牛顿迭代法和最小二乘法直线拟合代码

最近感觉啥都不会了，忘光了

#coding:utf-8def df(func,x):#求导    eps = 1.0e-4    return (func(x + eps) - func(x))/epsdef customFunc(x):    return pow(x,4) + 3 * pow(x,3) + 1.5 * pow(x, 2) - 4def newton(x, p, m):    x0 = x    k = 0    while (k < m):        k += 1        if df(customFunc, x0) == 0.0:            return 0        x1 = x0 - customFunc(x0)/df(customFunc, x0)        if abs(x1-x0) < p or abs(customFunc(x1)) < p:            print x1            return 1        else:            x0 = x1    return 0newton(2.0, 0.01, 100)def linematch(xl,yl):    sumx = sum(xl)    sumy = sum(yl)    sumx2 = sum([ j*j for j in xl])    sumxy = sum([ t[0] * t[1] for t in zip(xl, yl) ])    ncount = len(xl)        b = (sumx2 * sumy - sumx * sumxy) / (ncount * sumx2 - sumx * sumx)    k = (ncount * sumxy - sumx * sumy) / (ncount * sumx2 - sumx * sumx)    print 'function is y = %sx + %s'%(k, b)    k1 = (sumy * sumx - sumxy * ncount) / (sumx * sumx - sumx2 * ncount)    b1 = (sumy - sumx * k1)/ncount    print 'k1 = %s, b1 = %s'%(k1, b1)    print '##################'linematch([2,3,4,5], [1,2,3,4])linematch([2,3,4,5, 7], [5, 7, 9, 11, 15])linematch([2,3,4,5, 7, 9 , 11], [6, 9, 12 , 15 , 21, 27, 33])

公式推理：http://blog.csdn.net/ice_fire3/article/details/6709929

最小二乘法求多项式系数还没写出来，

2014.4.18ps:现在才知道最小二乘法的原理是统计里面的，基础不劳靠记公式总是记不住，理解之后整个就好推导出来