Dot product

From Rosetta Code
Task
Dot product
You are encouraged to solve this task according to the task description, using any language you may know.
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



11l[edit]

print(dot((1,  3, -5), (4, -2, -1)))
Output:
3

360 Assembly[edit]

*        Dot product               03/05/2016
DOTPROD  CSECT
         USING  DOTPROD,R15
         SR     R7,R7              p=0
         LA     R6,1               i=1
LOOPI    CH     R6,=AL2((B-A)/4)   do i=1 to hbound(a)
         BH     ELOOPI
         LR     R1,R6              i
         SLA    R1,2               *4
         L      R3,A-4(R1)         a(i)
         L      R4,B-4(R1)         b(i)
         MR     R2,R4              a(i)*b(i)
         AR     R7,R3              p=p+a(i)*b(i)
         LA     R6,1(R6)           i=i+1
         B      LOOPI
ELOOPI   XDECO  R7,PG              edit p
         XPRNT  PG,80              print buffer
         XR     R15,R15            rc=0
         BR     R14                return
A        DC     F'1',F'3',F'-5'
B        DC     F'4',F'-2',F'-1'
PG       DC     CL80' '            buffer
         YREGS
         END    DOTPROD
Output:
           3

8th[edit]

[1,3,-5] [4,-2,-1] ' n:* ' n:+ a:dot . cr
Output:
3

ABAP[edit]

report zdot_product
data: lv_n type i,
      lv_sum type i,
      lt_a type standard table of i,
      lt_b type standard table of i.

append: '1' to lt_a, '3' to lt_a, '-5' to lt_a.
append: '4' to lt_b, '-2' to lt_b, '-1' to lt_b.
describe table lt_a lines lv_n.

perform dot_product using lt_a lt_b lv_n changing lv_sum.

write lv_sum left-justified.

form dot_product using it_a like lt_a
                       it_b like lt_b
                       iv_n type i
                 changing
                       ev_sum type i.
  field-symbols: <wa_a> type i, <wa_b> type i.

  do iv_n times.
    read table: it_a assigning <wa_a> index sy-index, it_b assigning <wa_b> index sy-index.
    lv_sum = lv_sum + ( <wa_a> * <wa_b> ).
  enddo.
endform.
Output:
3

ACL2[edit]

(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![edit]

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[edit]

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])));

Ada[edit]

with Ada.Text_IO; use Ada.Text_IO;
procedure dot_product is
	type vect is array(Positive range <>) of Integer;
	v1 : vect := (1,3,-5);
	v2 : vect := (4,-2,-1);

	function dotprod(a: vect; b: vect) return Integer is
		sum : Integer := 0;
		begin
		if not (a'Length=b'Length) then raise Constraint_Error; end if;
		for p in a'Range loop
			sum := sum + a(p)*b(p);
		end loop;
		return sum;
	end dotprod;
	
begin
put_line(Integer'Image(dotprod(v1,v2)));
end dot_product;
Output:
3

Aime[edit]

real
dp(list a, list b)
{
    real p, v;
    integer i;

    p = 0;
    for (i, v in a) {
        p += v * b[i];
    }

    p;
}

integer
main(void)
{
    o_(dp(list(1r, 3r, -5r), list(4r, -2r, -1r)), "\n");

    0;
}
Output:
3

ALGOL 68[edit]

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[edit]

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.

APL[edit]

1 3 ¯5 +.× 4 ¯2 ¯1

Output:

3

AppleScript[edit]

Translation of: JavaScript
( functional version )
----------------------- DOT PRODUCT -----------------------

-- dotProduct :: [Number] -> [Number] -> Number
on dotProduct(xs, ys)
    if length of xs = length of ys then
        sum(zipWith(my mul, xs, ys))
    else
        missing value -- arrays of differing dimension
    end if
end dotProduct


-------------------------- TEST ---------------------------
on run
    
    dotProduct([1, 3, -5], [4, -2, -1])
    
