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",
...
)Nothing
[data.frame]
Data.frame with columns at least obj.cols, “prob” and “algorithm”.
[character(>= 3)]
Column names of the objective functions.
Default is c("f1", "f2", "f3").
[integer(1)]
Maximum number of plots to be displayed side by side in a row.
Default is 4.
[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.
Other EMOA performance assessment tools:
approximateNadirPoint(),
approximateRefPoints(),
approximateRefSets(),
computeDominanceRanking(),
emoaIndEps(),
makeEMOAIndicator(),
niceCellFormater(),
normalize(),
plotDistribution(),
plotFront(),
plotScatter2d(),
toLatex()