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"description": "pygtc.py\n=========\n\n**What is a Giant Triangle Confusogram?**\n\nA Giant-Triangle-Confusogram (GTC, aka triangle plot) is a way of\ndisplaying the results of a Monte-Carlo Markov Chain (MCMC) sampling or similar\nanalysis. (For a discussion of MCMC analysis, see the excellent ``emcee``\npackage.) The recovered parameter constraints are displayed on a grid in which\nthe diagonal shows the one-dimensional posteriors (and, optionally, priors) and\nthe lower-left triangle shows the pairwise projections. You might want to look\nat a plot like this if you are fitting a model to data and want to see the\nparameter covariances along with the priors.\n\nHere's an example of a GTC with some random data and arbitrary labels::\n\n pygtc.plotGTC(chains=[samples1,samples2],\n paramNames=names,\n chainLabels=chainLabels,\n truths=truths,\n truthLabels=truthLabels,\n priors=priors,\n paramRanges=paramRanges,\n figureSize='MNRAS_page')\n\n.. image:: https://raw.githubusercontent.com/SebastianBocquet/pygtc/master/docs/_static/demo_files/demo_9_1.png\n\n**But doesn't this already exist in corner.py, distUtils, etc...?**\n\nAlthough several other packages exists to make such a plot, we were unsatisfied\nwith the amount of extra work required to massage the result into something we\nwere happy to publish. With ``pygtc``, we hope to take that extra legwork out of\nthe equation by providing a package that gives a figure that is publication\nready on the first try! You should try all the packages and use the one you like\nmost; for us, that is ``pygtc``!\n\nInstallation\n------------\nFor a quick start, you can just use ``pip``. It will install the required\ndependencies for you (``numpy`` and ``matplotlib``)::\n\n pip install pygtc\n\nFor more installation details, see the `documentation `_.\n\nDocumentation\n-------------\nDocumentation is hosted at `ReadTheDocs `_,\nor check out `demo.ipynp `_,\nin this repository, for a working example.\n\nTo build your own local copy of the documentation you'll need to install sphinx. Then you can run ``make html`` from within the ``docs`` folder.\n\nCitation\n--------\nIf you use pygtc to generate plots for a publication, please cite as::\n\n @article{Bocquet2016,\n doi = {10.21105/joss.00046},\n url = {http://dx.doi.org/10.21105/joss.00046},\n year = {2016},\n month = {oct},\n publisher = {The Open Journal},\n volume = {1},\n number = {6},\n author = {Sebastian Bocquet and Faustin W. Carter},\n title = {pygtc: beautiful parameter covariance plots (aka. Giant Triangle Confusograms)},\n journal = {The Journal of Open Source Software}\n }\n\n\nCopyright 2016, Sebastian Bocquet and Faustin W. Carter\n\n.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.159091.svg\n :target: https://doi.org/10.5281/zenodo.159091\n",
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