numpy array:在作为输入的一组行和列的固定窗口内计算argmax的有效方法

import numpy as np
from scipy.ndimage import maximum_filter

def local_argmax(arr, window_size):
    # 创建一个与原数组形状相同的最大值滤波器结果数组
    max_filter_result = maximum_filter(arr, footprint=np.ones(window_size), mode='constant')
    
    # 找到最大值滤波器结果与原数组相等的索引，即为局部最大值的索引
    local_maxima_mask = (arr == max_filter_result)
    
    # 获取局部最大值的索引
    local_maxima_indices = np.argwhere(local_maxima_mask)
    
    return local_maxima_indices

# 示例二维数组
arr = np.array([[1, 2, 3],
                [4, 5, 6],
                [7, 8, 9]])

# 计算 2x2 窗口内的局部 argmax
window_size = (2, 2)
local_maxima_indices = local_argmax(arr, window_size)

print("局部最大值的索引：", local_maxima_indices)

# 使用 'reflect' 模式处理边缘情况
max_filter_result = maximum_filter(arr, footprint=np.ones(window_size), mode='reflect')