Nothing
context('weighted partition')
rngReset()
refmodel = testModel2
test_that('default', {
model = lcModelWeightedPartition(testLongData, response = 'Value', weights = postprob(refmodel))
expect_valid_lcModel(model)
expect_equivalent(nClusters(model), nClusters(refmodel))
expect_equivalent(trajectoryAssignments(model), trajectoryAssignments(refmodel))
expect_equivalent(postprob(model), postprob(refmodel))
})
test_that('non-unit weights', {
model = lcModelWeightedPartition(testLongData, response = 'Value', weights = 2 * postprob(refmodel))
expect_valid_lcModel(model)
expect_equivalent(nClusters(model), nClusters(refmodel))
expect_equivalent(trajectoryAssignments(model), trajectoryAssignments(refmodel))
expect_equivalent(postprob(model), postprob(refmodel))
})
# clusterTrajectories ####
partModel = lcModelWeightedPartition(
testLongData,
response = 'Value',
weights = postprob(refmodel)
)
test_that('clusterTrajectories with hard separation model', {
clusTrajs = clusterTrajectories(partModel)
expect_is(clusTrajs, 'data.frame')
expect_named(clusTrajs, c('Cluster', 'Assessment', 'Value'))
expect_is(clusTrajs$Cluster, 'factor')
expect_equivalent(unique(clusTrajs$Assessment), unique(testLongData$Assessment))
expect_equivalent(unique(clusTrajs$Cluster), unique(testLongData$Class))
refdata = copy(testLongData)
refdata[, Cluster := trajectoryAssignments(partModel)[make.idRowIndices(partModel)]]
expect_equal(
clusTrajs,
as.data.frame(refdata[, .(Value = mean(Value)), keyby = .(Cluster = Cluster, Assessment)])
)
})
test_that('clusterTrajectories with an unrepresented cluster', {
model = lcModelWeightedPartition(
testLongData,
response = 'Value',
weights = cbind(rep(1, nIds(partModel)), 0)
)
expect_warning({clusTrajs = clusterTrajectories(model)})
expect_true(all(as.data.table(clusTrajs)[Cluster == 'B', is.na(Value)]))
})
test_that('clusterTrajectories interpolation with an unrepresented cluster', {
model = lcModelWeightedPartition(
testLongData,
response = 'Value',
weights = cbind(rep(1, nIds(partModel)), 0)
)
expect_warning({clusTrajs = clusterTrajectories(model, at = .3523)})
expect_true(all(as.data.table(clusTrajs)[Cluster == 'B', is.na(Value)]))
})
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