[R] Double integration - Gauss Quadrature
Earl F. Glynn
efg at stowers-institute.org
Mon Sep 29 18:43:46 CEST 2008
"Susanne Pfeifer" <tiffy at tiffy.it> wrote in message
news:48DE3BE0.5020200 at tiffy.it...
> Hi,
>
> I would like to solve a double integral of the form
. . .
> but I would like to use Gauss Quadrature to do it.
> I have written the following code (using R's statmod package) which
> works fine for one integral but it doesn't work for a double one:
Maybe there's some way to use sapply as your code suggests, but I'm not sure
where you defined the $value that is being returned in your inner call:
gauss_legendre(function(x) x*y, 0, 1, nodes, weights)$value
I converted some old IDL code to do this 2D integral but without trying to
use your sapply:
# For N=5, see "known" values here:
# http://mathworld.wolfram.com/Legendre-GaussQuadrature.html
library(statmod)
N <- 5
GL <- gauss.quad(N)
nodes <- GL$nodes
weights <- GL$weights
##############################################
# 1D Gauss-Legendre
gauss_legendre <- function(f, a, b, nodes, weights)
{
C <- (b - a) / 2
D <- (b + a) / 2
sum <- 0.0
for (i in 1:length(nodes))
{
sum <- sum + weights[i] * f(nodes[i]*C + D)
}
return(C * sum)
}
##############################################
gauss_legendre2D_helper <- function(f, x, a2,b2, nodes, weights)
{
C <- (b2 - a2) / 2
D <- (b2 + a2) / 2
sum <- 0.0
for (i in 1:length(nodes))
{
y <- nodes[i]*C + D
sum <- sum + weights[i] * f(x,y)
}
return(C * sum)
}
gauss_legendre2D <- function(f, a1,b1, a2,b2, nodes, weights)
{
C <- (b1 - a1) / 2
D <- (b1 + a1) / 2
sum <- 0.0
for (i in 1:length(nodes))
{
x <- nodes[i]*C + D
sum <- sum + weights[i] * gauss_legendre2D_helper(f, x, a2, b2, nodes,
weights)
}
return(C * sum)
}
##############################################
# 1D Test:
gauss_legendre(function(x) {x}, 0.0, 1.0, nodes, weights)
# 2D Test:
gauss_legendre2D(function(x,y) {x*y}, 0.0, 1.0, 0.0, 1.0, nodes, weights)
# Minimal testing here:
> # 1D Test:
> gauss_legendre(function(x) {x}, 0.0, 1.0, nodes, weights)
[1] 0.5
>
> # 2D Test:
> gauss_legendre2D(function(x,y) {x*y}, 0.0, 1.0, 0.0, 1.0, nodes, weights)
[1] 0.25
BTW: I don't think you need N as large as you're using. The advantage of
Gauss-Legendre quadrature is fairly high precision without that many
function evaluations.
Formulas for those who may be interested:
1D Gauss-Legendre Quadrature
2D Gauss-Legendre Quadrature
This can be extended to a 3D integral evaluations, too.
efg
Earl F Glynn
Scientific Programmer
Stowers Institute for Medical Research
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