# partitionsRank: Rank Partitions/Compositions In RcppAlgos: High Performance Tools for Combinatorics and Computational Mathematics

 partitionsRank R Documentation

## Rank Partitions/Compositions

### Description

• Generate the rank (lexicographically) of partitions/compositions. These functions are the complement to `partitions/compositionsSample`. See the examples below.

• GMP support allows for exploration of partitions/compositions of vectors with many elements.

### Usage

``````partitionsRank(..., v, repetition = FALSE, freqs = NULL, target = NULL)

compositionsRank(..., v, repetition = FALSE, freqs = NULL,
target = NULL, weak = FALSE)
``````

### Arguments

 `...` vectors or matrices to be ranked. `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`). `repetition` Logical value indicating whether partitions/compositions should be with or without repetition. The default is `FALSE`. `freqs` A vector of frequencies used for producing all partitions of a multiset of `v`. Each element of `freqs` represents how many times each element of the source vector, `v`, is repeated. It is analogous to the `times` argument in `rep`. The default value is `NULL`. `target` Number to be partitioned. If `NULL`, `max(v)` will be used. `weak` (Compositions only) Logical flag indicating whether to allow terms of the sequence to be zero.

### Details

These algorithms rely on efficiently ranking the `n^{th}` lexicographical partition.

### Value

A vector of class `integer`, `numeric`, or `bigz` determined by the total number of partitions/compositions

### Note

`v` must be supplied.

Joseph Wood

### References

`partitionsSample`, `compositionsSample`
``````mySamp = partitionsSample(30, 8, TRUE, n = 5, seed = 10, namedSample = TRUE)