raptop changed the topic of #kspacademia to: https://gist.github.com/pdn4kd/164b9b85435d87afbec0c3a7e69d3e6d | Dogs are cats. Spiders are cat interferometers. | Космизм сегодня! | Document well, for tomorrow you may get mauled by a ネコバス. | <UmbralRaptor> egg|nomz|egg: generally if your eyes are dewing over, that's not the weather. | <ferram4> I shall beat my problems to death with an engineer. | We can haz pdf
<UmbralRaptor> What's two and a half orders of magnitdue between friends?
<UmbralRaptor> *magnitude
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<egg|cell|egg> Bofh: uncertainty, see backlog
<bofh> egg|cell|egg: yeah, I'm still trying to meaningfully figure this out :P
<UmbralRaptor> Silly thought: sampling 'densely' over the time series, what a histogram of semi-major axis, etc look like?
<egg|cell|egg> Bofh: well have you found any interesting papers or something https://mobile.twitter.com/bofh453/status/1087800873609244672
<kmath> https://twitter.com/bofh453/status/1087800873609244672 <bofh453> I feel *extremely painfully* called out. ⏎ ⏎ Like seriously I wish my damn perfectionism would fuck off, it's genuinel… https://t.co/WflraziDA2
<bofh> 03:53:57 <@UmbralRaptor> Silly thought: sampling 'densely' over the time series, what a histogram of semi-major axis, etc look like?
<bofh> Good question, actually.
<egg|cell|egg> UmbralRaptor: how densely
<egg|cell|egg> Here I'm looking at apsidal period, so one sample per Pe
<UmbralRaptor> If you have a lot of orbits, that's fine. (Enough to provide some resolution for at least 5 bins?)
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<egg|zzz|egg> UmbralRaptor: here I have > 4000 orbits https://i.imgur.com/SAgBNRi.png
<egg|zzz|egg> UmbralRaptor: but how do I turn that into an uncertainty on the mean, histogram or not
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<egg|laptop|egg> UmbralRaptor: is adsabs down?
<egg|laptop|egg> seems to be, thankfully there's http://cdsads.u-strasbg.fr/cgi-bin/nph-bib_query?1996AJ....111..541F which is up
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<UmbralRaptor> seems to be down here
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<egg|zzz|egg> UmbralRaptor: okay now it seems to be failing over to strasbourg
<egg|zzz|egg> which then 500s with "Please contact the server administrator, root@localhost"
<UmbralRaptor> aaaaaaaaa
<egg|zzz|egg> ;seen bofh
<kmath> egg|zzz|egg: bofh (bofh!~freebsd@138.68.64.246) was last seen posting in #kspacademia at 2019-01-24 03:59:08 +0000
<egg|zzz|egg> UmbralRaptor: so what do you want to do with a histogram
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<bofh> meow
<UmbralRaptor> egg|zzz|egg: try to better understand the distribution of values.
<egg|zzz|egg> UmbralRaptor: weird? https://i.imgur.com/fs3MQ8K.png
<UmbralRaptor> … yeah, that's weird
<bofh> egg|zzz|egg: what the hell, that's weird.
<egg|zzz|egg> bofh: well it looks like https://i.imgur.com/SAgBNRi.png, so do you eggspect a normal distribution
<bofh> point, nope.
<bofh> uniformly distributed makes sense, actually.
<egg|zzz|egg> bofh: so eggsperimenting with sums of sinusoids, um
<egg|zzz|egg> bofh: the stackoverflow formula, but up to lag n/4 instead of sqrt n, and with an absolute value in front of the sum to avoid negative variance (??) seems to work Ꙩ_ꙩ
<egg|zzz|egg> well, it still overestimates the error eventually, but less so?
<egg|zzz|egg> also it makes no sense
<egg|zzz|egg> moo
<bofh> HUH.
<bofh> That makes *absolutely* no sense, what the hell.
<UmbralRaptor> I mean, at this timescale, it's not all that stochastic?
<egg|zzz|egg> bofh: it does nicely dip when the sample size aligns with the period though :-p
<egg|zzz|egg> not that anything makes sense,
<egg|zzz|egg> bofh: 1993MNRAS.263..287K seems to have stuff involving fourier magic to estimate some manner of standard deviation but I'm not sure 1. whether it's applicable 2. how it works
<egg|zzz|egg> if you like DOIs more than adsabs codes
<egg|zzz|egg> 10.1093/mnras/263.2.287
<egg|zzz|egg> (I do not have a catpic with this paper, sorry)
<egg|zzz|egg> bofh: meow
<egg|zzz|egg> UmbralRaptor: well, it's all going to be a combination of periodic effects at any timescale (not sure what this is, it doesn't look like a year, maybe kozai?)
