矩阵形状| 使用Python的线性代数

Prerequisite: Linear Algebra | Defining a Matrix

先决条件： 线性代数| 定义矩阵

In the python code, we will add two Matrices. We can add two Matrices only and only if both the matrices have the same dimensions. Therefore, knowing the dimensions of the matrices turns out to be one of the major steps in Linear Algebra. The following code shows how an inbuilt function can be used to achieve our goal of the shape of a Matrix.

在python代码中，我们将添加两个矩阵。仅当两个矩阵的维数相同时，我们才可以添加两个矩阵。因此，了解矩阵的维数成为线性代数的主要步骤之一。以下代码展示了如何使用内置函数来实现矩阵形状的目标。

查找矩阵形状的Python代码 (Python code for fidning Shape of Matrix)

# Linear Algebra Learning Sequence
# Shape of Matrix 
import numpy as np
#Use of np.array() to define a matrix
V1 = np.array([[1,2,3],[2,3,5],[3,6,8],[323,623,823]])
V2 = np.array([[965,2413,78,44],[223,356,500,44],[312,66,78,44],[42,42,42,44],[44,44,44,44]])
print("--The Matrixa A-- \n",V1)
print("\n--The Matrix B-- \n",V2)
print("\n\n Shape of the matrix A: ", V1.shape)
print(" Shape of the matrix B: ", V2.shape)

Output:

输出：

--The Matrixa A-- 
[[  1   2   3]
[  2   3   5]
[  3   6   8]
[323 623 823]]
--The Matrix B-- 
[[ 965 2413   78   44]
[ 223  356  500   44]
[ 312   66   78   44]
[  42   42   42   44]
[  44   44   44   44]]
Shape of the matrix A:  (4, 3)
Shape of the matrix B:  (5, 4)