这里用到的是scipy.optimize的fmin和fminbound
import numpy as np
from matplotlib import pyplot as plt
from scipy.optimize import fmin,fminbound
def f(x):
return x**2+10*np.sin(x)+1
x=np.linspace(-10,10,num=500)
min1=fmin(f,3)#求3附近的极小值
min2=fmin(f,0)#求0附近的极小值
min_global=fminbound(f,-10,10)#这个区域的最小值
print(min1)
print(min2)
print(min_global)
plt.plot(x,f(x))
plt.show()
输出：
Optimization terminated successfully.
Current function value: 9.315586
Iterations: 15
Function evaluations: 30
Optimization terminated successfully.
Current function value: -6.945823
Iterations: 26
Function evaluations: 52
[3.83745117]
[-1.3064375]
-1.306440096615395
以上这篇python实现函数极小值就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持脚本之家。
