Dot product: Difference between revisions
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show dotprod [1 3 -5] [4 -2 -1] ; 3</lang> |
show dotprod [1 3 -5] [4 -2 -1] ; 3</lang> |
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=={{header|Lua}}== |
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<lang lua>function dotprod(a, b) |
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local ret = 0 |
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for i = 1, #a do |
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ret = ret + a[i] * b[i] |
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end |
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return ret |
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end |
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print(dotprod({1, 3, -5}, {4, -2, 1}))</lang> |
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=={{header|Oz}}== |
=={{header|Oz}}== |
Revision as of 06:46, 27 February 2010
You are encouraged to solve this task according to the task description, using any language you may know.
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 then sum the results to produce the answer.
C
<lang c>#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;
}</lang> Output: <lang>3</lang>
Clojure
Preconditions are new in 1.1. The actual code also works in older Clojure versions.
<lang clojure>(defn dot-product [c1 c2]
{:pre [(== (count c1) (count c2))]} (reduce + (map * c1 c2)) )
(println (dot-product [1 3 -5] [4 -2 -1]))</lang>
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.
<lang factor>USING: kernel math.vectors sequences ;
- dot-product ( u v -- w )
2dup [ length ] bi@ = [ v. ] [ "Vector lengths must be equal" throw ] if ;</lang>
( scratchpad ) { 1 3 -5 } { 4 -2 -1 } dot-product . 3
Fortran
<lang fortran>program test_dot_product
write (*, '(i0)') dot_product ((/1, 3, -5/), (/4, -2, -1/))
end program test_dot_product</lang> Output: <lang>3</lang>
Haskell
<lang haskell>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</lang>
J
<lang j> 1 3 _5 +/ . * 4 _2 _1 3
dotp=: +/ . * NB. Or defined as a verb (function) 1 3 _5 dotp 4 _2 _1
3</lang>
The conjunction .
applies generally to matricies and arrays of higher dimensions and can be used with verbs (functions) other than sum ( +/
) and product ( *
).
Logo
<lang logo>to dotprod :a :b
output apply "sum (map "product :a :b)
end
show dotprod [1 3 -5] [4 -2 -1] ; 3</lang>
Lua
<lang 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}))</lang>
Oz
Vectors are represented as lists in this example. <lang oz>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]}}</lang>
Perl
<lang 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</lang>
PL/I
<lang 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; </lang>
Python
<lang 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</lang>
Scheme
<lang scheme>(define (dot-product a b)
(apply + (map * a b)))
(display (dot-product (list 1 3 -5) (list 4 -2 -1))) (newline)</lang> Output: <lang>3</lang>
SNOBOL4
<lang snobol4> define("dotp(a,b)sum,i") :(dotp_end) dotp i = 1; sum = 0 loop sum = sum + (a * b)
i = i + 1 ?a :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</lang>
Tcl
<lang tcl>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"</lang> Output:
[1,3,-5] ∙ [4,-2,-1] = 3.0
TI-89 BASIC
dotP([1, 3, –5], [4, –2, –1]) 3