Python学习之路_scipy

1. Least squares

代码

from numpy import random  
from scipy import linalg  

A = random.randn(20, 20)  
b = random.randn(20, 1)  

x, residual, rank, s = linalg.lstsq(A, b)  
print(x)  
print(residual) 

结果

2.Optimization

代码

from scipy import optimize  
from numpy import sin, power, exp  

def f(x):  
    return -(power(sin(x - 2), 2) * exp( - power(x, 2)))  

res = optimize.minimize_scalar(f)  
if res.success:  
    print(res.x)  
    print(-res.fun)  

结果

3.Pairwise distances

代码

from scipy import spatial  
from numpy import random  

X = random.randint(1, 100, (10, 2))  
dst = spatial.distance_matrix(X, X)  
print(X)  
print(dst)  

结果