Given a set of x values and y values, this functions returns another function with the best fit line

bestFit.py

def LFIT(x,y):
	N = len(x)
	if N != len(y):
		return 0
	Sx = sum(x)
	Sy = sum(y)
	Sx2 = sum([n**2 for n in x])
	Sxy = sum([x[i]*y[i] for i in range(N)])
	b = (N*Sxy-Sx*Sy)/(N*Sx2-Sx**2)
	a = (Sy-b*Sx)/N
	def bestFit(k):
		if k=='a':
			return a
		elif k=='b':
			return b
		else:
			return b*k+a
	return bestFit