Dot product

Task

Create a function/use an in-built function, to compute the dot product, also known as the scalar product of two vectors.

If possible, make the vectors of arbitrary length.

As an example, compute the dot product of the vectors:

[1, 3, -5] and

[4, -2, -1]

If implementing the dot product of two vectors directly:

each vector must be the same length
multiply corresponding terms from each vector
sum the products (to produce the answer)

Related task

Vector products

ACL2

(defun dotp (v u)
   (if (or (endp v) (endp u))
       0
       (+ (* (first v) (first u))
          (dotp (rest v) (rest u)))))

> (dotp '(1 3 -5) '(4 -2 -1))
3

Action!

INT FUNC DotProduct(INT ARRAY v1,v2 BYTE len)
  BYTE i,res

  res=0
  FOR i=0 TO len-1
  DO
    res==+v1(i)*v2(i)
  OD
RETURN (res)

PROC PrintVector(INT ARRAY a BYTE size)
  BYTE i

  Put('[)
  FOR i=0 TO size-1
  DO
    PrintI(a(i))
    IF i<size-1 THEN
      Put(',)
    FI
  OD
  Put('])
RETURN

PROC Test(INT ARRAY v1,v2 BYTE len)
  INT res

  res=DotProduct(v1,v2,len)
  PrintVector(v1,len)
  Put('.)
  PrintVector(v2,len)
  Put('=)
  PrintIE(res)
RETURN

PROC Main()
  INT ARRAY
    v1=[1 3 65531],
    v2=[4 65534 65535]

  Test(v1,v2,3)
RETURN

Output:

Screenshot from Atari 8-bit computer

[1,3,-5].[4,-2,-1]=3

ActionScript

function dotProduct(v1:Vector.<Number>, v2:Vector.<Number>):Number
{
	if(v1.length != v2.length) return NaN;
	var sum:Number = 0;
	for(var i:uint = 0; i < v1.length; i++)
		sum += v1[i]*v2[i];
	return sum;
}
trace(dotProduct(Vector.<Number>([1,3,-5]),Vector.<Number>([4,-2,-1])));

ALGOL 68

Translation of: C++

Works with: ALGOL 68 version Standard - with prelude inserted manually

Works with: ALGOL 68G version Any - tested with release mk15-0.8b.fc9.i386

Works with: ELLA ALGOL 68 version Any (with appropriate job cards) - tested with release 1.8.8d.fc9.i386

MODE DOTFIELD = REAL;
MODE DOTVEC = [1:0]DOTFIELD;

# The "Spread Sheet" way of doing a dot product:
  o Assume bounds are equal, and start at 1 
  o Ignore round off error
#
PRIO SSDOT = 7;
OP SSDOT = (DOTVEC a,b)DOTFIELD: (
  DOTFIELD sum := 0;
  FOR i TO UPB a DO sum +:= a[i]*b[i] OD;
  sum
);

# An improved dot-product version:
  o Handles sparse vectors
  o Improves summation by gathering round off error
    with no additional multiplication - or LONG - operations.
#
OP * = (DOTVEC a,b)DOTFIELD: (
  DOTFIELD sum := 0, round off error:= 0;
  FOR i
# Assume bounds may not be equal, empty members are zero (sparse) #
    FROM LWB (LWB a > LWB b | a | b )
    TO UPB (UPB a < UPB b | a | b ) 
  DO
    DOTFIELD org = sum, prod = a[i]*b[i];
    sum +:= prod;
    round off error +:= sum - org - prod
  OD;
  sum - round off error
);

# Test: #
DOTVEC a=(1,3,-5), b=(4,-2,-1);

print(("a SSDOT b = ",fixed(a SSDOT b,0,real width), new line));
print(("a   *   b = ",fixed(a   *   b,0,real width), new line))

Output:

a SSDOT b = 3.000000000000000
a   *   b = 3.000000000000000

ALGOL W

begin
    % computes the dot product of two equal length integer vectors            %
    % (single dimension arrays ) the length of the vectors must be specified  %
    % in length.                                                              %
    integer procedure integerDotProduct( integer array a ( * )
                                       ; integer array b ( * )
                                       ; integer value length
                                       ) ;
    begin
        integer product;
        product := 0;
        for i := 1 until length do product := product + ( a(i) * b(i) );
        product
    end integerDotProduct ;

    % declare two vectors of length 3                                         %
    integer array v1, v2 ( 1 :: 3 );
    % initialise the vectors                                                  %
    v1(1) :=  1; v1(2) :=  3; v1(3) := -5;
    v2(1) :=  4; v2(2) := -2; v2(3) := -1;
    % output the dot product                                                  %
    write( integerDotProduct( v1, v2, 3 ) )
end.

Arturo

dotProduct: function [a,b][
    [ensure equal? size a size b]

    result: 0
    loop 0..(size a)-1 'i [
        result: result + a\[i] * b\[i]
    ]
    return result
]

print dotProduct @[1, 3, neg 5] @[4, neg 2, neg 1]
print dotProduct [1 2 3] [4 5 6]

Output:

3
32

AutoHotkey

Vet1 := "1,3,-5"
Vet2 := "4 , -2 , -1"
MsgBox % DotProduct( Vet1 , Vet2 )

;---------------------------

DotProduct( VectorA , VectorB )
{
  Sum := 0
  StringSplit, ArrayA, VectorA, `,, %A_Space%
  StringSplit, ArrayB, VectorB, `,, %A_Space%
  If ( ArrayA0 <> ArrayB0 )
    Return ERROR
  While ( A_Index <= ArrayA0 )
    Sum += ArrayA%A_Index% * ArrayB%A_Index%
  Return Sum
}

BASIC

Applesoft BASIC

Calculates the dot product of two random vectors of length N.

 100 :
 110  REM  DOT PRODUCT
 120 :
 130  REM  INITIALIZE VECTORS OF LENGTH N
 140  N = 3
 150  DIM V1(N): DIM V2(N)
 160  FOR I = 1 TO N
 170  V1(I) =  INT ( RND (1) * 20 - 9.5)
 180  V2(I) =  INT ( RND (1) * 20 - 9.5)
 190  NEXT I
 300 :
 310  REM  CALCULATE THE DOT PRODUCT
 320 :
 330  FOR I = 1 TO N:DP = DP + V1(I) * V2(I): NEXT I
 400 :
 410  REM  DISPLAY RESULT
 420 :
 430  PRINT "[";: FOR I = 1 TO N: PRINT " ";V1(I);: NEXT I
 440  PRINT "] . [";: FOR I = 1 TO N: PRINT " ";V2(I);: NEXT I
 450  PRINT "] = ";DP

Output:

]RUN
[ 7 2 -2] . [ 7 -5 8] = 23
]RUN
[ -3 -4 -8] . [ -8 7 6] = -52

BBC BASIC

BBC BASIC has a built-in dot-product operator:

      DIM vec1(2), vec2(2), dot(0)
      
      vec1() = 1, 3, -5
      vec2() = 4, -2, -1
      
      dot() = vec1() . vec2()
      PRINT "Result is "; dot(0)

Output:

Result is 3

BASIC256

Translation of: FreeBASIC

dim zero3d = {0.0, 0.0, 0.0}
dim zero5d = {0.0, 0.0, 0.0, 0.0, 0.0}
dim x = {1.0, 0.0, 0.0}
dim y = {0.0, 1.0, 0.0}
dim z = {0.0, 0.0, 1.0}
dim q = {1.0, 1.0, 3.14159}
dim r = {-1.0, 2.618033989, 3.0}

print " q dot r           = "; dot(q, r)
print " zero3d dot zero5d = "; dot(zero3d, zero5d)
print " zero3d dot x      = "; dot(zero3d, x)
print " z dot z           = "; dot(z, z)
print " y dot z           = "; dot(y, z)
end

function dot(a, b)
    if a[?] <> b[?] then return "NaN"

    dp = 0.0
    for i = 0 to a[?]-1
        dp += a[i] * b[i]
    next i
    return dp
end function

Befunge 93

v Space for variables
v Space for vector1
v Space for vector2
v http://rosettacode.org/wiki/Dot_product
                                            >00pv
>>55+":htgneL",,,,,,,,&:0`                  | 
v,,,,,,,"Length can't be negative."+55<
>,,,,,,,,,,,,,,,,,,,@                 |!`-10<
                                      >0.@                             
v,")".g00,,,,,,,,,,,,,,"Vector a(size "         <
0v01g00,")".g00,,,,,,,,,,,,,,"Vector b"<
0pvp2g01&p01-1g01<                     "
g>>         10g0`|               @.g30<(
1                >03g:-03p>00g1-`     |s
0      vp00-1g00p30+g30*g2-1g00g1-1g00<i
p      >        v         #            z
vp1g01&p01-1g01<>         ^            e
>      10g0`   |        vp01-1g01.g1<  
               >00g1-10p>10g:01-`   |  "
                                    >  ^

Output:

Length:
3
Vector a(size 3 )1
3
-5
1 3 -5 Vector b(size 3 )4
-2
-1

3

BQN

Multiply the two vectors, then sum the result.

•Show 1‿3‿¯5 +´∘× 4‿¯2‿¯1

# as a tacit function
DotP ← +´×
•Show 1‿3‿¯5 DotP 4‿¯2‿¯1

3
3

C#

static void Main(string[] args)
{
	Console.WriteLine(DotProduct(new decimal[] { 1, 3, -5 }, new decimal[] { 4, -2, -1 }));
	Console.Read();
}

private static decimal DotProduct(decimal[] vec1, decimal[] vec2) 
{
	if (vec1 == null)
		return 0;

	if (vec2 == null)
		return 0;

	if (vec1.Length != vec2.Length)
		return 0;

	decimal tVal = 0;
	for (int x = 0; x < vec1.Length; x++)
	{
		tVal += vec1[x] * vec2[x];
	}

	return tVal;
}

Output:

Alternative using Linq (C# 4)

Works with: C# version 4

public static decimal DotProduct(decimal[] a, decimal[] b) {
    return a.Zip(b, (x, y) => x * y).Sum();
}

C++

#include <iostream>
#include <numeric>

int main()
{
    int a[] = { 1, 3, -5 };
    int b[] = { 4, -2, -1 };

    std::cout << std::inner_product(a, a + sizeof(a) / sizeof(a[0]), b, 0) << std::endl;

    return 0;
}

Output:

Alternative using std::valarray

#include <valarray>
#include <iostream>

int main()
{
    std::valarray<double> xs = {1,3,-5};
    std::valarray<double> ys = {4,-2,-1};

    double result = (xs * ys).sum();

    std::cout << result << '\n';
    
    return 0;
}

Output:

Alternative using std::inner_product

#include <iostream>
#include <vector>
#include <numeric>

int main() {
  std::vector<int> v1 { 1,  3, -5, };
  std::vector<int> v2 { 4, -2, -1, };
  auto dp = std::inner_product(v1.cbegin(), v1.cend(), v2.cbegin(), 0);
  std::cout << "dot.product of {1,3,-5} and {4,-2,-1}: " << dp << std::endl;
  return 0;
}

Output:

dot.product of {1,3,-5} and {4,-2,-1}: 3

Clojure

Works with: Clojure version 1.1

Preconditions are new in 1.1. The actual code also works in older Clojure versions.

