rollupTree
The recursive-computation engine under massProps grows the accessors its consumer needed
Comparison · Infra & APIs
inlabru vs tf
A side-by-side editorial comparison of inlabru and tf — release velocity, themes, recent moves, and the top alternatives to consider.
inlabru vs tf: at a glance
What is inlabru?
A Bayesian spatial modelling package rebuilding its foundations one breaking release at a time
inlabru wraps INLA for spatial, point-process and latent-Gaussian models in R. It is mid-modernisation: since 2.12.0 cut the sp stack, each release has renamed part of the public surface, standardised how external packages attach custom mappers, or replaced internal machinery. 2.15.0 is the latest step, pairing a new predictor evaluation and linearisation implementation with broom's tidy(), glance() and augment() methods and four non-zero-truncated observation families.
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.
inlabru vs tf: editorial side-by-side
inlabru
2.5INFRA · APIS
A Bayesian spatial modelling package rebuilding its foundations one breaking release at a time
◆ Current state
inlabru wraps INLA for spatial, point-process and latent-Gaussian models in R. It is mid-modernisation: since 2.12.0 cut the sp stack, each release has renamed part of the public surface, standardised how external packages attach custom mappers, or replaced internal machinery. 2.15.0 is the latest step, pairing a new predictor evaluation and linearisation implementation with broom's tidy(), glance() and augment() methods and four non-zero-truncated observation families.
◆ Where it's heading
The arc is consolidation of the extension surface rather than expansion of the model catalogue. Every release adds mappers or families with one hand and removes a dependency, a re-export or a deprecated path with the other — plyr in 2.15.0, fmesher's Depends entry in 2.14.1, sp and ggmap in 2.12.0. The compatibility flag bru_compat_pre_2_14_enable and the temporary fm_int/fm_pixels re-exports show a maintainer sequencing breaks across releases instead of landing them together.
◆ Prediction
The 2.14 compatibility flag is still defaulting to TRUE and the fmesher re-exports are described in the entries as temporary, so the next obvious move is a release that flips bru_compat_pre_2_14_enable off and drops those re-exports.
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 inlabru 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 inlabru 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 inlabru and tf
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 23d agoinlabruPredictor linearisation rewritten; broom tidiers, truncated families
- 1mo agotfVector-valued functional data becomes a first-class type ⚡
- 3mo agoinlabruBugfix release: factor contrasts, raster extraction, error classes
- 5mo agotfCurve registration, five depth measures and sub-domain splitting
- 5mo agoinlabruNew mappers, standardised cgeneric support, bru_obs storage refactor
- 1y agoinlabruMapper classes shortened to bm_*, experimental predictor aggregation
- 1y agoinlabruDrops sp and ggmap for an sf-native spatial stack ⚡
- 2y agotfFix: tf_crosscov normalization
Frequently asked questions
What is the difference between inlabru and tf?
They serve adjacent needs but don't currently overlap on shipped themes. inlabru is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is inlabru better than tf?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. inlabru is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
What are the best alternatives to inlabru?
Top inlabru alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "inlabru alternatives" section above for the current picks, or visit /alternatives/inlabru 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.