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https://github.com/johannesbuchner/bxa

Bayesian X-ray analysis (nested sampling for Xspec and Sherpa)
https://github.com/johannesbuchner/bxa

model-selection nested-sampling python sherpa spectroscopy x-ray-astronomy xspec

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Bayesian X-ray analysis (nested sampling for Xspec and Sherpa)

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README 

        
About Bayesian X-ray Analysis (BXA)

------------------------------------



BXA connects the X-ray spectral analysis environments Xspec/Sherpa

to the nested sampling algorithm UltraNest 

for **Bayesian Parameter Estimation** and **Model comparison**.



BXA provides the following features:



* parameter estimation in arbitrary dimensions, which involves:

   * finding the best fit

   * computing error bars

   * computing marginal probability distributions

   * parallelisation with MPI

* plotting of spectral model vs. the data:

   * for the best fit

   * for each of the solutions (posterior samples)

   * for each component

* model selection:

   * computing the evidence for the considered model, 

     ready for use in Bayes factors

   * unlike likelihood-ratios, not limited to nested models 

* model discovery:

   * visualize deviations between model and data with Quantile-Quantile (QQ) plots.

     QQ-plots do not require binning and are more comprehensive than residuals.

     This will give you ideas on when to introduce more complex models, which 

     may again be tested with model selection



BXA shines especially



* when systematically analysing a large data-set, or

* when comparing multiple models

* when analysing low counts data-set with realistic models



because its robust and unsupervised fitting algorithm explores

even complicated parameter spaces in an automated fashion.

The user does not need to initialise to good starting points.

The `algorithm `_ automatically runs until convergence, and slows down to sample

carefully if complicated parameter spaces are encountered. This allows building automated analysis pipelines.



.. image:: https://img.shields.io/pypi/v/BXA.svg

        :target: https://pypi.python.org/pypi/BXA



.. image:: https://coveralls.io/repos/github/JohannesBuchner/BXA/badge.svg

        :target: https://coveralls.io/github/JohannesBuchner/BXA



.. image:: https://img.shields.io/badge/docs-published-ok.svg

        :target: https://johannesbuchner.github.io/BXA/

        :alt: Documentation Status



.. image:: https://img.shields.io/badge/GitHub-JohannesBuchner%2FBXA-blue.svg?style=flat

        :target: https://github.com/JohannesBuchner/BXA/

        :alt: Github repository



Who is using BXA?

-------------------------------



* Dr. Antonis Georgakakis, Dr. Angel Ruiz (NOA, Athens)

* Dr. Mike Anderson (MPA, Munich)

* Dr. Franz Bauer, Charlotte Simmonds (PUC, Jonathan Quirola Vásquez, Santiago)

* Dr. Stéphane Paltani, Dr. Carlo Ferrigno (ISDC, Geneva)

* Dr. Zhu Liu (NAO, Beijing)

* Dr. Georgios Vasilopoulos (Yale, New Haven)

* Dr. Francesca Civano, Dr. Aneta Siemiginowska (CfA/SAO, Cambridge)

* Dr. Teng Liu, Adam Malyali, Riccardo Arcodia, Sophia Waddell, Torben Simm, ... (MPE, Garching)

* Dr. Sibasish Laha, Dr. Alex Markowitz (UCSD, San Diego)

* Dr. Arash Bahramian (Curtin University, Perth)

* Dr. Peter Boorman (U of Southampton, Southampton; ASU, Prague)

* and `you `_?



Documentation

----------------



BXA's `documentation `_ is hosted at http://johannesbuchner.github.io/BXA/



Installation

-------------



First, you need to have either `Sherpa`_ or `Xspec`_ installed and its environment loaded.



BXA itself can installed easily using pip or conda::



	$ pip install bxa



If you want to install in your home directory, install with::



	$ pip install bxa --user



The following commands should not yield any error message::



	$ python -c 'import ultranest'

	$ python -c 'import xspec'

	$ sherpa



You may need to install python and some basic packages through your package manager. For example::



	$ yum install ipython python-matplotlib scipy numpy matplotlib

	$ apt-get install python-numpy python-scipy python-matplotlib ipython



BXA requires the following python packages: requests corner astropy h5py cython scipy tqdm.

They should be downloaded automatically. If they are not, install them

also with pip/conda.



The source code is available from https://github.com/JohannesBuchner/BXA,

so alternatively you can download and install it::

	

	$ git clone https://github.com/JohannesBuchner/BXA

	$ cd BXA

	$ python setup.py install



Or if you only want to install it for the current user::



	$ python setup.py install --user



**Supported operating systems**: 

BXA runs on all operating systems supported by 

`ciao/sherpa `_ or 

`heasoft/xspec `_.

The support is systematically tested for every BXA release by 

`Travis CI `_, but only for Ubuntu Linux.



Running

--------------



In *Sherpa*, load the package::



	jbuchner@ds42 ~ $ sherpa

	-----------------------------------------------------

	Welcome to Sherpa: CXC's Modeling and Fitting Package

	-----------------------------------------------------

	CIAO 4.4 Sherpa version 2 Tuesday, June 5, 2012



	sherpa-1> import bxa.sherpa as bxa

	sherpa-2> bxa.BXASolver?



For *Xspec*, start python or ipython::

	

	jbuchner@ds42 ~ $ ipython

	In [1]: import xspec

	

	In [2]: import bxa.xspec as bxa

	

	In [3]:	bxa.BXASolver?



Now you can use BXA. See the documentation pages for how

to perform analyses. Several examples are included.



.. _ultranest: http://johannesbuchner.github.io/UltraNest/



.. _Sherpa: http://cxc.harvard.edu/sherpa/



.. _Xspec: http://heasarc.gsfc.nasa.gov/docs/xanadu/xspec/



Code

-------------------------------



See the `code repository page `_ 



.. _cite:



Citing BXA correctly

---------------------



Refer to the `accompaning paper Buchner et al. (2014) `_ which gives introduction and 

detailed discussion on the methodology and its statistical footing.



We suggest giving credit to the developers of Sherpa/Xspec, UltraNest and of this software.

As an example::



	For analysing X-ray spectra, we use the analysis software BXA (\ref{Buchner2014}),

	which connects the nested sampling algorithm UltraNest (\ref{ultranest})

	with the fitting environment CIAO/Sherpa (\ref{Fruscione2006}).



Where the BibTex entries are:



* for BXA and the contributions to X-ray spectral analysis methodology (model comparison, model discovery, Experiment design, Model discovery through QQ-plots):



	- Buchner et al. (2014) A&A

	- The paper is available at `arXiv:1402.0004 `_

	- `bibtex entry `_



* for UltraNest: see https://johannesbuchner.github.io/UltraNest/issues.html#how-should-i-cite-ultranest

* for Sherpa: see `Sherpa`_

* for Xspec: see `Xspec`_