# eafdiffplot: Plot empirical attainment function differences In eaf: Plots of the Empirical Attainment Function

## 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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23``` ```eafdiffplot( data.left, data.right, col = c("#FFFFFF", "#808080", "#000000"), intervals = 5, 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, sci.notation = FALSE, left.panel.last = NULL, right.panel.last = NULL, ... ) ```

## 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_datasets()`. `col` A character vector of three colors for the magnitude of the differences of 0, 0.5, and 1. Intermediate colors are computed automatically given the value of `intervals`. Alternatively, a function such as `viridisLite::viridis()` that generates a colormap given an integer argument. `intervals` (`integer(1)`|`character()`) The absolute range of the differences [0, 1] is partitioned into the number of intervals provided. If an integer is provided, then labels for each interval are computed automatically. If a character vector is provided, its length is taken as the number of intervals. `percentiles` The percentiles of the EAF of each side that will be plotted as attainment surfaces. `NA` does not plot any. See `eafplot()`. `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()`. A value of `"none"` hides the 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` (`logical()` | `logical(1)`) Whether the objectives must be maximised instead of minimised. Either a single logical value that applies to all objectives or a vector of logical values, with one value per objective. `grand.lines` Whether to plot the grand-best and grand-worst attainment surfaces. `sci.notation` Generate prettier labels `left.panel.last, right.panel.last` An expression to be evaluated after plotting has taken place on each panel (left or right). This can be useful for adding points or text to either panel. Note that this works by lazy evaluation: passing this argument from other `plot` methods may well not work since it may be evaluated too early. `...` Other graphical parameters are passed down to `plot.default()`.

## 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. These 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 explains "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 https://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 = "point"` may seem to disappear 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.

## Value

No return value.

`read_datasets()`, `eafplot()`
 ``` 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``` ```## NOTE: The plots in the website look squashed because of how pkgdown ## generates them. They should look fine when you generate them yourself. extdata_dir <- system.file(package="eaf", "extdata") A1 <- read_datasets(file.path(extdata_dir, "ALG_1_dat.xz")) A2 <- read_datasets(file.path(extdata_dir, "ALG_2_dat.xz")) # These take time eafdiffplot(A1, A2, full.eaf = TRUE) if (requireNamespace("viridisLite", quietly=TRUE)) { viridis_r <- function(n) viridisLite::viridis(n, direction=-1) eafdiffplot(A1, A2, type = "area", col = viridis_r) } else { eafdiffplot(A1, A2, type = "area") } A1 <- read_datasets(file.path(extdata_dir, "wrots_l100w10_dat")) A2 <- read_datasets(file.path(extdata_dir, "wrots_l10w100_dat")) eafdiffplot(A1, A2, type = "point", sci.notation = TRUE, cex.axis=0.6) # A more complex example DIFF <- eafdiffplot(A1, A2, col = c("white", "blue", "red"), intervals = 5, type = "point", title.left=expression("W-RoTS," ~ lambda==100 * "," ~ omega==10), title.right=expression("W-RoTS," ~ lambda==10 * "," ~ omega==100), right.panel.last={ abline(a = 0, b = 1, col = "red", lty = "dashed")}) DIFF\$right[,3] <- -DIFF\$right[,3] ## Save the values to a file. # write.table(rbind(DIFF\$left,DIFF\$right), # file = "wrots_l100w10_dat-wrots_l10w100_dat-diff.txt", # quote = FALSE, row.names = FALSE, col.names = FALSE) ```