线性代数分块矩阵求逆矩阵
Linear algebra is the branch of mathematics concerning linear equations by using vector spaces and through matrices. Matrix is the key to linear algebra. All the linear algebra revolves around matrices. Columns are the heart of a Matrix. From column space to null space of a matrix is based on Columns. Therefore, whenever we have to go for Column operations, then we have to call our columns.
线性代数是使用向量空间和矩阵的线性方程组的数学分支。 矩阵是线性代数的关键。 所有线性代数都围绕矩阵旋转。 列是矩阵的核心。 矩阵的从列空间到空空间都是基于列的。 因此，每当必须进行列操作时，就必须调用列。
The following code shows how to call a whole column of a matrix.
以下代码显示了如何调用矩阵的整个列。
用于调用矩阵列的Python代码 (Python code for calling column of a matrix) # Linear Algebra Learning Sequence# Calling Column of a Matriximport numpy as np# Use of np.array() to define a matrixV = np.array([[1,2,3],[2,3,5],[3,6,8],[323,623,823]])print("--The Matrix-- n",V)j = int(input("Enter j (column number) : "))# Printing the V[i][j] element of the matrixln = len(V)for i in range(ln): print("Component [",i,"] [",j,"] :", V[i][j-1])Output:
输出：
--The Matrix-- [[ 1 2 3] [ 2 3 5] [ 3 6 8] [323 623 823]]Enter j (column number) : 2Component [ 0 ] [ 2 ] : 2Component [ 1 ] [ 2 ] : 3Component [ 2 ] [ 2 ] : 6Component [ 3 ] [ 2 ] : 623翻译自: https://www.includehelp.com/python/calling-column-of-a-matrix.aspx
线性代数分块矩阵求逆矩阵