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...@@ -79,18 +79,26 @@ The ML model predictions are compared to posterior overlap statistic results als ...@@ -79,18 +79,26 @@ The ML model predictions are compared to posterior overlap statistic results als
* subthreshold events? * subthreshold events?
#### Top level scripts: train-test workflow, data generation workflow, ML predictions workflow. #### Top level scripts: train-test workflow, data generation workflow, ML predictions workflow.
## Package Scripts ## Package Scripts
### Data preparation ### Data preparation
| Script | Short description | Status | git hash | Comment | final sign-off | | Script | Short description | Status | git hash | Comment | final sign-off |
|--------|-------------------|--------|----------|---------|----------------| |--------|-------------------|--------|----------|---------|----------------|
| [qt_utils.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/utils/qt_utils.py) | helper script for injecting gaussian noise given a psd and waveform. Also plots and saves Qtransforms. | Ongoing | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | Remove hard-coded numbers | -------------- | | [qt_utils.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/utils/qt_utils.py) | helper script for injecting gaussian noise given a psd and waveform. Also plots and saves Qtransforms. | Ongoing\
| [lensid_create_qts_lensed_injs.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/injections/lensid_create_qts_lensed_injs.py) | generates waveforms and q-transforms for simulated lensed events given a set of injection parameters, using analytical/O3a PSDs. Eg: `lensid_create_qts_lensed_injs -odir check -start 10 -n 3 -infile ~/lensid/data/injection_pars/haris-et-al/lensed_inj_data.npz -psd_mode 1 -qrange 2 -mode 2` | OK | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | ------- | -------------- | Ongoing-jrc | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | Remove hard-coded numbers | -------------- |
| [lensid_create_qts_unlensed_injs.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/injections/lensid_create_qts_unlensed_injs.py) | generates waveforms and q-transforms for simulated unlensed events given a set of injection parameters, using analytical/O3a PSDs. Eg: `lensid_create_qts_unlensed_injs -odir check -start 10 -n 3 -infile ~/lensid/data/injection_pars/haris-et-al/unlensed_inj_data.npz -psd_mode 1 -qrange 2 -mode 2` | OK | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | ------- | -------------- | | [lensid_create_qts_lensed_injs.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/injections/lensid_create_qts_lensed_injs.py) | generates waveforms and q-transforms for simulated lensed events given a set of injection parameters, using analytical/O3a PSDs. Eg: `lensid_create_qts_lensed_injs -odir check -start 10 -n 3 -infile ~/lensid/data/injection_pars/haris-et-al/lensed_inj_data.npz -psd_mode 1 -qrange 2 -mode 2` | OK\
| [lensid_create_lensed_df.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/injections/lensid_create_lensed_df.py) | generates dataframe containing tags for lensed simulated event pairs, with columns as img_0, img_1 and Lensing(=1). Eg: `lensid_create_lensed_df -odir check -outfile lensed.csv -start 10 -n 3 -infile ~/lensid/data/injection_pars/haris-et-al/lensed_inj_data.npz` | OK | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | ------- | -------------- | OK-jrc | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | ------- | -------------- |
| [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 | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | ------- | -------------- | | [lensid_create_qts_unlensed_injs.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/injections/lensid_create_qts_unlensed_injs.py) | generates waveforms and q-transforms for simulated unlensed events given a set of injection parameters, using analytical/O3a PSDs. Eg: `lensid_create_qts_unlensed_injs -odir check -start 10 -n 3 -infile ~/lensid/data/injection_pars/haris-et-al/unlensed_inj_data.npz -psd_mode 1 -qrange 2 -mode 2` | OK\
| [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 | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | ------- | -------------- | 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 | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | ------- | -------------- | | [lensid_create_lensed_df.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/package/lensid/injections/lensid_create_lensed_df.py) | generates dataframe containing tags for lensed simulated event pairs, with columns as img_0, img_1 and Lensing(=1). Eg: `lensid_create_lensed_df -odir check -outfile lensed.csv -start 10 -n 3 -infile ~/lensid/data/injection_pars/haris-et-al/lensed_inj_data.npz` | OK\
OK-jrc | 32d0854b1a68cf21827e65ca1c36feb7ca53d0f5 | ------- | -------------- |
| [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/aligo_virgo_psd.xml` Note: if this does not work try running this before `export PATH=$HOME/.local/bin:$PATH` | ------ | -------- | ------- | -------------- | | [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/aligo_virgo_psd.xml` Note: if this does not work try running this before `export PATH=$HOME/.local/bin:$PATH` | ------ | -------- | ------- | -------------- |
| [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/aligo_virgo_psd.xml` | ------ | -------- | ------- | -------------- | | [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/aligo_virgo_psd.xml` | ------ | -------- | ------- | -------------- |
| [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. | ------ | -------- | ------- | -------------- | | [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. | ------ | -------- | ------- | -------------- |
...@@ -99,14 +107,16 @@ The ML model predictions are compared to posterior overlap statistic results als ...@@ -99,14 +107,16 @@ The ML model predictions are compared to posterior overlap statistic results als
### Features extraction, Train/test/predict utilities ### Features extraction, Train/test/predict utilities
| Script | Short description | Status | git hash | Comment | final sign-off | | 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--- | -------- | ------- | -------------- | | [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\
| [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-- | -------- | ------- | -------------- | OK-jrc--- | -------- | ------- | -------------- |
| [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------ | -------- | the fixed directory inn densebet_input_matrix should be user-defined. Why is leakyrelu loaded? The logic of rfn(epoch) could be simplified.------- | -------------- | | [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-\
OK-jrc | -------- | ------- | -------------- |
| [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----- | -------- | arc: the fixed directory in densebet_input_matrix should be user-defined. Why is leakyrelu loaded? The logic of rfn(epoch) could be simplified.------- | -------------- |
## ML models: Training, Cross-validation, Optimisation, Testing, Comparison with BLU. ## ML models: Training, Cross-validation, Optimisation, Testing, Comparison with BLU.
