[ot-users] Functional curves

BAUDIN Michael michael.baudin at edf.fr
Wed Aug 9 10:37:05 CEST 2017


Hi all,

Here is an attempt at providing a PCA algorithm in OpenTURNS. I wrote it for Pamphile while we were working in the HDR algorithm.

Please use it with caution : the testing was rather fast and the implementation is quite slow, because of several for loop I could not remove.

I wrote it in order to make the algorithm written by Pamphile rely entirely on OpenTURNS. The main goal was not to avoid Sklearn, but rather to be able to integrate it into OT if later needed (and I think it will be needed soon).

While discussing with Pamphile, we were wondering if the current Karhunen-Love algorithm available in OT could be used in order to compute the PCA ?

Best regards,

Michaël

De : users-bounces at openturns.org [mailto:users-bounces at openturns.org]
Envoyé : mercredi 9 août 2017 09:17
À : users at openturns.org
Objet : Re: [ot-users] Functional curves


nice work!

the black curve is the median right ? I'm confused with the other 2 red ones.

j

________________________________
De : users-bounces at openturns.org<mailto:users-bounces at openturns.org> <users-bounces at openturns.org<mailto:users-bounces at openturns.org>> de la part de Pamphile ROY <roy at cerfacs.fr<mailto:roy at cerfacs.fr>>
Envoyé : mardi 8 août 2017 16:28:28
À : users
Objet : [ot-users] Functional curves

Hi everyone,

Thanks to Michaël Baudin's inputs, I have made a function which enables functional plots using openTURNS.
If you don't know this, it is useful when you have lots of 1D curves and you want to find the mean curve, outliers, etc.

Here is the GitHub:

https://github.com/tupui/HDR-Boxplot/tree/openTURNS

and in case, here is the reddit link:

https://www.reddit.com/r/Python/comments/6q6bgv/finding_median_curve_from_curves_hdr_boxplot/

The master branch is making heavy use of scikit-learn instead of OT. This choice is motivated by the speed and
by the ability to optimize easily the bandwidth (for kernel smoothing).

The openTURNS branch uses the class ot.KernelSmoothing and the function computeMinimumVolumeLevelSetWithThreshold.
Michaël has done some work for replacing the PCA's class from scikit-learn with OT. I will eventually get some time to integrate this (or someone can ;)).

Both branches are tested and slightly documented. Feel free to comment and even do pull requests :)

Cheers,

Pamphile ROY



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