renome multipoint.multicrit to moimbo (#279)

ja-thomas · jakob-r · commit b2f77613ac92 · 2016-11-24T11:46:42.000+01:00
diff --git a/R/checkStuff.R b/R/checkStuff.R
@@ -95,12 +95,12 @@ checkStuff = function(fun, par.set, design, learner, control) {
     if (control$propose.points == 1L) { # single point
     } else {                            # multi point
       if ((control$multipoint.method %in% c("cb", "cl", "cb") ||
-          control$multipoint.method == "multicrit" && control$multipoint.multicrit.objective != "mean.dist" )
+          control$multipoint.method == "moimbo" && control$multipoint.moimbo.objective != "mean.dist" )
         && learner$predict.type != "se") {
         stopf("For multipoint method '%s'%s, predict.type of learner %s must be set to 'se'!%s",
           control$multipoint.method,
-          ifelse(control$multipoint.method == "multicrit",
-            sprintf(" with objective '%s'", control$multipoint.multicrit.obj), ""),
+          ifelse(control$multipoint.method == "moimbo",
+            sprintf(" with objective '%s'", control$multipoint.moimbo.obj), ""),
           learner$id,
           ifelse(hasLearnerProperties(learner, "se"), "",
             "\nBut this learner does not support prediction of standard errors!"))
diff --git a/R/getSupportedMultipointInfillOptFunctions.R b/R/getSupportedMultipointInfillOptFunctions.R
@@ -6,5 +6,5 @@
 #' @return [\code{character}]
 #' @export
 getSupportedMultipointInfillOptFunctions = function() {
-  c("cl", "cb", "multicrit")
+  c("cl", "cb", "moimbo")
 }
diff --git a/R/proposePoints.R b/R/proposePoints.R
@@ -28,7 +28,7 @@ proposePoints.OptState = function(opt.state){
         res = proposePointsParallelCB(opt.state)
       else if (control$multipoint.method == "cl")
         res = proposePointsConstantLiar(opt.state)
-      else if (control$multipoint.method == "multicrit") {
+      else if (control$multipoint.method == "moimbo") {
         res = proposePointsMOIMBO(opt.state)
       }
     }
diff --git a/R/proposePointsMOIMBO.R b/R/proposePointsMOIMBO.R
@@ -51,7 +51,7 @@ proposePointsMOIMBO = function(opt.state, ...) {
   requirePackages("emoa", why = "multipointInfillOptMulticrit")
 
   n = control$propose.points
-  objective = control$multipoint.multicrit.objective
+  objective = control$multipoint.moimbo.objective
   design = convertOptPathToDf(opt.path, control)
 
   ch = checkFailedModels(models, par.set, n)
@@ -63,11 +63,11 @@ proposePointsMOIMBO = function(opt.state, ...) {
   repids = getParamIds(par.set, repeated = TRUE, with.nr = TRUE)
   mu = n
   # FIXME: what are good defaults?
-  mutate =  emoa::pm_operator(control$multipoint.multicrit.pm.eta, control$multipoint.multicrit.pm.p,
+  mutate =  emoa::pm_operator(control$multipoint.moimbo.pm.eta, control$multipoint.moimbo.pm.p,
     getLower(par.set), getUpper(par.set))
-  crossover = emoa::sbx_operator(control$multipoint.multicrit.sbx.eta, control$multipoint.multicrit.sbx.p,
+  crossover = emoa::sbx_operator(control$multipoint.moimbo.sbx.eta, control$multipoint.moimbo.sbx.p,
     getLower(par.set), getUpper(par.set))
-  mydist = switch(control$multipoint.multicrit.dist,
+  mydist = switch(control$multipoint.moimbo.dist,
     nearest.neighbor = distToNN,
     nearest.better = distToNB
   )
@@ -90,7 +90,7 @@ proposePointsMOIMBO = function(opt.state, ...) {
     Y[, y.dim] = -mydist(as.matrix(X), Y[,1])
 
   secs = measureTime({
-    for (i in seq_len(control$multipoint.multicrit.maxit)) {
+    for (i in seq_len(control$multipoint.moimbo.maxit)) {
       # Create new individual (mu + 1)
       parents = sample(seq_len(mu), 2)
       # get two kids from CX, sel. 1 randomly, mutate
@@ -118,13 +118,13 @@ proposePointsMOIMBO = function(opt.state, ...) {
         Y[, y.dim] = -mydist(as.matrix(X), Y[,1])
 
