python用fsolve、leastsq對非線性方程組進行求解
阿新 • • 發佈:2019-02-03
背景:
實現用python的optimize庫的fsolve對非線性方程組進行求解。可以看到這一個問題實際上還是一個優化問題,也可以用之前擬合函式的leastsq求解。下面用這兩個方法進行對比:程式碼:
from scipy.optimize import fsolve,leastsq from math import sin,cos def f(x): x0 = float(x[0]) x1 = float(x[1]) x2 = float(x[2]) return [ 5*x1+3, 4*x0*x0 - 2*sin(x1*x2), x1*x2-1.5 ] x0 = [1,1,1] result = fsolve(f,x0) print("===================") print() print("求解函式名稱:",fsolve.__name__) print("解:",result) print("各向量值:",f(result)) #擬合函式來求解 h = leastsq(f,x0) print("===================") print() print("求解函式名稱:",leastsq.__name__) print("解:",h[0]) print("各向量的值:",f(h[0]))
結果:
===================求解函式名稱: fsolve
解: [-0.70622057 -0.6 -2.5 ]
各向量值: [0.0, -9.126033262418787e-14, 5.329070518200751e-15]
===================
求解函式名稱: leastsq
解: [-0.70622057 -0.6 -2.5 ]
各向量的值: [0.0, -2.220446049250313e-16, 0.0]