Difference between revisions of "LST1Analysis MVA"

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== Ctools ==
 
== Ctools ==
 +
<pre style="color: blue">
 +
conda config --append channels conda-forge
 +
conda config --append channels cta-observatory
 +
conda create -n ctathai python=3.8
 +
conda activate ctathai
 +
conda install ctools
 +
conda install matplotlib
 +
conda install jupyterlab
 +
export CALDB=/path/where/you/installed/IRF/caldb
 +
export HESSDATA=/path/where/you/installed/HESS/data
 +
</pre>
 +
 +
=== Ctools commands ===
 
<pre style="color: blue">
 
<pre style="color: blue">
 
ctobssim  edisp=yes
 
ctobssim  edisp=yes
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$CTOOLS/share/examples/python/show_residuals.py resspec.fits
 
$CTOOLS/share/examples/python/show_residuals.py resspec.fits
 
</pre>
 
</pre>
 
  
 
== Fermipy ==
 
== Fermipy ==

Revision as of 08:58, 26 August 2021

Location of LST1 data at PIC

  • Directory: /pnfs/pic.es/data/cta/LST/Data/ZFITS/

Location of LST1 at La Palma

  • Directory: /fefs/onsite/data
    Use cp01/cp02 to copy out data, never the login machine

Run summary info/data-check

CTApipe

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

CTAPIPE_VER=0.10.5
wget https://raw.githubusercontent.com/cta-observatory/ctapipe/v$CTAPIPE_VER/environment.yml
conda env create -n cta -f environment.yml
conda activate cta
conda install -c conda-forge ctapipe=$CTAPIPE_VER

Analysis of LST1 data

Donwload LST analysis software cta-lstchain (wrapper that uses centrally supported ctapipe routines)

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

LSTCHAIN_VER=0.7.2
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
rm environment.yml

In case of problems with conda env try mamba:
conda install -c conda-forge -n base mamba
mamba env create -f environment.yml

Files needed to analyze golden Run 442 (20190527):

  • Pedestal run: pedestal_file_run446_0000.fits
  • Low level DRS4 calibration: calibration.hdf5

Run directly jupyter notebook

cd cta-lstchain/notebooks
jupyter notebook
-> select Analyze_real_muon_data.ipynb

Convert example jupyter notebook to python

cd cta-lstchain/notebooks
jupyter nbconvert --to python Analyze_real_muon_data.ipynb

Fix path of data, pedestal and calibration and run!

Lines to fix:
source = event_source(input_url="../data/LST-1.4.Run00442.0001.fits.fz",max_events=None)
pedestal_path="../pedestal/pedestal_file_run446_0000.fits",
with HDF5TableReader('../calibration/calibration.hdf5') as h5_table:

python Analyze_real_muon_data.py

Ctools

conda config --append channels conda-forge
conda config --append channels cta-observatory
conda create -n ctathai python=3.8
conda activate ctathai
conda install ctools
conda install matplotlib
conda install jupyterlab
export CALDB=/path/where/you/installed/IRF/caldb
export HESSDATA=/path/where/you/installed/HESS/data

Ctools commands

ctobssim  edisp=yes
fv events.fits
ctskymap 
ds9 skymap.fits 
ctbin
fv cntcube.fits 
ctexpcube
ctpsfcube
ctbkgcube
ctlike
csresmap
csresspec components=yes
$CTOOLS/share/examples/python/show_residuals.py resspec.fits

Fermipy

conda config --append channels fermi
conda create -n fermiset -c conda-forge -c fermi fermitools=2.0.8 python=3.7 clhep=2.4.4.1
conda activate fermiset
conda install fermipy