       # get elements we want to remove from current pop as index vector
-      to.kill = if (control$multipoint.multicrit.selection == "hypervolume") {
+      to.kill = if (control$multipoint.moimbo.selection == "hypervolume") {
         emoa::nds_hv_selection(t(Y))
-      } else if (control$multipoint.multicrit.selection == "crowdingdist") {
+      } else if (control$multipoint.moimbo.selection == "crowdingdist") {
         emoa::nds_cd_selection(t(Y))
-      } else if (control$multipoint.multicrit.selection == "first") {
+      } else if (control$multipoint.moimbo.selection == "first") {
         nds_1d_selection(t(Y), index = 1)
-      } else if (control$multipoint.multicrit.selection == "last") {
+      } else if (control$multipoint.moimbo.selection == "last") {
         nds_1d_selection(t(Y), index = y.dim)
       }
       X = X[-to.kill, ,drop = FALSE]
diff --git a/R/renderExampleRunPlotSingleCrit1d.R b/R/renderExampleRunPlotSingleCrit1d.R
@@ -93,7 +93,7 @@ renderExampleRunPlot1d = function(x, iter,
       evals[[name.crit]] = opt.direction *
         critfun(evals.x, list(model), control, par.set, convertOptPathToDf(opt.path, control)[idx.past,, drop = FALSE])
     } else {
-      objective = control$multipoint.multicrit.objective
+      objective = control$multipoint.moimbo.objective
       if (objective == "mean.dist") {
         evals[[name.crit]] = opt.direction * infillCritMeanResponse(evals.x, list(model), control, par.set, convertOptPathToDf(opt.path, control)[idx.past,, drop = FALSE])
       } else if (objective == "ei.dist") {
diff --git a/R/renderExampleRunPlotSingleCrit2d.R b/R/renderExampleRunPlotSingleCrit2d.R
@@ -59,7 +59,7 @@ renderExampleRunPlot2d = function(x, iter,
     if (proppoints == 1L) {
       evals[[name.crit]] = opt.direction * critfun(evals.x, models, control, par.set, opt.path[idx.past, ])
     } else {
-      objective = control$multipoint.multicrit.objective
+      objective = control$multipoint.moimbo.objective
       if (control$multipoint.method == "cb") {
         evals[[name.crit]] = opt.direction * infillCritMeanResponse(evals.x, models, control, par.set, opt.path[idx.past, ])
       } else {
diff --git a/R/setMBOControlMultiPoint.R b/R/setMBOControlMultiPoint.R
@@ -10,10 +10,10 @@
 #'   exp(1)-distribution, so do not define \code{infill.opt.cb.lambda}.
 #'   The optimizer for each proposal is configured in the same way as for the single point case,
 #'   i. e., by specifying \code{infill.opt} and related stuff.
-#'   \dQuote{multicrit}: Proposes points by evolutionary multicriteria optimization.
-#'   The EA is a (mu+1) type of algorithm and runs for \code{multicrit.maxit} generations.
+#'   \dQuote{moimbo}: Proposes points by multiobjective infill criteria via evolutionary multicriteria optimization.
+#'   The EA is a (mu+1) type of algorithm and runs for \code{moimbo.maxit} generations.
 #'   The population size is set to \code{propose.points}.
-#'   The selection criterion is \code{multicrit.selection}.
+#'   The selection criterion is \code{moimbo.selection}.
 #'   \dQuote{cl}: Proposes points by constant liar strategy.
 #'   Only meaningfull if \code{infill.crit == "cb"}
 #'   In the first step the kriging model is fitted based on the real data and the best point is calculated
