def third_main():
#np.set_printoptions(threshold=np.inf)
api = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2')
api_euw = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2',
Consts.REGIONS['europe_west'])
api_eune = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2',
Consts.REGIONS['europe_nordic_and_east'])
api_kr = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2',
Consts.REGIONS['korea'])
#loading the NA match ids
#data = json.loads(open('./BILGEWATER/EUW.json').read())
#data += json.loads(open('./BILGEWATER/EUW.json').read())
data = json.loads(open('./BILGEWATER/NA.json').read())
pop_spells = make_spells_dict()
match_num = 1
for matchid in data:
if match_num > 700:
break
print("On match number " + str(match_num))
#if match_num <= 10000:
#print(matchid)
#match = api_euw.get_match_info(matchid, {'includeTimeline': True})
#else:
match = api.get_match_info(matchid, {'includeTimeline': True})
if match is False or match['matchDuration'] < 1000:
print("Broken Match")
continue
for champ in match['participants']:
#get champ id and name
championID = champ['championId']
champ_name = champion_cache.find(championID)
if champ_name is False:
champ_name = api.get_champ_by_id(championID)['key']
champion_cache.place(championID, champ_name)
#combination so it does not matter which order summoner spells are chosen
spell1id = champ['spell2Id'] + champ['spell1Id']
spell2id = champ['spell1Id'] * champ['spell2Id']
if champ['spell2Id'] in pop_spells[champ_name]:
pop_spells[champ_name][champ['spell2Id']] += 1
else:
pop_spells[champ_name][champ['spell2Id']] = 1
if champ['spell1Id'] in pop_spells[champ_name]:
pop_spells[champ_name][champ['spell1Id']] += 1
else:
pop_spells[champ_name][champ['spell1Id']] = 1
#print(pop_spells)
#add to team list
match_num += 1
with open('spell_dict.json', 'w') as fp:
json.dump(pop_spells, fp)
def third_main():
#np.set_printoptions(threshold=np.inf)
api = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2')
api_euw = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2', Consts.REGIONS['europe_west'])
api_eune = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2', Consts.REGIONS['europe_nordic_and_east'])
api_kr = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2', Consts.REGIONS['korea'])
#loading the NA match ids
#data = json.loads(open('./BILGEWATER/EUW.json').read())
#data += json.loads(open('./BILGEWATER/EUW.json').read())
data = json.loads(open('./BILGEWATER/NA.json').read())
pop_spells = make_spells_dict()
match_num = 1
for matchid in data:
if match_num > 700:
break
print("On match number " + str(match_num))
#if match_num <= 10000:
#print(matchid)
#match = api_euw.get_match_info(matchid, {'includeTimeline': True})
#else:
match = api.get_match_info(matchid, {'includeTimeline': True})
if match is False or match['matchDuration'] < 1000:
print("Broken Match")
continue
for champ in match['participants']:
#get champ id and name
championID = champ['championId']
champ_name = champion_cache.find(championID)
if champ_name is False:
champ_name = api.get_champ_by_id(championID)['key']
champion_cache.place(championID, champ_name)
#combination so it does not matter which order summoner spells are chosen
spell1id = champ['spell2Id'] + champ['spell1Id']
spell2id = champ['spell1Id'] * champ['spell2Id']
if champ['spell2Id'] in pop_spells[champ_name]:
pop_spells[champ_name][champ['spell2Id']] += 1
else:
pop_spells[champ_name][champ['spell2Id']] = 1
if champ['spell1Id'] in pop_spells[champ_name]:
pop_spells[champ_name][champ['spell1Id']] += 1
else:
pop_spells[champ_name][champ['spell1Id']] = 1
#print(pop_spells)
#add to team list
match_num+=1
with open('spell_dict.json', 'w') as fp:
json.dump(pop_spells, fp)
def main():
