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Perfect Nested Sampling: Gaussian Likelihood and Gaussian Priors #371

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Description

This PR implements a Gaussian prior x Gaussian likelihood perfect nested sampling run with an analogous strategy to the uniform prior x Gaussian Likelihood, namely a two-phase prior/constrained likelihood sampling that switches over, sufficing in low (<10) dimensions to produce a perfect nested sampling run.

Fixes # (issue)

Checklist:

  • I have performed a self-review of my own code
  • My code is PEP8 compliant (flake8 anesthetic tests)
  • My code contains compliant docstrings (pydocstyle --convention=numpy anesthetic)
  • New and existing unit tests pass locally with my changes (python -m pytest)
  • I have added tests that prove my fix is effective or that my feature works
  • I have appropriately incremented the semantic version number in both README.rst and anesthetic/_version.py

@williamjameshandley williamjameshandley marked this pull request as draft March 13, 2024 23:14
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codecov bot commented Mar 13, 2024

Codecov Report

Attention: Patch coverage is 25.71429% with 26 lines in your changes are missing coverage. Please review.

Project coverage is 99.15%. Comparing base (54170d8) to head (3870183).

Files Patch % Lines
anesthetic/examples/perfect_ns.py 23.52% 26 Missing ⚠️
Additional details and impacted files
@@             Coverage Diff             @@
##            master     #371      +/-   ##
===========================================
- Coverage   100.00%   99.15%   -0.85%     
===========================================
  Files           36       36              
  Lines         3043     3073      +30     
===========================================
+ Hits          3043     3047       +4     
- Misses           0       26      +26     

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