第十三周作业 Scipy习题

import numpy as np
import numpy.matlib
import scipy.linalg
m=10
n=5
A = np.matlib.randn(m, n)   #生成A
b = np.matlib.rand(m, 1)      #随机生成向量b
x = scipy.linalg.lstsq(A,b)[0]
r = np.linalg.norm(A*x-b,ord=np.inf)
print("矩阵A:")
print(A)
print("矩阵B:")
print(b)
print("所求的x:")
print(x)
print("残差的无穷范数:")
print(r)


10.2


参考资料:

Scipy教程 - 优化和拟合库scipy.optimize

https://blog.csdn.net/pipisorry/article/details/51106570


import numpy   
import scipy.optimize  
  
f = lambda x:-1*(numpy.sin(x-2)**2)*(numpy.exp(-(x**2)))  
ans = scipy.optimize.minimize_scalar(f)
max = -1*ans['fun']
print('maximum:',max) 


10.3


import numpy as np
import scipy.spatial.distance as dist

n, m = 5, 5
X = np.random.randint(0, 10, size=(n, m))
table = dist.cdist(X, X)
print(table)

猜你喜欢

转载自blog.csdn.net/cjf16337023/article/details/80515374