def _distance(self, targetevent, events):
'''
Find similar games(events) with naive distance
todo: normalize to similar length
return Game object with optimal game
'''
SCORE_INIT = 99999
#Global scores
bestscore = SCORE_INIT
bestscore2 = SCORE_INIT
game = Game('', '')
for event in events:
localresult1 = 0
localresult2 = 0
for targ in targetevent.data:
tmin, tdescription = targ[0], targ[1]
preres = list(map(lambda x: -1 if x[1] != tdescription else (abs(tmin - x[0])), event.data))
res = abs(sum(preres))
minuscount = len(list(filter(lambda x: x == -1, preres)))
localresult1 += minuscount
localresult2 += res
if localresult1 < bestscore and localresult2 < bestscore2:
bestscore = localresult1
bestscore2 = localresult2
game = event
return game
def _chooseDefenceCenter(self, team, opteam, num):
""" Get optimal Defender to center """
players = list(getPlayersFromTeamByPos(self.teamdata, team, 'D(C)'))
params = ['TotalTackles', 'AerialWon', 'Rating','OffsidesWon','GameStarted',\
'ShotsBlocked', LASTNAME]
tomaxvalues = self._getParamValues(players, params)
tominvalues = self._getParamValues(
players, ['AerialLost', 'Dispossesed', 'Yellow', LASTNAME])
if len(tomaxvalues) > 1:
maxv = self._optimalPlayers(np.array(tomaxvalues), np.argmax, num,
players)
else:
maxv = tomaxvalues[0][-1:]
if len(tominvalues) > 1:
minv = self._optimalPlayers(np.array(tominvalues), np.argmin, num,
players)
else:
minv = tominvalues[0][-1:]
#if same players both in maxv and minv append in result list
data = list(set(maxv).intersection(set(minv)))
if len(data) < num:
return data + list(
map(
lambda x: x[LASTNAME],
self._getFromAnotherPos(team, 'D(C)', num - len(data),
data)))
#self._opteamOptimal(self.fwparams, opteam, players)
size = len(data)
if size == 2: return data
else: return data + list(filter(lambda x: x not in data, maxv))
def mostFreqEvents(self, startmin, endmin, *args, **kwargs):
""" Get Most frequent events from startmin until endmin
sample - Get sample from n games
"""
if( isinstance(startmin, int) != True or isinstance(endmin, int) != True):
raise LiveGameAnalysisException("Time need to be in int format")
if(startmin > endmin):
raise LiveGameAnalysisException("Starttime can't be greather then endtime")
sample = kwargs.get('sample')
if sample != None:
return self._sampleCase(startmin, endmin, self.data, sample)
preresult = []
sampledata = kwargs.get('data')
data = self.data if sampledata == None else sampledata
for game in data:
if len(data[game]) > 0:
filtering = list(
map(lambda x: x[1],
filter(lambda x: x[0] >= startmin and x[0] <= endmin,\
self.data[game][0])))
preresult += filtering
if len(preresult) > 0:
limit = kwargs.get('limit',0)
count = Counter(preresult)
lim = len(preresult) if limit == 0 else limit
return count.most_common()[0:lim]
def _distance(self, targetevent, events):
'''
Find similar games(events) with naive distance
todo: normalize to similar length
return Game object with optimal game
'''
SCORE_INIT = 99999
#Global scores
bestscore = SCORE_INIT
bestscore2 = SCORE_INIT
game = Game('', '')
for event in events:
localresult1 = 0
localresult2 = 0
for targ in targetevent.data:
tmin, tdescription = targ[0], targ[1]
preres = list(
map(
lambda x: -1 if x[1] != tdescription else
(abs(tmin - x[0])), event.data))
res = abs(sum(preres))
minuscount = len(list(filter(lambda x: x == -1, preres)))
localresult1 += minuscount
localresult2 += res
if localresult1 < bestscore and localresult2 < bestscore2:
