Consider whether exoplanet should use DensityDist rather than Potential

PyMC3 recommended way to include a custom likelihood function is with pm.DensityDist, e.g.

loglike = pm.DensityDist('loglike', logp, observed=y)

However in the exoplanet examples, the the GP likelihood is implemented as pm.Potential. The results are the same but it might be sensible to implement the samples using the standard PyMC3 way of doing it. Advantages include clear separating out of the observables. Additionally, some of the nice plotting functions like model_to_graphviz ignore potentials.

Here’s an example of what it would look like

pm.DensityDist("loglike", gp.log_likelihood, observed=(y - light_curve - mean))

[dfm]

@bmorris3: There shouldn’t be any issue with that syntax, but a simpler one might be:

pm.Normal("spitzer_depth_prior", mu=spitzer_depth, sigma=300, observed=0.0)

Which should work equivalently and I find somewhat more readable. (You can think of this “prior” as, instead, “data” from a previous experiment.)

[bmorris3]

Thanks for this, that’s definitely more readable!