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Numerical integration/Adaptive Simpson's method is a draft programming task. It is not yet considered ready to be promoted as a complete task, for reasons that should be found in its talk page.

Lychee (1969)'s Modified Adaptive Simpson's method (doi:10.1145/321526.321537) is a numerical quadrature method that recursively bisects the interval until the precision is high enough.

 ; Lychee's ASR, Modifications 1, 2, 3 procedure _quad_asr_simpsons(f, a, fa, b, fb) m := (a + b) / 2 fm := f(m) h := b - a return multiple [m, fm, (h / 6) * (f(a) + f(b) + 4*sum1 + 2*sum2)] procedure _quad_asr(f, a, fa, b, fb, tol, whole, m, fm, depth) lm, flm, left  := _quad_asr_simpsons(f, a, fa, m, fm) rm, frm, right := _quad_asr_simpsons(f, m, fm, b, fb) delta := left + right - whole tol' := tol / 2 if depth <= 0 or tol' == tol or abs(delta) <= 15 * tol: return left + right + delta / 15 else: return _quad_asr(f, a, fa, m, fm, tol', left , lm, flm, depth - 1) + _quad_asr(f, m, fm, b, fb, tol', right, rm, frm, depth - 1) procedure quad_asr(f, a, b, tol, depth) fa := f(a) fb := f(b) m, fm, whole := _quad_asr_simpsons(f, a, fa, b, fb) return _quad_asr(f, a, fa, b, fb, tol, whole, m, fm, depth)

## C

Translation of: zkl
#include <stdio.h>
#include <math.h>

typedef struct { double m; double fm; double simp; } triple;

/* "structured" adaptive version, translated from Racket */
triple _quad_simpsons_mem(double (*f)(double), double a, double fa, double b, double fb) {
// Evaluates Simpson's Rule, also returning m and f(m) to reuse.
double m = (a + b) / 2;
double fm = f(m);
double simp = fabs(b - a) / 6 * (fa + 4*fm + fb);
triple t = {m, fm, simp};
return t;
}

double _quad_asr(double (*f)(double), double a, double fa, double b, double fb, double eps, double whole, double m, double fm) {
// Efficient recursive implementation of adaptive Simpson's rule.
// Function values at the start, middle, end of the intervals are retained.
triple lt = _quad_simpsons_mem(f, a, fa, m, fm);
triple rt = _quad_simpsons_mem(f, m, fm, b, fb);
double delta = lt.simp + rt.simp - whole;
if (fabs(delta) <= eps * 15) return lt.simp + rt.simp + delta/15;
return _quad_asr(f, a, fa, m, fm, eps/2, lt.simp, lt.m, lt.fm) +
_quad_asr(f, m, fm, b, fb, eps/2, rt.simp, rt.m, rt.fm);
}

double quad_asr(double (*f)(double), double a, double b, double eps) {
// Integrate f from a to b using ASR with max error of eps.
double fa = f(a);
double fb = f(b);
triple t = _quad_simpsons_mem(f, a, fa, b, fb);
return _quad_asr(f, a, fa, b, fb, eps, t.simp, t.m, t.fm);
}

int main(){
double a = 0.0, b = 1.0;
double sinx = quad_asr(sin, a, b, 1e-09);
printf("Simpson's integration of sine from %g to %g = %f\n", a, b, sinx);
return 0;
}
Output:
Simpson's integration of sine from 0 to 1 = 0.459698

## Factor

Translation of: Julia
USING: formatting kernel locals math math.functions math.ranges
sequences ;
IN: rosetta-code.simpsons

:: simps ( f a b n -- x )
n even?
[ n "n must be even; %d was given" sprintf throw ] unless
b a - n / :> h
1 n 2 <range> 2 n 1 - 2 <range>
[ [ a + h * f call ] map-sum ] [email protected] [ 4 ] [ 2 ] bi*
[ * ] [email protected] a b [ f call ] [email protected] + + + h 3 / * ; inline

