Numpy笔记----------numpy矩阵操作-优快云博客

本文链接：https://blog.youkuaiyun.com/infinite_shadow/article/details/148314472

1.算数运算(加减乘除)

矩阵和数运算

import numpy as np
n = np.random.randint(0,10,size=(4,5))
print('n:',n)
#加法运算
add = n + 10
print('add:',add)
#减法运算
subtraction = n - 10
print('subtraction:',subtraction)
#乘法运算
multiplication = n * 10
print('multiplication:',multiplication)
#除法运算
division1 = n / 10 #除法
print('division1:',division1)
division2 = n // 10 #整除
print('division2:',division2)
#次方
exponentiation = n ** 2
print('exponentiation:',exponentiation)
#取余
remainder = n % 2
print('remainder:',remainder)

矩阵和矩阵运算

import numpy as np
n1 = np.random.randint(0,10,size=(4,5))
n2 = np.random.randint(0,10,size=(4,5))
print('n1:',n1)
print('n2:',n2)
#加法运算
add = n1 + n2
print('add:',add)
#减法运算
subtraction = n1 - n2
print('subtraction:',subtraction)
#乘法运算(对应元素相乘)
multiplication = n1 * n2
print('multiplication:',multiplication)

2.线性代数

矩阵积(np.dot) ⚠️注意：第一个矩阵的行数等于第二个矩阵的列数 $\begin{pmatrix} a_{11}& a_{12} & a_{13} \\ a_{21}& a_{22} & a_{23} \end{pmatrix} \begin{pmatrix} b_{11}&b _{12}\\ b_{21}&b _{22}\\ b_{31}&b_{32} \end{pmatrix} = \begin{pmatrix} a_{11}b_{11}+a_{12}b_{21}+a_{13}b_{31} &a_{11}b_{12}+a_{12}b_{22}+a_{13}b_{32} \\ a_{21}b_{11}+a_{22}b_{21}+a_{23}b_{31}& a_{21}b_{12}+a_{22}b_{22}+a_{23}b_{32} \end{pmatrix}$

import numpy as np
n1 = np.random.randint(0,10,size=(3,4))
n2 = np.random.randint(0,10,size=(4,5))
print('n1:',n1)
print('n2:',n2)
dot = np.dot(n1,n2)
print('dot:',dot)

其他线性代数运算

import numpy as np
n = np.array([[1,2,3],[2,4,5],[4,5,8]])
#逆矩阵(奇异矩阵无逆矩阵)
inv = np.linalg.inv(n)
print('inv:',inv)
#行列式
det = np.linalg.det(n)
print('det:',det)
#秩
rank = np.linalg.matrix_rank(n)
print('rank:',rank)

3.广播机制

【‼️重要】广播机制的两条规则

为缺失的维度补齐

确实元素用已有值填充

import numpy as np
n = np.arange(3).reshape((3,1))
m = np.arange(3)
print('n:',n)
print('m:',m)
x = n + m
print('x:',x)

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