test auto-indenter

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

diff --git a/pkg/R/constructionModelesLassoRank.R b/pkg/R/constructionModelesLassoRank.R
index fe75d2c..b997303 100644 (file)
--- a/pkg/R/constructionModelesLassoRank.R
+++ b/pkg/R/constructionModelesLassoRank.R
@@ -1,7 +1,7 @@
 #' constructionModelesLassoRank
 #'
 #' Construct a collection of models with the Lasso-Rank procedure.
-#' 
+#'
 #' @param S output of selectVariables.R
 #' @param k number of components
 #' @param mini integer, minimum number of iterations in the EM algorithm, by default = 10
@@ -14,7 +14,7 @@
 #' @param ncores Number of cores, by default = 3
 #' @param fast TRUE to use compiled C code, FALSE for R code only
 #' @param verbose TRUE to show some execution traces
-#' 
+#'
 #' @return a list with several models, defined by phi, rho, pi, llh
 #'
 #' @export
@@ -80,13 +80,17 @@ constructionModelesLassoRank <- function(S, k, mini, maxi, X, Y, eps, rank.min,
         phi[relevant, , ] <- res$phi
       }
       list(llh = llh, phi = phi, pi = S[[lambdaIndex]]$Pi, rho = S[[lambdaIndex]]$Rho)
-      
     }
   }
   
   # For each lambda in the grid we compute the estimators
-  out <- if (ncores > 1) 
-    parLapply(cl, seq_len(length(S) * Size), computeAtLambda) else lapply(seq_len(length(S) * Size), computeAtLambda)
+  out <- if (ncores > 1)
+  {
+    parLapply(cl, seq_len(length(S) * Size), computeAtLambda)
+  } else
+  {
+    lapply(seq_len(length(S) * Size), computeAtLambda)
+  }
   
   if (ncores > 1) 
     parallel::stopCluster(cl)