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......@@ -88,26 +88,26 @@ The ML model predictions are compared to posterior overlap statistic results als
| [lensid_create_unlensed_df.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/injections/lensid_create_unlensed_df.py) | generates dataframe containing tags for pairs of unlensed simulated events, with columns as img_0, img_1 and Lensing(=0). Eg: `lensid_create_unlensed_df -odir check -outfile unlensed.csv -start 10 -n 3 -infile ~/lensid/data/injection_pars/haris-et-al/unlensed_inj_data.npz` | OK, OK-jrc | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | ------- | -------------- |
| [lensid_create_lensed_inj_xmls.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/injections/lensid_create_lensed_inj_xmls.py) | helper script that outputs LAL inj.xml file for lensed simulated events given the injection parameters for bayestar. | OK, OK-jrc | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | ------- | -------------- |
| [lensid_create_unlensed_inj_xmls.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/injections/lensid_create_unlensed_inj_xmls.py) | helper script that outputs LAL inj.xml file for unlensed simulated events given the injection parameters for bayestar. | OK, OK-jrc | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | ------- | -------------- |
| [lensid_create_bayestar_sky_lensed_injs.sh](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/scripts/lensid_create_bayestar_sky_lensed_injs.sh) | generates bayestar skymaps(.fits) for lensed simulated events, using analytical/O3a PSDs. Also converts them to cartesian format and save as .npz files. Eg: `lensid_create_bayestar_sky_lensed_injs.sh -o check -s 10 -n 3 -i ~/lensid/data/injection_pars/haris-et-al/lensed_inj_data.npz -p ~/lensid/data/PSDs/analytical_psd.xml` Note: if this does not work try running this before `export PATH=$HOME/.local/bin:$PATH` | Ongoing | -------- | Issue created | -------------- |
| [lensid_create_bayestar_sky_unlensed_injs.sh](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/scripts/lensid_create_bayestar_sky_unlensed_injs.sh) | generates bayestar skymaps(.fits) for unlensed simulated events, using analytical/O3a PSDs. Also converts them to cartesian format and save as .npz files. Eg: `lensid_create_bayestar_sky_unlensed_injs.sh -o check -s 10 -n 3 -i ~/lensid/data/injection_pars/haris-et-al/unlensed_inj_data.npz -p ~/lensid/data/PSDs/analytical_psd.xml` | Ongoing | -------- | Issue created | -------------- |
| [lensid_fits_to_cart.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/utils/lensid_fits_to_cart.py) | helper script for converting HealPix skymap format(.fits) to cartesian. | Ongoing; need sanity check for hp.cartview | -------- | Issue created | -------------- |
| [lensid_create_bayestar_sky_lensed_injs.sh](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/scripts/lensid_create_bayestar_sky_lensed_injs.sh) | generates bayestar skymaps(.fits) for lensed simulated events, using analytical/O3a PSDs. Also converts them to cartesian format and save as .npz files. Eg: `lensid_create_bayestar_sky_lensed_injs.sh -o check -s 10 -n 3 -i ~/lensid/data/injection_pars/haris-et-al/lensed_inj_data.npz -p ~/lensid/data/PSDs/analytical_psd.xml` Note: if this does not work try running this before `export PATH=$HOME/.local/bin:$PATH` | OK-DC | cd113eaddc4a44336361af982852498aa605e7b0 | ------- | -------------- |
| [lensid_create_bayestar_sky_unlensed_injs.sh](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/scripts/lensid_create_bayestar_sky_unlensed_injs.sh) | generates bayestar skymaps(.fits) for unlensed simulated events, using analytical/O3a PSDs. Also converts them to cartesian format and save as .npz files. Eg: `lensid_create_bayestar_sky_unlensed_injs.sh -o check -s 10 -n 3 -i ~/lensid/data/injection_pars/haris-et-al/unlensed_inj_data.npz -p ~/lensid/data/PSDs/analytical_psd.xml` | OK-DC | cd113eaddc4a44336361af982852498aa605e7b0 | ------- | -------------- |
