Python实现的拟合二元一次函数功能示例【基于scipy模块】

# -*- coding:utf-8 -*-
#! python3
import numpy as np
from scipy.optimize import leastsq
import pylab as pl
def func(x,p):
  """
  数组拟合函数
  """
  A,k,theta = p
  return A*(x-k)**2+theta
def residuals(p,y,x):
  """
  残差
  """
  return y-func(x,p)
x = np.linspace(0,2,100)
A,k,theta = 10.,1,2. #真实数据参数
y0 = func(x,[A,k,theta]) #真实数据
y1 = y0 + 2 * np.random.randn(len(x)) #加入噪声序列
p0 = [7.,0.2,1.]
plsq = leastsq(residuals,p0,args = (y1,x))
print("真实参数:",[A,k,theta])
print("拟合参数:",plsq[0]) #试验数据拟合后的参数
pl.plot(x,y0,label = "real")
pl.plot(x,y1,label = "real+noise")
pl.plot(x,func(x,plsq[0]),label = "fitting")
pl.legend()
pl.show()