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Adds Monte Carlo Samplers #340
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## develop #340 +/- ##
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+ Coverage 98.76% 98.79% +0.03%
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Files 48 52 +4
Lines 3153 3581 +428
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+ Hits 3114 3538 +424
- Misses 39 43 +4 ☔ View full report in Codecov by Sentry. |
This is ready for a first review. There is a bit more work to do on integration testing for the slower convergence samplers, as well as integrating #357. I believe this PR is in a good state to be integrated into develop, with subsequent PRs improving the design structure and robustness all around. |
# Conflicts: # CHANGELOG.md
# Conflicts: # CHANGELOG.md
…dfS1, suggestions from review
…potential thread deadlock in optimisation_options test
… now optional arg with default=1
# Conflicts: # CHANGELOG.md
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Looks good, just some small comments
# Conflicts: # CHANGELOG.md
…imensions bugfix for single parameter inference
Description
Adds Pints-based Monte Carlo samplers. The full list of composed samplers can be found here.
This PR includes a base sampling class
BaseSampler
, of whichPintsBaseSampler
is a child. The Pints MCMC samplers are composed of PyBOP classes, which are constructed withinPintsBaseSampler
. This follows a similar structure to theBasePintsOptimiser
class. A genericMCMCSampler
class is included for use as a default, which is conceptually aligned with theOptimisation
class.Additions to the Priors class include the
JointLogPrior
.Two additional PR's will be chained around this one. The order of merge should be:
Issue reference
Fixes #6
Review
Before you mark your PR as ready for review, please ensure that you've considered the following:
Type of change
Key checklist:
$ pre-commit run
(or$ nox -s pre-commit
) (see CONTRIBUTING.md for how to set this up to run automatically when committing locally, in just two lines of code)$ nox -s tests
$ nox -s doctest
You can run integration tests, unit tests, and doctests together at once, using
$ nox -s quick
.Further checks:
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