Difference between revisions of "LST1School2021 MVA"

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Test
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== DL2 analysis ==
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== Software ==
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* Login in La Palma cluster instructions: [https://indico.cta-observatory.org/event/3687/attachments/20250/28790/Requirements.pdf Requirements.pdf]
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* Running remote notebook in the La Palma IT cluster
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<pre style="color: blue">
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ssh cp01
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source /fefs/aswg/software/conda/etc/profile.d/conda.sh
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conda activate lstchain-v0.8.2
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jupyter notebook --no-browser
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ssh -NfL localhost:8889:localhost:8889 monica.vazquez@cp01
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Open URL of notebook in local browser
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</pre>
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* Install lstchain in your local machine
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<pre style="color: blue">
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LSTCHAIN_VER=0.8.3
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wget https://raw.githubusercontent.com/cta-observatory/cta-lstchain/v$LSTCHAIN_VER/environment.yml
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conda env create -n lst -f environment.yml
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conda activate lst
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pip install lstchain==$LSTCHAIN_VER
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pip install lstmcpipe==0.5.1
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</pre>
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* Repository of example notebooks: [https://github.com/cta-observatory/2022_01_lstchain_school 2022_01_lstchain_school]
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* Install school software/data in your local machine & get data
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https://github.com/cta-observatory/2022_01_lstchain_school/blob/main/README.md
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<pre style="color: blue">
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conda install -c conda-forge -n base mamba
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git clone https://github.com/cta-observatory/2022_01_lstchain_school.git
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cd 2022_01_lstchain_school
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mamba env create -f environment.yml
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mamba activate lst-school-2022-01
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rsync -a cp01:/fefs/aswg/workspace/analysis-school-2022/ data/
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</pre>
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* LST1 + MAGIC analysis
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<pre style="color: blue">
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ssh cp01
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source /fefs/aswg/software/conda/etc/profile.d/conda.sh
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conda activate lst-school-2022-01-magic-lst1
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jupyter notebook --no-browser
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ssh -NfL localhost:8889:localhost:8889 monica.vazquez@cp01
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</pre>
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*GAMMALEARN
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<pre style="color: blue">
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cd /Users/monicava/LSTSCHOOL3/2022_01_lstchain_school/gammalearn
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mamba env create -f environment_glearn.yml
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conda activate glearn
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</pre>
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* ViTables
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<pre style="color: blue">
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conda create --name vitables pytables pyqt
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conda activate vitables
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pip install ViTables
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./ViTables &
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</pre>

Latest revision as of 16:41, 8 February 2022

DL2 analysis[edit]

Software[edit]

  • Running remote notebook in the La Palma IT cluster
ssh cp01
source /fefs/aswg/software/conda/etc/profile.d/conda.sh
conda activate lstchain-v0.8.2
jupyter notebook --no-browser
ssh -NfL localhost:8889:localhost:8889 monica.vazquez@cp01
Open URL of notebook in local browser
  • Install lstchain in your local machine
LSTCHAIN_VER=0.8.3
wget https://raw.githubusercontent.com/cta-observatory/cta-lstchain/v$LSTCHAIN_VER/environment.yml
conda env create -n lst -f environment.yml
conda activate lst
pip install lstchain==$LSTCHAIN_VER
pip install lstmcpipe==0.5.1
  • Install school software/data in your local machine & get data

https://github.com/cta-observatory/2022_01_lstchain_school/blob/main/README.md

conda install -c conda-forge -n base mamba

git clone https://github.com/cta-observatory/2022_01_lstchain_school.git
cd 2022_01_lstchain_school

mamba env create -f environment.yml
mamba activate lst-school-2022-01

rsync -a cp01:/fefs/aswg/workspace/analysis-school-2022/ data/
  • LST1 + MAGIC analysis
ssh cp01
source /fefs/aswg/software/conda/etc/profile.d/conda.sh
conda activate lst-school-2022-01-magic-lst1
jupyter notebook --no-browser
ssh -NfL localhost:8889:localhost:8889 monica.vazquez@cp01
  • GAMMALEARN
cd /Users/monicava/LSTSCHOOL3/2022_01_lstchain_school/gammalearn
mamba env create -f environment_glearn.yml
conda activate glearn
  • ViTables
conda create --name vitables pytables pyqt
conda activate vitables
pip install ViTables 
./ViTables &