LST analysis school January 2022 https://indico.cta-observatory.org/event/3687/
git clone https://github.com/cta-observatory/2022_01_lstchain_school.git
- You will need to install mamba :
conda install -c conda-forge -n base mamba
then, in the folder where you cloned your repo (2022_01_lstchain_school):
mamba env create -f environment.yml
This will install the version 0.8.4 of lstchain in the environment "lst-school-2022-01".
Anytime you want to use this environment in a new terminal, you have to activate it using:
conda activate lst-school-2022-01
Due to different versions of ctapipe
(v0.12 against v0.11) used for this session, we need to work with a different conda
environment.
If you want to work at the IT container, simply activate the lst-school-2022-01-magic-lst1
environment:
conda activate lst-school-2022-01-magic-lst1
and run the notebooks from there.
If you want to run the examples locally (recommended), you have to create a separate environment. Please do:
git clone https://github.com/cta-observatory/magic-cta-pipe.git
cd magic-cta-pipe
conda env create -n lst-school-2022-01-magic-lst1 -f environment.yml
conda activate lst-school-2022-01-magic-lst1
pip install .
Then follow the notebooks that are available in this repo (directory lst1_magic
).
The data used for the MAGIC+LST1 session are available at the IT container, see below. So you just need to synchronize again in order to download them (around 500 MB).
We collected a subset of LST data that you should copy to your computer and that is needed to run the notebooks locally.
To download the data, run this command from the base directory of this repository:
rsync -a --info=progress2 cp01:/fefs/aswg/workspace/analysis-school-2022/ data/
If you are on macOS, either install a more recent rsync using brew or leave out the --info option.