# comboGroups: Partition a Vector into Groups In RcppAlgos: High Performance Tools for Combinatorics and Computational Mathematics

 comboGroups R Documentation

## Partition a Vector into Groups

### Description

• Generate partitions of a vector into groups. See Create Combinations in R by Groups on https://stackoverflow.com for a direct use case of when the groups sizes are equal.

• Produce results in parallel using the `Parallel` or `nThreads` arguments.

• GMP support allows for exploration where the number of results is large.

• The output is in lexicographical order by groups.

### Usage

``````comboGroups(v, numGroups = NULL, grpSizes = NULL,
retType = "matrix", lower = NULL, upper = NULL,
Parallel = FALSE, nThreads = NULL)
``````

### Arguments

 `v` Source vector. If `v` is a positive integer, it will be converted to the sequence `1:v`. If `v` is a negative integer, it will be converted to the sequence `v:-1`. All atomic types are supported (See `is.atomic`). `numGroups` An Integer. The number of groups that the vector will be partitioned into. The default is `NULL`. If provided and `grpSize` is `NULL`, it must divide the length of v (if v is a vector) or v (if v is a scalar). `grpSizes` A vector of whole numbers representing the size of each group. The default is `NULL`. If provided, the sum of the elements must total the length of v (if v is a vector) or v (if v is a scalar). `retType` A string, "3Darray" or "matrix", that determines the shape of the output. The default is "matrix". Note, "3Darray" can only be used when the size of each group is uniform. When the size of each group varies, the return output will always be a matrix. `lower` The lower bound. Partitions of groups are generated lexicographically, thus utilizing this argument will determine which specific result to start generating from (e.g. `comboGroups(8, 2, lower = 30)` is equivalent to `comboGroups(8, 2)[30:comboGroupsCount(8, 2), ]`). This argument along with `upper` is very useful for generating results in chunks allowing for easy parallelization. `upper` The upper bound. Similar to `lower`, however this parameter allows the user to stop generation at a specific result (e.g. `comboGroups(8, 2, upper = 5)` is equivalent to `comboGroups(8, 2)[1:5, ]`) `Parallel` Logical value indicating whether results should be generated in parallel using `n - 1` threads, where `n` is the maximum number of threads. The default is `FALSE`. If `nThreads` is not `NULL`, it will be given preference (e.g. if user has 8 threads with `Parallel = TRUE` and `nThreads = 4`, only 4 threads will be spawned). If your system is single-threaded, the arguments `Parallel` and `nThreads` are ignored. `nThreads` Specific number of threads to be used. The default is `NULL`. See `Parallel`.

### Details

Conceptually, this problem can be viewed as generating all permutations of the vector `v` and removing the within group permutations. To illustrate this, let us consider the case of generating partitions of `1:8` into 2 groups each of size 4.

• To begin, generate the permutations of `1:8` and group the first/last four elements of each row.

 Grp1 Grp2 C1 C2 C3 C4 C5 C6 C7 C8 R1 | 1 2 3 4 | | 5 6 7 8 | R2 | 1 2 3 4 | | 5 6 8 7 | R3 | 1 2 3 4 | | 5 7 6 8 | R4 | 1 2 3 4 | | 5 7 8 6 | R5 | 1 2 3 4 | | 5 8 6 7 | R6 | 1 2 3 4 | | 5 8 7 6 |
• Note that the permutations above are equivalent partitions of 2 groups of size 4 as only the last four elements are permuted. If we look at at the `25^{th}` lexicographical permutation, we observe our second distinct partition.

 Grp1 Grp2 C1 C2 C3 C4 C5 C6 C7 C8 R24 | 1 2 3 4 | | 8 7 6 5 | R25 | 1 2 3 5 | | 4 6 7 8 | R26 | 1 2 3 5 | | 4 6 8 7 | R27 | 1 2 3 5 | | 4 7 6 8 | R28 | 1 2 3 5 | | 4 7 8 6 |
• Continuing on, we will reach the `3,457^{th}` lexicographical permutation, which represents the last result:

 Grp1 Grp2 C1 C2 C3 C4 C5 C6 C7 C8 R3454 | 1 6 7 5 | |8 3 4 2 | R3455 | 1 6 7 5 | |8 4 2 3 | R3456 | 1 6 7 5 | |8 4 3 2 | R3457 | 1 6 7 8 | | 2 3 4 5 | R3458 | 1 6 7 8 | |2 3 5 4 |
• For this small example, the method above will not be that computationally expensive. In fact, there are only 35 total partitions of `1:8` into 2 groups of size 4 out of a possible `factorial(8) = 40320` permutations. However, just doubling the size of the vector will make this approach infeasible as there are over 10 trillion permutations of `1:16`.

• The algorithm in `comboGroups` avoids these duplicate partitions of groups by utilizing an efficient algorithm analogous to the std::next_permutation found in the standard algorithm library in C++.

### Value

By default, a matrix is returned with column names corresponding to the associated group. If `retType = "3Darray"`, a named 3D array is returned.

### Note

• The maximum number of partitions of groups that can be generated at one time is `2^{31} - 1`. Utilizing `lower` and `upper` makes it possible to generate additional combinations/permutations.

• The length of `grpSizes` must equal `numGroups` if both `grpSize` and `numGroups` are provided.

Joseph Wood

### Examples

``````## return a matrix
comboGroups(8, 2)

## or a 3 dimensional array
temp = comboGroups(8, 2, retType = "3Darray")

## view the first partition
temp[1, , ]

## Example with groups of varying size
comboGroups(8, grpSizes = c(3, 5))

total = comboGroupsCount(11, grpSizes = c(3, 3, 5))

## Start generating from particular index
comboGroups(11, grpSizes = c(3, 3, 5), lower = total - 20)
``````

RcppAlgos documentation built on Oct. 3, 2023, 1:07 a.m.