help mata mm_subset()
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Title

mm_subset() -- Obtain subsets, compositions, and partitions

Syntax

info = mm_subsetsetup(n [, k])

real colvector mm_subset(info)

real matrix mm_subsets(n [, k])

info = mm_compositionsetup(n [, k, alt])

real colvector mm_composition(info)

real matrix mm_compositions(n [, k, alt])

real scalar mm_ncompositions(n [, k])

info = mm_partitionsetup(n [, k, pad, alt])

real colvector mm_partition(info)

real matrix mm_partitions(n [, k, alt])

real scalar mm_npartitions(n [, k])

real colvector mm_rsubset(n [, k])

real colvector mm_rcomposition(n [, k])

where

n: real scalar n

k: real scalar k

pad: real scalar indicating that the partitions be padded with 0s to have length k

alt: real scalar indicating that the alternative algorithm be used

and where info should be declared transmorphic.

Description

mm_subset(info), where info is set by mm_subsetsetup(), returns all k-subsets (combinations) of n elements, one at a time in lexicographic order. If k is omitted or if k==., the n-subset is returned. Hint: The total number of subsets can be computed as comb(n, k). Algorithm 5.8 from Reingold et al. (1977) is used to generate the subsets.

mm_subsets() is a wrapper for mm_subset() and returns a matrix containing all subsets.

mm_composition(info), where info is set by mm_compositionsetup(), returns all k-part compositions of a positive integer n, one at a time. If k is omitted or if k==., then the n-part compositions of n are returned. The default algorithm uses a direct approach and returns the compositions in anti-lexicographic order. The alternative algorithm, which is applied if alt!=0 is specified, generates the compositions indirectly (in lexicographic order) by using the mm_subset() function (as suggested by Reingold et al. 1977, p. 190-191). The default algorithm is about 1/3 faster than the alternative algorithm.

mm_compositions() is a wrapper for mm_composition() and returns a matrix containing all compositions.

mm_ncompositions() returns the total number of k-part compositions of n, which is equal to comb(n+k-1,k-1).

mm_partition(info), where info is set by mm_partitionsetup(), returns all partitions with k or fewer addends of a positive integer n, one at a time. If k is omitted or if k==., then the partitions with n or fewer addends are returned. The default algorithm is based on Algorithm ZS1 by Zoghbi and Stojmenovic (1998; with modifications to allow the k parameter) and returns the partitions in anti-lexicographic order. The alternative algorithm, which is applied if alt!=0 is specified, is based on Algorithm 5.12 in Reingold et al. (1977) and returns the partitions in lexicographic order. The default algorithm is much faster than the alternative algorithm, especially if k is low compared to n.

mm_partitions() is a wrapper for mm_partition() and returns a matrix containing all partitions.

mm_npartitions() returns the total number of partitions with k or fewer addends of a positive integer n (based on algorithms given on http://home.att.net/~numericana/answer/numbers.htm#partitions, with modifications to allow the k parameter). mm_npartitions() may be slow if k<n and n is large (> 1000, say).

mm_rsubset() returns a random k-subset of n elements. mm_rcomposition() returns a random k-part compositions of n (based on ideas presented in Reingold et al. 1977, p. 189).

The procedure to cycle through all combinations, compositions, or partitions is to initialize info using the setup function and then repeatedly call the combinatorial function until it returns J(0,1,.). For example:

info = mm_subsetsetup(n, k) while ((set=mm_subset(info)) != J(0,1,.)) { ... set ... }

Remarks

Examples:

: comb(4,3) 4 : mm_subsets(4,3) 1 2 3 4 +-----------------+ 1 | 1 1 1 2 | 2 | 2 2 3 3 | 3 | 3 4 4 4 | +-----------------+ : mm_ncompositions(4,3) 15 : mm_compositions(4,3) 1 2 3 4 5 6 7 8 9 10 +--------------------------------------------------- 1 | 4 3 3 2 2 2 1 1 1 1 2 | 0 1 0 2 1 0 3 2 1 0 3 | 0 0 1 0 1 2 0 1 2 3 +--------------------------------------------------- 11 12 13 14 15 --------------------------+ 1 0 0 0 0 0 | 2 4 3 2 1 0 | 3 0 1 2 3 4 | --------------------------+ : mm_npartitions(4,3) 4 : mm_partitions(4,3) 1 2 3 4 +-----------------+ 1 | 4 3 2 2 | 2 | 0 1 2 1 | 3 | 0 0 0 1 | +-----------------+ See the source code of mm_mgof() for some applications.

Diagnostics

mm_subset(), mm_composition(), and mm_permutation() return J(0,1,.) when there are no more combinations, compositions, or permutations.

Source code

mm_subset.mata

References

Reingold, E. M., J. Nievergelt, N. Deo (1977). Combinatorial Algorithms: Theory and Practice. Englewood Cliffs, NJ: Prentice-Hall. Zohgbi, A., I. Stojmenovic (1998). Fast Algorithms for Generating Partitions. International Journal of Computer Mathematics 70: 319-332.

Also see

Online: help for [M-5] cvpermute(), [M-4] statistical, mm_mgof(), moremata