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:
Cf. Averages/Pythagorean means
[edit] 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
[edit] ALGOL 68
# 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
[edit] APL
rms←{((+/⍵*2)÷⍴⍵)*0.5}
x←⍳10
rms x
6.204836823
[edit] AutoHotkey
[edit] 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
[edit] Avoiding a loop
Using these equations:
See wp:List of mathematical series
for a < b : 
We can show that:
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
[edit] AWK
#!/usr/bin/awk -f
# computes RMS of the 1st column of a data file
{
x = $1; # value of 1st column
S += x*x;
N++;
}
END {
print "RMS: ",sqrt(S/N);
}
[edit] BASIC
Note that this will work in Visual Basic and the Windows versions of PowerBASIC by simply wrapping the module-level code into the MAIN function, and changing PRINT to MSGBOX.
DIM i(1 TO 10) AS DOUBLE, L0 AS LONG
FOR L0 = 1 TO 10
i(L0) = L0
NEXT
PRINT STR$(rms#(i()))
FUNCTION rms# (what() AS DOUBLE)
DIM L0 AS LONG, tmp AS DOUBLE, rt AS DOUBLE
FOR L0 = LBOUND(what) TO UBOUND(what)
rt = rt + (what(L0) ^ 2)
NEXT
tmp = UBOUND(what) - LBOUND(what) + 1
rms# = SQR(rt / tmp)
END FUNCTION
See also: BBC BASIC, Liberty BASIC, PureBasic, Run BASIC
[edit] 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)
[edit] 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;
}
[edit] 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.
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());
}
}
}
[edit] 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 !
[edit] Clojure
(use '[clojure.contrib.math :only (sqrt)])
(defn rms [xs]
(sqrt (/ (reduce + (map #(* % %) xs))
(count xs))))
(println (rms (range 1 11)))
Output:
6.2048368229954285
[edit] CoffeeScript
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])
[edit] 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)))))
[edit] 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
[edit] 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.
[edit] 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
[edit] 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
[edit] 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
[edit] 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
[edit] 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))
}
}
[edit] Factor
: root-mean-square ( seq -- mean )
[ [ sq ] map-sum ] [ length ] bi / sqrt ;
( scratchpad ) 10 [1,b] root-mean-square . 6.204836822995428
[edit] 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
[edit] Fortran
Assume x stored in array x.
print *,sqrt( sum(x**2)/size(x) )
[edit] Go
package main
import (
"fmt"
"math"
)
func main() {
const n = 10
sum := 0.
for x := 1.; x <= n; x++ {
sum += x * x
}
fmt.Println(math.Sqrt(sum / n))
}
- Output:
6.2048368229954285
[edit] 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
[edit] Haskell
Given the mean function defiend in Averages/Pythagorean means:
main = print $ mean 2 [1 .. 10]
[edit] 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
[edit] 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
[edit] Io
rms := method (figs, (figs map(** 2) reduce(+) / figs size) sqrt)
rms( Range 1 to(10) asList ) println
[edit] 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.
[edit] 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
[edit] JavaScript
,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
[edit] 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
[edit] Logo
to rms :v
output sqrt quotient (apply "sum map [? * ?] :v) count :v
end
show rms iseq 1 10
[edit] 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})
[edit] Mathematica
RootMeanSquare@Range[10]
The above will give the precise solution
, to downgrade to 6.20484, use '10.' to imply asking for numeric solution, or append '//N' after the whole expression.
[edit] MATLAB
function rms = quadraticMean(list)
rms = sqrt(mean(list.^2));
end
Solution:
>> quadraticMean((1:10))
ans =
6.204836822995429
[edit] Maxima
L: makelist(i, i, 1, 10)$
rms(L) := sqrt(lsum(x^2, x, L)/length(L))$
rms(L), numer; /* 6.204836822995429 */
[edit] МК-61/52
0 П0 П1 С/П x^2 ИП0 x^2 ИП1 *
+ ИП1 1 + П1 / КвКор П0 БП
03
Instruction: В/О С/П Number С/П Number ...
Each time you press the С/П on the indicator would mean already entered numbers.
[edit] 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]));
}
}
[edit] NetRexx
/* NetRexx */
options replace format comments java crossref symbols nobinary
parse arg maxV .
if maxV = '' | maxV = '.' then maxV = 10
sum = 0
loop nr = 1 for maxV
sum = sum + nr ** 2
end nr
rmsD = Math.sqrt(sum / maxV)
say 'RMS of values from 1 to' maxV':' rmsD
return
Output:
RMS of values from 1 to 10: 6.204836822995428
[edit] Oberon-2
Oxford Oberon-2
MODULE QM;
IMPORT ML := MathL, Out;
VAR
nums: ARRAY 10 OF LONGREAL;
i: INTEGER;
PROCEDURE Rms(a: ARRAY OF LONGREAL): LONGREAL;
VAR
i: INTEGER;
s: LONGREAL;
BEGIN
s := 0.0;
FOR i := 0 TO LEN(a) - 1 DO
s := s + (a[i] * a[i])
END;
RETURN ML.Sqrt(s / LEN(a))
END Rms;
BEGIN
FOR i := 0 TO LEN(nums) - 1 DO
nums[i] := i + 1
END;
Out.String("Quadratic Mean: ");Out.LongReal(Rms(nums));Out.Ln
END QM.
