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：
Scalar Multiplication
标量乘法
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
