plotDistribution: Plot distribution of EMOA indicators.

In ecr: Evolutionary Computation in R

Plot distribution of EMOA indicators.

Description

Visualizes of empirical distributions of unary EMOA indicator based on the results of computeIndicators.

Usage

plotDistribution(
  inds,
  plot.type = "boxplot",
  fill = "algorithm",
  facet.type = "grid",
  facet.args = list(),
  logscale = character()
)

Arguments

inds	[data.frame] Data frame with columns “algorithm”, “prob”, “repl” and one additional column per EMOA indicator.
plot.type	[character(1)] Either “boxplot” (the default) for boxplots or “violin” for violin plots.
fill	[character(1)] Variable used to fill boxplots. Default is “algorithm”.
facet.type	[character(1)] Which faceting method to use? Pass “wrap” for facet_wrap or “grid” for facet_grid. Default is “wrap”.
facet.args	[list] Named list of arguments passed down to facet_wrap or facet_grid respectively (depends on facet.type). E.g., nrow to change layout. Default is the empty list. In this case data is grouped by problem and indicator.
logscale	[character] Vector of indicator names which should be log-transformed prior to visualization. Default is the empty character vector.

Value

[ggplot]

See Also

Other EMOA performance assessment tools: approximateNadirPoint(), approximateRefPoints(), approximateRefSets(), computeDominanceRanking(), emoaIndEps(), makeEMOAIndicator(), niceCellFormater(), normalize(), plotFront(), plotScatter2d(), plotScatter3d(), toLatex()

ecr documentation built on March 31, 2023, 10:07 p.m.