Commit d5fa709d authored by Anthony Coutant's avatar Anthony Coutant
Browse files

Updated last reminiscent mentions to "bnmixture" and replaced them by "elsa".

parent 35965766
Pipeline #18 failed with stages
......@@ -2,14 +2,14 @@
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
fastEdmonds <- function(froms, tos, weights, addDummyRoot) {
.Call('_bnmixture_fastEdmonds', PACKAGE = 'bnmixture', froms, tos, weights, addDummyRoot)
.Call('_elsa_fastEdmonds', PACKAGE = 'elsa', froms, tos, weights, addDummyRoot)
}
fastBipartiteEdgeIds <- function(nodesFrom, nodesTo) {
.Call('_bnmixture_fastBipartiteEdgeIds', PACKAGE = 'bnmixture', nodesFrom, nodesTo)
.Call('_elsa_fastBipartiteEdgeIds', PACKAGE = 'elsa', nodesFrom, nodesTo)
}
fastIndicesTable <- function(numWithDuplicates) {
.Call('_bnmixture_fastIndicesTable', PACKAGE = 'bnmixture', numWithDuplicates)
.Call('_elsa_fastIndicesTable', PACKAGE = 'elsa', numWithDuplicates)
}
This diff is collapsed.
......@@ -174,11 +174,7 @@ getWeightedGraphsPool = function(dataset, dataPool, eratio, edgesSpace, symmetri
tabs = g@attributes$tabs, stringsAsFactors = FALSE))
}
if(!is.null(parallelCluster)){
clusterEvalQ(parallelCluster, {source("../bnmixture/R/edgelists.R");
source("../bnmixture/R/edges.R");
source("../bnmixture/R/utils.R");
source("../bnmixture/R/learners.R");
library(bnlearn)})
clusterEvalQ(parallelCluster, {library(bnlearn)})
clusterExport(parallelCluster, c("dataset", "eratio", "edgesSpace", "epred",
"score", "parentIds", "symmetricSampling"), envir = environment())
parLapply(parallelCluster, dataPool, doIt)
......@@ -358,7 +354,7 @@ learnComponentsPool = function(graphsPool, edgesAll, toMaximize,
})
}
if(!is.null(parallelCluster)){
clusterEvalQ(parallelCluster, {library(devtools); load_all("../bnmixture")})
clusterEvalQ(parallelCluster, {library(devtools)})
clusterExport(parallelCluster, c("edgesAll", "toMaximize", "reverse", "learnFun"), envir = environment())
parLapply(parallelCluster, graphsPool, doIt)
}
......@@ -1132,14 +1128,14 @@ Pruning.components.unsignificant = function(components, threshold, pruneLowest =
#'
#' #Learn a components pool using the Learning.arborescence.fromWeightedGraph function to get a components pool only made of TOP spanning arborescences
#' topComponentsPool = learnComponentsPool(graphsPool, admissibleSpace, TRUE, Learning.arborescence.fromWeightedGraph, FALSE)
#'
#'
#' #Learn the components pool, this time targeting BOTTOM components (by minimizing the score)
#' bottomComponentsPool = learnComponentsPool(graphsPool, admissibleSpace, FALSE, Learning.arborescence.fromWeightedGraph, FALSE)
#'
#' #Combine components separately in each pool (50 combination of 5 models each)
#' topCompositeModels = combineComponentsInPool(topComponentsPool, 5, 50)
#' bottomCompositeModels = combineComponentsInPool(bottomComponentsPool, 5, 50)
#'
#'
#' #Merge both composite model pools to produce top / bottom pool of size 50
#' mergedCompositeModels = mergeTopBottomModelsFromPools(topCompositeModels, bottomCompositeModels)
#'
......
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/_package.R
\docType{bnmixture}
\name{bnmixture}
\alias{bnmixture}
\title{bnmixture}
\docType{elsa}
\name{elsa}
\alias{elsa}
\title{elsa}
\description{
Learn dynamic Bayesian networks from ensemble learning of very simple component models, such as Edmonds spanning arborescences.
}
......
