source("helper-common.R") test_that("eafplot", { skip_on_cran() pdf(file = "eafplot.pdf", title = "eafplot.pdf", width = 9, height = 6) ## FIXME: Add main=invokation ## FIXME: We need smaller data! eaftest <- function(a, b, maximise = c(FALSE, FALSE)) { A1 <- read_datasets(file.path(system.file(package="eaf"), "extdata", a)) A2 <- read_datasets(file.path(system.file(package="eaf"), "extdata", b)) if (!any(maximise)) { # FIXME: Colors are wrong eafplot(A1, type = "area", legend.pos = "bottomleft") eafplot(A1, type = "point") eafplot(A1, type = "point", pch = 20) # FIXME: This doesn't plot anything useful. eafplot(list(A1 = A1, A2 = A2), type = "area", legend.pos = "bottomleft") eafplot(list(A1 = A1, A2 = A2), type = "point") eafplot(list(A1 = A1, A2 = A2), type = "point", pch = 20) } else { A1m <- A1; A1m[, which(maximise)] <- -A1m[, which(maximise)] A2m <- A2; A2m[, which(maximise)] <- -A2m[, which(maximise)] # FIXME: Colors are wrong eafplot(A1m, type = "area", maximise = maximise, legend.pos = "bottomleft") eafplot(A1m, type = "point", maximise = maximise) eafplot(A1m, type = "point", pch = 20, maximise = maximise) eafplot(list(A1m = A1m, A2m = A2m), type = "area", maximise = maximise, legend.pos = "bottomleft") eafplot(list(A1m = A1m, A2m = A2m), type = "point", maximise = maximise) eafplot(list(A1m = A1m, A2m = A2m), type = "point", pch = 20, maximise = maximise) } return(TRUE) } expect_true(eaftest("wrots_l10w100_dat", "wrots_l100w10_dat")) expect_true(eaftest("tpls", "rest")) expect_true(eaftest("ALG_1_dat.xz", "ALG_2_dat.xz")) expect_true(eaftest("ALG_1_dat.xz", "ALG_2_dat.xz", maximise = c(TRUE, FALSE))) expect_true(eaftest("ALG_1_dat.xz", "ALG_2_dat.xz", maximise = c(FALSE, TRUE))) expect_true(eaftest("ALG_1_dat.xz", "ALG_2_dat.xz", maximise = c(TRUE, TRUE))) dev.off() }) data(HybridGA) test_that("eafplot SPEA2relativeVanzyl", { skip_on_cran() data(SPEA2relativeVanzyl) expect_snapshot_plot("SPEA2relativeVanzyl", { eafplot(SPEA2relativeVanzyl, percentiles = c(25, 50, 75), xlab = expression(C[E]), ylab = "Total switches", xlim = c(320, 400), extra.points = HybridGA$vanzyl, extra.legend = "Hybrid GA") }) expect_snapshot_plot("SPEA2relativeVanzyl-extra_points", { eafplot(SPEA2relativeVanzyl, percentiles = c(25, 50, 75), xlab = expression(C[E]), ylab = "Total switches", xlim = c(320, 400), extra.points = HybridGA$vanzyl, extra.legend = "Hybrid GA") }) }) test_that("eafplot SPEA2relativeRichmond", { skip_on_cran() data(SPEA2relativeRichmond) expect_snapshot_plot("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$richmond, extra.lty = "dashed", extra.legend = "Hybrid GA") }) expect_snapshot_plot("SPEA2relativeRichmond-extra_points", { eafplot(SPEA2relativeRichmond, percentiles = c(25, 50, 75), xlab = expression(C[E]), ylab = "Total switches", xlim = c(90, 140), ylim = c(0, 25), extra.points = HybridGA$richmond, extra.lty = "dashed", extra.legend = "Hybrid GA") }) }) test_that("eafplot SPEA2minstoptimeRichmond", { skip_on_cran() data(SPEA2minstoptimeRichmond) SPEA2minstoptimeRichmond[,2] <- SPEA2minstoptimeRichmond[,2] / 60 expect_snapshot_plot("SPEA2minstoptimeRichmond", { eafplot (SPEA2minstoptimeRichmond, xlab = expression(C[E]), ylab = "Minimum idle time (minutes)", las = 1, log = "y", maximise = c(FALSE, TRUE), main = "SPEA2 (Richmond)") }) expect_snapshot_plot("SPEA2minstoptimeRichmond-extra_points", { eafplot(SPEA2minstoptimeRichmond, xlab = expression(C[E]), ylab = "Minimum idle time (minutes)", las = 1, log = "y", maximise = c(FALSE, TRUE), main = "SPEA2 (Richmond)") }) })