bestscore = localresult1
bestscore2 = localresult2
game = event
return game
def mostFreqEvents(self, startmin, endmin, *args, **kwargs):
""" Get Most frequent events from startmin until endmin
sample - Get sample from n games
"""
if (isinstance(startmin, int) != True
or isinstance(endmin, int) != True):
raise LiveGameAnalysisException("Time need to be in int format")
if (startmin > endmin):
raise LiveGameAnalysisException(
"Starttime can't be greather then endtime")
sample = kwargs.get('sample')
if sample != None:
return self._sampleCase(startmin, endmin, self.data, sample)
preresult = []
sampledata = kwargs.get('data')
data = self.data if sampledata == None else sampledata
for game in data:
if len(data[game]) > 0:
filtering = list(
map(lambda x: x[1],
filter(lambda x: x[0] >= startmin and x[0] <= endmin,\
self.data[game][0])))
preresult += filtering
if len(preresult) > 0:
limit = kwargs.get('limit', 0)
count = Counter(preresult)
lim = len(preresult) if limit == 0 else limit
return count.most_common()[0:lim]
def initial_simplex(self):
cfg0 = self.initial_simplex_seed()
simplex = [cfg0]
params = self.manipulator.parameters(cfg0)
params = list(filter(lambda x: x.is_primitive(), params))
if len(params) == 0:
return simplex
q = (((math.sqrt(len(params) + 1.0) - 1.0) / (len(params) * math.sqrt(2.0)))
* self.initial_unit_edge_length)
p = q + ((1.0 / math.sqrt(2.0)) * self.initial_unit_edge_length)
base = [x.get_unit_value(cfg0) for x in params]
for j in xrange(len(base)):
if max(p, q) + base[j] > 1.0:
#flip this dimension as we would overflow our [0,1] bounds
base[j] *= -1.0
for i in xrange(len(params)):
simplex.append(self.manipulator.copy(cfg0))
params[i].set_unit_value(simplex[-1], abs(base[i] + p))
for j in xrange(i + 1, len(params)):
params[j].set_unit_value(simplex[-1], abs(base[i] + q))
return simplex
def _chooseDefenceCenter(self, team, opteam, num): """ Get optimal Defender to center """ players = list(getPlayersFromTeamByPos(self.teamdata, team, 'D(C)')) params = ['TotalTackles', 'AerialWon', 'Rating','OffsidesWon','GameStarted',\ 'ShotsBlocked', LASTNAME] tomaxvalues = self._getParamValues(players, params) tominvalues = self._getParamValues(players,['AerialLost','Dispossesed','Yellow', LASTNAME]) if len(tomaxvalues) > 1: maxv = self._optimalPlayers(np.array(tomaxvalues), np.argmax, num, players) else: maxv = tomaxvalues[0][-1:] if len(tominvalues) > 1: minv = self._optimalPlayers(np.array(tominvalues), np.argmin, num, players) else: minv = tominvalues[0][-1:] #if same players both in maxv and minv append in result list data = list(set(maxv).intersection(set(minv))) if len(data) < num: return data + list(map(lambda x: x[LASTNAME], self._getFromAnotherPos(team, 'D(C)', num-len(data), data))) #self._opteamOptimal(self.fwparams, opteam, players) size = len(data) if size == 2: return data else: return data + list(filter(lambda x: x not in data, maxv))
def query(self, value, *args, **kwargs):
if value == None:
raise Exception("This query is empty")
if self.calculation != None:
matches = self.calculation.get()
if isinstance(matches, MatchesData):
afunc = lambda results: list(filter(lambda game: value(len(game)), \
results))
result = self._asyncCall(afunc, params=matches.result)
return result
if isinstance(matches, PlayerData):
afunc = lambda results, val: list(filter(lambda x: val(x[0]), \
results))
return afunc(matches.data, value)
#return self._asyncCall(afunc, params=(matches.data,value, )).get()
