-
Notifications
You must be signed in to change notification settings - Fork 0
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
Priors/intermediate prior class #21
Draft
robbietuk
wants to merge
32
commits into
RDP/HessianVectorProduct
Choose a base branch
from
Priors/IntermediatePriorClass
base: RDP/HessianVectorProduct
Could not load branches
Branch not found: {{ refName }}
Loading
Could not load tags
Nothing to show
Loading
Are you sure you want to change the base?
Some commits from the old base branch may be removed from the timeline,
and old review comments may become outdated.
Draft
Priors/intermediate prior class #21
robbietuk
wants to merge
32
commits into
RDP/HessianVectorProduct
from
Priors/IntermediatePriorClass
Conversation
This file contains 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
* RDP accumulate_Hessian_times_input * Added RDP Hessian documentation * Add div by 0 safety * Add epsilon to Hessian function
Updates the math for the RDP
* RDP Documententation * QP use (off_)diagonal_second_derivative methods and documentation * Restructure RDP and QP Hessian logic * Improve RDP and QP documentation * Implement log cosh accumulate_Hessian_times_input in terms of derivatives * Documentation
* Add method get_is_convex(), which accesses prior is_convex parameter and only test convexity of priors if convex function * compute_Hessian method added to generalised prior and errors by default but with different messages depending on is_convex * Test rename and create test_Hessian_convexity and test_Hessian_methods * Add test for compute_Hessian * RelativeDifferencePrior initialisation call set_defaults * Modernise `compute_Hessian` for QP and LogCosh. Add `compute_Hessian` for RDP * Correct RDP second derivative functions * Major changes to test_Hessian_against_numerical, which loops over each voxel for perturbation response * Add verbosity suppression to suppress gradient info calls
Reenable PLS, but disable all numerical tests - just run setup.
Make is_convex() a pure virtual method in GeneralisedPrior to be implemented in each prior. FilterRoot is not convex as it does not have 0th or 2nd order behaviour
Co-authored-by: Kris Thielemans <KrisThielemans@users.noreply.github.com>
Co-authored-by: Kris Thielemans <KrisThielemans@users.noreply.github.com>
Co-authored-by: Kris Thielemans <KrisThielemans@users.noreply.github.com>
…o RDP/HessianVectorProduct
This removes two checks on Succeeded::no in GeneralisedObjectiveFunction
Currently I have added an intermediate class between
|
robbietuk
force-pushed
the
RDP/HessianVectorProduct
branch
from
June 27, 2022 21:20
15aebe7
to
6596d29
Compare
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.
This PR aims to add an intermediate class to the current prior hierarchy that will perform the iterations over each of the priors in STIR.