Version 1.4.0

New features

MCMC functionalities

• mcmc can now return and plot the mcmc best-fit model according to the maximum of the log-like:

  # NOTE: plot_mcmc_best_fit_model=True gets the parameters corresponding to the max log-like
  p=mcmc.plot_model(sed_data=sed_data,fit_range=[1E11, 2E27],size=1000,quantiles=[0.01,0.99],plot_mcmc_best_fit_model=True)
  p.setlim(y_min=1E-14,x_min=1E6,x_max=2E28)
  

• the mcmc best-fit model can be easily restored:

  mcmc.reset_to_mcmc_best_fit()
  

• McmcSampler.set_bounds() method can preserve or not fit boundaries

  # NOTE: preserve_fit_range=True preserves the model fit range for each parameter used in the MCMC
  mcmc.set_bounds(bound=5.0,bound_rel=True,preserve_fit_range=True)
  

• A complete example is available in the MCMC section of Model fitting 1: Only SSC and extended radio jet

Radio component in composite models

• Added a new analytical radio component, RadioSpectrum, for extended jet radio emission with self-absorption turnover and high-frequency cutoff. See Jet Radio Component: RadioSpectrum

• RadioSpectrum can be combined with a jet model in FitModel:

  from jetset.jet_radio_component import RadioSpectrum
  from jetset.model_manager import FitModel
  
  fit_model = FitModel(jet=prefit_jet, name='SSC-best-fit-lsb', template=None)
  fit_model.add_component(RadioSpectrum())
  fit_model.composite_expr = '(jet_leptonic+radio_spectrum)'
  

• A complete fitting workflow (SSC + extended radio component, minuit and MCMC) is available in Model fitting 1: Only SSC and extended radio jet

Leptonic equilibrium

• Added support for leptonic equilibrium jet models using injected emitters distributions. See Leptonic equilibrium

• The model can be created by passing an InjEmittersFactory distribution to Jet:

  from jetset.jet_model import Jet
  from jetset.jet_emitters_factory import InjEmittersFactory
  
  q_inj = InjEmittersFactory().create_inj_emitters('pl')
  my_jet = Jet(emitters_distribution=q_inj)
  

• Validation against the Fokker-Planck time-dependent solution in JetTimeEvol: Validation of the leptonic equilibrium against the Fokker-Plank equation solution

• End-to-end model fitting workflow with MCMC for leptonic equilibrium models: Model fitting 1: Leptonic equilibrim

data handling

• UL are handled when rebinning SED data

• added nu min/max to rebin

EC emission

• added pair production absorption for Dusty Torus and Broad Line Region

• internal absorption can be enabled for EC components (DT/BLR) and used in fitting workflows. See Internal absorption and Model fitting 3: External Compton

• optional use_R_H_profile_extrapolation in internal absorption setup to speed up evaluations:

  jetset_model.enable_internal_absorption('DT', use_R_H_profile_extrapolation=True)
  

• To enable internal absorption for model fitting see the How to enable Internal absorption section of Model fitting 3: External Compton

bug fixing

• minor bug fixes

• fixed some typo in variable names

C codebase

• Substantial refactoring of the C code, dividing the blob structure in several sub-structures, with hierarchy.

installation

• Added source installation via ./install.sh.

• Detects if you are in a conda/mamba/micromamba evn or a pip evn, and install JetSeT from source, together with the dependencies

• When run inside an active conda/mamba environment, ./install.sh syncs JetSeT constraints from requirements.txt into $CONDA_PREFIX/conda-meta/pinned. This pins JetSeT requirements in that environment and helps prevent later conda/mamba installs of other packages from overriding them. For pip virtual env, the problem

• This script is recommended when binaries are not available for your Python/platform, or for developers and advanced users.

• Run the script from the project root to install dependencies, compile extensions, and install JetSeT:

  ./install.sh
  

• If you want to skip the installation of dependencies

  ./install.sh -skip-dep
  

• If you want to experiment with different requirements (do it on your own risk):

  • edit the requirements.txt accordingly and:

  ./install.sh
  

• Verify the installation with, optional (not within the code repo dir):

  python -c "import jetset; print(jetset.__version__)"
  pytest --disable-warnings --pyargs -vvv jetset.tests.test_users::TestUser
  

• Full source-install requirements and troubleshooting are documented in Installation (including SWIG notes in Swig installation).