Merge branch 'master' into feature_noisy

Author: jakob-r

.Rbuildignore

@@ -16,3 +16,5 @@
 ^vignettes/.+_cache$
 ^vignettes/.+_files$
 ^vignettes/.+\.html$
+.github
+.covrignore

.gitignore

@@ -10,9 +10,8 @@ src/*.so
 plots
 tests/testthat/Rplots.pdf
 *.sublime-*
-vignettes/*_cache/
 vignettes/*_files/
 vignettes/*.html
 vignettes/*.R
-docs/articles/*_cache/
+*_cache
 .Rproj.user

.travis.yml

@@ -1,18 +1,44 @@
 language: r
+dist: trusty
 sudo: false
 cache: packages
-
 r:
-  - release
-  - devel
-
-r_github_packages:
-  - jimhester/covr
-
+- release
+- devel
+r_packages:
+- devtools
+- animation #vignettes: animation.Rmd
+- e1071 #vignette: machine_learning_with_mlrmbo.Rmd
+- pkgdown
+- covr
+addons:
+  apt:
+    packages:
+      - imagemagick
 env:
+  matrix:
+  - _R_CHECK_LENGTH_1_CONDITION_=true
   global:
-    - secure: "e2QLomaUqNvpHnGNdBXS4VO2/UWokrKl9UgYrqWo+fhpXaJiJuONNPNL44BuWZR2Cy7noTHrevVbTKBkGpqJR42mkjzcjd6qyR1Ctiveir+84/HTtmexouIUn5OFRH5dgyt/gquld31RlHlSYoKho3nZ7D7SnVExov9tp2FGRhU="
-
-# commented out because this call always needed 10+ minutes and time outed for travis
+    secure: efki/PoCvROHC5GMOWqL3hiYeU/no71mnw927ZLF/D0eo3L0aBjT6533KWy3S8w+kg4ilgZzoS5/Nu6PuVFmfPmOiXKj95ZZVkuHDjnAiBFPsowneruOAYNMpwGlM1A3Z3T6jTjtX+FtvlgukhVNrkNoXFy5SmZ5pclic0Z7zfM=
+before_script:
+- R --no-save <<< 'library("devtools"); document()'
 after_success:
-  - Rscript -e 'covr::codecov()'
+- 'if [[ "$TRAVIS_PULL_REQUEST" == "false" && "$TRAVIS_BRANCH" == "master" && "$TRAVIS_R_VERSION_STRING" == "release" && "$TRAVIS_EVENT_TYPE" != "cron" ]] ; then
+    R --no-save <<< "devtools::install(); pkgdown::build_site()";
+    git checkout master;
+    export TRAVIS_COMMIT_MSG="$(git log --format=%B --no-merges -n 1)";
+    git config --global user.name "Travis CI";
+    git config --global user.email "$COMMIT_AUTHOR_EMAIL";
+    git config credential.helper "store --file=.git/credentials";
+    echo "https://${GH_TOKEN}:@github.com" >> .git/credentials;
+    git config push.default matching;
+    git add --force man/*;
+    git add --force README.md;
+    git add --force docs/*;
+    git rm -r --cached $(find . -type d -name "*_cache");
+    git commit man DESCRIPTION NAMESPACE README.md docs -m "update auto-generated documentation [ci skip]" -m "$TRAVIS_COMMIT_MSG" || true;
+    git push;
+  fi;'
+- 'if [[ "$TRAVIS_R_VERSION_STRING" == "devel" && "$TRAVIS_EVENT_TYPE" != "cron" ]] ; then
+    Rscript -e "covr::coveralls()";
+  fi;'

