X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=R%2FselectVariables.R;fp=R%2FselectVariables.R;h=46fb3f33165106d2d4f3a91943b81ac7709b7b74;hp=03578c9d382fc867c92813e1f582c6a958da5f54;hb=07848d25af9f342f7d8e2dd103f2502d945afe54;hpb=621ec46ceb49d86ad3d525cfb263329f1d1faff8

diff --git a/R/selectVariables.R b/R/selectVariables.R
index 03578c9..46fb3f3 100644
--- a/R/selectVariables.R
+++ b/R/selectVariables.R
@@ -21,17 +21,19 @@
 #' @export
 selectVariables = function(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda,X,Y,seuil,tau)
 {
+	#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( 1:L, function(lambdaindex)
+	out = parLapply( seq_along(glambda), function(lambdaindex)
 	{
-		params = EMGLLF(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda[lambdaIndex],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) {
 			#from boolean matrix mxk of selected variables obtain the corresponding boolean m-vector,