Averages/Root mean square

Averages/Root mean square
You are encouraged to solve this task according to the task description, using any language you may know.

Compute the Root mean square of the numbers 1..10.

The root mean square is also known by its initial RMS (or rms), and as the quadratic mean.

The RMS is calculated as the mean of the squares of the numbers, square-rooted:

$x_{\mathrm{rms}} = \sqrt {{{x_1}^2 + {x_2}^2 + \cdots + {x_n}^2} \over n}.$

Cf. Averages/Pythagorean means

Ada

with Ada.Float_Text_IO; use Ada.Float_Text_IO;
with Ada.Numerics.Elementary_Functions;
use Ada.Numerics.Elementary_Functions;
procedure calcrms is
	type float_arr is array(1..10) of Float;
 
	function rms(nums : float_arr) return Float is
		sum : Float := 0.0;
		begin
		for p in nums'Range loop
			sum := sum + nums(p)**2;
		end loop;
		return sqrt(sum/Float(nums'Length));
	end rms;
 
	list : float_arr;
begin
list := (1.0,2.0,3.0,4.0,5.0,6.0,7.0,8.0,9.0,10.0);
put( rms(list) , Exp=>0);
end calcrms;

Output:

 6.20484

ALGOL 68

Works with: ALGOL 68 version Standard - no extensions to language used

Works with: ALGOL 68G version Any - tested with release 1.18.0-9h.tiny

Works with: ELLA ALGOL 68 version Any (with appropriate job cards)

# Define the rms PROCedure & ABS OPerators for LONG... REAL #
MODE RMSFIELD = #LONG...# REAL;
PROC (RMSFIELD)RMSFIELD rms field sqrt = #long...# sqrt;
INT rms field width = #long...# real width;
 
PROC crude rms = ([]RMSFIELD v)RMSFIELD: (
  RMSFIELD sum := 0;
  FOR i FROM LWB v TO UPB v DO sum +:= v[i]**2 OD;
  rms field sqrt(sum / (UPB v - LWB v + 1))
);
 
PROC rms = ([]RMSFIELD v)RMSFIELD: (
# round off error accumulated at standard precision #
  RMSFIELD sum := 0, round off error:= 0;
  FOR i FROM LWB v TO UPB v DO 
    RMSFIELD org = sum, prod = v[i]**2;
    sum +:= prod;
    round off error +:= sum - org - prod
  OD;
  rms field sqrt((sum - round off error)/(UPB v - LWB v + 1))
);
 
main: (
  []RMSFIELD one to ten = (1,2,3,4,5,6,7,8,9,10);
 
  print(("crude rms(one to ten): ", crude rms(one to ten), new line));
  print(("rms(one to ten): ",       rms(one to ten), new line))
)

Output:

crude rms(one to ten): +6.20483682299543e  +0
rms(one to ten): +6.20483682299543e  +0

APL

 rms←{((+/⍵*2)÷⍴⍵)*0.5}
 x←⍳10
 
 rms x
6.204836823

AutoHotkey

Using a loop

MsgBox, % RMS(1, 10)
 
 
;---------------------------------------------------------------------------
RMS(a, b) { ; Root Mean Square of integers a through b
;---------------------------------------------------------------------------
    n := b - a + 1
    Loop, %n%
        Sum += (a + A_Index - 1) ** 2
    Return, Sqrt(Sum / n)
}

Message box shows:

6.204837

Avoiding a loop

Using these equations:
$\sum_{i=1}^n i^2 = \frac{n(n+1)(2n+1)}{6}$ See wp:List of mathematical series

for a < b : $\sum_{i=a}^b i^2 = \sum_{i=1}^b i^2 - \sum_{i=1}^{a-1} i^2$

We can show that:
$\sum_{i=a}^b i^2 = \frac{b(b+1)(2b+1)-a(a-1)(2a-1)}{6}$

MsgBox, % RMS(1, 10)
 
 
;---------------------------------------------------------------------------
RMS(a, b) { ; Root Mean Square of integers a through b
;---------------------------------------------------------------------------
    Return, Sqrt((b*(b+1)*(2*b+1)-a*(a-1)*(2*a-1))/6/(b-a+1))
}

Message box shows:

6.204837

AWK

#!/usr/bin/awk -f
# computes RMS of the 1st column of a data file
{
    x  = $1;   # value of 1st column
    S += x*x;  
    N++;
}
 
END {
   print "RMS: ",sqrt(S/N);
}

BBC BASIC

      DIM array(9)
      array() = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
 
