python代码，先编写一个利用3σ原则剔除一维数组异常值的函数。然后利用for循环写出剔除多维数组异常值的方法

好的，我明白了。下面是Python代码，实现利用3σ原则剔除一维数组异常值的函数：

import numpy as np

def remove_outliers(data):
    mean = np.mean(data)
    std_dev = np.std(data)
    threshold = 3 * std_dev
    lower_bound = mean - threshold
    upper_bound = mean + threshold
    filtered_data = [elem for elem in data if (elem > lower_bound) and (elem < upper_bound)]
    return filtered_data

接下来，是利用for循环写出剔除多维数组异常值的方法：

import numpy as np

def remove_outliers(data):
    num_dims = len(data.shape)
    means = np.mean(data, axis=0)
    std_devs = np.std(data, axis=0)
    filtered_data = np.copy(data)

    for i in range(num_dims):
        col = data[:, i]
        threshold = 3 * std_devs[i]
        lower_bound = means[i] - threshold
        upper_bound = means[i] + threshold
        filtered_data = filtered_data[(col > lower_bound) & (col < upper_bound)]
    
    return filtered_data

这个函数用于多维数组，它首先计算每一列的平均值和标准差，然后分别计算每一列的上下阈值，最后使用for循环来逐一处理每一列的异常值。