pygtc.py
=========
**What is a Giant Triangle Confusogram?**
A Giant-Triangle-Confusogram (GTC, aka triangle plot) is a way of
displaying the results of a Monte-Carlo Markov Chain (MCMC) sampling or similar
analysis. (For a discussion of MCMC analysis, see the excellent ``emcee``
package.) The recovered parameter constraints are displayed on a grid in which
the diagonal shows the one-dimensional posteriors (and, optionally, priors) and
the lower-left triangle shows the pairwise projections. You might want to look
at a plot like this if you are fitting a model to data and want to see the
parameter covariances along with the priors.
Here's an example of a GTC with some random data and arbitrary labels::
pygtc.plotGTC(chains=[samples1,samples2],
paramNames=names,
chainLabels=chainLabels,
truths=truths,
truthLabels=truthLabels,
priors=priors,
paramRanges=paramRanges,
figureSize='MNRAS_page')
.. image:: https://raw.githubusercontent.com/SebastianBocquet/pygtc/master/docs/_static/demo_files/demo_9_1.png
**But doesn't this already exist in corner.py, distUtils, etc...?**
Although several other packages exists to make such a plot, we were unsatisfied
with the amount of extra work required to massage the result into something we
were happy to publish. With ``pygtc``, we hope to take that extra legwork out of
the equation by providing a package that gives a figure that is publication
ready on the first try! You should try all the packages and use the one you like
most; for us, that is ``pygtc``!
Installation
------------
For a quick start, you can install with either ``pip`` or ``conda``. Either will install the required
dependencies for you (``packaging``, ``numpy``, and ``matplotlib``)::
$ pip install pygtc
or, if you use ``conda``::
$ conda install pygtc -c conda-forge
For more installation details, see the `documentation <http://pygtc.readthedocs.io/>`_.
Documentation
-------------
Documentation is hosted at `ReadTheDocs <http://pygtc.readthedocs.io/>`_. Find
an exhaustive set of examples there!
Citation
--------
If you use pygtc to generate plots for a publication, please cite as::
@article{Bocquet2016,
doi = {10.21105/joss.00046},
url = {http://dx.doi.org/10.21105/joss.00046},
year = {2016},
month = {oct},
publisher = {The Open Journal},
volume = {1},
number = {6},
author = {Sebastian Bocquet and Faustin W. Carter},
title = {pygtc: beautiful parameter covariance plots (aka. Giant Triangle Confusograms)},
journal = {The Journal of Open Source Software}
}
Copyright 2016, Sebastian Bocquet and Faustin W. Carter
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.159091.svg
:target: https://doi.org/10.5281/zenodo.159091
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