      PRINT FNrms(array())
      END
 
      DEF FNrms(a()) = MOD(a()) / SQR(DIM(a(),1)+1)

C

#include <stdio.h>
#include <math.h>
 
double rms(double *v, int n)
{
  int i;
  double sum = 0.0;
  for(i = 0; i < n; i++)
    sum += v[i] * v[i];
  return sqrt(sum / n);
}
 
int main(void)
{
  double v[] = {1., 2., 3., 4., 5., 6., 7., 8., 9., 10.};
  printf("%f\n", rms(v, sizeof(v)/sizeof(double)));
  return 0;
}

C#

using System;
 
namespace rms
{
    class Program
    {
        static void Main(string[] args)
        {
            int[] x = new int[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
            Console.WriteLine(rootMeanSquare(x));
        }
 
        private static double rootMeanSquare(int[] x)
        {            
            double sum = 0;
            for (int i = 0; i < x.Length; i++)
            {
                sum += (x[i]*x[i]);
            }
            return Math.Sqrt(sum / x.Length);
        }
    }
}

An alternative method demonstrating the more functional style introduced by LINQ and lambda expressions in C# 3.

Works with: C# version 3

using System;
using System.Collections.Generic;
using System.Linq;
 
namespace rms
{
    class Program
    {
        static void Main(string[] args)
        {
            Console.WriteLine(rootMeanSquare(Enumerable.Range(1, 10)));
        }
 
        private static double rootMeanSquare(IEnumerable<int> x)
        {
            return Math.Sqrt((double)x.Sum(n => n * n) / x.Count());
        }
    }
}

C++

#include <iostream>
#include <vector>
#include <cmath>
#include <numeric>
 
int main( ) {
  std::vector<int> numbers ;
  for ( int i = 1 ; i < 11 ; i++ )
    numbers.push_back( i ) ;
  double meansquare = sqrt ( ( std::inner_product( numbers.begin(), numbers.end(), numbers.begin(), 0 ))/10.0 );
  std::cout << "The quadratic mean of the numbers 1 .. 10 is " << meansquare << " !\n" ;
  return 0 ;
}

Output:

The quadratic mean of the numbers 1 .. 10 is 6.20484 !

Clojure

(use '[clojure.contrib.math :only (sqrt)])
 
(defn rms [xs]
  (sqrt (/ (reduce + (map #(* % %) xs))
	   (count xs))))
 
(println (rms (range 1 11)))

Output:

6.2048368229954285

CoffeeScript

Translation of: JavaScript

    root_mean_square = (ary) ->
        sum_of_squares = ary.reduce ((s,x) -> s + x*x), 0
        return Math.sqrt(sum_of_squares / ary.length)
 
    alert root_mean_square([1..10])

Common Lisp

(loop for x from 1 to 10
      for xx = (* x x)
      for n from 1
      summing xx into xx-sum
      finally (return (sqrt (/ xx-sum n)))))

D

import std.stdio, std.math, std.algorithm, std.range;
 
real rms(R)(R d) {
  return sqrt(reduce!((a, b) => a + b * b)(d) / cast(real)d.length);
}
 
void main() {
  writefln("%.19f", rms(iota(1, 11)));
}

Output:

6.2048368229954282979

Delphi/Pascal

program AveragesMeanSquare;
 
{$APPTYPE CONSOLE}
 
uses Types;
 
function MeanSquare(aArray: TDoubleDynArray): Double;
var
  lValue: Double;
begin
  Result := 0;
 
  for lValue in aArray do
    Result := Result + (lValue * lValue);
  if Result > 0 then
    Result := Sqrt(Result / Length(aArray));
end;
 
begin
  Writeln(MeanSquare(TDoubleDynArray.Create()));
  Writeln(MeanSquare(TDoubleDynArray.Create(1,2,3,4,5,6,7,8,9,10)));
end.

E

Using the same generic mean function as used in pythagorean means:

def makeMean(base, include, finish) {
    return def mean(numbers) {
        var count := 0
        var acc := base
        for x in numbers {
            acc := include(acc, x)
            count += 1
        }
        return finish(acc, count)
    }
}
 
def RMS := makeMean(0, fn b,x { b+x**2 }, fn acc,n { (acc/n).sqrt() })

? RMS(1..10)
# value: 6.2048368229954285

Erlang

rms(Nums) ->
    math:sqrt(lists:foldl(fun(E,S) -> S+E*E end, 0, Nums) / length(Nums)).
 
rms([1,2,3,4,5,6,7,8,9,10]).

