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bpd/likelihood.py

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@@ -16,7 +16,7 @@ def shear_loglikelihood_unreduced(
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# assume e_obs.shape == (N, K, 2) where N is number of galaxies, K is samples per galaxy
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# the priors are callables for now on only ellipticities
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# the interim_prior should have been used when obtaining e_obs from the chain (i.e. for now same sigma)
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# normalizatoin in priors can be ignored for now as alpha is fixed.
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# normalization in priors can be ignored for now as alpha is fixed.
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_, K, _ = e_post.shape # (N, K, 2)
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e_post_mag = jnp.sqrt(e_post[..., 0] ** 2 + e_post[..., 1] ** 2)

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