def run(
BenchmarkTeam,
StatsToMaximize,
TeamsToInclude=[x for x in range(1,13)],
Population=1000,
Generations=60,
PlayersDictionary = team.readPickle('players'),
NumbersPerPositionAsList = [5,5,5,6,3],
TimeFrame = 'stats_lastmonth'
):
playersDic = PlayersDictionary
rwList = team.makePositionList('RW',playersDic,TeamsToInclude)
lwList = team.makePositionList('LW',playersDic,TeamsToInclude)
cList = team.makePositionList('C',playersDic,TeamsToInclude)
dList = team.makePositionList('D',playersDic,TeamsToInclude)
creator.create("FitnessMax", base.Fitness, weights=(1.0,) )
#creator.create("FitnessMax", base.Fitness, weights=tuple( [x/10 for x in range(10,(10-len(StatsToMaximize)),-1)] ) )
creator.create("Team", list, fitness=creator.FitnessMax)
toolbox = base.Toolbox()
toolbox.register("genteam", generateTeam, c=cList, rw=rwList, lw=lwList, d=dList, npos=NumbersPerPositionAsList)
toolbox.register("population", tools.initRepeat, list, toolbox.genteam)
toolbox.register("evaluate", evalTeamFitness, BT=BenchmarkTeam, stats=StatsToMaximize, p=playersDic, time=TimeFrame)
toolbox.register("mate", tools.cxTwoPoint)
toolbox.register("mutate", mutateTeam, indpb=0.05, c=cList, rw=rwList, lw=lwList, d=dList, npos=NumbersPerPositionAsList)
#toolbox.register("select", tools.selNSGA2)
toolbox.register("select", tools.selTournament, tournsize=10)
toolbox.decorate("mate", checkCrossover(c=cList, rw=rwList, lw=lwList, d=dList, npos=NumbersPerPositionAsList))
random.seed()
pop = toolbox.population(n=Population)
hof = tools.HallOfFame(1)
algorithms.eaSimple(pop, toolbox, cxpb=0.5, mutpb=0.2, ngen=Generations, halloffame=hof, verbose=True)
return( hof[0] , hof[0].fitness.values )
import random
import numpy
from deap import algorithms
from deap import base
from deap import creator
from deap import tools
import team
playersDic = team.readPickle('players')
teamsToInclude=[0,6]
rwList = team.makePositionList('RW',playersDic,teamsToInclude)
lwList = team.makePositionList('LW',playersDic,teamsToInclude)
cList = team.makePositionList('C',playersDic,teamsToInclude)
dList = team.makePositionList('D',playersDic,teamsToInclude)
statsToMaximize = [14,16,1,2,31,32]
#Define Player and Player's Fitness
creator.create("FitnessMax", base.Fitness, weights=tuple([1.0]*len(statsToMaximize)) )
creator.create("Team", list, fitness=creator.FitnessMax)
#Register Player Operations
def generateTeam(c,rw,lw,d):
return creator.Team(team.makeRandomTeam(c,rw,lw,d))
def evalTeamFitness(individual):
listOfPlayerStatsForIndividual = [[playersDic[player]['stats_lastmonth'][statid] for statid in statsToMaximize]for player in individual]
combinedStatsForIndividual = tuple([sum(totalstats) for totalstats in zip(*listOfPlayerStatsForIndividual)])
return combinedStatsForIndividual
toolbox = base.Toolbox()
toolbox.register("genteam", generateTeam, c=cList, rw=rwList, lw=lwList, d=dList)
import genetic
import team
#non-goalie stat categories
ng=[ 1,2,4,5,6,7,9,10,12,14,16,31,32]
MYTEAMID=6
players = team.readPickle('players')
myteam = team.readPickle('teams')[MYTEAMID]
#get only first 24 players
mystarters = myteam['team_roster'][:24]
#interesting stats in order of descending importance
st = [1,2,4,14,5,31,32]
def test(stat,time):
mystats = team.calcTeamStats(mystarters, stat, players, time)
head = team.statidHeader(stat)
t1,f1=genetic.run(mystarters,TeamsToInclude=[0,MYTEAMID],StatsToMaximize=stat,
TimeFrame=time, Population=1000, Generations=60)
print('\n\n\n\n\n\n\n')
[print(head[i],mystats[i]) for i in range(len(head))]
print()
gastats = team.calcTeamStats(t1, stat, players, time)
[print(head[i],gastats[i]) for i in range(len(head))]
m = set(mystarters)