[ sin ] 0 1 100 simps
"Simpson's rule integration of sin from 0 to 1 is: %u\n" printf
Output:
Simpson's rule integration of sin from 0 to 1 is: 0.4596976941573994

## Go

Like the zkl entry, this is also a translation of the Python code in the Wikipedia article.

package main

import (
"fmt"
"math"
)

type F = func(float64) float64

/* "structured" adaptive version, translated from Racket */
func quadSimpsonsMem(f F, a, fa, b, fb float64) (m, fm, simp float64) {
// Evaluates Simpson's Rule, also returning m and f(m) to reuse.
m = (a + b) / 2
fm = f(m)
simp = math.Abs(b-a) / 6 * (fa + 4*fm + fb)
return
}

func quadAsrRec(f F, a, fa, b, fb, eps, whole, m, fm float64) float64 {
// Efficient recursive implementation of adaptive Simpson's rule.
// Function values at the start, middle, end of the intervals are retained.
lm, flm, left := quadSimpsonsMem(f, a, fa, m, fm)
rm, frm, right := quadSimpsonsMem(f, m, fm, b, fb)
delta := left + right - whole
if math.Abs(delta) <= eps*15 {
return left + right + delta/15
}
return quadAsrRec(f, a, fa, m, fm, eps/2, left, lm, flm) +
quadAsrRec(f, m, fm, b, fb, eps/2, right, rm, frm)
}

func quadAsr(f F, a, b, eps float64) float64 {
// Integrate f from a to b using ASR with max error of eps.
fa, fb := f(a), f(b)
m, fm, whole := quadSimpsonsMem(f, a, fa, b, fb)
return quadAsrRec(f, a, fa, b, fb, eps, whole, m, fm)
}

func main() {
a, b := 0.0, 1.0
sinx := quadAsr(math.Sin, a, b, 1e-09)
fmt.Printf("Simpson's integration of sine from %g to %g = %f\n", a, b, sinx)
}
Output:
Simpson's integration of sine from 0 to 1 = 0.459698

## J

Typically one would choose the library implementation:

NB. integrate returns definite integral and estimated digits of accuracy
1&o. integrate 0 1
0.459698 9

0.459698

Note'expected answer computed by j www.jsoftware.com'

1-&:(1&o.d._1)0
0.459698

translated from c
)

mp=: +/ .* NB. matrix product

NB. Evaluates Simpson's Rule, also returning m and f(m) to reuse.
'a fa b fb'=. y
em=. a ([ + [: -: -~) b
fm=. u em
simp=. ((| b - a) % 6) * 1 4 1 mp fa , fm , fb
em, fm, simp
)

Simp=: 1 :'2{m'
Fm=: 1 :'1{m'
M=: 1 :'0{m'

NB. Efficient recursive implementation of adaptive Simpson's rule.
NB. Function values at the start, middle, end of the intervals are retained.
'a fa b fb eps whole em fm'=. y
lt=. u uquad_simpsons_mem(a, fa, em, fm)
rt=. u uquad_simpsons_mem(em, fm, b, fb)
delta=. lt Simp + rt Simp - whole
if. (| delta) <: eps * 15 do.
lt Simp + rt Simp + delta % 15
else.
(a, fa, em, fm, (-: eps), lt Simp, lt M, lt Fm) +&(u uquad_asr) (em, fm, b, fb, (-: eps), rt Simp, rt M, rt Fm)
end.
)

NB. Integrate u from a to b using ASR with max error of eps.
'a b eps'=. y
fa=. u a
fb=. u b
t=. u uquad_simpsons_mem a, fa, b, fb
u uquad_asr a, fa, b, fb, eps, t Simp, t M, t Fm
)

echo 'Simpson''s integration of sine from 0 to 1 = ' , ": 1&o. quad_asr 0 1 1e_9
Simpson's integration of sine from 0 to 1 = 0.459698

