RcppAlgos-package: High Performance Tools for Combinatorics and Computational...

RcppAlgos-packageR Documentation

High Performance Tools for Combinatorics and Computational Mathematics

Description

The RcppAlgos package attacks age-old problems in combinatorics and computational mathematics.

Goals

  1. The main goal is to encourage fresh and creative approaches to foundational problems. The question that most appropriately summarizes RcppAlgos is: "Can we do better?".

  2. Provide highly optimized functions that facilitates a broader spectrum of researchable cases. E.g

    • Investigating the structure of large numbers over wide ranges:

      • primeFactorizeSieve(10^13 - 10^7, 10^13 + 10^7)

      • primeSieve(2^53 - 10^10, 2^53 - 1, nThreads = 32)

    • Easily explore combinations/permutations/partitions that would otherwise be inaccessible due to time of execution/memory constraints:

      • c_iter = comboIter(10000, 100)
        bigSamp = gmp::urand.bigz(3, gmp::log2.bigz(comboCount(10000, 100)))
        c_iter[[bigSamp]] ## flexible iterator allows random sampling
      • p_iter = partitionsIter(5000, 100, target = 6000)
        p_iter[[1e9]] ## start iterating from index = 1e9
        p_iter@nextIter()
        p_iter@nextNIter(1e3)
      • comboGeneral(150, 5, constraintFun = "sum", Parallel = TRUE)

      • parallel::mclapply(seq(...), function(x) {
                    temp = permuteGeneral(15, 10, lower = x, upper = y)
                    ## analyze permutations
                    ## output results
            }, mc.cores = detectCores() - 1))
      • partitionsGeneral(0:80, repetition = TRUE)
      • permuteSample(rnorm(100), 10, freqs = rep(1:4, 25), n = 15, seed = 123)

      • set.seed(123)
        comboGeneral(runif(42, 0, 50), 10,
                     constraintFun = "mean",
                     comparisonFun = c(">","<"),
                     limitConstraints = c(39.876, 42.123))
  3. Speed!!!.... You will find that the functions in RcppAlgos are some of the fastest of their type available in R.

Author(s)

Joseph Wood


RcppAlgos documentation built on May 29, 2024, noon