Description:
beansp 2.25.0
BEANSp
Bayesian Estimation of Accreting Neutron Star parameters
Free software: MIT license
Documentation: https://beans-7.readthedocs.io/en/latest/
Repo: https://github.com/adellej/beans
Features
This software uses a Markov Chain Monte Carlo approach to match observations of an accreting neutron star in outburst with a simple ignition model to constrain parameters including the neutron star mass, radius, surface gravity, distance and system inclination, and accreted fuel composition.
The code is written in Python 3, except for settle which is a C++ code with a python wrapper. It makes use of Dan Foreman-Mackey’s python implementation of MCMC, emcee, available at https://github.com/dfm/emcee.
Credits
Software written by Adelle Goodwin and Duncan Galloway; for a full description see Goodwin et al. (2019, https://doi.org/10.1093/mnras/stz2638 or preprint at https://arxiv.org/pdf/1907.00996).
The original algorithm is described in Galloway & Cumming (2006,
https://iopscience.iop.org/article/10.1086/507598).
pySettle was forked from the original settle written by Andrew Cumming and
available at https://github.com/andrewcumming/settle
Package installation and usage
BEANSp is on pyPI (https://pypi.org/project/beansp/) so installation is
easy - either system-wide, or in virtual environment:
pip install beansp
You can then import the main Beans module as follows:
from beansp import Beans
(Please refer to this simple test script as an example.)
Build and installation from this github repository
Please refer to build instructions.
History
0.1.0 (2019-09-19)
First release on PyPI.
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Customer Reviews
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