rollupTree
The recursive-computation engine under massProps grows the accessors its consumer needed
Comparison · Infra & APIs
mpactr vs tf
A side-by-side editorial comparison of mpactr and tf — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-packages
mpactr vs tf: at a glance
What is mpactr?
mpactr spent two spring releases normalizing case in metadata after users kept tripping on it.
mpactr filters mass-spectrometry peak tables — removing contaminants, ion duplicates and low-reproducibility features before downstream metabolomics analysis — with a data.table and Rcpp core. Development is slow and the recent releases are small. The May pair both address the same friction: column names and imported table names arriving in inconsistent case and failing to match.
What is tf?
tf gave functional data a second dimension: curves whose values are vectors.
tf supplies the vector classes underneath the tidyfun stack — tfd for raw functional observations, tfb for basis-represented ones, both built on vctrs so curves sit in a data frame column and behave like any other vector. Until July that codomain was scalar. The 0.5.0 release adds tfd_mv and tfb_mv, classes for functions whose values are vectors in R^d, and rebuilds the analysis verbs to match.
mpactr vs tf: editorial side-by-side
mpactr
0.0INFRA · APIS
mpactr spent two spring releases normalizing case in metadata after users kept tripping on it.
◆ Current state
mpactr filters mass-spectrometry peak tables — removing contaminants, ion duplicates and low-reproducibility features before downstream metabolomics analysis — with a data.table and Rcpp core. Development is slow and the recent releases are small. The May pair both address the same friction: column names and imported table names arriving in inconsistent case and failing to match.
◆ Where it's heading
The package is stabilizing its input contract rather than growing its filtering methods. Metadata column names are now forced lowercase inside import_data() regardless of how the file was written, imported peak_tables names not present in the injection column are lowercased too, and get_meta_data() was renamed to get_metadata() in the same pass. Before that the work was infrastructural — Rcpp introduced to speed up filtering, data.table moved from Depends to Imports, and memory errors cleared so the package passes Valgrind and both sanitizers. Note the earliest entry compares against a v1.0.0 tag that precedes 0.1.0 in the repository, so version ordering in this feed is not reliable.
◆ Prediction
The case-normalization work has now touched both metadata columns and peak table names across two consecutive releases, which suggests the input-matching problem is not fully closed and a third pass is plausible. Nothing in these entries points to new filtering methods.
tf
0.0INFRA · APIS
tf gave functional data a second dimension: curves whose values are vectors.
◆ Current state
tf supplies the vector classes underneath the tidyfun stack — tfd for raw functional observations, tfb for basis-represented ones, both built on vctrs so curves sit in a data frame column and behave like any other vector. Until July that codomain was scalar. The 0.5.0 release adds tfd_mv and tfb_mv, classes for functions whose values are vectors in R^d, and rebuilds the analysis verbs to match.
◆ Where it's heading
The package is widening what a functional observation can be, then porting the toolkit onto it. Registration arrived first in 0.4.0 for univariate curves and immediately gained an srvf_mv method for aligning components jointly, and tfb_mfpc() ports principal component analysis to the multivariate case with a single set of scores shared across components. Alongside that runs steady dependency shedding — mvtnorm and pracma both replaced by inlined samplers that reproduce prior draws bit-for-bit, glue dropped for cli in the previous release — and an unusually long tail of NA-handling and edge-case fixes, several caught in pre-release review of the new classes.
◆ Prediction
The new classes ship with FPCA, registration and shape alignment but the release notes describe tidyfun::tf_unnest() as the consumer of one new export, so the visible next step is the rest of the tidyfun stack catching up to vector-valued columns. Expect follow-up patches on the vctrs casting paths, which is where most of this release's late fixes clustered.
Alternatives to mpactr and tf
Other Infra & APIs products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either mpactr or tf.
massProps
A mass-properties rollup spends a year on documentation and follows its sibling's API
writeAlizer
Six months of releases and not one of them touched the scoring models
samplr
A cognitive-science sampling package ships once, then goes quiet for eighteen months
stochvol
A Bayesian volatility sampler in its maintenance decade, paying for its own speed
midr
A black-box interpreter reaches CRAN, then learns multi-class and survival responses
Recent activity from mpactr and tf
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agotfVector-valued functional data becomes a first-class type ⚡
- 3mo agompactrPeak table names lowercased when absent from the injection column
- 3mo agompactrMetadata column names forced lowercase; get_metadata() renamed
- 5mo agotfCurve registration, five depth measures and sub-domain splitting
- 10mo agompactrValgrind and sanitizer memory issues cleared
- 1y agompactrRcpp added to speed up filtering; data.table moved to Imports
- 1y agompactrmpactr 0.1.0
- 2y agotfFix: tf_crosscov normalization
Frequently asked questions
What is the difference between mpactr and tf?
Both compete on the same themes — r-packages — within Infra & APIs. mpactr and tf are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is mpactr better than tf?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mpactr and tf are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
What are the best alternatives to mpactr?
Top mpactr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "mpactr alternatives" section above for the current picks, or visit /alternatives/mpactr for the full list with editorial commentary on each.
What are the best alternatives to tf?
Top tf alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "tf alternatives" section above for the current picks, or visit /alternatives/tf for the full list with editorial commentary on each.