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        "author": "Aaron R. Voelker",
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        "bugtrack_url": null,
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            "Development Status :: 5 - Production/Stable",
            "Framework :: Nengo",
            "Intended Audience :: Science/Research",
            "License :: Free for non-commercial use",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering :: Artificial Intelligence"
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        "description": ".. image:: https://arvoelke.github.io/nengolib-docs/_static/logo.png\n   :width: 64\n   :height: 64\n   :target: https://github.com/arvoelke/nengolib\n   :alt: Nengolib Logo\n\n.. image:: https://travis-ci.org/arvoelke/nengolib.svg?branch=master\n   :target: https://travis-ci.org/arvoelke/nengolib\n   :alt: Build Status\n\n.. image:: https://codecov.io/github/arvoelke/nengolib/coverage.svg?branch=master\n   :target: https://codecov.io/github/arvoelke/nengolib?branch=master\n   :alt: Code Coverage\n\nimport nengolib\n===============\n\nAdditional extensions and tools for modelling dynamical systems in\n`Nengo <https://github.com/nengo/nengo>`__.\n\n\n`Documentation <https://arvoelke.github.io/nengolib-docs/>`__\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThis project's documentation is hosted on GitHub.IO:\nhttps://arvoelke.github.io/nengolib-docs/.\n\n\nDevelopment\n~~~~~~~~~~~\n\nTo install the development version of nengolib::\n\n    git clone https://github.com/arvoelke/nengolib\n    cd nengolib\n    python setup.py develop\n\nNotebooks can be run manually in ``docs/notebooks`` by running::\n\n    pip install jupyter\n    jupyter notebook\n\n***************\nRelease History\n***************\n\n0.5.2 (September 10, 2019)\n==========================\n\n**Fixed**\n\n- Solved an issue where scipy.misc imports were relocated.\n  (`#182 <https://github.com/arvoelke/nengolib/pull/182>`_)\n\n0.5.1 (April 17, 2019)\n======================\n\nTested against Nengo versions 2.2.0-2.8.0. Requires ``nengo<3.0``.\n\n**Fixed**\n\n- A variety of miscellaneous fixes were made to the documentation.\n  The ``nengolib.networks.RollingWindow`` documentation references the\n  shifted Legendre polynomial equations for ``legendre == True``.\n  (`#176 <https://github.com/arvoelke/nengolib/pull/176>`_)\n\n0.5.0 (March 9, 2019)\n=====================\n\nTested against Nengo versions 2.2.0-2.8.0.\nWe now require ``numpy>=1.13.0``, ``scipy>=0.19.0``, and ``nengo>=2.2.0``.\n\n**Added**\n\n- Added the ``nengolib.RLS()`` recursive least-squares (RLS)\n  learning rule. This can be substituted for ``nengo.PES()``.\n  See ``notebooks/examples/full_force_learning.ipynb`` for an\n  example that uses this to implement spiking FORCE in Nengo.\n  (`#133 <https://github.com/arvoelke/nengolib/pull/133>`_)\n- Added the ``nengolib.stats.Rd()`` method for quasi-random sampling of\n  arbitrarily high-dimensional vectors. It is now the default method for\n  scattered sampling of encoders and evaluation points.\n  The method can be manually switched back to ``nengolib.stats.Sobol()``.\n  (`#153 <https://github.com/arvoelke/nengolib/pull/153>`_)\n- Added the ``nengolib.neuron.init_lif(sim, ens)`` helper function\n  for initializing the neural state of a ``LIF`` ensemble, from within\n  a simulator block, to represent ``0`` uniformly at the start.\n  (`#156 <https://github.com/arvoelke/nengolib/pull/156>`_)\n- Added ``nengolib.synapses.LegendreDelay`` as an alternative to\n  ``nengolib.synapses.PadeDelay`` -- it has an equivalent transfer function\n  but a state-space realization corresponding to the shifted\n  Legendre basis.\n  The network ``nengolib.networks.RollingWindow`` support ``legendre=True``\n  to make this system the default realization.\n  (`#161 <https://github.com/arvoelke/nengolib/pull/161>`_)\n\n\n**Fixed**\n\n- Release no longer requires ``pytest``.\n  (`#156 <https://github.com/arvoelke/nengolib/pull/156>`_)\n\n0.4.2 (May 18, 2018)\n====================\n\nTested against Nengo versions 2.1.0-2.7.0.\n\n**Added**\n\n- Solving for connection weights by accounting for the neural\n  dynamics. To use, pass in ``nengolib.Temporal()`` to\n  ``nengo.Connection`` for the ``solver`` parameter.\n  Requires ``nengo>=2.5.0``.\n  (`#137 <https://github.com/arvoelke/nengolib/pull/137>`_)\n\n0.4.1 (December 5, 2017)\n========================\n\nTested against Nengo versions 2.1.0-2.6.0.\n\n**Fixed**\n\n- Compatible with newest SciPy release (1.0.0).\n  (`#130 <https://github.com/arvoelke/nengolib/pull/130>`_)\n\n0.4.0b (June 7, 2017)\n=====================\n\nInitial beta release of nengolib.\nTested against Nengo versions 2.1.0-2.4.0.\n\n\n",
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