线性代数向量乘法_向量的标量乘法| 使用Python的线性代数

线性代数向量乘法

Prerequisite: Linear Algebra | Defining a Vector

先决条件： 线性代数| 定义向量

Linear algebra is the branch of mathematics concerning linear equations by using vector spaces and through matrices. In other words, a vector is a matrix in n-dimensional space with only one column. In linear algebra, there are two types of multiplication:

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。 换句话说，向量是n维空间中只有一列的矩阵。 在线性代数中，有两种类型的乘法：

1. Scalar Multiplication

   标量乘法

2. Cross Multiplication

   交叉乘法

In a scalar product, each component of the vector is multiplied by the same a scalar value. As a result, the vector’s length is increased by scalar value. 

在标量积中，向量的每个分量都乘以相同的标量值。 结果，向量的长度增加了标量值。

For example: Let a vector a = [4, 9, 7], this is a 3 dimensional vector (x,y and z)

例如：令向量a = [4、9、7]，这是3维向量(x，y和z)

So, a scalar product will be given as b = c*a

因此，标量积将给出为b = c * a

Where c is a constant scalar value (from the set of all real numbers R). The length vector b is c times the length of vector a.

其中c是常数标量值(来自所有实数R的集合)。 长度矢量b是向量a的长度c倍。

向量标量乘法的Python代码 (Python code for Scalar Multiplication of Vector)

# Vectors in Linear Algebra Sequnce (5)
# Scalar Multiplication of Vector

def scalar(c, a):
    b = []
    for i in range(len(a)):
        b.append(c*a[i])
    return b    

a = [3, 5, -5, 8] # This is a 4 dimensional vector

print("Vector a = ", a)
c = int(input("Enter the value of scalar multiplier: "))

# The vector b will have the same dimensions 
# but the overall magnitute is c times a
print("Vector (b = c*a) = ", scalar(c, a))

Output

输出量

Vector a =  [3, 5, -5, 8]
Enter the value of scalar multiplier: 3
Vector (b = c*a) =  [9, 15, -15, 24]

翻译自: https://www.includehelp.com/python/scalar-multiplication-of-vector.aspx

线性代数向量乘法