如何在N × N矩阵中计算跃迁，其中维度不是不连续的

Question

我有以下数据:

import numpy as np
import pandas as pd

arr = np.array([0, 1, 2, 3, 4, 6, 7, 5])
x = pd.Series([0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,5,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7]) 
print(arr)
print(type(arr))
[0 1 2 3 4 6 7 5]
<class 'numpy.ndarray'>

下面的代码可以很好地处理上面的数据:

m = [[0] * len(arr) for _ in enumerate(arr)]
for (i, j) in zip(x, x[1:]):
m[i][j] += 1

但是，当数据如下时，上述代码会产生以下错误:

arr = np.arry([0, 1, 2, 3, 4, 6, 7])
x = pd.Series([0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7])

错误——

m[i][j] += 1IndexError:列表索引超出范围"

Answer 1

@Ananda是正确的，但是你写的东西仍然可以工作，真正的问题是你传递了两种不同的类型

顶部是

arr = np.array([0, 1, 2, 3, 4, 6, 7, 5])

，底部是

arr = np.arry([[0, 1, 2, 3, 4, 6, 7]])

你需要底部是

arr = np.arry([0, 1, 2, 3, 4, 6, 7])

注意缺少第二组括号…

Answer 2

我想这就是你想要做的。

import numpy as np
import pandas as pd

arr = np.array([0, 1, 2, 3, 4, 6, 7])
x = pd.Series([0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7,0,1,2,3,4,6,7])
m = [[0] * (np.max(arr)+1) for _ in enumerate(np.arange(np.max(arr)+1))]
for (i, j) in zip(x, x[1:]):
m[i][j] += 1

在创建变量m时，您需要取arr的最大值，而不是它的长度。