| Scripts | Short description | Status | git hash | Comment | final sign-off | | Scripts | Short description | Status | git hash | Comment | final sign-off |
|----------|-------------------|--------|----------|---------|----------------| |---------|-------------------|--------|----------|---------|----------------|
| [train_densenets_qts.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/scripts/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: tensorflowenv on pcdev12@CIT has GPU | --OK---- | -------- | is it only on pcdev12? |----------------| | [train_densenets_qts.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/scripts/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: tensorflowenv on pcdev12@CIT has GPU | --OK-jrc | -------- | jrc: is it only on pcdev12? | ---------------- |
| [train_crossvalidate_test_XGB_qts.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/scripts/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` | ------ | -------- | ------- | -------------- | | [train_crossvalidate_test_XGB_qts.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/scripts/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` | ------ | -------- | ------- | -------------- |
| [train_crossvalidate_test_XGB_sky.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/scripts/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` | ------ | -------- | ------- | -------------- | | [train_crossvalidate_test_XGB_sky.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/scripts/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` | ------ | -------- | ------- | -------------- |
| [test_combined_ML_results.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/scripts/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` | ------ | -------- | ------- | -------------- | | [test_combined_ML_results.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/scripts/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` | ------ | -------- | ------- | -------------- |
...@@ -123,18 +133,17 @@ The ML model predictions are compared to posterior overlap statistic results als ...@@ -123,18 +133,17 @@ The ML model predictions are compared to posterior overlap statistic results als
### O3 analysis in git repo: [lensid-ml-o3](https://git.ligo.org/srashti.goyal/lensid-ml-o3) ### O3 analysis in git repo: [lensid-ml-o3](https://git.ligo.org/srashti.goyal/lensid-ml-o3)
| Notebook/Scripts | Short description | Status | git hash | Comment | final sign-off | | Notebook/Scripts | Short description | Status | git hash | Comment | final sign-off |
|----------|-------------------|--------|----------|---------|----------------| |------------------|-------------------|--------|----------|---------|----------------|
| [download_data.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o3/-/blob/master/data_download_preparation/download_data.ipynb) | Notebook for downloading skymaps(.fits) from GraceDB and strain data from ligo servers using GWpy. | ------ | -------- | ------- | -------------- | | [download_data.ipynb](https://git.ligo.org/srashti.goyal/lensid-ml-o3/-/blob/master/data_download_preparation/download_data.ipynb) | Notebook for downloading skymaps(.fits) from GraceDB and strain data from ligo servers using GWpy. | ------ | -------- | ------- | -------------- |
| [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` | ------ | -------- | ------- | -------------- | | [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` | ------ | -------- | ------- | -------------- |
| [ml_predict_workflow.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/scripts/ml_predict_workflow.py), [config_O3_events.yaml](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/scripts/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: `python ml_predict_workflow.py -config config_O3_events.yaml` Note: change `odir` in config file. | -------- | ---------- | --------- | ---------------- | | [ml_predict_workflow.py](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/scripts/ml_predict_workflow.py), [config_O3_events.yaml](https://git.ligo.org/srashti.goyal/lensid/-/blob/master/scripts/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: `python ml_predict_workflow.py -config config_O3_events.yaml` Note: change `odir` in config file. | -------- | ---------- | --------- | ---------------- |
| [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. | -------- | ---------- | --------- | ---------------- | | [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. | -------- | ---------- | --------- | ---------------- |
# Meetings # Meetings
Topic: ML Lensing Review Time: This is a recurring meeting Meet anytime Topic: ML Lensing Review Time: This is a recurring meeting Meet anytime
Join Zoom Meeting [https://illinois.zoom.us/j/86072629011?pwd=RUVGRjQ5ZFJJR2c4cEZBUkU1KzFzUT09](https://illinois.zoom.us/j/86072629011?pwd=RUVGRjQ5ZFJJR2c4cEZBUkU1KzFzUT09) Join Zoom Meeting <https://illinois.zoom.us/j/86072629011?pwd=RUVGRjQ5ZFJJR2c4cEZBUkU1KzFzUT09>
Meeting ID: 860 7262 9011 Password: 001303 Meeting ID: 860 7262 9011 Password: 001303
