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Python pacakge to flatten and fold parameter data structures.

Project description


This is a library (very much still in development) intended to make sensitivity analysis easier for optimization problems. The core functionality consists of tools for “folding” and “flattening” collections of parameters – i.e., for converting data structures of constrained parameters to and from vectors of unconstrained parameters.

For background and motivation, see the following papers:

Covariances, Robustness, and Variational Bayes
Ryan Giordano, Tamara Broderick, Michael I. Jordan

A Swiss Army Infinitesimal Jackknife
Ryan Giordano, Will Stephenson, Runjing Liu, Michael I. Jordan, Tamara Broderick

Evaluating Sensitivity to the Stick Breaking Prior in Bayesian Nonparametrics
Runjing Liu, Ryan Giordano, Michael I. Jordan, Tamara Broderick

Using the package.

We welcome new users! However, please be aware that the package is still in development. We encourage users to contact the author (github user rgiordan) for advice, bugs, or if you’re using the package for something important.


The package is not (yet) registered on pypi. To install, run the following command, pointing to the root of the git repo:

sudo -H pip3 install --user -e paragami.

Documentation and Examples.

For API documentation, see readthedocs.

Alternatively, check out the repo and run make html in docs/.

For motivating and expository Jupyter notebooks, see docs/example_notebooks/. A good place to start is docs/example_notebooks/front_page_example.ipynb.

Project details

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Files for paragami, version 0.1
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