    --> 3
end run


-------------------- GENERIC FUNCTIONS --------------------

-- foldl :: (a -> b -> a) -> a -> [b] -> a
on foldl(f, startValue, xs)
    tell mReturn(f)
        set v to startValue
        set lng to length of xs
        repeat with i from 1 to lng
            set v to |λ|(v, item i of xs, i, xs)
        end repeat
        return v
    end tell
end foldl


-- min :: Ord a => a -> a -> a
on min(x, y)
    if y < x then
        y
    else
        x
    end if
end min


-- mul :: Num -> Num -> Num
on mul(a, b)
    a * b
end mul


-- Lift 2nd class handler function into 1st class script wrapper 
-- mReturn :: Handler -> Script
on mReturn(f)
    if class of f is script then
        f
    else
        script
            property |λ| : f
        end script
    end if
end mReturn


-- sum :: [Number] -> Number
on sum(xs)
    script add
        on |λ|(a, b)
            a + b
        end |λ|
    end script
    
    foldl(add, 0, xs)
end sum


-- zipWith :: (a -> b -> c) -> [a] -> [b] -> [c]
on zipWith(f, xs, ys)
    set lng to min(length of xs, length of ys)
    set lst to {}
    tell mReturn(f)
        repeat with i from 1 to lng
            set end of lst to |λ|(item i of xs, item i of ys)
        end repeat
        return lst
    end tell
end zipWith
Output:
3

Arturo[edit]

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[edit]

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
}

AWK[edit]

# syntax: GAWK -f DOT_PRODUCT.AWK
BEGIN {
    v1 = "1,3,-5"
    v2 = "4,-2,-1"
    if (split(v1,v1arr,",") != split(v2,v2arr,",")) {
      print("error: vectors are of unequal lengths")
      exit(1)
    }
    printf("%g\n",dot_product(v1arr,v2arr))
    exit(0)
}
function dot_product(v1,v2,  i,sum) {
    for (i in v1) {
      sum += v1[i] * v2[i]
    }
    return(sum)
}
Output:
3

BASIC[edit]

Applesoft BASIC[edit]

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[edit]

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[edit]

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

bc[edit]

/* Calculate the dot product of two vectors a and b (represented as
 * arrays) of size n.
 */
define d(a[], b[], n) {
    auto d, i

    for (i = 0; i < n; i++) {
        d += a[i] * b[i]
    }
    return(d)
}    

a[0] = 1
a[1] = 3
a[2] = -5
b[0] = 4
b[1] = -2
b[2] = -1
d(a[], b[], 3)
Output:
3

BCPL[edit]

get "libhdr"

let dotproduct(A, B, len) = valof
$(  let acc = 0
    for i=0 to len-1 do
        acc := acc + A!i * B!i
    resultis acc
$)

let start() be 
$(  let A = table 1, 3, -5
    let B = table 4, -2, -1
    writef("%N*N", dotproduct(A, B, 3))
$)
Output:
3

Befunge 93[edit]

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[edit]

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

Bracmat[edit]

  ( dot
  =   a A z Z
    .     !arg:(%?a ?z.%?A ?Z)
        & !a*!A+dot$(!z.!Z)
      | 0
  )
& out$(dot$(1 3 -5.4 -2 -1));
Output:
3

C[edit]

#include <stdio.h>
#include <stdlib.h>

int dot_product(int *, int *, size_t);

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

        printf("%d\n", dot_product(a, b, sizeof(a) / sizeof(a[0])));

        return EXIT_SUCCESS;
}

int
dot_product(int *a, int *b, size_t n)
{
        int sum = 0;
        size_t i;

        for (i = 0; i < n; i++) {
                sum += a[i] * b[i];
        }

        return sum;
}
Output:
3

C#[edit]

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:
3

Alternative using Linq (C# 4)[edit]

Works with: C# version 4
public static decimal DotProduct(decimal[] a, decimal[] b) {
    return a.Zip(b, (x, y) => x * y).Sum();
}

C++[edit]

#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:
3

Alternative using std::valarray[edit]

#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:
3

Alternative using std::inner_product[edit]

#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[edit]

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]))

CLU[edit]

