Write a `particles` visualization demo using point-in-polygon
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- Dominant language
- TypeScript
- Stars
- 211
- Forks
- 29
- Avg merge
- 17h 30m
- Merged PRs (30d)
- 1
Description
We've been planning for a while to build a pip demo that uses index buffer objects and a viewport specified as a polygon for pip culling. This issue describes that project:
A web application is loaded that queries the api-server GPU backend to load a dataset onto GPU.
The api-server uses @rapidsai/cudf to load a large number of x,y point coordinates and metadata into a cudf.DataFrame.
The client app then queries for the points that contained in the current viewport and displays them.
It receives mouse events for scrolling and dragging that change the perspective on the displayed points, with a background image (or map) that translates and scales to match the GL geometry.
Whenever the perspective changes, the client requests an updated set of points from the original datasource, passing the current viewport coordinates to be used as a polygon.
api-server uses the viewport coordinates to cull the points with point-in-polygon before returning them over arrow.
https://github.com/rapidsai/node/issues/439#tasklist-block-78cf1f58-34c6-4e7b-a261-11ff5477a1f8
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the client application and api-server entry points for a particles visualization. Trace how the client sends viewport coordinates and how the server loads point coordinates with @rapidsai/cudf, performs point-in-polygon culling, and returns results over arrow. Done means an end-to-end demo supports scrolling and dragging, updates the viewport, and displays the returned points with a translating and scaling background image or map.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- nodejs, typescript
- Domain
- backend, data-visualization, web-dev
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100