else:
print("WHEN CALCULATION IS ZERO", self.preresult)
def query(self, value,*args,**kwargs):
if value == None:
raise Exception("This query is empty")
if self.calculation != None:
matches = self.calculation.get()
if isinstance(matches, MatchesData):
afunc = lambda results: list(filter(lambda game: value(len(game)), \
results))
result = self._asyncCall(afunc, params=matches.result)
return result
if isinstance(matches, PlayerData):
afunc = lambda results, val: list(filter(lambda x: val(x[0]), \
results))
return afunc(matches.data, value)
#return self._asyncCall(afunc, params=(matches.data,value, )).get()
else:
print("WHEN CALCULATION IS ZERO", self.preresult)
def _opteamOptimal(self, params, opteam, teamdata):
'''
Best players from opposite team
'''
gs = 'GameStarted'
opplayers = list(filter(lambda x:x[gs] > 0, \
getPlayersFromTeamByPos(self.teamdata, opteam, 'FW')))
#values = list(filter(lambda x: x[-1:][0] > 0, self._getParamValues(opplayers, params)))
for v in params.keys():
#print(opplayers)
for player in teamdata:
#preresult5 = list(F() << (_/player[gs]) << (filter, _ > 0))
preresult = list(
map(_/player[gs],
filter(_ > 0, \
map(lambda x: player[x], params[v]))
))
print(preresult)
def _opteamOptimal(self, params, opteam, teamdata): ''' Best players from opposite team ''' gs = 'GameStarted' opplayers = list(filter(lambda x:x[gs] > 0, \ getPlayersFromTeamByPos(self.teamdata, opteam, 'FW'))) #values = list(filter(lambda x: x[-1:][0] > 0, self._getParamValues(opplayers, params))) for v in params.keys(): #print(opplayers) for player in teamdata: #preresult5 = list(F() << (_/player[gs]) << (filter, _ > 0)) preresult = list( map(_/player[gs], filter(_ > 0, \ map(lambda x: player[x], params[v])) )) print(preresult)
def event(self, query): if query in self._playerParams: teams = list(self.data.teams.keys()) for team in teams: info = self.data.teams[team] result = list(filter(lambda x: x[LASTNAME] == self.target, info)) if len(result) > 0: return result[0][query] return None
def event(self, query):
if query in self._playerParams:
teams = list(self.data.teams.keys())
for team in teams:
info = self.data.teams[team]
result = list(
filter(lambda x: x[LASTNAME] == self.target, info))
if len(result) > 0:
return result[0][query]
return None
def _countTargetEventHelp(self, event, startmin, endmin): for name in self.data: evt = self.data[name] if len(evt) > 0: if endmin == 0 and startmin != 0: #Not tested! count_events = len(list(lambda x: x[1] == event and \ x[0] <= startmin, evt[0])) count_events = len(list(filter(lambda x: x[1] == event, evt[0]))) yield(evt[1], count_events)
def getPlayersByParams(teamdatas, params):
'''
List of params for all players from all teams
'''
teams = list(teamdatas.keys())
allparams = list(teamdatas[teams[0]][0].keys())
for team in teams:
for player in teamdatas[team]:
yield (list(map(lambda y: player[y], \
list(filter(lambda x: x in params, allparams)))))
def getPlayersByParams(teamdatas, params): ''' List of params for all players from all teams ''' teams = list(teamdatas.keys()) allparams = list(teamdatas[teams[0]][0].keys()) for team in teams: for player in teamdatas[team]: yield (list(map(lambda y: player[y], \ list(filter(lambda x: x in params, allparams)))))
def _countTargetEventHelp(self, event, startmin, endmin):
for name in self.data:
evt = self.data[name]
if len(evt) > 0:
if endmin == 0 and startmin != 0:
#Not tested!
