test: Hacky two way CKF #2717
Closed
test: Hacky two way CKF #2717
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
github-actions
bot
added
Component - Examples
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #2717 +/- ##
=======================================
Coverage 49.50% 49.50%
=======================================
Files 475 475
Lines 26975 26975
Branches 12454 12454
=======================================
Hits 13355 13355
Misses 4762 4762
Partials 8858 8858 ☔ View full report in Codecov by Sentry. |
|
closing after demonstration is finished |
kodiakhq bot
pushed a commit
that referenced
this pull request
Mar 28, 2024
After #2539 I want to finally refactor the CKF and remove the smoothing and the reference surface targeting from the core algorithm in order to make it more composable and less complicated. Before the CKF was basically only usable with smoothing turned on otherwise we would not receive any tracks. Now it always runs without smoothing and the user can decide what and how to smooth. Afterwards the user can decide which track state they want to extrapolate to a reference surface if necessary. IMO this makes the algorithm flow much easier to comprehend and gives the user more flexibility. This also makes an implementation of a two way finding easier as discovered in #2717 blocked by - #2723 --- Users can smooth and extrapolate tracks after the CKF returns them. Extrapolation can be achieved using the `Propagator` while smoothing can be done by the `GainMatrixSmoother`. For convenience this PR also includes helper functions to smooth and extrapolate single tracks or a whole track container. Example of smoothing and extrapolating tracks after the CKF https://github.com/acts-project/acts/blob/98186891d4bdc5b211f6af3e96ca59ace7c315cc/Examples/Algorithms/TrackFinding/src/TrackFindingAlgorithm.cpp#L172-L189
andiwand
added a commit
that referenced
this pull request
Apr 11, 2024
Resurrect #2717 from @andiwand, updating to the latest `main`, and removing earlier test (`MyTrackFindingAlgorithm`). blocked by - #3074 - #3075 - #3076 - #3077 - #3078 - #3086 --------- Co-authored-by: andiwand <[email protected]> Co-authored-by: Tim Adye <[email protected]>
Ragansu
pushed a commit
to Ragansu/acts
that referenced
this pull request
Apr 19, 2024
Resurrect acts-project#2717 from @andiwand, updating to the latest `main`, and removing earlier test (`MyTrackFindingAlgorithm`). blocked by - acts-project#3074 - acts-project#3075 - acts-project#3076 - acts-project#3077 - acts-project#3078 - acts-project#3086 --------- Co-authored-by: andiwand <[email protected]> Co-authored-by: Tim Adye <[email protected]>
EleniXoch
pushed a commit
to EleniXoch/acts
that referenced
this pull request
May 6, 2024
…ject#2722) After acts-project#2539 I want to finally refactor the CKF and remove the smoothing and the reference surface targeting from the core algorithm in order to make it more composable and less complicated. Before the CKF was basically only usable with smoothing turned on otherwise we would not receive any tracks. Now it always runs without smoothing and the user can decide what and how to smooth. Afterwards the user can decide which track state they want to extrapolate to a reference surface if necessary. IMO this makes the algorithm flow much easier to comprehend and gives the user more flexibility. This also makes an implementation of a two way finding easier as discovered in acts-project#2717 blocked by - acts-project#2723 --- Users can smooth and extrapolate tracks after the CKF returns them. Extrapolation can be achieved using the `Propagator` while smoothing can be done by the `GainMatrixSmoother`. For convenience this PR also includes helper functions to smooth and extrapolate single tracks or a whole track container. Example of smoothing and extrapolating tracks after the CKF https://github.com/acts-project/acts/blob/98186891d4bdc5b211f6af3e96ca59ace7c315cc/Examples/Algorithms/TrackFinding/src/TrackFindingAlgorithm.cpp#L172-L189
EleniXoch
pushed a commit
to EleniXoch/acts
that referenced
this pull request
May 6, 2024
Resurrect acts-project#2717 from @andiwand, updating to the latest `main`, and removing earlier test (`MyTrackFindingAlgorithm`). blocked by - acts-project#3074 - acts-project#3075 - acts-project#3076 - acts-project#3077 - acts-project#3078 - acts-project#3086 --------- Co-authored-by: andiwand <[email protected]> Co-authored-by: Tim Adye <[email protected]>
asalzburger
pushed a commit
to asalzburger/acts
that referenced
this pull request
May 21, 2024
…ject#2722) After acts-project#2539 I want to finally refactor the CKF and remove the smoothing and the reference surface targeting from the core algorithm in order to make it more composable and less complicated. Before the CKF was basically only usable with smoothing turned on otherwise we would not receive any tracks. Now it always runs without smoothing and the user can decide what and how to smooth. Afterwards the user can decide which track state they want to extrapolate to a reference surface if necessary. IMO this makes the algorithm flow much easier to comprehend and gives the user more flexibility. This also makes an implementation of a two way finding easier as discovered in acts-project#2717 blocked by - acts-project#2723 --- Users can smooth and extrapolate tracks after the CKF returns them. Extrapolation can be achieved using the `Propagator` while smoothing can be done by the `GainMatrixSmoother`. For convenience this PR also includes helper functions to smooth and extrapolate single tracks or a whole track container. Example of smoothing and extrapolating tracks after the CKF https://github.com/acts-project/acts/blob/98186891d4bdc5b211f6af3e96ca59ace7c315cc/Examples/Algorithms/TrackFinding/src/TrackFindingAlgorithm.cpp#L172-L189
asalzburger
pushed a commit
to asalzburger/acts
that referenced
this pull request
May 21, 2024
Resurrect acts-project#2717 from @andiwand, updating to the latest `main`, and removing earlier test (`MyTrackFindingAlgorithm`). blocked by - acts-project#3074 - acts-project#3075 - acts-project#3076 - acts-project#3077 - acts-project#3078 - acts-project#3086 --------- Co-authored-by: andiwand <[email protected]> Co-authored-by: Tim Adye <[email protected]>
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.
Not meant for merging but just wanted to put it out so we can easily display and discuss the code and results.
This is a very early attempt to use our existing CKF in both directions.
First we run the CKF with forward propagation with smoothing and then use the smoothed params to run an additional backward propagation for each forward track. Afterwards we can reverse the backward track states and modify the parent index that it becomes a single, longer track.
For now I drafted this in a new algorithm but I think we can extend the existing track finding algorithm to optionally do that and add a config with which direction to start.
Discovered problems
Discovered difficulties
cc @noemina @paulgessinger