(defn dot-product [& matrix]
  {:pre [(apply == (map count matrix))]}
  (apply + (apply map * matrix)))

(defn dot-product2 [x y]
 (->> (interleave x y)
      (partition 2 2)
      (map #(apply * %))
      (reduce +)))

(defn dot-product3
  "Dot product of vectors. Tested on version 1.8.0."
  [v1 v2]
  {:pre [(= (count v1) (count v2))]}
  (reduce + (map * v1 v2)))

;Example Usage
(println (dot-product [1 3 -5] [4 -2 -1]))
(println (dot-product2 [1 3 -5] [4 -2 -1]))
(println (dot-product3 [1 3 -5] [4 -2 -1]))

CoffeeScript

dot_product = (ary1, ary2) ->
  if ary1.length != ary2.length
    throw "can't find dot product: arrays have different lengths"
  dotprod = 0
  for v, i in ary1
    dotprod += v * ary2[i]
  dotprod

console.log dot_product([ 1, 3, -5 ], [ 4, -2, -1 ]) # 3
try
  console.log dot_product([ 1, 3, -5 ], [ 4, -2, -1, 0 ]) # exception
catch e
  console.log e

Output:

> coffee foo.coffee

3

can't find dot product: arrays have different lengths

Common Lisp

(defun dot-product (a b)
  (apply #'+ (mapcar #'* (coerce a 'list) (coerce b 'list))))

This works with any size vector, and (as usual for Common Lisp) all numeric types (rationals, bignums, complex numbers, etc.).

Maybe it is better to do it without coercing. Then we got a cleaner code.

(defun dot-prod (a b)
  (reduce #'+ (map 'simple-vector #'* a b)))

Crystal

Translation of: Ruby

class Vector
  property x, y, z
  
  def initialize(@x : Int64, @y : Int64, @z : Int64) end
      
  def dot_product(other : Vector)
    (self.x * other.x) + (self.y * other.y) + (self.z * other.z)
  end
end

puts Vector.new(1, 3, -5).dot_product Vector.new(4, -2, -1) # => 3

class Array
  def dot_product(other)
    raise "not the same size!" if self.size != other.size
    self.zip(other).sum { |(a, b)| a * b }
  end
end

p [8, 13, -5].dot_product [4, -7, -11]   # => -4

Output:

3
-4

D

void main() {
    import std.stdio, std.numeric;

    [1.0, 3.0, -5.0].dotProduct([4.0, -2.0, -1.0]).writeln;
}

Output:

Using an array operation:

void main() {
    import std.stdio, std.algorithm;

    double[3] a = [1.0, 3.0, -5.0];
    double[3] b = [4.0, -2.0, -1.0];
    double[3] c = a[] * b[];
    c[].sum.writeln;
}

Delphi

Works with: Lazarus

program Project1;

{$APPTYPE CONSOLE}

type
  doublearray = array of Double;

function DotProduct(const A, B : doublearray): Double;
var
I: integer;
begin
  assert (Length(A) = Length(B), 'Input arrays must be the same length');
  Result := 0;
  for I := 0 to Length(A) - 1 do
    Result := Result + (A[I] * B[I]);
end;

var
  x,y: doublearray;
begin
  SetLength(x, 3);
  SetLength(y, 3);
  x[0] := 1; x[1] := 3; x[2] := -5;
  y[0] := 4; y[1] :=-2; y[2] := -1;
  WriteLn(DotProduct(x,y));
  ReadLn;
end.

Output:

 3.00000000000000E+0000

Note: Delphi does not like arrays being declared in procedure headings, so it is necessary to declare it beforehand. To use integers, modify doublearray to be an array of integer.

EasyLang

func dotprod a[] b[] .
   for i to len a[]
      r += a[i] * b[i]
   .
   return r
.
print dotprod [ 1 3 -5 ] [ 4 -2 -1 ]

EchoLisp

(define a #(1 3 -5))
(define b #(4 -2 -1))

;; function definition
(define ( ⊗ a b) (for/sum ((x a)(y b)) (* x y)))
(⊗ a b) → 3

;; library
(lib 'math)
(dot-product a b) → 3

Emacs Lisp

(defun dot-product (v1 v2)
  (let ((res 0))
    (dotimes (i (length v1))
      (setq res (+ (* (elt v1 i) (elt v2 i)) res)))
    res))

(dot-product [1 2 3] [1 2 3]) ;=> 14
(dot-product '(1 2 3) '(1 2 3)) ;=> 14

F#

let dot_product (a:array<'a>) (b:array<'a>) =
    if Array.length a <> Array.length b then failwith "invalid argument: vectors must have the same lengths"
    Array.fold2 (fun acc i j -> acc + (i * j)) 0 a b

> dot_product [| 1; 3; -5 |] [| 4; -2; -1 |] ;;
val it : int = 3

Factor

The built-in word v. is used to compute the dot product. It doesn't enforce that the vectors are of the same length, so here's a wrapper.

USING: kernel math.vectors sequences ;

: dot-product ( u v -- w )
    2dup [ length ] bi@ =
    [ v. ] [ "Vector lengths must be equal" throw ] if ;

( scratchpad ) { 1 3 -5 } { 4 -2 -1 } dot-product .
3

FALSE

[[\1-$0=~][$d;2*1+\-ø\$d;2+\-ø@*@+]#]p:
3d: {Vectors' length}
1 3 5_ 4 2_ 1_ d;$1+ø@*p;!%. {Output: 3}

Fantom

Dot product of lists of Int:

class DotProduct
{
  static Int dotProduct (Int[] a, Int[] b)
  {
    Int result := 0
    [a.size,b.size].min.times |i|
    {
      result += a[i] * b[i]
    }
    return result
  }

  public static Void main ()
  {
    Int[] x := [1,2,3,4]
    Int[] y := [2,3,4]

    echo ("Dot product of $x and $y is ${dotProduct(x, y)}")
  }
}

Forth

: vector create cells allot ;
: th cells + ;

3 constant /vector
/vector vector a
/vector vector b

: dotproduct                           ( a1 a2 -- n)
  0 tuck ?do -rot over i th @ over i th @ * >r rot r> + loop nip nip
;

: vector! cells over + swap ?do i ! 1 cells +loop ;

-5  3 1 a /vector vector!
-1 -2 4 b /vector vector!

a b /vector dotproduct . 3 ok

The intrinsic function Dot_Product(X,Y) accepts various precisions of integer, floating-point and complex arrays (for which it is Sum(Conjg(x)*y)) and even logical, for which it is Any(x .AND. y) returning zero if either array is of length zero, or false for logical types.

Frink

dotProduct[v1, v2] :=
{
   if length[v1] != length[v2]
   {
      println["dotProduct: vectors are of different lengths."]
      return undef
   }
   
   return sum[map[{|c1,c2| c1 * c2}, zip[v1, v2]]]
}

FunL

import lists.zipWith

def dot( a, b )
  | a.length() == b.length() = sum( zipWith((*), a, b) )
  | otherwise = error( "Vector sizes must match" )

println( dot([1, 3, -5], [4, -2, -1]) )

Output:

FreeBASIC

#define NAN 0.0/0.0  'dot product of different-dimensioned vectors is no more defined than 0/0    

function dot( a() as double, b() as double ) as double
    if ubound(a)<>ubound(b) then return NAN
    dim as uinteger i
    dim as double dp = 0.0
    for i = 0 to ubound(a)
        dp += a(i)*b(i)
    next i
    return dp
end function

dim as double zero3d(0 to 2) = {0.0, 0.0, 0.0}     'some example vectors
dim as double zero5d(0 to 4) = {0.0, 0.0, 0.0, 0.0, 0.0}
dim as double x(0 to 2) = {1.0, 0.0, 0.0}
dim as double y(0 to 2) = {0.0, 1.0, 0.0}
dim as double z(0 to 2) = {0.0, 0.0, 1.0}
dim as double q(0 to 2) = {1.0, 1.0, 3.14159}
dim as double r(0 to 2) = {-1.0, 2.618033989, 3.0}

print " q dot r           = ", dot(q(), r())
print " zero3d dot zero5d = ", dot(zero3d(), zero5d())
print " zero3d dot x      = ", dot(zero3d(), x())
print " z dot z           = ", dot(z(), z())
print " y dot z           = ", dot(y(), z())

Output:

 q dot r           =         11.042803989
 zero3d dot zero5d =        -nan
 zero3d dot x      =         0
 z dot z           =         1
 y dot z           =         0

FutureBasic

local fn DotProduct( a as CFArrayRef, b as CFArrayRef ) as double
  NSInteger i
  double    dp = 0.0
  
  if len(a) != len(b) then alert 1, NSAlertStyleWarning,, @"Vectors have unequal length.", @"Okay" : exit fn
  
  for i = 0 to len(a)-1
    dp += fn NumberDoubleValue( a[i] ) * fn NumberDoubleValue( b[i] )
  next
end fn = dp

CFArrayRef a, b
NSUInteger i

a = @[@1, @3,  @-5]
b = @[@4, @-2, @-1]
printf @"Dot product of [%@, %@, %@].[%@, %@, %@] = %.4f", a[0], a[1], a[2], b[0], b[1], b[2], fn DotProduct( a, b )

a = @[@1.0, @1.0,  @3.14159]
b = @[@-1.0, @2.618033989, @3.0]
printf @"Dot product of [%@, %@, %@].[%@, %@, %@] = %.4f", a[0], a[1], a[2], b[0], b[1], b[2], fn DotProduct( a, b )

a = @[@8, @13, @-5]
b = @[@4, @-7, @-11]
printf @"Dot product of [%@, %@, %@].[%@, %@, %@] = %.4f", a[0], a[1], a[2], b[0], b[1], b[2], fn DotProduct( a, b )

a = @[@1, @2, @3]
b = @[@7, @8, @9]
printf @"Dot product of [%@, %@, %@].[%@, %@, %@] = %.4f", a[0], a[1], a[2], b[0], b[1], b[2], fn DotProduct( a, b )

CFMutableArrayRef x, y
x = fn MutableArrayWithCapacity(0)
y = fn MutableArrayWithCapacity(0)
for i = 0 to 9 : MutableArrayInsertObjectAtIndex( x, fn NumberWithInteger(i+ 1), i ) : next
for i = 0 to 9 : MutableArrayInsertObjectAtIndex( y, fn NumberWithInteger(i+11), i ) : next
    
printf @"Dot product of [1…10].[11…20] = %.4f", fn DotProduct( fn ArrayWithArray( x ), fn ArrayWithArray( y ) )
    
NSLog( @"%@", fn WindowPrintViewString( 1 ) )
    
HandleEvents

Output:

Dot product of [1, 3, -5].[4, -2, -1] = 3.0000
Dot product of [1, 1, 3.14159].[-1, 2.618033989, 3] = 11.0428
Dot product of [8, 13, -5].[4, -7, -11] = -4.0000
Dot product of [1, 2, 3].[7, 8, 9] = 50.0000
Dot product of [1…10].[11…20] = 935.0000

Fōrmulæ

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Programs in Fōrmulæ are created/edited online in its website.

In this page you can see and run the program(s) related to this task and their results. You can also change either the programs or the parameters they are called with, for experimentation, but remember that these programs were created with the main purpose of showing a clear solution of the task, and they generally lack any kind of validation.

