Metadata-Version: 1.1
Name: acor
Version: 1.1.1
Summary: Estimate the autocorrelation time of a time series quickly.
Home-page: http://github.com/dfm/acor
Author: Daniel Foreman-Mackey and Jonathan Goodman
Author-email: danfm@nyu.edu
License: MIT
Description: ACOR
        ====
        
        This is a direct port of a C++ routine by
        `Jonathan Goodman <http://www.math.nyu.edu/faculty/goodman/index.html>`_ (NYU)
        called `ACOR <http://www.math.nyu.edu/faculty/goodman/software/acor/>`_ that
        estimates the autocorrelation time of time series data very quickly.
        
        `Dan Foreman-Mackey <http://danfm.ca>`_ (NYU) made a few surface changes to
        the interface in order to write a Python wrapper (with the permission of the
        original author).
        
        Installation
        ------------
        
        Just run ::
        
            pip install acor
        
        with ``sudo`` if you really need it.
        
        Otherwise, download the source code
        `as a tarball <https://github.com/dfm/acor/tarball/master>`_
        or clone the git repository from `GitHub <https://github.com/dfm/acor>`_: ::
        
            git clone https://github.com/dfm/acor.git
        
        Then run ::
        
            cd acor
            python setup.py install
        
        to compile and install the module ``acor`` in your Python path. The only
        dependency is `NumPy <http://numpy.scipy.org/>`_ (including the
        ``python-dev`` and ``python-numpy-dev`` packages which you might have to
        install separately on some systems).
        
        Usage
        -----
        
        Given some time series ``x``, you can estimate the autocorrelation time
        (``tau``) using: ::
        
            import acor
            tau, mean, sigma = acor.acor(x)
        
        References
        ----------
        
        * http://www.math.nyu.edu/faculty/goodman/software/acor/index.html
        * http://www.stat.unc.edu/faculty/cji/Sokal.pdf
        
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
