R/selectiontotale.R

   1 #Return a list of outputs, for each lambda in grid: selected,Rho,Pi
   2 selectiontotale = function(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda,X,Y,thresh,tau){
   3   require(parallel)
   4     cl = parallel::makeCluster( parallel::detectCores() / 4 ) # <-- ça devrait être un argument
   5     parallel::clusterExport(cl=cl,
   6                             varlist=c("phiInit","rhoInit","gamInit","mini","maxi","glambda","X","Y","thresh","tau"),
   7                             envir=environment())
   8     #Pour chaque lambda de la grille, on calcule les coefficients
   9     out = parLapply( 1:length(glambda), function(lambdaindex)
  10     {
  11       params =
  12         EMGLLF(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda[lambdaIndex],X,Y,tau)
  13
  14       p = dim(phiInit)[1]
  15       m = dim(phiInit)[2]
  16       #selectedVariables: list where element j contains vector of selected variables in [1,m]
  17       selectedVariables = lapply(1:p, function(j) {
  18         #from boolean matrix mxk of selected variables obtain the corresponding boolean m-vector,
  19         #and finally return the corresponding indices
  20         seq_len(m)[ apply( abs(params$phi[j,,]) > thresh, 1, any ) ]
  21       })
  22
  23       list("selected"=selectedVariables,"Rho"=params$Rho,"Pi"=params$Pi)
  24     })
  25     parallel::stopCluster(cl)
  26   }