Solution

Dot product is intrinsically supported in Fōrmulæ.

Test case

Special cases

Programmed. A program can be created to calculate the dot product of two vectors:

GAP

# Built-in

[1, 3, -5]*[4, -2, -1];
# 3

GLSL

The dot product is built-in:

float dot_product = dot(vec3(1, 3, -5), vec3(4, -2, -1));

Go

Implementation

package main

import (
    "errors"
    "fmt"
    "log"
)

var (
    v1 = []int{1, 3, -5}
    v2 = []int{4, -2, -1}
)

func dot(x, y []int) (r int, err error) {
    if len(x) != len(y) {
        return 0, errors.New("incompatible lengths")
    }
    for i, xi := range x {
        r += xi * y[i]
    }
    return
}

func main() {
    d, err := dot([]int{1, 3, -5}, []int{4, -2, -1})
    if err != nil {
        log.Fatal(err)
    }
    fmt.Println(d)
}

Output:

Library gonum/floats

package main

import (
    "fmt"

    "github.com/gonum/floats"
)

var (
    v1 = []float64{1, 3, -5}
    v2 = []float64{4, -2, -1}
)

func main() {
    fmt.Println(floats.Dot(v1, v2))
}

Output:

Groovy

Solution:

def dotProduct = { x, y ->
    assert x && y && x.size() == y.size()
    [x, y].transpose().collect{ xx, yy -> xx * yy }.sum()
}

Test:

println dotProduct([1, 3, -5], [4, -2, -1])

Output:

Haskell

dotp :: Num a => [a] -> [a] -> a 
dotp a b | length a == length b = sum (zipWith (*) a b)
         | otherwise = error "Vector sizes must match"
 
main = print $ dotp [1, 3, -5] [4, -2, -1] -- prints 3

Or, using the Maybe monad to avoid exceptions and keep things composable:

dotProduct :: Num a => [a] -> [a] -> Maybe a
dotProduct a b 
  | length a == length b = Just $ dp a b
  | otherwise = Nothing
    where
      dp x y = sum $ zipWith (*) x y


main :: IO ()
main = print n
  where
    Just n = dotProduct [1, 3, -5] [4, -2, -1]

Hoon

|=  [a=(list @sd) b=(list @sd)]
  =|  sum=@sd
  |-
  ?:  |(?=(~ a) ?=(~ b))  sum
  $(a t.a, b t.b, sum (sum:si sum (pro:si i.a i.b)))

Hy

(defn dotp [a b]
  (assert (= (len a) (len b)))
  (sum (genexpr (* aterm bterm)
                [(, aterm bterm) (zip a b)])))

(assert (= 3 (dotp [1 3 -5] [4 -2 -1])))

Icon and Unicon

The procedure below computes the dot product of two vectors of arbitrary length or generates a run time error if its arguments are the wrong type or shape.

procedure main()
write("a dot b := ",dotproduct([1, 3, -5],[4, -2, -1]))
end

procedure dotproduct(a,b)   #: return dot product of vectors a & b or error
if *a ~= *b & type(a) == type(b) == "list" then runerr(205,a) # invalid value
every (dp := 0) +:= a[i := 1 to *a] * b[i]
return dp
end

IDL

a = [1, 3, -5]
b = [4, -2, -1]
c = a#TRANSPOSE(b)
c = TOTAL(a*b,/PRESERVE_TYPE)

Idris

module Main

import Data.Vect

dotProduct : (Num a) => Vect n a -> Vect n a -> a
dotProduct = (sum .) . zipWith (*)

main : IO ()
main = printLn $ dotProduct [1,2,3] [1,2,3]

J

   1 3 _5  +/ . * 4 _2 _1
3
   dotp=: +/ . *                  NB. Or defined as a verb (function)
   1 3 _5  dotp 4 _2 _1
3

Note also: The verbs built using the conjunction . generally apply to matricies and arrays of higher dimensions and can be built with verbs (functions) other than sum ( +/ ) and product ( * ).

Spelling issue: The conjunction . needs to be preceded by a space. This is because J's spelling rules say that if the character '.' is preceded by any other character, it is included in the same parser token that included that other character. In other words, 1.23e4, '...' and /. are each examples of "parser tokens".

Janet

(defn dot-product
  "Calculates the dot product of two vectors."
  [vec-a vec-b]
  (assert (= (length vec-a) (length vec-b)) "Vector sizes must match")
  (sum (map * vec-a vec-b)))

(print (dot-product [1 3 -5] [4 -2 -1]))

Java

public class DotProduct {
	
	public static void main(String[] args) {
		double[] a = {1, 3, -5};
		double[] b = {4, -2, -1};
		
		System.out.println(dotProd(a,b));
	}
	
	public static double dotProd(double[] a, double[] b){
		if(a.length != b.length){
			throw new IllegalArgumentException("The dimensions have to be equal!");
		}
		double sum = 0;
		for(int i = 0; i < a.length; i++){
			sum += a[i] * b[i];
		}
		return sum;
	}
}

Output:

3.0

JavaScript

ES5

function dot_product(ary1, ary2) {
    if (ary1.length != ary2.length)
        throw "can't find dot product: arrays have different lengths";
    var dotprod = 0;
    for (var i = 0; i < ary1.length; i++)
        dotprod += ary1[i] * ary2[i];
    return dotprod;
}

print(dot_product([1,3,-5],[4,-2,-1])); // ==> 3
print(dot_product([1,3,-5],[4,-2,-1,0])); // ==> exception

We could also use map and reduce in lieu of iteration,

function dotp(x,y) {
    function dotp_sum(a,b) { return a + b; }
    function dotp_times(a,i) { return x[i] * y[i]; }
    if (x.length != y.length)
        throw "can't find dot product: arrays have different lengths";
    return x.map(dotp_times).reduce(dotp_sum,0);
}

dotp([1,3,-5],[4,-2,-1]); // ==> 3
dotp([1,3,-5],[4,-2,-1,0]); // ==> exception

ES6

Composing functional primitives into a dotProduct() which returns a null value (rather than an error) when the array lengths are unmatched.

(() => {
    "use strict";

    // ------------------- DOT PRODUCT -------------------

    // dotProduct :: [Num] -> [Num] -> Either Null Num
    const dotProduct = xs =>
        ys => xs.length === ys.length
            ? sum(zipWith(mul)(xs)(ys))
            : null;


    // ---------------------- TEST -----------------------

    // main :: IO ()
    const main = () =>
        dotProduct([1, 3, -5])([4, -2, -1]);


    // --------------------- GENERIC ---------------------

    // mul :: Num -> Num -> Num
    const mul = x =>
        y => x * y;


    // sum :: [Num] -> Num
    const sum = xs =>
    // The numeric sum of all values in xs.
        xs.reduce((a, x) => a + x, 0);


    // zipWith :: (a -> b -> c) -> [a] -> [b] -> [c]
    const zipWith = f =>
    // A list constructed by zipping with a
    // custom function, rather than with the
    // default tuple constructor.
        xs => ys => xs.map(
            (x, i) => f(x)(ys[i])
        ).slice(
            0, Math.min(xs.length, ys.length)
        );

    // MAIN ---
    return main();
})();

jq

The dot-product of two arrays, x and y, can be computed using dot(x;y) defined as follows:

def dot(x; y):
  reduce range(0;x|length) as $i (0; . + x[$i] * y[$i]);

Suppose however that we are given an array of objects, each of which has an "x" field and a "y" field, and that we wish to compute SIGMA( x * y ) where the sum is taken over the array, and where x and y denote the values in the "x" and "y" fields respectively.

This can most usefully be accomplished in jq with the aid of SIGMA(f) defined as follows:

def SIGMA( f ): reduce .[] as $o (0; . + ($o | f )) ;

Given the array of objects as input, the dot-product is then simply SIGMA( .x * .y ).

Example:

dot( [1, 3, -5]; [4, -2, -1]) # => 3

[ {"x": 1, "y": 4},  {"x": 3, "y": -2},  {"x": -5, "y": -1} ]
  | SIGMA( .x * .y ) # => 3

Jsish

From Javascript ES5 imperative entry.

/* Dot product, in Jsish */
function dot_product(ary1, ary2) {
    if (ary1.length != ary2.length) throw "can't find dot product: arrays have different lengths";
    var dotprod = 0;
    for (var i = 0; i < ary1.length; i++) dotprod += ary1[i] * ary2[i];
    return dotprod;
}

;dot_product([1,3,-5],[4,-2,-1]);
;//dot_product([1,3,-5],[4,-2,-1,0]);

/*
=!EXPECTSTART!=
dot_product([1,3,-5],[4,-2,-1]) ==> 3
dot_product([1,3,-5],[4,-2,-1,0]) ==>
PASS!: err = can't find dot product: arrays have different lengths
=!EXPECTEND!=
*/

Output:

prompt$ jsish --U dotProduct.jsi
dot_product([1,3,-5],[4,-2,-1]) ==> 3
dot_product([1,3,-5],[4,-2,-1,0]) ==>
PASS!: err = can't find dot product: arrays have different lengths

prompt$ jsish -u dotProduct.jsi
[PASS] dotProduct.jsi

Julia

Dot products and many other linear-algebra functions are built-in functions in Julia (and are largely implemented by calling functions from LAPACK).

x = [1, 3, -5]
y = [4, -2, -1]
z = dot(x, y)
z = x'*y
z = x ⋅ y

K

   +/1 3 -5 * 4 -2 -1
3

   1 3 -5 _dot 4 -2 -1
3

Klingphix

:sq_mul
    %c %i
    ( ) !c
    len [
        !i
        $i get rot $i get rot * $c swap 0 put !c
    ] for
    $c
;
 
:sq_sum
    0 swap
    len [
        get rot + swap
    ] for
    swap
;
 
( 1 3 -5 ) ( 4 -2 -1 )
sq_mul
sq_sum
pstack

" " input

Kotlin

Works with: Kotlin version 1.0+

fun dot(v1: Array<Double>, v2: Array<Double>) =
    v1.zip(v2).map { it.first * it.second }.reduce { a, b -> a + b }

fun main(args: Array<String>) {
    dot(arrayOf(1.0, 3.0, -5.0), arrayOf(4.0, -2.0, -1.0)).let { println(it) }
}

Output:

3.0

Lambdatalk

{def dotp
 {def dotp.r
  {lambda {:v1 :v2 :acc}
   {if {A.empty? :v1}
    then :acc
    else {dotp.r {A.rest :v1} {A.rest :v2}
                 {+ {* {A.first :v1} {A.first :v2}} :acc}}}}}
 {lambda {:v1 :v2}
  {if {= {A.length :v1} {A.length :v2}}
   then {dotp.r :v1 :v2 0}
   else Vectors must be of equal length}}}
-> dotp

{dotp {A.new 1 3 -5} {A.new 4 -2}}
-> Vectors must be of equal length

{dotp {A.new 1 3 -5} {A.new 4 -2 -1}}
-> 3

LFE

(defun dot-product (a b)
  (: lists foldl #'+/2 0
    (: lists zipwith #'*/2 a b)))

Liberty BASIC

vectorA$ = "1, 3, -5"
vectorB$ = "4, -2, -1"
print "DotProduct of ";vectorA$;" and "; vectorB$;" is ";
print DotProduct(vectorA$, vectorB$)

'arbitrary length
vectorA$ = "3, 14, 15, 9, 26"
vectorB$ = "2, 71, 18, 28, 1"
print "DotProduct of ";vectorA$;" and "; vectorB$;" is ";
print DotProduct(vectorA$, vectorB$)

end

function DotProduct(a$, b$)
    DotProduct = 0
    i = 1
    while 1
        x$=word$( a$, i, ",")
        y$=word$( b$, i, ",")
        if x$="" or y$="" then exit function
        DotProduct = DotProduct + val(x$)*val(y$)
        i = i+1
    wend
end function

LLVM

; This is not strictly LLVM, as it uses the C library function "printf".
; LLVM does not provide a way to print values, so the alternative would be
; to just load the string into memory, and that would be boring.

