# new_dict = dict(zip(m.values(), m.keys()))
# sorted_arr = sorted(new_dict.keys())
# for n in reversed(sorted_arr):
# print names[new_dict[n]] + " " + str(n)
mad = open("madresults.txt", "r")
curseason = "0"
curInd = -1
correct = 0
wrong = 0
correctAvg = 0.0
overCorrect = 0
wrongAvg = 0.0
lowestWrong = 0.0
curSe = seasons[0]
s = pr.rank(curSe)
winsPredict = dict()
countPredict = dict()
count = 0
rest = 0
restWins = 0
for res in mad:
gam = res.split("\t")
if curseason is not gam[0]:
curseason = gam[0]
curInd += 1
curSe = seasons[curInd]
s = pr.rank(curSe)
overCorrect += correct
# if curInd is not 0:
# print 'The average for wins in season ' + str(curInd + 1995) + ' is ' + str(correctAvg/correct) + ' with ' + str(correct) + ' correct. Wrong is ' + str(wrongAvg/wrong) + ' with ' + str(wrong) + ' wrong and a low of ' + str(lowestWrong) + '. correct percentage is ' + str(float(correct)/(correct + wrong))
from copy import deepcopy
names = dict()
e = open('teamname.txt', 'r')
for name in e:
sp = name.split('\t')
names[sp[0]] = sp[1][0:len(sp[1])-1]
f = open('2014se.txt', 'r')
seasons = []
seas = dict() #team, score
for line in f:
gam = line.split('\t')
if gam[2] in seas:
team1 = seas[gam[2]]
else:
team1 = Team(names[gam[2]])
if gam[4] in seas:
team2 = seas[gam[4]]
else:
team2 = Team(names[gam[4]])
team1.addGame(Game(gam[4], gam[3], gam[5]))
team2.addGame(Game(gam[2], gam[5], gam[3]))
seas[gam[2]] = deepcopy(team1)
seas[gam[4]] = deepcopy(team2)
seasons.append(deepcopy(seas))
j = seas
pr = PageRank()
m = pr.rank(j)
for team in j.keys():
print names[team] + '\t' + str(m[team]*169.6 + j[team].getScores()[0]*0.0701)