DESCRIPTION

@@ -1,24 +1,25 @@
 Package: mlrMBO
-Title: A Toolbox for Model-Based Optimization of Expensive Black-Box Functions
+Title: Bayesian Optimization and Model-Based Optimization of Expensive Black-Box Functions
 Description: Flexible and comprehensive R toolbox for model-based optimization
-    ('MBO'), also known as Bayesian optimization. It is designed for both single-
-    and multi-objective optimization with mixed continuous, categorical and
-    conditional parameters. The machine learning toolbox 'mlr' provide dozens
-    of regression learners to model the performance of the target algorithm with
-    respect to the parameter settings. It provides many different infill criteria
-    to guide the search process. Additional features include multi-point batch
-    proposal, parallel execution as well as visualization and sophisticated
-    logging mechanisms, which is especially useful for teaching and understanding
-    of algorithm behavior. 'mlrMBO' is implemented in a modular fashion, such that
-    single components can be easily replaced or adapted by the user for specific use
-    cases.
+    ('MBO'), also known as Bayesian optimization. It implements the Efficient
+    Global Optimization Algorithm and is designed for both single- and multi-
+    objective optimization with mixed continuous, categorical and conditional
+    parameters. The machine learning toolbox 'mlr' provide dozens of regression
+    learners to model the performance of the target algorithm with respect to
+    the parameter settings. It provides many different infill criteria to guide
+    the search process. Additional features include multi-point batch proposal,
+    parallel execution as well as visualization and sophisticated logging
+    mechanisms, which is especially useful for teaching and understanding of
+    algorithm behavior. 'mlrMBO' is implemented in a modular fashion, such that
+    single components can be easily replaced or adapted by the user for specific
+    use cases.
 Authors@R: c(
-    person("Bernd", "Bischl", email = "[email protected]", role = c("aut")),
-    person("Jakob", "Bossek", email = "[email protected]", role = "aut"),
-    person("Jakob", "Richter", email = "[email protected]", role = c("aut", "cre")),
+    person("Bernd", "Bischl", email = "[email protected]", role = c("aut"), comment = c(ORCID = "0000-0001-6002-6980")),
+    person("Jakob", "Richter", email = "[email protected]", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-4481-5554")),
+    person("Jakob", "Bossek", email = "[email protected]", role = "aut", comment = c(ORCID = "0000-0002-4121-4668")),
     person("Daniel", "Horn", email = "[email protected]", role = "aut"),
-    person("Michel", "Lang", email = "[email protected]", role = "aut"),
-    person("Janek", "Thomas", email = "[email protected]", role = "aut"))
+    person("Michel", "Lang", email = "[email protected]", role = "aut", comment = c(ORCID = "0000-0001-9754-0393")),
+    person("Janek", "Thomas", email = "[email protected]", role = "aut", comment = c(ORCID = "0000-0003-4511-6245")))
 License: BSD_2_clause + file LICENSE
 URL: https://github.com/mlr-org/mlrMBO
 BugReports: https://github.com/mlr-org/mlrMBO/issues
@@ -52,13 +53,13 @@ Suggests:
     party,
     randomForest,
     rmarkdown,
+    rgenoud,
     rpart,
     testthat,
-    eaf,
     covr
 LazyData: yes
 Encoding: UTF-8
 ByteCompile: yes
-Version: 1.1.2
+Version: 1.1.3
 RoxygenNote: 6.0.1
 VignetteBuilder: knitr

NAMESPACE

@@ -1,5 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(initCrit,InfillCritAdaCB)
 S3method(initCrit,InfillCritCB)
 S3method(initCrit,default)
 S3method(plot,MBOMultiObjResult)
@@ -39,6 +40,7 @@ export(initSMBO)
 export(makeMBOControl)
 export(makeMBOInfillCrit)
 export(makeMBOInfillCritAEI)
+export(makeMBOInfillCritAdaCB)
 export(makeMBOInfillCritCB)
 export(makeMBOInfillCritDIB)
 export(makeMBOInfillCritEI)

NEWS.md

@@ -1,3 +1,10 @@
+# mlrMBO 1.1.2
+
+* Adaptive infill criterions. Infill criterions now have to support an `progress` argument. Termination criterions now can supply a `progress` return value.
+* Fix for parEGO + EI (Issue #407)
+* `save.on.disk` now can take arbitrary numeric vectors to specify iterations, when to save on disk.
+* Spelling mistakes for infill criterions will now be cought. (Issue #417)
+
 # mlrMBO 1.1.1
 
 * `makeMBOControl()` has `on.surrogate.error` argument which enables random proposals if the surrogate model fails.

