Metadata-Version: 1.1
Name: obliquity
Version: 0.2
Summary: Infer the stellar obliquity distribution of transiting planet systems.
Home-page: https://github.com/timothydmorton/obliquity
Author: Timothy D. Morton
Author-email: tim.morton@gmail.com
License: UNKNOWN
Description: =========
        obliquity
        =========
        
        Infer the stellar obliquity distribution of transiting planet systems, following `Morton & Winn (2014) <http://arxiv.org/abs/1408.6606>`_. 
        
        Makes use of the `simpledist <https://github.com/timothydmorton/simpledist>`_ package, which will be installed 
        as a dependency with installation of this package.
        
        There are two main tasks this package does:
        
        1. Calculate posteriors of cos(I) given measurements of Rstar, Prot, Vsin(I).
        
        2. Infer the Fisher distribution parameter $\kappa$ given a sample of cos(I) posteriors.
        
        See below for a quick intro, and the `notebook demo <http://nbviewer.ipython.org/github/timothydmorton/obliquity/blob/master/notebooks/demo.ipynb>`_ for more.
        
        Installation
        ------------
        
        ::
        
           $ pip install [--user] obliquity
           
        Or clone the repository and install:
        
        ::
        
            $ git clone https://github.com/timothydmorton/obliquity.git
            $ cd obliquity
            $ python setup.py install [--user]
        
        Basic usage
        -----------
        
        .. code-block:: python
        
            from obliquity.distributions import Cosi_Distribution
            cosi_dist = Cosi_Distribution((1.3,0.1),(15,0.3),(3.5,0.5)) #Radius, Prot, VsinI
            cosi_dist.summary_plot()
        
        Command-line scripts
        --------------------
        
        In addition to the ``obliquity`` module, this package also installs a few command-line scripts.  
        
        ``write_cosi_dist``: This calculates a ``Cosi_Distribution`` given input parameters, and writes the distribution to 
        file (`.h5` format that can be easily re-loaded back). e.g.,
        
        ::
        
            $ write_cosi_dist test.h5 -R 1.3 0.1 -P 14 0.3 -V 4 0.5
        
        After having done this, you could launch up python and read in the distribution as follows:
        
        .. code-block:: python
        
            from obliquity import Cosi_Distribution_FromH5
            cosi_dist = Cosi_Distribution_FromH5('test.h5')
            cosi_dist.summary_plot()
        
        This is particularly useful for running batch jobs and doing more analysis later.
        
        
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Astronomy