<egg|zzz|egg> UmbralRaptor: but I want to estimate its mean :-/
<bofh> 20:35:17 <@egg|zzz|egg> bofh: 1993MNRAS.263..287K seems to have stuff involving fourier magic to estimate some manner of standard deviation but I'm not sure 1. whether it's applicable 2. how it works
<bofh> I'm trying to figure out 2. right now, moment.
<egg|zzz|egg> meow
* egg|zzz|egg meows repeatedly at bofh's door
<bofh> adsabs is kinda sketchy for me atm? keep getting root@localhost errors
<bofh> plz to kidnap me to FR or something ;_;
<kmath> <✔Alex_Parker> We got our first high-resolution MVIC panchromatic image of 2014 MU69 down. With a little deconvolution magic, it i… https://t.co/MpFHNHC8p4
<SnoopJeDi> HELLO BEAUTIFUL
<UmbralRaptor> Cubewano!
<egg|zzz|egg> bofh: try strasbourg
<egg|zzz|egg> bofh: for adsabs
<egg|zzz|egg> bofh: http://cdsads.u-strasbg.fr/
<egg|zzz|egg> bofh: harvard seems to be flaky
<egg|zzz|egg> bofh: is Strasvard like Nancago
<bofh> LOL
<bofh> and yeah, strasbourg works.
<egg|zzz|egg> meow
<egg|zzz|egg> bofh: okay, on my test sum of sinusoids, Sqrt@Total[(Abs[Fourier[#][[;; 3]]])^2/Length[#]]& is a really good and tight majoration of the error of the mean??? Ꙩ_ꙩ
<egg|zzz|egg> bofh: (vaguely inspired by that paper)
<egg|zzz|egg> even ;;2
<egg|zzz|egg> hmmm
<egg|zzz|egg> wait with ;;1 it's eggsactly the absolute value of the mean, maybe my test vector is too regular,
<egg|zzz|egg> yeah nevermind
<egg|zzz|egg> ah derp I thought I was doing 2;;, but yes, taking the mean is taking the mean, news at 11
<egg|zzz|egg> hmmmm, Sqrt[Total[Abs[Fourier[#][[2 ;; 10]]]]/Length[#]] (i.e. low frequencies) does behave decently?
<egg|zzz|egg> (other values of 10 are available)
<bofh> 22:06:10 <@egg|zzz|egg> bofh: okay, on my test sum of sinusoids, Sqrt@Total[(Abs[Fourier[#][[;; 3]]])^2/Length[#]]& is a really good and tight majoration of the error of the mean??? Ꙩ_ꙩ
<bofh> WHAT THE HELL that doesn't *make* any sense?
<egg|zzz|egg> bofh: no it does if the mean is 0, because it's the mean + 2 terms of the Fourier eggspanson
<egg|zzz|egg> bofh: more interesting is the 2;;10
<egg|zzz|egg> i.e. drop the mean, take low frequencies
<egg|zzz|egg> I feel like I'm missing a square somewhere compared to the Koen Lombard paper
<egg|zzz|egg> 2;;5 is OK tbh
<egg|zzz|egg> bofh: tbh just the 2nd term of the DFT seems to do the job?? Ꙩ_ꙩ
<bofh> I mean the first term of the DFT would be your input mean, the second term would... I'm not sure how to describe it but that makes *sense* to me intuitively.
<egg|zzz|egg> bofh: the terms are related to the autocorrelation function by (2) in Koen Lombard
<bofh> Ahh, right, that makes sense.
<egg|zzz|egg> bofh: and then you have (19) that seems like dark magic
<bofh> I'm still not sure I understand (19) at all.
<egg|zzz|egg> I think (19) gets mentioned in 1996AJ....111..541F in the context of what I'm trying to do
<egg|zzz|egg> bofh: you'll like 1996AJ....111..541F, it does stats with braket notation
<egg|zzz|egg> cc UmbralRaptor
<bofh> okay I actually strongly approve of that.