; Additional comments have been inserted, as well as changes made from the output produced by clang such as putting more meaningful labels for the jumps

;--- The declarations for the external C functions
declare i32 @printf(i8*, ...)

$"INTEGER_FORMAT" = comdat any

@main.a = private unnamed_addr constant [3 x i32] [i32 1, i32 3, i32 -5], align 4
@main.b = private unnamed_addr constant [3 x i32] [i32 4, i32 -2, i32 -1], align 4
@"INTEGER_FORMAT" = linkonce_odr unnamed_addr constant [4 x i8] c"%d\0A\00", comdat, align 1

; Function Attrs: noinline nounwind optnone uwtable
define i32 @dot_product(i32*, i32*, i64) #0 {
  %4 = alloca i64, align 8                              ;-- allocate copy of n
  %5 = alloca i32*, align 8                             ;-- allocate copy of b
  %6 = alloca i32*, align 8                             ;-- allocate copy of a
  %7 = alloca i32, align 4                              ;-- allocate sum
  %8 = alloca i64, align 8                              ;-- allocate i
  store i64 %2, i64* %4, align 8                        ;-- store a copy of n
  store i32* %1, i32** %5, align 8                      ;-- store a copy of b
  store i32* %0, i32** %6, align 8                      ;-- store a copy of a
  store i32 0, i32* %7, align 4                         ;-- store 0 in sum
  store i64 0, i64* %8, align 8                         ;-- store 0 in i
  br label %loop

loop:
  %9 = load i64, i64* %8, align 8                       ;-- load i
  %10 = load i64, i64* %4, align 8                      ;-- load n
  %11 = icmp ult i64 %9, %10                            ;-- i < n
  br i1 %11, label %loop_body, label %exit

loop_body:
  %12 = load i32*, i32** %6, align 8                    ;-- load a
  %13 = load i64, i64* %8, align 8                      ;-- load i
  %14 = getelementptr inbounds i32, i32* %12, i64 %13   ;-- calculate a[i]
  %15 = load i32, i32* %14, align 4                     ;-- load a[i]

  %16 = load i32*, i32** %5, align 8                    ;-- load b
  %17 = load i64, i64* %8, align 8                      ;-- load i
  %18 = getelementptr inbounds i32, i32* %16, i64 %17   ;-- calculate b[i]
  %19 = load i32, i32* %18, align 4                     ;-- load b[i]

  %20 = mul nsw i32 %15, %19                            ;-- temp = a[i] * b[i]

  %21 = load i32, i32* %7, align 4                      ;-- load sum
  %22 = add nsw i32 %21, %20                            ;-- add sum and temp
  store i32 %22, i32* %7, align 4                       ;-- store sum

  %23 = load i64, i64* %8, align 8                      ;-- load i
  %24 = add i64 %23, 1                                  ;-- increment i
  store i64 %24, i64* %8, align 8                       ;-- store i
  br label %loop

exit:
  %25 = load i32, i32* %7, align 4                      ;-- load sum
  ret i32 %25                                           ;-- return sum
}

; Function Attrs: noinline nounwind optnone uwtable
define i32 @main() #0 {
  %1 = alloca [3 x i32], align 4                        ;-- allocate a
  %2 = alloca [3 x i32], align 4                        ;-- allocate b

  %3 = bitcast [3 x i32]* %1 to i8*
  call void @llvm.memcpy.p0i8.p0i8.i64(i8* %3, i8* bitcast ([3 x i32]* @main.a to i8*), i64 12, i32 4, i1 false)

  %4 = bitcast [3 x i32]* %2 to i8*
  call void @llvm.memcpy.p0i8.p0i8.i64(i8* %4, i8* bitcast ([3 x i32]* @main.b to i8*), i64 12, i32 4, i1 false)

  %5 = getelementptr inbounds [3 x i32], [3 x i32]* %2, i32 0, i32 0
  %6 = getelementptr inbounds [3 x i32], [3 x i32]* %1, i32 0, i32 0
  %7 = call i32 @dot_product(i32* %6, i32* %5, i64 3)

  %8 = call i32 (i8*, ...) @printf(i8* getelementptr inbounds ([4 x i8], [4 x i8]* @"INTEGER_FORMAT", i32 0, i32 0), i32 %7)
  ret i32 0
}

; Function Attrs: argmemonly nounwind
declare void @llvm.memcpy.p0i8.p0i8.i64(i8* nocapture writeonly, i8* nocapture readonly, i64, i32, i1) #1

attributes #0 = { noinline nounwind optnone uwtable "correctly-rounded-divide-sqrt-fp-math"="false" "disable-tail-calls"="false" "less-precise-fpmad"="false" "no-frame-pointer-elim"="false" "no-infs-fp-math"="false" "no-jump-tables"="false" "no-nans-fp-math"="false" "no-signed-zeros-fp-math"="false" "no-trapping-math"="false" "stack-protector-buffer-size"="8" "target-cpu"="x86-64" "target-features"="+fxsr,+mmx,+sse,+sse2,+x87" "unsafe-fp-math"="false" "use-soft-float"="false" }

Output:

Logo

to dotprod :a :b
  output apply "sum (map "product :a :b)
end

show dotprod [1 3 -5] [4 -2 -1]    ; 3

Logtalk

dot_product(A, B, Sum) :-
    dot_product(A, B, 0, Sum).

dot_product([], [], Sum, Sum).
dot_product([A| As], [B| Bs], Acc, Sum) :-
    Acc2 is Acc + A*B,
    dot_product(As, Bs, Acc2, Sum).

Lua

function dotprod(a, b)
  local ret = 0
  for i = 1, #a do
    ret = ret + a[i] * b[i]
  end
  return ret
end

print(dotprod({1, 3, -5}, {4, -2, 1}))

M2000 Interpreter

Version 12 can use types for arrays (earlier versions use variant type by default).

So we can adjust the return value of Dot() to be the same as the first item of first array. All functions of M2000 return variant type (including objects) or array of variant values, for multiple values (which is an object too).

Module dot_product {
      A=(1,3,-5)
      B=(4,-2,-1)
      Function Dot(a, b) {
            if len(a)<>len(b) Then Error "not same length"
            if len(a)=0 then Error "empty vectors"
            object a1=each(a), b1=each(b)
            // take type by first item in a()
            long lowbound=dimension(a,1,0)
            sum=a#val(lowbound)-a#val(lowbound)
            While a1, b1 {sum+=array(a1)*array(b1)}
            =sum
      }
      Print Dot(A, B)=3
      Print Dot((1,3,-5), (4,-2,-1), 0)=3
      dim k(2 to 4) as long long, z(3) as long long
      k(2)=1,3,-5
      z(0)=4,-2,-1
      result=Dot(k(), z())
      Print result=3, type$(result)="Long Long"   
}
Module dot_product

Maple

Between Arrays, Vectors, or Matrices you can use the dot operator:

<1,2,3> . <4,5,6>

Array([1,2,3]) . Array([4,5,6])

Between any of the above or lists, you can use the LinearAlgebra[DotProduct] function:

LinearAlgebra( <1,2,3>, <4,5,6> )

LinearAlgebra( Array([1,2,3]), Array([4,5,6]) )

LinearAlgebra([1,2,3], [4,5,6] )

Mathematica / Wolfram Language

{1,3,-5}.{4,-2,-1}

MATLAB

The dot product operation is a built-in function that operates on vectors of arbitrary length.

A = [1 3 -5]
B = [4 -2 -1]
C = dot(A,B)

For the Octave implimentation:

function C = DotPro(A,B)
  C = sum( A.*B );
end

Maxima

[1, 3, -5] . [4, -2, -1];
/* 3 */

Mercury

This will cause a software_error/1 exception if the lists are of different lengths.

:- module dot_product.
:- interface.

:- import_module io.
:- pred main(io::di, io::uo) is det.

:- implementation.
:- import_module int, list.

main(!IO) :-
    io.write_int([1, 3, -5] `dot_product` [4, -2, -1], !IO),
    io.nl(!IO).

:- func dot_product(list(int), list(int)) = int.

dot_product(As, Bs) =
    list.foldl_corresponding((func(A, B, Acc) = Acc + A * B), As, Bs, 0).

МК-61/52

С/П	*	ИП0	+	П0	С/П	БП	00

Input: В/О x₁ С/П x₂ С/П y₁ С/П y₂ С/П ...

Modula-2

MODULE DotProduct;
FROM RealStr IMPORT RealToStr;
FROM Terminal IMPORT WriteString,WriteLn,ReadChar;

TYPE Vector =
    RECORD
        x,y,z : REAL
    END;

PROCEDURE DotProduct(u,v : Vector) : REAL;
BEGIN
    RETURN u.x*v.x + u.y*v.y + u.z*v.z
END DotProduct;

VAR
    buf : ARRAY[0..63] OF CHAR;
    dp : REAL;
BEGIN
    dp := DotProduct(Vector{1.0,3.0,-5.0},Vector{4.0,-2.0,-1.0});
    RealToStr(dp, buf);
    WriteString(buf);
    WriteLn;

    ReadChar
END DotProduct.

MUMPS

DOTPROD(A,B)
 ;Returns the dot product of two vectors. Vectors are assumed to be stored as caret-delimited strings of numbers.
 ;If the vectors are not of equal length, a null string is returned.
 QUIT:$LENGTH(A,"^")'=$LENGTH(B,"^") ""
 NEW I,SUM
 SET SUM=0
 FOR I=1:1:$LENGTH(A,"^") SET SUM=SUM+($PIECE(A,"^",I)*$PIECE(B,"^",I))
 KILL I
 QUIT SUM

Nemerle

This will cause an exception if the arrays are different lengths.

using System;
using System.Console;
using Nemerle.Collections.NCollectionsExtensions;

module DotProduct
{
    DotProduct(x : array[int], y : array[int]) : int
    {
        $[(a * b)|(a, b) in ZipLazy(x, y)].FoldLeft(0, _+_);    
    }
    
    Main() : void
    {
        def arr1 = array[1, 3, -5]; def arr2 = array[4, -2, -1];
        WriteLine(DotProduct(arr1, arr2));
    }
}

NetRexx

/* NetRexx */
options replace format comments java crossref savelog symbols binary

whatsTheVectorVictor = [[double 1.0, 3.0, -5.0], [double 4.0, -2.0, -1.0]]
dotProduct = Rexx dotProduct(whatsTheVectorVictor)
say dotProduct.format(null, 2)

return

method dotProduct(vec1 = double[], vec2 = double[]) public constant returns double signals IllegalArgumentException
  if vec1.length \= vec2.length then signal IllegalArgumentException('Vectors must be the same length')

  scalarProduct = double 0.0
  loop e_ = 0 to vec1.length - 1
    scalarProduct = vec1[e_] * vec2[e_] + scalarProduct
    end e_

  return scalarProduct

method dotProduct(vecs = double[,]) public constant returns double signals IllegalArgumentException
  return dotProduct(vecs[0], vecs[1])

newLISP

(define (dot-product x y) 
  (apply + (map * x y)))

(println (dot-product '(1 3 -5) '(4 -2 -1)))

Nim

# Compile time error when a and b are differently sized arrays
# Runtime error when a and b are differently sized seqs
proc dotp[T](a,b: T): int =
  doAssert a.len == b.len
  for i in a.low..a.high:
    result += a[i] * b[i]

echo dotp([1,3,-5], [4,-2,-1])
echo dotp(@[1,2,3],@[4,5,6])

Another version which allows to mix arrays and sequences provided they have the same length. It works also with miscellaneous number types (integers, floats).

