vse.py

from imp import reload

from mydecorators import autoassign, cached_property, setdefaultattr, timeit
import random
from numpy.lib.scimath import sqrt
from numpy.core.fromnumeric import mean, std
from numpy.lib.function_base import median
from numpy.ma.core import floor
from test.test_binop import isnum
from debugDump import *


from voterModels import *
from stratFunctions import *
from methods import *
from uuid import uuid4
import csv, os
join = os.path.join




def uniquify(seq):
    # order preserving
    checked = []
    for e in seq:
       if e not in checked:
           checked.append(e)
    return checked

class CsvBatch:
    @timeit
    @autoassign
    def __init__(self, model, methods, nvot, ncand, niter,
            baseName = None, media=truth, seed=None, force=False):
        """A harness function which creates niter elections from model and finds three kinds
        of utility for all methods given.

        for instance:

        >>> csvs = CsvBatch(PolyaModel(), [[Score(), baseRuns], [Mav(), medianRuns]], nvot=5, ncand=4, niter=3)
        >>> len(csvs.rows)
        54
        """
        rows = []
        emodel = str(model)
        if (seed is None):
            seed = (baseName or '') + str(niter)
            self.seed = seed
        random.seed(seed)
        try:
            from git import Repo
            repo = Repo(os.getcwd())
            if not force:
                assert not repo.is_dirty()
            self.repo_version = repo.head.commit.hexsha
        except:
            self.repo_version = 'unknown repo version'
        for i in range(niter):
            eid = uuid4()
            electorate = model(nvot, ncand)
            for method, chooserFuns in methods:
                results = method.resultsTable(eid, emodel, ncand, electorate, chooserFuns, media=media)
                rows.extend(results)
            debug(i,results[1:3])
        self.rows = rows
        if baseName:
            self.saveFile(baseName)

    def saveFile(self, baseName="SimResults"):
        """print the result of doVse in an accessible format.
        for instance:

        csvs.saveFile()
        """
        i = 1
        while os.path.isfile(baseName + str(i) + ".csv"):
            i += 1
        keys = ["vse", "method", "chooser", *list(self.rows[0].keys())]
        for n in range(4):
            keys.extend([f"tallyName{str(n)}", f"tallyVal{str(n)}"])
        keys = uniquify(keys)
        with open(baseName + str(i) + ".csv", "w") as myFile:
            print(
                f"# {dict(media=self.media.__name__, version=self.repo_version, seed=self.seed, model=self.model, methods=self.methods, nvot=self.nvot, ncand=self.ncand, niter=self.niter)}",
                file=myFile,
            )

            dw = csv.DictWriter(myFile, keys, restval = "NA")
            dw.writeheader()
            for r in self.rows:
                dw.writerow(r)



medianRuns = [
               OssChooser([beHon,ProbChooser([(1/2, beStrat), (1/2, beHon)])]),


               ProbChooser([(1/4, beX), (3/4, beHon)]),
               ProbChooser([(1/2, beX), (1/2, beHon)]),
               ProbChooser([(3/4, beX), (1/4, beHon)]),

               ProbChooser([(0.5, beStrat), (0.5, beHon)]),
               ProbChooser([(1/3, beStrat), (1/3, beHon), (1/3, beX)]),

               LazyChooser(),
               ProbChooser([(1/2, LazyChooser()), (1/2, beHon)]),

               ]

baseRuns = [
           OssChooser([beHon,ProbChooser([(1/2, beStrat), (1/2, beHon)])]),

           ProbChooser([(1/4, beStrat), (3/4, beHon)]),
           ProbChooser([(1/2, beStrat), (1/2, beHon)]),
           ProbChooser([(3/4, beStrat), (1/4, beHon)]),

           ]

allSystems = [[Score(1000), baseRuns],
                [Score(10), baseRuns],
                [Score(2), baseRuns],
                [Score(1), baseRuns],
                [BulletyApprovalWith(.6), baseRuns],
                [Srv(10), baseRuns],
                [Srv(2), baseRuns],
                [Plurality(), baseRuns],
                [Borda(), baseRuns],
                [Irv(), baseRuns],
                [IrvPrime(), baseRuns],
                [Schulze(), baseRuns],
                [Rp(), baseRuns],
                [V321(), baseRuns],
                [Mav(), medianRuns],
                [Mj(), medianRuns],
                [IRNR(), baseRuns],
                 ]

#request from Mark: "SRV0-2, SRV0-3, SRV0-4, SRV0-5, SRV0-6, SRV0-7, SRV0-8, SRV0-9, SRV0-10, Score0-10, 321, Approval, IRV and plurality"
markMethods = [
                [Srv(2), baseRuns],
                [Srv(3), baseRuns],
                [Srv(4), baseRuns],
                [Srv(5), baseRuns],
                [Srv(6), baseRuns],
                [Srv(7), baseRuns],
                [Srv(8), baseRuns],
                [Srv(9), baseRuns],
                [Score(10), baseRuns],
                [V321(), baseRuns],
                [BulletyApprovalWith(.6), baseRuns],
                [Irv(), baseRuns],
                [Plurality(), baseRuns],
                 ]

#usage example:
#>>> from vse import *
#>>> vses = CsvBatch(KSModel(dcdecay=(1,3),wcdecay=(1.5,3), dccut = .2, wcalpha=1.5),
#           allSystems, nvot=40, ncand=6, niter=15000, baseName="target",
#           media=fuzzyMediaFor())

if __name__ == "__main__":
    import doctest
    setDebug( False)
    doctest.testmod()