# Dot product

(Redirected from Matrices/dot product)

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)

## 11l

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

## 360 Assembly

```*        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

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

## ABAP

```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

```(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:
```[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])));
```

```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

```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

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.```

## APL

```1 3 ¯5 +.× 4 ¯2 ¯1
```

Output:

`3`

## AppleScript

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)
on |λ|(a, b)
a + b
end |λ|
end script

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

```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
}
```

## AWK

```# 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

### 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```

## bc

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

## BCPL

```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

```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```

## Bracmat

```  ( 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

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

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

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

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

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#

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

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)

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), b, 0) << std::endl;

return 0;
}
```
Output:
`3`

### 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:
`3`

### 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]))
```

## CLU

```% 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

```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)))
```

## Component Pascal

```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 := 1;v1 := 3;v1 := -5;
v2 := 4;v2 := -2;v2 := -1;

StdLog.Int(Calculate(v1,v2));StdLog.Ln
END Test;

END DotProduct.
```

Execute: ^Q DotProduct.Test

Output:
```3
```

## Cowgol

```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, &B, @sizeof A));
print_nl();```
Output:
`3`

## 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:
`3`

Using an array operation:

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

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

## Dart

```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

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 := 1; x := 3; x := -5;
y := 4; y :=-2; y := -1;
WriteLn(DotProduct(x,y));
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

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

```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

```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:
 int a = (1, 3, -5);
 int b = (4, -2, -1);
write(dot_product(a, b))
corp```
Output:
`3`

## 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
```

## Eiffel

```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

```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

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

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

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

```(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

```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

```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#

```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
```

## Fortran

```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

```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:
`3`

## 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, a, a, b, b, b, fn DotProduct( a, b )

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

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

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

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.

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.

## 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:
```3
```

### 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:
```3
```

## 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:
`3`

```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:
%11 = icmp ult i64 %9, %10                            ;-- i < n
br i1 %11, label %loop_body, label %exit

loop_body:
%14 = getelementptr inbounds i32, i32* %12, i64 %13   ;-- calculate a[i]

%18 = getelementptr inbounds i32, i32* %16, i64 %17   ;-- calculate b[i]

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

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

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

exit:
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`

## 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;

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;

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, vecs)
```

## 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])
```

## 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 := 1;y := 4;
x := 3;y := -2;
x := -5;y := -1;
Out.Int(DotProduct(x,y),0);Out.Ln
END DotProduct.
```
Output:
```3
```

## 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~;`

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:
```3
```

## 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:
```3
```

## 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
}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:
`3`

## 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) {
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

### no 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 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

```/*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

```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::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:
`3`

## 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 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:
`     3`

## 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:
```3
```

## TI-89 BASIC

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

## 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:
`3`

## 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:
` 3`

## 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:
`3`

## 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}))
End Sub

End Module
```
Output:
`3`

## 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:
```3
```

## 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'

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
mov r9, rdx
mov rcx, rax
mov rax, 0
mov rdx, 0

.next:
mov rbx, [r9]
imul rbx, [r8]
loop .next

ret
endp

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:
`3`

## 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
```