Output:

6.2048368229954285

Euphoria

function rms(sequence s)
    atom sum
    if length(s) = 0 then
        return 0
    end if
    sum = 0
    for i = 1 to length(s) do
        sum += power(s[i],2)
    end for
    return sqrt(sum/length(s))
end function
 
constant s = {1,2,3,4,5,6,7,8,9,10}
? rms(s)

Output:

6.204836823

F#

Uses a lambda expression and function piping.

let RMS (x:float list) : float = List.map (fun y -> y**2.0) x |> List.average |> System.Math.Sqrt
 
let res = RMS [1.0..10.0]

Answer (in F# Interactive window):

val res : float = 6.204836823

Fantom

class Main
{
  static Float averageRms (Float[] nums)
  {
    if (nums.size == 0) return 0.0f
    Float sum := 0f
    nums.each { sum += it * it }
    return (sum / nums.size.toFloat).sqrt
  }
 
  public static Void main ()
  {
    a := [1f,2f,3f,4f,5f,6f,7f,8f,9f,10f]
    echo ("RMS Average of $a is: " + averageRms(a))
  }
}

Factor

: root-mean-square ( seq -- mean )
    [ [ sq ] map-sum ] [ length ] bi / sqrt ;

( scratchpad ) 10 [1,b] root-mean-square .
6.204836822995428

Forth

: rms ( faddr len -- frms )
  dup >r 0e
  floats bounds do
    i f@ fdup f* f+
  float +loop
  r> s>f f/ fsqrt ;
 
create test 1e f, 2e f, 3e f, 4e f, 5e f, 6e f, 7e f, 8e f, 9e f, 10e f,
test 10 rms f.    \ 6.20483682299543

Fortran

Assume x stored in array x.

print *,sqrt( sum(x**2)/size(x) )

Go

package main
 
import (
    "fmt"
    "math"
)
 
func main() {
    sum := 0.
    for n := 1.; n <= 10; n++ {
        sum += n*n
    }
    fmt.Println(math.Sqrt(sum/10))
}

Groovy

Solution:

def quadMean = { list ->
    list == null \
        ? null \
        : list.empty \
            ? 0 \
            : ((list.collect { it*it }.sum()) / list.size()) ** 0.5
}

Test:

def list = 1..10
def Q = quadMean(list)
println """
list: ${list}
   Q: ${Q}
"""

Output:

list: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
   Q: 6.2048368229954285

Haskell

Given the mean function defiend in Averages/Pythagorean means:

main = print $ mean 2 [1 .. 10]

HicEst

sum = 0
DO i = 1, 10
   sum = sum + i^2
ENDDO
WRITE(ClipBoard) "RMS(1..10) = ", (sum/10)^0.5 

RMS(1..10) = 6.204836823

Icon and Unicon

procedure main()
every put(x := [], 1 to 10)
writes("x := [ "); every writes(!x," "); write("]")
write("Quadratic mean:",q := qmean!x)
end

procedure qmean(L[])             #: quadratic mean
   local m
   if *L = 0 then fail
   every (m := 0.0) +:= !L^2
   return sqrt(m / *L)
end

Io

rms := method (figs, (figs map(** 2) reduce(+) / figs size) sqrt)
 
rms( Range 1 to(10) asList ) println

J

Solution:

rms=: (+/ % #)&.:*:

Example Usage:

  rms 1 + i. 10
6.20484

*: means square

(+/ % #) is an idiom for mean.

&.: means under -- in other words, we square numbers, take their average and then use the inverse of square on the result. (see also the page on &. which does basically the same thing but with different granularity -- item at a time instead of everything at once.

Java

public class RMS {
    public static double rms(double[] nums){
        double ms = 0;
        for (int i = 0; i < nums.length; i++)
            ms += nums[i] * nums[i];
        ms /= nums.length;
        return Math.sqrt(ms);
    }
 
    public static	void main(String[] args){
        double[] nums = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0};
        System.out.println("The RMS of the numbers from 1 to 10 is " + rms(nums));
    }
}

Output:

The RMS of the numbers from 1 to 10 is 6.2048368229954285

JavaScript

Works with: JavaScript version 1.8

,

Works with: Firefox version 3.0

function root_mean_square(ary) {
    var sum_of_squares = ary.reduce(function(s,x) {return (s + x*x)}, 0);
    return Math.sqrt(sum_of_squares / ary.length);
}
 
print( root_mean_square([1,2,3,4,5,6,7,8,9,10]) ); // ==> 6.2048368229954285

Liberty BASIC

'   [RC] Averages/Root mean square
 
    SourceList$     ="1 2 3 4 5 6 7 8 9 10"
 
    '   If saved as an array we'd have to have a flag for last data.
    '   LB has the very useful word$() to read from delimited strings.
    '   The default delimiter is a space character, " ".
 
