tests/testthat/test-significanceMap.R

In wiesenfa/challengeR: Analyzing assessment data of biomedical image analysis competitions and visualization of results

# Copyright (c) German Cancer Research Center (DKFZ)
# All rights reserved.
#
# This file is part of challengeR.
#
# challengeR is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later version.
#
# challengeR is distributed in the hope that it will be useful,
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# GNU General Public License for more details.
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# You should have received a copy of the GNU General Public License
# along with challengeR. If not, see <https://www.gnu.org/licenses/>.

test_that("significance map for single-task data set has no title", {
  data <- rbind(
    data.frame(algo="A1", value=0.8, case="C1"),
    data.frame(algo="A2", value=0.6, case="C1"),
    data.frame(algo="A3", value=0.4, case="C1"),
    data.frame(algo="A1", value=0.2, case="C2"),
    data.frame(algo="A2", value=0.1, case="C2"),
    data.frame(algo="A3", value=0.0, case="C2"))

  challenge <- as.challenge(data, taskName="T1", algorithm="algo", case="case", value="value", smallBetter=FALSE)

  ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")

  actualPlot <- significanceMap(ranking)
  expect_is(actualPlot, "ggplot")
  expect_equal(actualPlot$labels$title, NULL)
})

test_that("significance map for multi-task data set have titles", {
  dataTask1 <- cbind(task="T1",
                     rbind(
                       data.frame(algo="A1", value=0.8, case="C1"),
                       data.frame(algo="A2", value=0.6, case="C1"),
                       data.frame(algo="A3", value=0.4, case="C1"),
                       data.frame(algo="A1", value=0.2, case="C2"),
                       data.frame(algo="A2", value=0.1, case="C2"),
                       data.frame(algo="A3", value=0.0, case="C2")
                     ))
  dataTask2 <- cbind(task="T2",
                     rbind(
                       data.frame(algo="A1", value=0.2, case="C1"),
                       data.frame(algo="A2", value=0.3, case="C1"),
                       data.frame(algo="A3", value=0.4, case="C1"),
                       data.frame(algo="A1", value=0.7, case="C2"),
                       data.frame(algo="A2", value=0.8, case="C2"),
                       data.frame(algo="A3", value=0.9, case="C2")
                     ))

  data <- rbind(dataTask1, dataTask2)

  challenge <- as.challenge(data, by="task", algorithm="algo", case="case", value="value", smallBetter=FALSE)

  ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")

  actualPlots <- significanceMap(ranking)
  actualPlotTask1 <- actualPlots[[1]]
  actualPlotTask2 <- actualPlots[[2]]

  expect_is(actualPlotTask1, "ggplot")
  expect_equal(actualPlotTask1$labels$title, "T1")

  expect_is(actualPlotTask2, "ggplot")
  expect_equal(actualPlotTask2$labels$title, "T2")
})