count_events = len(list(lambda x: x[1] == event and \
x[0] <= startmin, evt[0]))
count_events = len(
list(filter(lambda x: x[1] == event, evt[0])))
yield (evt[1], count_events)
def _sampleCase(self, startmin, endmin, data, size): """ Return random sample with size in data with """ sto = list(map(lambda x: data[x], data)) sampledata = np.random.choice(sto,size) result = [] for game in sampledata: if len(game) > 0: result += list( map(lambda x: x[1], filter(lambda x: x[0] >= startmin and x[0] <= endmin,\ game[0]))) return Counter(result).most_common()
def initial_simplex(self):
cfg0 = self.initial_simplex_seed()
simplex = [cfg0]
params = self.manipulator.parameters(cfg0)
params = filter(lambda x: x.is_primitive(), params)
for p in params:
simplex.append(self.manipulator.copy(cfg0))
v = p.get_unit_value(simplex[-1])
if v <= 0.5:
v += self.initial_unit_edge_length
else:
v -= self.initial_unit_edge_length
p.set_unit_value(simplex[-1], v)
return simplex
def optimalInner(matr, func, num, players, res=set()): c = Counter(func(matr, axis=0)).most_common(num) result = set(map(lambda x: players[x[0]][LASTNAME], c)) if len(result) == num: res |= result return False, list(res) idxs = list(filter(lambda x: players[x][LASTNAME] in result, \ range(len(players)))) temp = matr.tolist() for i in idxs: del players[i] del temp[i] res |= result return True, (np.array(temp), func, num-len(result), players, res)
def _sampleCase(self, startmin, endmin, data, size):
""" Return random sample with size in data
with
"""
sto = list(map(lambda x: data[x], data))
sampledata = np.random.choice(sto, size)
result = []
for game in sampledata:
if len(game) > 0:
result += list(
map(lambda x: x[1],
filter(lambda x: x[0] >= startmin and x[0] <= endmin,\
game[0])))
return Counter(result).most_common()
def _add_cheapest_travelcard(self, destination: Station, origin: Station, season_ticket: Optional[SeasonTicket]) -> JourneyCosts:
possible_travelcards = self._get_possible_travelcards(destination, origin)
filter_null_results = filter(lambda tc: tc is not None)
cheapest: Pipe[Travelcard] = Pipe(possible_travelcards) >> \
filter_null_results >> \
sort(lambda tc: tc.annual_price) >> \
first
if cheapest.value is None:
raise JourneyCostError("No travelcard found for {} to {}".format(origin.name, destination.name))
return JourneyCosts(season_ticket, cheapest.value)
def optimalInner(matr, func, num, players, res=set()):
c = Counter(func(matr, axis=0)).most_common(num)
result = set(map(lambda x: players[x[0]][LASTNAME], c))
if len(result) == num:
res |= result
return False, list(res)
idxs = list(filter(lambda x: players[x][LASTNAME] in result, \
range(len(players))))
temp = matr.tolist()
for i in idxs:
del players[i]
del temp[i]
res |= result
return True, (np.array(temp), func, num - len(result), players,
res)
def _getFromAnotherPos(self, team, pos, num, stored):
"""
'plan b', get players from another positions
in case when no players in the target pos.
arguments:
team - target team
pos - current pos
num - number of players needed
stored - already chosen players
return: list of players(raw)
TODO: set ranking
"""
anotherpos = pos[0:pos.find('(')]
return list(filter(lambda x: anotherpos in x['PositionShort'] and\
x[LASTNAME] not in stored
, self.teamdata[team]))[0:num]
def _getFromAnotherPos(self, team, pos, num, stored):
"""
'plan b', get players from another positions
in case when no players in the target pos.
