From: emilie Date: Thu, 16 Mar 2017 15:03:33 +0000 (+0100) Subject: few details X-Git-Url: https://git.auder.net/variants/current/doc/scripts/img/pieces/common.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