[RF] Fix counting Asimov generation with multiple floating parameters - #23104
Open
guitargeek wants to merge 1 commit into
Open
[RF] Fix counting Asimov generation with multiple floating parameters#23104guitargeek wants to merge 1 commit into
guitargeek wants to merge 1 commit into
Conversation
When generating a counting Asimov dataset, the AsymptoticCalculator identified the expected value of an observable in a Gaussian or Poisson term as "the single non-constant server that is not the observable". This heuristic failed whenever both the mean and the width of a Gaussian were floating, could not see constness through derived quantities like RooFormulaVars, and silently set the observable to the value of the *sigma* parameter when the mean was constant but sigma floated. The heuristic is unnecessary: RooGaussian and RooPoisson expose their proxies via getX() and getMean(). Use the exact (x, mean) pair and set whichever of the two is the observable to the value of the other one. The width and the constness of the parameters no longer matter, and the direction where the mean is the observable (constraint terms with global observables) keeps working. The RooMultiVarGaussian path goes through the same helper with xVec()[i] and muVec()[i]. Fixes the four failure cases from ROOT-10096, covered by a new test. Fixes [ROOT-10096](https://its.cern.ch/jira/browse/ROOT-10069) 🤖 Done with the help of AI
Test Results 23 files 23 suites 3d 14h 27m 51s ⏱️ For more details on these failures, see this check. Results for commit 83fce74. |
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
1 participant
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
When generating a counting Asimov dataset, the AsymptoticCalculator identified the expected value of an observable in a Gaussian or Poisson term as "the single non-constant server that is not the observable". This heuristic failed whenever both the mean and the width of a Gaussian were floating, could not see constness through derived quantities like RooFormulaVars, and silently set the observable to the value of the sigma parameter when the mean was constant but sigma floated.
The heuristic is unnecessary: RooGaussian and RooPoisson expose their proxies via getX() and getMean(). Use the exact (x, mean) pair and set whichever of the two is the observable to the value of the other one. The width and the constness of the parameters no longer matter, and the direction where the mean is the observable (constraint terms with global observables) keeps working. The RooMultiVarGaussian path goes through the same helper with xVec()[i] and muVec()[i].
Fixes the four failure cases from ROOT-10096, covered by a new test.
Fixes ROOT-10096
🤖 Done with the help of AI