JetSeT is an open source C/Python framework to reproduce radiative and accelerative processes acting in relativistic jets,
allowing to fit the numerical models to observed data. The main features of this framework are:

handling observed data: re-binning, definition of data sets, bindings to astropy tables and quantities definition of complex numerical radiative scenarios: Synchrotron Self-Compton (SSC), external Compton (EC) and EC against the CMB
Constraining of the model in the pre-fitting stage, based on accurate and already published phenomenological trends. In particular, starting from phenomenological parameters, such as spectral indices, peak fluxes and frequencies, and spectral curvatures, that the code evaluates automatically, the pre-fitting algorithm is able to provide a good starting model,following the phenomenological trends that I have implemented. fitting of multiwavelength SEDs using
both frequentist approach (iminuit) and bayesian MCMC sampling (emcee)
Self-consistent temporal evolution of the plasma under the effect of radiative, accelerative processes, and adiabatic expansion. Both first order and second order (stochastic acceleration) processes are implemented.

Acknowledgements

If you use this code in any kind of scientific publication please cite the following papers:

Tramacere A. 2020 https://ui.adsabs.harvard.edu/abs/2020ascl.soft09001T/abstract
Tramacere A. et al. 2011 http://adsabs.harvard.edu/abs/2011ApJ...739...66T
Tramacere A. et al. 2009 http://adsabs.harvard.edu/abs/2009A%26A...501..879T
Massaro E. et. al 2006 http://adsabs.harvard.edu/abs/2006A%26A...448..861M

Licence

JetSeT is released under a 3-clause BSD license, for deatils see License file

Documentation

visit: https://jetset.readthedocs.io/en/latest/

run the notebook on binder:

Installation

NOTE: Starting from version 1.1.0, python 2 is not supported anymore. Python >=3.8 is suggested, older python 3 versions (< 3.8) should work.

Install JetSeT from Anaconda

create a virtual environment (not necessary, but suggested):

conda create --name jetset python=3.9 ipython jupyter

conda activate jetset
install the code:

conda install -c andreatramacere jetset

if conda fails with dependencies you can try

conda install -c andreatramacere -c astropy -c conda-forge 'jetset>=1.2'

Install JetSeT from pip

MacOS
- create a virtual environment (not necessary, but suggested): pip install jetset
Linux

NOTE: currently, pip binaries for linux are not provided, so pip will build the binary on the fly. Hence:
- install swig with of these methods and check that you have a C compiler (gcc)
- pip install jetset
if fails, use one of the following methods
1. Use anaconda
OR
1. Install from source
OR
1. Install the git release binaries from git releases

Install JetSeT GitHub binaries

Install the git release binaries from git releases

run the test

pytest --disable-warnings  --pyargs  -vvv jetset.tests.test_users::TestUser

Install the JetSeT from source

Download the code

Get the source code from:
- https://github.com/andreatramacere/jetset/archive/stable.tar.gz
Uncompress the archive jetset-stable.tar.gz
cd to the dir
- cd jetset-stable

Installation from source using Anaconda

Install requirements, run on the command line:
- conda install --yes swig">=3.0.0"
- conda install -c astropy -c conda-forge --file requirements.txt

if anaconda fails to install swig, you can try one of the following alternative methods

run on the command line:
- python setup.py clean
- python setup.py install
run the test (optional, run all the examples outside the installation dir)

cd ~/
mkdir test_jetset
cd test_jetset
pytest  --pyargs  -vvv jetset.tests.test_users::TestUser

Installation from source using PIP

Install requirements, run on the command line:
- pip install swig>=3.0.0
- pip install -r requirements.txt
if pip fails to install swig, you can try one of the following alternative methods
run on the command line:
- python setup.py clean
- python setup.py install
run the test (optional, run all the examples outside the installation dir)

cd ~/
mkdir test_jetset
cd test_jetset
pytest  --pyargs  -vvv jetset.tests.test_users::TestUser

Requirements

The following python packages are required:

    python =3.9 (python 3.9 is suggested, older python 3 versions should  work, python 2 is not supported any more from version>=1.1.0)
    setuptools
    scipy
    numpy
    astropy
    matplotlib
    swig
    future
    iminuit
    corner
    six
    emcee
    pyyaml
    numba
    sherpa

A C compiler is also necessary, plus the SWIG wrapper generator.

All the dependencies are installed following the Anaconda method OR the pip method, as described above.

jetset code repoistory

The code is hosted here:

https://github.com/andreatramacere/jetset

laofei177 / jetset