Python实现线性拟合与一元函数绘图的完整示例

#-*- coding:utf-8 -*-
import math
import matplotlib.pyplot as plt
def linefit(x , y):
  N = float(len(x))
  sx,sy,sxx,syy,sxy=0,0,0,0,0
  for i in range(0,int(N)):
    sx += x[i]
    sy += y[i]
    sxx += x[i]*x[i]
    syy += y[i]*y[i]
    sxy += x[i]*y[i]
  a = (sy*sx/N -sxy)/( sx*sx/N -sxx)
  b = (sy - a*sx)/N
  r = abs(sy*sx/N-sxy)/math.sqrt((sxx-sx*sx/N)*(syy-sy*sy/N))
  return a,b,r
if __name__ == '__main__':
  x=[ 1 ,2 ,3 ,4 ,5 ,6]
  y=[ 2.5 ,3.51 ,4.45 ,5.52 ,6.47 ,7.51]
  a,b,r=linefit(x,y)
  print("X=",x)
  print("Y=",y)
  print("拟合结果: y = %10.5f x + %10.5f , r=%10.5f" % (a,b,r) )
  plt.plot(x, y, "r:", linewidth=2)
  plt.grid(True)
  plt.show()

#-*- coding:utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
import math
f = lambda x:5*x+4
tx = np.linspace(0,10,50)
print tx
plt.plot(tx, f(tx), "r-", linewidth=2)
plt.grid(True)
plt.show()