| [lensid_fits_to_cart.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/utils/lensid_fits_to_cart.py) | helper script for converting HealPix skymap format(.fits) to cartesian. | OK-DC | ac95f97e0c7e8d584b68ed364f353a5ed4bbb12d | need sanity check for hp.cartview during results review | |
| [lensid_sky_injs_cart.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/injections/lensid_sky_injs_cart.py) | helper script for managing IO of fits_to_cart.py script for injection study | OK | ac95f97e0c7e8d584b68ed364f353a5ed4bbb12d | Issue created | -------------- |
### Features extraction, Train/test/predict utilities
| Script | Short description | Status | git hash | Comment | final sign-off |
|--------|-------------------|--------|----------|---------|----------------|
| [lensid_get_features_qts_ml.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/feature_extraction/lensid_get_features_qts_ml.py) | Script for calculating densenets output and other features from the Q-transforms images which go as input to "XGBoost with QTs model". Requires trained denset models for three detectors. Eg: `lensid_get_features_qts_ml -infile check/lensed.csv -outfile check/lensed_QTs.csv -dense_models_dir ~/lensid/saved_models/ -data_dir check` | -OK-DC, OK-jrc--- | f9b7075d0e6ca8db211a0c3e43299af1eb428410 | ------- | -------------- |
| [lensid_get_features_sky_ml.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/feature_extraction/lensid_get_features_sky_ml.py) | Script for calculating features from the bayestar skymaps which go as input to "XGBoost with Skymaps" model. Eg: `lensid_get_features_sky_ml -infile check/lensed.csv -outfile check/lensed_sky.csv -data_dir check` | -OK-DC , OK-jrc | f9b7075d0e6ca8db211a0c3e43299af1eb428410 | ------- | -------------- |
| [lensid_get_features_qts_ml.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/feature_extraction/lensid_get_features_qts_ml.py) | Script for calculating densenets output and other features from the Q-transforms images which go as input to "XGBoost with QTs model". Requires trained denset models for three detectors. Eg: `lensid_get_features_qts_ml -infile check/lensed.csv -outfile check/lensed_QTs.csv -dense_models_dir ~/lensid/saved_models/ -data_dir check` | -OK-DC, OK-jrc--- | f9b7075d0e6ca8db211a0c3e43299af1eb428410 | -------------- | -------------- |
| [lensid_get_features_sky_ml.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/feature_extraction/lensid_get_features_sky_ml.py) | Script for calculating features from the bayestar skymaps which go as input to "XGBoost with Skymaps" model. Eg: `lensid_get_features_sky_ml -infile check/lensed.csv -outfile check/lensed_sky.csv -data_dir check` | -OK-DC , OK-jrc | f9b7075d0e6ca8db211a0c3e43299af1eb428410 | -------------- | -------------- |
| [ml_utils.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/utils/ml_utils.py) | utility script containing all machine learning model functions for training, FAP computation, predictions etc. | in progress-jrc | -------- | Why is leakyrelu loaded? The logic of rfn(epoch) could be simplified.------- | -------------- |
### ML models: Training, Cross-validation, Optimisation, Testing, Comparison with BLU , Predictions
| Scripts | Short description | Status | git hash | Comment | final sign-off |
|---------|-------------------|--------|----------|---------|----------------|
| [train_densenets_qts.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/train_test/train_densenets_qts.py) | Train densenet with qtransform for a given detector. Eg: `python train_densenets_qts.py -lensed_df ~/strong-lensing-ml/data/dataframes/train/lensed.csv -unlensed_df ~/strong-lensing-ml/data/dataframes/train/unlensed_half.csv -odir dense_out/cit/ -epochs 10 -data_dir ~/alice_data_lensid/qts/train/`. Note: requires `tensorflow-gpu` to load CUDA libraries. | --OK-jrc | -------- | | ---------------- |
| [train_crossvalidate_test_XGB_qts.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/train_test/train_crossvalidate_test_XGB_qts.py) | Trains, cross-validate and compare to BLU "XGBoost with QTs" model. Requires dataframe that already has the input features calculated from the Qtransform images and trained DenseNets. `python train_crossvalidate_test_XGB_qts.py -help` | OK-jrc\\ | jrc: the values of the parameters of XGBoost could be documented. | | |
