CompEcon Toolbox:
DemQua08
Illustrates integration using Simpson's rule
Randall Romero Aguilar, PhD

This demo is based on the original Matlab demo accompanying the Computational Economics and Finance 2001 textbook by Mario Miranda and Paul Fackler.

Last updated: 2020-Sep-10

In [ ]:
if 'google.colab' in str(get_ipython()):
print("This notebook is running on Google Colab. Installing the compecon package.")
!pip install compecon

In [ ]:
from numpy import poly1d,polyfit, linspace, array
from compecon import qnwsimp, demo
import matplotlib.pyplot as plt

In [ ]:
n = 1001
xmin, xmax = -1, 1
xwid = xmax-xmin
x = linspace(xmin, xmax, n)

In [ ]:
f = poly1d([2.0, -1.0, 0.5, 5.0])

In [ ]:
def fitquad(xi):
newcoef = polyfit(xi, f(xi), 2)
return poly1d(newcoef)

In [ ]:
def plot_simp(n):
xi, wi = qnwsimp(n+1, xmin, xmax)

fig, ax = plt.subplots()
ax.plot(x, f(x), linewidth=3)

for k in range(n//2):
xii = xi[(2*k):(2*k+3)]
xiii = linspace(xii[0], xii[2], 125)
ax.fill_between(xiii, p(xiii), alpha=0.35, color='LightSkyBlue')
ax.plot(xiii, p(xiii),color='Tab:Orange', linestyle='--')

plt.vlines(xi, 0, f(xi),'k', linestyle=':')
plt.hlines(0,xmin-0.1, xmax+0.1,'k',linewidth=2)
plt.xlim(xmin-0.1, xmax+0.1)
xtl = ['$x_{%d}$' % i for i in range(n+1)]
xtl[0] += '=a'
xtl[n] += '=b'
plt.xticks(xi, xtl)
plt.yticks([0],['0'])
plt.legend([r'$f(x)$', f'$\\tilde{{f}}_{n+1}(x)$'])
return fig

In [ ]:
def plot_simp(n):
xi, wi = qnwsimp(n+1, xmin, xmax)

fig, ax = plt.subplots()
ax.plot(x, f(x), linewidth=3)

for k in range(n//2):
xii = xi[(2*k):(2*k+3)]
xiii = linspace(xii[0], xii[2], 125)
ax.fill_between(xiii, p(xiii), alpha=0.35, color='LightSkyBlue')
ax.plot(xiii, p(xiii), color='Tab:Orange', linestyle='--')

ax.vlines(xi, 0, f(xi), color='Tab:Orange', linestyle=':')
ax.axhline(0,color='k',linewidth=2)

xtl = [f'$x_{i}$' for i in range(n+1)]
xtl[0] += '=a'
xtl[n] += '=b'

ax.set(xlim=[xmin-0.1, xmax+0.1], xticks=xi, xticklabels=xtl,
yticks=[0], yticklabels=['0'])

plt.legend([r'$f(x)$', f'$\\tilde{{f}}_{n+1}(x)$'])
return fig

figs = [plot_simp(n) for n in [2, 4, 8]]
#demo.savefig(figs,name='demqua08')