function B = CreateEndpointSE() B{1,1} = [0 0 0; 1 1 0; 0 0 0]; B{1,2} = [0 1 1; 0 0 1; 0 1 1]; for k = 2:4 B{k,1} = rot90(B{k-1,1}); B{k,2} = rot90(B{k-1,2}); end B{5,1} = [1 0 0; 0 1 0; 0 0 0]; B{5,2} = [0 1 1; 1 0 1; 1 1 1]; for k = 6:8 B{k,1} = rot90(B{k-1,1}); B{k,2} = rot90(B{k-1,2}); end end改成python代码

下面是将该函数转化为 Python 代码后的实现：

import numpy as np

def CreateEndpointSE():
    B = {}
    B[1, 1] = np.array([[0, 0, 0], [1, 1, 0], [0, 0, 0]], dtype=bool)
    B[1, 2] = np.array([[0, 1, 1], [0, 0, 1], [0, 1, 1]], dtype=bool)
    for k in range(2, 5):
        B[k, 1] = np.rot90(B[k-1, 1])
        B[k, 2] = np.rot90(B[k-1, 2])
    B[5, 1] = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 0]], dtype=bool)
    B[5, 2] = np.array([[0, 1, 1], [1, 0, 1], [1, 1, 1]], dtype=bool)
    for k in range(6, 9):
        B[k, 1] = np.rot90(B[k-1, 1])
        B[k, 2] = np.rot90(B[k-1, 2])
    return B

需要注意的是，Python 中的字典对象可以用来代替 MATLAB 中的 cell 数组，可以方便地存储不同类型的数据。此外，该函数中的 rot90 函数在 NumPy 中也有实现，可以直接调用。

相关问题

0/1背包问题的伪代码

以下是 0/1 背包问题的伪代码：

// 输入：
// - w: 物品重量数组
// - v: 物品价值数组
// - W: 背包容量
// 输出：最大价值

function knapsack(w, v, W):
    n = w.length
    // dp[i][j] 表示前 i 个物品，容量为 j 时的最大价值
    dp = new Array(n+1).fill(0).map(() => new Array(W+1).fill(0))

    for i from 1 to n:
        for j from 1 to W:
            if j < w[i-1]:
                // 背包容量不足，无法装入第 i 个物品
                dp[i][j] = dp[i-1][j]
            else:
                // 能够装入第 i 个物品，考虑是否放入背包
                dp[i][j] = max(dp[i-1][j], dp[i-1][j-w[i-1]] + v[i-1])

    return dp[n][W]

其中 `max(a, b)` 返回 `a` 和 `b` 中的较大值。

ValueError: high <= 0

This error occurs when the value of the "high" parameter in a function is less than or equal to 0.

For example, let's say you're trying to generate a random number using the "random.randint()" function in Python. This function takes two parameters: the lowest possible value and the highest possible value for the random number. If you set the "high" parameter to a value less than or equal to 0, you will get the "ValueError: high <= 0" error.

Here's an example code snippet that would produce this error:

import random

# Generate a random number between 1 and 0 (which is not possible)
random_number = random.randint(1, 0)

# This will produce the "ValueError: high <= 0" error

To fix this error, make sure that the "high" parameter is set to a value greater than 0. For example:

import random

# Generate a random number between 1 and 10
random_number = random.randint(1, 10)

# This will not produce an error