arguments:
team - target team
pos - current pos
num - number of players needed
stored - already chosen players
return: list of players(raw)
TODO: set ranking
"""
anotherpos = pos[0:pos.find('(')]
return list(filter(lambda x: anotherpos in x['PositionShort'] and\
x[LASTNAME] not in stored
, self.teamdata[team]))[0:num]
def runPlayer(self):
self.ifParamsNotEmpty()
findlastname = lambda name: list(filter(lambda x: name in x, self.preresult))
result = []
dictresult =[]
value = self.value
for team in self.useddata.keys():
for player in self.useddata[team]:
target = findlastname(player[LASTNAME])
if len(target) > 0:
res = list(target[0])
if value in player:
dictdata = {}
dictdata[value] = player[value]
dictdata['lastname'] = player[LASTNAME]
res.append(player[value])
result.append(res)
dictresult.append(dictdata)
return result
def runPlayer(self):
self.ifParamsNotEmpty()
findlastname = lambda name: list(
filter(lambda x: name in x, self.preresult))
result = []
dictresult = []
value = self.value
for team in self.useddata.keys():
for player in self.useddata[team]:
target = findlastname(player[LASTNAME])
if len(target) > 0:
res = list(target[0])
if value in player:
dictdata = {}
dictdata[value] = player[value]
dictdata['lastname'] = player[LASTNAME]
res.append(player[value])
result.append(res)
dictresult.append(dictdata)
return result
def getGames(self, name):
""" Get games where contains 'name' (as team)"""
teams = self.games.keys()
return list(
map(lambda m: self.games[m],
filter(lambda x: name in x.split(), teams)))
def _getBetweenMinutes(self, game, startmin, endmin):
""" Get game between startmin and endmin """
data, info = game
return Game(list(reversed(list(filter(lambda x: x[0] >= startmin and \
x[0] <= endmin, data)))), info)
def getPlayer(teamdata, lastname): """ teamdata - dict with all teams Return target player from team by last name """ return list(filter(lambda x: x[LASTNAME] == lastname, teamdata))[0]
def extractInfo(self, data, targteam):
result = list(filter(lambda x: x[2].find(targteam) != -1, data))
rating = self._getRating(result)
minuts = list(self._getGamesUntilMinute(25))
def _innerFilter(self, func, elements): """ Filtering elements from datastore(self.data) or from already prepared (data) """ return list(filter(func, elements))
def extractInfo(self, data, targteam): result = list(filter(lambda x: x[2].find(targteam) != -1, data)) rating = self._getRating(result) minuts = list(self._getGamesUntilMinute(25))
def _filterUsed(self, players, stored):
""" Reject players wich alread in stored """
return list(filter(lambda x: x[LASTNAME] not in stored, players))
def getGames(self, name): """ Get games where contains 'name' (as team)""" teams = self.games.keys() return list(map(lambda m: self.games[m], filter(lambda x: name in x.split(), teams)))
def _filterUsed(self, players, stored): """ Reject players wich alread in stored """ return list(filter(lambda x: x[LASTNAME] not in stored, players))
def getPlayersFromTeamByPos(teamsdata, team, pos): """ Return all players in target pos. For example all forwards from team """ return list(filter(lambda x: x['positionshort'] == pos, teamsdata[team]))
def cfg_to_str(self, cfg):
params = list(filter(Parameter.is_primitive,
self.manipulator.parameters(cfg)))
params.sort(key=_.name)
return str(tuple([x.get_unit_value(cfg) for x in params]))
def _innerFilter(self, func, elements):
"""
Filtering elements from datastore(self.data) or from already prepared (data)
"""
return list(filter(func, elements))
def inner(self):
return head(filter(bool, map(fn, self.comments.all())))
def _getBetweenMinutes(self, game, startmin, endmin): """ Get game between startmin and endmin """ data, info = game return Game(list(reversed(list(filter(lambda x: x[0] >= startmin and \ x[0] <= endmin, data)))), info)
def test_filter_withList(self):
out = list(iters.filter(_ < 10, [1, 2, 11]))
self.assertEqual([1, 2], out)
self.assertEqual(list, type(out))
def getPlayersFromTeamByPos(teamsdata, team, pos):
""" Return all players in target pos.
For example all forwards from team """
return list(filter(lambda x: x['positionshort'] == pos, teamsdata[team]))
def test_filter_withTuple(self):
out = tuple(iters.filter(_ < 10, (1, 2, 11)))
self.assertEqual((1, 2), out)
self.assertEqual(tuple, type(out))
def cfg_to_str(self, cfg):
params = list(filter(Parameter.is_primitive,
self.manipulator.parameters(cfg)))
params.sort(key=_.name)
return str(tuple(map(lambda x: x.get_unit_value(cfg), params)))
def getPlayer(teamdata, lastname):
"""
teamdata - dict with all teams
Return target player from team by last name """
return list(filter(lambda x: x[LASTNAME] == lastname, teamdata))[0]