merge selectVariables.R doc and selectiontotale.R code into selectVariables.R

[valse.git] / R / selectiontotale.R

diff --git a/R/selectiontotale.R b/R/selectiontotale.R
deleted file mode 100644 (file)
index 673bc3b..0000000
--- a/R/selectiontotale.R
+++ /dev/null
@@ -1,25 +0,0 @@
-#Return a list of outputs, for each lambda in grid: selected,Rho,Pi
-selectiontotale = function(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda,X,Y,seuil,tau)
-{
-       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)
-       {
-               params = EMGLLF(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda[lambdaIndex],X,Y,tau)
-
-               p = dim(phiInit)[1]
-               m = dim(phiInit)[2]
-               #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,
-                       #and finally return the corresponding indices
-                       seq_len(m)[ apply( abs(params$phi[j,,]) > seuil, 1, any ) ]
-               })
-
-               list("selected"=selectedVariables,"Rho"=params$Rho,"Pi"=params$Pi)
-       })
-       parallel::stopCluster(cl)
-}