#np.set_printoptions(threshold=np.inf)
api = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2')
api_euw = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2', Consts.REGIONS['europe_west'])
api_eune = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2', Consts.REGIONS['europe_nordic_and_east'])
api_kr = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2', Consts.REGIONS['korea'])
#loading the NA match ids
data = json.loads(open('./BILGEWATER/EUW.json').read())
#data += json.loads(open('./BILGEWATER/EUNE.json').read())
#data += json.loads(open('./BILGEWATER/KR.json').read())
data += json.loads(open('./BILGEWATER/NA.json').read())
csv_data = np.zeros(shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
pop_items = make_items_dict()
pop_spells = make_spells_dict()
team_comps = {}
data_col_base = len(Consts.STAT_TO_MATRIX)
_fill_champ_id_range(csv_data, data_col_base)
match_num = 1
for matchid in data:
print("On match number " + str(match_num))
if match_num <= 10000:
#print(matchid)
match = api_euw.get_match_info(matchid, {'includeTimeline': True})
else:
match = api.get_match_info(matchid, {'includeTimeline': True})
win_team = []
lose_team = []
if match is False or match['matchDuration'] < 1000:
print("Broken Match")
continue
for champ in match['participants']:
#get champ id and name
championID = champ['championId']
champ_name = champion_cache.find(championID)
if champ_name is False:
champ_name = api.get_champ_by_id(championID)['key']
champion_cache.place(championID, champ_name)
chmp_mtrx_index = CHAMP_TO_MATRIX[champ_name]
#these methods return values which must then be input into the matrix
offense, defense, utility = _parse_masteries(champ.get('masteries', []))
kills, deaths, assists, phys_dmg, mgc_dmg, true_dmg, dmg_taken, team_jgl, enemy_jgl, win = _parse_stats(champ['stats'], championID)
cs_min, gold_min = _parse_timeline(champ['timeline'])
#combination so it does not matter which order summoner spells are chosen
spell1id = champ['spell2Id'] + champ['spell1Id']
spell2id = champ['spell1Id'] * champ['spell2Id']
if champ['spell2Id'] in pop_spells[champ_name]:
pop_spells[champ_name][champ['spell2Id']] += 1
else:
pop_spells[champ_name][champ['spell2Id']] = 1
if champ['spell1Id'] in pop_spells[champ_name]:
pop_spells[champ_name][champ['spell1Id']] += 1
else:
pop_spells[champ_name][champ['spell1Id']] = 1
#print(pop_spells)
#place data into matrix
#attack range not changed because data is normalized anyway
csv_data_delta = np.array([offense, defense, utility, kills, deaths, assists, phys_dmg, mgc_dmg, true_dmg, dmg_taken, team_jgl, enemy_jgl,
0, cs_min, gold_min, spell1id, spell2id, win])
csv_data[chmp_mtrx_index, data_col_base + 1:data_col_base + len(Consts.VARIABLE_TO_MATRIX) + 1] += csv_data_delta
#these methods input data directly into matrix
csv_data = _parse_runes(champ.get('runes', []), csv_data, chmp_mtrx_index)
csv_data = _parse_items(champ['stats'], csv_data, chmp_mtrx_index, pop_items, True)
#add 1 to champion counter
csv_data[chmp_mtrx_index, Consts.BLACK_MARKET_FEATURES-1]+=1
#add to team list
if win == 1:
win_team.append(champ_name)
else:
lose_team.append(champ_name)
if SHOW_MATRIX:
print(csv_data)
win_team = tuple(sorted(win_team))
#print(win_team)
lose_team = tuple(sorted(lose_team))
#print(lose_team)
team_comps = add_to_team_comps(win_team, lose_team, team_comps)
#print(team_comps)
match_num+=1
np.savetxt('data.csv', csv_data, delimiter= ",", comments = "")
with open('item_dict.json', 'w') as fp:
json.dump(pop_items, fp)
with open('team_dict.json', 'w') as fp:
json.dump(team_comps, fp)
with open('spell_dict.json', 'w') as fp:
json.dump(pop_spells, fp)
def second_main():
#np.set_printoptions(threshold=np.inf)
api = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2')