@@ -24,37 +24,37 @@
 #'   Default is \code{cb}.
 #' @param cl.lie [\code{function}]\cr
 #'   Function used by constant liar method for lying. Default is \code{min}.
-#' @param multicrit.objective [\code{character(1)}]\cr
+#' @param moimbo.objective [\code{character(1)}]\cr
 #'   Objectives which are optimized in multicrit approach.
 #'   Possible values are: \dQuote{mean.dist}, \dQuote{ei.dist}, \dQuote{mean.se}, \dQuote{mean.se.dist}.
 #'   Default is \dQuote{ei.dist}.
-#' @param multicrit.dist [\code{character(1)}]\cr
+#' @param moimbo.dist [\code{character(1)}]\cr
 #'   Distance function used in multicrit EA.
 #'   Possible values are: \dQuote{nearest.neigbor}, \dQuote{nearest.better}.
 #'   Default is \dQuote{nearest.better}.
 #FIXME: a link to the definition of nearest.better and nearest.neigbor?
-#' @param multicrit.selection [\code{character(1)}]\cr
+#' @param moimbo.selection [\code{character(1)}]\cr
 #'   Method used for selecting 1 element for removal from the population
 #'   in each iteration of the multicriteria EA.
 #'   Possible values are:
 #'   \dQuote{hypervolume}: Non-dominated sorting + hypervolume contribution.
 #'   \dQuote{crowdingdist}: Non-dominated sorting + crowding distance based ranking.
-#'   \dQuote{first}: Non-dominated sorting + first objective of \code{multicrit.objective} as criterion.
-#'   \dQuote{last}: Non-dominated sorting + last objective of \code{multicrit.objective} as criterion.
+#'   \dQuote{first}: Non-dominated sorting + first objective of \code{moimbo.objective} as criterion.
+#'   \dQuote{last}: Non-dominated sorting + last objective of \code{moimbo.objective} as criterion.
 #'   Default is \code{hypervolume}.
-#' @param multicrit.maxit [\code{character(1)}]\cr
+#' @param moimbo.maxit [\code{character(1)}]\cr
 #'   Number of generations for multicriteria EA.
 #'   Default is 100.
-#' @param multicrit.sbx.eta [\code{numeric(1)}]\cr
+#' @param moimbo.sbx.eta [\code{numeric(1)}]\cr
 #'   Distance parameter of crossover distribution, see \code{\link[emoa]{sbx_operator}}.
 #'   Default is 15.
-#' @param multicrit.sbx.p [\code{numeric(1)}]\cr
+#' @param moimbo.sbx.p [\code{numeric(1)}]\cr
 #'   Probability of 1-point crossover, see \code{\link[emoa]{sbx_operator}}.
 #'   Default is 1.
-#' @param multicrit.pm.eta [\code{numeric(1)}]\cr
+#' @param moimbo.pm.eta [\code{numeric(1)}]\cr
 #'   Distance parameter of mutation distribution, see \code{\link[emoa]{pm_operator}}.
 #'   Default is 15.
-#' @param multicrit.pm.p [\code{numeric(1)}]\cr
+#' @param moimbo.pm.p [\code{numeric(1)}]\cr
 #'   Probability of 1-point mutation, see \code{\link[emoa]{pm_operator}}.
 #'   Default is 1.
 #' @return [\code{\link{MBOControl}}].
@@ -63,12 +63,12 @@
 setMBOControlMultiPoint = function(control,
   method = NULL,
   cl.lie = NULL,
-  multicrit.objective = NULL,
-  multicrit.dist = NULL,
-  multicrit.selection = NULL,
-  multicrit.maxit = NULL,
-  multicrit.sbx.eta = NULL, multicrit.sbx.p = NULL,
-  multicrit.pm.eta = NULL, multicrit.pm.p = NULL) {
+  moimbo.objective = NULL,
+  moimbo.dist = NULL,
+  moimbo.selection = NULL,
+  moimbo.maxit = NULL,
+  moimbo.sbx.eta = NULL, moimbo.sbx.p = NULL,
+  moimbo.pm.eta = NULL, moimbo.pm.p = NULL) {
 
