Question regarding `gp.conditional` and `gp.prior`

I think this is because you fit the model with compiled_gp_model and then are generating conditionals with gp_model, which would explain why the conditionals look like they are coming from a prior. Try fitting the model with:

with gp_model:
    idata = pm.sample(chains=2, nuts_sampler="nutpie")

And see if things look any better.

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