dontrun + fixed test

R/addExperiments.R

@@ -23,7 +23,6 @@
 #'   Default is FALSE.
 #' @return Invisibly returns vector of ids of added experiments.
 #' @examples
-#' \dontrun{
 #' ### EXAMPLE 1 ###
 #' reg <- makeExperimentRegistry(id="example1", file.dir=tempfile())
 #'
@@ -93,7 +92,6 @@
 #'
 #' # Submit the jobs to the batch system
 #' submitJobs(reg)
-#' waitForJobs(reg)
 #'
 #' # Calculate the misclassification rate for all (already done) jobs.
 #' reduce <- function(job, res) {
@@ -139,11 +137,9 @@
 #' # add experiments and submit
 #' addExperiments(reg, repls=10)
 #' submitJobs(reg)
-#' waitForJobs(reg)
 #'
 #' # Gather informations from the experiments, in this case function value and if the algorithm convergenced:
 #' reduceResultsExperiments(reg, fun=function(job, res) res[c("value", "convergence")])
-#' }
 #' @aliases Experiment
 #' @export
 addExperiments = function(reg, prob.designs, algo.designs, repls=1L, skip.defined=FALSE) {

R/getIndex.R

@@ -28,7 +28,6 @@
 #' @return [\code{list}]. List of factors.
 #' @export
 #' @examples
-#' \dontrun{
 #' # create a registry and add problems and algorithms
 #' reg = makeExperimentRegistry("getIndex", file.dir=tempfile(""))
 #' addProblem(reg, "prob", static = 1)
@@ -37,7 +36,6 @@
 #' ad = list(makeDesign("f0"), makeDesign("f1", exhaustive=list(i=1:10, k=1:3)))
 #' addExperiments(reg, algo.designs=ad)
 #' submitJobs(reg)
-#' waitForJobs(reg)
 #'
 #' # get grouped job ids
 #' ids = getJobIds(reg)
@@ -50,7 +48,6 @@
 #' f = function(aggr, job, res) aggr + res
 #' by(ids.f1, getIndex(reg, ids.f1, by.algo.pars=k), reduceResults, reg=reg, fun=f)
 #' by(ids.f1, getIndex(reg, ids.f1, by.algo.pars=i), reduceResults, reg=reg, fun=f)
-#' }
 getIndex = function(reg, ids, by.prob=FALSE, by.algo=FALSE, by.repl=FALSE,
                     by.prob.pars, by.algo.pars, enclos = parent.frame()) {
   checkArg(reg, "ExperimentRegistry")

R/reduceResultsExperiments.R

@@ -127,7 +127,6 @@ reduceResultsExperiments = function(reg, ids, part=NA_character_, fun, ...,
 #' @return [\code{character}]. Names of of columns.
 #' @export
 #' @examples
-#' \dontrun{
 #' reg <- makeExperimentRegistry("BatchExample", seed=123, file.dir=tempfile())
 #' addProblem(reg, "p1", static=1)
 #' addProblem(reg, "p2", static=2)
@@ -139,11 +138,9 @@ reduceResultsExperiments = function(reg, ids, part=NA_character_, fun, ...,
 #' ad2 <- makeDesign("a2", exhaustive=list(alpha=1:2, beta=5:6))
 #' addExperiments(reg, algo.designs=list(ad1, ad2), repls=2)
 #' submitJobs(reg)
-#' waitForJobs(reg)
 #' data <- reduceResultsExperiments(reg)
 #' library(plyr)
 #' ddply(data, getResultVars(data, "group"), summarise, mean_y = mean(y))
-#' }
 getResultVars = function(data, type="group") {
   checkArg(data, "ReducedResultsExperiments")
   checkArg(type, choices=c("prob", "prob.pars", "algo", "algo.pars", "group", "result"))

inst/tests/test_testJob.R

@@ -5,6 +5,6 @@ test_that("testJob", {
   a1 = addAlgorithm(reg, id="a1", fun=function(static, dynamic) static)
   addExperiments(reg, p1, a1)
   expect_equal(testJob(reg, 1L, external=FALSE), 1)
-  if (isExpensiveExampleOk())
+  if (isExpensiveExampleOk() && interactive()) # FIXME
     expect_equal(testJob(reg, 1L, external=TRUE), 1)
 })

man/addExperiments.Rd

@@ -41,7 +41,6 @@ Add experiments for running algorithms on problems to the
 registry, so they can be executed later.
 }
 \examples{
-\dontrun{
 ### EXAMPLE 1 ###
 reg <- makeExperimentRegistry(id="example1", file.dir=tempfile())
 
@@ -111,7 +110,6 @@ if (do.tests) {
 
 # Submit the jobs to the batch system
 submitJobs(reg)
-waitForJobs(reg)
 
 # Calculate the misclassification rate for all (already done) jobs.
 reduce <- function(job, res) {
@@ -157,10 +155,8 @@ addAlgorithm(reg, "sann", fun=function(static, dynamic) {
 # add experiments and submit
 addExperiments(reg, repls=10)
 submitJobs(reg)
-waitForJobs(reg)
 
 # Gather informations from the experiments, in this case function value and if the algorithm convergenced:
 reduceResultsExperiments(reg, fun=function(job, res) res[c("value", "convergence")])
 }
-}
 

man/getIndex.Rd

@@ -45,7 +45,6 @@ like \code{\link{tapply}}, \code{\link{by}} or
 \code{\link{aggregate}}.
 }
 \examples{
-\dontrun{
 # create a registry and add problems and algorithms
 reg = makeExperimentRegistry("getIndex", file.dir=tempfile(""))
 addProblem(reg, "prob", static = 1)
@@ -54,7 +53,6 @@ addAlgorithm(reg, "f1", function(static, dynamic, i, k) static * i^k)
 ad = list(makeDesign("f0"), makeDesign("f1", exhaustive=list(i=1:10, k=1:3)))
 addExperiments(reg, algo.designs=ad)
 submitJobs(reg)
-waitForJobs(reg)
 
 # get grouped job ids
 ids = getJobIds(reg)
@@ -68,5 +66,4 @@ f = function(aggr, job, res) aggr + res
 by(ids.f1, getIndex(reg, ids.f1, by.algo.pars=k), reduceResults, reg=reg, fun=f)
 by(ids.f1, getIndex(reg, ids.f1, by.algo.pars=i), reduceResults, reg=reg, fun=f)
 }
-}
 

man/getResultVars.Rd

@@ -23,7 +23,6 @@ getResultVars(data, type = "group")
 Useful helper for e.g. package plyr and such.
 }
 \examples{
-\dontrun{
 reg <- makeExperimentRegistry("BatchExample", seed=123, file.dir=tempfile())
 addProblem(reg, "p1", static=1)
 addProblem(reg, "p2", static=2)
@@ -35,10 +34,8 @@ ad1 <- makeDesign("a1", exhaustive=list(alpha=1:2))
 ad2 <- makeDesign("a2", exhaustive=list(alpha=1:2, beta=5:6))
 addExperiments(reg, algo.designs=list(ad1, ad2), repls=2)
 submitJobs(reg)
-waitForJobs(reg)
 data <- reduceResultsExperiments(reg)
 library(plyr)
 ddply(data, getResultVars(data, "group"), summarise, mean_y = mean(y))
 }
-}