R/RcppExports.R

In FLSSS: Mining Rigs for Problems in the Subset Sum Family

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

auxKnapsack01bb <- function(weight, value, caps, itemNcaps = integer(0), maxCore = 7L, tlimit = 60, ub = "MT", simplify = TRUE) {
    .Call(`_FLSSS_auxKnapsack01bb`, weight, value, caps, itemNcaps, maxCore, tlimit, ub, simplify)
}

auxGAPbbMulthreadKPs <- function(cost, profitOrLoss, budget, maxCore = 7L, tlimit = 60, ub = "MT", greedyBranching = TRUE, optim = "max") {
    .Call(`_FLSSS_auxGAPbbMulthreadKPs`, cost, profitOrLoss, budget, maxCore, tlimit, ub, greedyBranching, optim)
}

auxGAPbbMulthreadNodes <- function(cost, profitOrLoss, budget, maxCore = 7L, threadLoad = 32L, tlimit = 60, ub = "MT", greedyBranching = TRUE, optim = "max") {
    .Call(`_FLSSS_auxGAPbbMulthreadNodes`, cost, profitOrLoss, budget, maxCore, threadLoad, tlimit, ub, greedyBranching, optim)
}

auxKnapsack01dp <- function(weight, value, caps, maxCore = 7L, tlimit = 60, simplify = TRUE) {
    .Call(`_FLSSS_auxKnapsack01dp`, weight, value, caps, maxCore, tlimit, simplify)
}

auxGAPbbDpMulthreadKPs <- function(cost, profitOrLoss, budget, maxCore = 7L, tlimit = 60, greedyBranching = TRUE, optim = "max") {
    .Call(`_FLSSS_auxGAPbbDpMulthreadKPs`, cost, profitOrLoss, budget, maxCore, tlimit, greedyBranching, optim)
}

auxGAPbbDpMulthreadNodes <- function(cost, profitOrLoss, budget, maxCore = 7L, threadLoad = 32L, tlimit = 60, greedyBranching = TRUE, optim = "max") {
    .Call(`_FLSSS_auxGAPbbDpMulthreadNodes`, cost, profitOrLoss, budget, maxCore, threadLoad, tlimit, greedyBranching, optim)
}

testFindBound003GAP <- function(dividedV, target, profit, ME) {
    .Call(`_FLSSS_testFindBound003GAP`, dividedV, target, profit, ME)
}

testFindBound003GAP2 <- function(dividedV, targetMAX) {
    .Call(`_FLSSS_testFindBound003GAP2`, dividedV, targetMAX)
}

z_GAP <- function(maxCore, dividedV, profitV, MAXmat, zeroBasedLB, zeroBasedUB, duration, threadLoad = 8L, verbose = TRUE, heuristic = FALSE) {
    .Call(`_FLSSS_z_GAP`, maxCore, dividedV, profitV, MAXmat, zeroBasedLB, zeroBasedUB, duration, threadLoad, verbose, heuristic)
}

auxGAPgaGivenRandomSeeds <- function(cost, profitOrLoss, budget, randomSeeds, populationSize = 100L, generations = 1000L, optim = "max", maxCore = 7L) {
    .Call(`_FLSSS_auxGAPgaGivenRandomSeeds`, cost, profitOrLoss, budget, randomSeeds, populationSize, generations, optim, maxCore)
}

z_Gknapsack <- function(len, vr, maskV, profitVec, targetMat, MEr, LBr, UBr, duration, useBiSearch, maxCore, avgThreadLoad, verbose, approx) {
    .Call(`_FLSSS_z_Gknapsack`, len, vr, maskV, profitVec, targetMat, MEr, LBr, UBr, duration, useBiSearch, maxCore, avgThreadLoad, verbose, approx)
}

z_findBound <- function(len, V, target, me, initialLB = -1L, initialUB = -1L, findBoundTimes = 1L, useBinarySearch = 0L, UBfirst = 0L) {
    .Call(`_FLSSS_z_findBound`, len, V, target, me, initialLB, initialUB, findBoundTimes, useBinarySearch, UBfirst)
}

z_findBoundIntegerized <- function(len, V, mask, target, me, initialLB = -1L, initialUB = -1L, findBoundTimes = 1L, useBinarySearch = 0L, UBfirst = 0L) {
    .Call(`_FLSSS_z_findBoundIntegerized`, len, V, mask, target, me, initialLB, initialUB, findBoundTimes, useBinarySearch, UBfirst)
}

z_FLSSS <- function(len, v, target, ME, LB, UB, solutionNeed = 1L, tlimit = 60, useBiSrchInFB = FALSE, valueType = "double") {
    .Call(`_FLSSS_z_FLSSS`, len, v, target, ME, LB, UB, solutionNeed, tlimit, useBiSrchInFB, valueType)
}

