PipeOpFDACor, PipeOpFDADerive, PipeOpFDAExtract, PipeOpFDAIntegrate, PipeOpFDAInterpol, PipeOpFDAScaleRange, PipeOpFDASmooth, PipeOpFDAWavelets, and PipeOpFDAZoom.PipeOpFDABsignal now uses the argument values instead of index positions, which changes the features for grids other than 1, ..., p.PipeOpFDAInterpol now determines the "union", "intersect", and "minmax" grids during training and reuses them during prediction, instead of computing them from the prediction data.PipeOpFDARegister no longer fails during prediction when the "srvf" method gets fdasrvf::time_warping() arguments such as penalty_method or centroid_type in args.PipeOpFDAScaleRange now keeps the evaluator and maps the domain to [lower, upper].PipeOpFDAScaleRange now stores its state under $state$trafos.PipeOpFDAWavelets no longer supports irregular functional data, where coefficients of curves with different lengths were misaligned. Use PipeOpFDAInterpol first.PipeOpFPCA now uses the n_components from training during prediction.PipeOps no longer forward affect_columns to their backend functions.PipeOpFDAInterpol now reports which grid, left, and right combination is invalid instead of failing with an opaque assertion.PipeOpFDAInterpol now errors when left and right fall outside the domain of a functional column.tf version 0.5.0.PipeOpFDAWavelets no longer errors when filter is a wt.filter object or a numeric vector. Generated columns are now named <column>_wav_<i> regardless of the filter.PipeOpFDAZoom now accepts a one-sided begin or end instead of requiring both.as.data.table(mlr_pipeops) no longer errors with object 'value' not found when mlr3fda is loaded.PipeOpFDACatch22 for extracting the catch22 time series features from functional columns via Rcatch22::catch22_all().PipeOpFDAIntegrate for extracting the definite integral of functional columns via tf::tf_integrate().mlr3fda to mlr_reflections$loaded_packages to fix errors when using mlr3fda in parallel.PipeOpFDADepth for computing the data depth of functional columns via tf::tf_depth().PipeOpFDADerive for computing derivatives of functional columns via tf::tf_derive().PipeOpFDAExtract gained the "sd" feature for extracting the standard deviation.PipeOpFDAFourier is now several times faster.PipeOpFDARegister for aligning functional columns to a learned template via tf::tf_register().fuel task now correctly names the scalar column h2o instead of h20.Mlr3Error and Mlr3Warning classes for errors and warnings.PipeOpFDAFourier for extracting fast Fourier transform features from functional columns.PipeOpFDABsignalPipeOpFDARandomEffectPipeOpFDATsfeaturesPipeOpFDAWaveletsPipeOpFDAZoomPipeOpFDACorPipeOpFDAScaleRangeInitial CRAN release.