A javascript code for Romberg integration

As I am writing backend JavaScript for simulations in teaching Numerical Methods, I have also started developing some functions for some numerical techniques. Here is a function for Romberg integration.

function auto_integrator_trap_romb_hnm(func,a,b,nmax,tol_ae,tol_rae)
// func=integrand
// a= lower limit of integration
// b= upper limit of integration
// nmax = number of partitions, n=2^nmax
// tol_ae= maximum absolute approximate error acceptable (should be >=0)
// tol_rae=maximum absolute relative approximate error acceptable (should be >=0)
// integ_value= estimated value of integral

//Checking for input errors
	if (typeof a !== 'number') 
		  throw new TypeError('<a> must be a number');
    if (typeof b !== 'number') 
		  throw new TypeError('<b> must be a number');
    if ((!Number.isInteger(nmax)) || (nmax<1))
		  throw new TypeError('<nmax> must be an integer greater than or equal to one.');
	if ((typeof tol_ae !== 'number') || (tol_ae<0)) 
		  throw new TypeError('<tole_ae> must be a number greater than or equal to zero');
	if ((typeof tol_rae !== 'number') || (tol_rae<=0)) 
		  throw new TypeError('<tole_ae> must be a number greater than or equal to zero');
	var h=b-a
	// initialize matrix where the values of integral are stored
	var Romb = []; // rows
	for (var i = 0; i < nmax+1; i++) 
		for (var j = 0; j < nmax+1; j++) 
	//calculating the value with 1-segment trapezoidal rule
	var integ_val=Romb[0][0]
	for (var i=1; i<=nmax; i++)
	// updating the value with double the number of segments
	// by only using the values where they need to be calculated
	// See https://blog.autarkaw.com/2009/02/28/an-efficient-formula-for-an-automatic-integrator-based-on-trapezoidal-rule/
		var integ=0
		for (var j=1; j<=2**i-1; j+=2)
			var integ=integ+func(a+j*h)
		// Using Romberg method to calculate next extrapolatable value
		// See https://young.physics.ucsc.edu/115/romberg.pdf
		for (k=1; k<=i; k++)
			var addterm=Romb[i][k-1]-Romb[i-1][k-1]

			//Calculating absolute approximate error
			var Ea=math.abs(Romb[i][k]-Romb[i][k-1])
			//Calculating absolute relative approximate error
			var epsa=math.abs(Ea/Romb[i][k])*100.0
			//Assigning most recent value to the return variable
			// returning the value if either tolerance is met
			if ((epsa<tol_rae) || (Ea<tol_ae))
	// returning the last calculated value of integral whether tolerance is met or not

Here we are testing it for a typical integrand of f(x)=1/x. Take it for a spin and see how well it works. Make it even better.

<!DOCTYPE html>
<meta content="text/html;charset=utf-8" http-equiv="Content-Type">
<meta content="utf-8" http-equiv="encoding">
	<title>A test for the automatic integrator based on Romberg integration and trapezoidal rule</title>
// This program is written to test the romberg integration scheme that is used
// as an automatic integrator
// a= lower limit of integration
// b= upper limit of integraton
// nmax= number of partitions, segment is then 2^nmax 
// tol_ae= tolerance on absolute approximate error 
// tol_rae=tolerance on percentage absolute relative approximate error 
var a=0.001
var b=10
var nmax=20
var tol_ea=0.0
var tol_rae=0.0000000005

var abc=auto_integrator_trap_romb_hnm(func,a,b,nmax,tol_ea,tol_rae)
console.log("romberg "+abc)

var exact=math.log(b)-math.log(a)
console.log("exact "+exact)
function func(x)
   //var pi=4*math.atan(1.0)
   //var val=2/math.sqrt(pi)*math.exp(-x*x)
   var val=1/x


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