A library to consume your fitting chains! Produce likelihood surfaces, plot your walks to check convergence, output a LaTeX table of the marginalised parameter distributions with uncertainties and significant figures all done for you, or throw in a bunch of chains from different models and perform some model selection!

Click through to the online documentation

Install via pip:

pip install chainconsumer

Install via conda:

conda install -c samreay chainconsumer 

I would like to thank the following people for their contribution in issues, algorithms and code snippets which have helped improve ChainConsumer:

• Chris Davis (check out https://github.com/cpadavis/preliminize)
• Joe Zuntz
• Scott Dedelson
• Elizabeth Krause
• David Parkinson
• Caitlin Adams
• Tom McClintock
• Steven Murray
• J. Michael Burgess
• Matthew Kirby
• Michael Troxel
• Eduardo Rozo
• Warren Morningstar

Users on some Linux platforms have reported issues rendering plots using ChainConsumer. The common error states that dvipng: not found, and as per StackOverflow post, it can be solved by explicitly install the matplotlib dependency dvipng via sudo apt-get install dvipng.

• Adding ability to turn off chain names in plot_summary.

• Fixing bug with plot_walks that required truth values.
• Fixing flaw in configure to allow for updating values.
• Fixing bug where summary values are cached without reference to the summary statistic method.

• Adding ability to plot maximum points on 2D contour, not just global posterior maximum.
• Fixing truth dictionary mutation on plot_walks

• Adding ability to pass in a power to raise the surface to for each chain.
• Adding methods to retrieve the maximum posterior point: Analysis.get_max_posteriors
• Adding ability to plot maximum posterior points. Can control marker_size, marker_style, marker_alpha, and whether to plot contours, points or both.
• Finishing migration of configuration options you can specify when adding chains rather than configuring all chains with configure.

• (Attempting to) enable fully automated releases to Github, PyPI, Zenodo and conda.

• (Attempting to) enable fully automated releases to Github, PyPI, Zenodo and conda.

• Changing default sigma2d to False. May chance how your plots are displayed.
• Allowing format specification when adding chains.
• Making yule_walker (and thus all of statsmodels) a conditional import.
• Updating minimum version of requirements to reduce issues with install.

• Fixing bug in label rendering for contour sigma labels.
• Improving parsing of sigma in configure, such that you don't need a leading zero.

• Fixing bug in get_correlations.

• Changing default colour order.
• Improving behaviour of shade_gradient.

• Refactoring project structure.
• Updating colours for better legibility.
• Setting shade=True automatically if shade_alpha is overriden.

• Removing bbox_inches="tight" due to a bug in matplotlib v2.1.0.
• Adding more colour shortcuts.

• Making rainbow colours slightly more visible by darkening the yellow regions.

• Can now pass a list of filenames to save out, to make generating a PNG and PDF option in one go easier
• Adding method plot_summary

• Adding option to specify the confidence interval (area) for parameter summaries.
• Adding three extra methods for parameter summaries from Andrae 2010: max symmetric, max shortest and max central stats.

• Fixing a bug that caused ChainConsumer to crash in some cases when you specified a number of parameters.

• Fixing bug that made parameter ordering incorrect in some circumstances.

• Fixing error when plotting walks with small weights.

• Fixing issue where refactoring broke parameter blinding.

• ChainConsumer now only finds extents of relevant parameters when plotting, instead of all parameters.

• Updating extents so previous updates do something.

• Adding example and code to deal with non-TeX watermarks.

• Increasing extents again.
• Updating legend defaults.
• Code refactor.
• Can now specify which chains to plot when plotting contours.
• Adding watermark text.

• Increase control over legend with kwargs.
• Can specify legend subplot location.
• Increased legend options with coloured text.
• Added shade_gradient option.
• Increase the amount of default extent given.

• Adding ability to blind parameters.

• Adding ability to plot contour levels, either in confidence levels or sigma.
• Changed shading defaults.

• Legend gets placed in top right corner now when plot_hsits is False and there are only two parameters.

• sigma2d correctly defaults to True now.

• Adding log_weights to the detected colour parameters.
• Contours now support 1D Gaussian levels and 2D Gaussian levels (thanks @matthewkirby).

• Adding Matched Elliptical Gaussian Kernel Density Estimator to replace statsmodels KDE.

• Fixing bug in covariance calculation when getting the LaTeX table (did not affect contours)

• Default figure size is now 1.5 inches per parameter, instead of 1. Also decreasing default font size, so that printing summaries is less likely to overlap surfaces.

• Label font size now applies to legend.

• Code quality improvements
• Documentation update

• Refactoring ChainConsumer due to growing size.
• Improve bin limits to reduce overly large bins that form when some low-weight samples are located far away from the mean.
• Fixed issue generating text with one sided distributions.
• Adding ability to specify weights or posterior as the colour parameter.
• Color scatter with uniform weights doesn't have first plot a different color.
• Adding ability to control subplot spacing.
• Adding method plot_distributions to quickly plot marginalised distributions.

• Fixing bug in Gelman-Rubin diagnostic. Thanks Warren!

• Moving rc parameters before plot creation to fix issues with parallel plot generation.

• Fixing an integer division bug where python 2 contour shading was setting to 0 alpha.

• Fixing bug where tick font size was only honoured when ticks were on an angle.

• Adding ability to specify label font size, tick font size, and whether the ticks should be on an angle.

• Bug fix for those with latest numpy which removed a deprecated method I was using.
• Adding ability to get parameter covariance tables.

• Adding ability to get parameter correlation tables.

• Removing unnecessary debug output.

• Can remove lists of chains properly now.

• Adding ability to remove chains.

• Adding ability to plot the walks of multiple chains together.

• Removing unnecessary debug output.

• Bugfix for python 2.7

• Adding usetex to configure method.
• When plotting walks, plots weights in log space if the mean weight is less than 0.1
• Adding AIC
• Adding BIC
• Adding DIC
• Adding method to output model comparison table.

• Adding coloured scatter.
• Disallowing grid data and KDE.
• Adding more examples.
• Consolidating all configures into one method.
• Improved extent finding.
• Updating smoothing to use reflect and not constant.
• Improving max statistics being able to find ranges on cliff edges.
• Printing parameter summaries without parameter labels.

• Removing ability to having vectorised dictionary inputs for grid data due to 2.7 compatibility issues.

• Fixing bug when smoothing grid data.
• Adding more input options.
• Grids can now be specified using a list of parameter vectors.

• Better determination of extents for data with extreme weighting.
• Able to scale figure size using float when plotting.

• Modifying API defaults for smoothing with grid data.
• Allowing both smoothing and bins to be passed in as lists.

• Adding support for grid data.

• Fixing bug in Gelman-Rubin statistic

• Improving text labels again.

• Improving text labels for high value data.

• Adding Gelman-Rubin and Geweke diagnostic methods.

• Adding options for alternate statistics.

• Updating setup so that dependencies are automatically installed.

• Modifying the add_chain API, so that you can pass dictionaries!

• Smarter extent tick labels and offsets.
• Adding list based line styles, widths, shading and opacity.
• Adding two more examples.

• Preconfiguring logging.

• Adding 2D Gaussian smoothing for the contour surfaces.
• Renaming contourf and contourf_alpha to shade and shade_alpha.
• Updating some of the example plots.

• Updating package setup scripts.

• Updating package setup scripts.

• Adding markdown paper.

• Updating setup and package details

• Initial zenodo release

• Adding in smoothing, making it default
• Adding extra example to show how to remove smoothing.

• Adding in tests

• Initial PyPi push