X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FmultiRun.R;h=f38f9f3a1b418f808007857fe2601a62d69ce673;hb=0f5fbd1371011f25cd1f6caf0e826d2ea9e4e245;hp=1cebaab7b3e9dc60c40abf5f39fc7b577418c7d5;hpb=cf673dee64ab0ce02ccaaba0fb63a9a4589ee8aa;p=morpheus.git

diff --git a/pkg/R/multiRun.R b/pkg/R/multiRun.R
index 1cebaab..f38f9f3 100644
--- a/pkg/R/multiRun.R
+++ b/pkg/R/multiRun.R
@@ -17,13 +17,13 @@
 #' @return A list of nf aggregates of N results (matrices).
 #'
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' β <- matrix(c(1,-2,3,1),ncol=2)
 #'
 #' # Bootstrap + computeMu, morpheus VS flexmix ; assumes fargs first 3 elts X,Y,K
 #' io <- generateSampleIO(n=1000, p=1/2, β=β, b=c(0,0), "logit")
 #' μ <- normalize(β)
-#' res <- multiRun(list(X=io$X,Y=io$Y,optargs=list(K=2,jd_nvects=0)), list(
+#' res <- multiRun(list(X=io$X,Y=io$Y,optargs=list(K=2)), list(
 #'   # morpheus
 #'   function(fargs) {
 #'     library(morpheus)
@@ -57,8 +57,7 @@
 #'     library(morpheus)
 #'     K <- fargs$optargs$K
 #'     μ <- computeMu(fargs$X, fargs$Y, fargs$optargs)
-#'     V <- list( p=rep(1/K,K-1), β=μ, b=c(0,0) )
-#'     optimParams(V,fargs$optargs)$β
+#'     optimParams(fargs$K,fargs$link,fargs$optargs)$run(list(β=μ))$β
 #'   },
 #'   # flexmix
 #'   function(fargs) {
@@ -74,7 +73,8 @@
 #'     io = generateSampleIO(fargs$n, fargs$p, fargs$β, fargs$b, fargs$optargs$link)
 #'     fargs$X = io$X
 #'     fargs$Y = io$Y
-#'     fargs$optargs$K = ncol(fargs$β)
+#'     fargs$K = ncol(fargs$β)
+#'     fargs$link = fargs$optargs$link
 #'     fargs$optargs$M = computeMoments(io$X,io$Y)
 #'     fargs
 #'   }, N=10, ncores=3)
@@ -82,48 +82,48 @@
 #'   res[[i]] <- alignMatrices(res[[i]], ref=β, ls_mode="exact")}
 #' @export
 multiRun <- function(fargs, estimParams,
-	prepareArgs = function(x,i) x, N=10, ncores=3, agg=lapply, verbose=FALSE)
+  prepareArgs = function(x,i) x, N=10, ncores=3, agg=lapply, verbose=FALSE)
 {
-	if (!is.list(fargs))
-		stop("fargs: list")
-	# No checks on fargs: supposedly done in estimParams[[i]]()
-	if (!is.list(estimParams))
-		estimParams = list(estimParams)
-	# Verify that the provided parameters estimations are indeed functions
-	lapply(seq_along(estimParams), function(i) {
-		if (!is.function(estimParams[[i]]))
-			stop("estimParams: list of function(fargs)")
-	})
-	if (!is.numeric(N) || N < 1)
-		stop("N: positive integer")
+  if (!is.list(fargs))
+    stop("fargs: list")
+  # No checks on fargs: supposedly done in estimParams[[i]]()
+  if (!is.list(estimParams))
+    estimParams = list(estimParams)
+  # Verify that the provided parameters estimations are indeed functions
+  lapply(seq_along(estimParams), function(i) {
+    if (!is.function(estimParams[[i]]))
+      stop("estimParams: list of function(fargs)")
+  })
+  if (!is.numeric(N) || N < 1)
+    stop("N: positive integer")
 
-	estimParamAtIndex <- function(index)
-	{
-		fargs <- prepareArgs(fargs, index)
-		if (verbose)
-			cat("Run ",index,"\n")
-		lapply(seq_along(estimParams), function(i) {
-			if (verbose)
-				cat("   Method ",i,"\n")
-			out <- estimParams[[i]](fargs)
-			if (is.list(out))
-				do.call(rbind, out)
-			else
-				out
-		})
-	}
+  estimParamAtIndex <- function(index)
+  {
+    fargs <- prepareArgs(fargs, index)
+    if (verbose)
+      cat("Run ",index,"\n")
+    lapply(seq_along(estimParams), function(i) {
+      if (verbose)
+        cat("   Method ",i,"\n")
+      out <- estimParams[[i]](fargs)
+      if (is.list(out))
+        do.call(rbind, out)
+      else
+        out
+    })
+  }
 
-	if (ncores > 1)
-	{
-		cl = parallel::makeCluster(ncores, outfile="")
-		parallel::clusterExport(cl, c("fargs","verbose"), environment())
-		list_res = parallel::clusterApplyLB(cl, 1:N, estimParamAtIndex)
-		parallel::stopCluster(cl)
-	}
-	else
-		list_res = lapply(1:N, estimParamAtIndex)
+  if (ncores > 1)
+  {
+    cl = parallel::makeCluster(ncores, outfile="")
+    parallel::clusterExport(cl, c("fargs","verbose"), environment())
+    list_res = parallel::clusterApplyLB(cl, 1:N, estimParamAtIndex)
+    parallel::stopCluster(cl)
+  }
+  else
+    list_res = lapply(1:N, estimParamAtIndex)
 
-	# De-interlace results: output one list per function
-	nf <- length(estimParams)
-	lapply( seq_len(nf), function(i) lapply(seq_len(N), function(j) list_res[[j]][[i]]) )
+  # De-interlace results: output one list per function
+  nf <- length(estimParams)
+  lapply( seq_len(nf), function(i) lapply(seq_len(N), function(j) list_res[[j]][[i]]) )
 }