api_euw = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2', Consts.REGIONS['europe_west'])
api_eune = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2', Consts.REGIONS['europe_nordic_and_east'])
api_kr = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2', Consts.REGIONS['korea'])
#loading the NA match ids
data = json.loads(open('./BILGEWATER/EUW.json').read())
data += json.loads(open('./BILGEWATER/KR.json').read())
data += json.loads(open('./BILGEWATER/NA.json').read())
data_col_base = len(Consts.STAT_TO_MATRIX)
#initialize different arrays
marksman_data = np.zeros(shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
support_data = np.zeros(shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
mage_data = np.zeros(shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
tank_data = np.zeros(shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
phys_data = np.zeros(shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
mgc_data = np.zeros(shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
jgler_data = np.zeros(shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
ass_data = np.zeros(shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
data_list = {'Magical Bruiser': mgc_data, 'Assassin': ass_data, 'Jungler': jgler_data, 'Marksman': marksman_data, 'Support': support_data, 'Mage': mage_data, 'Tank': tank_data, 'Physical Bruiser': phys_data}
for role in data_list:
_fill_champ_id_range(data_list[role], data_col_base)
#initialize k-cluster
kmean, scaler = KLearn.get_k_learn()
match_num = 1
for matchid in data:
print("On match number " + str(match_num))
if match_num <= 10000:
#print(matchid)
match = api_euw.get_match_info(matchid, {'includeTimeline': True})
elif match_num <= 20000:
match = api_kr.get_match_info(matchhid, {'includeTimeline': True})
else:
match = api.get_match_info(matchhid, {'includeTimeline': True})
if match['matchDuration'] < 1000:
print("Broken Match")
continue
for champ in match['participants']:
champ_data = np.zeros(shape=[1, Consts.BLACK_MARKET_FEATURES])
#get champ id and name
championID = champ['championId']
champ_name = champion_cache.find(championID)
if champ_name is False:
champ_name = api.get_champ_by_id(championID)['key']
champion_cache.place(championID, champ_name)
chmp_mtrx_index = CHAMP_TO_MATRIX[champ_name]
#these methods return values which must then be input into the matrix
offense, defense, utility = _parse_masteries(champ.get('masteries', []))
kills, deaths, assists, phys_dmg, mgc_dmg, true_dmg, dmg_taken, team_jgl, enemy_jgl, win = _parse_stats(champ['stats'], championID)
cs_min, gold_min = _parse_timeline(champ['timeline'])
#combination so it does not matter which order summoner spells are chosen
spell1id = champ['spell2Id'] + champ['spell1Id']
spell2id = champ['spell1Id'] * champ['spell2Id']
#place data into matrix
#attack range not changed because data is normalized anyway
data_delta = np.array([offense, defense, utility, kills, deaths, assists, phys_dmg, mgc_dmg, true_dmg, dmg_taken, team_jgl, enemy_jgl,
0, cs_min, gold_min, spell1id, spell2id, win])
champ_data[0, data_col_base + 1:data_col_base + len(Consts.VARIABLE_TO_MATRIX) + 1] += data_delta
#these methods input data directly into matrix
champ_data = _parse_runes(champ.get('runes', []), champ_data, 0)
champ_data = _parse_items(champ['stats'], champ_data, 0, {}, False)
#add 1 to champion counter
champ_data[0, Consts.BLACK_MARKET_FEATURES-1]+=1
cluster_num = find_cluster(kmean, scaler, champ_data)
data_list[KLearn.roles[cluster_num]][chmp_mtrx_index] += champ_data.flatten()
match_num+=1
for role in data_list:
np.savetxt('role_data' + role + '.csv', data_list[role], delimiter= ",", comments = "")
def main():
