Difference between revisions of "LST1School2021 MVA"
| Line 23: | Line 23: | ||
* Repository of example notebooks: [https://github.com/cta-observatory/2022_01_lstchain_school 2022_01_lstchain_school] | * Repository of example notebooks: [https://github.com/cta-observatory/2022_01_lstchain_school 2022_01_lstchain_school] | ||
| − | * Install school software/data in your local machine | + | * Install school software/data in your local machine & get data |
https://github.com/cta-observatory/2022_01_lstchain_school/blob/main/README.md | https://github.com/cta-observatory/2022_01_lstchain_school/blob/main/README.md | ||
<pre style="color: blue"> | <pre style="color: blue"> | ||
| Line 33: | Line 33: | ||
mamba env create -f environment.yml | mamba env create -f environment.yml | ||
mamba activate lst-school-2022-01 | mamba activate lst-school-2022-01 | ||
| + | |||
| + | rsync -a cp01:/fefs/aswg/workspace/analysis-school-2022/ data/ | ||
</pre> | </pre> | ||
Revision as of 10:37, 8 February 2022
- 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 NAME.SURNAME@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
