I’m currently using BayesWave for analysis of simulated supernova gravitational waveforms and am wondering how I add a source location to the simulated data? I am not sure whether this is something I do through BayesWave or separately before injecting the signal using something like the ‘Projecting a Signal into the Detector Frame’ code from PyCBC. Would anyone be able to help?
What I would suggest doing is the “MDC-style” injections. In this case you make .gwf frames that contain the signal (with no added noise) projected into the detectors. I think that should be pretty straightforward with pycbc or gwpy. Then you can feed those frames to BayesWave and add the signal to either real or simulated data. Some examples of how to do that with BW can be found here: Burst style MDCs — BayesWave 0.1 documentation
Thank you so much for the response! I have been able to generate .gwf files and put them through BayesWave, I’m just not sure how to ‘give’ the waveform a source location. I’ve tried using the project_wave function in pycbc but that doesn’t seem to give me accurate results when analysing in Bayeswave. I assume I’ve misunderstood the process/missed a step perhaps?
Ah ok I might have misunderstood the question. Just to clarify, do you mean:
- how to make the .gwf frames from a given location? (If this is the question I’d probably have to pass it off to someone who’s more familiar with pycbc)
- How to tell BayesWave to only look at one point in the sky?
- How to get the sky location from BayesWave output?
or something else?
So sorry if my question was confusing! I do mean your first point.
I unfortunately don’t know off the top of my head the best way to do that, I bet it’s doable with either pycbc or gwpy though. I’ll see if I can find something!
Thank you for helping me! I have found a paper that did a very similar project to mine and have emailed the author for guidance, will let you know if I hear back from them.