O3b-analysis.md

@@ -43,7 +43,7 @@ The test has been performed using a LALInference based code, and the details of
 | --- | --- | --- | --- | --- |---|---|
 | 1. | [events_selection_o3b_new.ipynb](https://git.ligo.org/muhammed.saleem/o3siqm-updates/-/blob/master/o3b/scripts/PE_o3b/events_selection_o3b_new.ipynb) | sayantani.datta| Notebook adapted from [here](https://git.ligo.org/publications/O3/o3b-cbc-tgr/-/blob/master/scripts/PE/events_snr.ipynb) with  git hash:`e5ef6b6e17de7a2e4156087fd1e5038937929a32`. The diff file with the modified version can be found here on CIT:`/home/sayantani.datta/repos/o3siqm-updates/o3b/scripts/PE_o3b/diff_o3b_selection_OG_mod.txt`. Since SIQM tests work better for spinning systems, a selection criteria is added which checks if chi_eff posteriors exclude zero at least at 68% CI. This is for o3b events. | | Run these notebook on CIT within any suitable conda env like `igwn-py38-20210107` |Anuradha :heavy_check_mark: (aedc4806713205e225f0eb3b4c3fcdb570350768)  <br> Aditya :heavy_check_mark: (aedc4806713205e225f0eb3b4c3fcdb570350768) |
 | 2. | [event_selection_o3a.py](https://git.ligo.org/muhammed.saleem/o3siqm-updates/-/blob/master/o3b/scripts/event_selection_o3a.py) | sayantani.datta| Inspiral SNR calculation section is adapted from [here](https://git.ligo.org/publications/O3/o3a-cbc-tgr/-/blob/master/notebooks/Event_Selection_Optimal_SNR.ipynb). Since SIQM tests work better for spinning systems, a selection criteria is added which checks if chi_eff posteriors exclude zero at 95%/68% credible levels. This is for o3a events.  | Archisman: Script looks good. Need to check that the events listed below line 234 are indeed the ones which do not satisfy the iFAR criterion. | Run these notebook on CIT within any suitable conda env like `igwn-py38-20210107` | Aditya :heavy_check_mark: (b5bc0d054068a9e0f16962111c6f80eeaaa26622)  <br> Archisman :heavy_check_mark: |
-| 3. | [event_selection_o1o2.py](https://git.ligo.org/muhammed.saleem/o3siqm-updates/-/blob/master/o3b/scripts/event_selection_o1o2.py) | divyajyoti.nln | Events have been selected from the list used in O3a analysis ([Table2A](https://git.ligo.org/nv.krishnendu/lalsuite/-/wikis/O3a-Spin-Quadrupole-BH-mimicker-test-results/o3a-review-report/#table-2a-list-of-events-from-o1o2-for-all-these-cases-psd-is-fixed-to-the-one-given-in-the-base-config-file)). Since SIQM tests work better for spinning systems, a selection criteria is added which checks if chi_eff posteriors exclude zero at 95%/68% credible levels. This is for o1o2 events.  |  | Run these notebook on CIT within any suitable conda env like `igwn-py38-20210107` | Aditya  <br> Archisman |
+| 3. | [event_selection_o1o2.ipynb](https://git.ligo.org/muhammed.saleem/o3siqm-updates/-/blob/master/o3b/scripts/event_selection_o1o2.ipynb) | divyajyoti.nln | Events have been selected from the list used in O3a analysis ([Table2A](https://git.ligo.org/nv.krishnendu/lalsuite/-/wikis/O3a-Spin-Quadrupole-BH-mimicker-test-results/o3a-review-report/#table-2a-list-of-events-from-o1o2-for-all-these-cases-psd-is-fixed-to-the-one-given-in-the-base-config-file)). Since SIQM tests work better for spinning systems, a selection criteria is added which checks if chi_eff posteriors exclude zero at 95%/68% credible levels. This is for o1o2 events.  |  | Run these notebook on CIT within any suitable conda env like `igwn-py38-20210107` | Aditya  <br> Archisman |
 
