Difference between revisions of "BCAL hadronic efficiencies"
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== Description of Method == | == Description of Method == | ||
+ | |||
+ | This procedure determines a (biased) efficiency for each cell using charged tracks that are tracked with the drift chambers and point at the BCAL. The sample of tracks consists of charged particles with a reconstructed track and a matched shower in the BCAL. While the absolute value of the efficiency does not reflect the true efficiency of a cell, it is used to monitor the uniformity from run to run and can effectively identify issues with the data and the software reconstruction process. In checking the efficiency for a given layer, the algorithm requires a pointing track and a hit in at least one layer past the layer of interest, except for layer 4 since this is the last layer. The code then checks whether here is a hit close to the extrapolated track in the layer of interest (currently +/- 3 sectors). An inefficiency is tagged if no hit is found in this range. Efficiencies are computed, averaged over other variables, as a function of position along the calorimeter z, track momentum pmom, and cell id. | ||
+ | |||
+ | The cell id is defined as id = 4(Module-1) + sector; Module = (id-1)/4 + 1; sector = id - (Module-1)*4. id range= [1-192], Module range = [1-48], sector range = [1-4] | ||
== Analysis Procedure == | == Analysis Procedure == | ||
− | The code is located on [https://github.com/JeffersonLab/halld_recon/tree/master/src/plugins/monitoring/BCAL_Hadronic_Eff Github]. The user will be mainly interested in the scripts contained in the folder ''ROOT_macros | + | The code is located on [https://github.com/JeffersonLab/halld_recon/tree/master/src/plugins/monitoring/BCAL_Hadronic_Eff Github]. The user will be mainly interested in the scripts contained in the folder ''ROOT_macros. |
− | Steps to extract the BCAL Hadronic Efficiencies: | + | Steps to extract the BCAL Hadronic Efficiencies (see README file on Github): |
− | + | # Generate the root trees using the BCAL_Hadronic_Eff plugin. This is usually completed as part of the routine GlueX monitoring launches. | |
− | + | #* The output trees are located in files such as /cache/halld/offline_monitoring/RunPeriod-2019-11/ver12/tree_bcal_hadronic_eff/merged/tree_*.root | |
+ | # Run python script Read_bcal_hadronic_eff2.py. Edit the file as needed to point to the correct directories. | ||
+ | #* Create directories with the names of 'root', 'dat' and 'pdf' | ||
+ | #* Execute the python script Read_bcal_hadronic_eff2.py. | ||
+ | #* This script iteratively executes the Read_bcal_hadronic_eff2.C script on each of the root trees. | ||
+ | #* The ROOT output files will be placed in the 'root/' subdirectory. | ||
+ | #* Summaries of the efficiencies are stored in the 'dat/' subdirectory. These will be used later for plotting summaries. | ||
+ | #* Output plots with details of the efficiency systematics are placed in the 'pdf/' subdirectory. These can be checked for problems. | ||
+ | # Run python script plot_bcal_hadronic_eff.py. Edit the file as needed to point to the correct directories. | ||
+ | #* The output of this script is just a file called plot_bcal_hadronic_eff.list, which contains the list of run numbers obtained from the 'dat' subdirectory. | ||
+ | # Run the ROOT script plot_bcal_hadronic_eff.C, Edit as needed to produce useful output. | ||
+ | #* The output of this script is the file bcal_hadronic_eff.pdf file with various plots of efficiency vs run number. | ||
− | + | == Index Mapping == | |
− | + | * The mapping between the index in the BCAL Hadronic Efficiency histograms and module is as follows (the mapping is for each layer): | |
− | + | * Correspondence between histogram id and Module/Sector: id = 4*(Module-1) + sector; Module = (id-1)/4 + 1; sector = id - (Module-1)*4. | |
− | + | * Range of variables: Histogram id range= [1-192], module=[1-48], sector=[1-4] | |
− | + | ||
− | + | ||
− | + | == MC Efficiency table == | |
− | + | ||
− | + | * If inefficient or dead channels are found, the CCDB channel_mc_efficiency table should be updated to match the data. A script to update CCDB can be found on GitHub: | |
− | + | * [https://github.com/JeffersonLab/hd_utilities/blob/master/CCDButils/ccdb_put_channel_mc_efficiency.py Python script to update CCDB channel_mc_efficiency] | |
+ | * CCDB id = (module-1)*32 + (layer-1)*8 + (sector-1)*2 + end | ||
+ | * Range of variables: CCDB id=[0-1535], module=[1-48], layer=[1-4], sector=[1-4], end=[0-1], where up=0, down=1. | ||
== Data Studies == | == Data Studies == | ||
+ | * Log book entry for Spring 2020 [https://logbooks.jlab.org/entry/3873741 Spring 2020 ver26] | ||
+ | * Log book entry for Spring 2020 [https://logbooks.jlab.org/entry/3854515 Spring 2020 ver17] with a link to Tolga's validation plots | ||
+ | * Log book entry for Spring 2020 [https://logbooks.jlab.org/entry/3845485 Spring 2020 ver18] | ||
+ | * Log book entry for Spring 2020 [https://logbooks.jlab.org/entry/3845480 Spring 2020 ver16] | ||
+ | * Log book entry for Spring 2020 [https://logbooks.jlab.org/entry/3830769 Log Entry 3830769]. Set CCDB BCAL/channel_mc_efficiency for M22 S3 L4 Up (Runs 72120-72435). | ||
+ | * Log book entry for Spring 2020 [https://logbooks.jlab.org/entry/3817726 Log Entry 3817726]. Set CCDB BCAL/channel_mc_efficiency for M37 L1 S4 Down (Runs 72316-72369) | ||