Output:
Quadratic Mean: 6.20483682300
[edit] 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();
}
}
}
[edit] 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 *)
[edit] ooRexx
call testAverage .array~of(10, 9, 8, 7, 6, 5, 4, 3, 2, 1)
call testAverage .array~of(10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, 0, 0, 0, .11)
call testAverage .array~of(30, 10, 20, 30, 40, 50, -100, 4.7, -11e2)
::routine testAverage
use arg list
say "list =" list~toString("l", ", ")
say "root mean square =" rootmeansquare(list)
say
::routine rootmeansquare
use arg numbers
-- return zero for an empty list
if numbers~isempty then return 0
sum = 0
do number over numbers
sum += number * number
end
return rxcalcsqrt(sum/numbers~items)
::requires rxmath LIBRARY
[edit] 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
[edit] 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).
[edit] Perl
use v5.10.0;
sub rms
{
my $r = 0;
$r += $_**2 for @_;
return sqrt( $r/@_ );
}
say rms(1..10);
[edit] Perl 6
sub rms(*@nums) { sqrt [+](@nums X** 2) / @nums }
say rms 1..10;
[edit] PL/I
declare A(10) fixed decimal static initial (1,2,3,4,5,6,7,8,9,10);
n = hbound(A,1);
RMS = sqrt(sum(A**2)/n);
[edit] PicoLisp
(scl 5)
(let Lst (1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0)
(prinl
(format
(sqrt
(*/
(sum '((N) (*/ N N 1.0)) Lst)
1.0
(length Lst) )
T )
*Scl ) ) )
Output:
6.20484
[edit] PostScript
/findrms{
/x exch def
/sum 0 def
/i 0 def
x length 0 eq{}
{
x length{
/sum x i get 2 exp sum add def
/i i 1 add def
}repeat
/sum sum x length div sqrt def
}ifelse
sum ==
}def
[1 2 3 4 5 6 7 8 9 10] findrms
Output:
6.20483685
[1 10] 1 range dup 0 {dup * +} fold exch length div sqrt
[edit] Powerbuilder
long ll_x, ll_y, ll_product
decimal ld_rms
ll_x = 1
ll_y = 10
DO WHILE ll_x <= ll_y
ll_product += ll_x * ll_x
ll_x ++
LOOP
ld_rms = Sqrt(ll_product / ll_y)
//ld_rms value is 6.20483682299542849
[edit] PowerShell
function get-rms([float[]]$nums){
$sqsum=$nums | foreach-object { $_*$_} | measure-object -sum | select-object -expand Sum
return [math]::sqrt($sqsum/$nums.count)
}
get-rms @(1..10)
[edit] 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
[edit] Python
>>> 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.
[edit] Qi
(define rms
R -> (sqrt (/ (APPLY + (MAPCAR * R R)) (length R))))
[edit] R
sqrt(sum((1:10)^2/10))
or generally, for x
x<-1:10
sqrt(sum((x)^2/length(x)))
[edit] Racket
#lang racket
(define (rms nums)
(sqrt (/ (for/sum ([n nums]) (* n n)) (length nums))))
[edit] REXX
REXX has no built-in SQRT function, so a RYO version is included here.
This particular SQRT function was programmed for speed, as this SQRT function has two critical components:
- the initial guess (for the square root)
- the number of digits used during the computations
The SQRT code was optimized to use the minimum amount of digits (precision) for each iteration of the
calculation as well as a reasonable attempt at providing a first-guess square root by essentially halving
the number using logrithmic (base ten) arithmetic.
/*REXX program to compute the root mean square of a series of numbers.*/
parse arg n . /*get the argument (maybe). */
if n=='' then n=10 /*Not specified? Then assume 10.*/
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 /*j*/
rms=sqrt(sum/n) /*divide by N, then get SQRT. */
say 'root mean square for 1──►'n "is" rms /*show & tell.*/
exit /*stick a fork in it, we're done.*/
/*──────────────────────────────────SQRT subroutine─────────────────────────*/
sqrt: procedure; parse arg x;if x=0 then return 0;d=digits();numeric digits 11
g=.sqrtGuess(); do j=0 while p>9; m.j=p; p=p%2+1; end; do k=j+5 to 0 by -1
if m.k>11 then numeric digits m.k;g=.5*(g+x/g);end;numeric digits d;return g/1
.sqrtGuess: if x<0 then say 'negative number' x; numeric form; m.=11
p=d+d%4+2; parse value format(x,2,1,,0) 'E0' with g 'E' _ .; return g*.5'E'_%2
output
root mean square for 1──►10 is 6.2048368229954282980666209777247378499279652953641
[edit] 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
[edit] 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
[edit] 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;
[edit] Scala
def rms(nums: Seq[Int]) = math.sqrt(nums.map(math.pow(_, 2)).sum / nums.size)
println(rms(1 to 10))
[edit] 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
[edit] 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;
[edit] Smalltalk
(((1 to: 10) inject: 0 into: [ :s :n | n*n + s ]) / 10) sqrt.
[edit] SNOBOL4
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
[edit] Tcl
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
[edit] 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
[edit] 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
[edit] 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
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