From: emilie <emilie@devijver.org>
Date: Thu, 16 Mar 2017 15:03:33 +0000 (+0100)
Subject: few details
X-Git-Url: https://git.auder.net/%7B%7B%20asset%28%27mixstore/images/css/current/gitweb.css?a=commitdiff_plain;h=e54d1bb9c8788781c0a2bd911bb14a087a98e7bf;p=valse.git

few details
---

diff --git a/R/selectiontotale.R b/R/selectiontotale.R
new file mode 100644
index 0000000..1690386
--- /dev/null
+++ b/R/selectiontotale.R
@@ -0,0 +1,26 @@
+#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$Pi)
+    })
+    parallel::stopCluster(cl)
+  }
\ No newline at end of file
diff --git a/R/valse.R b/R/valse.R
index e5205a5..f84c2c5 100644
--- a/R/valse.R
+++ b/R/valse.R
@@ -40,15 +40,13 @@ valse = function(X,Y,procedure,selecMod,gamma = 1,mini = 10,
     piInit	<<- init$piInit
     gamInit <<- init$gamInit
     
-    gridLambda <<- gridLambda(phiInit, rhoInit, piInit, tauInit, X, Y, gamma, mini, maxi, eps)
+    gridLambda <<- gridLambda(phiInit, rhoInit, piInit, gamInit, X, Y, gamma, mini, maxi, eps)
     
     print("Compute relevant parameters")
     #select variables according to each regularization parameter
     #from the grid: A1 corresponding to selected variables, and
     #A2 corresponding to unselected variables.
-    params = selectiontotale(phiInit,rhoInit,piInit,tauInit,
-                             mini,maxi,gamma,gridLambda,
-                             X,Y,thresh,eps)
+    params = selectiontotale(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,gridLambda,X,Y,1e-8,eps)
     A1 <<- params$A1
     A2 <<- params$A2
     Rho <<- params$Rho