* Log book entry for Spring 2020 data [https://logbooks.jlab.org/entry/3812382 Log Entry 3812382] | * Log book entry for Spring 2020 data [https://logbooks.jlab.org/entry/3812382 Log Entry 3812382] | ||
* Log book entry for 2018 [https://logbooks.jlab.org/entry/3642018 Log Entry 3642018] | * Log book entry for 2018 [https://logbooks.jlab.org/entry/3642018 Log Entry 3642018] | ||
* Log book entry for 2017 tracking improvements (comparison between versions 19 and 21) [https://logbooks.jlab.org/entry/3486656 Log Entry 3486656] | * Log book entry for 2017 tracking improvements (comparison between versions 19 and 21) [https://logbooks.jlab.org/entry/3486656 Log Entry 3486656] | ||
* Log book entry for 2016 and 2017 efficiency studies [https://logbooks.jlab.org/entry/3478578 Log Entry 3478578]. Shows comparison of data and MC and including inefficient channels into the CCDB database. | * Log book entry for 2016 and 2017 efficiency studies [https://logbooks.jlab.org/entry/3478578 Log Entry 3478578]. Shows comparison of data and MC and including inefficient channels into the CCDB database. |
Latest revision as of 14:49, 19 May 2022
Contents
Description of Method
This procedure determines a (biased) efficiency for each cell using charged tracks that are tracked with the drift chambers and point at the BCAL. The sample of tracks consists of charged particles with a reconstructed track and a matched shower in the BCAL. While the absolute value of the efficiency does not reflect the true efficiency of a cell, it is used to monitor the uniformity from run to run and can effectively identify issues with the data and the software reconstruction process. In checking the efficiency for a given layer, the algorithm requires a pointing track and a hit in at least one layer past the layer of interest, except for layer 4 since this is the last layer. The code then checks whether here is a hit close to the extrapolated track in the layer of interest (currently +/- 3 sectors). An inefficiency is tagged if no hit is found in this range. Efficiencies are computed, averaged over other variables, as a function of position along the calorimeter z, track momentum pmom, and cell id.
The cell id is defined as id = 4(Module-1) + sector; Module = (id-1)/4 + 1; sector = id - (Module-1)*4. id range= [1-192], Module range = [1-48], sector range = [1-4]
Analysis Procedure
The code is located on Github. The user will be mainly interested in the scripts contained in the folder ROOT_macros.
Steps to extract the BCAL Hadronic Efficiencies (see README file on Github):
- Generate the root trees using the BCAL_Hadronic_Eff plugin. This is usually completed as part of the routine GlueX monitoring launches.
- The output trees are located in files such as /cache/halld/offline_monitoring/RunPeriod-2019-11/ver12/tree_bcal_hadronic_eff/merged/tree_*.root
- Run python script Read_bcal_hadronic_eff2.py. Edit the file as needed to point to the correct directories.
- Create directories with the names of 'root', 'dat' and 'pdf'
- Execute the python script Read_bcal_hadronic_eff2.py.
- This script iteratively executes the Read_bcal_hadronic_eff2.C script on each of the root trees.
- The ROOT output files will be placed in the 'root/' subdirectory.
- Summaries of the efficiencies are stored in the 'dat/' subdirectory. These will be used later for plotting summaries.
- Output plots with details of the efficiency systematics are placed in the 'pdf/' subdirectory. These can be checked for problems.
- Run python script plot_bcal_hadronic_eff.py. Edit the file as needed to point to the correct directories.
- The output of this script is just a file called plot_bcal_hadronic_eff.list, which contains the list of run numbers obtained from the 'dat' subdirectory.
- Run the ROOT script plot_bcal_hadronic_eff.C, Edit as needed to produce useful output.
- The output of this script is the file bcal_hadronic_eff.pdf file with various plots of efficiency vs run number.
Index Mapping
- The mapping between the index in the BCAL Hadronic Efficiency histograms and module is as follows (the mapping is for each layer):
- Correspondence between histogram id and Module/Sector: id = 4*(Module-1) + sector; Module = (id-1)/4 + 1; sector = id - (Module-1)*4.
- Range of variables: Histogram id range= [1-192], module=[1-48], sector=[1-4]
MC Efficiency table
- If inefficient or dead channels are found, the CCDB channel_mc_efficiency table should be updated to match the data. A script to update CCDB can be found on GitHub:
- Python script to update CCDB channel_mc_efficiency
- CCDB id = (module-1)*32 + (layer-1)*8 + (sector-1)*2 + end
- Range of variables: CCDB id=[0-1535], module=[1-48], layer=[1-4], sector=[1-4], end=[0-1], where up=0, down=1.
Data Studies
- Log book entry for Spring 2020 Spring 2020 ver26
- Log book entry for Spring 2020 Spring 2020 ver17 with a link to Tolga's validation plots
- Log book entry for Spring 2020 Spring 2020 ver18
- Log book entry for Spring 2020 Spring 2020 ver16
- Log book entry for Spring 2020 Log Entry 3830769. Set CCDB BCAL/channel_mc_efficiency for M22 S3 L4 Up (Runs 72120-72435).
- Log book entry for Spring 2020 Log Entry 3817726. Set CCDB BCAL/channel_mc_efficiency for M37 L1 S4 Down (Runs 72316-72369)
- Log book entry for Spring 2020 data Log Entry 3812382
- Log book entry for 2018 Log Entry 3642018
- Log book entry for 2017 tracking improvements (comparison between versions 19 and 21) Log Entry 3486656
- Log book entry for 2016 and 2017 efficiency studies Log Entry 3478578. Shows comparison of data and MC and including inefficient channels into the CCDB database.