few details
[valse.git] / R / selectiontotale.R
diff --git a/R/selectiontotale.R b/R/selectiontotale.R
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+#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
+    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)
+    {
+      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$phi[j,,]) > thresh, 1, any ) ]
+      })
+      
+      list("selected"=selectedVariables,"Rho"=params$Rho,"Pi"=params$Pi)
+    })
+    parallel::stopCluster(cl)
+  }
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