-
Notifications
You must be signed in to change notification settings - Fork 24
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Adds Monte Carlo Samplers #340
Conversation
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## develop #340 +/- ##
===========================================
+ Coverage 98.76% 98.79% +0.03%
===========================================
Files 48 52 +4
Lines 3153 3581 +428
===========================================
+ 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
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
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:
Thank you for contributing to our project! Your efforts help us to deliver great software.