## Java

import java.util.function.Function;

public static void main(String[] args) {
Function<Double,Double> f = x -> sin(x);
System.out.printf("integrate sin(x), x = 0 .. Pi = %2.12f. Function calls = %d%n", quadratureAdaptiveSimpsons(f, 0, Math.PI, 1e-8), functionCount);
functionCount = 0;
System.out.printf("integrate sin(x), x = 0 .. 1 = %2.12f. Function calls = %d%n", quadratureAdaptiveSimpsons(f, 0, 1, 1e-8), functionCount);
}

private static double quadratureAdaptiveSimpsons(Function<Double,Double> function, double a, double b, double error) {
double fa = function.apply(a);
double fb = function.apply(b);
}

private static double quadratureAdaptiveSimpsonsRecursive(Function<Double,Double> function, double a, double fa, double b, double fb, double error, double whole, double m, double fm) {
double delta = left.s + right.s - whole;
if ( Math.abs(delta) <= 15*error ) {
return left.s + right.s + delta / 15;
}
}

private static Triple quadratureAdaptiveSimpsonsOne(Function<Double,Double> function, double a, double fa, double b, double fb) {
double m = (a + b) / 2;
double fm = function.apply(m);
return new Triple(m, fm, Math.abs(b-a) / 6 * (fa + 4*fm + fb));
}

private static class Triple {
double x, fx, s;
private Triple(double m, double fm, double s) {
this.x = m;
this.fx = fm;
this.s = s;
}
}

private static int functionCount = 0;

private static double sin(double x) {
functionCount++;
return Math.sin(x);
}

}

Output:
integrate sin(x), x = 0 .. Pi = 1.999999999998.  Function calls = 121
integrate sin(x), x = 0 .. 1 = 0.459697694131.  Function calls = 33

## Julia

Originally from Modesto Mas, https://mmas.github.io/simpson-integration-julia

function simps(f::Function, a::Number, b::Number, n::Number)
iseven(n) || throw("n must be even, and \$n was given")
h = (b-a)/n
s = f(a) + f(b)
s += 4 * sum(f.(a .+ collect(1:2:n) .* h))
s += 2 * sum(f.(a .+ collect(2:2:n-1) .* h))
h/3 * s
end

println("Simpson's rule integration of sin from 0 to 1 is: ", simps(sin, 0.0, 1.0, 100))

Output:
Simpson's rule integration of sin from 0 to 1 is: 0.45969769415739936

## Kotlin

Translation of: Go
// Version 1.2.71

import kotlin.math.abs
import kotlin.math.sin

typealias F = (Double) -> Double
typealias T = Triple<Double, Double, Double>

/* "structured" adaptive version, translated from Racket */
fun quadSimpsonsMem(f: F, a: Double, fa: Double, b: Double, fb: Double): T {
// Evaluates Simpson's Rule, also returning m and f(m) to reuse
val m = (a + b) / 2
val fm = f(m)
val simp = abs(b - a) / 6 * (fa + 4 * fm + fb)
return T(m, fm, simp)
}

fun quadAsrRec(f: F, a: Double, fa: Double, b: Double, fb: Double,
eps: Double, whole: Double, m: Double, fm: Double): Double {
// Efficient recursive implementation of adaptive Simpson's rule.
// Function values at the start, middle, end of the intervals are retained.
val (lm, flm, left) = quadSimpsonsMem(f, a, fa, m, fm)
val (rm, frm, right) = quadSimpsonsMem(f, m, fm, b, fb)
val delta = left + right - whole
if (abs(delta) <= eps * 15) return left + right + delta / 15
return quadAsrRec(f, a, fa, m, fm, eps / 2, left, lm, flm) +
quadAsrRec(f, m, fm, b, fb, eps / 2, right, rm, frm)
}

fun quadAsr(f: F, a: Double, b: Double, eps: Double): Double {
// Integrate f from a to b using ASR with max error of eps.
val fa = f(a)
val fb = f(b)
val (m, fm, whole) = quadSimpsonsMem(f, a, fa, b, fb)
return quadAsrRec(f, a, fa, b, fb, eps, whole, m, fm)
}

fun main(args: Array<String>) {
val a = 0.0
val b = 1.0
val sinx = quadAsr(::sin, a, b, 1.0e-09)
println("Simpson's integration of sine from \$a to \$b = \${"%6f".format(sinx)}")
}
Output:
Simpson's integration of sine from 0.0 to 1.0 = 0.459698