    SumOfSquares    =0
    n               =0      '   This holds index to number, and counts number of data.
    data$           ="666"  '   temporary dummy to enter the loop.
 
    while data$ <>""                                '   we loop until no data left.
        data$           =word$( SourceList$, n +1)  '   first data, as a string
        NewVal          =val( data$)                '   convert string to number
        SumOfSquares    =SumOfSquares +NewVal^2     '   add to existing sum of squares
        n =n +1                                     '   increment number of data items found
    wend
 
    n =n -1
 
    print "Supplied data was ";         SourceList$
    print "This contained ";            n; " numbers."
    print "R.M.S. value is ";           ( SumOfSquares /n)^0.5
 
    end

Logo

to rms :v
  output sqrt quotient (apply "sum map [? * ?] :v) count :v
end
 
show rms iseq 1 10

Lua

function sumsq(a, ...) return a and a^2 + sumsq(...) or 0 end
function rms(t) return (sumsq(unpack(t)) / #t)^.5 end
 
print(rms{1, 2, 3, 4, 5, 6, 7, 8, 9, 10})

Mathematica

RootMeanSquare@Range[10]

MATLAB

function rms = quadraticMean(list)    
    rms = sqrt(mean(list.^2));
end

Solution:

>> quadraticMean((1:10))
 
ans =
 
   6.204836822995429

Maxima

L: makelist(i, i, 1, 10)$
 
rms(L) := sqrt(lsum(x^2, x, L)/length(L))$
 
rms(L), numer;   /* 6.204836822995429 */

Nemerle

using System;
using System.Console;
using System.Math;
 
module RMS
{
    RMS(x : list[int]) : double
    {
        def sum = x.Map(fun (x) {x*x}).FoldLeft(0, _+_);
        Sqrt((sum :> double) / x.Length)
    }
 
    Main() : void
    {
        WriteLine("RMS of [1 .. 10]: {0:g6}", RMS($[1 .. 10]));
    }
}

Objeck

bundle Default {
  class Hello {
    function : Main(args : String[]) ~ Nil {
      values := [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0];
      RootSquareMean(values)->PrintLine();
    }
 
    function : native : RootSquareMean(values : Float[]) ~ Float {
      sum := 0.0;
      each(i : values) {
        x := values[i]->Power(2.0);
        sum += values[i]->Power(2.0);
      };
 
      return (sum / values->Size())->SquareRoot();
    }
  }
}

OCaml

let rms a =
  sqrt (Array.fold_left (fun s x -> s +. x*.x) 0.0 a /.
        float_of_int (Array.length a))
;;
 
rms (Array.init 10 (fun i -> float_of_int (i+1))) ;;
(* 6.2048368229954285 *)

Oz

declare
  fun {Square X} X*X end
 
  fun {RMS Xs}
     {Sqrt
      {Int.toFloat {FoldL {Map Xs Square} Number.'+' 0}}
      /
      {Int.toFloat {Length Xs}}}
  end
in 
  {Show {RMS {List.number 1 10 1}}}

Output:

6.2048

PARI/GP

General RMS calculation:

RMS(v)={
  sqrt(sum(i=1,#v,v[i]^2)/#v)
};
 
RMS(vector(10,i,i))

Specific functions for the first n positive integers:

RMS_first(n)={
  sqrt((n+1)*(2*n+1)/6)
};
 
RMS_first(10)

Asymptotically this is n/sqrt(3).

Perl

use v5.10.0;
sub rms
{
        my $r = 0;
        $r += $_**2 for @_;
        return sqrt( $r/@_ );
}
 
say rms(1..10);

Perl 6

sub rms(*@nums) {
    sqrt( ([+] @nums X** 2) / +@nums );
}
 
say rms(1..10);

PL/I

declare A(10) fixed decimal static initial (1,2,3,4,5,6,7,8,9,10);
n = hbound(A,1);
RMS = sqrt(sum(A**2)/n);

PicoLisp

(scl 5)
 
(let Lst (1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0)
   (prinl
      (format
         (sqrt
            (*/
               (sum '((N) (*/ N N 1.0)) Lst)
               1.0
               (length Lst) )
            T )
         *Scl ) ) )

