Interpolation Error

In [1]:
import numpy as np
import numpy.linalg as la
import matplotlib.pyplot as pt

Let's fix a function to interpolate:

In [2]:
if 1:
    def f(x):
        return np.exp(1.5*x)
elif 0:
    def f(x):
        return np.sin(20*x)
    def f(x):
        return (x>=0.5).astype(
In [3]:
x_01 = np.linspace(0, 1, 1000)
pt.plot(x_01, f(x_01))
[<matplotlib.lines.Line2D at 0x7fc031aad908>]

And let's fix some parameters. Note that the interpolation interval is just $[0,h]$, not $[0,1]$!

In [4]:
degree = 1
h = 1

nodes = 0.5 + np.linspace(-h/2, h/2, degree+1)
array([ 0.,  1.])

Now build the Vandermonde matrix:

In [5]:
V = np.array([
    for i in range(degree+1)
In [6]:
array([[ 1.,  0.],
       [ 1.,  1.]])

Now find the interpolation coefficients as coeffs:

In [7]:
coeffs = la.solve(V, f(nodes))

Here are some points. Evaluate the interpolant there:

In [8]:
x_0h = 0.5+np.linspace(-h/2, h/2, 1000)
In [9]:
interp_0h = 0*x_0h
for i in range(degree+1):
    interp_0h += coeffs[i] * x_0h**i

Now plot the interpolant with the function:

In [10]:
pt.plot(x_01, f(x_01), "--", color="gray", label="$f$")
pt.plot(x_0h, interp_0h, color="red", label="Interpolant")
pt.plot(nodes, f(nodes), "or")
<matplotlib.legend.Legend at 0x7fc031a4c6d8>

Also plot the error:

In [11]:
error = interp_0h - f(x_0h)

pt.plot(x_0h, error)

print("Max error: %g" % np.max(np.abs(error)))
Max error: 0.633384

  • What does the error look like? (Approximately)
  • How will the error react if we shrink the interval?
  • What will happen if we increase the polynomial degree?