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analysis-galactic-sources-cta-km3net

Analysis pipeline for galactic source searches with CTA and KM3NeT

https://github.com/km3net/analysis-galactic-sources-cta-km3net

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
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    DOI references
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    Academic publication links
    Links to: arxiv.org, zenodo.org
  • ○
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (15.3%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Analysis pipeline for galactic source searches with CTA and KM3NeT

Basic Info
  • Host: GitHub
  • Owner: KM3NeT
  • License: bsd-3-clause
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 5.01 MB
Statistics
  • Stars: 1
  • Watchers: 4
  • Forks: 0
  • Open Issues: 0
  • Releases: 2
Created almost 3 years ago · Last pushed almost 3 years ago
Metadata Files
Readme License Codemeta

README.md

License DOI

CTA and KM3NeT Common Source Search

This repository contains the prospects for combined analyses of hadronic emission from γ-ray sources in the Milky Way with CTA and KM3NeT/ARCA. It complements the publication "Prospects for combined analyses of hadronic emission from γ-ray sources in the Milky Way with CTA and KM3NeT" (arxiv:2309.03007), and for in-depth description of the analysis please refer to the paper. The aim of this analysis is to simulate how well a combined analysis of CTA and KM3NeT data can differentiate between hadronic and leptonic emission scenarios of galactic gamma-ray sources. The focus is on the comparison of the combined analysis to the separate analysis of the two instruments within Gammapy. This content is only compatible with gammapy v0.17, later versions are not supported.
It should be noted, that gammapy v0.17 is not compatible with the M1 CPU. The only option to run this analysis with this CPU is to use a docker image. This option will be provided in the next version of the repository.

Content

  • Analysis/: Notebooks to reproduce the analysis
  • data/: Instrument Response Functions (IRFs) and flux model for the sources
  • envs/: Configuration files for setting up the python environment
  • src/: supplementary scripts

Installation

Download

First it is required to download the whole content of the repository, it can be done using git: sh git clone git@github.com:KM3NeT/Analysis-galactic-sources-CTA-KM3NeT.git or sh git clone https://github.com/KM3NeT/Analysis-galactic-sources-CTA-KM3NeT.git then sh cd cta-and-km3net/

Creating the environment

Using conda

In order to use conda to build the environment, conda has to be installed. To see how, use these Installation instructions.

Build environment using conda from environment.yml file: sh conda env create -f envs/environment.yml conda activate km3net_cta_env

Using venv

It requires to build a dedicated environment. Build environment using pip, first it requires to install manually python3.8, then install virtualenv: ```sh pip install virtualenv

for standard preinstalled python 3.8

virtualenv venv --python=python3.8

or specify path

virtualenv venv --python=/path/to/python3.8 acitvate `venv`: sh

on Windows

.\venv\Scripts\activate.ps1

on Linux

source venv/bin/activate Install necessary packages: sh pip install cython numpy pip install -r requirements.txt ```

Using Jupyter

In order to run the notebooks, you need to have Jupyter installed. You can install it using pip install jupyter or following the instructions at the Juypter website.

Running the Jupyter kernel

Jupyter notebook kernel and launch your notebook: sh python -m ipykernel install --user --name=km3net_cta jupyter-notebook And for zsh shell, you need to execute these lines first before installation of the kernel zsh conda install -c conda-forge notebook conda install -c conda-forge nb_conda_kernels

Integration with REANA

Analysis can be run in REANA, for this purpose it needs to install reana-client inside virtual environment: ```sh

inside venv or conda env

pip install reana-client `` $\textcolor{red}{\text{Warning!}}$ reana-client` is currently not compatible with Windows even inside a conda environment.

After installation of the client, it needs to set connection using a token. For convinience all REANA commands are specified in run_reana.sh script. Launch the script in terminal. ```sh export REANASERVERURL=https://reana.cern.ch export REANAACCESSTOKEN=YOUR_TOKEN . run_reana.sh

get the results of analysis

reana-client download ```

Owner

  • Name: KM3NeT
  • Login: KM3NeT
  • Kind: organization

Inofficial collection of open source KM3NeT software

CodeMeta (codemeta.json) 

