| [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 | Done | | \-------------- | |
| [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: |
| [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. | Need to clean up | | \-------------- | |
| [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. | Done | | \-------------- | |
O4a Predictions:
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@@ -114,7 +114,7 @@ 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, | Done | | \-------------- | |
| [Config](https://git.ligo.org/srashti.goyal/alensidforlensingflow/-/blob/main/Examples/SimpleExample/config_o4a.yaml) | ML models and config for production runs, | Done | | \-------------- | |
| [O4a Production Run](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/lensid_runs/O4a_alensid/result/) | ML Production run on CIT | Done | | \-------------- | |
| [investigations_visualisations.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/investigations_visualisations.ipynb?ref_type=heads) | Investigations with BD cuts, Eyeballing pairs, and comparing the performances with the other pipelines | Done | | \-------------- | |
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@@ -201,7 +201,7 @@ The review call happen on Wednesdays 1 PM CEST/ 4:30 PM IST virtual IFPA room: h
## 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
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@@ -281,4 +281,14 @@ 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.
\ No newline at end of file
* [x] Train a final ML and background while optimising.
## 22 May 2025
* We discussed the LensID results and the things that need to be reviewed.
* The results are produced manually and not with LensingFlow, as requested by the group.
* The Result review page is updated with final results, and JR and Sourabh will go through the.