<egg|zzz|egg> bofh: look at the paragraph after the one containing (5.4) in 1996AJ....111..541F, that's where they cite Koen and Lombard (and how I found the latter)
<bofh> sec, opening
<UmbralRaptor> !?
<egg|zzz|egg> UmbralRaptor: the mean is just the projection on |1>
<bofh> holy fuck this is actually *readable*
<bofh> YES
<egg|zzz|egg> bofh: but then there's a part II to that paper, where he does basically the same paper but in---galaxy brain---tensor index notation
<bofh> augh please no
<egg|zzz|egg> bofh: index notation is good actually
<egg|zzz|egg> that's in 1996AJ....111..555F
<egg|zzz|egg> bofh: from the abstract: "It is quite convenient for distinguishing a variety of different vector spaces, and is the most compact notation for all the sums which arise in the analysis."
<egg|zzz|egg> bofh: but anyway, there's something going on between (4.5) from Foster and (19) from Koen and Lombard
<bofh> Yeah, let me grab my copy of Koen and Lombard first
<egg|zzz|egg> bofh: by the way, how do i compute the 2nd coefficient of the Fourier transform
<egg|zzz|egg> I hear there is a fast fourier
<SnoopJeDi> LOL
<bofh> I'm uncertain there's a faster way than just doing FFT and grabbing the second element, at least for large data
<bofh> LOL
<egg|zzz|egg> bofh: how does FFT work
<egg|zzz|egg> how is FFT formed
<SnoopJeDi> inner products \o/
<egg|zzz|egg> SnoopJeDi: https://twitter.com/mrkgrnao/status/1057980486549524483 Poisson has better puns
<kmath> <mrkgrnao> There's a MathOverflow comment about how the correct name for a morphism of Poisson manifolds is obviously "ichthyo… https://t.co/QcMS0wNmIc
<SnoopJeDi> Yea, agreed
<SnoopJeDi> especially if 'boisson' is fair game
<bofh> Wait, 'Boisson'? :p
<SnoopJeDi> oh, I didn't realize it was a surname too
<egg|zzz|egg> bofh: drink
<bofh> I mean I know, I'm just wondering where it was used in the context of Poisson Geometry.
<SnoopJeDi> I wasn't thinking of anything in particular, I just always tie the two together mentally
<SnoopJeDi> I guess because fish <> water <> drink
<egg|zzz|egg> Twitter truncations of adsabs links look silly....…
<egg|zzz|egg> SnoopJeDi: "distribution de poissons" certainly sounds weirder than "distribution de boissons"
* egg|zzz|egg hands out fish and drinks
<SnoopJeDi> egg|zzz|egg, btw did you hear about the new French fish sauce company using novel statistics to responsibly manage their fishing practices?
<SnoopJeDi> boisson poisson: Poisson moisson de poisson
<egg|zzz|egg> but Poisson isn't an adjective (and adjectives aren't generally prefix anyway), it's poissonien(ne) or de Poisson
<SnoopJeDi> yea I figured I'd probably screwed that one up but had already sunk too much into forcing it as it was
<egg|zzz|egg> :D
<SnoopJeDi> would "moisson de poisson de Poisson" be sensible, or would "moisson poissonien de poisson" be more idiomatic?
<egg|zzz|egg> <egg|zzz|egg> bofh: but anyway, there's something going on between (4.5) from Foster and (19) from Koen and Lombard << that would be (5.4), not 4.5
<egg|zzz|egg> SnoopJeDi: moisson is feminine, so it would be a moisson poissonienne
<egg|zzz|egg> which really sounds like Groethendieck got into stats
<egg|zzz|egg> where are the sheathes
<SnoopJeDi> bah, I never was much of a gambler
<egg|zzz|egg> Grothendieck*
<egg|zzz|egg> sheaves*
<egg|zzz|egg> bofh: so assuming τ^2 in (5.4) is S0(ε) from (19) and above, what is r in the sense of (5.4) if I pick only one frequency (the 2nd coefficient), is it 2 or 1
<egg|zzz|egg> hm i guess it's 1 because I'm only modeling the mean, and the number of frequencies I pick is how I estimate τ^2, not a different basis
<egg|zzz|egg> bofh: if I'm only computing one coefficient of the dft, isn't it easier to do so naively from the definition? I don't see what I gain from the fft algorithms there
<egg|zzz|egg> bofh: i.e. why do it in n log n then eggstract one coefficient that I could have computed in n
<egg|zzz|egg> bofh: meeeeoooow