线性代数矩阵转置乘法
Prerequisite:
先决条件：
Defining Matrix using Numpy
使用Numpy定义矩阵
Determinant of a Matrix
矩阵的行列式
Transpose Matrix
转置矩阵
Here, we will learn that the determinant of the transpose is equal to the matrix itself. This is one of the key properties in Linear Algebra and is being used in major parts of Matrix and Determinants.
在这里，我们将了解转置的行列式等于矩阵本身。 这是线性代数的关键属性之一，并且在矩阵和行列式的主要部分中使用。
Example:
例：
使用Python代码查找转置矩阵的行列式 (Python code to find the determinant of a transpose matrix) # Linear Algebra Learning Sequence# Transpose Determinantimport numpy as npM1 = np.array([[2,1,4], [2,1,2], [2,3,2]])print("Matrix (M1) :n", M1)print("Transpose (M1.T) :n", M1.T)print()print('nnDeterminant of Matrix : ', np.linalg.det(M1))print('nDeterminant of transpose : ', np.linalg.det(M1.T))Output:
输出：
Matrix (M1) : [[2 1 4] [2 1 2] [2 3 2]]Transpose (M1.T) : [[2 2 2] [1 1 3] [4 2 2]]Determinant of Matrix : 7.999999999999998Determinant of transpose : 7.999999999999998翻译自: https://www.includehelp.com/python/determinant-of-a-transpose-matrix.aspx
线性代数矩阵转置乘法