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Comparison · Infra & APIs

ggpointless vs mdatools

A side-by-side editorial comparison of ggpointless and mdatools — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-packages

ggpointless vs mdatools: at a glance

Featureggpointlessmdatools
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2-extensions, data-visualization, pictogram-charts, alpha-gradientschemometrics, spectroscopy, classification, multiway-analysis
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is ggpointless?

ggpointless keeps adding the ggplot2 layers nobody else bothered to write.

ggpointless is a small ggplot2 extension collecting geoms that sit outside the standard set — Lexis diagrams, Chaikin-smoothed paths, hanging chains, Fourier reconstructions — and it has grown steadily rather than changed shape. The May release is the largest yet: isotype and pictogram bar charts as stacks of discrete unit cells, a family of geoms that fade paths, segments, curves and reference lines along their length, and geom_gridline(), which draws grid lines as a layer on top of the data rather than beneath it.

Read the full ggpointless trajectory →

What is mdatools?

mdatools spun out its cross-validation method, then came back for three-way data.

mdatools is a long-running chemometrics package covering PCA, PLS regression, SIMCA and DD-SIMCA classification, MCR resolution and a large spectral preprocessing framework. Its releases are infrequent and each one tends to carry one substantive idea plus a handful of fixes. The June release opens a direction the package had not previously taken: DD-SIMCA classification of three-way data, through PARAFAC and Tucker decompositions.

Read the full mdatools trajectory →

ggpointless vs mdatools: editorial side-by-side

G
ggpointless
INFRA · APIS
0.0

ggpointless keeps adding the ggplot2 layers nobody else bothered to write.

◆ Current state

ggpointless is a small ggplot2 extension collecting geoms that sit outside the standard set — Lexis diagrams, Chaikin-smoothed paths, hanging chains, Fourier reconstructions — and it has grown steadily rather than changed shape. The May release is the largest yet: isotype and pictogram bar charts as stacks of discrete unit cells, a family of geoms that fade paths, segments, curves and reference lines along their length, and geom_gridline(), which draws grid lines as a layer on top of the data rather than beneath it.

◆ Where it's heading

Two patterns are visible. Ideas get generalized rather than left as one-offs: geom_area_fade() in the previous release established alpha gradients via grid::linearGradient(), and the recent release spreads that treatment across paths, lines, steps, segments, curves and the three reference-line geoms, each with the same fade_direction and alpha_fade_to arguments. And each new geom is expected to survive real plots — the unit charts work under coord_equal, coord_polar, coord_radial, coord_flip and faceting, and geom_gridline reads positions from trained scales and inherits styling from the theme's panel grid. The package also tracks ggplot2 closely, requiring 4.0.0 and using make_constructor() and gg_par() internally, and it dropped its bundled datasets outright rather than maintain stale copies.

◆ Prediction

The fade treatment now covers most path-like geoms but not the area and ribbon family beyond geom_area_fade(), which is where the pattern has room left to run. The unit-cell charts arrive with a label helper and no fill or grouping variants, so those are the plausible next additions.

M
mdatools
INFRA · APIS
0.0

mdatools spun out its cross-validation method, then came back for three-way data.

◆ Current state

mdatools is a long-running chemometrics package covering PCA, PLS regression, SIMCA and DD-SIMCA classification, MCR resolution and a large spectral preprocessing framework. Its releases are infrequent and each one tends to carry one substantive idea plus a handful of fixes. The June release opens a direction the package had not previously taken: DD-SIMCA classification of three-way data, through PARAFAC and Tucker decompositions.

◆ Where it's heading

The shape of the package has been managed deliberately rather than allowed to sprawl. Procrustes cross-validation grew large enough to warrant its own package and was moved out to pcv in 0.14.0; preprocessing was consolidated in 0.12.0 into a composable prep() framework rather than a set of loose functions. Around that, the recurring work is numerical: a more stable SIMPLS implementation, cross-validation rewritten to accept user-supplied segment indices, prep.savgol() and prep.alsbasecorr() rewritten for speed, and now the baseline iteration default raised to match the web applications the maintainer also runs.

◆ Prediction

Three-way DD-SIMCA arrives with two decompositions and no companion regression or resolution methods for multiway data, so extending the multiway path to the rest of the toolkit is the obvious follow-up. The alignment of defaults with the maintainer's web applications suggests those two codebases will keep being reconciled.

Alternatives to ggpointless and mdatools

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 ggpointless or mdatools.

See all ggpointless alternatives → · See all mdatools alternatives →

Recent activity from ggpointless and mdatools

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agomdatoolsDD-SIMCA classification arrives for three-way data
  2. 3mo agoggpointlessPictogram unit charts, gridline layers and a family of fading geoms
  3. 5mo agoggpointlessFourier and arch geoms, area fades and glowing points
  4. 5mo agomdatoolsv. 0.15.0
  5. 2y agomdatoolsData frames converted to matrices automatically for model training
  6. 2y agoggpointlessgeom_catenary() draws a hanging chain
  7. 3y agomdatoolscv.scope lets centering and scaling follow the global or local set
  8. 3y agomdatoolsProcrustes cross-validation moves out to its own pcv package
  9. 3y agomdatoolsgetRegcoeffs() fixed for unscaled models; ipls() gains a full mode
  10. 3y agoggpointlessgeom_chaikin() adds corner-cutting path smoothing
  11. 4y agoggpointlessgeom_lexis() and the female_leaders dataset

Frequently asked questions

What is the difference between ggpointless and mdatools?

Both compete on the same themes — r-packages — within Infra & APIs. ggpointless and mdatools 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 ggpointless better than mdatools?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggpointless and mdatools 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 ggpointless?

Top ggpointless alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ggpointless alternatives" section above for the current picks, or visit /alternatives/ggpointless for the full list with editorial commentary on each.

What are the best alternatives to mdatools?

Top mdatools alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "mdatools alternatives" section above for the current picks, or visit /alternatives/mdatools for the full list with editorial commentary on each.