Advertisement
Not a member of Pastebin yet?
Sign Up,
it unlocks many cool features!
- import numpy as np
- import matplotlib.pyplot as plt
- %matplotlib inline
- f = np.poly1d([5, 1])
- x = np.linspace(0, 10, 30)
- y = f(x) + 6*np.random.normal(size=len(x))
- plt.plot(x, y,"or")
- a=np.vstack([x,np.ones(len(x))]).T
- linfit=np.dot(np.linalg.inv(np.dot(a.T,a)),np.dot(a.T,y))
- print(linfit)
- lstsqr=np.linalg.lstsq(a,y)[0]
- print(lstsqr)
- m,n=np.polyfit(x,y,1)
- xn=np.linspace(0,10,100)
- yn=np.polyval([m,n],xn)
- plt.plot(xn,yn)
Advertisement
Add Comment
Please, Sign In to add comment
Advertisement