三次样条插值Python实现

r囧r小猫 2022-05-23 07:38 504阅读 0赞

## 函数 ##

y = 1 1 + x 2 y = \\frac\{1\}\{1 + x^2\} y=1\+x21

## 算法分析 ##

三次样条插值。就是在分段插值的一种情况。  
**要求：**

*  在每个分段区间上是三次多项式（这就是三次样条中的三次的来源）
 *  在整个区间（开区间）上二阶导数连续（当然啦，这里主要是强调在节点上的连续）
 *  加上边界条件。边界条件只需要给出两个方程。构建一个方程组，就可以解出所有的参数。

这里话，根据第一类样条作为边界。（就是知道两端节点的导数数值，然后来做三次样条插值）

**但是这里也分为两种情况，分别是这个数值是随便给的一个数，还是说根据函数的在对应点上数值给出。**

## 情况一：两边导数数值给出 ##

这里假设数值均为1。即  f ′ ( x 0 ) = f ′ ( x n ) = 1 f'(x\_0) = f'(x\_n) = 1 f′(x0)=f′(xn)=1的情况。

## 情况一图像 ##

![这里写图片描述][70]

## 情况一代码 ##

import numpy as np
    from sympy import *
    import matplotlib.pyplot as plt
    
    
    def f(x):
        return 1 / (1 + x ** 2)
    
    
    def cal(begin, end, i):
        by = f(begin)
        ey = f(end)
        I = Ms[i] * ((end - n) ** 3) / 6 + Ms[i + 1] * ((n - begin) ** 3) / 6 + (by - Ms[i] / 6) * (end - n) + (
                ey - Ms[i + 1] / 6) * (n - begin)
        return I
    
    
    def ff(x):  # f[x0, x1, ..., xk]
        ans = 0
        for i in range(len(x)):
            temp = 1
            for j in range(len(x)):
                if i != j:
                    temp *= (x[i] - x[j])
            ans += f(x[i]) / temp
        return ans
    
    
    def calM():
        lam = [1] + [1 / 2] * 9
        miu = [1 / 2] * 9 + [1]
        # Y = 1 / (1 + n ** 2)
        # df = diff(Y, n)
        x = np.array(range(11)) - 5
        # ds = [6 * (ff(x[0:2]) - df.subs(n, x[0]))]
        ds = [6 * (ff(x[0:2]) - 1)]
        for i in range(9):
            ds.append(6 * ff(x[i: i + 3]))
        # ds.append(6 * (df.subs(n, x[10]) - ff(x[-2:])))
        ds.append(6 * (1 - ff(x[-2:])))
        Mat = np.eye(11, 11) * 2
        for i in range(11):
            if i == 0:
                Mat[i][1] = lam[i]
            elif i == 10:
                Mat[i][9] = miu[i - 1]
            else:
                Mat[i][i - 1] = miu[i - 1]
                Mat[i][i + 1] = lam[i]
        ds = np.mat(ds)
        Mat = np.mat(Mat)
        Ms = ds * Mat.I
        return Ms.tolist()[0]
    
    
    def calnf(x):
        nf = []
        for i in range(len(x) - 1):
            nf.append(cal(x[i], x[i + 1], i))
        return nf
    
    
    def calf(f, x):
        y = []
        for i in x:
            y.append(f.subs(n, i))
        return y
    
    
    def nfSub(x, nf):
        tempx = np.array(range(11)) - 5
        dx = []
        for i in range(10):
            labelx = []
            for j in range(len(x)):
                if x[j] >= tempx[i] and x[j] < tempx[i + 1]:
                    labelx.append(x[j])
                elif i == 9 and x[j] >= tempx[i] and x[j] <= tempx[i + 1]:
                    labelx.append(x[j])
            dx = dx + calf(nf[i], labelx)
        return np.array(dx)
    
    
    def draw(nf):
        plt.rcParams['font.sans-serif'] = ['SimHei']
        plt.rcParams['axes.unicode_minus'] = False
        x = np.linspace(-5, 5, 101)
        y = f(x)
        Ly = nfSub(x, nf)
        plt.plot(x, y, label='原函数')
        plt.plot(x, Ly, label='三次样条插值函数')
        plt.xlabel('x')
        plt.ylabel('y')
        plt.legend()
    
        plt.savefig('1.png')
        plt.show()
    
    
    def lossCal(nf):
        x = np.linspace(-5, 5, 101)
        y = f(x)
        Ly = nfSub(x, nf)
        Ly = np.array(Ly)
        temp = Ly - y
        temp = abs(temp)
        print(temp.mean())
    
    
    if __name__ == '__main__':
        x = np.array(range(11)) - 5
        y = f(x)
    
        n, m = symbols('n m')
        init_printing(use_unicode=True)
        Ms = calM()
        nf = calnf(x)
        draw(nf)
        lossCal(nf)

