#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,thresh,tau){
- require(parallel)
- cl = parallel::makeCluster( parallel::detectCores() / 4 ) # <-- ça devrait être un argument
+selectiontotale = function(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda,X,Y,thresh,tau, parallel = FALSE){
+ if (parallel) {
+ require(parallel)
+ cl = parallel::makeCluster( parallel::detectCores() / 4) # <-- ça devrait être un argument
parallel::clusterExport(cl=cl,
varlist=c("phiInit","rhoInit","gamInit","mini","maxi","glambda","X","Y","thresh","tau"),
envir=environment())
#Pour chaque lambda de la grille, on calcule les coefficients
- out = parLapply( 1:length(glambda), function(lambdaindex)
+ out = parLapply(cl, 1:length(glambda), function(lambdaIndex)
{
params =
EMGLLF(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda[lambdaIndex],X,Y,tau)
list("selected"=selectedVariables,"Rho"=params$Rho,"Pi"=params$Pi)
})
parallel::stopCluster(cl)
- }
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+ }
+ else {
+ selectedVariables = list()
+ Rho = list()
+ Pi = list()
+ #Pour chaque lambda de la grille, on calcule les coefficients
+ for (lambdaIndex in 1:length(glambda)){
+ print(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[[lambdaIndex]] = 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$phi[j,,]) > thresh, 1, any ) ]
+ })
+ Rho[[lambdaIndex]] = params$Rho
+ Pi[[lambdaIndex]] = params$Pi
+ }
+ list("selected"=selectedVariables,"Rho"=Rho,"Pi"=Pi)
+ }
+}
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