selectors now know if they are specified for single- or multi-objecti…

…ve funs

R/doTheEvolution.R

@@ -51,6 +51,16 @@ doTheEvolution = function(objective.fun, control) {
     par.set = makeParamSet(makeNumericParam("dummy", lower = 0, upper = 1))
   }
 
+  # check compatibility of selectors and #objectives
+  selectors = c(control$parent.selector, control$survival.selector)
+  desired.tag = if (n.objectives == 1L) "single-objective" else "multi-objective"
+  lapply(selectors, function(selector) {
+    if (desired.tag %nin% attr(selector, "supported.objectives")) {
+      stopf("Selector '%s' cannot be applied to problem with %i objectives.",
+        getOperatorName(selector), n.objectives)
+    }
+  })
+
   y.names = paste0("y", seq(n.objectives))
 
   n.population = control$n.population

R/getSupportedRepresentations.R → R/getOperatorsTags.R

@@ -1,7 +1,4 @@
-#' Returns the representations which a specific operator supports.
-#'
-#' Operators and representation types are not mandatory compatible. This function
-#' detemines the types an operator can operate on.
+#' Returns the character vector of tags which describe a specific operator.
 #'
 #' @param operator [\code{ecr_operator}]\cr
 #'   Operator object.

R/makeSelector.R

@@ -10,12 +10,19 @@
 # @param supported [\code{character}]\cr
 #   Vector of strings/names of supported parameter representations. For example
 #   'permutation', 'float', 'binary'.
+# @param supported.objectives [\code{character}]\cr
+#   At least one of \dQuote{single-objective} or \dQuote{multi-objective}.
 # @return [\code{ecr_selector}]
 #   selector object.
-makeSelector = function(selector, name, description,
-  supported = getAvailableRepresentations()) {
+makeSelector = function(
+  selector,
+  name, description,
+  supported = getAvailableRepresentations(),
+  supported.objectives) {
   assertFunction(selector, args = c("population", "n.select", "control"), ordered = TRUE)
+  assertSubset(supported.objectives, c("single-objective", "multi-objective"))
   selector = makeOperator(selector, name, description, supported)
+  selector = setAttribute(selector, "supported.objectives", supported.objectives)
   selector = addClasses(selector, c("ecr_selector"))
   return(selector)
 }

R/selector.greedy.R

@@ -15,6 +15,7 @@ makeGreedySelector = function() {
   makeSelector(
     selector = selector,
     name = "Greedy selector",
-    description = "Return the best individuals regarding the fitness value."
+    description = "Return the best individuals regarding the fitness value.",
+    supported.objectives = c("single-objective")
   )
 }

R/selector.k-tournament.R

@@ -31,6 +31,7 @@ makeTournamentSelector = function(k = 3L) {
   makeSelector(
     selector = selector,
     name = "k-Tournament selector",
-    description = "Select k individuals at random, choose the best, repeat until mating pool is filled."
+    description = "Select k individuals at random, choose the best, repeat until mating pool is filled.",
+    supported.objectives = c("single-objective")
   )
 }

R/selector.roulettewheel.R

@@ -32,6 +32,7 @@ makeRouletteWheelSelector = function() {
   makeSelector(
     selector = selector,
     name = "Roulette-Wheel selector",
-    description = "Selects individuals in a fitness-proportional fashion."
+    description = "Selects individuals in a fitness-proportional fashion.",
+    supported.objectives = c("single-objective")
   )
 }

R/selector.simple.R

@@ -17,6 +17,7 @@ makeSimpleSelector = function() {
   makeSelector(
     selector = selector,
     name = "Simple selector",
-    description = "Simply returns the entire population."
+    description = "Simply returns the entire population.",
+    supported.objectives = c("single-objective", "multi-objective")
   )
 }

