Standard_Matrix

• 假设我们有一个样本矩阵X，每一列表示一个样本，现在我们要把样本转换成均值为0，方差为1的样本矩阵
  $$\begin{array}{c}{X}_{standard}=\frac{X-\mu }{s}\end{array}$$
• python 测试代码如下：

import numpy as np

np.set_printoptions(suppress=True, precision=3)


class MeanVarianceMatrix(object):
    def __init__(self, matrix):
        self.matrix = matrix
        self.standard_matrix = np.zeros_like(self.matrix)

    def get_standard_matrix(self):
        my_mean = np.mean(self.matrix, axis=0)
        my_std = np.std(self.matrix, axis=0)
        self.standard_matrix = (self.matrix - my_mean) / my_std
        check_mean = np.mean(self.standard_matrix)
        check_var = np.var(self.standard_matrix)
        print(f"*"*50)
        print(f"matrix=\n{self.matrix}")
        print(f"standard_matrix=\n{self.standard_matrix}")
        print(f"check_mean={round(check_mean)}")
        print(f"check_var={round(check_var)}")
        print(f"*"*50)


if __name__ == "__main__":
    my_matrix_list = [np.random.randint(1, 20, (3, 3)) for _ in range(5)]
    my_matrix = np.random.randint(1, 10, (3, 3))
    for i_matrix in my_matrix_list:
        my_stand = MeanVarianceMatrix(i_matrix)
        my_stand.get_standard_matrix()

• 结果如下：

**************************************************
matrix=
[[ 8 10  9]
 [ 7  9 19]
 [ 1 15  1]]
standard_matrix=
[[ 0.863 -0.508 -0.091]
 [ 0.539 -0.889  1.268]
 [-1.402  1.397 -1.177]]
check_mean=0
check_var=1
**************************************************
**************************************************
matrix=
[[13  7 18]
 [12  2  4]
 [16  6 11]]
standard_matrix=
[[-0.392  0.926  1.225]
 [-0.981 -1.389 -1.225]
 [ 1.373  0.463  0.   ]]
check_mean=0
check_var=1
**************************************************
**************************************************
matrix=
[[19 16  1]
 [10  9  1]
 [10 13 10]]
standard_matrix=
[[ 1.414  1.162 -0.707]
 [-0.707 -1.279 -0.707]
 [-0.707  0.116  1.414]]
check_mean=0
check_var=1
**************************************************
**************************************************
matrix=
[[ 4  5 12]
 [ 8 13  5]
 [ 6  6  7]]
standard_matrix=
[[-1.225 -0.843  1.359]
 [ 1.225  1.405 -1.019]
 [ 0.    -0.562 -0.34 ]]
check_mean=0
check_var=1
**************************************************
**************************************************
matrix=
[[ 5 14 17]
 [ 6 10  4]
 [11 11  5]]
standard_matrix=
[[-0.889  1.373  1.411]
 [-0.508 -0.981 -0.79 ]
 [ 1.397 -0.392 -0.621]]
check_mean=0
check_var=1
**************************************************