#np.set_printoptions(threshold=np.inf)
api = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2')
api_euw = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2',
Consts.REGIONS['europe_west'])
api_eune = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2',
Consts.REGIONS['europe_nordic_and_east'])
api_kr = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2',
Consts.REGIONS['korea'])
#loading the NA match ids
data = json.loads(open('./BILGEWATER/EUW.json').read())
#data += json.loads(open('./BILGEWATER/EUNE.json').read())
#data += json.loads(open('./BILGEWATER/KR.json').read())
data += json.loads(open('./BILGEWATER/NA.json').read())
csv_data = np.zeros(
shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
pop_items = make_items_dict()
pop_spells = make_spells_dict()
team_comps = {}
data_col_base = len(Consts.STAT_TO_MATRIX)
_fill_champ_id_range(csv_data, data_col_base)
match_num = 1
for matchid in data:
print("On match number " + str(match_num))
if match_num <= 10000:
#print(matchid)
match = api_euw.get_match_info(matchid, {'includeTimeline': True})
else:
match = api.get_match_info(matchid, {'includeTimeline': True})
win_team = []
lose_team = []
if match is False or match['matchDuration'] < 1000:
print("Broken Match")
continue
for champ in match['participants']:
#get champ id and name
championID = champ['championId']
champ_name = champion_cache.find(championID)
if champ_name is False:
champ_name = api.get_champ_by_id(championID)['key']
champion_cache.place(championID, champ_name)
chmp_mtrx_index = CHAMP_TO_MATRIX[champ_name]
#these methods return values which must then be input into the matrix
offense, defense, utility = _parse_masteries(
champ.get('masteries', []))
kills, deaths, assists, phys_dmg, mgc_dmg, true_dmg, dmg_taken, team_jgl, enemy_jgl, win = _parse_stats(
champ['stats'], championID)
cs_min, gold_min = _parse_timeline(champ['timeline'])
#combination so it does not matter which order summoner spells are chosen
spell1id = champ['spell2Id'] + champ['spell1Id']
spell2id = champ['spell1Id'] * champ['spell2Id']
if champ['spell2Id'] in pop_spells[champ_name]:
pop_spells[champ_name][champ['spell2Id']] += 1
else:
pop_spells[champ_name][champ['spell2Id']] = 1
if champ['spell1Id'] in pop_spells[champ_name]:
pop_spells[champ_name][champ['spell1Id']] += 1
else:
pop_spells[champ_name][champ['spell1Id']] = 1
#print(pop_spells)
#place data into matrix
#attack range not changed because data is normalized anyway
csv_data_delta = np.array([
offense, defense, utility, kills, deaths, assists, phys_dmg,
mgc_dmg, true_dmg, dmg_taken, team_jgl, enemy_jgl, 0, cs_min,
gold_min, spell1id, spell2id, win
])
csv_data[chmp_mtrx_index, data_col_base + 1:data_col_base +
len(Consts.VARIABLE_TO_MATRIX) + 1] += csv_data_delta
#these methods input data directly into matrix
csv_data = _parse_runes(champ.get('runes', []), csv_data,
chmp_mtrx_index)
csv_data = _parse_items(champ['stats'], csv_data, chmp_mtrx_index,
pop_items, True)
#add 1 to champion counter
csv_data[chmp_mtrx_index, Consts.BLACK_MARKET_FEATURES - 1] += 1
#add to team list
if win == 1:
win_team.append(champ_name)
else:
lose_team.append(champ_name)
if SHOW_MATRIX:
print(csv_data)
win_team = tuple(sorted(win_team))
#print(win_team)
lose_team = tuple(sorted(lose_team))
#print(lose_team)
team_comps = add_to_team_comps(win_team, lose_team, team_comps)
#print(team_comps)
match_num += 1
np.savetxt('data.csv', csv_data, delimiter=",", comments="")
with open('item_dict.json', 'w') as fp:
json.dump(pop_items, fp)
with open('team_dict.json', 'w') as fp:
json.dump(team_comps, fp)
with open('spell_dict.json', 'w') as fp:
json.dump(pop_spells, fp)
def second_main():
#np.set_printoptions(threshold=np.inf)
api = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2')
