Repository navigation
Conversation
Passing a list as the `acq_noise_var` argument of `elfi.BOLFI` in the RTD example results in an error: ``` ValueError: Either acquisition noise is a float or it is a dictionary of floats defining variance for each parameter dimension. ``` This commit changes the input from a list to a dict.
Fix requirements
* remove copy override * update changelog
* Update CHANGELOG * Pass maxiter to scipy.optimize.minimize
* Add arviz-dependency to requirements * Include InferenceData-object to results * Fix 085 (#465) * add __init__.py to elfi/methods/bsl/ * Update CHANGELOG.rst * Bump version (#466) * Clean up inference data-object wrapper * Update CHANGELOG * Fix typo * Update info on supported Python versions. * Fix error caused by new version of numpy * Enable maxiter option * Remove forgotten print-commands * Remove arviz-elements * Remove arviz dependency * Include setuptools in requirements
* sample randmaxvar batches * sample candidate initial points from prior * update changelog * fix whitespace error * update sampling candidate points * fix maxvar initialisation --------- Co-authored-by: Henri Pesonen <henri.e.pesonen@gmail.com>
* Add changelog-description * Add arziv-mocking for rtd build
* add adjusted acquisition factory * add tests * fix class type * fix class type * rename adjusted acquisition class
* copy kernel * update changelog * update matplotlib version --------- Co-authored-by: Henri Pesonen <henri.e.pesonen@gmail.com>
* make mcmc sample return idata with chains * update sample class name * update changelog
* update target model initialisation * update changelog --------- Co-authored-by: Henri Pesonen <henri.e.pesonen@gmail.com>
* extend surrogate model with a classifier * fix acquisition gradients * add tests * fix initialisation with zero samples * update tests * update changelog * fix zero division problem * restore target model initialisation make this a separate pull request since it solves an unrelated issue. the initialisation issue becomes more acute in the failure-robust model but it still takes a bad seed for initialisation to fail * update visualisation and returned evidence update plot gp to mask non-finite evidence so that the robust model does not need to filter these out * update tests * update tests --------- Co-authored-by: Henri Pesonen <henri.e.pesonen@gmail.com>
Co-authored-by: hpesonen <33959025+hpesonen@users.noreply.github.com>
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
0.8.8 (2026-10-08)
numpy >= 2.0arziv-mocking to rtd-setupInferenceData`` to be used witharviz`randmaxvarbatch acquisitions and initialisation by enabling sampling from priormaxiterinbo.utils.minimize