% Compute the dot product of two sequences
% If the sequences are not the same length, it signals length_mismatch
% Any type may be used as long as it supports addition and multiplication
dot_product = proc [T: type] (a, b: sequence[T])
              returns (T) signals (length_mismatch, empty, overflow)
              where T has add: proctype (T,T) returns (T) signals (overflow),
                          mul: proctype (T,T) returns (T) signals (overflow) 
    sT = sequence[T]
    % throw errors if necessary
    if sT$size(a) ~= sT$size(b) then signal length_mismatch end
    if sT$empty(a) then signal empty end
    
    % because we don't know what type T is yet, we can't instantiate it 
    % with a default value, so we use the first pair from the sequences
    s: T := sT$bottom(a) * sT$bottom(b) resignal overflow
    for i: int in int$from_to(2, sT$size(a)) do
        s := s + a[i] * b[i] resignal overflow
    end
    return(s)
end dot_product

% calculate the dot product of the given example
start_up = proc ()
    po: stream := stream$primary_output()
    
    a: sequence[int] := sequence[int]$[1, 3, -5]
    b: sequence[int] := sequence[int]$[4, -2, -1]

    stream$putl(po, int$unparse(dot_product[int](a,b)))
end start_up
Output:
3

CoffeeScript[edit]

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[edit]

(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)))

Component Pascal[edit]

MODULE DotProduct;
IMPORT StdLog;
	
PROCEDURE Calculate*(x,y: ARRAY OF INTEGER): INTEGER;
VAR
	i,sum: INTEGER;
BEGIN
	sum := 0;
	FOR i:= 0 TO LEN(x) - 1 DO
		INC(sum,x[i] * y[i]);
	END;
	RETURN sum
END Calculate;

PROCEDURE Test*;
VAR
	i,sum: INTEGER;
	v1,v2: ARRAY 3 OF INTEGER;
BEGIN
	v1[0] := 1;v1[1] := 3;v1[2] := -5;
	v2[0] := 4;v2[1] := -2;v2[2] := -1;
	
	StdLog.Int(Calculate(v1,v2));StdLog.Ln
END Test;

END DotProduct.

Execute: ^Q DotProduct.Test

Output:
3

Cowgol[edit]

include "cowgol.coh";

sub dotproduct(a: [int32], b: [int32], len: intptr): (n: int32) is
    n := 0;
    while len > 0 loop
        n := n + [a] * [b];
        a := @next a;
        b := @next b;
        len := len - 1;
    end loop;
end sub;

sub printsgn(n: int32) is
    if n<0 then
        print_char('-');
        n := -n;
    end if;
    print_i32(n as uint32);
end sub;

var A: int32[] := {1, 3, -5};
var B: int32[] := {4, -2, -1};

printsgn(dotproduct(&A[0], &B[0], @sizeof A));
print_nl();
Output:
3

Crystal[edit]

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[edit]

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

    [1.0, 3.0, -5.0].dotProduct([4.0, -2.0, -1.0]).writeln;
}
Output:
3

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;
}

Dart[edit]

num dot(List<num> A, List<num> B){
  if (A.length != B.length){
    throw new Exception('Vectors must be of equal size');
  }
  num result = 0;
  for (int i = 0; i < A.length; i++){
    result += A[i] * B[i];
  }
  return result;
}

void main(){
  var l = [1,3,-5];
  var k = [4,-2,-1];
  print(dot(l,k));
}
Output:
3

Delphi[edit]

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.