api_euw = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2',
Consts.REGIONS['europe_west'])
api_eune = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2',
Consts.REGIONS['europe_nordic_and_east'])
api_kr = RiotAPI('be8ccf5f-5d08-453f-84f2-ec89ddd7cea2',
Consts.REGIONS['korea'])
#loading the NA match ids
data = json.loads(open('./BILGEWATER/EUW.json').read())
data += json.loads(open('./BILGEWATER/KR.json').read())
data += json.loads(open('./BILGEWATER/NA.json').read())
data_col_base = len(Consts.STAT_TO_MATRIX)
#initialize different arrays
marksman_data = np.zeros(
shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
support_data = np.zeros(
shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
mage_data = np.zeros(
shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
tank_data = np.zeros(
shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
phys_data = np.zeros(
shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
mgc_data = np.zeros(
shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
jgler_data = np.zeros(
shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
ass_data = np.zeros(
shape=[Consts.BLACK_MARKET_CHAMPIONS, Consts.BLACK_MARKET_FEATURES])
data_list = {
'Magical Bruiser': mgc_data,
'Assassin': ass_data,
'Jungler': jgler_data,
'Marksman': marksman_data,
'Support': support_data,
'Mage': mage_data,
'Tank': tank_data,
'Physical Bruiser': phys_data
}
for role in data_list:
_fill_champ_id_range(data_list[role], data_col_base)
#initialize k-cluster
kmean, scaler = KLearn.get_k_learn()
match_num = 1
for matchid in data:
print("On match number " + str(match_num))
if match_num <= 10000:
#print(matchid)
match = api_euw.get_match_info(matchid, {'includeTimeline': True})
elif match_num <= 20000:
match = api_kr.get_match_info(matchhid, {'includeTimeline': True})
else:
match = api.get_match_info(matchhid, {'includeTimeline': True})
if match['matchDuration'] < 1000:
print("Broken Match")
continue
for champ in match['participants']:
champ_data = np.zeros(shape=[1, Consts.BLACK_MARKET_FEATURES])
#get champ id and name
championID = champ['championId']
champ_name = champion_cache.find(championID)
if champ_name is False:
champ_name = api.get_champ_by_id(championID)['key']
champion_cache.place(championID, champ_name)
chmp_mtrx_index = CHAMP_TO_MATRIX[champ_name]
#these methods return values which must then be input into the matrix
offense, defense, utility = _parse_masteries(
champ.get('masteries', []))
kills, deaths, assists, phys_dmg, mgc_dmg, true_dmg, dmg_taken, team_jgl, enemy_jgl, win = _parse_stats(
champ['stats'], championID)
cs_min, gold_min = _parse_timeline(champ['timeline'])
#combination so it does not matter which order summoner spells are chosen
spell1id = champ['spell2Id'] + champ['spell1Id']
spell2id = champ['spell1Id'] * champ['spell2Id']
#place data into matrix
#attack range not changed because data is normalized anyway
data_delta = np.array([
offense, defense, utility, kills, deaths, assists, phys_dmg,
mgc_dmg, true_dmg, dmg_taken, team_jgl, enemy_jgl, 0, cs_min,
gold_min, spell1id, spell2id, win
])
champ_data[0, data_col_base + 1:data_col_base +
len(Consts.VARIABLE_TO_MATRIX) + 1] += data_delta
#these methods input data directly into matrix
champ_data = _parse_runes(champ.get('runes', []), champ_data, 0)
champ_data = _parse_items(champ['stats'], champ_data, 0, {}, False)
#add 1 to champion counter
champ_data[0, Consts.BLACK_MARKET_FEATURES - 1] += 1
cluster_num = find_cluster(kmean, scaler, champ_data)
data_list[KLearn.roles[cluster_num]][
chmp_mtrx_index] += champ_data.flatten()
match_num += 1
for role in data_list:
np.savetxt('role_data' + role + '.csv',
data_list[role],
delimiter=",",
comments="")
