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Comparison · Analytics

hydroloom vs rempsyc

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

Shared themes:r-package

hydroloom vs rempsyc: at a glance

Featurehydroloomrempsyc
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themeshydrology, network-analysis, geospatial, r-packageapa-formatting, psychology-research, statistical-tables, ggplot2
Last editorial update6h ago1h ago
WebsiteVisit →Visit →

What is hydroloom?

USGS puts a type system over its river network toolkit so errors surface at dispatch

hydroloom builds and navigates hydrologic flow networks, carrying functionality migrated out of nhdplusTools. Version 1.2.0 introduces an S3 class hierarchy — hy_topo, hy_leveled, hy_node, hy_flownetwork — assigned automatically by hy() and by producer functions, letting the package validate input at dispatch time and emit guided errors. Outlet detection is now defined explicitly: a row is an outlet when its toid is not in id, with reserved values, NA and implicit absence all accepted.

Read the full hydroloom trajectory →

What is rempsyc?

Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.

rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.

Read the full rempsyc trajectory →

hydroloom vs rempsyc: editorial side-by-side

H
hydroloom
ANALYTICS
0.0

USGS puts a type system over its river network toolkit so errors surface at dispatch

◆ Current state

hydroloom builds and navigates hydrologic flow networks, carrying functionality migrated out of nhdplusTools. Version 1.2.0 introduces an S3 class hierarchy — hy_topo, hy_leveled, hy_node, hy_flownetwork — assigned automatically by hy() and by producer functions, letting the package validate input at dispatch time and emit guided errors. Outlet detection is now defined explicitly: a row is an outlet when its toid is not in id, with reserved values, NA and implicit absence all accepted.

◆ Where it's heading

The package spent its first releases porting and broadening — non-dendritic network support, divergence routing, subsetting that follows diversions out of a basin — and has now turned to making that surface safe to use. The class hierarchy is the structural expression of that turn: instead of every function re-checking whether a data frame has the columns it needs, the type carries the guarantee. The explicit outlet rule resolves a category of failure where valid networks errored on NA or orphan toid values.

◆ Prediction

The release notes flag that subclass attributes are stripped by standard dplyr operations, which is the kind of rough edge that usually generates follow-up work — expect attribute preservation or restoration helpers next.

R
rempsyc
ANALYTICS
0.0

Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.

◆ Current state

rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.

◆ Where it's heading

Two forces drive this package and neither is its own roadmap. The first is APA style: when the 7th edition advised against beta for standardized coefficients, the package switched its output to italic b with an asterisk. The second is the surrounding ecosystem — formatting is aligned to what lavaanExtra and afex produce, contrast handling was delegated to easystats' modelbased, and Excel correlation matrix export was handed entirely to the correlation package to cut maintenance.

◆ Prediction

The pattern of delegating functionality to specialist packages while keeping the formatting layer is well established and likely continues. Because releases bundle many small dev versions, the next one will probably again mix plotting refinements with fixes surfaced by upstream changes.

Alternatives to hydroloom and rempsyc

Other Analytics 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 hydroloom or rempsyc.

See all hydroloom alternatives → · See all rempsyc alternatives →

Recent activity from hydroloom and rempsyc

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

  1. 2mo agohydroloomhydroloom v1.2.0
  2. 5mo agohydroloomTest tolerances relaxed for CRAN Fedora checks
  3. 5mo agohydroloomNetwork subsetting and divergence-routed accumulation
  4. 10mo agohydroloomSort and indexing fixes
  5. 11mo agorempsycPoint labels and per-group correlations added to nice_scatter
  6. 1y agorempsycExcel correlation export delegated to the correlation package
  7. 1y agohydroloomUpmain and downmain navigation for non-dendritic networks
  8. 2y agorempsycTable spacing control and a fix for name collision with afex
  9. 2y agorempsycStandardized coefficients switch to APA 7th edition b* notation
  10. 2y agohydroloomInitial release completing the nhdplusTools migration
  11. 2y agorempsycLegend and standardization-check fixes
  12. 2y agorempsycnice_table starts coercing model objects automatically

Frequently asked questions

What is the difference between hydroloom and rempsyc?

Both compete on the same themes — r-package — within Analytics. hydroloom and rempsyc 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 hydroloom better than rempsyc?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hydroloom and rempsyc 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 Analytics products to evaluate alongside.

What are the best alternatives to hydroloom?

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

What are the best alternatives to rempsyc?

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