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test_that("regr_FDboost is equal to reference", {
skip_on_cran()
requirePackagesOrSkip("FDboost", default.method = "load")
lrn = makeLearner("regr.FDboost", knots = 40L, df = 4L, mstop = 100L)
mlr.mod = train(lrn, fda.regr.fs.task)
frm = as.formula(mlr.mod$learner.model$formulaFDboost)
# Get the features in a data.frame and matrix column
mat.list = getTaskData(fda.regr.fs.task, functionals.as = "matrix")
# Add matricies for fd.grids
fdns = colnames(getFunctionalFeatures(fda.regr.fs.task))
fdg = namedList(fdns)
fd.grids = lapply(fdns, function(name) seq_len(ncol(mat.list[, name])))
names(fd.grids) = fdns
fdg = setNames(fd.grids, stri_paste(fdns, ".grid"))
mat.list = c(mat.list, fdg)
ctrl = learnerArgsToControl(mboost::boost_control, mstop = 100L, nu = 0.1)
true.mod = FDboost::FDboost(frm, data = mat.list,
timeformula = ~ bols(1), control = ctrl, family = mboost::Gaussian())
prd = predict(mlr.mod, newdata = getTaskData(fda.regr.fs.task,
functionals.as = "matrix"))
prd2 = predict(true.mod, as.list(getTaskData(fda.regr.fs.task,
functionals.as = "matrix")))
expect_equal(prd$data$response, prd2)
})
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