plotScatter3d function

Visualize three-objective Pareto-front approximations.

Given a data frame with the results of (multiple) runs of (multiple) different three-objective optimization algorithms on (multiple) problem instances the function generates 3D scatterplots of the obtained Pareto-front approximations.

plotScatter3d(
  df,
  obj.cols = c("f1", "f2", "f3"),
  max.in.row = 4L,
  package = "scatterplot3d",
  ...
)

Arguments

• df: [data.frame]

  Data.frame with columns at least obj.cols, prob and algorithm .

• obj.cols: [character(>= 3)]

  Column names of the objective functions. Default is c("f1", "f2", "f3").

• max.in.row: [integer(1)]

  Maximum number of plots to be displayed side by side in a row. Default is 4.

• package: [character(1L)]

  Which package to use for 3d scatterplot generation? Possible choices are scatterplot3d , plot3D , plot3Drgl

  or plotly . Default is scatterplot3d .

• ...: [any]

  Further arguments passed down to scatterplot function.

Returns

Nothing

See Also

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