eafdiffplot: Empirical attainment function differences

Description

Plot the differences between the empirical attainment functions of two data sets as a two-panel plot, where the left side shows the values of the left EAF minus the right EAF and the right side shows the differences in the other direction.

Usage

eafdiffplot(data.left, data.right, intervals = c("[0.0, 0.2)","[0.2, 0.4)","[0.4, 0.6)", "[0.6, 0.8)","[0.8, 1.0]"), col = c("#FFFFFF", "#BFBFBF","#808080","#404040","#000000"), percentiles = c(50), full.eaf = FALSE, type = "area", legend.pos = if (full.eaf) "bottomleft" else "topright", title.left = deparse(substitute(data.left)), title.right = deparse(substitute(data.right)), xlim = NULL, ylim = NULL, cex = par("cex"), cex.lab = par("cex.lab"), cex.axis = par("cex.axis"), maximise = c(FALSE, FALSE), grand.lines = TRUE, ...)

Arguments

data.left, data.right

data frames corresponding to the input data of left and right sides, respectively. Each data frame has at least three columns, the third one being the set of each point. See also read.data.sets.

intervals

a character vector that determines the levels of EAF differences that are plotted. length(intervals) defines in how many intervals the EAF differences are partitioned, whereas intervals gives the labels of each interval for the legend.

col

a character vector giving the color for each interval. There must be as many colors as intervals, that is, length(col) == length(intervals).

percentiles

the percentiles of the EAF of each side that will be plotted as attainment surfaces. NA does not plot any. See eafplot.default.

full.eaf

whether to plot the EAF of each side instead of the differences between the EAFs.

type

whether the EAF differences are plotted as points (points) or whether to color the areas that have at least a certain value (area).

legend.pos

the position of the legend. See legend.

title.left, title.right

title for left and right panels, respectively.

xlim, ylim, cex, cex.lab, cex.axis

graphical parameters, see plot.default.

maximise

whether the first and/or second objective correspond to a maximisation problem.

grand.lines

whether to plot the grand-best and grand-worst attainment surfaces.

...

other graphical parameters are passed down to plot.default.

Value

No return value.

Details

This function calculates the differences between the EAFs of two data sets, and plots on the left the differences in favour of the left data set, and on the right the differences in favour of the right data set. By default, it also plots the grand best and worst attainment surfaces, that is, the 0% and 100%-attainment surfaces over all data. This two surfaces delimit the area where differences may exist. In addition, it also plots the 50%-attainment surface of each data set. With type = "point", only the points where there is a change in the value of the EAF difference are plotted. This means that for areas where the EAF differences stays constant, the region will appear in white even if the value of the differences in that region is large. This explain "white holes" surrounded by black points.

With type = "area", the area where the EAF differences has a certain value is plotted. The idea for the algorithm to compute the areas was provided by Carlos M. Fonseca. The implementation uses R polygons, which some PDF viewers may have trouble rendering correctly (See http://cran.r-project.org/doc/FAQ/R-FAQ.html#Why-are-there-unwanted-borders). Plots (should) look correct when printed.

Large differences that appear when using type = "points" may seem to dissapear when using type = "area". The explanation is the points size is independent of the axes range, therefore, the plotted points may seem to cover a much larger area than the actual number of points. On the other hand, the areas size is plotted with respect to the objective space, without any extra borders. If the range of an area becomes smaller than one-pixel, it won't be visible. As a consequence, zooming in or out certain regions of the plots does not change the apparent size of the points, whereas it affects considerably the apparent size of the areas.

Examples

Run this code

A1 <- read.data.sets(file.path(system.file(package="eaf"), "extdata", "ALG_1_dat"))
A2 <- read.data.sets(file.path(system.file(package="eaf"), "extdata", "ALG_2_dat"))
eafdiffplot(A1, A2, type = "area")
## Not run: 
# eafdiffplot(A1, A2, type = "point")
# eafdiffplot(A1, A2, full.eaf = TRUE)
# ## End(Not run)