...@@ -173,7 +182,7 @@ Meeting ID: 860 7262 9011 Password: 001303 ...@@ -173,7 +182,7 @@ Meeting ID: 860 7262 9011 Password: 001303
### Action items: ### Action items:
* [x] sequence of data gen/utility scripts * [x] sequence of data gen/utility scripts
* [x] diagnostics on training/testing set (lensed and unlensed) , ref: [https://git.ligo.org/shaon.ghosh/EM_Bright_ML/-/tree/master/O2-HL-rates-injections](https://git.ligo.org/shaon.ghosh/EM_Bright_ML/-/tree/master/O2-HL-rates-injections) * [x] diagnostics on training/testing set (lensed and unlensed) , ref: <https://git.ligo.org/shaon.ghosh/EM_Bright_ML/-/tree/master/O2-HL-rates-injections>
## 28 May 2021 ## 28 May 2021
...@@ -293,13 +302,13 @@ Meeting ID: 860 7262 9011 Password: 001303 ...@@ -293,13 +302,13 @@ Meeting ID: 860 7262 9011 Password: 001303
## 20 August 2021 ## 20 August 2021
* We discussed about packaging of the pipeline, and the git issue which Deep created. [here](https://git.ligo.org/srashti.goyal/strong-lensing-ml/-/issues/1). * We discussed about packaging of the pipeline, and the git issue which Deep created. [here](https://git.ligo.org/srashti.goyal/strong-lensing-ml/-/issues/1 "Code changes required").
* We also discussed about the preliminary results and deciding on threshold on FPP for getting the candidate pairs. * We also discussed about the preliminary results and deciding on threshold on FPP for getting the candidate pairs.
### Action items: ### Action items:
* [x] Investigate extreme events in the test set for the BLU & ML, by seeing their QTs and skymaps to understand the independent behaviour of ML & BLU. * [x] Investigate extreme events in the test set for the BLU & ML, by seeing their QTs and skymaps to understand the independent behaviour of ML & BLU.
* [x] Use entry points as mentioned [here](https://git.ligo.org/srashti.goyal/strong-lensing-ml/-/issues/1). * [x] Use entry points as mentioned [here](https://git.ligo.org/srashti.goyal/strong-lensing-ml/-/issues/1 "Code changes required").
* [x] Create new repo for the package and package data, and probably move this review page also over there. * [x] Create new repo for the package and package data, and probably move this review page also over there.
## 24 & 27 August 2021 ## 24 & 27 August 2021
...@@ -323,7 +332,7 @@ Meeting ID: 860 7262 9011 Password: 001303 ...@@ -323,7 +332,7 @@ Meeting ID: 860 7262 9011 Password: 001303
## 7 September 2021 ## 7 September 2021
* We discussed the data preparation process for real events and also which events would be finally selected based on O3b catalogue. Deep suggested to look for offline events to make sure that the info doesn't change. * We discussed the data preparation process for real events and also which events would be finally selected based on O3b catalogue. Deep suggested to look for offline events to make sure that the info doesn't change.
* J.R and Deep agree that we can send out preliminary set of results with the existing machine and background injections, we have about \~100 events with FPP<1e-2. * J.R and Deep agree that we can send out preliminary set of results with the existing machine and background injections, we have about <span dir="">\~</span>100 events with FPP<1e-2.
* Deep suggested to visually inspect the candidate pairs, based on their QTs and skymaps. * Deep suggested to visually inspect the candidate pairs, based on their QTs and skymaps.
### Action items: ### Action items:
...@@ -336,21 +345,14 @@ Meeting ID: 860 7262 9011 Password: 001303 ...@@ -336,21 +345,14 @@ Meeting ID: 860 7262 9011 Password: 001303
## 14 September 2021 ## 14 September 2021
* We discussed about the pending tasks before the result review and decided to follow up via emails till the code review finishes. * We discussed about the pending tasks before the result review and decided to follow up via emails till the code review finishes.
* Deep and JR both suggested to converted all the neccesary codes into scripts format as diff would work properly with scripts instead of notebooks. Both also suggested to write config files for training and testing the ML models. * Deep and JR both suggested to converted all the neccesary codes into scripts format as diff would work properly with scripts instead of notebooks. Both also suggested to write config files for training and testing the ML models.
### Action items: ### Action items:
- [x] Write config files for train-test workflow. * [x] Write config files for train-test workflow.
* [x] Generate dataset from scratch on CIT.
- [x] Generate dataset from scratch on CIT. * [x] Write a script and config for full ML predictions.
* [x] Update event list for O3 events and send to the lensing channel.
- [x] Write a script and config for full ML predictions. * [ ] get posterior paths and plot corners for the event pairs.
* [ ] Ask lensing group for the O3b representative psd.
- [x] Update event list for O3 events and send to the lensing channel. * [ ] Work on ML 2.0
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- [ ] get posterior paths and plot corners for the event pairs.
- [ ] Ask lensing group for the O3b representative psd.
- [ ] Work on ML 2.0
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