Difference between revisions of "LST1Analysis MVA2"

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LST1 Analysis 2024
+
'''LST1 Analysis after Software School 2024'''
 +
 
 +
== MVA Analysis pages ==
 +
* [https://www.lst1.iac.es/wiki/index.php/OP313_MVA OP313_MVA]
  
 
== Creating DL3 in the La Palma IT cluster ==
 
== Creating DL3 in the La Palma IT cluster ==
Line 5: Line 8:
 
School scripts/notebooks: '''/fefs/aswg/workspace/analysis-school-2024/cta-lstchain'''
 
School scripts/notebooks: '''/fefs/aswg/workspace/analysis-school-2024/cta-lstchain'''
  
−
* Open remote connection
+
<font style="color: red"> NOTE: the home directory has limited quota. Should use /fefs/aswg/workspace/monica.vazquez for the output instead!</font>
 +
 
 +
=== Open remote connection ===
 
<pre style="color: blue">
 
<pre style="color: blue">
 
ssh cp03
 
ssh cp03
Line 16: Line 21:
 
http://localhost:88XX/?token=YYYYYYYYYYYY
 
http://localhost:88XX/?token=YYYYYYYYYYYY
  
 +
In another terminal:
 
ssh -NfL localhost:88XX:localhost:88XX monica.vazquez@cp03
 
ssh -NfL localhost:88XX:localhost:88XX monica.vazquez@cp03
 
</pre>
 
</pre>
  
 +
=== Select good quality data ===
 
<pre style="color: blue">
 
<pre style="color: blue">
−
* Select good quality data
 
 
Run notebook:
 
Run notebook:
 
/home/monica.vazquez/LST1SCHOOL2024/notebooks/data_quality.ipynb
 
/home/monica.vazquez/LST1SCHOOL2024/notebooks/data_quality.ipynb
 
</pre>
 
</pre>
−
data_quality notebook settings:
+
data_quality notebook settings to select crab data taken in the night 2023/01/17:
 
<pre>
 
<pre>
 
files = glob.glob("/fefs/aswg/data/real/OSA/DL1DataCheck_LongTerm/v0.10/2023????/DL1_datacheck_2023*.h5")
 
files = glob.glob("/fefs/aswg/data/real/OSA/DL1DataCheck_LongTerm/v0.10/2023????/DL1_datacheck_2023*.h5")
Line 33: Line 39:
 
</pre>
 
</pre>
  
 +
To check the most recent version of all the data use this location:
 +
 +
'''/fefs/aswg/data/real/OSA/DL1DataCheck_LongTerm/night_wise/all/'''
  
−
Copy good run list to:
+
Copy the output good run list:
 +
<pre>
 
/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11699.h5
 
/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11699.h5
 
/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11700.h5
 
/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11700.h5
Line 40: Line 50:
 
/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11702.h5
 
/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11702.h5
 
/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11703.h5
 
/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11703.h5
 +
</pre>
 +
to
 +
/home/monica.vazquez/LST1SCHOOL2024/helpful_scripts/file_list.txt
 +
 +
=== DL1 to DL2 ===
 +
<pre style="color: blue">
 +
cd /home/monica.vazquez/LST1SCHOOL2024/helpful_scripts
 +
./launch_dl1_dl2.sh /fefs/aswg/data/models/AllSky/20230927_v0.10.4_crab_tuned/dec_2276 /fefs/aswg/data/models/AllSky/20230927_v0.10.4_crab_tuned/dec_2276/lstchain_config_2023-09-27.json
 +
# check batch job status
 +
squeue –u monica.vazquez
 +
# check they completed well
 +
sacct -u monica.vazquez
 +
</pre>
 +
 +
==== Processing v0.9 DL1 data ====
 +
 +
Process v0.9 DL1 files as if they were v0.10. Use lstchain v0.10 for the analysis, and v0.10 versions of the MC products (RF models and DL2).
 +
 +
==== Recommended MC trainings ====
 +
 +
Model files are located in: '''/fefs/aswg/data/models/AllSky/'''
 +
 +
{| class="wikitable"
 +
|-
 +
!colspan="3"| Recommended trainings
 +
|-
 +
| style="background-color: lightblue;"|
 +
'''Source'''
 +
| style="background-color: lightblue;"|
 +
'''Model'''
 +
| style="background-color: lightblue;"|
 +
'''json'''
 +
|-
 +
| Crab Nebula tuned
 +
| 20230927_v0.10.4_crab_tuned
 +
| lstchain_config_2023-09-27.json
 +
|-
 +
| Standard Dark complete production
 +
| 20230901_v0.10.4_allsky_base_prod
 +
| lstchain_config_2023-09-01.json
 +
|-
 +
| Standard Dark recent/incomplete!
 +
| 20240131_allsky_v0.10.5_all_dec_base
 +
| lstchain_config_2024-01-31.json
 +
|-
 +
|}
 +
 +
====Exploration of DL2 data====
 +
<pre style="color: blue">
 +
Run notebook:
 +
/home/monica.vazquez/LST1SCHOOL2024/notebooks/explore_DL2.ipynb
 +
</pre>
 +
 +
=== IRF creation ===
 +
Use the test MC of the same declination line used in the DL2 step
 +
 +
[[File:Examples_configs_pointings_19_1.png | 300px ]]
 +
 +
<pre style="color: blue">
 +
cd /home/monica.vazquez/LST1SCHOOL2024/helpful_scripts
 +
cp /fefs/aswg/workspace/analysis-school-2024/cta-lstchain/docs/examples/irf_dl3_tool_config.json .
 +
</pre>
 +
The default json has energy dependent gammaness and theta containment cuts of 70%
 +
<pre>
 +
"gh_efficiency": 0.7
 +
"theta_containment": 0.7
 +
</pre>
  
