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performance vs silx

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

performance vs silx: at a glance

Featureperformancesilx
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesr-language, model-diagnostics, bayesian, easystatssynchrotron, qt, hdf5, scientific plotting
Last editorial update57m ago2h ago
WebsiteVisit →Visit →

What is performance?

performance keeps adding ways to check a model you have already fitted.

performance is at 0.17.1, which added check_priors() for prior predictive checks on Bayesian models and gave check_overdispersion(), check_model() and check_predictions() arguments to control residual type and plot range. The releases before it are a similar mix: a -2LL criterion column in test_likelihoodratio(), Bayesian predictive checks routed through modelbased, and in 0.16.0 a set of breaking renames including RMSA to the correct RMSR.

Read the full performance trajectory →

What is silx?

silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.

silx releases a couple of times a year and reached 3.0.0 in April 2026, which raised the Python floor to 3.10 and switched the default Qt binding to PySide6. The same release reworked the viewer's data views: 3D scatter support, dedicated RGB(A) image views, the composite ImageView split into Plot2dView and ComplexImageView, and NXdata stacks displayed as images. 3.1.0 has since added asinh axis scaling, the twilight colormaps, and dark-theme icons.

Read the full silx trajectory →

performance vs silx: editorial side-by-side

P
performance
ANALYTICS
0.0

performance keeps adding ways to check a model you have already fitted.

◆ Current state

performance is at 0.17.1, which added check_priors() for prior predictive checks on Bayesian models and gave check_overdispersion(), check_model() and check_predictions() arguments to control residual type and plot range. The releases before it are a similar mix: a -2LL criterion column in test_likelihoodratio(), Bayesian predictive checks routed through modelbased, and in 0.16.0 a set of breaking renames including RMSA to the correct RMSR.

◆ Where it's heading

Two consistent habits. Diagnostics keep gaining arguments to narrow what is examined — ppc_range, x_limits, maximum_dots, show_ci — which reads as a package being used on models large and awkward enough that the defaults stopped working. And simulated residuals via DHARMa keep displacing standard ones as the basis for the checks themselves.

◆ Prediction

With check_priors() newly added and Bayesian predictive checks now routed through modelbased, the next release most likely extends the Bayesian diagnostic set rather than reworking the frequentist checks.

S
silx
ANALYTICS
2.5

silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.

◆ Current state

silx releases a couple of times a year and reached 3.0.0 in April 2026, which raised the Python floor to 3.10 and switched the default Qt binding to PySide6. The same release reworked the viewer's data views: 3D scatter support, dedicated RGB(A) image views, the composite ImageView split into Plot2dView and ComplexImageView, and NXdata stacks displayed as images. 3.1.0 has since added asinh axis scaling, the twilight colormaps, and dark-theme icons.

◆ Where it's heading

The project is doing a generational refresh of its GUI layer: modern Qt binding, modules broken out of the composite widgets that had accumulated responsibilities, and the theming work that a desktop application needs to look current. Underneath, the recurring fixes are about HDF5 behavior in real facility environments — file locking, NFS refresh, Windows display paths — which is where a synchrotron toolkit actually gets stressed. Feature growth is concentrated in silx view rather than the library API.

◆ Prediction

Expect the 3.1.x line to keep filling in plotting options and theming, with the PySide6 default flushing out binding-specific bugs from downstream applications over the next few releases.

Alternatives to performance 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 performance or silx.

See all performance alternatives → · See all silx alternatives →

Recent activity from performance and silx

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

  1. 2d agosilx3.1.0: asinh axis scaling, twilight colormaps, dark-theme icons
  2. 1mo agoperformancecheck_priors() added; overdispersion plots use simulated residuals
  3. 2mo agoperformance-2LL criterion column and unified Bayesian predictive checks
  4. 3mo agosilx3.0.1: 2026/05/07
  5. 3mo agosilx3.0.0: PySide6 becomes the default Qt binding, Python 3.10 required
  6. 3mo agosilx3.0.0rc1: release candidate for the PySide6 migration
  7. 6mo agoperformanceBreaking renames plus point-count and CI controls in check_model()
  8. 8mo agoperformancecheck_autocorrelation() methods for DHARMa objects
  9. 10mo agoperformanceFixes CRAN checks after an rstanarm update
  10. 11mo agoperformancetinytable output format in display()
  11. 1y agosilx2.2.2: 2025/04/07
  12. 1y agosilx2.2.0b0: HSDS URL support and a multi-curve comparison window

Frequently asked questions

What is the difference between performance and silx?

They serve adjacent needs but don't currently overlap on shipped themes. silx 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 performance better than silx?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. silx 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 performance?

Top performance alternatives in Analytics are ranked by recent ship velocity. Browse the "performance alternatives" section above for the current picks, or visit /alternatives/easystats-performance 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.