# Runtime error if lengths of arrays or sequences differ.

func dotProduct[T](a, b: openArray[T]): T =
  doAssert a.len == b.len
  for i in 0..a.high:
    result += a[i] * b[i]

echo dotProduct([1,3,-5], [4,-2,-1])
echo dotProduct(@[1,2,3],@[4,5,6])
echo dotProduct([1.0, 2.0, 3.0], @[7.0, 8.0, 9.0])

Nu

Works with: Nushell version 0.97.1

def 'math dot' [v] {
  zip $v | each { math product } | math sum
}

[1 3 -5] | math dot [4 -2 -1]

Output:

Oberon-2

Works with: oo2c version 2

MODULE DotProduct;
IMPORT
  Out := NPCT:Console;

VAR
  x,y: ARRAY 3 OF LONGINT;

PROCEDURE DotProduct(a,b: ARRAY OF LONGINT): LONGINT;
VAR 
  resp, i: LONGINT;
BEGIN
  ASSERT(LEN(a) = LEN(b));
  resp := 0;
  FOR i := 0 TO LEN(x) - 1 DO
    INC(resp,x[i]*y[i])
  END;
  RETURN resp
END DotProduct;

BEGIN
  x[0] := 1;y[0] := 4;
  x[1] := 3;y[1] := -2;
  x[2] := -5;y[2] := -1; 
  Out.Int(DotProduct(x,y),0);Out.Ln
END DotProduct.

Output:

Objeck

bundle Default {
  class DotProduct {
    function : Main(args : String[]) ~ Nil {
      DotProduct([1, 3, -5], [4, -2, -1])->PrintLine();
    }
    
    function : DotProduct(array_a : Int[], array_b : Int[]) ~ Int {
      if(array_a = Nil) {
        return 0;
      };
     
      if(array_b = Nil) {
        return 0;
      };
     
      if(array_a->Size() <> array_b->Size()) {
        return 0;
      };
      
      val := 0;
      for(x := 0; x < array_a->Size(); x += 1;) {
        val += (array_a[x] * array_b[x]);
      };
     
      return val;
    }
  }
}

Objective-C

#import <stdio.h>
#import <stdint.h>
#import <stdlib.h>
#import <string.h>
#import <Foundation/Foundation.h>

// this class exists to return a result between two
// vectors: if vectors have different "size", valid
// must be NO
@interface VResult : NSObject
{
 @private
  double value;
  BOOL valid;
}
+(instancetype)new: (double)v isValid: (BOOL)y;
-(instancetype)init: (double)v isValid: (BOOL)y;
-(BOOL)isValid;
-(double)value;
@end

@implementation VResult
+(instancetype)new: (double)v isValid: (BOOL)y
{
  return [[self alloc] init: v isValid: y];
}
-(instancetype)init: (double)v isValid: (BOOL)y
{
  if ((self == [super init])) {
    value = v;
    valid = y;
  }
  return self;
}
-(BOOL)isValid { return valid; }
-(double)value { return value; }
@end


@interface RCVector : NSObject
{
 @private
  double *vec;
  uint32_t size;
}
+(instancetype)newWithArray: (double *)v ofLength: (uint32_t)l; 
-(instancetype)initWithArray: (double *)v ofLength: (uint32_t)l;
-(VResult *)dotProductWith: (RCVector *)v;
-(uint32_t)size;
-(double *)array;
-(void)free;
@end

@implementation RCVector
+(instancetype)newWithArray: (double *)v ofLength: (uint32_t)l
{
  return [[self alloc] initWithArray: v ofLength: l];
}
-(instancetype)initWithArray: (double *)v ofLength: (uint32_t)l
{
  if ((self = [super init])) {
    size = l;
    vec = malloc(sizeof(double) * l);
    if ( vec == NULL )
      return nil;
    memcpy(vec, v, sizeof(double)*l);
  }
  return self;
}
-(void)dealloc
{
  free(vec);
}
-(uint32_t)size { return size; }
-(double *)array { return vec; }
-(VResult *)dotProductWith: (RCVector *)v
{
  double r = 0.0;
  uint32_t i, s;
  double *v1;
  if ( [self size] != [v size] ) return [VResult new: r isValid: NO];
  s = [self size];
  v1 = [v array];
  for(i = 0; i < s; i++) {
    r += vec[i] * v1[i];
  }
  return [VResult new: r isValid: YES];
}
@end

double val1[] = { 1, 3, -5 };
double val2[] = { 4,-2, -1 }; 

int main()
{
  @autoreleasepool {
    RCVector *v1 = [RCVector newWithArray: val1 ofLength: sizeof(val1)/sizeof(double)];
    RCVector *v2 = [RCVector newWithArray: val2 ofLength: sizeof(val1)/sizeof(double)];
    VResult *r = [v1 dotProductWith: v2];
    if ( [r isValid] ) {
      printf("%lf\n", [r value]);
    } else {
      fprintf(stderr, "length of vectors differ\n");
    }
  }
  return 0;
}

OCaml

With lists:

let dot = List.fold_left2 (fun z x y -> z +. x *. y) 0.

(*
# dot [1.0; 3.0; -5.0] [4.0; -2.0; -1.0];;
- : float = 3.
*)

With arrays:

let dot v u =
  if Array.length v <> Array.length u
  then invalid_arg "Different array lengths";
  let times v u =
    Array.mapi (fun i v_i -> v_i *. u.(i)) v
  in Array.fold_left (+.) 0. (times v u)

(*
# dot [| 1.0; 3.0; -5.0 |] [| 4.0; -2.0; -1.0 |];;
- : float = 3.
*)

Octave

See Dot product#MATLAB for an implementation. If we have a row-vector and a column-vector, we can use simply *.

a = [1, 3, -5]
b = [4, -2, -1] % or [4; -2; -1] and avoid transposition with '
disp( a * b' )  % ' means transpose

Oforth

: dotProduct  zipWith(#*) sum ;

Output:

>[ 1, 3, -5] [ 4, -2, -1 ] dotProduct .
3

Ol

(define (dot-product a b)
  (apply + (map * a b)))
 
(print (dot-product '(1 3 -5) '(4 -2 -1)))
; ==> 3

Oz

Vectors are represented as lists in this example.

declare
  fun {DotProduct Xs Ys}
     {Length Xs} = {Length Ys} %% assert
     {List.foldL {List.zip Xs Ys Number.'*'} Number.'+' 0}
  end
in
  {Show {DotProduct [1 3 ~5] [4 ~2 ~1]}}

PARI/GP

dot(u,v)={
  sum(i=1,#u,u[i]*v[i])
};

Alternative

dot(u,v) = u * v~;

Pascal

See Delphi

Perl

sub dotprod
{
        my($vec_a, $vec_b) = @_;
        die "they must have the same size\n" unless @$vec_a == @$vec_b;
        my $sum = 0;
        $sum += $vec_a->[$_] * $vec_b->[$_] for 0..$#$vec_a;
        return $sum;
}

my @vec_a = (1,3,-5);
my @vec_b = (4,-2,-1);

print dotprod(\@vec_a,\@vec_b), "\n"; # 3

Phix

?sum(sq_mul({1,3,-5},{4,-2,-1}))

Output:

Phixmonti

def sq_mul
    0 tolist var c
    len for
        var i
        i get rot i get rot * c swap 0 put var c
    endfor
    c
enddef

def sq_sum
    0 swap
    len for
        get rot + swap
    endfor
    swap
enddef

1 3 -5 3 tolist
4 -2 -1 3 tolist
sq_mul
sq_sum
pstack

PHP

<?php
function dot_product($v1, $v2) {
  if (count($v1) != count($v2))
    throw new Exception('Arrays have different lengths');
  return array_sum(array_map('bcmul', $v1, $v2));
}

echo dot_product(array(1, 3, -5), array(4, -2, -1)), "\n";
?>

Picat

go =>
  L1 = [1, 3, -5],
  L2 = [4, -2, -1],

  println(dot_product=dot_product(L1,L2)),
  catch(println(dot_product([1,2,3,4],[1,2,3])),E, println(E)),
  nl.

dot_product(L1,L2) = _, L1.length != L2.length  => 
  throw($dot_product_not_same_length(L1,L2)).
dot_product(L1,L2) = sum([L1[I]*L2[I] : I in 1..L1.length]).

Output:

dot_product = 3
dot_product_not_same_length([1,2,3,4],[1,2,3])

PicoLisp

(de dotProduct (A B)
   (sum * A B) )

(dotProduct (1 3 -5) (4 -2 -1))

Output:

-> 3

PL/I

get (n);
begin;
   declare (A(n), B(n)) float;
   declare dot_product float;

   get list (A);
   get list (B);
   dot_product = sum(a*b);
   put (dot_product);
end;

Plain English

To run:
Start up.
Make an example vector and another example vector.
Compute a dot product of the example vector and the other example vector.
Destroy the example vector. Destroy the other example vector.
Convert the dot product to a string.
Write the string on the console.
Wait for the escape key.
Shut down.

An element is a thing with a number.

A vector is some elements.

To add a number to a vector:
Allocate memory for an element.
Put the number into the element's number.
Append the element to the vector.

To multiply a vector by another vector:
If the vector's count is not the other vector's count, exit.
Get an element from the vector.
Get another element from the other vector.
Loop.
If the element is nil, exit.
Multiply the element's number by the other element's number.
Put the element's next into the element.
Put the other element's next into the other element.
Repeat.

A sum is a number.

To find a sum of a vector:
Get an element from the vector.
Loop.
If the element is nil, exit.
Add the element's number to the sum.
Put the element's next into the element.
Repeat.

A product is a number.

To compute a dot product of a vector and another vector:
If the vector's count is not the other vector's count, exit.
Multiply the vector by the other vector.
Find a sum of the vector.
Put the sum into the dot product.

To make an example vector and another example vector:
Add 1 to the example vector.
Add 3 to the example vector.
Add -5 to the example vector.
Add 4 to the other example vector.
Add -2 to the other example vector.
Add -1 to the other example vector.