DWScript[edit]

For arbitrary length vectors, using a precondition to check vector length:

function DotProduct(a, b : array of Float) : Float;
require
   a.Length = b.Length;
var
   i : Integer;
begin
   Result := 0;
   for i := 0 to a.High do
      Result += a[i]*b[i];
end;

PrintLn(DotProduct([1,3,-5], [4,-2,-1]));

Using built-in 4D Vector type:

var a := Vector(1, 3, -5, 0);
var b := Vector(4, -2, -1, 0);

PrintLn(a * b);
Ouput in both cases:
3

Déjà Vu[edit]

dot a b:
	if /= len a len b:
		Raise value-error "dot product needs two vectors with the same length"

	0
	while a:
		+ * pop-from a pop-from b

!. dot [ 1 3 -5 ] [ 4 -2 -1 ]
Output:
3

Draco[edit]

proc nonrec dot_product([*] int a, b) int:
    int total;
    word i;
    total := 0;
    for i from 0 upto dim(a,1)-1 do
        total := total + a[i] * b[i]
    od;
    total
corp

proc nonrec main() void:
    [3] int a = (1, 3, -5);
    [3] int b = (4, -2, -1);
    write(dot_product(a, b))
corp
Output:
3

EchoLisp[edit]

(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

Eiffel[edit]

class
	APPLICATION

create
	make

feature {NONE} -- Initialization

	make
			-- Run application.
		do
			print(dot_product(<<1, 3, -5>>, <<4, -2, -1>>).out)
		end

feature -- Access

	dot_product (a, b: ARRAY[INTEGER]): INTEGER
			-- Dot product of vectors `a' and `b'.
		require
			a.lower = b.lower
			a.upper = b.upper
		local
			i: INTEGER
		do
			from
				i := a.lower
			until
				i > a.upper
			loop
				Result := Result + a[i] * b[i]
				i := i + 1
			end
		end
end
Ouput:
3

Ela[edit]

Translation of: Haskell
open list

dotp a b | length a == length b = sum (zipWith (*) a b)
         | else = fail "Vector sizes must match."

dotp [1,3,-5] [4,-2,-1]
Output:
3

Elena[edit]

ELENA 5.0 :

import extensions;
import system'routines;
 
extension op
{
    method dotProduct(int[] array)
        = self.zipBy(array, (x,y => x * y)).summarize();
}
 
public program()
{
    console.printLine(new int[]{1, 3, -5}.dotProduct(new int[]{4, -2, -1}))
}
Output:
3

Elixir[edit]

Translation of: Erlang
defmodule Vector do
  def dot_product(a,b) when length(a)==length(b), do: dot_product(a,b,0)
  def dot_product(_,_) do
    raise ArgumentError, message: "Vectors must have the same length."
  end
  
  defp dot_product([],[],product), do: product
  defp dot_product([h1|t1], [h2|t2], product), do: dot_product(t1, t2, product+h1*h2)
end

IO.puts Vector.dot_product([1,3,-5],[4,-2,-1])
Output:
3

Elm[edit]

Translation of: Elm
dotp: List number -> List number -> Maybe number
dotp a b =
    if List.length a /= List.length b then
        Nothing
    else
        Just (List.sum <| List.map2 (*) a b)

dotp [1,3,-5] [4,-2,-1])
Output:
3

Emacs Lisp[edit]

(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

Erlang[edit]

dotProduct(A,B) when length(A) == length(B) -> dotProduct(A,B,0);
dotProduct(_,_) -> erlang:error('Vectors must have the same length.').

dotProduct([H1|T1],[H2|T2],P) -> dotProduct(T1,T2,P+H1*H2);
dotProduct([],[],P) -> P.

dotProduct([1,3,-5],[4,-2,-1]).
Output:
3

Euphoria[edit]

function dotprod(sequence a, sequence b)
    atom sum
    a *= b
    sum = 0
    for n = 1 to length(a) do
        sum += a[n]
    end for
    return sum
end function

? dotprod({1,3,-5},{4,-2,-1})
Output:
3
-- Here is an alternative method,
-- using the standard Euphoria Version 4+ Math Library
include std/math.e
sequence a = {1,3,-5}, b = {4,-2,-1}  -- Make them any length you want
? sum(a * b)
Output:
3

F#[edit]

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[edit]

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[edit]

[[\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[edit]

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[edit]

: 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

Fortran[edit]

program test_dot_product

  write (*, '(i0)') dot_product ([1, 3, -5], [4, -2, -1])

end program test_dot_product
Output:
3

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[edit]

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[edit]

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:
3

FreeBASIC[edit]

#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

Fōrmulæ[edit]

Fōrmulæ programs are not textual, visualization/edition of programs is done showing/manipulating structures but not text. Moreover, there can be multiple visual representations of the same program. Even though it is possible to have textual representation —i.e. XML, JSON— they are intended for storage and transfer purposes more than visualization and edition.

