generate_data.EAF_diff_Approximate {IOHanalyzer}

Generate EAF-differences between each function and the remaining portfolio

Description

This is an approximation of “, since the number of required polygons can quickly become problematic for plotly. This function uses discretized contour matrices instead, which trades off accuracy for scalability.

Usage

generate_data.EAF_diff_Approximate(
  dsList,
  xmin,
  xmax,
  ymin,
  ymax,
  x.log = T,
  y.log = T
)

Arguments

dsList

The DataSetList object, containing at least 2 IDs

xmin

Minimum runtime to consider

xmax

Maximum runtime to consider

ymin

Minimum f(x) to consider

ymax

Maximum f(x) to consider

x.log

Whether to scale the y-space logarithmically

y.log

Whether to scale the y-space logarithmically

Examples

generate_data.EAF_diff_Approximate(subset(dsl, funcId == 1), 1, 16, 1, 16)