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Comparison · Analytics
ribd vs rpymat
A side-by-side editorial comparison of ribd and rpymat — release velocity, themes, recent moves, and the top alternatives to consider.
ribd vs rpymat: at a glance
What is ribd?
The pedsuite's coefficient engine: broadening what it computes, then making the plots publishable.
ribd computes relatedness coefficients from pedigrees, covering kinship, inbreeding, kappa, condensed and detailed identity coefficients, and two-locus versions of several of these, in autosomal and X-chromosomal form. The IBD triangle is now drawable in base graphics, ggplot2 or plotly, with an optional inset pedigree, and custom relationships can be placed on it. The most recent release is dominated by correctness work, fixing pair ordering and row alignment in coefficient tables and edge cases for pedigree lists, unrelated individuals and self-pairs.
What is rpymat?
After three dormant years, rpymat returned to fix the OpenMP crash that breaks R and conda together
rpymat manages an isolated conda-based Python environment for R packages, providing a reproducible bridge without touching the user's system Python. It released steadily through 2022-2023 and then went quiet for nearly three years. 0.1.9 in May 2026 is the first release since, and it addresses a specific and long-standing failure mode.
ribd vs rpymat: editorial side-by-side
ribd
2.5ANALYTICS
The pedsuite's coefficient engine: broadening what it computes, then making the plots publishable.
◆ Current state
ribd computes relatedness coefficients from pedigrees, covering kinship, inbreeding, kappa, condensed and detailed identity coefficients, and two-locus versions of several of these, in autosomal and X-chromosomal form. The IBD triangle is now drawable in base graphics, ggplot2 or plotly, with an optional inset pedigree, and custom relationships can be placed on it. The most recent release is dominated by correctness work, fixing pair ordering and row alignment in coefficient tables and edge cases for pedigree lists, unrelated individuals and self-pairs.
◆ Where it's heading
The arc runs from generality to presentation to precision. Early releases replaced narrow functions with general ones, most visibly when gKinship() absorbed generalisedKinship() and identityCoefs() superseded the separate autosomal and X-chromosomal identity functions in favour of an Xchrom argument. The middle stretch turned the IBD triangle into a proper plotting surface across three graphics systems. The current phase reads as consolidation, with the newest release listing six bug fixes against four features, several of them alignment errors in output tables, which is where a coefficient library most needs to be exactly right.
◆ Prediction
The two new internal functions in the latest release, inbreedingContributions() and ancestralKinship(), are the kind of thing that surfaces publicly a release or two later, so expect them to become exported decomposition tools. The correctness push through pedigree lists and edge cases suggests the near-term focus stays on hardening rather than new coefficient families.
rpymat
0.0ANALYTICS
After three dormant years, rpymat returned to fix the OpenMP crash that breaks R and conda together
◆ Current state
rpymat manages an isolated conda-based Python environment for R packages, providing a reproducible bridge without touching the user's system Python. It released steadily through 2022-2023 and then went quiet for nearly three years. 0.1.9 in May 2026 is the first release since, and it addresses a specific and long-standing failure mode.
◆ Where it's heading
The work is about surviving the seams between two runtimes. 0.1.9 addresses OpenMP double-initialization — the error users hit when R's OpenMP and conda's disagree — by setting KMP_DUPLICATE_LIB_OK as a compromise, and adds fix_omp_conflict() to symlink over conda's built-in version as the recommended real fix. The caveat is stated plainly: users must re-run it whenever R is updated, and the ABI versions must match. Earlier releases followed the same pattern, with 0.1.2 fixing segfaults from incompatible BLAS between numpy and R.
◆ Prediction
The recurring theme across releases is native library conflicts between the R and conda stacks, so further releases are likely to keep patching that surface as Python versions move. The three-year gap makes cadence unpredictable.
Alternatives to ribd and rpymat
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 ribd or rpymat.
spsurvey
spsurvey has spent four years consolidating after its 5.0.0 rewrite rather than adding to it
StreamCatTools
StreamCatTools is quietly moving off web services and onto cloud-native GeoParquet
reproducible
reproducible added a windowed read path so remote GeoTiffs never fully download
qcTAF
qcTAF is building an automated checklist for reproducible fisheries assessments, one criterion at a time
ieegio
ieegio's first release lands electrode trajectory burning and a WebGL-free surface plot
Recent activity from ribd and rpymat
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 12d agoribdCustom relationships on the IBD triangle; six alignment and edge-case fixes
- 2mo agorpymatOpenMP conflict workaround and fix_omp_conflict() helper
- 1y agoribdkappaIBD() can skip across-component pairs on large pedigrees
- 2y agoribdIBD triangle plots gain ggplot2 and plotly backends, plus inset pedigrees
- 3y agoribdTriangle line clipping, automatic plot margins, citation info
- 3y agorpymatFix installation regression from 0.1.5
- 3y agorpymatFile choosers, reticulate conversion ports and reusable conda detection
- 3y agoribdTwo-locus functions overhauled; twoLocusInbreeding and ELR added
- 4y agoribdIdentity coefficients unified behind identityCoefs() and an Xchrom argument
- 4y agorpymatWindows support and BLAS segfault fix
Frequently asked questions
What is the difference between ribd and rpymat?
They serve adjacent needs but don't currently overlap on shipped themes. ribd 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 ribd better than rpymat?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ribd 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 Analytics products to evaluate alongside.
What are the best alternatives to ribd?
Top ribd alternatives in Analytics are ranked by recent ship velocity. Browse the "ribd alternatives" section above for the current picks, or visit /alternatives/ribd for the full list with editorial commentary on each.
What are the best alternatives to rpymat?
Top rpymat alternatives in Analytics are ranked by recent ship velocity. Browse the "rpymat alternatives" section above for the current picks, or visit /alternatives/rpymat for the full list with editorial commentary on each.