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')
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
!
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.
Documentation is hosted at ReadTheDocs. Find an exhaustive set of examples there!
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