scipy 習題

10.1

# -*- coding: utf-8 -*-
"""
Created on Mon Jun  4 20:38:48 2018

@author: 12046
"""

import numpy
import scipy.linalg

m=5
n=3

A=numpy.random.random(size=(m,n))
b=numpy.random.random(size=(m))

x=scipy.linalg.lstsq(A,b)[0]
ans = numpy.linalg.norm(numpy.dot(A,x)-b)  
print(ans)

10.2

# -*- coding: utf-8 -*-
"""
Created on Mon Jun  4 21:00:40 2018

@author: 12046
"""

import numpy as np
import scipy.optimize

def f(x):
    return (-np.sin(x-2)**2)*np.exp(-(x**2))

res=scipy.optimize.minimize_scalar(f)
print(-res.fun)

10.3

# -*- coding: utf-8 -*-
"""
Created on Mon Jun  4 21:12:49 2018

@author: 12046
"""

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

m=10
n=5
A=np.random.random(size=(m,n))

result=dist.pdist(A,metric='euclidean')
print(result)