## Nim

Direct translation of Python code from Wikipedia entry.

import math, sugar

type Func = float -> float

func quadSimpsonsMem(f: Func; a, fa, b, fb: float): tuple[m, fm, val: float] =
## Evaluates the Simpson's Rule, also returning m and f(m) to reuse
result.m = (a + b) / 2
result.fm = f(result.m)
result.val = abs(b - a) * (fa + 4 * result.fm + fb) / 6

func quadAsr(f: Func; a, fa, b, fb, eps, whole, m, fm: float): float =
## Efficient recursive implementation of adaptive Simpson's rule.
## Function values at the start, middle, end of the intervals are retained.
let (lm, flm, left) = f.quadSimpsonsMem(a, fa, m, fm)
let (rm, frm, right) = f.quadSimpsonsMem(m, fm, b, fb)
let delta = left + right - whole
result = if abs(delta) <= 15 * eps:
left + right + delta / 15
else:
f.quadAsr(a, fa, m, fm, eps / 2, left, lm, flm) +
f.quadAsr(m, fm, b, fb, eps / 2, right, rm, frm)

func quadAsr(f: Func; a, b, eps: float): float =
## Integrate f from a to b using Adaptive Simpson's Rule with max error of eps.
let fa = f(a)
let fb = f(b)
let (m, fm, whole) = f.quadSimpsonsMem(a, fa, b, fb)
result = f.quadAsr(a, fa, b, fb, eps, whole, m, fm)

echo "Simpson's integration of sine from 0 to 1 = ", sin.quadAsr(0, 1, 1e-9)
Output:
Simpson's integration of sine from 0 to 1 = 0.4596976941317859

## Perl

Translation of: Raku
use strict;
use warnings;

my(\$f, \$left, \$right, \$eps) = @_;
my \$lf = eval "\$f(\$left)";
my \$rf = eval "\$f(\$right)";
my (\$mid, \$midf, \$whole) = Simpson_quadrature_mid(\$f, \$left, \$lf, \$right, \$rf);
return recursive_Simpsons_asr(\$f, \$left, \$lf, \$right, \$rf, \$eps, \$whole, \$mid, \$midf);

my(\$g, \$l, \$lf, \$r, \$rf) = @_;
my \$mid = (\$l + \$r) / 2;
my \$midf = eval "\$g(\$mid)";
(\$mid, \$midf, abs(\$r - \$l) / 6 * (\$lf + 4 * \$midf + \$rf))
}

sub recursive_Simpsons_asr {
my(\$h, \$a, \$fa, \$b, \$fb, \$eps, \$whole, \$m, \$fm) = @_;
my (\$lm, \$flm, \$left) = Simpson_quadrature_mid(\$h, \$a, \$fa, \$m, \$fm);
my (\$rm, \$frm, \$right) = Simpson_quadrature_mid(\$h, \$m, \$fm, \$b, \$fb);
my \$delta = \$left + \$right - \$whole;
abs(\$delta) <= 15 * \$eps
? \$left + \$right + \$delta / 15
: recursive_Simpsons_asr(\$h, \$a, \$fa, \$m, \$fm, \$eps/2, \$left, \$lm, \$flm) +
recursive_Simpsons_asr(\$h, \$m, \$fm, \$b, \$fb, \$eps/2, \$right, \$rm, \$frm)
}
}

my (\$a, \$b) = (0, 1);
printf "Simpson's integration of sine from \$a to \$b = %.9f", \$sin
Output:
Simpson's integration of sine from 0 to 1 = 0.459697694

