4 ms·

> it's about creating a data structure that allows you to quickly answer queries with which to build visualizations Hm, I see, so this can output the virtual m

by pyalot2 13y ago

> it's about creating a data structure that allows you to quickly answer queries with which to build visualizations Hm, I see, so this can output the virtual miplevels quickly? Also, would it work with a "full" dataset (i.e. no empty cells)? > About your interpolation point: yes, we could (and do sometimes) use interpolation and smoothing. Also consider miplevel interpolation, makes the transitions between levels much easier on the eye (doesn't work well with nearest sampling).

cscheid 13y ago
> Hm, I see, so this can output the virtual miplevels quickly? Yes: when you see the tiles on (say) http://www.nanocubes.net/view.html#twitter http://www.nanocubes.net/view.html#twitter, what you're getting is not a precomputed tile: the server is actually visiting the datastructure every time (and I hope I can convince you that at that speed, it is not touching 210 million points :). The reason you can't precompute all choices is simply that there's too many of them and you'd run out of bits in the universe (the paper, http://www.nanocubes.net/assets/pdf/nanocubes_paper.pdf http://www.nanocubes.net/assets/pdf/nanocubes_paper.pdf, has details). > Also, would it work with a "full" dataset (i.e. no empty cells)? Not exactly. We get away with an in-memory data cube exactly because in many practical cases the data is sparse over the address space. With dense data you'll take a much more significant memory hit (but it's one you'll have to take with any aggregation scheme. The paper, again, has details) > Also consider miplevel interpolation, makes the transitions between levels much easier on the eye (doesn't work well with nearest sampling). That's fair, although again we're hoping to keep the WebGL version feature-compatible with the leaflet.js version (that does canvas-only, and has no zoom transition at all); the smooth version looks nicer, as you can see in the (bit on the PR-heavy side, sorry) following video https://www.youtube.com/watch?v=8P9QA6TJwys#t=69 https://www.youtube.com/watch?v=8P9QA6TJwys#t=69

by pyalot2 13y ago

cscheid 13y ago

> Hm, I see, so this can output the virtual miplevels quickly? Yes: when you see the tiles on (say) http://www.nanocubes.net/view.html#twitter http://www.nanocubes.net/view.html#twitter, what you're getting is not a precomputed tile: the server is actually visiting the datastructure every time (and I hope I can convince you that at that speed, it is not touching 210 million points :). The reason you can't precompute all choices is simply that there's too many of them and you'd run out of bits in the universe (the paper, http://www.nanocubes.net/assets/pdf/nanocubes_paper.pdf http://www.nanocubes.net/assets/pdf/nanocubes_paper.pdf, has details). > Also, would it work with a "full" dataset (i.e. no empty cells)? Not exactly. We get away with an in-memory data cube exactly because in many practical cases the data is sparse over the address space. With dense data you'll take a much more significant memory hit (but it's one you'll have to take with any aggregation scheme. The paper, again, has details) > Also consider miplevel interpolation, makes the transitions between levels much easier on the eye (doesn't work well with nearest sampling). That's fair, although again we're hoping to keep the WebGL version feature-compatible with the leaflet.js version (that does canvas-only, and has no zoom transition at all); the smooth version looks nicer, as you can see in the (bit on the PR-heavy side, sorry) following video https://www.youtube.com/watch?v=8P9QA6TJwys#t=69 https://www.youtube.com/watch?v=8P9QA6TJwys#t=69