Metadata-Version: 2.1
Name: gastimator
Version: 0.3.4
Summary: Implementation of a Python MCMC gibbs-sampler with adaptive stepping
Home-page: https://github.com/TimothyADavis/GAStimator
Author: Timothy A. Davis
Author-email: DavisT@cardiff.ac.uk
License: GNU GPLv3
Description: # GAStimator
        Implementation of a Python MCMC gibbs-sampler with adaptive stepping. 
        
        While this is a simple MCMC algorithm, it is robust and stable and well suited to high dimensional problems with many degrees of freedom and very sharp likelihood features. For instance kinematic modelling of datacubes with this code has been found to be orders of magnitude quicker than using more advanced affine-invariant MCMC methods. 
        
        ### Install
        You can install GAStimator with `pip install gastimator`. Alternatively you can download the code here, navigate to the directory you unpack it too, and run `python setup.py install`.
            
        It requires the following modules:
        
        * numpy
        * matplotlib
        * plotbin
        * joblib
        
        ### Documentation
        
        To get you started, see the walk through here: https://github.com/TimothyADavis/GAStimator/blob/master/documentation/GAStimator_Documentation.ipynb
        
        
        Author & License
        -----------------
        
        Copyright 2019 Timothy A. Davis
        
        Built by `Timothy A. Davis <https://github.com/TimothyADavis>`. Licensed under
        the GNU General Public License v3 (GPLv3) license (see ``LICENSE``).
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
