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Comparison · Analytics
see vs silx
A side-by-side editorial comparison of see and silx — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:data-visualization
see vs silx: at a glance
What is see?
see grows wherever easystats adds a diagnostic, one plot method at a time.
see is the visualization layer for the easystats ecosystem, supplying plot() methods for performance, parameters and datawizard objects. Each release adds methods for whatever those packages shipped — prior predictive checks, DAG diagrams, factor-analysis graphs — alongside steady theme and geom refinement.
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.
see vs silx: editorial side-by-side
see
0.0ANALYTICS
see grows wherever easystats adds a diagnostic, one plot method at a time.
◆ Current state
see is the visualization layer for the easystats ecosystem, supplying plot() methods for performance, parameters and datawizard objects. Each release adds methods for whatever those packages shipped — prior predictive checks, DAG diagrams, factor-analysis graphs — alongside steady theme and geom refinement.
◆ Where it's heading
Growth here is downstream-driven rather than self-directed: see expands to cover new diagnostics as easystats produces them. Running alongside that is a sustained investment in presentation control — theme arguments on plot methods, elements that scale with base_size — which suits users embedding these plots in documents rather than glancing at them interactively.
◆ Prediction
Expect new plot methods to keep arriving in step with performance and parameters releases, with continued theming work rather than any change in the package's scope.
silx
5.0ANALYTICS
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 see 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 see or silx.
Omni
Omni ships weekly, and almost every week the headline item is an AI feature.
Plotly
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
aniread
aniread stops asking you to know which tracker wrote the file
Rho
Rho's release machinery finally produced a stable build — and it shipped no new product.
Usermaven
Usermaven closed the loop: data comes in from anywhere, and now it goes back out.
Recent activity from see and silx
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 5h agosilxFitWidget fix for loading a fit function from file
- 9d agosilx3.1.0: asinh axis scaling, twilight colormaps, dark-theme icons
- 1mo agoseesee 0.14.1 adds plots for prior checks and grouped means
- 2mo agoseesee 0.14.0 renders factor loadings as node-edge graphs
- 3mo agosilx3.0.1: silx view fails to disable HDF5 file locking
- 3mo agosilx3.0.0: PySide6 becomes the default Qt binding, Python 3.10 required ⚡
- 3mo agosilx3.0.0rc1: release candidate for the PySide6 migration
- 6mo agoseesee 0.13.0 fixes reversed plot sorting, adds theme arguments
- 11mo agoseesee 0.12.0 extends normality checks to psych factor models
- 1y agosilx2.2.2: plot axes limits, OpenGL axes and libhdf5 1.14 fixes
- 1y agoseesee 0.11.0 scales theme elements with base_size
- 1y agoseesee 0.10.0 plots random-effect group levels for mixed models
Frequently asked questions
What is the difference between see and silx?
Both compete on the same themes — data-visualization — within Analytics. silx is currently shipping more aggressively (velocity 5.0 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 see 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 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 see?
Top see alternatives in Analytics are ranked by recent ship velocity. Browse the "see alternatives" section above for the current picks, or visit /alternatives/see-r 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.