R/tnetpost.R

In mccallm/ternarynet: Ternary Network Estimation

tnetpost <- function(tfit, mdelta = as.integer(10000), msample = as.integer(2000), temperatureScale = 1.0, xSeed = NA) {
  ssObj <- as.vector(t(steadyStateObj(tfit)) + 2)
  pObj <- as.integer(t(perturbationObj(tfit)) + 2)

  nGene <- as.integer(nrow(steadyStateObj(tfit)))
  nExperiment <- as.integer(ncol(steadyStateObj(tfit)))

  if (is.na(xSeed)) xSeed <- as.integer(floor(runif(1) * 10000))
  ### set.seed(xSeed) # removed to make BiocCheck happy - HAS 4/12/2021

  inputParams <- inputParams(tfit)

  obj <- .Call("tnetpost", msample, mdelta, temperatureScale, xSeed(tfit), scoreType(inputParams), perturbationType(inputParams), backupStage(inputParams), maxStage(inputParams), maxTransition(inputParams), epsilon(inputParams), beta0(inputParams), chi0(inputParams), delta(inputParams), rho(inputParams), ne(inputParams), maxDegree(inputParams), pAddParent(inputParams), pExchangeParent(inputParams), neighborDegree(inputParams), pNeighborhood(inputParams), nGene, nExperiment, edgePenalty(inputParams), m0(inputParams), ssObj, pObj, newScore(tfit), minScore(tfit), degreeObjMin(tfit), graphObjMin(tfit), tableObjMin(tfit), finalTemperature(tfit))

  ternaryPost(perturbationObj = perturbationObj(tfit), steadyStateObj = steadyStateObj(tfit), geneNames = geneNames(tfit), experimentNames = experimentNames(tfit), scores = obj$scores, degreeObjs = matrix(obj$degreeObjs, nrow = length(obj$scores), byrow = TRUE), graphObjs = array(obj$graphObjs, dim = c(nGene, nGene, length(obj$scores))), tableObjs = array(obj$tableObjs, dim = c(length(obj$tableObjs) / (nGene * length(obj$scores)), nGene, length(obj$scores))), inputParams = inputParams)
}