   assertClass(control, "MBOControl")
 
@@ -85,32 +85,32 @@ setMBOControlMultiPoint = function(control,
   }
   assertFunction(control$multipoint.cl.lie)
 
-  control$multipoint.multicrit.objective = coalesce(multicrit.objective, control$multipoint.multicrit.objective, "ei.dist")
-  assertChoice(control$multipoint.multicrit.objective, choices = c("mean.dist", "ei.dist", "mean.se", "mean.se.dist"))
+  control$multipoint.moimbo.objective = coalesce(moimbo.objective, control$multipoint.moimbo.objective, "ei.dist")
+  assertChoice(control$multipoint.moimbo.objective, choices = c("mean.dist", "ei.dist", "mean.se", "mean.se.dist"))
 
-  control$multipoint.multicrit.dist = coalesce(multicrit.dist, control$multipoint.multicrit.dist, "nearest.better")
-  assertChoice(control$multipoint.multicrit.dist, choices = c("nearest.neighbor", "nearest.better"))
+  control$multipoint.moimbo.dist = coalesce(moimbo.dist, control$multipoint.moimbo.dist, "nearest.better")
+  assertChoice(control$multipoint.moimbo.dist, choices = c("nearest.neighbor", "nearest.better"))
 
-  control$multipoint.multicrit.selection = coalesce(multicrit.selection, control$multipoint.multicrit.selection, "hypervolume")
-  assertChoice(control$multipoint.multicrit.selection, choices = c("hypervolume", "crowdingdist", "first", "last"))
+  control$multipoint.moimbo.selection = coalesce(moimbo.selection, control$multipoint.moimbo.selection, "hypervolume")
+  assertChoice(control$multipoint.moimbo.selection, choices = c("hypervolume", "crowdingdist", "first", "last"))
 
-  if (!is.null(multicrit.maxit)) {
-    multicrit.maxit = asCount(multicrit.maxit)
+  if (!is.null(moimbo.maxit)) {
+    moimbo.maxit = asCount(moimbo.maxit)
   }
-  control$multipoint.multicrit.maxit = coalesce(multicrit.maxit, control$multipoint.multicrit.maxit, 100L)
-  assertCount(control$multipoint.multicrit.maxit, na.ok = FALSE, positive = TRUE)
+  control$multipoint.moimbo.maxit = coalesce(moimbo.maxit, control$multipoint.moimbo.maxit, 100L)
+  assertCount(control$multipoint.moimbo.maxit, na.ok = FALSE, positive = TRUE)
 
-  control$multipoint.multicrit.sbx.eta = coalesce(multicrit.sbx.eta, control$multipoint.multicrit.sbx.eta, 15)
-  assertNumber(control$multipoint.multicrit.sbx.eta, na.ok = FALSE, lower = 0)
+  control$multipoint.moimbo.sbx.eta = coalesce(moimbo.sbx.eta, control$multipoint.moimbo.sbx.eta, 15)
+  assertNumber(control$multipoint.moimbo.sbx.eta, na.ok = FALSE, lower = 0)
 
-  control$multipoint.multicrit.sbx.p = coalesce(multicrit.sbx.p, control$multipoint.multicrit.sbx.p, 1)
-  assertNumber(control$multipoint.multicrit.sbx.p, na.ok = FALSE, lower = 0, upper = 1)
+  control$multipoint.moimbo.sbx.p = coalesce(moimbo.sbx.p, control$multipoint.moimbo.sbx.p, 1)
+  assertNumber(control$multipoint.moimbo.sbx.p, na.ok = FALSE, lower = 0, upper = 1)
 
-  control$multipoint.multicrit.pm.eta = coalesce(multicrit.pm.eta, control$multipoint.multicrit.pm.eta, 15)
-  assertNumber(control$multipoint.multicrit.pm.eta, na.ok = FALSE, lower = 0)
+  control$multipoint.moimbo.pm.eta = coalesce(moimbo.pm.eta, control$multipoint.moimbo.pm.eta, 15)
+  assertNumber(control$multipoint.moimbo.pm.eta, na.ok = FALSE, lower = 0)
 
-  control$multipoint.multicrit.pm.p = coalesce(multicrit.pm.p, control$multipoint.multicrit.pm.p, 1)
-  assertNumber(control$multipoint.multicrit.pm.p, na.ok = FALSE, lower = 0, upper = 1)
+  control$multipoint.moimbo.pm.p = coalesce(moimbo.pm.p, control$multipoint.moimbo.pm.p, 1)
+  assertNumber(control$multipoint.moimbo.pm.p, na.ok = FALSE, lower = 0, upper = 1)
 
