# import the libraries we need for number crunching and plotting
import numpy as np
import matplotlib.pyplot as pl

#generate random data for the experiment
#generate a series w from zero to 20
w = np.arange(0.0, 21.0, 1.0)
#generate a linear series y=mx+c using m=5 and c=10 and add some random offsets to it
d = 5.0 * w + 10.0 + np.random.normal(0.0, 5.0, w.size)

# find thevalues of m and c from the randowm data generated
m,c=np.polyfit(w,d,1)

#plot the dataset and the linear fit derived above
pl.plot(w, m * w + c, 'b-', label='Best fit line')
pl.plot(w,d,'k.')

pl.show()