!date

Tue May 11 05:08:27 PDT 2021

From Guillem Martí-Devesa guillem.marti-devesa@uibk.ac.at: sent: 5/7/2021 22:21 (PT) received: 5/8/2021 04:00 plots generated 5/8/2021 04:45

Hi Toby, Last year I read the work from Matthew and wanted to apply it to some binaries. May I try it on Eta Car? We are getting out a paper on it and could be interesting to see what results can we get with bayesian blocks on the periastron(s). Cheers, Guillem

from wtlike import WtLike, PointSource
source = PointSource('Eta Car')
source

Source "Eta Car" at: (l,b)=(287.597,-0.630)

Create the WtLike object with the source:

First time it takes ~10 min to extract the photon dataset, then make default 7-day cells for likelihood analysis.

wtl = WtLike(source)

SourceData: photons and exposure for Eta Car: Restoring from cache with key "Eta Car_data"
WtLike: Source Eta Car with:
	 data:     1,501,690  photons   from 2008-08-04 to 2021-05-06
	 exposure: 3,270,057 intervals  from 2008-08-04 to 2021-05-06
	 est. rates from weights: source 6.69e-08/s, background 4.15e-06/s, S/N ratio 0.02
CellData: Bin photon data into 665 1-week bins from 54683.0 to 59338.0
LightCurve: select 658 cells for fitting with e>0.5 & n>2

Make a weekly light curve for the 12 2/3 years.

wtl.plot();

Determine position of peak

wtl.fluxes.query('flux>5')

	t	tw	n	ts	flux	errors	limit
504	58214.5	7.0	4076	124.2	6.64	(-0.689, 0.696)	7.80
505	58221.5	7.0	6822	483.6	11.55	(-0.639, 0.644)	12.62
506	58228.5	7.0	9512	495.4	9.31	(-0.501, 0.504)	10.14
507	58235.5	7.0	5991	132.6	5.55	(-0.547, 0.551)	6.46

Make a plot around the peak

wtl.plot(tzero=58100, xlim=(0,200) );

Expand the scale

Make a daily view.

daily = wtl.view((58200, 58250, 1))
daily.plot();

CellData: Bin photon data into 50 1-day bins from 58200.0 to 58250.0
LightCurve: select 28 cells for fitting with e>0.5 & n>2