fix some errors

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

diff --git a/pkg/R/main.R b/pkg/R/main.R
index 8f845f4..2cd345d 100644 (file)
--- a/pkg/R/main.R
+++ b/pkg/R/main.R
@@ -21,7 +21,7 @@
 #' #TODO: a few examples
 #' @export
 valse = function(X, Y, procedure='LassoMLE', selecMod='DDSE', gamma=1, mini=10, maxi=50,
-       eps=1e-4, kmin=2, kmax=2, rang.min=1, rang.max=10, ncores_outer=1, ncores_inner=3,
+       eps=1e-4, kmin=2, kmax=4, rang.min=1, rang.max=10, ncores_outer=1, ncores_inner=1, size_coll_mod = 50,
        verbose=FALSE)
 {
   p = dim(X)[2]
@@ -54,8 +54,8 @@ valse = function(X, Y, procedure='LassoMLE', selecMod='DDSE', gamma=1, mini=10,
     grid_lambda <- computeGridLambda(P$phiInit, P$rhoInit, P$piInit, P$gamInit, X, Y,
                        gamma, mini, maxi, eps)
                # TODO: 100 = magic number
-    if (length(grid_lambda)>100)
-      grid_lambda = grid_lambda[seq(1, length(grid_lambda), length.out = 100)]
+    if (length(grid_lambda)>size_coll_mod)
+      grid_lambda = grid_lambda[seq(1, length(grid_lambda), length.out = size_coll_mod)]
 
                if (verbose)
                        print("Compute relevant parameters")
@@ -63,15 +63,15 @@ valse = function(X, Y, procedure='LassoMLE', selecMod='DDSE', gamma=1, mini=10,
     #from the grid: S$selected corresponding to selected variables
     S = selectVariables(P$phiInit, P$rhoInit, P$piInit, P$gamInit, mini, maxi, gamma,
                        grid_lambda, X, Y, 1e-8, eps, ncores_inner) #TODO: 1e-8 as arg?! eps?
-
+    
     if (procedure == 'LassoMLE')
                {
       if (verbose)
                                print('run the procedure Lasso-MLE')
       #compute parameter estimations, with the Maximum Likelihood
       #Estimator, restricted on selected variables.
-      models <- constructionModelesLassoMLE(phiInit, rhoInit, piInit, gamInit, mini,
-                               maxi, gamma, X, Y, thresh, eps, S$selected, ncores_inner, verbose)
+      models <- constructionModelesLassoMLE(P$phiInit, P$rhoInit, P$piInit, P$gamInit, mini,
+                               maxi, gamma, X, Y, thresh, eps, S, ncores_inner, artefact = 1e3, verbose)
     }
                else
                {
@@ -87,12 +87,10 @@ valse = function(X, Y, procedure='LassoMLE', selecMod='DDSE', gamma=1, mini=10,
 
        # List (index k) of lists (index lambda) of models
        models_list <-
-               #if (ncores_k > 1)
          if (ncores_outer > 1)
                        parLapply(cl, kmin:kmax, computeModels)
                else
                        lapply(kmin:kmax, computeModels)
-       #if (ncores_k > 1)
        if (ncores_outer > 1)
                parallel::stopCluster(cl)
 
@@ -103,12 +101,13 @@ valse = function(X, Y, procedure='LassoMLE', selecMod='DDSE', gamma=1, mini=10,
        }
 
        # Get summary "tableauRecap" from models ; TODO: jusqu'à ligne 114 à mon avis là c'est faux :/
-       tableauRecap = t( sapply( models_list, function(models) {
+       tableauRecap = sapply( models_list, function(models) {
                llh = do.call(rbind, lapply(models, function(model) model$llh))
     LLH = llh[-1,1]
     D = llh[-1,2]
-               c(LLH, D, rep(k, length(model)), 1:length(model))
-       } ))
+               c(LLH, D, rep(k, length(LLH)), 1:length(LLH))
+       }) 
+       tableauRecap
        if (verbose)
                print('Model selection')
   tableauRecap = tableauRecap[rowSums(tableauRecap[, 2:4])!=0,]
@@ -125,5 +124,5 @@ valse = function(X, Y, procedure='LassoMLE', selecMod='DDSE', gamma=1, mini=10,
                        modSel@BIC_capushe$model
                else if (selecMod == 'AIC')
                        modSel@AIC_capushe$model
-  model[[tableauRecap[indModSel,3]]][[tableauRecap[indModSel,4]]]
+  models_list[[tableauRecap[indModSel,3]]][[tableauRecap[indModSel,4]]]
 }