Output:

PostScript

/dotproduct{
/x exch def
/y exch def
/sum 0 def
/i 0 def
x length y length eq %Check if both arrays have the same length
{
x length{
/sum x i get y i get mul sum add def
/i i 1 add def
}repeat
sum ==
}
{
-1 ==
}ifelse
}def

PowerShell

function dotproduct( $a, $b) {
    $a | foreach -Begin {$i = $res = 0} -Process { $res += $_*$b[$i++] } -End{$res}
} 
dotproduct (1..2) (1..2) 
dotproduct (1..10) (11..20)

Output:

 
5 
935

Prolog

Works with SWI-Prolog.

dot_product(L1, L2, N) :-
	maplist(mult, L1, L2, P),
	sumlist(P, N).

mult(A,B,C) :-
	C is A*B.

Example :

 ?- dot_product([1,3,-5], [4,-2,-1], N).
N = 3.

PureBasic

Procedure dotProduct(Array a(1),Array b(1))
  Protected i, sum, length = ArraySize(a())

  If ArraySize(a()) = ArraySize(b())
    For i = 0 To length
      sum + a(i) * b(i)
    Next
  EndIf

  ProcedureReturn sum
EndProcedure

If OpenConsole()
  Dim a(2)
  Dim b(2)
  
  a(0) = 1 : a(1) = 3 : a(2) = -5
  b(0) = 4 : b(1) = -2 : b(2) = -1
  
  PrintN(Str(dotProduct(a(),b())))
  
  Print(#CRLF$ + #CRLF$ + "Press ENTER to exit"): Input()
  CloseConsole()
EndIf

Python

def dotp(a,b):
    assert len(a) == len(b), 'Vector sizes must match'
    return sum(aterm * bterm for aterm,bterm in zip(a, b))

if __name__ == '__main__':
    a, b = [1, 3, -5], [4, -2, -1]
    assert dotp(a,b) == 3

Option types can provide a composable alternative to assertions and error-handling. Here is an example of an Either type, which returns either a computed value (in a Right wrapping), or an explanatory string (in a Left wrapping).

A higher order either function can apply one of two supplied functions to an Either value - one for Left Either values, and one for Right Either values:

Works with: Python version 3.7

'''Dot product'''

from operator import (mul)


# dotProduct :: Num a => [a] -> [a] -> Either String a
def dotProduct(xs):
    '''Either the dot product of xs and ys,
       or a string reporting unmatched vector sizes.
    '''
    return lambda ys: Left('vector sizes differ') if (
        len(xs) != len(ys)
    ) else Right(sum(map(mul, xs, ys)))


# TEST ----------------------------------------------------
# main :: IO ()
def main():
    '''Dot product of other vectors with [1, 3, -5]'''

    print(
        fTable(main.__doc__ + ':\n')(str)(str)(
            compose(
                either(append('Undefined :: '))(str)
            )(dotProduct([1, 3, -5]))
        )([[4, -2, -1, 8], [4, -2], [4, 2, -1], [4, -2, -1]])
    )


# GENERIC -------------------------------------------------

# Left :: a -> Either a b
def Left(x):
    '''Constructor for an empty Either (option type) value
       with an associated string.
    '''
    return {'type': 'Either', 'Right': None, 'Left': x}


# Right :: b -> Either a b
def Right(x):
    '''Constructor for a populated Either (option type) value'''
    return {'type': 'Either', 'Left': None, 'Right': x}


# append (++) :: [a] -> [a] -> [a]
# append (++) :: String -> String -> String
def append(xs):
    '''Two lists or strings combined into one.'''
    return lambda ys: xs + ys


# compose (<<<) :: (b -> c) -> (a -> b) -> a -> c
def compose(g):
    '''Right to left function composition.'''
    return lambda f: lambda x: g(f(x))


# either :: (a -> c) -> (b -> c) -> Either a b -> c
def either(fl):
    '''The application of fl to e if e is a Left value,
       or the application of fr to e if e is a Right value.
    '''
    return lambda fr: lambda e: fl(e['Left']) if (
        None is e['Right']
    ) else fr(e['Right'])


# FORMATTING ----------------------------------------------

# fTable :: String -> (a -> String) ->
#                     (b -> String) -> (a -> b) -> [a] -> String
def fTable(s):
    '''Heading -> x display function -> fx display function ->
                     f -> xs -> tabular string.
    '''
    def go(xShow, fxShow, f, xs):
        ys = [xShow(x) for x in xs]
        w = max(map(len, ys))
        return s + '\n' + '\n'.join(map(
            lambda x, y: y.rjust(w, ' ') + ' -> ' + fxShow(f(x)),
            xs, ys
        ))
    return lambda xShow: lambda fxShow: lambda f: lambda xs: go(
        xShow, fxShow, f, xs
    )


# MAIN ---
if __name__ == '__main__':
    main()

Output:

Dot product of other vectors with [1, 3, -5]:

[4, -2, -1, 8] -> Undefined :: vector sizes differ
       [4, -2] -> Undefined :: vector sizes differ
    [4, 2, -1] -> 15
   [4, -2, -1] -> 3

QBasic

Works with: QBasic version 1.1

Translation of: FreeBASIC

DIM zero3d(2)  'some example vectors
zero3d(0) = 0!: zero3d(1) = 0!: zero3d(2) = 0!
DIM zero5d(4)
zero5d(0) = 0!: zero5d(1) = 0!: zero5d(2) = 0!: zero5d(3) = 0!: zero5d(4) = 0!
DIM x(2): x(0) = 1!: x(1) = 0!: x(2) = 0!
DIM y(2): y(0) = 0!: y(1) = 1!: y(2) = 0!
DIM z(2): z(0) = 0!: z(1) = 0!: z(2) = 1!
DIM q(2): q(0) = 1!: q(1) = 1!: q(2) = 3.14159
DIM r(2): r(0) = -1!: r(1) = 2.618033989#: r(2) = 3!

PRINT " q dot r           = "; dot(q(), r())
PRINT " zero3d dot zero5d = "; dot(zero3d(), zero5d())
PRINT " zero3d dot x      = "; dot(zero3d(), x())
PRINT " z dot z           = "; dot(z(), z())
PRINT " y dot z           = "; dot(y(), z())

FUNCTION dot (a(), b())
    IF UBOUND(a) <> UBOUND(b) THEN dot = 0
    
    dp = 0!
    FOR i = 0 TO UBOUND(a)
        dp = dp + (a(i) * b(i))
    NEXT i
    dot = dp
END FUNCTION

Quackery

[ 0 unrot witheach
    [ over i^ peek * 
      rot + swap ] 
  drop ]             is .prod ( [ [ --> n )

 ' [ 1 3 -5 ] ' [ 4 -2 -1 ] .prod echo

Output:

R

Here are several ways to do the task.

x <- c(1, 3, -5)
y <- c(4, -2, -1)

sum(x*y)  # compute products, then do the sum
x %*% y   # inner product

# loop implementation
dotp <- function(x, y) {
	n <- length(x)
	if(length(y) != n) stop("invalid argument")
	s <- 0
	for(i in 1:n) s <- s + x[i]*y[i]
	s
}

dotp(x, y)

Racket

#lang racket
(define (dot-product l r) (for/sum ([x l] [y r]) (* x y)))

(dot-product '(1 3 -5) '(4 -2 -1))

;; dot-product works on sequences such as vectors:
(dot-product #(1 2 3) #(4 5 6))

Raku

(formerly Perl 6)

Works with: Rakudo version 2010.07

We use the square-bracket meta-operator to turn the infix operator + into a reducing list operator, and the guillemet meta-operator to vectorize the infix operator *. Length validation is automatic in this form.

sub infix:<·> { [+] @^a »*« @^b }

say (1, 3, 5)·(4, -2, 1);

Rascal

import List;

public int dotProduct(list[int] L, list[int] M){
	result = 0;
	if(size(L) == size(M)) {
		while(size(L) >= 1) {
		    result += (head(L) * head(M));
		    L = tail(L);
		    M = tail(M);
	        }
	        return result; 
	}
	else {
		throw "vector sizes must match";
	}
}

Alternative solution

If a matrix is represented by a relation of <x-coordinate, y-coordinate, value>, then function below can be used to find the Dot product.

import Prelude;

public real matrixDotproduct(rel[real x, real y, real v] column1, rel[real x, real y, real v] column2){
	return (0.0 | it + v1*v2 | <x1,y1,v1> <- column1, <x2,y2,v2> <- column2, y1==y2);
}

//a matrix, given by a relation of x-coordinate, y-coordinate, value.
public rel[real x, real y, real v] matrixA = {
<0.0,0.0,12.0>, <0.0,1.0, 6.0>, <0.0,2.0,-4.0>, 
<1.0,0.0,-51.0>, <1.0,1.0,167.0>, <1.0,2.0,24.0>, 
<2.0,0.0,4.0>, <2.0,1.0,-68.0>, <2.0,2.0,-41.0>
};

REBOL

REBOL []

a: [1 3 -5]
b: [4 -2 -1]

dot-product: function [v1 v2] [sum] [
    if (length? v1) != (length? v2) [
        make error! "error: vector sizes must match"
    ]
    sum: 0
    repeat i length? v1 [
        sum: sum + ((pick v1 i) * (pick v2 i)) 
    ]
]

dot-product a b

REXX

With error checking

/*REXX program computes the dot product of two equal size vectors (of any size).*/
vectorA =  '  1   3  -5  '               /*populate vector  A  with some numbers*/
vectorB =  '  4  -2  -1  '               /*    "       "    B    "    "     "   */
Say  'vector A =' vectorA                /*display the elements of vector A.    */
Say  'vector B =' vectorB                /*   "     "     "      "   "    B.    */
p=dot_product(vectorA,vectorB)           /*invoke function & compute dot product*/
Say                                      /*display a blank line for readability.*/
Say 'dot product =' p                    /*display the dot product              */
Exit                                     /*stick a fork in it,  we're all done. */
/*------------------------------------------------------------------------------*/
dot_product:                             /* compute the dot product             */
  Parse Arg A,B
  /* Begin Error Checking                                                       */
  If words(A)<>words(B) Then
    Call exit 'Vectors aren''t the same size:' words(A) '<>' words(B)
  Do i=1 To words(A)
    If datatype(word(A,i))<>'NUM' Then
      Call exit 'Element' i 'of vector A isn''t a number:' word(A,i)
    If datatype(word(B,i))<>'NUM' Then
      Call exit 'Element' i 'of vector B isn''t a number:' word(B,i)
    End
  /* End Error Checking                                                         */
  product=0                              /* initialize the  sum  to   0  (zero).*/
  Do i=1 To words(A)
    product=product+word(A,i)*word(B,i)  /*multiply corresponding numbers       */
    End
  Return product
exit:
  Say '***error***' arg(1)
  Exit 13

output using the default (internal) inputs:

vector A =   1   3  -5
vector B =   4  -2  -1

dot product =  3

Ring

aVector = [2, 3, 5]
bVector = [4, 2, 1]
sum = 0
see dotProduct(aVector, bVector)

func dotProduct cVector, dVector
     for n = 1 to len(aVector)
         sum = sum + cVector[n] * dVector[n]
     next
     return sum

RLaB

In its simplest form dot product is a composition of two functions: element-by-element multiplication '.*' followed by sumation of an array. Consider an example:

x = rand(1,10);
y = rand(1,10);
s = sum( x .* y );

Warning: element-by-element multiplication is matrix optimized. As the interpretation of the matrix optimization is quite general, and unique to RLaB, any two matrices can be so multiplied irrespective of their dimensions. It is up to user to check whether in his/her case the matrix optimization needs to be restricted, and then to implement restrictions in his/her code.

