Metadata-Version: 2.1
Name: surfinBH
Version: 0.1.2.dev1
Summary: Surrogate Final BH properties.
Home-page: https://github.com/vijayvarma392/surfinBH
Author: Vijay Varma
Author-email: vvarma@caltech.edu
License: UNKNOWN
Description: [![github](https://img.shields.io/badge/GitHub-surfinBH-blue.svg)](https://github.com/vijayvarma392/surfinBH)
        [![DOI](https://zenodo.org/badge/145179417.svg)](https://zenodo.org/badge/latestdoi/145179417)
        [![license](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/vijayvarma392/surfinBH/blob/master/LICENSE)
        [![Build Status](https://travis-ci.org/vijayvarma392/surfinBH.svg?branch=master)](https://travis-ci.org/vijayvarma392/surfinBH)
        
        # Welcome to surfinBH!
        
        <img src="https://raw.githubusercontent.com/vijayvarma392/surfinBH/master/images/point_break.jpeg" alt="Point Break" width="400px"/>
        
        
        <br/>
        <br/>
        
        _**surfinBH**_ provides _**sur**rogate **fin**al **B**lack_ _**H**ole_
        properties for mergers of binary black holes (BBH).
        
        These fits are described in the following papers: <br/>
        [1] Vijay Varma, Davide Gerosa, François Hébert, Leo C. Stein and Hao Zhang,
        2018, in preparation.
        
        If you find this package useful in your work, please cite reference [1] and,
        if available, the relevant paper describing the particular model. Please also
        cite this package, see the DOI badge at the top of this page for BibTeX keys.
        
        This package is compatible with both python2 and python3.
        This package lives on [GitHub](https://github.com/vijayvarma392/surfinBH) and
        is tested every day with [Travis CI](https://travis-ci.org/). You can see the
        current build status of the master branch at the top of this page.
        
        ## Installation
        
        ### PyPI
        _**surfinBH**_ is available through [PyPI](https://pypi.org/project/surfinBH/):
        
        ```shell
        pip install surfinBH
        ```
        
        
        ### From source
        
        ```shell
        git clone https://github.com/vijayvarma392/surfinBH
        cd surfinBH
        git submodule init
        git submodule update
        python setup.py install
        ```
        
        If you do not have root permissions, replace the last step with
        `python setup.py install --user`
        
        
        ## Dependencies
        All of these can be installed through pip or conda.
        * [numpy](https://docs.scipy.org/doc/numpy/user/install.html)
        * [scipy](https://www.scipy.org/install.html)
        * [h5py](http://docs.h5py.org/en/latest/build.html)
        * [scikit-learn](http://scikit-learn.org/stable/install.html) (at least 0.19.1)
        * [lalsuite](https://pypi.org/project/lalsuite)
        * [NRSur7dq2](https://pypi.org/project/NRSur7dq2) (at least 1.0.5)
        
        ## Usage
        
        ```python
        import surfinBH
        ```
        
        ### See list of available fits
        ```python
        print(surfinBH.fits_collection.keys())
        >>> ['surfinBH3dq8', 'surfinBH7dq2']
        ```
        
        Pick your favorite fit and get some basic information about it.
        ```python
        fit_name = 'surfinBH7dq2'
        
        surfinBH.fits_collection[fit_name].desc
        >>> 'Fits for remnant mass, spin and kick veclocity for generically precessing BBH systems.'
        
        surfinBH.fits_collection[fit_name].refs
        >>> 'arxiv.2018.xxxx'
        ```
        
        ### Load the fit
        This only needs to be done **once** at the start of your script.
        ```python
        fit = surfinBH.LoadFits(fit_name)
        >>> Loaded surfinBH7dq2 fit.
        ```
        ### Evaluation
        The evaluation of each fit is different, so be sure to read the documentation.
        This also describes the frames in which different quantities are defined.
        ```python
        help(fit)
        ```
        
        We also provide ipython examples for usage of different fits:
        
        * [surfinBH3dq8](https://github.com/vijayvarma392/surfinBH/blob/master/examples/example_3dq8.ipynb)
        
        * [surfinBH7dq2](https://github.com/vijayvarma392/surfinBH/blob/master/examples/example_7dq2.ipynb)
        
        ## Making contributions
        See this
        [README](https://github.com/vijayvarma392/surfinBH/blob/master/README_developers.md)
        for instructions on how to make contributions to this package.
        
        You can find the list of contributors
        [here](https://github.com/vijayvarma392/surfinBH/graphs/contributors).
        
        
        ## Credits
        The code is developed and maintained by [Vijay Varma](http://www.tapir.caltech.edu/~vvarma/). Please, report bugs to
        [&#118;&#118;&#097;&#114;&#109;&#097;&#064;&#099;&#097;&#108;&#116;&#101;&#099;&#104;&#046;&#101;&#100;&#117;](mailto:&#118;&#118;&#097;&#114;&#109;&#097;&#064;&#099;&#097;&#108;&#116;&#101;&#099;&#104;&#046;&#101;&#100;&#117;).
        
Keywords: black-holes gravitational-waves Gaussian-process-regression
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
