total_connection += winrate.loc[hero1][hero2]
for enemy in against:
total_connection -= lose_rate.loc[next_hero_id][enemy]
if total_connection > best_connection:
best_hero = next_hero_id
best_connection = total_connection
return best_hero.item()
# In[25]:
pick = Heroes()
pick.add(Hero.from_name(''))
ban = Heroes()
ban.add(Hero.from_name('Shadow Fiend'))
ban.add(Hero.from_name('Invoker'))
against = Heroes()
against.add(Hero.from_name('Slardar'))
against.add(Hero.from_name('Witch Doctor'))
while len(pick) < 5:
next_hero = get_next_hero(list(pick.get_ids()),
ban=list(ban.get_ids()),
against=list(against.get_ids()))
pick.add(Hero(next_hero))
class Match(object):
''' Representation of the single match.
Attributes:
id (int) : id of the match
radiant (Heroes): Heroes in radiant team
dire (Heroes): Heroes in dire team
'''
def __init__(self, match_id: int):
''' Calls the API and creates a match representation from result.
Args:
match_id: Dota match ID
'''
if not isinstance(match_id, int):
raise TypeError('`match_id` must have type int.')
else:
self.id = match_id
response = api.get_match_details(match_id=match_id)
# TODO: check supported modes, rewrote this
if response['game_mode'] != 2 and response['game_mode'] != 16:
raise NotImplementedError(
'Sorry, Match currently' +
' does not support {}'.format(response['game_mode_name']) +
' game mode.')
self.radiant = Heroes()
self.dire = Heroes()
self.radiant_win = response['radiant_win']
# select picks and add heroes to appropriate teams
for pick in filter(lambda x: x['is_pick'], response['picks_bans']):
if pick['team'] == 0:
self.radiant.add(Hero(pick['hero_id']))
else:
self.dire.add(Hero(pick['hero_id']))
def get_description(self, include):
''' Returns description of certain match.
Description consist of 3 parts: radiant description, dire description
and result. Complete length of description vector is 2n + 1, where
n is a length of side description (depends on choosen parameters).
Args:
include (list): the same with Hero.get_description().
Returns:
pd.Series
'''
# get descriptions of sides
radiant_description = self.radiant.get_description(include)
dire_description = self.dire.get_description(include)
len_desc = radiant_description.shape[0]
# create array for MultiIndex object
index_arrays = [['radiant'] * len_desc + ['dire'] * len_desc,
list(radiant_description.index) * 2]
# convert array to list of tuples
index_tuples = list(zip(*index_arrays))
# add result comlumn
index_tuples.append(('result', 'radiant_win'))
index = pd.MultiIndex.from_tuples(index_tuples,
names=['side', 'variables'])
# unite all the columns
variables = [*radiant_description, *dire_description, self.radiant_win]
description = pd.Series(variables, index=index)
return description