test_that("Regular solution is accurate",{
  data(Ericactree)
  controlsolution <- AssessMonophyly(Ericactree)
  #  test solution object
  expect_equal(length(controlsolution[[1]]), 7)
	expect_is(controlsolution, "list")
  # Test summary table
  expect_equal(dim(controlsolution[[1]]$summary)[1], 6)
  expect_equal(dim(controlsolution[[1]]$summary)[2], 2)
  #  Test summary entries
  expect_equal(as.numeric(controlsolution[[1]]$summary[1,1]), 32)
  expect_equal(as.numeric(controlsolution[[1]]$summary[2,1]), 9)
  expect_equal(as.numeric(controlsolution[[1]]$summary[3,1]), 6)
  expect_equal(as.numeric(controlsolution[[1]]$summary[4,1]), 17)
  expect_equal(as.numeric(controlsolution[[1]]$summary[5,1]), 7)
  expect_equal(as.numeric(controlsolution[[1]]$summary[6,1]), 1)
  expect_equal(as.numeric(controlsolution[[1]]$summary[1,2]), 77)
  expect_equal(as.numeric(controlsolution[[1]]$summary[2,2]), 25)
  expect_equal(as.numeric(controlsolution[[1]]$summary[3,2]), 35)
  expect_equal(as.numeric(controlsolution[[1]]$summary[4,2]), 17)
  expect_equal(as.numeric(controlsolution[[1]]$summary[5,2]), 11)
  expect_equal(as.numeric(controlsolution[[1]]$summary[6,2]), 2)
  #  Test result table
  expect_equal(dim(controlsolution[[1]]$result)[1], 32)
  expect_equal(dim(controlsolution[[1]]$result)[2], 8)
  #  Test lenghts of taxa and tip lists
  expect_equal(length(controlsolution[[1]]$IntruderTaxa), 6)
  expect_equal(length(controlsolution[[1]]$IntruderTips), 6)
  expect_equal(length(controlsolution[[1]]$OutlierTaxa), 1)
  expect_equal(length(controlsolution[[1]]$OutlierTips), 1)
  #  Test Tipstates
  expect_equal(dim(controlsolution[[1]]$TipStates)[1], 77)
  expect_equal(dim(controlsolution[[1]]$TipStates)[2], 3)
})

test_that("Multifurcating solution1 is accurate",{
  data(Ericactree)
  library(paleotree)
  multifurcEric1 <- collapseNodes(Ericactree, nodeID = c(150:153), collapseType="forward", leave.zlb=FALSE)
  solution1 <- AssessMonophyly(multifurcEric1)
  #  test solution object
  expect_equal(length(solution1[[1]]), 7)
	expect_is(solution1, "list")
  # Test summary table
  expect_equal(dim(solution1[[1]]$summary)[1], 6)
  expect_equal(dim(solution1[[1]]$summary)[2], 2)
  #  Test summary entries
  expect_equal(as.numeric(solution1[[1]]$summary[1,1]), 32)
  expect_equal(as.numeric(solution1[[1]]$summary[2,1]), 9)
  expect_equal(as.numeric(solution1[[1]]$summary[3,1]), 6)
  expect_equal(as.numeric(solution1[[1]]$summary[4,1]), 17)
  expect_equal(as.numeric(solution1[[1]]$summary[5,1]), 7)
  expect_equal(as.numeric(solution1[[1]]$summary[6,1]), 1)
  expect_equal(as.numeric(solution1[[1]]$summary[1,2]), 77)
  expect_equal(as.numeric(solution1[[1]]$summary[2,2]), 25)
  expect_equal(as.numeric(solution1[[1]]$summary[3,2]), 35)
  expect_equal(as.numeric(solution1[[1]]$summary[4,2]), 17)
  expect_equal(as.numeric(solution1[[1]]$summary[5,2]), 11)
  expect_equal(as.numeric(solution1[[1]]$summary[6,2]), 2)
  #  Test result table
  expect_equal(dim(solution1[[1]]$result)[1], 32)
  expect_equal(dim(solution1[[1]]$result)[2], 8)
  #  Test lenghts of taxa and tip lists
  expect_equal(length(solution1[[1]]$IntruderTaxa), 6)
  expect_equal(length(solution1[[1]]$IntruderTips), 6)
  expect_equal(length(solution1[[1]]$OutlierTaxa), 1)
  expect_equal(length(solution1[[1]]$OutlierTips), 1)
  #  Test Tipstates
  expect_equal(dim(solution1[[1]]$TipStates)[1], 77)
  expect_equal(dim(solution1[[1]]$TipStates)[2], 3)
})

