Birbla

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how does this stack up to evilcharts? my main use case is mapping out data onto frontend, and there are a lot of great libraries out there

by kl01

been stuck on matplotlib for centuries, academia loves such a change

by NickyHeC

This is awesome, can easily see this becoming a standard library. Can't wait for the 3D and volume visualizations.

by HoneySpoons

Interesting; how do the examples compare to datashader?

Edit: for my use cases, I use napari (~1e7-8 points) if I need true interactivity; otherwise, datashader/holoviz, or even just fast-histogram's 2D histograms work.

For extremely large point clouds, these caveats[0] still apply. It irks me when people make dense scatterplots without any indication of just how dense some portions are.

Still, if it can indeed handle 1e10 points, that's pretty impressive.

[0]: https://datashader.org/user_guide/Plotting_Pitfalls.html

by ahns

Interesting approach to large scale visualisation. Moving reduction into Rust and sending screen bounded data to WebGL seems much more sensible than pushing millions of raw points into the browser. How does it perform with real time updates? I am assuming it is much more performant? Any plans for a prod deployment?

by raychis

I’m not convinced GPU acceleration is a meaningful advantage for most charting use cases. Most dashboards don’t render enough data for it to matter. Once a chart is dense enough for rendering to become the bottleneck, it normally is already be too crowded to be meaningful. Zooming can justify supporting larger datasets, but sampling/viewport culling and level of detail often avoid drawing unnecessary points...

by kasts

Check out mosaic from uwdata which works on top of Observable plot

Or plotly-resampler which works on top of plotly and uses the rust package tsdownsample to aggregate on the 4pixels per pixel shown level (to make antialias work)

the grammar of graphics approach really is a great abstraction, and I'd love to see xy work in that direction

by hantusk

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  • Hacker News
  • how does this stack up to evilcharts? my main use case is mapping out data onto frontend, and there are a lot of great libraries out there
    by kl01
  • been stuck on matplotlib for centuries, academia loves such a change
    by NickyHeC
  • it's possible to render data out-of-core with XY, allowing it to render the entirety of OpenStreetMaps (that's 10,742,674,832 nodes!) with sub-second pan/zooms. it's a bit difficult to host online but you can try it out locally: https://github.com/reflex-dev/xy/tree/main/examples/osm
    by adhami
  • This is awesome, can easily see this becoming a standard library. Can't wait for the 3D and volume visualizations.
    by HoneySpoons
  • Interesting; how do the examples compare to datashader?

    Edit: for my use cases, I use napari (~1e7-8 points) if I need true interactivity; otherwise, datashader/holoviz, or even just fast-histogram's 2D histograms work.

    For extremely large point clouds, these caveats[0] still apply. It irks me when people make dense scatterplots without any indication of just how dense some portions are.

    Still, if it can indeed handle 1e10 points, that's pretty impressive.

    [0]: https://datashader.org/user_guide/Plotting_Pitfalls.html

    by ahns
  • Interesting approach to large scale visualisation. Moving reduction into Rust and sending screen bounded data to WebGL seems much more sensible than pushing millions of raw points into the browser. How does it perform with real time updates? I am assuming it is much more performant? Any plans for a prod deployment?
    by raychis
  • I’m not convinced GPU acceleration is a meaningful advantage for most charting use cases. Most dashboards don’t render enough data for it to matter. Once a chart is dense enough for rendering to become the bottleneck, it normally is already be too crowded to be meaningful. Zooming can justify supporting larger datasets, but sampling/viewport culling and level of detail often avoid drawing unnecessary points...
    by kasts
  • Check out mosaic from uwdata which works on top of Observable plot

    Or plotly-resampler which works on top of plotly and uses the rust package tsdownsample to aggregate on the 4pixels per pixel shown level (to make antialias work)

    the grammar of graphics approach really is a great abstraction, and I'd love to see xy work in that direction

    by hantusk