X-Git-Url: https://git.auder.net/doc/html/img/rock_paper_scissors_lizard_spock.gif?a=blobdiff_plain;f=pkg%2FR%2FselectVariables.R;h=bfe4042d1ec639173b38bd65ac9cb113c186b564;hb=a3cbbaea1cc3c107e5ca62ed1ffe7b9499de0a91;hp=f717caeb46125472a1565b3024f7385c43ec952d;hpb=96b591b7a76da9780e766ead693eb065281b6d62;p=valse.git
diff --git a/pkg/R/selectVariables.R b/pkg/R/selectVariables.R
index f717cae..bfe4042 100644
--- a/pkg/R/selectVariables.R
+++ b/pkg/R/selectVariables.R
@@ -23,7 +23,7 @@
#' @export
#'
selectVariables <- function(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma,
- glambda, X, Y, thresh = 1e-08, eps, ncores = 3, fast = TRUE)
+ glambda, X, Y, thresh = 1e-08, eps, ncores = 3, fast)
{
if (ncores > 1) {
cl <- parallel::makeCluster(ncores, outfile = "")
@@ -52,14 +52,18 @@ selectVariables <- function(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma
}
# For each lambda in the grid, we compute the coefficients
- out <- if (ncores > 1)
- parLapply(cl, glambda, computeCoefs) else lapply(glambda, computeCoefs)
+ out <-
+ if (ncores > 1) {
+ parLapply(cl, glambda, computeCoefs)
+ } else {
+ lapply(glambda, computeCoefs)
+ }
if (ncores > 1)
parallel::stopCluster(cl)
# Suppress models which are computed twice En fait, ca ca fait la comparaison de
# tous les parametres On veut juste supprimer ceux qui ont les memes variables
- # sélectionnées sha1_array <- lapply(out, digest::sha1) out[
- # duplicated(sha1_array) ]
+ # sélectionnées
+ # sha1_array <- lapply(out, digest::sha1) out[ duplicated(sha1_array) ]
selec <- lapply(out, function(model) model$selected)
ind_dup <- duplicated(selec)
ind_uniq <- which(!ind_dup)