−
/home/monica.vazquez/LST1SCHOOL2024/helpful_scripts/file_list.txt
+
<pre style="color: blue">
 +
cd /home/monica.vazquez/LST1SCHOOL2024/helpful_scripts
 +
mkdir IRF
 +
DL2MC=/fefs/aswg/data/mc/DL2/AllSky/20230927_v0.10.4_crab_tuned/
 +
./launch_irf_creation.sh $DL2MC/TestingDataset/dec_2276 ./irf_dl3_tool_config.json gh_eff_0.7_th_cont_0.7
 
</pre>
 
</pre>
  
−
* DL1 to DL2 Step
+
=== DL2 to DL3 ===
 +
 
 
<pre style="color: blue">
 
<pre style="color: blue">
 
cd /home/monica.vazquez/LST1SCHOOL2024/helpful_scripts
 
cd /home/monica.vazquez/LST1SCHOOL2024/helpful_scripts
−
./launch_dl1_dl2.sh /fefs/aswg/data/models/AllSky/20230927_v0.10.4_crab_tuned/dec_2276 /fefs/aswg/data/models/AllSky/20230927_v0.10.4_crab_tuned/dec_2276/lstchain_config_2023-09-27.json
+
cp /fefs/aswg/workspace/analysis-school-2024/cta-lstchain/docs/examples/irf_dl3_tool_config.json .
 +
IRFDIR=IRF/20230927_v0.10.4_crab_tuned/dec_2276/gh_eff_0.7_th_cont_0.7
 +
./launch_dl2_dl3.sh ./irf_dl3_tool_config.json ./DL2 $IRFDIR Crab\ Nebula
 +
</pre>
 +
(if source name has a blank space you have to escape it, using a backslash)
 +
 
 +
==== Create DL3 index files ====
 +
<pre style="color: blue">
 +
cd /home/monica.vazquez/LST1SCHOOL2024/helpful_scripts/DL3
 +
lstchain_create_dl3_index_files -d ./DL3 -p dl3\*.fits.gz
 +
</pre>
 +
 
 +
In case the DL3 are unzipped, redo index file creation command:
 +
<pre style="color: red">
 +
gzip -d ./DL3/dl3\*.fits.gz
 +
lstchain_create_dl3_index_files --overwrite -d ./DL3 -p dl3\*.fits
 +
</pre>
 +
 
 +
Output files to be used together with DL3 in gammapy:
 +
 
 +
'''hdu-index.fits.gz''' and '''obs-index.fits.gz'''
 +
 
 +
== Running DL3 gammapy analysis locally ==
 +
 
 +
<pre style="color: blue">
 +
#mamba create -c conda-forge -n lstchain-v0.10.7 python=3.11 lstchain=0.10.7
 +
 
 +
conda activate lstchain-v0.10.7
 +
#transfer the DL3 files to laptop
 +
scp cp03:/home/monica.vazquez/LST1SCHOOL2024/helpful_scripts/DL3/*fits* /Users/monicava/Documents/CODE/LST1ANALYSIS/DL3/Crab_20230117
 +
</pre>
 +
 
 +
Run locally the notebooks:
 +
 
 +
* Theta2: '''plot_theta2_from_dl3.ipynb'''
 +
 
 +
Change/check:
 +
<pre>
 +
base_dir = Path("/Users/monicava/Documents/CODE/LST1ANALYSIS/DL3")
 +
label="Crab_20230117"
 +
dl3_path = base_dir / label
 +
 
 +
target_position = SkyCoord.from_name("Crab Nebula")
 +
</pre>
 +
[[File:theta2_Stacked_Crab_20230117.png | 400px ]]
 +
 
