feat: Add decentering parameterization and decentering+cw capabilities#107
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meyers-academic wants to merge 15 commits into
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feat: Add decentering parameterization and decentering+cw capabilities#107meyers-academic wants to merge 15 commits into
meyers-academic wants to merge 15 commits into
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… block matrices in signals.py
ArrayLogL wraps a dict-based likelihood so JIT/grad see a single array leaf instead of a ~136-key parameter dict, avoiding the per-leaf pytree marshalling that dominates GPU forward/grad time. Exposed as .loglike_arr on PulsarLikelihood, GlobalLikelihood, and ArrayLikelihood. sample_uniform and makelogprior_uniform gain an array=True flag producing/consuming the matching flat layout; the dict-based logprior now reduces array-valued parameters to a scalar. Tests: ArrayLogL cases in test_likelihood.py, new test_prior.py for the array prior path. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
… the likelihood slowing things down.
… being required for the whole package.
# Conflicts: # src/discovery/likelihood.py # src/discovery/params.py
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…ge. sneaking in the change now.
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Add decentering transformation to
ArrayLikelihood.clogL. This is not quite complete. Task list below. But it's ready for people to look at.If you supply a correlated model, the decentering will ignore the correlations so that it can be vectorized across pulsars.
make_kernelproduct_gpcomponentso that we can also sample CWs (need to be careful of order if decentering is included. decentering should be applied first)meansin thecommongpto create a transformation that implements the CWs.