Methods for running simulations to calculate Voter Satisfaction Efficiency (VSE) of various voting systems in various conditions.
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Failed to load latest commit information.
docs SRV->Star (final??) Jul 2, 2018
test fix use of old internal test library: ImportError: No module named 't… Jan 13, 2017
.project Point to the docs; Rename README to Feb 21, 2017
newResults.txt Include Srv, KsModel; other updates Jan 7, 2017
tenK.txt README: more tests; More doc; drop writeLn call Jan 16, 2017
vseBrochure.svg SRV->Star Jul 2, 2018
vseCheck.R SRV->Star Jul 2, 2018

Voter Satisfaction Efficiency

These are some methods for running VSE (Voter Satisfaction Efficiency) simulations for various voting systems.

See Voter Satisfaction Efficiency for an explanation of the methods and results.

Installing the code

Requirements: python3, scipy, pydoc

Testing uses pydoc, which should make most things pretty self-documenting.


python3 -m doctest
python3 -m doctest
python3 -m doctest

Running simulations


$ python3
>>> csvs = CsvBatch(PolyaModel(), [[Score(), baseRuns], [Mav(), medianRuns]], nvot=5, ncand=4, niter=3)
>>> csvs.saveFile()

and look for the results in SimResults1.csv