel.ipynb)\n", "## [Pairwise Correlation Panel](https://nbviewer.jupyter.org/github/prmiles/notebooks/blob/master/mcmcplot/matplotlib_routines/pairwise_correlation_panel.ipynb)\n", "Key Features:\n", "- Basic pairwise correlation panel plotting.\n", "- Adding 50% and 95% probability contours.\n", "- Defining parameter names and editing plot appearance using settings.\n", "- Manually editing plot features.\n", "\n", "
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\n", "\n", "---\n", "[](https://nbviewer.jupyter.org/github/prmiles/notebooks/blob/master/mcmcplot/seaborn_routines/joint_distributions.ipynb)\n", "## [Joint Distributions](https://nbviewer.jupyter.org/github/prmiles/notebooks/blob/master/mcmcplot/seaborn_routines/joint_distributions.ipynb)\n", "Key Features:\n", "- Basic joint distribution plotting.\n", "- Changing the type of joint distribution.\n", "- Editing the seaborn style and settings.\n", "\n", "
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\n", "\n", "---\n", "[](https://nbviewer.jupyter.org/github/prmiles/notebooks/blob/master/mcmcplot/seaborn_routines/paired_density_matrix.ipynb)\n", "## [Paired Density Matrix](https://nbviewer.jupyter.org/github/prmiles/notebooks/blob/master/mcmcplot/seaborn_routines/paired_density_matrix.ipynb)\n", "Key Features:\n", "- Basic paired density matrix plotting.\n", "- Changing the main diagonal, lower triangle, and upper triangle plot types.\n", "- Editing the seaborn style and settings.\n", "\n", "
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