......@@ -7,7 +7,7 @@ using namespace Rcpp;
// fastEdmonds
Rcpp::DataFrame fastEdmonds(std::vector<int> froms, std::vector<int> tos, std::vector<double> weights, bool addDummyRoot);
RcppExport SEXP _bnmixture_fastEdmonds(SEXP fromsSEXP, SEXP tosSEXP, SEXP weightsSEXP, SEXP addDummyRootSEXP) {
RcppExport SEXP _elsa_fastEdmonds(SEXP fromsSEXP, SEXP tosSEXP, SEXP weightsSEXP, SEXP addDummyRootSEXP) {
BEGIN_RCPP
Rcpp::RObject rcpp_result_gen;
Rcpp::RNGScope rcpp_rngScope_gen;
......@@ -21,7 +21,7 @@ END_RCPP
}
// fastBipartiteEdgeIds
NumericVector fastBipartiteEdgeIds(Rcpp::CharacterVector nodesFrom, Rcpp::CharacterVector nodesTo);
RcppExport SEXP _bnmixture_fastBipartiteEdgeIds(SEXP nodesFromSEXP, SEXP nodesToSEXP) {
RcppExport SEXP _elsa_fastBipartiteEdgeIds(SEXP nodesFromSEXP, SEXP nodesToSEXP) {
BEGIN_RCPP
Rcpp::RObject rcpp_result_gen;
Rcpp::RNGScope rcpp_rngScope_gen;
......@@ -33,7 +33,7 @@ END_RCPP
}
// fastIndicesTable
IntegerVector fastIndicesTable(IntegerVector numWithDuplicates);
RcppExport SEXP _bnmixture_fastIndicesTable(SEXP numWithDuplicatesSEXP) {
RcppExport SEXP _elsa_fastIndicesTable(SEXP numWithDuplicatesSEXP) {
BEGIN_RCPP
Rcpp::RObject rcpp_result_gen;
Rcpp::RNGScope rcpp_rngScope_gen;
......@@ -44,13 +44,13 @@ END_RCPP
}
static const R_CallMethodDef CallEntries[] = {
{"_bnmixture_fastEdmonds", (DL_FUNC) &_bnmixture_fastEdmonds, 4},
{"_bnmixture_fastBipartiteEdgeIds", (DL_FUNC) &_bnmixture_fastBipartiteEdgeIds, 2},
{"_bnmixture_fastIndicesTable", (DL_FUNC) &_bnmixture_fastIndicesTable, 1},
{"_elsa_fastEdmonds", (DL_FUNC) &_elsa_fastEdmonds, 4},
{"_elsa_fastBipartiteEdgeIds", (DL_FUNC) &_elsa_fastBipartiteEdgeIds, 2},
{"_elsa_fastIndicesTable", (DL_FUNC) &_elsa_fastIndicesTable, 1},
{NULL, NULL, 0}
};
RcppExport void R_init_bnmixture(DllInfo *dll) {
RcppExport void R_init_elsa(DllInfo *dll) {
R_registerRoutines(dll, NULL, CallEntries, NULL, NULL);
R_useDynamicSymbols(dll, FALSE);
}
load_all("../bnmixture")
load_all("../elsa")
load_all(".")
library(rbenchmark)
......@@ -170,9 +170,9 @@ dataSetMaker <- function()
#function which treat real data set from a file
useRealDataSet <- function()
{
geneData <- read.table("../../bnmixture-exp/data/dream/d8c1.insilico.dyn.nostimuli.tsv", skip = 2, header = TRUE)
geneData <- read.table("../../elsa-exp/data/dream/d8c1.insilico.dyn.nostimuli.tsv", skip = 2, header = TRUE)
gene <- read.table("../../bnmixture-exp/data/dream/d8c1.insilico.dyn.nostimuli.tsv", header = TRUE)
gene <- read.table("../../elsa-exp/data/dream/d8c1.insilico.dyn.nostimuli.tsv", header = TRUE)
dataSet <- data.frame(geneData[1:length(geneData)])
......@@ -206,7 +206,7 @@ compareM_MV <- function(MEdges)
edgesListDone <- list()
MVEdges <- read.table("~/Desktop/bnmixture/bnmixture-exp/data/dream/d8c1.insilico.gs.tsv", header = FALSE)
MVEdges <- read.table("~/Desktop/elsa/elsa-exp/data/dream/d8c1.insilico.gs.tsv", header = FALSE)
for (MEdgesBrowse in 1:length(MEdges@edgeIds))
{
......
library(testthat)
library(bnmixture)
library(elsa)
test_check("bnmixture", reporter = "summarize")
test_check("elsa", reporter = "summarize")
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