Difference between revisions of "LST1School2021 MVA"

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m (Monicava moved page LST1School2021 to LST1School2021 MVA)
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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 NAME.SURNAME@cp01
+
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 NAME.SURNAME@cp01
+
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>

Revision as of 12:50, 8 February 2022

  • 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 &