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Don't assume parameter presence in hierarchical likelihood #41

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@bfarr

The posterior predictive checks in hierarchical_likelihood() assume mass_1 and mass_ratio are present in pedata and injdata, e.g.,

if posterior_predictive_check:
if param_names is not None and injdata is not None and pedata is not None:
pe_weights = jnp.exp(logpe_weights)
inj_weights = jnp.exp(loginj_weights)
cond = jnp.less(pedata["mass_1"], m1min) | jnp.greater(pedata["mass_1"], mmax)

which shouldn't be required.

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