| [train_crossvalidate_test_XGB_sky.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/train_test/train_crossvalidate_test_XGB_sky.py) | Train, cross-validates and compare to BLU "XGBoost with Skymaps" model. Requires dataframe that already has the input features calculated from the Bayestar/PE skymaps. `python train_crossvalidate_test_XGB_sky.py -help` | OK-jrc | -------------- | | |
| [test_combined_ML_results.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/train_test/test_combined_ML_results.py) | Test and compare to BLU overall ML model. Requires dataframes that already has the ML predictions calculated from the qts and skymaps. `python test_combined_ML_results.py -help` | OK-jrc | -------------- | | |
| [ml_predict_workflow.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/ml_predict_workflow.py), [config_O3_events.yaml](https://git.ligo.org/srashti.goyal/lensid-ml-o3/-/blob/master/config_O3_events.yaml) | Script for computing ML predictions for a given event pairs in dataframe, their skymaps, Qtransforms and the trained ML models. Optionally computes the False Positive Probabilities given the background. It requires config file as input. Eg: `lensid_make_predictions -config /home/srashti.goyal/lensid-ml-O3/config_O3_events.yaml` Note: change `odir` in **config** file. | -------- | ---------- | --------- | ---------------- |
| [train_densenets_qts.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/train_test/train_densenets_qts.py) | Train densenet with qtransform for a given detector. Eg: `python train_densenets_qts.py -lensed_df ~/strong-lensing-ml/data/dataframes/train/lensed.csv -unlensed_df ~/strong-lensing-ml/data/dataframes/train/unlensed_half.csv -odir dense_out/cit/ -epochs 10 -data_dir ~/alice_data_lensid/qts/train/`. Note: requires `tensorflow-gpu` to load CUDA libraries. | OK-DC; OK-jrc | a60740bb5a0cccb2be8e8184f16c0c7c93f8150b | | ---------------- |
| [train_crossvalidate_test_XGB_qts.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/train_test/train_crossvalidate_test_XGB_qts.py) | Trains, cross-validate and compare to BLU "XGBoost with QTs" model. Requires dataframe that already has the input features calculated from the Qtransform images and trained DenseNets. `python train_crossvalidate_test_XGB_qts.py -help` | OK-DC; OK-jrc\\ | jrc: the values of the parameters of XGBoost could be documented. | | |
| [train_crossvalidate_test_XGB_sky.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/train_test/train_crossvalidate_test_XGB_sky.py) | Train, cross-validates and compare to BLU "XGBoost with Skymaps" model. Requires dataframe that already has the input features calculated from the Bayestar/PE skymaps. `python train_crossvalidate_test_XGB_sky.py -help` | OK-DC; OK-jrc | a60740bb5a0cccb2be8e8184f16c0c7c93f8150b | | |
| [test_combined_ML_results.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/train_test/test_combined_ML_results.py) | Test and compare to BLU overall ML model. Requires dataframes that already has the ML predictions calculated from the qts and skymaps. `python test_combined_ML_results.py -help` | OK-DC; OK-jrc | a60740bb5a0cccb2be8e8184f16c0c7c93f8150b | | |
| [ml_predict_workflow.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/ml_predict_workflow.py), [config_O3_events.yaml](https://git.ligo.org/srashti.goyal/lensid-ml-o3/-/blob/master/config_O3_events.yaml) | Script for computing ML predictions for a given event pairs in dataframe, their skymaps, Qtransforms and the trained ML models. Optionally computes the False Positive Probabilities given the background. It requires config file as input. Eg: `lensid_make_predictions -config /home/srashti.goyal/lensid-ml-O3/config_O3_events.yaml` Note: change `odir` in **config** file. | -------- | ---------- | DC: Should be considered in the results review | ---------------- |
