Open skhrg opened 6 months ago
Can we get an update on this @skhrg ?
Had a student work on this over the summer and by jove it worked! I'd like to have him clean up and speed up the code before its ready for others to run but I'll send you his poster on slack.
Mostly just a looming todo item for me so that I can feel ok about putting this on the back burner and work on more pressing things.
Finding jumps with a matched filter seems to mostly work but there are some issues namely:
But wavelets make a lot of sense here since they are good at dealing with these sorts of localized features.
A naive attempt of looking at the CWT with a
gaus1
wavelet seems to work well, but CWTs are probably more expensive than we need. This paper uses a DWT dydatic scales and seems to be the basis of a lot of modern approaches (though I cannot find a python implementation of the wavelet they use). This paper is a good followup with more information about dealing with noise.Regardless of the exact technique used I think my takeaway is that using methods like this to then get an estimate of the Lipshitz regularity would be a very powerful technique in our flagging toolkit (since that also get us glitches at the same time but in a way where we know what is what). This paper is a good overview of estimating alpha.
I can imagine two modes here that we could use:
Overall I think that these sorts of wavelet techniques have the potential to be the final boss of giltch and jump flagging and merit a detailed look (the literature on this specific application seems deep). Will try to get something worthy of a PR cobbled together in the coming weeks.