这里用到的是scipy.optimize的fmin和fminbound
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import numpy as npfrom matplotlib import pyplot as pltfrom scipy.optimize import fmin,fminbound def f(x): return x**2+10*np.sin(x)+1x=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：
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Optimization terminated successfully. Current function value: 9.315586 Iterations: 15 Function evaluations: 30Optimization 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服务器之家。
原文链接：https://blog.csdn.net/your_answer/article/details/79170869
