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hubEvals vs silx

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

hubEvals vs silx: at a glance

FeaturehubEvalssilx
SectorAnalyticsAnalytics
Velocity score2.55.0
Sparks · 30d00
Top themesforecast-evaluation, scoring, epidemiology, r-packagescientific-computing, data-visualization, synchrotron, qt
Last editorial update2d ago2h ago
WebsiteVisit →Visit →

What is hubEvals?

Forecast-hub scoring that learned to handle joint, sample-based predictions.

hubEvals scores model output from collaborative forecasting hubs, wrapping scoringutils and translating hubverse formats into forecast objects it can evaluate. The package has moved quickly from a thin translation layer to something that handles every output type the hubverse defines — quantile, mean, median, nominal and ordinal pmf, and samples. The most recent releases are almost entirely about the failure modes of relative skill scoring rather than about new metrics.

Read the full hubEvals trajectory →

What is silx?

silx settles into maintenance a release after its PySide6 migration

silx is in the quiet phase after a generational release. 3.1.1 is a single fix to FitWidget loading a fit function from file. The release before it, 3.1.0, was the first real feature work since the migration - asinh axis scaling, twilight colormaps, and dark-theme icons - and 3.0.1 was similarly small. The 3.0.0 cut that reset the Qt binding and Python floor still defines what the line is doing.

Read the full silx trajectory →

hubEvals vs silx: editorial side-by-side

H
hubEvals
ANALYTICS
2.5

Forecast-hub scoring that learned to handle joint, sample-based predictions.

◆ Current state

hubEvals scores model output from collaborative forecasting hubs, wrapping scoringutils and translating hubverse formats into forecast objects it can evaluate. The package has moved quickly from a thin translation layer to something that handles every output type the hubverse defines — quantile, mean, median, nominal and ordinal pmf, and samples. The most recent releases are almost entirely about the failure modes of relative skill scoring rather than about new metrics.

◆ Where it's heading

Two threads dominate. The first is coverage of output types, which reached its widest point with sample-based and compound scoring. The second, and the one occupying every recent release, is making relative skill degrade gracefully: single-model input, comparison groups with one model, and groups missing the requested baseline have each been converted from a cryptic upstream abort into a defined result. That pattern — inherited scoringutils errors being caught and given hub-specific meaning — is the clearest signal of where this package adds value.

◆ Prediction

Expect continued work smoothing scoringutils error surfaces into hub-aware behaviour, and performance attention on relative skill, which was explicitly optimised in the latest release.

S
silx
ANALYTICS
5.0

silx settles into maintenance a release after its PySide6 migration

◆ Current state

silx is in the quiet phase after a generational release. 3.1.1 is a single fix to FitWidget loading a fit function from file. The release before it, 3.1.0, was the first real feature work since the migration - asinh axis scaling, twilight colormaps, and dark-theme icons - and 3.0.1 was similarly small. The 3.0.0 cut that reset the Qt binding and Python floor still defines what the line is doing.

◆ Where it's heading

The cadence has slowed markedly since April, and the content has shifted from structural change to plotting and colormap refinement. That is the expected shape after a binding migration: downstream beamline code needs a stable target, so the project trades feature velocity for a quiet surface. The gap between 3.0.1 in May and 3.1.0 in August is the clearest signal of the deliberate slowdown.

◆ Prediction

Expect further point releases servicing the plotting and fitting widgets rather than another structural change, with feature work continuing to arrive in the 3.1.x minors rather than patches.

Alternatives to hubEvals and silx

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 hubEvals or silx.

See all hubEvals alternatives → · See all silx alternatives →

Recent activity from hubEvals and silx

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

  1. 5h agosilxFitWidget fix for loading a fit function from file
  2. 9d agosilx3.1.0: asinh axis scaling, twilight colormaps, dark-theme icons
  3. 27d agohubEvalsScored-forecast counts and faster relative skill
  4. 1mo agohubEvalsDisaggregated relative skill no longer aborts the whole call
  5. 1mo agohubEvalsSingle-model scoring returns relative skill of 1 instead of erroring
  6. 3mo agosilx3.0.1: silx view fails to disable HDF5 file locking
  7. 3mo agosilx3.0.0: PySide6 becomes the default Qt binding, Python 3.10 required
  8. 3mo agosilx3.0.0rc1: release candidate for the PySide6 migration
  9. 5mo agohubEvalsSample output types and multivariate compound scoring
  10. 6mo agohubEvalsScoring on transformed scales via transform arguments
  11. 11mo agohubEvalsFirst release: score_model_out() and the scoringutils bridge
  12. 1y agosilx2.2.2: plot axes limits, OpenGL axes and libhdf5 1.14 fixes

Frequently asked questions

What is the difference between hubEvals and silx?

They serve adjacent needs but don't currently overlap on shipped themes. silx is currently shipping more aggressively (velocity 5.0 vs 2.5), 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 hubEvals better than silx?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. silx is currently shipping more aggressively (velocity 5.0 vs 2.5), 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 hubEvals?

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

What are the best alternatives to silx?

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