## Investigations: Injection parameters, features statistics, PSDs etc.
| Notebook | Short description | Status | git hash | Comment | final sign-off |
......@@ -120,8 +120,8 @@ The ML model predictions are compared to posterior overlap statistic results als
## ML Predictions: O3 Real events, Data preparation, FAP computation, Comparison with BLU
| Notebook/Scripts | Short description | Status | git hash | Comment | final sign-off |
|------------------|-------------------|--------|----------|---------|----------------|
| [data_download.py](https://git.ligo.org/srashti.goyal/lensid-ml-o3/-/blob/master/data_download_preparation/data_download.py) | Script for downloading events info, skymaps(.fits) from GraceDB and strain data from ligo servers using GWpy. Note: needs valid ligo key path(line 26) for accessing non-public data in Gracedb., eg: `/tmp/x509up*` | ------ | -------- | ------- | -------------- |
| [data_prepare.py](https://git.ligo.org/srashti.goyal/lensid-ml-o3/-/blob/master/data_download_preparation/data_prepare.py) | Preparing Qtransform images, dataframes and skymaps for O3 real events given the event list and raw data downloaded from LIGO servers. Note: raw data on CIT is in `/home/srashti.goyal/lensid-ml-o3/data_download_preparation/O3` | Ongoing | -------- | ---| -------------- |
| [data_download.py](https://git.ligo.org/srashti.goyal/lensid-ml-o3/-/blob/master/data_download_preparation/data_download.py) | Script for downloading events info, skymaps(.fits) from GraceDB and strain data from ligo servers using GWpy. Note: needs valid ligo key path(line 26) for accessing non-public data in Gracedb., eg: `/tmp/x509up*` | DC: OK | 2e3215024a42c08081d612c3713ffd54fbba5f7e | ------- | -------------- |
| [data_prepare.py](https://git.ligo.org/srashti.goyal/lensid-ml-o3/-/blob/master/data_download_preparation/data_prepare.py) | Preparing Qtransform images, dataframes and skymaps for O3 real events given the event list and raw data downloaded from LIGO servers. Note: raw data on CIT is in `/home/srashti.goyal/lensid-ml-o3/data_download_preparation/O3` | DC: OK | 2e3215024a42c08081d612c3713ffd54fbba5f7e | --- | -------------- |
| [condor_lensid_make_predictions.py](https://git.ligo.org/srashti.goyal/lensid-ml-o3/-/blob/master/condor_lensid_make_predictions.py), [config_O3_events.yaml](https://git.ligo.org/srashti.goyal/lensid-ml-o3/-/blob/master/config_O3_events.yaml) | Condor Script for computing ML predictions and FPPs using, [ml_predict_workflow.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/ml_predict_workflow.py). Eg: `python condor_lensid_make_predictions` Note: change `exec_file_loc` in the script according to your installation and `odir` in config file. | OK-DC | ca47c5ce71fa7405b84c944235a8646abcd216d4 | --------- | ---------------- |
| [get_candidates_compare_to_blu.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o3/-/blob/master/O3_ML_gwtc3/get_candidates_compare_to_blu.ipynb) | Notebook for comparing ML and BLU results for the full O3 catalogue of BBHs. | -------- | ---------- | --------- | ---------------- |
| [investigations_visualisations.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o3/-/blob/master/review/investigations_visualisations.ipynb) | Notebook to visualise qtransforms and skymaps of the interesting candidate real event pairs. | -------- | Should this be reviewed? | --------- | ---------------- |
......@@ -189,7 +189,6 @@ Meeting ID: 860 7262 9011 Password: 001303
### Action items:
* [x] Prepare features extracting and training scripts for review
* [x] Download bayestar skymaps with other authentication method, as Deep suggested.
* [x] Prepare testing scripts along with comparison with BLU.
......@@ -353,11 +352,9 @@ Meeting ID: 860 7262 9011 Password: 001303
### Action items:
* [x] Check off all the comments and issues in the review table.
* [x] Prepare injection set for super-sub pairs. Lensed and Unlensed.
* [x] Write scripts for submitting condor dags.
## 12 October 2021
* We discussed about the git issues that Deep created for data generation scripts.
......@@ -376,7 +373,6 @@ Meeting ID: 860 7262 9011 Password: 001303
### Action items:
* [x] write scripts for data downloading of real events.
## 26 October 2021
......@@ -386,8 +382,8 @@ Meeting ID: 860 7262 9011 Password: 001303
* Srashti shall work towards result review.
* We discussed the sanity check of healpix cartesian projection( [hp_cartview.ipynb](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/review/hp_cartview.ipynb) ).
### Action items:
* [ ] simplify/optimise the learning rate scheduler in densenets training.
* [ ] cosmetic changes in column names for BLU dataframes.
* [ ] write script for systematic BLU calculation and plots for the O3 real events.
......