update to get a valse programm which could be run

[valse.git] / pkg / R / selectVariables.R

diff --git a/pkg/R/selectVariables.R b/pkg/R/selectVariables.R
index ce7d3b3..e4ed179 100644 (file)
--- a/pkg/R/selectVariables.R
+++ b/pkg/R/selectVariables.R
@@ -41,22 +41,24 @@ selectVariables = function(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambd
                m = dim(phiInit)[2]
 
                #selectedVariables: list where element j contains vector of selected variables in [1,m]
-               selectedVariables = lapply(1:p, function(j) {
+               selectedVariables = sapply(1:p, function(j) { ## je me suis permise de changer le type, 
+                 ##une liste de liste ca devenait compliqué je trouve pour choper ce qui nous intéresse
                        #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$phi[j,,]) > thresh, 1, any ) ]
+                       #seq_len(m)[ apply( abs(params$phi[j,,]) > thresh, 1, any ) ]
+                 c(seq_len(m)[ apply( abs(params$phi[j,,]) > thresh, 1, any ) ], 
+                   rep(0, m-length(seq_len(m)[ apply( abs(params$phi[j,,]) > thresh, 1, any ) ] ) ))
                })
 
-               list("selected"=selectedVariables,"Rho"=params$Rho,"Pi"=params$Pi)
+               list("selected"=selectedVariables,"Rho"=params$rho,"Pi"=params$pi)
        }
 
        # Pour chaque lambda de la grille, on calcule les coefficients
        out <-
-               if (ncores > 1)
-                       parLapply(cl, seq_along(glambda, computeCoefs)
-               else
-                       lapply(seq_along(glambda), computeCoefs)
-       if (ncores > 1)
-               parallel::stopCluster(cl)
+               if (ncores > 1){
+                       parLapply(cl, seq_along(glambda, computeCoefs))}
+               else lapply(seq_along(glambda), computeCoefs)
+       if (ncores > 1){
+               parallel::stopCluster(cl)}
        out
 }