Prerequisites:

先决条件：

• numpy.matmul( ) matrix multiplication

  numpy.matmul()矩阵乘法

• Identity matrix

  身份矩阵

In linear algebra, the identity matrix, of size n is the n × n square matrix with ones on the main diagonal and zeros elsewhere. It is denoted by I. Also known as the unit matrix because its determinant value is 1 irrespective of size. This is the key feature of an Identity matrix and it plays an important role in Linear Algebra.

在线性代数中，大小为n的单位矩阵是n×n方阵，主对角线上为1，其他地方为零。 用I表示。 也称为单位矩阵，因为其行列式值为1，与大小无关。 这是恒等矩阵的关键特征，在线性代数中起着重要的作用。

The identity matrix has the property that, Multiplying k identity matrices gives an identity matrix (I^k = I).

单位矩阵具有以下性质：将k个单位矩阵相乘得到一个单位矩阵( I ^k = I )。

身份矩阵属性的Python代码( ^IK = I) (Python code for identity matrix property (I^k = I))

# Linear Algebra Learning Sequence
# Identity Matrix Property (I^k = I)
import numpy as np
# identity Matrix 
I = np.eye(4)   
print("\n---I(4x4)---\n", I)
k = 14
Ik = I
for i in range(14):
Ik = I*Ik
print('\n\n--- I^k ----\n', Ik)

Output:

输出：

---I(4x4)---
[[1. 0. 0. 0.]
[0. 1. 0. 0.]
[0. 0. 1. 0.]
[0. 0. 0. 1.]]
--- I^k ----
[[1. 0. 0. 0.]
[0. 1. 0. 0.]
[0. 0. 1. 0.]
[0. 0. 0. 1.]]

翻译自: https://www.includehelp.com/python/identity-matrix-property-i-k-i.aspx