implement prior generation
This MR implements parsing a mixture of specified priors, fixed parameters and then adding in defaults.
There's a new function in prior.py
and a couple of changes to run_sampler.py
.
An example of the new usage is shown in BasicTutorial.py
and Injection.py
.
Thoughts @paul-lasky @gregory.ashton @moritz.huebner?
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I'm afraid I'm not a fan of having 'fixed_parameters' and 'priors', I don't see why they need to be separated. From a 'big picture' point of view, they are not different, one is just a delta function, the other is something else (i.e. uniform or Gaussian etc). One a pragmatic level, if I want to quickly fix a parameter and rerun something, I now have to add it to a list of fixed parameters which takes longer and is more error prone. Sorry if I'm missing something.
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@gregory.ashton does this look better? It also has the ability to remove junk (waveform approximant strings) that happen to have been left in the prior.
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- 87151c7e - update syntax in Injection.py tutorial
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- 33059813 - Merge branch 'fill_prior' of git.ligo.org:Monash/peyote into fill_prior
- 40937470 - fix fill_priors to deal with bad waveform generator variables
- 82cf5813 - add function to write prior distribution to file
- 8ae58ed7 - make sampler write the prior to file
- 0fd899cf - update Injection tutorial to new prior interface
Toggle commit listThe changes in
prior.py
are now pretty extensive, including some changes to the names of parameters of prior models, most notably,PowerLaw
andUniform
.@gregory.ashton or @paul-lasky can this be merged in?
This now fills in the prior and also adds functionality to print the prior to file and does this before starting the sampler.
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enabled an automatic merge when the pipeline for 1041a950 succeeds
enabled an automatic merge when the pipeline for 8828f254 succeeds
mentioned in commit a92343dc