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        "author": "Shay Palachy",
        "author_email": "shaypal5@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Software Development :: Libraries",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "ssdts_matching\n##############\n|PyPI-Status| |PyPI-Versions| |Build-Status| |Codecov| |LICENCE|\n\nFast optimal matching of items for source-sharing derivative time series.\n\n.. code-block:: python\n\n  from ssdts_matching import dynamic_timestamp_match\n  dynamic_timestamp_match(timestamp1, timestamps2, delta=20)\n\n.. contents::\n\n.. section-numbering::\n\nInstallation\n============\n\nInstall ``ssdts_matching`` with:\n\n.. code-block:: bash\n\n  pip install ssdts_matching\n\n\nFeatures\n========\n\n* Pure Python.\n* Compatible with Python 3.5+.\n* Dependencies:\n\n  * numpy\n  * `sortedcontainers <https://pypi.python.org/pypi/sortedcontainers>`_\n\n\nUse\n===\n\nYou can get a matching of two timestamp series with\n\n.. code-block:: python\n\n  from ssdts_matching import dynamic_timestamp_match\n  dynamic_timestamp_match(timestamp1, timestamps2, delta=20)\n\n\nSix different functions, in an increasing level of complexity, are procided:\n\n\npopping_greedy_timestamp_match\n------------------------------\n\nTries to match two timestamp series in a greedy fashion. Timestamps are popped from their lists as they are matched.\n\nRuns in ``O(M*log(N))`` where ``M=len(timestamps1)`` and ``M=len(timestamps2)``. Not guarenteed to find an optimal matching error-wise, where the error is the sum of differences between matched pairs.\n\n\ngreedy_timestamp_match\n----------------------\n\nTries to match two timestamp series in a greedy fashion.\n\nRuns in ``O(M*log(N))`` where ``M=len(timestamps1)`` and ``M=len(timestamps2)``. If the resulting match is an injective function from the first series to the second one then the solution is optimal error-wise, where the error is the sum of differences between matched pairs. Otherwise, it is not.\n\n\ndynamic_timestamp_match\n-----------------------\n\nOptimally matches two timestamp series using dynamic programming.\n\nRuns in ``O(M*N)``, where ``M=len(timestamps1)`` and ``N=len(timestamps2)``. Guarentees an optimal solution error-wise, where the error is the sum of differences between matched pairs.\n\n\nhybrid_timestamp_match\n----------------------\n\nFinds the optimal matching of two timestamps series using both a greedy algorithm and a dynamic one.\n\nRuns in ``O(M*N)``, where ``M=len(timestamps1)`` and ``N=len(timestamps2)``, but has a better average running time than ``dynamic_timestamp_match`` if some inputs can be optimally solved with the greedy algorithm. Guarentees an optimal solution error-wise, where the error is the sum of differences between matched pairs.\n\n\nvertical_aligned_timestamp_match\n--------------------------------\n\nMatches two timestamps series by partioning them by verticals (pairs of timestamps from both series with identical values) and matching each partition using the hybrid approach.\n\nRuns in O(M*N), where ``M=len(timestamps1)`` and ``N=len(timestamps2)``. Does not guarentee an optimal solution error-wise, where the error is the sum of differences between matched pairs.\n\n\ndelta_partitioned_timestamp_match\n---------------------------------\n\nttempts to match the two given series of timestamps by partioning the first series into ``2 * delta``-separated buckets, and applying the given matching function to each (any of the above functions can be used), combining the sub-solution into a matching.\n\nIf the provided matching function yields optimal matchings, than so is the matching provided by this function. The algorithm is not guarenteed to be symmetric; giving the same two series in the opposite order may yield a different matching.\n\n\nContributing\n============\n\nPackage author and current maintainer is Shay Palachy (shay.palachy@gmail.com); You are more than welcome to approach him for help. Contributions are very welcomed.\n\nInstalling for development\n--------------------------\n\nClone:\n\n.. code-block:: bash\n\n  git clone git@github.com:shaypal5/ssdts_matching.git\n\n\nInstall in development mode with test dependencies:\n\n.. code-block:: bash\n\n  cd ssdts_matching\n  pip install -e \".[test]\"\n\n\nRunning the tests\n-----------------\n\nTo run the tests, use:\n\n.. code-block:: bash\n\n  python -m pytest --cov=ssdts_matching\n\n\nAdding documentation\n--------------------\n\nThis project is documented using the `numpy docstring conventions`_, which were chosen as they are perhaps the most widely-spread conventions that are both supported by common tools such as Sphinx and result in human-readable docstrings (in my personal opinion, of course). When documenting code you add to this project, please follow `these conventions`_.\n\n.. _`numpy docstring conventions`: https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt\n.. _`these conventions`: https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt\n\n\nCredits\n=======\nCreated by Shay Palachy  (shay.palachy@gmail.com).\n\n\n.. |PyPI-Status| image:: https://img.shields.io/pypi/v/ssdts_matching.svg\n  :target: https://pypi.python.org/pypi/ssdts_matching\n\n.. |PyPI-Versions| image:: https://img.shields.io/pypi/pyversions/ssdts_matching.svg\n   :target: https://pypi.python.org/pypi/ssdts_matching\n\n.. |Build-Status| image:: https://travis-ci.org/shaypal5/ssdts_matching.svg?branch=master\n  :target: https://travis-ci.org/shaypal5/ssdts_matching\n\n.. |LICENCE| image:: https://img.shields.io/pypi/l/ssdts_matching.svg\n  :target: https://pypi.python.org/pypi/ssdts_matching\n\n.. |Codecov| image:: https://codecov.io/github/shaypal5/ssdts_matching/coverage.svg?branch=master\n   :target: https://codecov.io/github/shaypal5/ssdts_matching?branch=master\n",
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