Output:

6.20484

PostScript

/findrms{
/x exch def
/sum 0 def
/i 0 def
x length 0 eq{}
{
x length{
/sum x i get 2 exp sum add def
/i i 1 add def
}repeat
/sum sum x length div sqrt def
}ifelse
sum ==
}def
 
[1 2 3 4 5 6 7 8 9 10] findrms

Output:

6.20483685

Library: initlib

[1 10] 1 range dup 0 {dup * +} fold exch length div sqrt

Powerbuilder

long ll_x, ll_y, ll_product
decimal ld_rms
 
ll_x = 1
ll_y = 10
DO WHILE ll_x <= ll_y
	ll_product += ll_x * ll_x
	ll_x ++
LOOP
ld_rms = Sqrt(ll_product / ll_y)
 
//ld_rms value is 6.20483682299542849

PowerShell

function get-rms([float[]]$nums){
   $sqsum=$nums | foreach-object { $_*$_} | measure-object -sum | select-object -expand Sum
   return [math]::sqrt($sqsum/$nums.count)
}
 
get-rms @(1..10) 

PureBasic

NewList MyList()  ; To hold a unknown amount of numbers to calculate
 
If OpenConsole()
  Define.d result
  Define i, sum_of_squares
 
  ;Populate a random amounts of numbers to calculate
  For i=0 To (Random(45)+5) ; max elements is unknown to the program
    AddElement(MyList())
    MyList()=Random(15)  ; Put in a random number
  Next
 
  Print("Averages/Root mean square"+#CRLF$+"of : ")  
 
  ; Calculate square of each element, print each & add them together
  ForEach MyList()  
    Print(Str(MyList())+" ")             ; Present to our user
    sum_of_squares+MyList()*MyList()     ; Sum the squares, e.g
  Next
 
  ;Present the result
  result=Sqr(sum_of_squares/ListSize(MyList()))
  PrintN(#CRLF$+"= "+StrD(result))
 
  PrintN("Press ENTER to exit"): Input()
  CloseConsole()
EndIf

Python

Works with: Python version 3

>>> from math import sqrt
>>> def qmean(num):
	return sqrt(sum(n*n for n in num)/len(num))
 
>>> qmean(range(1,11))
6.2048368229954285

Note that function range in Python includes the first limit of 1, excludes the second limit of 11, and has a default increment of 1.

The Python 2 version is nearly identical, except you must cast the sum to a float to get float division instead of integer division; or better, do a from __future__ import division, which works on Python 2.2+ as well as Python 3, and makes division work consistently like it does in Python 3.

Qi

(define rms
  R -> (sqrt (/ (APPLY + (MAPCAR * R R)) (length R))))

R

sqrt(sum((1:10)^2/10))

or generally, for x

x<-1:10
sqrt(sum((x)^2/length(x)))

REXX

REXX has no built-in SQRT, so a simple version is included here.

/*REXX program to compute root mean square. */
 
parse arg n .                          /*get the argument (maybe).      */
if n=='' then n=10                     /*if not specified, assume ten.  */
 
numeric digits 50                      /*let's go a little overboard.   */
 
sum=0                                  /*sum of numbers squared (so far)*/
 
  do j=1 for n                         /*step through   N   integers.   */
  sum=sum+j**2                         /*sum the squares of the integers*/
  end
 
rms=sqrt(sum/n)                        /*divide by  N,  then get  SQRT. */
say 'root mean square for 1-->'n "is" rms                 /*show & tell.*/
exit
 
 
/*SQRT subroutine*/
sqrt: procedure; parse arg x
if x=0 then return 0                   /*handle special case of zero.   */
d=digits()                             /*get the current precision.     */
numeric digits digits()+2              /*ensure extra precision.        */
g=x/4                                  /*try get a so-so 1st guesstimate*/
old=0                                  /*set OLD guess to zero.         */
 
  do forever
  g=.5*(g+x/g)                         /*do the nitty-gritty calculation*/
  if g=old then leave                  /*if G is the same as old, quit. */
  old=g                                /*save OLD for next iteration.   */
  end                                  /*  .5*   is faster than    /2   */
 
numeric digits d                       /*restore the original precision.*/
return g/1                             /*normalize to old precision.    */

Output:

root mean square for 1-->10 is 6.2048368229954282980666209777247378499279652953641