## Phix

Translation of: Go
function quadSimpsonsMem(integer f, atom a, fa, b, fb)
-- Evaluates Simpson's Rule, also returning m and f(m) to reuse.
atom m = (a + b) / 2,
fm = call_func(f,{m}),
simp = abs(b-a) / 6 * (fa + 4*fm + fb)
return {m, fm, simp}
end function

function quadAsrRec(integer f, atom a, fa, b, fb, eps, whole, m, fm)
-- Efficient recursive implementation of adaptive Simpson's rule.
-- Function values at the start, middle, end of the intervals are retained.
atom {lm, flm, left} := quadSimpsonsMem(f, a, fa, m, fm),
{rm, frm, rght} := quadSimpsonsMem(f, m, fm, b, fb),
delta := left + rght - whole
if abs(delta) <= eps*15 then
return left + rght + delta/15
end if
return quadAsrRec(f, a, fa, m, fm, eps/2, left, lm, flm) +
quadAsrRec(f, m, fm, b, fb, eps/2, rght, rm, frm)
end function

function quadAsr(integer f, atom a, b, eps)
-- Integrate f from a to b using ASR with max error of eps.
atom fa := call_func(f,{a}),
fb := call_func(f,{b}),
{m, fm, whole} := quadSimpsonsMem(f, a, fa, b, fb)
return quadAsrRec(f, a, fa, b, fb, eps, whole, m, fm)
end function

-- we need a mini wrapper to get a routine_id for sin()
-- (because sin() is implemented in low-level assembly)
function _sin(atom a)
return sin(a)
end function

atom a := 0.0, b := 1.0,
sinx := quadAsr(routine_id("_sin"), a, b, 1e-09)
printf(1,"Simpson's integration of sine from %g to %g = %f\n", {a, b, sinx})
Output:
Simpson's integration of sine from 0 to 1 = 0.459698

## Python

#! python3

'''
example

\$ python3 /tmp/integrate.py
Simpson's integration of sine from 0.0 to 1.0 = 0.4596976941317858

expected answer computed by j www.jsoftware.com

1-&:(1&o.d._1)0
0.459698

translated from c
'''

import math

import collections
triple = collections.namedtuple('triple', 'm fm simp')

def _quad_simpsons_mem(f: callable, a: float , fa: float, b: float, fb: float)->tuple:
'''
Evaluates Simpson's Rule, also returning m and f(m) to reuse.
'''

m = a + (b - a) / 2
fm = f(m)
simp = abs(b - a) / 6 * (fa + 4*fm + fb)
return triple(m, fm, simp,)

def _quad_asr(f: callable, a: float, fa: float, b: float, fb: float, eps: float, whole: float, m: float, fm: float)->float:
'''
Efficient recursive implementation of adaptive Simpson's rule.
Function values at the start, middle, end of the intervals are retained.
'''

lt = _quad_simpsons_mem(f, a, fa, m, fm)
rt = _quad_simpsons_mem(f, m, fm, b, fb)
delta = lt.simp + rt.simp - whole
return (lt.simp + rt.simp + delta/15
if (abs(delta) <= eps * 15) else
_quad_asr(f, a, fa, m, fm, eps/2, lt.simp, lt.m, lt.fm) +
_quad_asr(f, m, fm, b, fb, eps/2, rt.simp, rt.m, rt.fm)
)

def quad_asr(f: callable, a: float, b: float, eps: float)->float:
'''
Integrate f from a to b using ASR with max error of eps.
'''

fa = f(a)
fb = f(b)
t = _quad_simpsons_mem(f, a, fa, b, fb)
return _quad_asr(f, a, fa, b, fb, eps, t.simp, t.m, t.fm)

def main():
(a, b,) = (0.0, 1.0,)
sinx = quad_asr(math.sin, a, b, 1e-09);
print("Simpson's integration of sine from {} to {} = {}\n".format(a, b, sinx))

main()

## Raku

(formerly Perl 6)

Works with: Rakudo version 2018.10

Fairly direct translation of the Python code.

