Pymcmcstat

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.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.4127047.svg
:target: https://doi.org/10.5281/zenodo.4127047

- Fixed 79 - Chainstats display now auto updates formatting for really large or small numbers.
- Fixed 82 - Initial value check routine in Parallel MCMC now correctly removes extra columns.

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:target: https://doi.org/10.5281/zenodo.3342988

- Added feature to results structure to store all parameters names, regardless of whether or not they are included in sampling.
- Added mcmcplot package to requirements. MCMCPlotting module is noted as deprecated.
- Added new module for uncertainty propagation. Aims to provide more flexible API for user to plot different combinations of credible and prediction intervals.
- Added a plotting routine so that you can plot a 2-D interval in 3-D space.

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.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3261287.svg
:target: https://doi.org/10.5281/zenodo.3261287

- Added acceptance rate display feature when calling chain statistics
- User can specify `skip` or `maxpoints` in pairwise correlation and chain panel plots in order to thin chain.
- User can request item definitions when calling `chainstats`.
- Resolved 51 by adding method to check if limits are incompatible. User is provided with more descriptive error message.
- Updated documentation for Bayesian components.
- Added saving routines to accomodate post-processing. A lighter version of the results dictionary is saved to json when log routines are used for chains. This should address 55.
- Option to return KDE objects when using `plot_density_panel`. User can then evaluate pdf directly. This should address 66.

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.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.2660145.svg
:target: https://doi.org/10.5281/zenodo.2660145

- Fixed bug 41.
- Updated how version attribute is defined in package and referenced in setup.py and documentation.

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.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.2630882.svg
:target: https://doi.org/10.5281/zenodo.2630882

- Added custom sampler feature. Interface requires creation of a class, but allows for inclusion of things like Gibbs samplers. User can explicitly pass in features to the sum-of-squares function.
- Added check routines for reading in parallel MCMC results to ensure only directories with name 'chain_' are queried.
- All files were updated to comply with formatting standards using *flake8*.
- Added coverage report check to ensure minimal testing requirements are met.
- Added original covariance matrix to results structure for reference.

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.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.1407136.svg
:target: https://doi.org/10.5281/zenodo.1407136

- Added optimal handling of prior function used numpy array multiplication.
- Fixed bug with saving results to json file - output directory now automatically made.
- Updated PI plotting to allow any valid matplotlib input.
- Added Gelman-Rubin diagnostics to ChainStatistics module, with display feature.
- Added numpy error settings option to MCMC initialization.
- Setup no adaptation feature. Can sample parameters without adapting them.
- Added restart routine to ParallelMCMC. Can restart from json files.
- Added parallel chain organization routines to the chain subpackage.