nchoose

Version 3.0 (2,87 ko) par Jos (10584)
all combinations of the elements of a set
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Mise à jour 8 fév. 2019

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W = nchoose(S) returns all possible combinations of 0, 1, or more
elements of the set S, having N elements. There are 2^N combinations
in total. W is a cell array and each cell holds one of these
combination (as a row vector).
S can be a cell array, and each cell of W will then contain a cell
array. W is the powerset of S, as it includes the empty set (0
elements) as it first cell.

For a vector of integers I, W = nchoose(S, I) returns only the sets
indicated by the indices I. This might be useful for large sets.

Examples:
nchoose([2 4 6 8])
% -> { [] ;
% [2] ;
% [4] ;
% [2 4] ;
% [6] ;
% ...
% [2 6 8] ;
% [4 6 8] ;
% [2 4 6 8]} ; % in total 16 different combinations

nchoose([33 22 11], [1 8 4])
% -> { [] ; [33 22 11] ; [ 33 11]}

Notes:
- For sets containing more than 18 elements a warning is given, as this
can take some time. Hit Ctrl-C to intterupt calculations.
- If S contain non-unique elements (e.g. S = [1 1 2]), nchoose will
return non-unique cells. In other words, nchoose treats all elements
of S as being unique. One could use nchoose(UNIQUE(S)) to avoid that.
- Loosely speaking, nchoose(S) collects all output of multiple calls to
NCHOOSEK(S, K) where K is looping from 1 to the number of elements of
S. The implementation of nchoose, however, does rely of a different
method and is much faster than such a loop.
- For more information, see: http://en.wikipedia.org/wiki/Power_set

See also nchoosek, perms,
permn, nchoose2, allcomb on the file Exchange

Citation pour cette source

Jos (10584) (2024). nchoose (https://www.mathworks.com/matlabcentral/fileexchange/20011-nchoose), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2018a
Compatible avec toutes les versions
Plateformes compatibles
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Remerciements

A inspiré : nchoosecrit(S, FUN)

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Version Publié le Notes de version
3.0

implemented powers and subset

2.2.0.0

updated description
update contact info. Works on most ML releases

1.1.0.0

reference to powerset

1.0.0.0

improved algorithm (thank US!)