my \$lf = f(\$left);
my \$rf = f(\$right);
my (\$mid, \$midf, \$whole) = Simpson-quadrature-mid(&f, \$left, \$lf, \$right, \$rf);
return recursive-Simpsons-asr(&f, \$left, \$lf, \$right, \$rf, ε, \$whole, \$mid, \$midf);

sub Simpson-quadrature-mid(&g, \$l, \$lf, \$r, \$rf){
my \$mid = (\$l + \$r) / 2;
my \$midf = g(\$mid);
(\$mid, \$midf, (\$r - \$l).abs / 6 * (\$lf + 4 * \$midf + \$rf))
}

sub recursive-Simpsons-asr(&h, \$a, \$fa, \$b, \$fb, \$eps, \$whole, \$m, \$fm){
my (\$lm, \$flm, \$left) = Simpson-quadrature-mid(&h, \$a, \$fa, \$m, \$fm);
my (\$rm, \$frm, \$right) = Simpson-quadrature-mid(&h, \$m, \$fm, \$b, \$fb);
my \$delta = \$left + \$right - \$whole;
\$delta.abs <= 15 * \$eps
?? \$left + \$right + \$delta / 15
!! recursive-Simpsons-asr(&h, \$a, \$fa, \$m, \$fm, \$eps/2, \$left, \$lm, \$flm) +
recursive-Simpsons-asr(&h, \$m, \$fm, \$b, \$fb, \$eps/2, \$right, \$rm, \$frm)
}
}

my (\$a, \$b) = 0e0, 1e0;
say "Simpson's integration of sine from \$a to \$b = \$sin";
Output:
Simpson's integration of sine from 0 to 1 = 0.459697694

## REXX

Translation of: Go
/*REXX program performs numerical integration using adaptive Simpson's method.          */
numeric digits length( pi() ) - length(.) /*use # of digits in pi for precision. */
a= 0; b= 1; f= 'SIN' /*define values for A, B, and F. */
sinx= quadAsr('SIN',a,b,"1e" || (-digits() + 1) )
say "Simpson's integration of sine from " a ' to ' b ' = ' sinx
exit /*stick a fork in it, we're all done. */
/*──────────────────────────────────────────────────────────────────────────────────────*/
pi: pi= 3.14159265358979323846; return pi /*pi has twenty-one decimal digits. */
r2r: return arg(1) // (pi() *2) /*normalize radians ──► a unit circle, */
/*──────────────────────────────────────────────────────────────────────────────────────*/
quadSimp: procedure; parse arg f,a,fa,b,fb; m= (a+b) / 2; interpret 'fm=' f"(m)"
simp= abs(b-a) / 6 * (fa + 4*fm + fb); return m fm simp
/*──────────────────────────────────────────────────────────────────────────────────────*/
quadAsr: procedure; parse arg f,a,b,eps; interpret 'fa=' f"(a)"
interpret 'fb=' f"(b)"
parse value quadSimp(f,a,fa,b,fb) with m fm whole
/*──────────────────────────────────────────────────────────────────────────────────────*/
quadAsrR: procedure; parse arg f,a,fa,b,fb,eps,whole,m,fm; frac= digits() * 3 / 4
parse value quadSimp(f,a,fa,m,fm) with lm flm left
parse value quadSimp(f,m,fm,b,fb) with rm frm right
\$= left + right - whole /*calculate delta.*/
if abs(\$)<=eps*frac then return left + right + \$/frac
/*──────────────────────────────────────────────────────────────────────────────────────*/
sin: procedure; parse arg x; x= r2r(x); numeric fuzz min(5, max(1, digits() -3) )
if x=pi*.5 then return 1; if x==pi * 1.5 then return -1
if abs(x)=pi | x=0 then return 0
#= x; _= x; q= x*x
do k=2 by 2 until p=#; p= #; _= - _ * q / (k * (k+1) ); #= # + _
end /*k*/
return #
output   when using the default inputs:
Simpson's integration of sine from  0  to  1  =  0.459697694131860282602