R/OptState.R

@@ -39,6 +39,8 @@ NULL
 #  @param time.used \code{integer(1)} \cr
 #    The time in seconds we are already used for optimization since the very start.
 #    This counts all iterations together and is necessary for continuation with a given time budget.
+#  @param progress \code{numeric(1)} \cr
+#    The progress in percent determined by the termination criterion.
 
 # IMPORTANT NOTE:
 # See this as a constructor and it's variables as member variables.
@@ -48,7 +50,7 @@ NULL
 
 makeOptState = function(opt.problem, loop = 0L, tasks = NULL, models = NULL,
   time.model = NULL, opt.result = NULL, state = "init", opt.path = NULL,
-  time.last.saved = Sys.time(), loop.starttime = Sys.time(), time.used = 0L, time.created = Sys.time()) {
+  time.last.saved = Sys.time(), loop.starttime = Sys.time(), time.used = 0L, progress = 0, time.created = Sys.time()) {
 
   opt.state = new.env()
 
@@ -65,6 +67,7 @@ makeOptState = function(opt.problem, loop = 0L, tasks = NULL, models = NULL,
   opt.state$time.last.saved = time.last.saved
   opt.state$loop.starttime = loop.starttime
   opt.state$time.used = time.used
+  opt.state$progress = progress
 
   opt.state$random.seed = getRandomSeed()
   opt.state$time.created = time.created

R/OptState_getter.R

@@ -34,6 +34,11 @@ getOptStateTasks = function(opt.state) {
   tasks
 }
 
+getOptStateDesigns = function(opt.state) {
+  tasks = getOptStateTasks(opt.state)
+  lapply(tasks, getTaskData)
+}
+
 getOptStateTimeModel = function(opt.state) {
   opt.path = getOptStateOptPath(opt.state)
   time.model = opt.state$time.model
@@ -119,17 +124,23 @@ getOptStateState = function(opt.state) {
 
 getOptStateTermination = function(opt.state) {
   terminate = shouldTerminate.OptState(opt.state)
+  setOptStateProgress(opt.state, terminate$progress)
   # update only if termination condition is met
   if (terminate$term) {
     setOptStateState(opt.state, terminate$code)
   }
   terminate
 }
 
+getOptStateProgress = function(opt.state) {
+  opt.state$progress
+}
+
 getOptStateValidStates = function() {
   c("init", "iter", getOptStateValidTerminationStates())
 }
 
 getOptStateValidTerminationStates = function() {
   c("term.iter", "term.time", "term.exectime", "term.yval", "term.feval", "term.custom")
 }
+

R/OptState_setter.R

@@ -58,3 +58,9 @@ setOptStateState = function(opt.state, state) {
   opt.state$state = state
   invisible()
 }
+
+setOptStateProgress = function(opt.state, progress) {
+  assertNumber(progress, null.ok = TRUE)
+  opt.state$progress = progress
+  invisible()
+}

R/SMBO.R

@@ -69,7 +69,7 @@ updateSMBO = function(opt.state, x, y) {
   assertNumeric(y[[1]], len = control$n.objectives)
 
 
-  infill.values = control$infill.crit$fun(points = x, models = getOptStateModels(opt.state)[[1]], control = control, design = convertOptPathToDf(opt.path, control), attributes = TRUE, iter = getOptStateLoop(opt.state))
+  infill.values = control$infill.crit$fun(points = x, models = getOptStateModels(opt.state)[[1]], control = control, designs = getOptStateDesigns(opt.state), attributes = TRUE, iter = getOptStateLoop(opt.state))
 
   prop = makeProposal(
     control = control,