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" Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something. " https://news.ycombinator.com/newsguidelines.html
Nice, i'd be interested to know which method for drawing lines (which is hard [0]) it uses. [0] https://mattdesl.svbtle.com/drawing-lines-is-hard
https://almarklein.org/triangletricks.html
https://almarklein.org/line_rendering.html
A big shader refactor was done in this PR: https://github.com/pygfx/pygfx/pull/628
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Aren't you missing the entire point of exploratory data analysis? Eigenfaces are an example of what you can come up with as the end product of your data exploration, after you've tried many ways of looking at the data and determined that eigenfaces are useful. Your whole third paragraph seems to be criticizing the core purpose of exploratory data analysis as though one should always be able to skip directly to the ne…
As a whole, of course you have a point - big visualisations when done properly should help with data exploration. However, from my experience they rarely (but not never) do. I think it's specific to the type of data you work with and the visualisation you employ. Let me give an example. Imagine we have some big data - like an OMIC dataset about chromatin modification differences between smokers and non-smokers. Genom…
Re: wtallis, I think my original complaint about EDA per se is indeed off the mark.
Certainly creating a 20x20 grid of live-updating GPU plots and visualizations is a form of EDA, but it seems to suggest a complete lack of intuition about the problem you're solving. Like you're just going spelunking in a data set to see what you can find... and that's all you've got; no hypothesis, no nothing. I think if you're able to form even the meagerest of hypotheses, you should be able to eliminate most of these visualizations and focus on something much, much simpler.
I guess this tool purports to eliminate some of this, but there is also a degree of time-wasting involved in setting up all these visualizations. If you do more thinking up front, you can zero in on a smaller and more targeted subset of experiments. Simpler EDA tools may suffice. If you can prove your point with a single line or scatter plot (or number?), that's really the best case scenario.
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I've also worked on designing new matrix decompositions, and I've never found the need for anything but `imshow`...
ok, different libraries have different use cases, the type of data we work with absolutely necessitates dynamic visualization. You wouldn't view a video with imshow would you?
It's hard for me to imagine what you're doing that necessitates such fancy tools, but I'm definitely interested to learn! My failure of imagination is just that.
Very cool effort. That said, and it's probably because of the kind of work that I do, but I have almost never found the four challenges to be any kind of a problem for me. Although I do think there is some kind of contradiction there. Plotting (exploratory data analyis ("EDA"), really) is all about distilling key insights and finding features hidden in data. But you have to some kind of intuition about where the need…
I agree with you sfpotter, very interesting. Looks in some ways similar to PyQtGraph regarding real time plotting. I agree with you regarding matplotlib, although I find a lot of faults/frustration in using it. Both your points on 3D plotting and WYSIWYG editor would be extremely nice and as far as I know nothing exists in python ticking these marks. For 3D I typically default to Matlab as I've found it to be the mos…
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ok, different libraries have different use cases, the type of data we work with absolutely necessitates dynamic visualization. You wouldn't view a video with imshow would you?
Every time I've needed to scrub through something in time like that, dumping a ton of frames to disk using imshow has been good enough. Usually, the limiting factor is how quickly I can generate a single frame. It's hard for me to imagine what you're doing that necessitates such fancy tools, but I'm definitely interested to learn! My failure of imagination is just that.
I think a killer feature of these gpu-plotting libraries would be if they could take torch/jax cuda arrays directly and not require a (slow) transfer over cpu.
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Eigendecomposition of the covariance matrix, essentially PCA, is probably the first non-trivial step in the analysis of any dataset. The idea in the comment above seems to be that it's more useful to combine some basic knowledge of statistics with simpler visualisation techniques, rather than to quickly generate thousands of shallower plots. Being able to generate thousands of plot is useful, of course, but I would a…
> Eigendecomposition of the covariance matrix, essentially PCA, is probably the first non-trivial step in the analysis of any dataset For a sufficiently narrow definition of "dataset", perhaps. I don't think it's the obvious step one when you want to start understanding a time series dataset, for example. (Fourier transform would be a more likely step two, after step one of actually look at some of your data .)
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" Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something. " https://news.ycombinator.com/newsguidelines.html
I appreciate the warning and if it's not by claude I apologize, but I do think we should be allowed to express scepticism if things posted are just AI slop (and if we have to fear getting banned or what-have-you as a consequence I genuinely think that's worse for HN long term than the alternative).
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In the browser only jupyter for now, you can use voila to make a server based application using jupyter: https://github.com/voila-dashboards/voila As Caitlin pointed out below pyodide is a future goal.
This is very nice. But thinking more along the lines of, can I embed a single interactive widget in a blog post.