 +
* SED & LC: '''post_DL3_analysis.ipynb'''
 +
 
 +
Change/check:
 +
<pre>
 +
base_dir = Path("/Users/monicava/Documents/CODE/LST1ANALYSIS/DL3")
 +
label="Crab_20230117"
 +
dl3_path = base_dir / label
 +
 
 +
filename = dl3_path / "dl3_LST-1.Run11699.fits"
 +
 
 +
target_position = SkyCoord.from_name("Crab", frame='icrs')
 +
</pre>
 +
 
 +
[[File:SED_Crab_20230117.png | 400px ]] [[File:LC_Crab_20230117.png | 400px ]]
 +
 
 +
== DL3 cuts ==
 +
 
 +
The '''fill_X_cut''' is used by the main pyirf function [https://pyirf.readthedocs.io/en/latest/api/pyirf.cuts.calculate_percentile_cut.html#pyirf.cuts.calculate_percentile_cut pyirf.cuts.calculate_percentile_cut] to give a "fill value" for bins, where the number of events is lower than min_event_p_en_bin (100 by default). Here X can be for gammaness, theta or alpha.
 +
In principle, yes, one should change both max_X_cut and fill_X_cut appropriately. However, in lstchain, we have also added a "rolling" feature on the cut values for such bins, update_fill_cuts, which takes the values in the nearest filled bin
 +
The default consideration of 100 events, was tested for the energy axes with 5 energy bins per decade. So far, it seems reasonable for any analyses
 +
 
 +
By number of events you mean MC events with which to compute the cut for the requested efficiency, right?
 +
Yes, for each energy bin
 +
Indeed for the bins with too short MC stats I think adopting the closest (in E) bin with good stats is reasonable
 +
 
 +
== SLURM COMMANDS ==
 +
 
 +
<pre>
 +
squeue -u monica.vazquez
 +
squeue -t RUNNING
 +
scontrol show jobid XXX
 +
scancel -u monica.vazquez
 
</pre>
 
</pre>

Latest revision as of 11:04, 15 March 2024

LST1 Analysis after Software School 2024

MVA Analysis pages[edit]

Creating DL3 in the La Palma IT cluster[edit]

School scripts/notebooks: /fefs/aswg/workspace/analysis-school-2024/cta-lstchain

NOTE: the home directory has limited quota. Should use /fefs/aswg/workspace/monica.vazquez for the output instead!

Open remote connection[edit]

ssh cp03

source /fefs/aswg/software/conda/etc/profile.d/conda.sh
conda activate lstchain-v0.10.7
jupyter notebook --no-browser

Link for browser in printout:
http://localhost:88XX/?token=YYYYYYYYYYYY

In another terminal:
ssh -NfL localhost:88XX:localhost:88XX monica.vazquez@cp03

Select good quality data[edit]

Run notebook:
/home/monica.vazquez/LST1SCHOOL2024/notebooks/data_quality.ipynb

data_quality notebook settings to select crab data taken in the night 2023/01/17: 

files = glob.glob("/fefs/aswg/data/real/OSA/DL1DataCheck_LongTerm/v0.10/2023????/DL1_datacheck_2023*.h5")
source_coordinates = SkyCoord.from_name("Crab Nebula")
max_zenith = 35 * u.deg
first_date = 20230117
last_date  = 20230117

To check the most recent version of all the data use this location:

/fefs/aswg/data/real/OSA/DL1DataCheck_LongTerm/night_wise/all/

Copy the output good run list: 

/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11699.h5
/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11700.h5
/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11701.h5
/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11702.h5
/fefs/aswg/data/real/DL1/20230117/v0.10/tailcut84/dl1_LST-1.Run11703.h5

to /home/monica.vazquez/LST1SCHOOL2024/helpful_scripts/file_list.txt

DL1 to DL2[edit]

cd /home/monica.vazquez/LST1SCHOOL2024/helpful_scripts
./launch_dl1_dl2.sh /fefs/aswg/data/models/AllSky/20230927_v0.10.4_crab_tuned/dec_2276 /fefs/aswg/data/models/AllSky/20230927_v0.10.4_crab_tuned/dec_2276/lstchain_config_2023-09-27.json
# check batch job status
squeue –u monica.vazquez
# check they completed well
sacct -u monica.vazquez

Processing v0.9 DL1 data[edit]

Process v0.9 DL1 files as if they were v0.10. Use lstchain v0.10 for the analysis, and v0.10 versions of the MC products (RF models and DL2).

