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hey david
nice to have someone in same boat. thanks!
yes we had draw one using d3js for kmeans clusters using that example including zoom and select box but when reaching 20k plots it slows down in frame rate.
so we planning to change rendering from svg to webgl.
wow that huge amount of data is what you plot in d3js?or non js lib?how much it slows for you?
hi mark
what is vega?js lib?
3secs means both generation and rendering?how many points in total? i must be doing something wrong. with my graph it is only kmeans document clustering of and scatterplot of 20000 points making browser sluggish.
we are slowing at 20k so something is off . it is just 20k * 1
i found it but only have canvas vs svg right?from looking from description.webgl is faster tho.
i am doing with sklearn python. but the prob is serverside
urhg.i meant browser side not server
A lot of the power of d3 is binding to the DOM, which has performance limits for elements in the hundreds or few thousands. You probably want to avoid this part of d3 for these applications, but you can still use many other powerful pieces of d3 to assist you with webgl.
You can use scales to map your data into spatial and color dimensions. This is pure javascript and shouldn't be slow at those numbers.
You could also use the brush component or zoom behavior, simply layer it over the top of your webgl visualization using the same scales.
D3 is like a toolbelt for making data visualizations with web standards, it is at its most elegant when using SVG, just keep in mind you can mix and match the standards and the tools!
yeah sorry it is just comparisons between d3svg vs webgl pixi vs kinetic canvas
can you give me link of mike's experiment?
we are testing with pixijs and threejs
webgl2d with textures implementation of pixi is alot faster than svg but threejs partical system is very fast. we plot 500000 particles without dropping a frame.
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