python

关注公众号 jb51net

关闭
首页 > 脚本专栏 > python > python牛顿插值法

用Python实现Newton插值法

作者:Amiyai

最近在做数值分析的作业,作业里面的小数点让计算能力本就薄弱的我雪上加霜,为了偷个小懒快速把作业完成,所以有了这篇博客。哈哈哈哈哈,让我们一起复制copy,完成作业,哈哈哈哈需要的朋友可以参考下

1. n阶差商实现

def diff(xi,yi,n):
    """
    param xi:插值节点xi
    param yi:插值节点yi
    param n: 求几阶差商
    return: n阶差商
    """
    if len(xi) != len(yi):  #xi和yi必须保证长度一致
        return
    else:
        diff_quot = [[] for i in range(n)]
        for j in range(1,n+1):
            if j == 1:
                for i in range(n+1-j):
                    diff_quot[j-1].append((yi[i]-yi[i+1]) / (xi[i] - xi[i + 1]))
            else:
                for i in range(n+1-j):
                    diff_quot[j-1].append((diff_quot[j-2][i]-diff_quot[j-2][i+1]) / (xi[i] - xi[i + j]))
    return diff_quot

测试一下:

xi = [1.615,1.634,1.702,1.828]
yi = [2.41450,2.46259,2.65271,3.03035]
n = 3
print(diff(xi,yi,n))

返回的差商结果为:

[[2.53105263157897, 2.7958823529411716, 2.997142857142854], [3.0440197857724347, 1.0374252793901158], [-9.420631485362996]]

2. 牛顿插值实现

def Newton(x):
    f = yi[0]
    v = []
    r = 1
    for i in range(n):
        r *= (x - xi[i])
        v.append(r)
        f += diff_quot[i][0] * v[i]
    return f

测试一下:

x = 1.682
print(Newton(x))

结果为:

2.5944760289639732

3.完整Python代码

def Newton(xi,yi,n,x):
    """
    param xi:插值节点xi
    param yi:插值节点yi
    param n: 求几阶差商
    param x: 代求近似值
    return: n阶差商
    """
    if len(xi) != len(yi):  #xi和yi必须保证长度一致
        return
    else:
        diff_quot = [[] for i in range(n)]
        for j in range(1,n+1):
            if j == 1:
                for i in range(n+1-j):
                    diff_quot[j-1].append((yi[i]-yi[i+1]) / (xi[i] - xi[i + 1]))
            else:
                for i in range(n+1-j):
                    diff_quot[j-1].append((diff_quot[j-2][i]-diff_quot[j-2][i+1]) / (xi[i] - xi[i + j]))
    print(diff_quot)
    
    f = yi[0]
    v = []
    r = 1
    for i in range(n):
        r *= (x - xi[i])
        v.append(r)
        f += diff_quot[i][0] * v[i]
    return f

到此这篇关于用Python实现牛顿插值法的文章就介绍到这了,更多相关python牛顿插值法内容请搜索脚本之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持脚本之家!

您可能感兴趣的文章:
阅读全文