Question

我基本上有n个玩家，每个玩家我都在计算它们与其他玩家的相似程度，并按顺序或相似性存储它们。

我正在使用Pearson Correlation Coefficient来衡量任何两个玩家之间的相似性。现在基本上我想要一个数据结构，我可以在其中存储每个玩家的信息，包括它们与所有其他玩家之间的相似性值。所以对于player1，我想保留其与所有其他玩家的相似度值列表。因此我想到创建一个数组列表，每个索引都代表玩家，例如索引0将是玩家1，依此类推。现在在索引中我们将有一个字典数组。每个字典都有playerId和值的关键字作为自身与我们所指的玩家之间的相似性。

Player1 --> [[player2:0.0], [player3:0.5]]

so we would have one array where we have player1,player2,player3
and then in each index we have information as showed above.

Answer 1

让我们保持简单。您只需要一个字典和两个辅助方法，如下所示

这考虑了播放器1和播放器之间的相似性。无论在放置期间的顺序如何，player2保持不变。得到。

similarities = {}

def set_sim(players, sim):
    similarities[tuple(sorted(players))] = sim

def get_sim(players):
    return similarities.get(tuple(sorted(players)))

以下是如何使用它们

>>> set_sim(['Player3', 'Player1'], 2)
>>> set_sim(['Player1', 'Player2'], 3)
>>> set_sim(['Player2', 'Player3'], 3)
>>> get_sim(['Player3','Player2'])
3
>>> similarities
{('Player1', 'Player2'): 3, ('Player2', 'Player3'): 3, ('Player1', 'Player3'): 2}

如果您需要寻找其他玩家，辅助方法应该再次轻松。

def get_other_players(player):
    for pair in similarities.keys():
        try:
            other_player = pair[(pair.index(player)+1)%2]
            print other_player, "=", similarities[pair]
        except ValueError:
            pass

日志：

>>> set_sim(['Player9','Player4'], .02)
>>> set_sim(['Player3','Player4'], .8)
>>> set_sim(['Player12','Player4'], 1.5)

>>> get_other_players('Player4')
Player9 = 0.02
Player3 = 0.8
Player12 = 1.5

Answer 2

我的英语很差，所以我认为你的意思是

player1 = {'player2': 0.0, 'player3': 0.5}
for x in player1:
    print(x, ' is ', player1[x])

Answer 3

是吗？

from collections import namedtuple

p1 = namedtuple('p1', ['p2', 'p3'])
p2 = namedtuple('p2', ['p1', 'p3'])
p3 = namedtuple('p3', ['p1', 'p2'])

p1.p2 = 0.4
p1.p3 = 1.1

p2.p1 = 1.5
p2.p3 = 0.0

p3.p1 = 0.5
p3.p2 = 1.0

total = (p1, p2, p3)

for i in total:
    print('* {}'.format(i.__name__))
    for i2 in i._fields:
        print('{}->{}: {}'.format(i2, i.__name__, eval(i2 + '.' + i.__name__)))

也许有一种更优雅的方式来做到这一点，但它有效...... = P

Answer 4

您可能正在寻找dictionary

players = {
    "player1": 0.0,
    "player2": 0.0,
    "player3": 0.5,
}

然后您可以将其作为

进行访问

players["player1"]

或用

更改

players["player2"] = 0.7

添加新

players["player4"] = 0.1

并查看全部

print(players)

Answer 5

similarity={
   'player1': { 'player2': 0.0,
                'player3': 0.5 },

   'player2': { 'player1': 0.0,
                'player3': 0.8 },

   'player3': { 'player1': 0.5,
                'player2': 0.8 }
   }

print(similarity['player1'])
# will give you: {'player2': 0.0, 'player3': 0.5}

print(similarity['player1']['player3'])
# will give you 0.5

更强大的解决方案：

class Sim:

    __data = None

    def __init__(self):
        self.__data = dict()

    def set(self, player1, player2, similarity):

        if not self.__data.has_key(player1):
            self.__data[player1] = dict()

        if not self.__data.has_key(player2):
            self.__data[player2] = dict()

        self.__data[player1][player2] = similarity
        self.__data[player2][player1] = similarity

    def get(self, player1, player2):
        return self.__data[player1][player2]

    def __str__(self):
        return str(self.__data)

    def __repr__(self):
        return repr(self.__data)


example=Sim()
example.set('player1', 'player2', 0)
example.set('player1', 'player3', 0.5)

print(example)
# will print: 
# {'player2': {'player1': 0}, 'player3': {'player1': 0.5}, 'player1': {'player2': 0, 'player3': 0.5}}

如何在python中创建字典数组

5 个答案: