如何按指定的步长挑选矩阵的列

import numpy as np

def select_columns(matrix, step):
    # 获取矩阵的列数
    num_columns = matrix.shape[1]
    # 计算挑选后的矩阵的列数
    selected_columns = int(np.ceil(num_columns / step))
    # 创建新矩阵
    new_matrix = np.empty((matrix.shape[0], selected_columns))

    # 按步长挑选列
    for i in range(selected_columns):
        start_col = i * step
        end_col = min((i + 1) * step, num_columns)
        new_matrix[:, i] = np.mean(matrix[:, start_col:end_col], axis=1)
    
    return new_matrix

# 示例用法
matrix = np.array([[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
                   [11, 12, 13, 14, 15, 16, 17, 18, 19, 20]])

step = 3
result = select_columns(matrix, step)
print(result)