Ruby

class Array
  def quadratic_mean
    Math.sqrt( self.inject(0) {|s, y| s += y*y}.to_f / self.length )
  end
end
 
class Range
  def quadratic_mean
    self.to_a.quadratic_mean
  end
end
 
(1..10).quadratic_mean  # => 6.20483682299543

and a non object-oriented solution:

def rms(seq)
  Math.sqrt(seq.inject(0.0) {|sum, x| sum += x*x} / seq.length)
end
puts rms (1..10).to_a # => 6.2048368229954285

Run BASIC

valueList$   = "1 2 3 4 5 6 7 8 9 10"
while word$(valueList$,i +1) <> ""             ' grab values from list
  thisValue  = val(word$(valueList$,i +1))     ' turn values into numbers
  sumSquares = sumSquares + thisValue ^ 2      ' sum up the squares
  i = i +1                                     ' 
wend
print "List of Values:";valueList$;" containing ";i;" values"
print "Root Mean Square =";(sumSquares/i)^0.5

Output: List of Values:1 2 3 4 5 6 7 8 9 10 containing 10 values Root Mean Square =6.20483682

Sather

class MAIN is
  -- irrms stands for Integer Ranged RMS
  irrms(i, f:INT):FLT
    pre i <= f
  is
    sum ::= 0;
    loop
      sum := sum + i.upto!(f).pow(2);
    end;
    return (sum.flt / (f-i+1).flt).sqrt;
  end;
 
  main is
    #OUT + irrms(1, 10) + "\n";
  end; 
end;

Scala

def rms(nums: Seq[Int]) = math.sqrt(nums.map(math.pow(_, 2)).sum / nums.size)
println(rms(1 to 10))

Scheme

(define (rms nums)
  (sqrt (/ (apply + (map * nums nums))
           (length nums))))
 
(rms '(1 2 3 4 5 6 7 8 9 10))

Output:

6.20483682299543

Seed7

$ include "seed7_05.s7i";
  include "float.s7i";
  include "math.s7i";
 
const array float: numbers is [] (1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0);
 
const func float: rms (in array float: numbers) is func
  result
    var float: rms is 0.0;
  local
    var float: number is 0.0;
    var float: sum is 0.0;
  begin
    for number range numbers do
      sum +:= number ** 2;
    end for;
    rms := sqrt(sum / flt(length(numbers)));
  end func;
 
const proc: main is func
  begin
    writeln(rms(numbers) digits 7);
  end func;

Smalltalk

(((1 to: 10) inject: 0 into: [ :s :n | n*n + s ]) / 10) sqrt.

SNOBOL4

Works with: Macro Spitbol

Works with: CSnobol

There is no built-in sqrt( ) function in Snobol4+.

        define('rms(a)i,ssq') :(rms_end)
rms     i = i + 1; ssq = ssq + (a<i> * a<i>) :s(rms)
        rms = sqrt(1.0 * ssq / prototype(a)) :(return)
rms_end
 
*       # Fill array, test and display
        str = '1 2 3 4 5 6 7 8 9 10'; a = array(10)
loop    i = i + 1; str len(p) span('0123456789') . a<i> @p :s(loop)
        output = str ' -> ' rms(a)
end

Output:

1 2 3 4 5 6 7 8 9 10 -> 6.20483682

Tcl

Works with: Tcl version 8.5

proc qmean list {
    set sum 0.0
    foreach value $list { set sum [expr {$sum + $value**2}] }
    return [expr { sqrt($sum / [llength $list]) }]
}
 
puts "RMS(1..10) = [qmean {1 2 3 4 5 6 7 8 9 10}]"

Output:

RMS(1..10) = 6.2048368229954285

Ursala

using the mean function among others from the flo library

#import nat
#import flo
 
#cast %e
 
rms = sqrt mean sqr* float* nrange(1,10)

output:

6.204837e+00

Vala

Valac probably needs to have the flag "-X -lm" added to include the C Math library.

double rms(double[] list){
	double sum_squares = 0;
	double mean;
 
	foreach ( double number in list){
		sum_squares += (number * number);
	}
 
	mean = Math.sqrt(sum_squares / (double) list.length);
 
	return mean;
} // end rms
 
public static void main(){
	double[] list = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
	double mean = rms(list);
 
	stdout.printf("%s\n", mean.to_string());
}

Output:

6.2048368229954285

XPL0

code CrLf=9;
code real RlOut=48;
int  N;
real S;
[S:= 0.0;
for N:= 1 to 10 do S:= S + sq(float(N));
RlOut(0, sqrt(S/10.0));
CrLf(0);
]

Output:

    6.20484