z_FLSSSvariableTree <- function(len, v, target, ME, LB, UB, solutionNeed = 1L, tlimit = 60, useBiSrchInFB = FALSE, useFloat = FALSE) {
    .Call(`_FLSSS_z_FLSSSvariableTree`, len, v, target, ME, LB, UB, solutionNeed, tlimit, useBiSrchInFB, useFloat)
}

z_mFLSSS <- function(maxCore, len, vr, maskV, d, dlst, dl, dust, du, targetMat, MEr, LBr, UBr, sizeNeed, duration, useBiSearch = 0L) {
    .Call(`_FLSSS_z_mFLSSS`, maxCore, len, vr, maskV, d, dlst, dl, dust, du, targetMat, MEr, LBr, UBr, sizeNeed, duration, useBiSearch)
}

arbFLSSS <- function(len, V, target, givenKsumTable = NULL, solutionNeed = 1L, maxCore = 7L, tlimit = 60, approxNinstance = 1000L, ksumK = 4L, ksumTableSizeScaler = 30L, verbose = TRUE) {
    .Call(`_FLSSS_arbFLSSS`, len, V, target, givenKsumTable, solutionNeed, maxCore, tlimit, approxNinstance, ksumK, ksumTableSizeScaler, verbose)
}

decomposeArbFLSSS <- function(len, V, target, approxNinstance = 1000L, maxCore = 7L, ksumTable = NULL, ksumK = 4L, ksumTableSizeScaler = 30L, verbose = TRUE) {
    .Call(`_FLSSS_decomposeArbFLSSS`, len, V, target, approxNinstance, maxCore, ksumTable, ksumK, ksumTableSizeScaler, verbose)
}

arbFLSSSobjRun <- function(X, solutionNeed = 1L, tlimit = 60, maxCore = 7L, ksumK = 0L, ksumTableSizeScaler = 30L, verbose = TRUE) {
    .Call(`_FLSSS_arbFLSSSobjRun`, X, solutionNeed, tlimit, maxCore, ksumK, ksumTableSizeScaler, verbose)
}

ksumHash <- function(ksumK, V, ksumTableSizeScaler = 30L, target = NULL, len = 0L, approxNinstance = 1000L, verbose = TRUE, maxCore = 7L) {
    .Call(`_FLSSS_ksumHash`, ksumK, V, ksumTableSizeScaler, target, len, approxNinstance, verbose, maxCore)
}

z_mFLSSScomoPar <- function(maxCore, len, vr, maskV, d, dlst, dl, dust, du, targetr, MEr, LBr, UBr, sizeNeededForAll, duration, useBiSearch = 0L, avgThreadLoad = 8L) {
    .Call(`_FLSSS_z_mFLSSScomoPar`, maxCore, len, vr, maskV, d, dlst, dl, dust, du, targetr, MEr, LBr, UBr, sizeNeededForAll, duration, useBiSearch, avgThreadLoad)
}

z_mFLSSSimage <- function(len, vr, maskV, d, dlst, dl, dust, du, targetMat, MEr, LBr, UBr, sizeNeed, useBiSearch = 0L, Ninstance = 100000L) {
    .Call(`_FLSSS_z_mFLSSSimage`, len, vr, maskV, d, dlst, dl, dust, du, targetMat, MEr, LBr, UBr, sizeNeed, useBiSearch, Ninstance)
}

z_mFLSSSimport <- function(mflsssObj, sizeNeed, tlimit) {
    .Call(`_FLSSS_z_mFLSSSimport`, mflsssObj, sizeNeed, tlimit)
}

z_mFLSSSvariableTree <- function(maxCore, len, vr, d, dlst, dl, dust, du, keyInd, originalTarget, keyTarget, scaleFactor, MEr, LBr, UBr, sizeNeed, duration, useFloat, useBisearchInFindBounds = 0L) {
    .Call(`_FLSSS_z_mFLSSSvariableTree`, maxCore, len, vr, d, dlst, dl, dust, du, keyInd, originalTarget, keyTarget, scaleFactor, MEr, LBr, UBr, sizeNeed, duration, useFloat, useBisearchInFindBounds)
}

z_integerize <- function(len, V, target, ME, precisionLevel) {
    .Call(`_FLSSS_z_integerize`, len, V, target, ME, precisionLevel)
}

z_which64intAndSize <- function(largestSubsetSum) {
    .Call(`_FLSSS_z_which64intAndSize`, largestSubsetSum)
}

z_collapseTo64int <- function(x, which64int, bitSize) {
    .Call(`_FLSSS_z_collapseTo64int`, x, which64int, bitSize)
}

z_mask <- function(which64int, bitSize) {
    .Call(`_FLSSS_z_mask`, which64int, bitSize)
}