add possibility to visualize optimization process of numeric functions

DESCRIPTION

@@ -18,12 +18,12 @@ License: BSD_2_clause + file LICENSE
 Depends:
     ParamHelpers (>= 1.3),
     BBmisc (>= 1.6),
-    smoof
+    smoof (>= 1.0),
+    ggplot2 (>= 1.0.0)
 Imports:
-    ggplot2,
     checkmate (>= 1.1),
     parallelMap (>= 1.1),
     reshape2 (>= 1.4.1),
     gridExtra (>= 0.9.1)
 Suggests:
-    testthat
+    testthat (>= 0.9.1)

NAMESPACE

@@ -1,5 +1,6 @@
 # Generated by roxygen2 (4.1.0): do not edit by hand
 
+S3method(autoplot,ecr_result)
 S3method(getOperatorCheckFunction,ecr_operator)
 S3method(getOperatorDefaultParameters,ecr_operator)
 S3method(getOperatorName,ecr_operator)
@@ -36,7 +37,7 @@ import(BBmisc)
 import(ParamHelpers)
 import(checkmate)
 import(ggplot2)
+import(gridExtra)
 import(parallelMap)
 import(reshape2)
 import(smoof)
-importFrom(gridExtra,arrangeGrob)

R/autoplotECRResult.R

@@ -1,52 +1,62 @@
 #' Plot optimization trace.
 #'
+#' Call this function on the result object of an \code{\link{ecr}} function call
+#' to visualize the optimization trace.
+#'
 #' @param object [\code{ecr_result}]\cr
 #'   ecr result object.
 #' @param xlim [\code{numeric(2)} | NULL]\cr
 #'   Lower and upper bound for generation. If \code{NULL}, this is set automatically.
 #' @param ylim [\code{numeric(2)} | NULL]\cr
 #'   Lower and upper bound for fitness. If \code{NULL}, this is set automatically.
+#' @param show.process [\code{logical(1)}]\cr
+#'   Should the function itself with the population be plotted as well? Default is
+#'   \code{FALSE}.
 #' @param log.fitness [\code{logical(1)}]\cr
 #'   Log-transform fitness values? Default is \code{FALSE}.
 #' @param ... [any]\cr
 #'   Not used.
-#' @return [\code{\link[ggplot2]{ggplot}}]
-# @export
+#' @return Nothing.
+#' @export
 autoplot.ecr_result = function(object, xlim = NULL, ylim = NULL, show.process = FALSE, log.fitness = FALSE, ...) {
   assertFlag(show.process, na.ok = FALSE)
   obj.fun = object$objective.fun
   n.params = getNumberOfParameters(obj.fun)
 
-  if (show.process) {
-    if (n.params > 2L || isMultiobjective(obj.fun)) {
-      stopf("Visualization not possible for multi-objective functions or function with greater than 2 parameters.")
-    }
-    pl.fun = autoplot(obj.fun)
-    if (length(object$control$save.population.at)) {
-      population = object$population.storage[["0"]]
+  op = as.data.frame(object$opt.path)
+  unique.dobs = unique(op$dob)
+  # we start with the second dob, since otherwise there is not enough info to plot
+  for (dob in unique.dobs[2:length(unique.dobs)]) {
+    pl.trace = plotTrace(op[which(op$dob <= dob), ], xlim, ylim, log.fitness, ...)
+    pl.trace = pl.trace + ggtitle(sprintf("Optimization trace for function '%s'", getName(object$objective.fun)))
+    if (show.process) {
+      if (n.params > 2L || isMultiobjective(obj.fun)) {
+        stopf("Visualization not possible for multi-objective functions or functions with greater than 2 parameters.")
+      }
+      if (!length(object$control$save.population.at)) {
+        stopf("Cannot visualize population since no population was stored! Take a glance a the 'save.population.at' control parameter.")
+      }
+      pl.fun = autoplot(obj.fun)
+      population = object$population.storage[[as.character(dob)]]
       df.points = data.frame(x = population$individuals, y = population$fitness)
-      pl.fun = pl.fun + geom_point(data = df.points, aes(x = x, y = y), colour = "tomato")
+      pl.fun = pl.fun + geom_point(data = df.points, aes_string(x = "x", y = "y"), colour = "tomato")
       pl.fun = pl.fun + geom_hline(yintercept = min(population$fitness), linetype = "dashed", colour = "gray")
     }
+    if (show.process) {
+      #FIXME: this seems to fail!
+      BBmisc::requirePackages(c("grid", "gridExtra"), why = "ecr")
+      pl = do.call(gridExtra::arrangeGrob, list(pl.fun, pl.trace, ncol = 1))
+    } else {
+      pl = pl.trace
+    }
+    pause()
+    print(pl)
   }
-
-  pl.trace = autoplot(object$opt.path, xlim, ylim, log.fitness, ...)
-  pl.trace = pl.trace + ggtitle(sprintf("Optimization trace for function '%s'", getName(object$objective.fun)))
-
-  if (show.process) {
-    requirePackages("gridExtra", why = "ecr")
-    pl = do.call(arrangeGrob, list(pl.fun, pl.trace, ncol = 1))
-  } else {
-    pl = pl.trace
-  }
-  return (pl)
 }
 
 # autoplot function for opt.path used by ecr
-autoplot.OptPath = function(object, xlim, ylim, log.fitness, ...) {
-  ggdf = as.data.frame(object)
-  ggdf = ggdf[c("dob", "pop.min.fitness", "pop.mean.fitness", "pop.median.fitness", "pop.max.fitness")]
-
+plotTrace = function(df, xlim, ylim, log.fitness, ...) {
+  ggdf = df[c("dob", "pop.min.fitness", "pop.mean.fitness", "pop.median.fitness", "pop.max.fitness")]
   xlim = BBmisc::coalesce(xlim, c(0, max(ggdf$dob)))
   ylim = BBmisc::coalesce(ylim, c(0, max(ggdf$pop.max.fitness)))
   assertNumeric(ylim, len = 2L, any.missing = FALSE)
@@ -69,4 +79,4 @@ autoplot.OptPath = function(object, xlim, ylim, log.fitness, ...) {
   }
 
   return(pl)
-}
+}

R/zzz.R

@@ -5,5 +5,5 @@
 #' @import checkmate
 #' @import parallelMap
 #' @import reshape2
-#' @importFrom gridExtra arrangeGrob
+#' @import gridExtra
 NULL

man/autoplot.ecr_result.Rd

@@ -17,16 +17,21 @@ Lower and upper bound for generation. If \code{NULL}, this is set automatically.
 \item{ylim}{[\code{numeric(2)} | NULL]\cr
 Lower and upper bound for fitness. If \code{NULL}, this is set automatically.}
 
+\item{show.process}{[\code{logical(1)}]\cr
+Should the function itself with the population be plotted as well? Default is
+\code{FALSE}.}
+
 \item{log.fitness}{[\code{logical(1)}]\cr
 Log-transform fitness values? Default is \code{FALSE}.}
 
 \item{...}{[any]\cr
 Not used.}
 }
 \value{
-[\code{\link[ggplot2]{ggplot}}]
+Nothing.
 }
 \description{
-Plot optimization trace.
+Call this function on the result object of an \code{\link{ecr}} function call
+to visualize the optimization trace.
 }