[高级编程技术作业-Week 13]Scipy相关习题练习

Code：

#10.1

import numpy as np
import scipy.optimize as opt 

m = 10
n = 5

A = np.random.random((m, n))
b = np.random.normal(size = m)

result = opt.lsq_linear(A, b)
print(result['x'])

Code：

#10.2

import numpy as np
import scipy.optimize as opt
import matplotlib.pyplot as plt

def f(x):
    return (-1) * (np.sin(x - 2))**2 * np.exp(-x*x) 
     
result = opt.minimize_scalar(f) 
print(-result['fun'])

Analysis：因为SciPy没有最大值函数，故将问题进行转换：要求f(x)的最大值，即求-f(x)的最小值的相反数。

Code：

#10.3

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

n = 10
m = 2

X = np.random.normal(size = (n, m))
result = dis.pdist(X) 
print(result)