symdevplot: Plot the symmetric deviation function.

In mooplot: Graphical Visualizations for Multi-Objective Optimization

Plot the symmetric deviation function.

Description

The symmetric deviation function is the probability for a given target in the objective space to belong to the symmetric difference between the Vorob'ev expectation and a realization of the (random) attained set.

Usage

symdevplot(
  x,
  sets,
  VE,
  threshold,
  nlevels = 11,
  ve.col = "blue",
  xlim = NULL,
  ylim = NULL,
  legend.pos = "topright",
  main = "Symmetric deviation function",
  col.fun = function(n) gray(seq(0, 0.9, length.out = n)^2)
)

Arguments

x	matrix()|data.frame() Matrix or data frame of numerical values, where each row gives the coordinates of a point. If sets is missing, the last column of x gives the sets.
sets	integer() A vector that indicates the set of each point in x. If missing, the last column of x is used instead.
VE, threshold	Vorob'ev expectation and threshold, e.g., as returned by moocore::vorobT().
nlevels	(integer(1)) Number of levels in which is divided the range of the symmetric deviation.
ve.col	Plotting parameters for the Vorob'ev expectation.
xlim, ylim, main	Graphical parameters, see plot.default().
legend.pos	The position of the legend, see legend(). A value of "none" hides the legend.
col.fun	Function that creates a vector of n colors, see heat.colors().

Value

No return value, called for side effects

Author(s)

Mickael Binois

References

\insertRef

BinGinRou2015gauparmoocore

C. Chevalier (2013), Fast uncertainty reduction strategies relying on Gaussian process models, University of Bern, PhD thesis.

\insertRef

Molchanov2005theorymoocore

See Also

moocore::vorobT() moocore::vorobDev() eafplot()

Examples

data(CPFs, package = "moocore")
res <- moocore::vorobT(CPFs, reference = c(2, 200))
print(res$threshold)

## Display Vorob'ev expectation and attainment function
# First style
eafplot(CPFs[,1:2], sets = CPFs[,3], percentiles = c(0, 25, 50, 75, 100, res$threshold),
        main = substitute(paste("Empirical attainment function, ",beta,"* = ", a, "%"),
                          list(a = formatC(res$threshold, digits = 2, format = "f"))))

# Second style
eafplot(CPFs[,1:2], sets = CPFs[,3], percentiles = c(0, 20, 40, 60, 80, 100),
        col = gray(seq(0.8, 0.1, length.out = 6)^0.5), type = "area",
        legend.pos = "bottomleft", extra.points = res$VE, extra.col = "cyan",
        extra.legend = "VE", extra.lty = "solid", extra.pch = NA, extra.lwd = 2,
        main = substitute(paste("Empirical attainment function, ",beta,"* = ", a, "%"),
                          list(a = formatC(res$threshold, digits = 2, format = "f"))))
# Vorob'ev deviation
VD <- moocore::vorobDev(CPFs, reference = c(2, 200), VE = res$VE)
# Display the symmetric deviation function.
symdevplot(CPFs, VE = res$VE, threshold = res$threshold, nlevels = 11)
# Levels are adjusted automatically if too large.
symdevplot(CPFs, VE = res$VE, threshold = res$threshold, nlevels = 200, legend.pos = "none")

# Use a different palette.
symdevplot(CPFs, VE = res$VE, threshold = res$threshold, nlevels = 11, col.fun = heat.colors)

mooplot documentation built on April 4, 2025, 1:50 a.m.