RPL

Being a language for a calculator, RPL makes this easy.

 [ 1  3 -5 ]
 [ 4 -2 -1 ]
 DOT

Ruby

With the standard library, require 'matrix' and call Vector#inner_product.

irb(main):001:0> require 'matrix'
=> true
irb(main):002:0> Vector[1, 3, -5].inner_product Vector[4, -2, -1]
=> 3

Or implement dot product.

class Array
  def dot_product(other)
    raise "not the same size!" if self.length != other.length
    zip(other).sum {|a, b| a*b}
  end
end

p [1, 3, -5].dot_product [4, -2, -1]   # => 3

Run BASIC

v1$ = "1, 3, -5"
v2$ = "4, -2, -1"

print "DotProduct of ";v1$;" and "; v2$;" is ";dotProduct(v1$,v2$)
end
 
function dotProduct(a$, b$)
    while word$(a$,i + 1,",") <> ""
       i = i + 1
       v1$=word$(a$,i,",")
       v2$=word$(b$,i,",")
       dotProduct = dotProduct + val(v1$) * val(v2$)
    wend
end function

Rust

Implemented as a simple function with check for equal length of vectors.

// alternatively, fn dot_product(a: &Vec<u32>, b: &Vec<u32>)
// but using slices is more general and rustic
fn dot_product(a: &[i32], b: &[i32]) -> Option<i32> {
    if a.len() != b.len() { return None }
    Some(
        a.iter()
            .zip( b.iter() )
            .fold(0, |sum, (el_a, el_b)| sum + el_a*el_b)
    )
}


fn main() {
    let v1 = vec![1, 3, -5];
    let v2 = vec![4, -2, -1];

    println!("{}", dot_product(&v1, &v2).unwrap());
}

Alternatively as a very generic function which works for any two types that can be multiplied to result in a third type which can be added with itself. Works with any argument convertible to an Iterator of known length (ExactSizeIterator).

Uses an unstable feature.

#![feature(zero_one)] // <-- unstable feature
use std::ops::{Add, Mul};
use std::num::Zero;

fn dot_product<T1, T2, U, I1, I2>(lhs: I1, rhs: I2) -> Option<U>
    where T1: Mul<T2, Output = U>,
          U: Add<U, Output = U> + Zero,
          I1: IntoIterator<Item = T1>,
          I2: IntoIterator<Item = T2>,
          I1::IntoIter: ExactSizeIterator,
          I2::IntoIter: ExactSizeIterator,
{
    let (iter_lhs, iter_rhs) = (lhs.into_iter(), rhs.into_iter());
    match (iter_lhs.len(), iter_rhs.len()) {
        (0, _) | (_, 0) => None,
        (a,b) if a != b => None,
        (_,_) => Some( iter_lhs.zip(iter_rhs)
           .fold(U::zero(), |sum, (a, b)| sum + (a * b)) )
    }
}



fn main() {
    let v1 = vec![1, 3, -5];
    let v2 = vec![4, -2, -1];

    println!("{}", dot_product(&v1, &v2).unwrap());
}

S-lang

print(sum([1, 3, -5] * [4, -2, -1]));

Output:

3.0

[sum() returns a double from integer arrays]

Sather

Built-in class VEC "implements" euclidean (geometric) vectors.

class MAIN is
  main is
    x ::= #VEC(|1.0, 3.0, -5.0|);
    y ::= #VEC(|4.0, -2.0, -1.0|);
    #OUT + x.dot(y) + "\n";
  end;
end;

Scala

Library: Scala

class Dot[T](v1: Seq[T])(implicit n: Numeric[T]) {
  import n._ // import * operator
  def dot(v2: Seq[T]) = {
    require(v1.size == v2.size)
    (v1 zip v2).map{ Function.tupled(_ * _)}.sum
  }
}

object Main extends App {
  implicit def toDot[T: Numeric](v1: Seq[T]) = new Dot(v1)

  val v1 = List(1, 3, -5)
  val v2 = List(4, -2, -1)
  println(v1 dot v2)
}

Scheme

Works with: Scheme version R

^{5}

RS

(define (dot-product a b)
  (apply + (map * a b)))

(display (dot-product '(1 3 -5) '(4 -2 -1)))
(newline)

Output:

Scilab

A = [1 3 -5]
B = [4 -2 -1]
C = sum(A.*B)

Seed7

$ include "seed7_05.s7i";

$ syntax expr: .().dot.() is  -> 6;  # priority of dot operator

const func integer: (in array integer: a) dot (in array integer: b) is func
  result
    var integer: sum is 0;
  local
    var integer: index is 0;
  begin
    if length(a) <> length(b) then
      raise RANGE_ERROR;
    else
      for index range 1 to length(a) do
        sum +:= a[index] * b[index];
      end for;
    end if;
  end func;
 
const proc: main is func
  begin
    writeln([](1, 3, -5) dot [](4, -2, -1));
  end func;

Sidef

func dot_product(a, b) {
    (a »*« b)«+»;
};
say dot_product([1,3,-5], [4,-2,-1]);   # => 3

Slate

v@(Vector traits) <dot> w@(Vector traits)
"Dot-product."
[
  (0 below: (v size min: w size)) inject: 0 into:
    [| :sum :index | sum + ((v at: index) * (w at: index))]
].

Smalltalk

Works with: GNU Smalltalk

Array extend
[
  * anotherArray [
       |acc| acc := 0.
       self with: anotherArray collect: [ :a :b |
          acc := acc + ( a * b )
       ].
       ^acc
  ]
]

( #(1 3 -5) * #(4 -2 -1 ) ) printNl.

SNOBOL4

        define("dotp(a,b)sum,i")        :(dotp_end)
dotp    i = 1; sum = 0      
loop    sum = sum + (a<i> * b<i>)
        i = i + 1 ?a<i> :s(loop)
        dotp = sum      :(return)
dotp_end

        a = array(3); a<1> = 1; a<2> = 3; a<3> = -5; 
        b = array(3); b<1> = 4; b<2> = -2; b<3> = -1;
        output = dotp(a,b)
end

SparForte

As a structured script.

#!/usr/local/bin/spar
pragma annotate( summary, "dotproduct" )
       @( description, "Create a function/use an in-built function, to compute" )
       @( description, "the dot product, also known as the scalar product of two" )
       @( description, "vectors. If possible, make the vectors of arbitrary length." )
       @( description, "As an example, compute the dot product of the vectors [1," )
       @( description, " 3, -5] and [4, -2, -1]." )
       @( description, "If implementing the dot product of two vectors directly," )
       @( description, "each vector must be the same length; multiply" )
       @( description, "corresponding terms from each vector then sum the results" )
       @( description, "to produce the answer. " )
       @( see_also, "http://rosettacode.org/wiki/Dot_product" )
       @( author, "Ken O. Burtch" );
pragma license( unrestricted );

pragma restriction( no_external_commands );

procedure dotproduct is
  type vect3 is array(1..3) of integer;
  v1 : constant vect3 := (1,3,-5);
  v2 : constant vect3 := (4,-2,-1);

  sum_total : integer := 0;
begin
  if arrays.length( v1 ) /= arrays.length( v2 ) then
     put_line( standard_error, "different lengths" );
     command_list.set_exit_status( 193 );
     return;
  end if;
  if arrays.first( v1 ) /= arrays.first( v2 ) then
     put_line( standard_error, "different starts" );
     command_list.set_exit_status( 194 );
     return;
  end if;
  for p in arrays.first( v1 )..arrays.last( v1 ) loop
      sum_total := @ + v1(p)*v2(p);
  end loop;
  ? sum_total;
end dotproduct;

SPARK

Works with SPARK GPL 2010 and GPS GPL 2010.

By defining numeric subtypes with suitable ranges we can prove statically that there will be no run-time errors. (The Simplifier leaves 2 VCs unproven, but these are clearly provable by inspection.)

The precondition enforces equality of the ranges of the two vectors.

with Spark_IO;
--# inherit Spark_IO;
--# main_program;
procedure Dot_Product_Main
--# global in out Spark_IO.Outputs;
--# derives Spark_IO.Outputs from *;
is
   Limit : constant := 1000;
   type V_Elem is range -Limit .. Limit;
   V_Size : constant := 100;
   type V_Index is range 1 .. V_Size;
   type Vector is array(V_Index range <>) of V_Elem;

   type V_Prod is range -(Limit**2)*V_Size .. (Limit**2)*V_Size;
   --# assert V_Prod'Base is Integer;

   subtype Index3 is V_Index range 1 .. 3;
   subtype Vector3 is Vector(Index3);
   Vect1 : constant Vector3 := Vector3'(1, 3, -5);
   Vect2 : constant Vector3 := Vector3'(4, -2, -1);

   function Dot_Product(V1, V2 : Vector) return V_Prod
   --# pre  V1'First = V2'First
   --#  and V1'Last  = V2'Last;
   is
      Sum : V_Prod := 0;
   begin
      for I in V_Index range V1'Range
      --# assert Sum in -(Limit**2)*V_Prod(I-1) .. (Limit**2)*V_Prod(I-1);
      loop
         Sum := Sum + V_Prod(V1(I)) * V_Prod(V2(I));
      end loop;
      return Sum;
   end Dot_Product;

begin
   Spark_IO.Put_Integer(File  => Spark_IO.Standard_Output,
                        Item  => Integer(Dot_Product(Vect1, Vect2)),
                        Width => 6,
                        Base  => 10);
end Dot_Product_Main;

Output:

SQL

ANSI sql does not support functions and is missing some other concepts that would be needed for a general case implementation of inner product (column names and tables would need to be first class in SQL -- capable of being passed to functions).

However, inner product is fairly simple to specify in SQL.

