def getCurrentMatch(summonerName, region="NA"):
riotapi.set_region(region)
summoner = riotapi.get_summoner_by_name(summonerName)
match = riotapi.get_current_game(summoner)
if match is None:
return None
roleMap = allRoles(match)
# for x in roleMap:
# print x.champion.name, x.side.name, roleMap[x]
if len(roleMap.keys()) < 10:
print "Role confusion!"
return None
statMap = {}
rankMap = {}
nonNormMap = {}
for p in match.participants:
role = roleMap[p]
stats, nonNorm, rank = avgPerformance.getAvgPerformance(p, role)
if stats is None:
#currently filling with avg gold?
stats = getAvg()
rank = "unranked"
statMap[p.side.name+role] = list(stats)
rankMap[p] = rank
nonNormMap[p] = nonNorm
print p.summoner_name, p.side.name+role
statVector = (statMap['blueTop']+statMap['blueMid']+statMap['blueJung']+
statMap['blueSup']+statMap['blueADC']+statMap['redTop']+
statMap['redMid']+statMap['redJung']+statMap['redSup']+
statMap['redADC'])
model = fetchModel(match)
results = model.predict_proba(statVector)
return format.prepareReturn(roleMap, rankMap, nonNormMap, results, match)
def getCurrentMatch(summonerName, region="NA"):
riotapi.set_region(region)
try:
summoner = riotapi.get_summoner_by_name(summonerName)
match = riotapi.get_current_game(summoner)
except APIError as e:
print e
return None
if match is None:
return None
if match.mode.name != "classic":
print "Not classic"
return None
roleMap = allRoles(match)
if len(roleMap.keys()) < 10:
roleMap = assignRandom(match)
print "Role confusion!"
statMap = {}
rankMap = {}
nonNormMap = {}
for p in match.participants:
role = roleMap[p]
try:
stats, nonNorm, rank = avgPerformance.getAvgPerformance(p, role)
except:
stats = getAvg(p.side.name+role)
rank = "unranked"
nonNorm = [0, 0, 0, 0, 0, 0]
statMap[p.side.name+role] = list(stats)
rankMap[p] = rank
nonNormMap[p] = nonNorm
print p.summoner_name, p.side.name+role
statVector = (statMap['blueTop']+statMap['blueMid']+statMap['blueJung']+
statMap['blueSup']+statMap['blueADC']+statMap['redTop']+
statMap['redMid']+statMap['redJung']+statMap['redSup']+
statMap['redADC'])
model = fetchModel(match, rankMap)
results = model.predict_proba(statVector)
return format.prepareReturn(roleMap, rankMap, nonNormMap, results, match)
blueGuess = 0.0
redGuess = 0.0
model = pickle.load(open('model'))['gold']
random.shuffle(matchList)
for i in range(len(matchList)):
try:
testMatch = matchList[i].match(include_timeline=True)
except:
continue
matchClass = parseMatch.getWinner(testMatch)
roleMap = parseMatch.getRoles(testMatch)
inv_map = {v: k for k, v in roleMap.items()}
statMap = {}
for p in testMatch:
try:
stats, webStats, rank = avgPerformance.getAvgPerformance(p)
except:
stats = getAvg(inv_map[p.id])
print len(stats)
statMap[p.id] = list(stats)
print p.summoner_name
try:
statVector = (statMap[roleMap['blueTop']]+statMap[roleMap['blueMid']]+statMap[roleMap['blueJung']]+
statMap[roleMap['blueSup']]+statMap[roleMap['blueADC']]+statMap[roleMap['redTop']]+
statMap[roleMap['redMid']]+statMap[roleMap['redJung']]+statMap[roleMap['redSup']]+
statMap[roleMap['redADC']])
except KeyError as c:
print c
continue
results = model.predict(statVector)
guessClass = results #for SVM