Programs in Fōrmulæ are created/edited online in its website, However they run on execution servers. By default remote servers are used, but they are limited in memory and processing power, since they are intended for demonstration and casual use. A local server can be downloaded and installed, it has no limitations (it runs in your own computer). Because of that, example programs can be fully visualized and edited, but some of them will not run if they require a moderate or heavy computation/memory resources, and no local server is being used.

In this page you can see the program(s) related to this task and their results.

GAP[edit]

# Built-in

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

GLSL[edit]

The dot product is built-in:

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

Go[edit]

Implementation[edit]

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:
3

Library gonum/floats[edit]

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:
3

Groovy[edit]

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:
3

Haskell[edit]

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:

dotp
  :: Num a
  => [a] -> [a] -> Maybe a
dotp a b
  | length a == length b = Just $ sum (zipWith (*) a b)
  | otherwise = Nothing

main :: IO ()
main = mbPrint $ dotp [1, 3, -5] [4, -2, -1] -- prints 3

mbPrint
  :: Show a
  => Maybe a -> IO ()
mbPrint (Just x) = print x
mbPrint n = print n

Hoon[edit]

|=  [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[edit]

(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[edit]

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[edit]

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

Idris[edit]

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[edit]

   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".

Java[edit]

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[edit]

ES5[edit]

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[edit]

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

(() => {
    'use strict';

    // dotProduct :: [Int] -> [Int] -> Int
    const dotProduct = (xs, ys) => {
        const sum = xs => xs ? xs.reduce((a, b) => a + b, 0) : undefined;

        return xs.length === ys.length ? (
            sum(zipWith((a, b) => a * b, xs, ys))
        ) : undefined;
    }

    // zipWith :: (a -> b -> c) -> [a] -> [b] -> [c]
    const zipWith = (f, xs, ys) => {
        const ny = ys.length;
        return (xs.length <= ny ? xs : xs.slice(0, ny))
            .map((x, i) => f(x, ys[i]));
    }

    return dotProduct([1, 3, -5], [4, -2, -1]);
})();
Output:
3

jq[edit]

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[edit]

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[edit]

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[edit]

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

   1 3 -5 _dot 4 -2 -1
3

Klingphix[edit]

: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[edit]

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[edit]

{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[edit]

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

Liberty BASIC[edit]

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[edit]

; 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:
3

[edit]

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

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

Logtalk[edit]

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[edit]

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[edit]

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"
            Let a1=each(a), b1=each(b), sum=0
            While a1, b1 {sum+=array(a1)*array(b1)}
            =sum
      }
      Print Dot(A, B)
      Print Dot((1,3,-5), (4,-2,-1))
}
Module dot_product

Maple[edit]

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[edit]

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

MATLAB[edit]

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[edit]

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

Mercury[edit]

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[edit]

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[edit]

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[edit]

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[edit]

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[edit]

/* 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[edit]

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

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

Nim[edit]

# 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])

Oberon-2[edit]

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:
3

Objeck[edit]

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[edit]

#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[edit]

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[edit]

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[edit]

: dotProduct  zipWith(#*) sum ;
Output:
>[ 1, 3, -5] [ 4, -2, -1 ] dotProduct .
3

Ol[edit]

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

Oz[edit]

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[edit]

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

Pascal[edit]

See Delphi

Perl[edit]

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[edit]

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

Phixmonti[edit]

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[edit]

<?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[edit]

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[edit]

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

(dotProduct (1 3 -5) (4 -2 -1))
Output:
-> 3

PL/I[edit]

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[edit]

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:
3

PostScript[edit]

/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[edit]

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[edit]

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[edit]

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[edit]

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[edit]

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[edit]

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

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

R[edit]

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[edit]

#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[edit]

(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.

say [+] (1, 3, -5) »*« (4, -2, -1);

