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matlabmatrixcartesian-product
emper
emper

Reputation: 401

Cartesian product in MATLAB

Here is the simplified version of the problem I have. Suppose I have a vector

p=[1 5 10]

and another one

q=[.75 .85 .95]

And I want to come up with the following matrix:

res=[1, .75;
     1, .85;
     1, .95;
     5, .75;
     5, .85;
     5, .95;
    10, .75;
    10, .85;
    10, .95]

This is also known as the Cartesian Product. How can I do that?

Upvotes: 21

Views: 28815

Answers (3)

Cameron Bieganek
Cameron Bieganek

Reputation: 7684

Here's a function, cartesian_product, that can handle any type of input, including string arrays, and returns a table with column names that match the names of the input variables. Inputs that are not variables are given names like var1, var2, etc.

function tbl = cartesian_product(varargin)
    names = arrayfun(@inputname, 1:nargin, 'UniformOutput', false);
    
    for i = 1:nargin
        if isempty(names{i})
            names{i} = ['var' num2str(i)];
        end
    end
    
    rev_args = flip(varargin);
    
    [A{1:nargin}] = ndgrid(rev_args{:});

    B = cellfun(@(x) x(:), A, 'UniformOutput', false);
    C = flip(B);
    
    tbl = table(C{:}, 'VariableNames', names);
end

>> x = ["a" "b"];
>> y = 1:3;
>> z = 4:5;
>> cartesian_product(x, y, z)

ans =

  12×3 table

     x     y    z
    ___    _    _

    "a"    1    4
    "a"    1    5
    "a"    2    4
    "a"    2    5
    "a"    3    4
    "a"    3    5
    "b"    1    4
    "b"    1    5
    "b"    2    4
    "b"    2    5
    "b"    3    4
    "b"    3    5

>> cartesian_product(1:2, 3:4)

ans =

  4×2 table

    var1    var2
    ____    ____

     1       3  
     1       4  
     2       3  
     2       4

Upvotes: 2

jruizaranguren
jruizaranguren

Reputation: 13615

A similar approach as the one described by @nibot can be found in matlab central file-exchange.

It generalizes the solution to any number of input sets. This would be a simplified version of the code:

function C = cartesian(varargin)
    args = varargin;
    n = nargin;

    [F{1:n}] = ndgrid(args{:});

    for i=n:-1:1
        G(:,i) = F{i}(:);
    end

    C = unique(G , 'rows');
end

For instance:

cartesian(['c','d','e'],[1,2],[50,70])

ans =

    99     1    50
    99     1    70
    99     2    50
    99     2    70
   100     1    50
   100     1    70
   100     2    50
   100     2    70
   101     1    50
   101     1    70
   101     2    50
   101     2    70

Upvotes: 6

nibot
nibot

Reputation: 14928

Here's one way:

[X,Y] = meshgrid(p,q);
result = [X(:) Y(:)];

The output is:

result =

    1.0000    0.7500
    1.0000    0.8500
    1.0000    0.9500
    5.0000    0.7500
    5.0000    0.8500
    5.0000    0.9500
   10.0000    0.7500
   10.0000    0.8500
   10.0000    0.9500

Upvotes: 50

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