## Sidef

Translation of: Raku

func quadrature_mid(l, lf, r, rf) {
var mid = (l+r)/2
var midf = f(mid)
(mid, midf, abs(r-l)/6 * (lf + 4*midf + rf))
}

func recursive_asr(a, fa, b, fb, ε, whole, m, fm) {
var (lm, flm, left) = quadrature_mid(a, fa, m, fm)
var (rm, frm, right) = quadrature_mid(m, fm, b, fb)
var Δ = (left + right - whole)
abs(Δ) <= 15*ε
? (left + right + Δ/15)
: (__FUNC__(a, fa, m, fm, ε/2, left, lm, flm) +
__FUNC__(m, fm, b, fb, ε/2, right, rm, frm))
}

var (lf = f(left), rf = f(right))
var (mid, midf, whole) = quadrature_mid(left, lf, right, rf)
recursive_asr(left, lf, right, rf, ε, whole, mid, midf)
}

var (a = 0, b = 1)
say "Simpson's integration of sine from #{a} to #{b} ≈ #{area}"
Output:
Simpson's integration of sine from 0 to 1 ≈ 0.45969769413186

## Wren

Translation of: Go
Library: Wren-fmt
import "/fmt" for Fmt

/* "structured" adaptive version, translated from Racket */
var quadSimpsonMem = Fn.new { |f, a, fa, b, fb|
// Evaluates Simpson's Rule, also returning m and f.call(m) to reuse.
var m = (a + b) / 2
var fm = f.call(m)
var simp = (b - a).abs / 6 * (fa + 4*fm + fb)
return [m, fm, simp]
}

quadAsrRec = Fn.new { |f, a, fa, b, fb, eps, whole, m, fm|
// Efficient recursive implementation of adaptive Simpson's rule.
// Function values at the start, middle, end of the intervals are retained.
var r1 = quadSimpsonMem.call(f, a, fa, m, fm)
var r2 = quadSimpsonMem.call(f, m, fm, b, fb)
var lm = r1[0]
var flm = r1[1]
var left = r1[2]
var rm = r2[0]
var frm = r2[1]
var right = r2[2]
var delta = left + right - whole
if (delta.abs < eps * 15) return left + right + delta/15
return quadAsrRec.call(f, a, fa, m, fm, eps/2, left, lm, flm) +
quadAsrRec.call(f, m, fm, b, fb, eps/2, right, rm, frm)
}

var quadAsr = Fn.new { |f, a, b, eps|
// Integrate f from a to b using ASR with max error of eps.
var fa = f.call(a)
var fb = f.call(b)
var r = quadSimpsonMem.call(f, a, fa, b, fb)
var m = r[0]
var fm = r[1]
var whole = r[2]
return quadAsrRec.call(f, a, fa, b, fb, eps, whole, m, fm)
}

var a = 0
var b = 1
var sinx = quadAsr.call(Fn.new { |x| x.sin }, a, b, 1e-09)
Fmt.print("Simpson's integration of sine from \$d to \$d = \$f", a, b, sinx)
Output:
Simpson's integration of sine from 0 to 1 = 0.459698

## zkl

Translation of: Python
# "structured" adaptive version, translated from Racket
#Evaluates the Simpson's Rule, also returning m and f(m) to reuse"""
m,fm := (a + b)/2, f(m);
return(m,fm, (b - a).abs()/6*(fa + fm*4 + fb));
}
fcn _quad_asr(f, a,fa, b,fb, eps, whole, m,fm){
# Efficient recursive implementation of adaptive Simpson's rule.
# Function values at the start, middle, end of the intervals are retained.

delta:=left + right - whole;
if(delta.abs() <= eps*15) return(left + right + delta/15);
_quad_asr(f, a,fa, m,fm, eps/2, left , lm,flm) +
_quad_asr(f, m,fm, b,fb, eps/2, right, rm,frm)
}