 ### Config and PE sample checks
 
@@ -68,7 +68,7 @@ The test has been performed using a LALInference based code, and the details of
 |1. | [create_samples_all.py](https://git.ligo.org/muhammed.saleem/o3siqm-updates/-/blob/master/o3b/scripts/create_samples_all.py)  | divyajyoti.nln | Creates PESummary pages for all runs and stores them at /home/tgr.o3/o3b-tgr/results/sim/o3b |  | 1. Activate conda env on CIT: `source /cvmfs/oasis.opensciencegrid.org/ligo/sw/conda/etc/profile.d/conda.sh`<br/> `conda activate igwn-py38` 2. Run with python | Aditya :heavy_check_mark: (ca1594207cdf1c923d299f10a11851a8b9a75484) : <br> Anuradha :heavy_check_mark: (ca1594207cdf1c923d299f10a11851a8b9a75484)|
 |2. | [upload_to_data_release.py](https://git.ligo.org/muhammed.saleem/o3siqm-updates/-/blob/master/o3b/scripts/upload_to_data_release.py)  | divyajyoti.nln | Copies the final samples into the data release directory in CIT: `/home/tgr.o3/o3b-tgr/results/sim/` |  | 1. Activate conda env on CIT: `source /cvmfs/oasis.opensciencegrid.org/ligo/sw/conda/etc/profile.d/conda.sh`<br/> `conda activate igwn-py38` 2. Run with python | Archisman :heavy_check_mark: <br> Anuradha :heavy_check_mark: (8329e4d437dc882afacd078efa4bbc7188aaab34)|
 |2. | [pull_data_updated.py](https://git.ligo.org/muhammed.saleem/o3siqm-updates/-/blob/master/o3b/scripts/pull_data_updated.py)  | Krishnendu| Creates release ready samples *.dat.gz at /home/tgr.o3/o3b-tgr/release/sim/{EVENTS} for all events from taking samples from /home/tgr.o3/o3b-tgr/results/sim/o3b  |  | 1. Activate conda env on CIT: `source /cvmfs/oasis.opensciencegrid.org/ligo/sw/conda/etc/profile.d/conda.sh`<br/> `conda activate igwn-py38` 2. Run with python | Archisman: :heavy_check_mark: (4162c84e) <br> Anuradha: :x:|
-|3. | [get_o1o2o3a_events.ipynb](https://git.ligo.org/muhammed.saleem/o3siqm-updates/-/blob/master/o3b/scripts/get_o1o2o3a_events.ipynb)  | Krishnendu| Take  *.dat.gz samples of o1o2o3a events from the release repo and update /home/tgr.o3/o3b-tgr/results/sim/{EVENTS}  | Archisman: The link to the script seems incorrect. | 1. Activate conda env on CIT: `source /cvmfs/oasis.opensciencegrid.org/ligo/sw/conda/etc/profile.d/conda.sh`<br/> `conda activate igwn-py38` 2. Run with python | Archisman: :heavy_check_mark: (60d6a600) <br> Anuradha: :x:|
+|3. | [get_o1o2o3a_events.py](https://git.ligo.org/muhammed.saleem/o3siqm-updates/-/blob/master/o3b/scripts/get_o1o2o3a_events.py)  | Krishnendu| Take  *.dat.gz samples of o1o2o3a events from the release repo and update /home/tgr.o3/o3b-tgr/results/sim/{EVENTS}  | Archisman: The link to the script seems incorrect. | 1. Activate conda env on CIT: `source /cvmfs/oasis.opensciencegrid.org/ligo/sw/conda/etc/profile.d/conda.sh`<br/> `conda activate igwn-py38` 2. Run with python | Archisman: :heavy_check_mark: (60d6a600) <br> Anuradha: :x:|
 
 ## O3b data release details: [wiki link](https://git.ligo.org/nv.krishnendu/lalsuite/-/wikis/O3b-data-release)