Given two tables A and B where A has key columns i and j and B has key columns j and k and both have value columns N, the inner product of A and B would be:

select i, k, sum(A.N*B.N) as N
        from A inner join B on A.j=B.j
        group by i, k

Standard ML

With lists:

val dot = ListPair.foldlEq Real.*+ 0.0

(*
- dot ([1.0, 3.0, ~5.0], [4.0, ~2.0, ~1.0]);
val it = 3.0 : real
*)

With vectors:

fun dot (v, u) = (
  if Vector.length v <> Vector.length u then
    raise ListPair.UnequalLengths
  else ();
  Vector.foldli (fn (i, v_i, z) => v_i * Vector.sub (u, i) + z) 0.0 v
  )

(*
- dot (#[1.0, 3.0, ~5.0], #[4.0, ~2.0, ~1.0]);
val it = 3.0 : real
*)

Stata

With row vectors:

matrix a=1,3,-5
matrix b=4,-2,-1
matrix c=a*b'
di el("c",1,1)

With column vectors:

matrix a=1\3\-5
matrix b=4\-2\-1
matrix c=a'*b
di el("c",1,1)

Mata

With row vectors:

a=1,3,-5
b=4,-2,-1
a*b'

With column vectors:

a=1\3\-5
b=4\-2\-1
a'*b

In both cases, one cas also write

sum(a:*b)

Swift

Works with: Swift version 1.2+

func dot(v1: [Double], v2: [Double]) -> Double {
  return reduce(lazy(zip(v1, v2)).map(*), 0, +)
}

println(dot([1, 3, -5], [4, -2, -1]))

Output:

3.0

Tcl

Library: Tcllib (Package: math::linearalgebra)

package require math::linearalgebra 

set a {1 3 -5}
set b {4 -2 -1}
set dotp [::math::linearalgebra::dotproduct $a $b]
proc pp vec {return \[[join $vec ,]\]}
puts "[pp $a] \u2219 [pp $b] = $dotp"

Output:

[1,3,-5] ∙ [4,-2,-1] = 3.0

TI-83 BASIC

To perform a matrix dot product on TI-83, the trick is to use lists (and not to use matrices).

sum({1,3,–5}*{4,–2,–1})

Output:

TI-89 BASIC

dotP([1, 3, –5], [4, –2, –1])

Output:

True BASIC

FUNCTION dot (a(), b())
    IF UBOUND(a) <> UBOUND(b) THEN LET dot = 0
    LET dp = 0.0
    FOR i = LBOUND(a) TO UBOUND(a)
        LET dp = dp + (a(i) * b(i))
    NEXT i
    LET dot = dp
END FUNCTION

DIM zero3d(3)
LET zero3d(1) = 0.0
LET zero3d(2) = 0.0
LET zero3d(3) = 0.0
DIM zero5d(5)
LET zero5d(1) = 0.0
LET zero5d(2) = 0.0
LET zero5d(3) = 0.0
LET zero5d(4) = 0.0
LET zero5d(5) = 0.0
DIM x(3)
LET x(1) = 1.0
LET x(2) = 0.0
LET x(3) = 0.0
DIM y(3)
LET y(1) = 0.0
LET y(2) = 1.0
LET y(3) = 0.0
DIM z(3)
LET z(1) = 0.0
LET z(2) = 0.0
LET z(3) = 1.0
DIM q(3)
LET q(1) = 1.0
LET q(2) = 1.0
LET q(3) = 3.14159
DIM r(3)
LET r(1) = -1.0
LET r(2) = 2.618033989
LET r(3) = 3.0

PRINT " q dot r           = "; dot(q(), r())
PRINT " zero3d dot zero5d = "; dot(zero3d(), zero5d())
PRINT " zero3d dot x      = "; dot(zero3d(), x())
PRINT " z dot z           = "; dot(z(), z())
PRINT " y dot z           = "; dot(y(), z())
END

Output:

q dot r           = 11.042804
zero3d dot zero5d = 0
zero3d dot x      = 0
z dot z           = 1
y dot z           = 0

Ursala

A standard library function for dot products of floating point numbers exists, but a new one can be defined for integers as shown using the map operator (*) with the zip suffix (p) to construct a "zipwith" operator (*p), which operates on the integer product function. A catchable exception is thrown if the list lengths are unequal. This function is then composed (+) with a cumulative summation function, which is constructed from the binary sum function, and the reduction operator (:-) with 0 specified for the vacuous sum.

#import int

dot = sum:-0+ product*p

#cast %z

test = dot(<1,3,-5>,<4,-2,-1>)

Output:

VBA

Private Function dot_product(x As Variant, y As Variant) As Double
    dot_product = WorksheetFunction.SumProduct(x, y)
End Function

Public Sub main()
    Debug.Print dot_product([{1,3,-5}], [{4,-2,-1}])
End Sub

Output:

VBScript

WScript.Echo DotProduct("1,3,-5","4,-2,-1")

Function DotProduct(vector1,vector2)
	arrv1 = Split(vector1,",")
	arrv2 = Split(vector2,",")
	If UBound(arrv1) <> UBound(arrv2) Then
		WScript.Echo "The vectors are not of the same length."
		Exit Function
	End If
	DotProduct = 0
	For i = 0 To UBound(arrv1)
		DotProduct = DotProduct + (arrv1(i) * arrv2(i))
	Next
End Function

Output:

Visual Basic

Works with: Visual Basic version 6

Option Explicit

Function DotProduct(a() As Long, b() As Long) As Long
Dim l As Long, u As Long, i As Long
  Debug.Assert DotProduct = 0 'return value automatically initialized with 0
  l = LBound(a())
  If l = LBound(b()) Then
    u = UBound(a())
    If u = UBound(b()) Then
      For i = l To u
        DotProduct = DotProduct + a(i) * b(i)
      Next i
    Exit Function
    End If
  End If
  Err.Raise vbObjectError + 123, , "invalid input"
End Function

Sub Main()
Dim a() As Long, b() As Long, x As Long
  ReDim a(2)
  a(0) = 1
  a(1) = 3
  a(2) = -5
  ReDim b(2)
  b(0) = 4
  b(1) = -2
  b(2) = -1
  x = DotProduct(a(), b())
  Debug.Assert x = 3
  ReDim Preserve a(3)
  a(3) = 10
  ReDim Preserve b(3)
  b(3) = 2
  x = DotProduct(a(), b())
  Debug.Assert x = 23
  ReDim Preserve a(4)
  a(4) = 10
  On Error Resume Next
  x = DotProduct(a(), b())
  Debug.Assert Err.Number = vbObjectError + 123
  Debug.Assert Err.Description = "invalid input"
End Sub

Visual Basic .NET

Translation of: C#

Module Module1

    Function DotProduct(a As Decimal(), b As Decimal()) As Decimal
        Return a.Zip(b, Function(x, y) x * y).Sum()
    End Function

    Sub Main()
        Console.WriteLine(DotProduct({1, 3, -5}, {4, -2, -1}))
        Console.ReadLine()
    End Sub

End Module

Output:

V (Vlang)

fn dot(x []int, y []int) !int {
    if x.len != y.len {
        return error("incompatible lengths")
    }
	mut r := 0
    for i, xi in x {
        r += xi * y[i]
    }
    return r
}
 
fn main() {
    d := dot([1, 3, -5], [4, -2, -1])!

    println(d)
}

Output:

Wart

def (dot_product x y)
  (sum+map (*) x y)

+ is punned (overloaded) here; when applied to functions it denotes composition. Also, (*) is used to skip infix expansion.

Output:

(dot_product '(1 3 -5) '(4 -2 -1))
=> 3

Wren

class Vector {
    construct new(a) {
        if (a.type != List || a.count == 0 || !a.all { |i| i is Num }) {
            Fiber.abort("Argument must be a non-empty list of numbers.")
        }
        _a = a
    }

    a { _a }
    length { _a.count }

    dot(other) {
        if (other.type != Vector || length != other.length) {
            Fiber.abort("Argument must be a Vector of the same length.")
        }
        var sum = 0
        for (i in 0...length) sum = sum + _a[i] * other.a[i]
        return sum
    }

    toString { _a.toString }
}

var v1 = Vector.new([1, 3, -5])
var v2 = Vector.new([4, -2, -1])

System.print("The dot product of %(v1) and %(v2) is %(v1.dot(v2)).")

Output:

The dot product of [1, 3, -5] and [4, -2, -1] is 3.

Library: Wren-vector

Alternatively, using the above module:

import "./vector" for Vector3

var v1 = Vector3.new(1, 3, -5)
var v2 = Vector3.new(4, -2, -1)

System.print("The dot product of %(v1) and %(v2) is %(v1.dot(v2)).")

Output:

The dot product of (1, 3, -5) and (4, -2, -1) is 3.

X86 Assembly

Using FASM. Targets x64 Microsoft Windows.

format PE64 console
entry start

    include 'win64a.inc'

section '.text' code readable executable

    start:
        stdcall dotProduct, vA, vB
        invoke printf, msg_num, rax
        
        stdcall dotProduct, vA, vC
        invoke printf, msg_num, rax
        
        invoke ExitProcess, 0
        
    proc dotProduct vectorA, vectorB
        mov rax, [rcx]
        cmp rax, [rdx]
        je .calculate
        
        invoke printf, msg_sizeMismatch
        mov rax, 0
        ret
        
        .calculate:
        mov r8, rcx
        add r8, 8
        mov r9, rdx
        add r9, 8
        mov rcx, rax
        mov rax, 0
        mov rdx, 0
        
        .next:
            mov rbx, [r9]
            imul rbx, [r8]
            add rax, rbx
            add r8, 8
            add r9, 8
            loop .next
        
        ret
    endp

section '.data' data readable

    msg_num db "%d", 0x0D, 0x0A, 0
    msg_sizeMismatch db "Size mismatch; can't calculate.", 0x0D, 0x0A, 0
    
    struc Vector [symbols] {
        common
        .length dq (.end - .symbols) / 8
        .symbols dq symbols
        .end:
    }
    
    vA Vector 1, 3, -5
    vB Vector 4, -2, -1
    vC Vector 7, 2, 9, 0
    
section '.idata' import data readable writeable

    library kernel32, 'KERNEL32.DLL',\
            msvcrt, 'MSVCRT.DLL'

    include 'api/kernel32.inc'

    import  msvcrt,\
            printf, 'printf'

Output:

3
Size mismatch; can't calculate.
0

XPL0

include c:\cxpl\codes;

func DotProd(U, V, L);
int U, V, L;
int S, I;
[S:= 0;
for I:= 0 to L-1 do S:= S + U(I)*V(I);
return S;
];

[IntOut(0, DotProd([1, 3, -5], [4, -2, -1], 3));
CrLf(0);
]

Output:

Yabasic

sub sq_mul(a(), b(), c())
	local n, i
	
	n = arraysize(a(), 1)
	
	for i = 1 to n
		c(i) = a(i) * b(i)
	next i
end sub

sub sq_sum(a())
	local n, i, r
	
	n = arraysize(a(), 1)
	
	for i = 1 to n
		r = r + a(i)
	next i
	return r
end sub

dim a(3), b(3), c(3)

a(1) = 1 : a(2) = 3 : a(3) = -5
b(1) = 4 : b(2) = -2 : b(3) = -1
sq_mul(a(), b(), c())

print sq_sum(c())

Zig

const std = @import("std");
const Vector = std.meta.Vector;

pub fn main() !void {
    const a: Vector(3, i32) = [_]i32{1, 3, -5};
    const b: Vector(3, i32) = [_]i32{4, -2, -1};
    var dot: i32 = @reduce(.Add, a*b);

    try std.io.getStdOut().writer().print("{d}\n", .{dot});
}

zkl

fcn dotp(a,b){Utils.zipWith('*,a,b).sum()}

zipWith stops at the shortest of the lists

Output:

dotp(T(1,3,-5),T(4,-2,-1,666)) //-->3

If exact length is a requirement

fcn dotp2(a,b){if(a.len()!=b.len())throw(Exception.ValueError);
   Utils.zipWith('*,a,b).sum()
}

ZX Spectrum Basic

10 DIM a(3): LET a(1)=1: LET a(2)=3: LET a(3)=-5
20 DIM b(3): LET b(1)=4: LET b(2)=-2: LET b(3)=-1
30 LET sum=0
40 FOR i=1 TO 3: LET sum=sum+a(i)*b(i): NEXT i
50 PRINT sum