rollupTree
The recursive-computation engine under massProps grows the accessors its consumer needed
A side-by-side editorial comparison of humind and remap — release velocity, themes, recent moves, and the top alternatives to consider.
The MSNI humanitarian needs framework as code, rewritten and re-broken every year
humind turns household survey data into Multi-Sector Needs Index severity scores across WASH, Protection, SNFI, Food Security, Education and Health. Its version line tracks the annual MSNI framework revision — 2024.x, 2025.x, 2026.x — with narrow correctness patches between rollouts. v2026.2.0 is the current rollout and the most structural one in the visible history: water-quantity scoring moved out into a new mandatory prerequisite, food-security severity now comes from a different matrix, and the impactR4PHU runtime dependency is gone.
A regional-model smoother in long-term maintenance, four years past its last real feature.
remap fits separate models to geographic regions and blends their predictions into a continuous surface, using the min_n nearest observations so region boundaries do not show as discontinuities. The methodological work is finished — the last behavioural change landed in 2022, and everything since has been unit handling, compiler warnings, dependency compatibility and citation updates. The July release is one such patch.
humind turns household survey data into Multi-Sector Needs Index severity scores across WASH, Protection, SNFI, Food Security, Education and Health. Its version line tracks the annual MSNI framework revision — 2024.x, 2025.x, 2026.x — with narrow correctness patches between rollouts. v2026.2.0 is the current rollout and the most structural one in the visible history: water-quantity scoring moved out into a new mandatory prerequisite, food-security severity now comes from a different matrix, and the impactR4PHU runtime dependency is gone.
Two things move together. The framework content is revised yearly — indicators added, weights corrected, instruments swapped — and the package keeps absorbing pipeline it used to delegate, most visibly by vendoring add_fcs(), add_hhs(), add_rcsi(), add_lcsi() and add_fcm_phase() locally rather than importing them. Each rollout is explicitly breaking and the release notes have grown per-function 'Action:' instructions, which reads as maintainers who expect every downstream dashboard to need rewiring on the same annual clock.
The 2025 line settled into narrow patches immediately after its rollout — 1.2, 1.3 and 1.4 fixed a separator argument, a schema rename and a shelter misclassification rather than adding indicators. Expect the 2026 line to do the same: correctness fixes against the new WASH, FCLCM and shelter-damage logic before any further framework change.
remap fits separate models to geographic regions and blends their predictions into a continuous surface, using the min_n nearest observations so region boundaries do not show as discontinuities. The methodological work is finished — the last behavioural change landed in 2022, and everything since has been unit handling, compiler warnings, dependency compatibility and citation updates. The July release is one such patch.
This is a stable academic package tracking its ecosystem rather than growing. The visible pattern is reactive maintenance: sf's 1.0.0 transition, ggplot2's size-to-linewidth rename, a gcc-UBSAN error on zero-point distance calculations, and now a check that distance matrices passed to remap() and predict() are converted to kilometres. Note that the feed's timestamps invert the version order — 0.3.1 is stamped seconds after 0.3.2 despite being the earlier release, so recency in this feed is not a reliable guide to sequence.
Nothing in these entries points to new capability. The realistic expectation is more of the same: a patch whenever sf, ggplot2 or a CRAN check surfaces an incompatibility, at roughly the observed cadence of one release every year or two.
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 humind or remap.
The recursive-computation engine under massProps grows the accessors its consumer needed
A mass-properties rollup spends a year on documentation and follows its sibling's API
Six months of releases and not one of them touched the scoring models
A cognitive-science sampling package ships once, then goes quiet for eighteen months
A Bayesian volatility sampler in its maintenance decade, paying for its own speed
A black-box interpreter reaches CRAN, then learns multi-class and survival responses
See all humind alternatives → · See all remap alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. humind is currently shipping more aggressively (velocity 3.8 vs 0.0), with 1 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. humind is currently shipping more aggressively (velocity 3.8 vs 0.0), with 1 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.
Top humind alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "humind alternatives" section above for the current picks, or visit /alternatives/humind for the full list with editorial commentary on each.
Top remap alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "remap alternatives" section above for the current picks, or visit /alternatives/remap for the full list with editorial commentary on each.