{
  "@context": "https://doi.org/10.5063/schema/codemeta-2.0",
  "@type": "SoftwareSourceCode",
  "license": "https://spdx.org/licenses/BSD-3-Clause",
  "codeRepository": "https://github.com/KM3NeT/Analysis-galactic-sources-CTA-KM3NeT",
  "dateCreated": "2023-04-03",
  "datePublished": "2023-08-29",
  "dateModified": "2023-08-29",
  "downloadUrl": "https://github.com/KM3NeT/Analysis-galactic-sources-CTA-KM3NeT",
  "issueTracker": "https://github.com/KM3NeT/Analysis-galactic-sources-CTA-KM3NeT/issues",
  "name": "Prospects for combined galactic source searches with CTA and KM3NeT",
  "version": "1.0.0",
  "description": "This repository contains the prospects for combined analyses of hadronic emission from -ray sources in the Milky Way with CTA and KM3NeT/ARCA. It complements the publication \"Prospects for combined analyses of hadronic emission from -ray sources in the Milky Way with CTA and KM3NeT\"",
  "applicationCategory": "Astroparticle physics",
  "releaseNotes": "First commit in line with paper publication.",
  "referencePublication": "https://arxiv.org/abs/2309.03007",
  "developmentStatus": "active",
  "readme": "https://github.com/KM3NeT/Analysis-galactic-sources-CTA-KM3NeT/README.md",
  "softwareVersion": "1.0.0",
  "keywords": [
    "CTA",
    "KM3NeT",
    "neutrinos",
    "gamma rays"
  ],
  "programmingLanguage": [
    "Python 3"
  ],
  "operatingSystem": [
    "Linux",
    "Windows"
  ],
  "softwareRequirements": [
    "Python 3.8",
    "gammapy 0.17"
  ],
  "author": [
    {
      "@type": "Person",
      "@id": "https://orcid.org/0000-0002-7378-4024",
      "givenName": "Tim",
      "familyName": "Unbehaun",
      "email": "tim.unbehaun@fau.de",
      "affiliation": {
        "@type": "Organization",
        "name": "FAU Erlangen-Nrnberg"
      }
    },
    {
      "@type": "Person",
      "@id": "https://orcid.org/0000-0002-9667-8654",
      "givenName": "Lars",
      "familyName": "Mohrmann",
      "email": "lars.mohrmann@mpi-hd.mpg.de",
      "affiliation": {
        "@type": "Organization",
        "name": "Max-Planck-Institut fr Kernphysik"
      }
    },
    {
      "@type": "Person",
      "@id": "https://orcid.org/0000-0003-2772-1927",
      "givenName": "Mikhail",
      "familyName": "Smirnov",
      "email": "gear8mike@gmail.com",
      "affiliation": {
        "@type": "Organization",
        "name": "FAU Erlangen-Nrnberg"
      }
    },
    {
      "@type": "Person",
      "@id": "https://orcid.org/0000-0003-1233-7738",
      "givenName": "Jutta",
      "familyName": "Schnabel",
      "email": "jutta.schnabel@fau.de",
      "affiliation": {
        "@type": "Organization",
        "name": "FAU Erlangen-Nrnberg"
      }
    }
  ],
  "contributor": [
    {
      "@type": "Person",
      "@id": "https://orcid.org/ 0000-0001-7821-8673",
      "givenName": "Tams",
      "familyName": "Gl",
      "email": "tamas.gal@fau.de",
      "affiliation": {
        "@type": "Organization",
        "name": "FAU Erlangen-Nrnberg"
      }
    }
  ],
  "maintainer": [
    {
      "@type": "Organization",
      "@id": "https://km3net.org",
      "name": "KM3NeT Collaboration",
      "email": "opendata@km3net.de",
      "url": "http://openscience.km3net.de"
    }
  ]
}

GitHub Events

Total
Last Year

Committers

Last synced: over 1 year ago

All Time
  • Total Commits: 23
  • Total Committers: 3
  • Avg Commits per committer: 7.667
  • Development Distribution Score (DDS): 0.217
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Misha Smirnov m****v@k****e 18
YouSchnabel 7****l 3
Jutta Schnabel j****l@f****e 2
Committer Domains (Top 20 + Academic)
fau.de: 1 km3net.de: 1

Issues and Pull Requests

Last synced: about 1 year ago

All Time
  • Total issues: 0
  • Total pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: 2 days
  • Total issue authors: 0
  • Total pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
Issue Authors
Pull Request Authors
  • YouSchnabel (1)
  • gear8mike (1)
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