python numpy数组归一化和反归一化

以下是Python中使用numpy对数组进行归一化和反归一化的示例代码：

1. 归一化：

import numpy as np

def normalize_array(arr):
    min_val = np.min(arr)
    max_val = np.max(arr)
    normalized_arr = (arr - min_val) / (max_val - min_val)
    return normalized_arr

# 示例
arr = np.array([1, 2, 3, 4, 5])
normalized_arr = normalize_array(arr)
print(normalized_arr)  # 输出：[0.   0.25 0.5  0.75 1.  ]

2. 反归一化：

import numpy as np

def denormalize_array(arr, original_arr):
    min_val = np.min(original_arr)
    max_val = np.max(original_arr)
    denormalized_arr = arr * (max_val - min_val) + min_val
    return denormalized_arr

# 示例
normalized_arr = np.array([0.   , 0.25 , 0.5  , 0.75 , 1.   ])
original_arr = np.array([1, 2, 3, 4, 5])
denormalized_arr = denormalize_array(normalized_arr, original_arr)
print(denormalized_arr)  # 输出：[1. 2. 3. 4. 5.]