   return(control)
 }
diff --git a/inst/examples/ex_1d_numeric_multipoint.R b/inst/examples/ex_1d_numeric_multipoint.R
@@ -19,10 +19,10 @@ ctrl = setMBOControlTermination(ctrl, iters = 10L)
 
 ctrl = setMBOControlMultiPoint(
 	ctrl,
-  	method = "multicrit",
-  	multicrit.objective = "ei.dist",
-  	multicrit.dist = "nearest.neighbor",
-  	multicrit.maxit = 200L
+  method = "moimbo",
+  moimbo.objective = "ei.dist",
+  moimbo.dist = "nearest.neighbor",
+  moimbo.maxit = 200L
 )
 
 lrn = makeLearner("regr.km", predict.type = "se", covtype = "matern3_2")
diff --git a/inst/examples/ex_2d_numeric_multipoint.R b/inst/examples/ex_2d_numeric_multipoint.R
@@ -12,10 +12,10 @@ obj.fun = makeBraninFunction()
 ctrl = makeMBOControl(propose.points = 5L)
 ctrl = setMBOControlTermination(ctrl, iters = 10L)
 ctrl = setMBOControlMultiPoint(ctrl,
-  method = "multicrit",
-  multicrit.objective = "ei.dist",
-  multicrit.dist = "nearest.neighbor",
-  multicrit.maxit = 200L
+  method = "moimbo",
+  moimbo.objective = "ei.dist",
+  moimbo.dist = "nearest.neighbor",
+  moimbo.maxit = 200L
 )
 
 lrn = makeLearner("regr.km", predict.type = "se", covtype = "matern3_2")
diff --git a/tests/testthat/test_exampleRun.R b/tests/testthat/test_exampleRun.R
@@ -81,10 +81,10 @@ test_that("renderExampleRunPlot produces list of ggplot2 objects", {
   ctrl = makeMBOControl(propose.points = 3)
   ctrl = setMBOControlTermination(ctrl, iters = n.iters)
   ctrl = setMBOControlMultiPoint(ctrl,
-    method = "multicrit",
-    multicrit.objective = "ei.dist",
-    multicrit.dist = "nearest.neighbor",
-    multicrit.maxit = 200L
+    method = "moimbo",
+    moimbo.objective = "ei.dist",
+    moimbo.dist = "nearest.neighbor",
+    moimbo.maxit = 200L
   )
 
   run = exampleRun(obj.fun, learner = default.kriging, control = ctrl, points.per.dim = 50L)
diff --git a/tests/testthat/test_multipoint_multicrit.R b/tests/testthat/test_multipoint_multicrit.R
@@ -13,11 +13,11 @@ test_that("multipoint multicrit", {
         ctrl = makeMBOControl(propose.points = 4L)
         ctrl = setMBOControlTermination(ctrl, iters = 1L)
         ctrl = setMBOControlMultiPoint(ctrl,
-          method = "multicrit",
-          multicrit.objective = obj,
-          multicrit.dist = dist,
-          multicrit.sel = sel,
-          multicrit.maxit = 30L
+          method = "moimbo",
+          moimbo.objective = obj,
+          moimbo.dist = dist,
+          moimbo.sel = sel,
+          moimbo.maxit = 30L
         )
 
         res = mbo(f, des, learner = default.kriging, control = ctrl)

Original file line number	Diff line number	Diff line change
`@@ -6,5 +6,5 @@`
`6`	`6`	`#' @return [\code{character}]`
`7`	`7`	`#' @export`
`8`	`8`	`getSupportedMultipointInfillOptFunctions = function() {`
`9`		`- c("cl", "cb", "multicrit")`
	`9`	`+ c("cl", "cb", "moimbo")`
`10`	`10`	`}`
Original file line number	Diff line number	Diff line change
`@@ -28,7 +28,7 @@ proposePoints.OptState = function(opt.state){`
`28`	`28`	`res = proposePointsParallelCB(opt.state)`
`29`	`29`	`else if (control$multipoint.method == "cl")`
`30`	`30`	`res = proposePointsConstantLiar(opt.state)`
`31`		`- else if (control$multipoint.method == "multicrit") {`
	`31`	`+ else if (control$multipoint.method == "moimbo") {`
`32`	`32`	`res = proposePointsMOIMBO(opt.state)`
`33`	`33`	`}`
`34`	`34`	`}`