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Welcome to Naima — naima v0.8.dev761

Naima is a Python package for computation of non-thermal radiation from relativistic particle populations. It includes tools to perform MCMC fitting of radiative models to X-ray, GeV, and TeV spectra using emcee. An affine-invariant ensemble sampler for Markov Chain Monte Carlo. Naima is an Astropy. There are two main components of the package: a set of nonthermal Radiative Models. And a set of utility functions that make it easier to fit a given model to observed spectral data (see Model fitting. Please...

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Naima is a Python package for computation of non-thermal radiation from relativistic particle populations. It includes tools to perform MCMC fitting of radiative models to X-ray, GeV, and TeV spectra using emcee. An affine-invariant ensemble sampler for Markov Chain Monte Carlo. Naima is an Astropy. There are two main components of the package: a set of nonthermal Radiative Models. And a set of utility functions that make it easier to fit a given model to observed spectral data (see Model fitting. Please...

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Welcome to Naima — naima v0.8.dev761 | naima.readthedocs.io Reviews

https://naima.readthedocs.io

Naima is a Python package for computation of non-thermal radiation from relativistic particle populations. It includes tools to perform MCMC fitting of radiative models to X-ray, GeV, and TeV spectra using emcee. An affine-invariant ensemble sampler for Markov Chain Monte Carlo. Naima is an Astropy. There are two main components of the package: a set of nonthermal Radiative Models. And a set of utility functions that make it easier to fit a given model to observed spectral data (see Model fitting. Please...

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naima.readthedocs.io

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Radiative Models — naima v0.8

http://naima.readthedocs.io/en/latest/radiative.html

Naima contains several radiative models that can be used to compute the non-thermal emission from populations of relativistic electrons or protons. Below there is a brief explanation of each model, and full details on the physics and motivation for the implementation can be found in the referenced articles. All the radiative models take a particle distribution function as a first argument. Several particle distribution functions can be found in the. For details about the inverse Compton model).:. These s...

2

Tutorial — naima v0.8

http://naima.readthedocs.io/en/latest/tutorial.html

The first step in fitting a model to an observed spectrum is to read the spectrum into the appropriate format. See Data format. For an explanation of the format and an example, and Units system. For a brief explanation of the unit system used in Naima. We load the spectral data with. RXJ1713 HESS 2007.dat. Building the model and prior functions. Naima includes several models in the. Module that make it easier to fit common functional forms for spectra (. As well as several radiative models (. In addition...

3

Sherpa models — naima v0.8

http://naima.readthedocs.io/en/latest/sherpa.html

Package is a modeling and fitting application which can be used to fit a variety of data from spatial morphology to forward-folding spectral analysis. It is part of the Chandra analysis software pacakage ( CIAO. But it can be easily installed standalone by using the Anaconda Python. Distribution. The standalone Python version of sherpa. Can be installed along with Naima as follows:. Is the path where you have installed Anaconda. Naima provides wrappers for the Radiative Models. ICbeta frozen 1 0 10.

4

Installation — naima v0.8

http://naima.readthedocs.io/en/latest/installation.html

Naima requires Python 2.7, 3.4, or 3.5 and the following packages to be installed: Numpy. These will be installed automatically if you follow one of the installation methods below. All of the above packages are available in a typical scientific python installation (or in all-in-one Python installations such as the Anaconda Python Distribution. Or can be installed through. The Anaconda python distribution. Conda config - add channels astropy $ conda install naima. Conda update - all. That is not a problem...

5

Model fitting — naima v0.8

http://naima.readthedocs.io/en/latest/mcmc.html

Naima can derive the best-fit and uncertainty distributions of spectral model parameters through Markov Chain Monte Carlo (MCMC) sampling of their likelihood distributions. The following will only describe the implementation of Naima to do so, but a full explanation of MCMC or the sampling algorithm can be found in MacKay (2003). And Foreman-Mackey et al. (2013). It is also advisable to consult the documentation for the emcee package. Which is used for the MCMC sampling. For a parameter vector ( vec{p} ).

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Welcome to Naima — naima v0.8.dev761

Naima is a Python package for computation of non-thermal radiation from relativistic particle populations. It includes tools to perform MCMC fitting of radiative models to X-ray, GeV, and TeV spectra using emcee. An affine-invariant ensemble sampler for Markov Chain Monte Carlo. Naima is an Astropy. There are two main components of the package: a set of nonthermal Radiative Models. And a set of utility functions that make it easier to fit a given model to observed spectral data (see Model fitting. Please...

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