Rascal[edit]

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[edit]

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[edit]

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[edit]

no error checking[edit]

/*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 in the vector A.*/
say  'vector B = '   vectorB                     /*   "     "     "      "  "    "    B.*/
p=.Prod(vectorA, vectorB)                        /*invoke function & compute dot product*/
say                                              /*display a blank line for readability.*/
say  'dot product = '   p                        /*display the dot product to terminal. */
exit                                             /*stick a fork in it,  we're all done. */
/*──────────────────────────────────────────────────────────────────────────────────────*/
.Prod:  procedure;  parse arg A,B                /*this function compute the dot product*/
        $=0                                      /*initialize the sum to  0 (zero).     */
                    do j=1  for words(A)         /*multiply each number in the vectors. */
                    $=$+word(A,j) * word(B,j)    /*  ··· and add the product to the sum.*/
                    end   /*j*/
        return $                                 /*return the sum to function's invoker.*/

output   using the default (internal) inputs:

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

dot product =  3

with error checking[edit]

/*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 in the vector A.*/
say  'vector B = '   vectorB                     /*   "     "     "      "  "    "    B.*/
p=.prod(vectorA, vectorB)                        /*invoke function & compute dot product*/
say                                              /*display a blank line for readability.*/
say  'dot product = '   p                        /*display the dot product to terminal. */
exit                                             /*stick a fork in it,  we're all done. */
/*──────────────────────────────────────────────────────────────────────────────────────*/
.prod: procedure;  parse arg A,B                 /*this function compute the dot product*/
       lenA = words(A);           @.1= 'A'       /*the number of numbers in vector  A.  */
       lenB = words(B);           @.2= 'B'       /* "     "    "    "     "    "    B.  */
                                                 /*Also, define 2 literals to hold names*/
       if lenA\==lenB  then do;   say "***error*** vectors aren't the same size:" /*oops*/
                                  say '            vector  A  length = '   lenA
                                  say '            vector  B  length = '   lenB
                                  exit 13        /*exit pgm with bad─boy return code 13.*/
                            end
       $=0                                       /*initialize the  sum  to   0  (zero). */
                 do j=1  for lenA                /*multiply each number in the vectors. */
                 #.1=word(A,j)                   /*use array to hold 2 numbers at a time*/
                 #.2=word(B,j)
                                  do k=1  for 2;   if datatype(#.k,'N')  then iterate
                                  say "***error*** vector "      @.k      ' element'    j,
                                      " isn't numeric: "     n.k;                  exit 13
                                  end   /*k*/
                 $=$ + #.1 * #.2                 /*  ··· and add the product to the sum.*/
                 end      /*j*/
       return $                                  /*return the sum to function's invoker.*/

output   is the same as the 1st REXX version.

Ring[edit]

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[edit]

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[edit]

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

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

Ruby[edit]

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
    self.zip(other).inject(0) {|dp, (a, b)| dp += a*b}
  end
end

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

Run BASIC[edit]

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[edit]

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[edit]

print(sum([1, 3, -5] * [4, -2, -1]));
Output:
3.0

[sum() returns a double from integer arrays]

Sather[edit]

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[edit]

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[edit]

Works with: Scheme version RRS
(define (dot-product a b)
  (apply + (map * a b)))

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

Scilab[edit]

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

Seed7[edit]

$ 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[edit]

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

Slate[edit]

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[edit]

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[edit]

        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

SPARK[edit]

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:
     3

SQL[edit]

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[edit]

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[edit]

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[edit]

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[edit]

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[edit]

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[edit]

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:
3

TI-89 BASIC[edit]

dotP([1, 3, –5], [4, –2, –1])
Output:
3

Ursala[edit]

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:
3

VBA[edit]

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:
 3

VBScript[edit]

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:
3

Visual Basic[edit]

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[edit]

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:
3

Vlang[edit]

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:
3

Wart[edit]

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[edit]

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.

X86 Assembly[edit]

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[edit]

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:
3

Yabasic[edit]

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[edit]

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[edit]

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[edit]

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