Fastplotlib: GPU-accelerated, fast, and interactive plotting library

Re:Fastplotlib: GPU-accelerated, fast, and interactive plott... by wtallis on Tuesday March 11, 2025 @02:55PM (#43335835)

> 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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Re:Fastplotlib: GPU-accelerated, fast, and interactive plott... by fpl-dev on Tuesday March 11, 2025 @04:21PM (#43336607)

Exactly that's a good example!

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Re:Fastplotlib: GPU-accelerated, fast, and interactive plott... by mturmon on Tuesday March 11, 2025 @06:20PM (#43337723)

I agree, but: the technique of “singular spectrum analysis” is pretty much PCA applied to a covariance matrix resulting from time-lagging the original time series. (https://en.wikipedia.org/wiki/Singular_spectrum_analysis)

So this is not unheard of for time series analysis.

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