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silx settles into maintenance a release after its PySide6 migration
Comparison · Analytics
Plotly vs spatstat.model
A side-by-side editorial comparison of Plotly and spatstat.model — release velocity, themes, recent moves, and the top alternatives to consider.
Plotly vs spatstat.model: at a glance
What is Plotly?
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
Plotly ships on two tracks. Plotly Studio, the desktop AI app-builder, releases every one to two weeks and has spent v0.0.80 through v0.0.86 on credential handling, reasoning transparency, personalization and now the reliability of the agent session engine itself. Plotly Cloud is the louder track: since late May it has added viewer-seat pricing, domain verification, per-app compute modes with credit-metered billing, and customer-owned domains with managed TLS.
What is spatstat.model?
spatstat's inference layer builds out determinantal and cluster process fitting
spatstat.model fits point process models and provides the diagnostics that go with them. The recent window is dominated by determinantal point process work — a variance-covariance matrix and more diagnostics in 3.7-2, additional `intensity` and `repul` methods in 3.7-1, and ROC curves for determinantal models in 3.5-0. Cluster and Cox process inference has advanced in parallel, with Waagepetersen's composite likelihood arriving in 3.6-1.
Plotly vs spatstat.model: editorial side-by-side
Plotly
6.3ANALYTICS
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
◆ Current state
Plotly ships on two tracks. Plotly Studio, the desktop AI app-builder, releases every one to two weeks and has spent v0.0.80 through v0.0.86 on credential handling, reasoning transparency, personalization and now the reliability of the agent session engine itself. Plotly Cloud is the louder track: since late May it has added viewer-seat pricing, domain verification, per-app compute modes with credit-metered billing, and customer-owned domains with managed TLS.
◆ Where it's heading
The Cloud releases are assembling the standard pieces of a hosting business in order — identity first (domain verification, explicitly framed as the step before SSO), then billing (viewer seats, then metered compute credits), and now production-grade serving (custom domains, automatic certificate renewal). Studio is being hardened as the authoring front end that feeds it: Universal Deployment pushed beyond Dash apps, credentials saved once and reused, a Winget channel to widen Windows installs, and in v0.0.86 a rebuilt session engine plus automatic retries so agent runs survive expired tokens. The two tracks converge on one funnel — author in Studio, deploy to Cloud, pay by compute consumed.
◆ Prediction
The Domain Verification entry names SSO as the next step and places it in the Enterprise tier, so single sign-on is the most likely Cloud release next. Studio should hold its one-to-two-week cadence, with the newly added app thumbnails pointing toward more work on browsing and organizing generated apps.
spatstat.model
2.5ANALYTICS
spatstat's inference layer builds out determinantal and cluster process fitting
◆ Current state
spatstat.model fits point process models and provides the diagnostics that go with them. The recent window is dominated by determinantal point process work — a variance-covariance matrix and more diagnostics in 3.7-2, additional `intensity` and `repul` methods in 3.7-1, and ROC curves for determinantal models in 3.5-0. Cluster and Cox process inference has advanced in parallel, with Waagepetersen's composite likelihood arriving in 3.6-1.
◆ Where it's heading
The pattern is that model classes enter the package as fitting machinery first and only later gain the apparatus that makes them usable in practice — standard errors, diagnostics, residuals, model checking. Determinantal processes are visibly midway through that progression, reaching variance-covariance estimation only in the most recent release. Around this, the package has been broadening where models can be fitted at all: replicated point patterns on linear networks in 3.5-0, extended spatial logistic regression, and conversion of recursively partitioned models to tessellations.
◆ Prediction
Expect determinantal model support to keep filling out along the same path other model classes took, since variance estimation has only just arrived and partial residuals already exist for the cluster and Cox families. The entries do not signal a move into three dimensions here, unlike the geometry and simulation packages.
Alternatives to Plotly and spatstat.model
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 Plotly or spatstat.model.
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.
OpenCTI
OpenCTI spends a release unblocking queues and hardening upserts
Grafana Mimir
Mimir's feed is a weekly Helm bot, with the 3.2 candidate the only real release in months
See all Plotly alternatives → · See all spatstat.model alternatives →
Recent activity from Plotly and spatstat.model
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 14d agoPlotlyCustom Domains in Plotly Cloud ⚡
- 22d agospatstat.modelVariance-covariance and diagnostics for determinantal models
- 24d agoPlotlyPlotly Studio v0.0.85: Breadcrumbs & minor bug fixes
- 1mo agoPlotlyPlotly Studio v0.0.84: Faster AI, Saved Credentials, and Winget Support
- 1mo agoPlotlyCompute Modes and App Sizing in Plotly Cloud ⚡
- 1mo agoPlotlyPlotly Studio 0.0.83: Dash Update and macOS Fixes
- 2mo agoPlotlyPlotly Studio v0.0.82: Override for credential redaction, stability fixes
- 2mo agospatstat.modelMore intensity and repul methods; boundary-aware predictions
- 6mo agospatstat.modelComposite likelihood for cluster processes
- 8mo agospatstat.modelReplicated network models and partial residuals
- 10mo agospatstat.modelintensity.ppm improvements for Geyer models
- 1y agospatstat.modelROC curve support substantially extended
Frequently asked questions
What is the difference between Plotly and spatstat.model?
They serve adjacent needs but don't currently overlap on shipped themes. Plotly is currently shipping more aggressively (velocity 6.3 vs 2.5), 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.
Is Plotly better than spatstat.model?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Plotly is currently shipping more aggressively (velocity 6.3 vs 2.5), with 1 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 Plotly?
Top Plotly alternatives in Analytics are ranked by recent ship velocity. Browse the "Plotly alternatives" section above for the current picks, or visit /alternatives/plotly for the full list with editorial commentary on each.
What are the best alternatives to spatstat.model?
Top spatstat.model alternatives in Analytics are ranked by recent ship velocity. Browse the "spatstat.model alternatives" section above for the current picks, or visit /alternatives/spatstat-model for the full list with editorial commentary on each.