| [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 | JR-Should one worry about the missing npz files? What is the difference between ML and dense? Which curve is QT+skymaps? | \-------------- | |
| [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. | Done | | \-------------- | |
| [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 | | \-------------- | |
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 | | \-------------- | :heavy_check_mark: |
| [O4a Production Run](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/lensid_runs/O4a_alensid/result/) | ML Production run on CIT | Done | | \-------------- | |
| [O4a Production Run](https://ldas-jobs.ligo.caltech.edu/~srashti.goyal/lensid_runs/O4a_alensid/result/) | ML Production run on CIT | Done | | \-------------- | :heavy_check_mark: |
| [investigations_visualisations.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o4/-/blob/master/investigations_visualisations.ipynb?ref_type=heads) | ML pipeline run through a notebook with Investigations/Eyeballing pairs and comparing the performances with the other pipelines | Done | | \-------------- | |
Publication results:
...
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@@ -195,7 +195,7 @@ 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.
