Fix initial points sampling #156
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Replace #153 |
kazewong
reviewed
Sep 16, 2024
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| key, subkey = jax.random.split(key) | ||
| guess = self.prior.sample(subkey, self.sampler.n_chains) | ||
| guess = self.prior.sample(subkey, non_finite_index.sum()) |
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The guesses are not guaranteed to be finite, hence the original implementation. Please change it back
kazewong
reviewed
Sep 16, 2024
| @@ -558,14 +558,14 @@ def maximize_likelihood( | |||
| ): | |||
| parameter_names = prior.parameter_names | |||
| for transform in sample_transforms: | |||
| parameter_names = transform.propagate_name(parameter_names) | |||
| parameter_names = jax.vmap(transform.propagate_name)(parameter_names) | |||
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One does not need vmap for propagating the names
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Fix bug in
jim.sample()and use the same code forHeterodynedTransientLikelihoodFD.maximize_likelihood().