🎉 UltraPlot 1.x highlights — celebrating 200 stars! ⭐

[cvanelteren]

🎉 Thank you for 200 stars!

UltraPlot 1.x has been all about making great plots simpler — richer visuals with less code, better geospatial workflows, scientific time that “just works,” and rock-solid defaults.
You’ve helped shape this journey — thank you! 🙌

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✨ Highlights you can use today

🆕 New plot types
Curved quiver — reveal local turning without dense streamlines. Discrete arrows that follow curvature; a sweet spot between quiver and streamplot. 📘 Docs
Beeswarm — see every data point without overlap. Great for comparing distributions across categories.
Networks + Lollipops — clearer storytelling for graphs and dense bar charts with minimal code.

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🌍 Better geospatial plotting
- GeoAxes ticks you can control (lonticklen, latticklen, ticklen) — independent of gridlines — for polished maps. - Axis sharing across Geo subplots that “looks right” without manual tweaks. - Rasterization toggles and DMS fixes for performance and reliable labels on heavy geo figures.

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🎨 Colorbars, labels, and colormaps
- Vertical inset colorbars for compact, beautiful figures. - Centered labels for discrete maps, discrete colors for quiver, and fewer surprises with diverging norms. - Lazy colormap loading for faster startup when you only need a few.

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🕰️ Scientific time that “just works”
CFTime support — non-standard calendars (noleap, gregorian, etc.) are automatically formatted — perfect for climate and xarray workflows.	⏱️

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🛠️ Ergonomics and reliability
- Handler-based configuration: register rc handlers that apply smart side-effects (e.g., turn a simple cycle into a full Matplotlib axes.prop_cycle). - Deterministic tests, better CI, improved docs/gallery, and a persistent DOI for citation.	⚙️

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🚀 Get started

• Install: pip install ultraplot
• Docs: https://ultraplot.readthedocs.io
• Full changelog: GitHub releases
• Cite: DOI 10.5281/zenodo.15733565