Metadata-Version: 1.1
Name: pycorrelate
Version: 0.1.0
Summary: Fast and accurate timestamps correlation in python.
Home-page: https://github.com/tritemio/pycorrelate
Author: Antonino Ingargiola
Author-email: tritemio@gmail.com
License: GNU General Public License v3
Description: ===========
        Pycorrelate
        ===========
        
        
        .. image:: https://img.shields.io/pypi/v/pycorrelate.svg
                :target: https://pypi.python.org/pypi/pycorrelate
        
        .. image:: https://img.shields.io/travis/tritemio/pycorrelate.svg
                :target: https://travis-ci.org/tritemio/pycorrelate
        
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                :target: https://pycorrelate.readthedocs.io/en/latest/?badge=latest
                :alt: Documentation Status
        
        **Pycorrelate** computes fast and accurate cross-correlation over
        arbitrary time lags.
        Cross-correlations can be calculated on "uniformly-sampled" signals
        or on "point-processes", such as photon timestamps.
        Pycorrelate allows computing cross-correlation at log-spaced lags covering
        several orders of magnitude. This type of cross-correlation is
        commonly used in physics or biophysics for techniques such as
        *fluorescence correlation spectroscopy* (`FCS <https://en.wikipedia.org/wiki/Fluorescence_correlation_spectroscopy>`__) or
        *dynamic light scattering* (`DLS <https://en.wikipedia.org/wiki/Dynamic_light_scattering>`__).
        
        Two types of correlations are implemented:
        
        - `ucorrelate <https://pycorrelate.readthedocs.io/en/latest/api.html#pycorrelate.pycorrelate.ucorrelate>`__:
          the classical text-book linear cross-correlation between two signals
          defined at **uniformly spaced** intervals.
          Only positive lags are computed and a max lag can be specified.
          Thanks to the limit in the computed lags, this function is much faster than
          `numpy.correlate <https://docs.scipy.org/doc/numpy/reference/generated/numpy.correlate.html#numpy.correlate>`__.
        
        - `pcorrelate <https://pycorrelate.readthedocs.io/en/latest/api.html#pycorrelate.pycorrelate.pcorrelate>`__:
          cross-correlation of discrete events
          in a point-process. In this case input arrays can be timestamps or
          positions of "events", for example **photon arrival times**.
          This function implements the algorithm in
          `Laurence et al. Optics Letters (2006) <https://doi.org/10.1364/OL.31.000829>`__.
          This is a generalization of the multi-tau algorithm which retains
          high execution speed while allowing arbitrary time-lag bins.
        
        Pycorrelate is implemented in Python 3 and operates on standard numpy arrays.
        Execution speed is optimized using `numba <https://numba.pydata.org/>`__.
        
        * Free software: GNU General Public License v3
        * Documentation: https://pycorrelate.readthedocs.io.
        
        
        =======
        History
        =======
        
        0.1.0 (2017-07-23)
        ------------------
        
        * First release on PyPI.
        
Keywords: pycorrelate
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