R/setupECRControl.R

@@ -100,7 +100,7 @@ setupECRControl = function(
     representation = representation,
     survival.strategy = survival.strategy,
     n.elite = n.elite,
-    n.targets = NULL, # we set this by hand here
+    #n.targets = n.targets,
     save.population.at = save.population.at,
     target.name = target.name,
     stopping.conditions = stopping.conditions,

inst/examples/sms_emoa_example.R

@@ -1,14 +1,23 @@
 library(smoof)
 library(ecr)
 
+# THIS FILE IS WORK-IN-PROGRESS/EXPERIMENAL
+
+# COLLECTION OF FIXME
+#FIXME: integrate NondominatedSetSelector as ecr_selector
+#FIXME: we need to check in setupECRControl or in ecr if the operators can work
+# on multi-objective stuff
+#
+
 # Get set of dominated individuals.
 #
 # @param x [list]
 #   Set of 2D fitness values.
 # @param fn [function]
 #   Fitness function.
 # @return [list]
-#FIXME: formulate this for matrices where each column describes one vector
+#FIXME: formulate this for matrices where each column describes one vector. However,
+# this is just a naive imolementation for testing purpose. Will be replaced
 getDominatedSet = function(x) {
   n = length(x)
 
@@ -44,41 +53,38 @@ makeNondominatedSetSelector = function() {
       survive.idx = setdiff(seq(n), idx)
       return(makePopulation(inds[survive.idx], population$fitness[, survive.idx, drop = FALSE]))
     },
-    supported = "float",
+    supported.objectives = "multi-objective",
     name = "Nondominated set selector",
     description = "description"
   )
 }
 
 ctrl = setupECRControl(
-  n.population = 10L,
-  n.offspring = 1L,
+  n.population = 20L,
+  n.offspring = 10L,
   representation = "float",
   monitor = makeConsoleMonitor()
 )
 
 ctrl = setupEvolutionaryOperators(
   ctrl,
+  # tournamend and roulette wheel work on scalar fitness values only
+  # Thus, simply select two random elements for reproduction
   parent.selector = makeSimpleSelector(),
   mutator = makeGaussMutator(),
   recombinator = makeCrossoverRecombinator(),
+  # everything can be used, we just needed a multi-objective-specific survival selector
   survivalSelector = makeNondominatedSetSelector()
 )
 
 obj.fn = smoof::makeZDT1Function(2L)
 
 res = doTheEvolution(obj.fn, ctrl)
-stop("FIN")
-
-
-# Determine the number of elements for each individual by which it is dominated.
-#
-# @param x [list]
-#   Set of fitness values.
-# @return [integer]
-#   Each position contains the number of individuals by which this one is dominated.
-#getDominanceNumber = function()
-inds = list(c(1, 2), c(2, 1), c(2, 2), c(1, 3), c(1.5, 1.3))
-
-print(getDominatedSet(inds))
 
+pl = smoof::visualizeParetoOptimalFront(obj.fn)
+pf = res$pareto.front
+pf = as.data.frame(t(pf))
+names(pf) = paste0("x", 1:2)
+pl = pl + geom_point(data = pf, aes(x = x1, y = x2), colour = "green")
+print(pl)
+stop("FIN")

man/getSupportedRepresentations.Rd

@@ -1,8 +1,8 @@
 % Generated by roxygen2 (4.1.0): do not edit by hand
-% Please edit documentation in R/getSupportedRepresentations.R
+% Please edit documentation in R/getOperatorsTags.R
 \name{getSupportedRepresentations}
 \alias{getSupportedRepresentations}
-\title{Returns the representations which a specific operator supports.}
+\title{Returns the character vector of tags which describe a specific operator.}
 \usage{
 getSupportedRepresentations(operator)
 }
@@ -15,7 +15,6 @@ Operator object.}
   Vector of representation types.
 }
 \description{
-Operators and representation types are not mandatory compatible. This function
-detemines the types an operator can operate on.
+Returns the character vector of tags which describe a specific operator.
 }