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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.py
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt  # グラフ描画のために追加

def p(x, n, xi, b):
    y = b[n]
    for l in range(n-1, -1, -1):
        y = (x - xi[l]) * y + b[l]
    return y

def f(x):
    return np.exp(x)

def NewtonCoef(xi, m, b):
    for n in range(m+1):
        b[n] = f(xi[n])
        for l in range(n):
            b[n] = (b[n] - b[l]) / (xi[n] - xi[l])
    return 0

def main():
    m = 7
    Pi = np.pi
    dt = Pi / (m + 1)
    xi=[0.5*(i+0.5)**dt for i in range(m+1)]
    b = [0] * (m+1)
    NewtonCoef(xi, m, b)
    print("degree={}".format(m))
    npoints = 10  # グラフ描画のために点数を増やす
    dx = 1.0 / npoints
    x_vals = []
    y_vals = []
    y_actual = []
    for i in range(npoints+1):
        x = -0.5 + i * dx
        y = p(x, m, xi, b)
        x_vals.append(x)
        y_vals.append(y)
        y_actual.append(f(x))
        print("p({:4.1f})={:17.10e} error={:9.2e}".format(x, y, y - f(x)))
    
    # グラフ描画
    plt.plot(x_vals, y_vals, label='Polynomial Approximation')
    plt.plot(x_vals, y_actual, label='Actual exp(x)', linestyle='dashed')
    plt.legend()
    plt.xlabel('x')
    plt.ylabel('y')
    plt.title('Polynomial Approximation vs Actual exp(x)')
    plt.show()

main()




実行結果

console
degree=7
p(-0.5)= 6.0614600182e-01 error=-3.85e-04
p(-0.4)= 6.7011869962e-01 error=-2.01e-04
p(-0.3)= 7.4071916923e-01 error=-9.91e-05
p(-0.2)= 8.1868559326e-01 error=-4.52e-05
p(-0.1)= 9.0481871138e-01 error=-1.87e-05
p( 0.0)= 9.9999316793e-01 error=-6.83e-06
p( 0.1)= 1.1051688255e+00 error=-2.09e-06
p( 0.2)= 1.2214022713e+00 error=-4.87e-07
p( 0.3)= 1.3498587431e+00 error=-6.45e-08
p( 0.4)= 1.4918247010e+00 error= 3.32e-09
p( 0.5)= 1.6487212731e+00 error= 2.41e-09


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