Update Result Review O4a authored by Srashti Goyal's avatar Srashti Goyal
......@@ -22,15 +22,19 @@ O4a repo: [lensid-ml-o4](https://git.ligo.org/srashti.goyal/lensid-ml-o4)
- Methods paper: [here](https://arxiv.org/abs/2106.12466)
- Methods presentation: [slides](https://docs.google.com/presentation/d/10bIhtFae5RIJ3WBJg1Lcy7PueSKwxh1m2APRDN0w0PA/edit?usp=sharing)
# Final statement
# Final sign-off
### Reviewer: Jean-Rene Cudell [@jean-rene.cudell](https://git.ligo.org/jean-rene.cudell) , Sourabh Magare [@sourabh.magare](https://git.ligo.org/sourabh.magare)
#### Reviewer: Jean-Rene Cudell [@jean-rene.cudell](https://git.ligo.org/jean-rene.cudell) :white_check_mark: , Sourabh Magare @sourabh.magare :white_check_mark:
Analysts: Srashti Goyal @srashti.goyal
Final Sign-off: Date:
Final Sign-off Date: 01.07.2025
Git hash:
Analysis Repo: [lensid-ml-o4](https://git.ligo.org/srashti.goyal/lensid-ml-o4)
Git hash: 45532558450d2d3997e8120d058c9d04fe9ea39a
#### Review Statement: [here](https://git.ligo.org/srashti.goyal/lensid/-/wikis/Result-Review-O4a/final-statement)
# Result review
......@@ -51,13 +55,13 @@ ML Models:
| [PSD_plots.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/retraining_for_O4/PSD_plots.ipynb) | Comparison of the PSDs used for training and testing in O3 and O4 etc. | Reviewed | Reviewed | 5f525a652d0374f11a207bc8158f7c75d37de884 | :heavy_check_mark: :heavy_check_mark: |
| ML QTs [L1](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/O4a_training/L1/uniform_config_lr_0.01_ep_15_bs_500/), [H1](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/O4a_training/uniform_config_lr_0.01_ep_15_bs_500/) | Production ML QTs models train directories. Uniform in masses for H1 and L1 | Reviewed | OK | \-------------- | :heavy_check_mark: :heavy_check_mark: |
| [2vs3det.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/retraining_for_O4/2vs3det.ipynb) | Train and Test ML Skymaps. Benchmark performance for HL v/s HLV | Reviewed | Why some values are NaN in DataFrame?, Why no orange curve in plots?, Choice of hyperparameters for training? - Sourabh | 5f525a652d0374f11a207bc8158f7c75d37de884 | :heavy_check_mark: :heavy_check_mark: |
| [make_predictions.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/O4a_make_predictions.ipynb) | Demo LensID O4a, ML models benchmark performance and background estimations. | Reviewed | | 45532558450d2d3997e8120d058c9d04fe9ea39a | :heavy_check_mark: :heavy_check_mark:|
| [make_predictions.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/O4a_make_predictions.ipynb) | Demo LensID O4a, ML models benchmark performance and background estimations. | Reviewed | | 45532558450d2d3997e8120d058c9d04fe9ea39a | :heavy_check_mark: :heavy_check_mark: |
O4a Predictions:
| File(s) | Short description | Status | Comment | Git hash | Sign-off |
|---------|-------------------|--------|---------|----------|----------|
| [Config](https://git.ligo.org/srashti.goyal/alensidforlensingflow/-/blob/main/Examples/SimpleExample/config_o4a.yaml) | ML models and config for production runs | Reviewed | | faee7a4334dd7f5781f4f8c90e36497fd2b0aeea| :heavy_check_mark: :heavy_check_mark: |
| [Config](https://git.ligo.org/srashti.goyal/alensidforlensingflow/-/blob/main/Examples/SimpleExample/config_o4a.yaml) | ML models and config for production runs | Reviewed | | faee7a4334dd7f5781f4f8c90e36497fd2b0aeea | :heavy_check_mark: :heavy_check_mark: |
| [O4a Production Run](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/lensid_runs/O4a_alensid/result/) | ML Production run on CIT | Reviewed | | \-------------- | :heavy_check_mark: :heavy_check_mark: |
| [investigations_visualisations.html](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/investigations_lensidO4a.html) | ML pipeline run through a notebook with Investigations/Eyeballing pairs and comparing the performances with the other pipelines | Done | | \-------------- | :heavy_check_mark: :heavy_check_mark: |
......@@ -68,7 +72,7 @@ Publication results:
| [Final Results](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/LensID_results_5May25.csv) | O4a Pairs analysed by LensID | Done | | b3a5135e0f03ad7587e53b2814feb2de10b94507 | :heavy_check_mark: :heavy_check_mark: |
| [Interesting Pairs](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/interesting_pairs_5May25.csv?ref_type=heads) | Pairs passed for follow-up analysis | Done | What statistics are included in ML FPP? and Are Matchfilter chirp masses used for Bhattacharya distance?- Sourabh | d20a4c29ffa623e771d664709747a57bb68ae5ce | :heavy_check_mark: :heavy_check_mark: |
| [final_results_plots.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/final_results_plots.ipynb) | Plot of rejected and selected pairs | needs PWT approval | | \-------------- | :heavy_check_mark: :heavy_check_mark: |
| [Lensing paper plot](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/LensID_O4a.pdf) | Plot of rejected and selected pairs | needs PWT approval | The legend of the x axis is cut. Also it would be good to use different symbols for points which are kept and points which are not. | \-------------- | :heavy_check_mark: :heavy_check_mark:|
| [Lensing paper plot](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/LensID_O4a.pdf) | Plot of rejected and selected pairs | needs PWT approval | The legend of the x axis is cut. Also it would be good to use different symbols for points which are kept and points which are not. | \-------------- | :heavy_check_mark: :heavy_check_mark: |
# Review Calls
......@@ -144,7 +148,7 @@ The review call happens on Wednesdays 1 PM CEST/ 4:30 PM IST virtual IFPA room:
## 8 November 2023
* We discussed the integration of lensid with the lensing flow and visited the new package: https://git.ligo.org/srashti.goyal/alensidforlensingflow
* JR suggested to use O4a real noise PSDs for the training and testing of the final ML model for the production runs. (detchar)\[https://ldas-jobs.ligo-wa.caltech.edu/~detchar/summary\\\\\\\\\\]
* JR suggested to use O4a real noise PSDs for the training and testing of the final ML model for the production runs. (detchar)\[https://ldas-jobs.ligo-wa.caltech.edu/~detchar/summary\\\\\\\\\\\]
* We are still unsure about the inclusion of the population and the time delay lensing priors for the follow-up strategy.
## Action items
......@@ -224,8 +228,6 @@ We also want to prepare a document to quantify all the things. One main issue is
### Action items
* [x] Prepare the scripts for result review.
* [x] Train a final ML and background while optimising.
## 22 May 2025
......@@ -247,4 +249,4 @@ We also want to prepare a document to quantify all the things. One main issue is
### Action items
* [x] Address comments and concerns of JR and Sourabh
* [X] JR & Sourabh will prepare the final review statement.
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* [x] JR & Sourabh will prepare the final review statement.
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