Python numpy线性代数用法实例解析

> import numpy as np
> x=np.array([[1,2,3],[4,5,6]])
> y=np.array([[7,8],[-1,7],[8,9]])
> x
array([[1, 2, 3],
    [4, 5, 6]])
> y
array([[ 7, 8],
    [-1, 7],
    [ 8, 9]])
> x.dot(y)
array([[ 29, 49],
    [ 71, 121]])
> np.dot(x,y)
array([[ 29, 49],
    [ 71, 121]])

> a=np.array([[1,2],[3,4]])
> b=np.array([[11,12],[12,13]])
> np.vdot(a,b)
123

result=1*11+2*12+3*12+4*13

> np.inner(np.array([1,2,3]),np.array([0,1,0]))
2

result=1*0+2*1+3*0

> np.inner(np.array([1,2,3]),np.array([0,1,0]))
2
> a=np.array([[1,2],[3,4]])
> np.linalg.det(a)
-2.0000000000000004

x + y + z = 6
2y + 5z = -4
2x + 5y - z = 27

> import numpy as np
> a = np.array([[1,1,1],[0,2,5],[2,5,-1]])
> ainv = np.linalg.inv(a)#求矩阵的逆
> b = np.array([[6],[-4],[27]])
> x = np.linalg.solve(a,b)#求解需要A-1和B
> x
array([[ 5.],
    [ 3.],
    [-2.]])
>