Description Usage Arguments Details Value Methods (by class) See Also Examples
Computes and plots the Empirical Attainment Function, either as attainment surfaces for certain percentiles or as points.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42  eafplot(x, ...)
## Default S3 method:
eafplot(
x,
sets = NULL,
groups = NULL,
percentiles = c(0, 50, 100),
attsurfs = NULL,
xlab = NULL,
ylab = NULL,
xlim = NULL,
ylim = NULL,
log = "",
type = "point",
col = NULL,
lty = c("dashed", "solid", "solid", "solid", "dashed"),
lwd = 1.75,
pch = NA,
cex.pch = par("cex"),
las = par("las"),
legend.pos = "topright",
legend.txt = NULL,
extra.points = NULL,
extra.legend = NULL,
extra.pch = 4:25,
extra.lwd = 0.5,
extra.lty = NA,
extra.col = "black",
maximise = c(FALSE, FALSE),
xaxis.side = "below",
yaxis.side = "left",
axes = TRUE,
sci.notation = FALSE,
...
)
## S3 method for class 'formula'
eafplot(formula, data, groups = NULL, subset = NULL, ...)
## S3 method for class 'list'
eafplot(x, ...)

x 
Either a matrix of data values, or a data frame, or a list of data frames of exactly three columns. 
... 
Other graphical parameters to 
sets 
(numeric) 
groups 
This may be used to plot profiles of different algorithms on the same plot. 
percentiles 
(numeric) 
attsurfs 
TODO 
xlab, ylab, xlim, ylim, log, col, lty, lwd, pch, cex.pch, las 
Graphical
parameters, see 
type 
(character(1)) 
legend.pos 
the position of the legend, see 
legend.txt 
a character or expression vector to appear in the
legend. If 
extra.points 
A list of matrices or data.frames with
twocolumns. Each element of the list defines a set of points, or
lines if one of the columns is 
extra.legend 
A character vector providing labels for the groups of points. 
extra.pch, extra.lwd, extra.lty, extra.col 
Control the graphical aspect
of the points. See 
maximise 
( 
xaxis.side 
On which side that xaxis is drawn. Valid values are
"below" and "above". See 
yaxis.side 
On which side that yaxis is drawn. Valid values are "left"
and "right". See 
axes 
A logical value indicating whether both axes should be drawn on the plot. 
sci.notation 
Generate prettier labels 
formula 
A formula of the type: 
data 
Dataframe containing the fields mentioned in the formula and in groups. 
subset 
( 
This function can be used to plot random sets of points like those obtained by different runs of biobjective stochastic optimization algorithms. An EAF curve represents the boundary separating points that are known to be attainable (that is, dominated in Pareto sense) in at least a fraction (quantile) of the runs from those that are not. The median EAF represents the curve where the fraction of attainable points is 50%. In single objective optimization the function can be used to plot the profile of solution quality over time of a collection of runs of a stochastic optimizer.
No value is returned.
default
: Main function
formula
: Formula interface
list
: List interface for lists of data.frames or matrices
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51  data(gcp2x2)
tabucol < subset(gcp2x2, alg != "TSinN1")
tabucol$alg < tabucol$alg[drop=TRUE]
eafplot(time + best ~ run, data = tabucol, subset = tabucol$inst=="DSJC500.5")
## Not run: # These take time
eafplot(time + best ~ run  inst, groups=alg, data=gcp2x2)
eafplot(time + best ~ run  inst, groups=alg, data=gcp2x2,
percentiles=c(0,50,100), cex.axis = 1.2, lty = c(2,1,2), lwd = c(2,2,2),
col = c("black","blue","grey50"))
extdata_path < system.file(package = "eaf", "extdata")
A1 < read_datasets(file.path(extdata_path, "ALG_1_dat.xz"))
A2 < read_datasets(file.path(extdata_path, "ALG_2_dat.xz"))
eafplot(A1, percentiles = 50, sci.notation = TRUE)
eafplot(list(A1 = A1, A2 = A2), percentiles = 50)
## Save as a PDF file.
# dev.copy2pdf(file = "eaf.pdf", onefile = TRUE, width = 5, height = 4)
## End(Not run)
## Using extra.points
## Not run:
data(HybridGA)
data(SPEA2relativeVanzyl)
eafplot(SPEA2relativeVanzyl, percentiles = c(25, 50, 75),
xlab = expression(C[E]), ylab = "Total switches", xlim = c(320, 400),
extra.points = HybridGA$vanzyl, extra.legend = "Hybrid GA")
data(SPEA2relativeRichmond)
eafplot (SPEA2relativeRichmond, percentiles = c(25, 50, 75),
xlab = expression(C[E]), ylab = "Total switches",
xlim = c(90, 140), ylim = c(0, 25),
extra.points = HybridGA$richmond, extra.lty = "dashed",
extra.legend = "Hybrid GA")
eafplot (SPEA2relativeRichmond, percentiles = c(25, 50, 75),
xlab = expression(C[E]), ylab = "Total switches",
xlim = c(90, 140), ylim = c(0, 25), type = "area",
extra.points = HybridGA$richmond, extra.lty = "dashed",
extra.legend = "Hybrid GA", legend.pos = "bottomright")
data(SPEA2minstoptimeRichmond)
SPEA2minstoptimeRichmond[,2] < SPEA2minstoptimeRichmond[,2] / 60
eafplot (SPEA2minstoptimeRichmond, xlab = expression(C[E]),
ylab = "Minimum idle time (minutes)", maximise = c(FALSE, TRUE),
las = 1, log = "y", main = "SPEA2 (Richmond)",
legend.pos = "bottomright")
## End(Not run)

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