Recommended MC trainings[edit]

Model files are located in: /fefs/aswg/data/models/AllSky/

Recommended trainings

Source

Model

json

Crab Nebula tuned 20230927_v0.10.4_crab_tuned lstchain_config_2023-09-27.json
Standard Dark complete production 20230901_v0.10.4_allsky_base_prod lstchain_config_2023-09-01.json
Standard Dark recent/incomplete! 20240131_allsky_v0.10.5_all_dec_base lstchain_config_2024-01-31.json

Exploration of DL2 data[edit]

Run notebook:
/home/monica.vazquez/LST1SCHOOL2024/notebooks/explore_DL2.ipynb

IRF creation[edit]

Use the test MC of the same declination line used in the DL2 step

Examples configs pointings 19 1.png 

cd /home/monica.vazquez/LST1SCHOOL2024/helpful_scripts
cp /fefs/aswg/workspace/analysis-school-2024/cta-lstchain/docs/examples/irf_dl3_tool_config.json .

The default json has energy dependent gammaness and theta containment cuts of 70% 

"gh_efficiency": 0.7
"theta_containment": 0.7

cd /home/monica.vazquez/LST1SCHOOL2024/helpful_scripts
mkdir IRF
DL2MC=/fefs/aswg/data/mc/DL2/AllSky/20230927_v0.10.4_crab_tuned/
./launch_irf_creation.sh $DL2MC/TestingDataset/dec_2276 ./irf_dl3_tool_config.json gh_eff_0.7_th_cont_0.7

DL2 to DL3[edit]

cd /home/monica.vazquez/LST1SCHOOL2024/helpful_scripts
cp /fefs/aswg/workspace/analysis-school-2024/cta-lstchain/docs/examples/irf_dl3_tool_config.json .
IRFDIR=IRF/20230927_v0.10.4_crab_tuned/dec_2276/gh_eff_0.7_th_cont_0.7
./launch_dl2_dl3.sh ./irf_dl3_tool_config.json ./DL2 $IRFDIR Crab\ Nebula

(if source name has a blank space you have to escape it, using a backslash)

Create DL3 index files[edit]

cd /home/monica.vazquez/LST1SCHOOL2024/helpful_scripts/DL3
lstchain_create_dl3_index_files -d ./DL3 -p dl3\*.fits.gz

In case the DL3 are unzipped, redo index file creation command: 

gzip -d ./DL3/dl3\*.fits.gz
lstchain_create_dl3_index_files --overwrite -d ./DL3 -p dl3\*.fits

Output files to be used together with DL3 in gammapy:

hdu-index.fits.gz and obs-index.fits.gz

Running DL3 gammapy analysis locally[edit]

#mamba create -c conda-forge -n lstchain-v0.10.7 python=3.11 lstchain=0.10.7 

conda activate lstchain-v0.10.7
#transfer the DL3 files to laptop
scp cp03:/home/monica.vazquez/LST1SCHOOL2024/helpful_scripts/DL3/*fits* /Users/monicava/Documents/CODE/LST1ANALYSIS/DL3/Crab_20230117

Run locally the notebooks:

  • Theta2: plot_theta2_from_dl3.ipynb

Change/check: 

base_dir = Path("/Users/monicava/Documents/CODE/LST1ANALYSIS/DL3")
label="Crab_20230117" 
dl3_path = base_dir / label

target_position = SkyCoord.from_name("Crab Nebula")

Theta2 Stacked Crab 20230117.png

  • SED & LC: post_DL3_analysis.ipynb

Change/check: 

base_dir = Path("/Users/monicava/Documents/CODE/LST1ANALYSIS/DL3")
label="Crab_20230117" 
dl3_path = base_dir / label

filename = dl3_path / "dl3_LST-1.Run11699.fits"

target_position = SkyCoord.from_name("Crab", frame='icrs')

SED Crab 20230117.png LC Crab 20230117.png

DL3 cuts[edit]

The fill_X_cut is used by the main pyirf function pyirf.cuts.calculate_percentile_cut to give a "fill value" for bins, where the number of events is lower than min_event_p_en_bin (100 by default). Here X can be for gammaness, theta or alpha. In principle, yes, one should change both max_X_cut and fill_X_cut appropriately. However, in lstchain, we have also added a "rolling" feature on the cut values for such bins, update_fill_cuts, which takes the values in the nearest filled bin The default consideration of 100 events, was tested for the energy axes with 5 energy bins per decade. So far, it seems reasonable for any analyses

By number of events you mean MC events with which to compute the cut for the requested efficiency, right? Yes, for each energy bin Indeed for the bins with too short MC stats I think adopting the closest (in E) bin with good stats is reasonable

SLURM COMMANDS[edit]

squeue -u monica.vazquez
squeue -t RUNNING 
scontrol show jobid XXX
scancel -u monica.vazquez
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