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参考文献

数値計算の基礎と応用[新訂版]
数値解析学への入門
杉浦 洋(南山大学教授) 著
発行日 2009/12/10

準備

オンラインコンパイラを使用します。

ソースコード

sample.c
#include <stdio.h>
#include <math.h>

#define M 7

void NewtonCoef(double xi[], int m, double b[]) {
    for (int n = 0; n <= m; n++) {
        b[n] = exp(xi[n]);
        for (int l = 0; l < n; l++) {
            b[n] = (b[n] - b[l]) / (xi[n] - xi[l]);
        }
    }
}

double p(double x, int n, double xi[], double b[]) {
    double y = b[n];
    for (int l = n - 1; l >= 0; l--) {
        y = (x - xi[l]) * y + b[l];
    }
    return y;
}

double f(double x) {
    return exp(x);
}

int main() {
    int m = M;
    double Pi = 3.14159265358979323846;
    double dt = Pi / (m + 1);
    double xi[M + 1];
    double b[M + 1];

    for (int i = 0; i <= m; i++) {
        xi[i] = 0.5 * exp(-pow((i + 0.5) * dt, 2));
    }

    NewtonCoef(xi, m, b);

    printf("degree=%d\n", m);
    int npoints = 10;
    double dx = 1.0 / npoints;

    for (int i = 0; i <= npoints; i++) {
        double x = -0.5 + i * dx;
        double y = p(x, m, xi, b);
        printf("p(%4.1f)=%17.10e error=%9.2e\n", x, y, y - f(x));
    }

    return 0;
}


実行結果

console
degree=7
p(-0.5)= 6.0653008427e-01 error=-5.75e-07
p(-0.4)= 6.7031991139e-01 error=-1.35e-07
p(-0.3)= 7.4081819865e-01 error=-2.20e-08
p(-0.2)= 8.1873075113e-01 error=-1.95e-09
p(-0.1)= 9.0483741799e-01 error=-4.42e-11
p( 0.0)= 1.0000000000e+00 error= 0.00e+00
p( 0.1)= 1.1051709181e+00 error= 4.88e-13
p( 0.2)= 1.2214027582e+00 error=-2.07e-12
p( 0.3)= 1.3498588075e+00 error=-5.23e-11
p( 0.4)= 1.4918246978e+00 error= 1.84e-10
p( 0.5)= 1.6487212700e+00 error=-6.51e-10

[Execution complete with exit code 0]
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