test_that("Multifurcating solution2 is accurate",{
  data(Ericactree)
  library(paleotree)
  multifurcEric2 <- collapseNodes(Ericactree, nodeID = c(100), collapseType="forward", leave.zlb=FALSE)
  solution2 <- AssessMonophyly(multifurcEric2)
  #  test solution object
  expect_equal(length(solution2[[1]]), 7)
	expect_is(solution2, "list")
  # Test summary table
  expect_equal(dim(solution2[[1]]$summary)[1], 6)
  expect_equal(dim(solution2[[1]]$summary)[2], 2)
  #  Test summary entries
  expect_equal(as.numeric(solution2[[1]]$summary[1,1]), 32)
  expect_equal(as.numeric(solution2[[1]]$summary[2,1]), 8)
  expect_equal(as.numeric(solution2[[1]]$summary[3,1]), 7)
  expect_equal(as.numeric(solution2[[1]]$summary[4,1]), 17)
  expect_equal(as.numeric(solution2[[1]]$summary[5,1]), 8)
  expect_equal(as.numeric(solution2[[1]]$summary[6,1]), 1)
  expect_equal(as.numeric(solution2[[1]]$summary[1,2]), 77)
  expect_equal(as.numeric(solution2[[1]]$summary[2,2]), 23)
  expect_equal(as.numeric(solution2[[1]]$summary[3,2]), 37)
  expect_equal(as.numeric(solution2[[1]]$summary[4,2]), 17)
  expect_equal(as.numeric(solution2[[1]]$summary[5,2]), 12)
  expect_equal(as.numeric(solution2[[1]]$summary[6,2]), 2)
  #  Test result table
  expect_equal(dim(solution2[[1]]$result)[1], 32)
  expect_equal(dim(solution2[[1]]$result)[2], 8)
  #  Test lenghts of taxa and tip lists
  expect_equal(length(solution2[[1]]$IntruderTaxa), 7)
  expect_equal(length(solution2[[1]]$IntruderTips), 7)
  expect_equal(length(solution2[[1]]$OutlierTaxa), 1)
  expect_equal(length(solution2[[1]]$OutlierTips), 1)
  #  Test Tipstates
  expect_equal(dim(solution2[[1]]$TipStates)[1], 77)
  expect_equal(dim(solution2[[1]]$TipStates)[2], 3)
})

test_that("Multifurcating solution3 is accurate",{
  data(Ericactree)
  library(paleotree)
  multifurcEric3 <- collapseNodes(Ericactree, nodeID = c(139:140, 143:145), collapseType="forward", leave.zlb=FALSE)
  solution3 <- AssessMonophyly(multifurcEric3)
  #  test solution object
  expect_equal(length(solution3[[1]]), 7)
	expect_is(solution3, "list")
  # Test summary table
  expect_equal(dim(solution3[[1]]$summary)[1], 6)
  expect_equal(dim(solution3[[1]]$summary)[2], 2)
  #  Test summary entries
  expect_equal(as.numeric(solution3[[1]]$summary[1,1]), 32)
  expect_equal(as.numeric(solution3[[1]]$summary[2,1]), 9)
  expect_equal(as.numeric(solution3[[1]]$summary[3,1]), 6)
  expect_equal(as.numeric(solution3[[1]]$summary[4,1]), 17)
  expect_equal(as.numeric(solution3[[1]]$summary[5,1]), 9)
  expect_equal(as.numeric(solution3[[1]]$summary[6,1]), 1)
  expect_equal(as.numeric(solution3[[1]]$summary[1,2]), 77)
  expect_equal(as.numeric(solution3[[1]]$summary[2,2]), 25)
  expect_equal(as.numeric(solution3[[1]]$summary[3,2]), 35)
  expect_equal(as.numeric(solution3[[1]]$summary[4,2]), 17)
  expect_equal(as.numeric(solution3[[1]]$summary[5,2]), 13)
  expect_equal(as.numeric(solution3[[1]]$summary[6,2]), 2)
  #  Test result table
  expect_equal(dim(solution3[[1]]$result)[1], 32)
  expect_equal(dim(solution3[[1]]$result)[2], 8)
  #  Test lenghts of taxa and tip lists
  expect_equal(length(solution3[[1]]$IntruderTaxa), 6)
  expect_equal(length(solution3[[1]]$IntruderTips), 6)
  expect_equal(length(solution3[[1]]$OutlierTaxa), 1)
  expect_equal(length(solution3[[1]]$OutlierTips), 1)
  #  Test Tipstates
  expect_equal(dim(solution3[[1]]$TipStates)[1], 77)
  expect_equal(dim(solution3[[1]]$TipStates)[2], 3)
})