X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FselectVariables.R;h=e4ed179c3fbcc49c1b1cc0903beae3e0742b53d5;hb=93285a2d87991291c96f661208ddde248297a3b5;hp=46fb3f33165106d2d4f3a91943b81ac7709b7b74;hpb=f33f35efc9a01f93bb61959522d90ee6a76b892e;p=valse.git

diff --git a/pkg/R/selectVariables.R b/pkg/R/selectVariables.R
index 46fb3f3..e4ed179 100644
--- a/pkg/R/selectVariables.R
+++ b/pkg/R/selectVariables.R
@@ -1,4 +1,5 @@
 #' selectVariables
+#'
 #' It is a function which construct, for a given lambda, the sets of relevant variables.
 #'
 #' @param phiInit an initial estimator for phi (size: p*m*k)
@@ -19,30 +20,45 @@
 #' @examples TODO
 #'
 #' @export
-selectVariables = function(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda,X,Y,seuil,tau)
+#'
+selectVariables = function(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda,
+	X,Y,thresh,tau, ncores=1) #ncores==1 ==> no //
 {
-	#TODO: parameter ncores (chaque tâche peut aussi demander du parallélisme...)
-	cl = parallel::makeCluster( parallel::detectCores() / 4 )
-	parallel::clusterExport(cl=cl,
-		varlist=c("phiInit","rhoInit","gamInit","mini","maxi","glambda","X","Y","seuil","tau"),
-		envir=environment())
-	#Pour chaque lambda de la grille, on calcule les coefficients
-	out = parLapply( seq_along(glambda), function(lambdaindex)
+	if (ncores > 1)
+	{
+		cl = parallel::makeCluster(ncores)
+		parallel::clusterExport(cl=cl,
+			varlist=c("phiInit","rhoInit","gamInit","mini","maxi","glambda","X","Y","thresh","tau"),
+			envir=environment())
+	}
+
+	# Calcul pour un lambda
+	computeCoefs <-function(lambda)
 	{
+		params = EMGLLF(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,lambda,X,Y,tau)
+
 		p = dim(phiInit)[1]
 		m = dim(phiInit)[2]
 
-		params = EMGLLF(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda[lambdaIndex],X,Y,tau)
-
 		#selectedVariables: list where element j contains vector of selected variables in [1,m]
-		selectedVariables = lapply(1:p, function(j) {
+		selectedVariables = sapply(1:p, function(j) { ## je me suis permise de changer le type, 
+		  ##une liste de liste ca devenait compliqué je trouve pour choper ce qui nous intéresse
 			#from boolean matrix mxk of selected variables obtain the corresponding boolean m-vector,
 			#and finally return the corresponding indices
-			seq_len(m)[ apply( abs(params$phi[j,,]) > seuil, 1, any ) ]
+			#seq_len(m)[ apply( abs(params$phi[j,,]) > thresh, 1, any ) ]
+		  c(seq_len(m)[ apply( abs(params$phi[j,,]) > thresh, 1, any ) ], 
+		    rep(0, m-length(seq_len(m)[ apply( abs(params$phi[j,,]) > thresh, 1, any ) ] ) ))
 		})
 
-		list("selected"=selectedVariables,"Rho"=params$Rho,"Pi"=params$Pi)
-	})
-	parallel::stopCluster(cl)
+		list("selected"=selectedVariables,"Rho"=params$rho,"Pi"=params$pi)
+	}
+
+	# Pour chaque lambda de la grille, on calcule les coefficients
+	out <-
+		if (ncores > 1){
+			parLapply(cl, seq_along(glambda, computeCoefs))}
+		else lapply(seq_along(glambda), computeCoefs)
+	if (ncores > 1){
+		parallel::stopCluster(cl)}
 	out
 }