better plotting experience with unstable models

Small update that improves the user experience when analyzing models that are numerically unstable. The plotting functions now work, even if the model has failed to converge.

v0.9.3: Merge pull request #15 from harmsm/main

Minor bugfix release.

v0.9.2

Adds Bayesian MCMC convergence testing.

v0.9.1

Changes

• Added fit quality assessment statistics
• Changed how parameters are summarized for bootstrap and Bayesian MCMC modes. Rather than reporting the parameter means, dataprob now reports the mode estimated via a Gaussian kernel density estimator applied to the pseudo-replicate or posterior distribution.
• Updated and expanded docs and example notebooks

final api, pre-release

Fully functional dataprob library.

This release has the final API that will go into the announcement release, with full documentation and a complete test suite. It is a pre-release to allow testing by users, as well as to test integration with pip, readthedocs, and colab.

v0.2.0

Added the ability to use gaussian priors in Bayesian inferences, increased test coverage, and fixed bugs throughout code.

v0.2.1

Added the ability to use gaussian priors in Bayesian inferences, increased test coverage, and fixed bugs throughout code.

alpha release for pypi

Merge pull request #8 from harmsm/main

finalize automatic pypi publishing

First release

Alpha release of code for calculating probability of data given specific models.