Difference between revisions of "LST1School2021 MVA"
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| + | == DL2 analysis == | ||
| + | |||
| + | == 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] | * Login in La Palma cluster instructions: [https://indico.cta-observatory.org/event/3687/attachments/20250/28790/Requirements.pdf Requirements.pdf] | ||
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conda activate lstchain-v0.8.2 | conda activate lstchain-v0.8.2 | ||
jupyter notebook --no-browser | jupyter notebook --no-browser | ||
| − | ssh -NfL localhost:8889:localhost:8889 | + | ssh -NfL localhost:8889:localhost:8889 monica.vazquez@cp01 |
Open URL of notebook in local browser | Open URL of notebook in local browser | ||
</pre> | </pre> | ||
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conda activate lst-school-2022-01-magic-lst1 | conda activate lst-school-2022-01-magic-lst1 | ||
jupyter notebook --no-browser | jupyter notebook --no-browser | ||
| − | ssh -NfL localhost:8889:localhost:8889 | + | ssh -NfL localhost:8889:localhost:8889 monica.vazquez@cp01 |
</pre> | </pre> | ||
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mamba env create -f environment_glearn.yml | mamba env create -f environment_glearn.yml | ||
conda activate glearn | conda activate glearn | ||
| + | </pre> | ||
| + | |||
| + | * ViTables | ||
| + | <pre style="color: blue"> | ||
| + | conda create --name vitables pytables pyqt | ||
| + | conda activate vitables | ||
| + | pip install ViTables | ||
| + | ./ViTables & | ||
</pre> | </pre> | ||
Latest revision as of 16:41, 8 February 2022
DL2 analysis[edit]
Software[edit]
- Login in La Palma cluster instructions: Requirements.pdf
- 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
- Repository of example notebooks: 2022_01_lstchain_school
- 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 &
