The posterior predictive checks in hierarchical_likelihood() assume mass_1 and mass_ratio are present in pedata and injdata, e.g.,
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if posterior_predictive_check: |
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if param_names is not None and injdata is not None and pedata is not None: |
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pe_weights = jnp.exp(logpe_weights) |
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inj_weights = jnp.exp(loginj_weights) |
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cond = jnp.less(pedata["mass_1"], m1min) | jnp.greater(pedata["mass_1"], mmax) |
which shouldn't be required.
The posterior predictive checks in
hierarchical_likelihood()assumemass_1andmass_ratioare present inpedataandinjdata, e.g.,GWInferno/gwinferno/pipeline/analysis.py
Lines 380 to 384 in 4460e22
which shouldn't be required.