## 情况二：两边导数数值由函数本身算出 ##

这里假设数值均为1。即  f ′ ( x i ) = S ′ ( x i ) ( i = 0 , n ) f'(x\_i) = S'(x\_i) (i = 0, n) f′(xi)=S′(xi)(i=0,n)的情况。

## 情况二图像 ##

![这里写图片描述][70 1]

## 情况二代码 ##

import numpy as np
    from sympy import *
    import matplotlib.pyplot as plt
    
    
    def f(x):
        return 1 / (1 + x ** 2)
    
    
    def cal(begin, end, i):
        by = f(begin)
        ey = f(end)
        I = Ms[i] * ((end - n) ** 3) / 6 + Ms[i + 1] * ((n - begin) ** 3) / 6 + (by - Ms[i] / 6) * (end - n) + (
                ey - Ms[i + 1] / 6) * (n - begin)
        return I
    
    
    def ff(x):  # f[x0, x1, ..., xk]
        ans = 0
        for i in range(len(x)):
            temp = 1
            for j in range(len(x)):
                if i != j:
                    temp *= (x[i] - x[j])
            ans += f(x[i]) / temp
        return ans
    
    
    def calM():
        lam = [1] + [1 / 2] * 9
        miu = [1 / 2] * 9 + [1]
        Y = 1 / (1 + n ** 2)
        df = diff(Y, n)
        x = np.array(range(11)) - 5
        ds = [6 * (ff(x[0:2]) - df.subs(n, x[0]))]
        # ds = [6 * (ff(x[0:2]) - 1)]
        for i in range(9):
            ds.append(6 * ff(x[i: i + 3]))
        ds.append(6 * (df.subs(n, x[10]) - ff(x[-2:])))
        # ds.append(6 * (1 - ff(x[-2:])))
        Mat = np.eye(11, 11) * 2
        for i in range(11):
            if i == 0:
                Mat[i][1] = lam[i]
            elif i == 10:
                Mat[i][9] = miu[i - 1]
            else:
                Mat[i][i - 1] = miu[i - 1]
                Mat[i][i + 1] = lam[i]
        ds = np.mat(ds)
        Mat = np.mat(Mat)
        Ms = ds * Mat.I
        return Ms.tolist()[0]
    
    
    def calnf(x):
        nf = []
        for i in range(len(x) - 1):
            nf.append(cal(x[i], x[i + 1], i))
        return nf
    
    
    def calf(f, x):
        y = []
        for i in x:
            y.append(f.subs(n, i))
        return y
    
    
    def nfSub(x, nf):
        tempx = np.array(range(11)) - 5
        dx = []
        for i in range(10):
            labelx = []
            for j in range(len(x)):
                if x[j] >= tempx[i] and x[j] < tempx[i + 1]:
                    labelx.append(x[j])
                elif i == 9 and x[j] >= tempx[i] and x[j] <= tempx[i + 1]:
                    labelx.append(x[j])
            dx = dx + calf(nf[i], labelx)
        return np.array(dx)
    
    
    def draw(nf):
        plt.rcParams['font.sans-serif'] = ['SimHei']
        plt.rcParams['axes.unicode_minus'] = False
        x = np.linspace(-5, 5, 101)
        y = f(x)
        Ly = nfSub(x, nf)
        plt.plot(x, y, label='原函数')
        plt.plot(x, Ly, label='三次样条插值函数')
        plt.xlabel('x')
        plt.ylabel('y')
        plt.legend()
    
        plt.savefig('1.png')
        plt.show()
    
    
    def lossCal(nf):
        x = np.linspace(-5, 5, 101)
        y = f(x)
        Ly = nfSub(x, nf)
        Ly = np.array(Ly)
        temp = Ly - y
        temp = abs(temp)
        print(temp.mean())
    
    
    if __name__ == '__main__':
        x = np.array(range(11)) - 5
        y = f(x)
    
        n, m = symbols('n m')
        init_printing(use_unicode=True)
        Ms = calM()
        nf = calnf(x)
        draw(nf)
        lossCal(nf)

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ExOTk5MDQxMg_size_16_color_FFFFFF_t_70]

[70]: /images/20220523/687a515355b34086846f694a12f92cd2.png
[70 1]: /images/20220523/7ac26122d1cf447ca0a220a419008f7f.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ExOTk5MDQxMg_size_16_color_FFFFFF_t_70]: /images/20220523/c81d83688820413cb6948c749d889a16.png