Newton's method in 1D

Copyright (C) 2020 Andreas Kloeckner

MIT License Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
In [28]:
import numpy as np
import matplotlib.pyplot as pt

Here's a function:

In [29]:
a = 17.09
b = 9.79
c = 0.6317
d = 0.9324
e = 0.4565

def f(x):
    return a*x**4 + b*x**3 + c*x**2 + d*x + e

def df(x):
    return 4*a*x**3 + 3*b*x**2 + 2*c*x + d

def d2f(x):
    return 3*4*a*x**2 + 2*3*b*x + 2*c

Let's plot the thing:

In [30]:
xmesh = np.linspace(-1, 0.5
                    , 100)
pt.ylim([-1, 3])
pt.plot(xmesh, f(xmesh))
Out[30]:
[<matplotlib.lines.Line2D at 0x7f3774d78cf8>]

Let's fix an initial guess:

In [31]:
x = 0.3
In [32]:
dfx = df(x)
d2fx = d2f(x)

# carry out the Newton step
xnew = x - dfx / d2fx

# plot approximate function
pt.plot(xmesh, f(xmesh))
pt.plot(xmesh, f(x) + dfx*(xmesh-x) + d2fx*(xmesh-x)**2/2)
pt.plot(x, f(x), "o", color="red")
pt.plot(xnew, f(xnew), "o", color="green")
pt.ylim([-1, 3])

# update
x = xnew
print(x)

0.14466962664624314
  • What convergence order does this method achieve?
In [33]:
# Quadratic, because it's just like doing 'equation-solving Newton' on f'.