prefsampling 0.0.1

Algorithms to sample preferences of all kinds.

PrefSampling

A small package providing all the algorithms to sample preferences

Development

We try to enforce uniformity within the package. Here are some general guidelines.

• All samplers have num_agents and num_candidates as their first positional arguments
• All samplers accept a seed parameter to set the seed of the random number generator

The tests are run with unittest. This is the procedure when adding a new sampler.

• Add the sampler to the list ALL_SAMPLERS in test_samplers.py. The basic requirements (parameters, validation, etc.) that any sampler need to satisfy will then be checked.
• Add the sampler to corresponding test file for its ballot format (e.g., test_ordinal_samplers.py).
• If needed, add a file test_ballotformat_samplername.py for tests that are specific to the sampler.

The doc is generated using sphinx. We use the numpy style guide. The napoleon extension for Sphinx is used and the HTML style is defined by the Book Sphinx Theme.

To generate the doc, first move inside the docs-source folder and run the following:

make clean 
make html

This will generate the documentation locally (in the folder docs-source/build). If you want the documentation to also be updated when pushing, run:

make github

After having pushed, the documentation will automatically be updated.