Metadata-Version: 1.1
Name: nengolib
Version: 0.5.2
Summary: Tools for robust dynamics in Nengo
Home-page: https://github.com/arvoelke/nengolib/
Author: Aaron R. Voelker
Author-email: arvoelke@gmail.com
License: Free for non-commercial use (see Nengo license)
Download-URL: https://github.com/arvoelke/nengolib/archive/v0.5.2.tar.gz
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        import nengolib
        ===============
        
        Additional extensions and tools for modelling dynamical systems in
        `Nengo <https://github.com/nengo/nengo>`__.
        
        
        `Documentation <https://arvoelke.github.io/nengolib-docs/>`__
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        This project's documentation is hosted on GitHub.IO:
        https://arvoelke.github.io/nengolib-docs/.
        
        
        Development
        ~~~~~~~~~~~
        
        To install the development version of nengolib::
        
            git clone https://github.com/arvoelke/nengolib
            cd nengolib
            python setup.py develop
        
        Notebooks can be run manually in ``docs/notebooks`` by running::
        
            pip install jupyter
            jupyter notebook
        
        ***************
        Release History
        ***************
        
        0.5.2 (September 10, 2019)
        ==========================
        
        **Fixed**
        
        - Solved an issue where scipy.misc imports were relocated.
          (`#182 <https://github.com/arvoelke/nengolib/pull/182>`_)
        
        0.5.1 (April 17, 2019)
        ======================
        
        Tested against Nengo versions 2.2.0-2.8.0. Requires ``nengo<3.0``.
        
        **Fixed**
        
        - A variety of miscellaneous fixes were made to the documentation.
          The ``nengolib.networks.RollingWindow`` documentation references the
          shifted Legendre polynomial equations for ``legendre == True``.
          (`#176 <https://github.com/arvoelke/nengolib/pull/176>`_)
        
        0.5.0 (March 9, 2019)
        =====================
        
        Tested against Nengo versions 2.2.0-2.8.0.
        We now require ``numpy>=1.13.0``, ``scipy>=0.19.0``, and ``nengo>=2.2.0``.
        
        **Added**
        
        - Added the ``nengolib.RLS()`` recursive least-squares (RLS)
          learning rule. This can be substituted for ``nengo.PES()``.
          See ``notebooks/examples/full_force_learning.ipynb`` for an
          example that uses this to implement spiking FORCE in Nengo.
          (`#133 <https://github.com/arvoelke/nengolib/pull/133>`_)
        - Added the ``nengolib.stats.Rd()`` method for quasi-random sampling of
          arbitrarily high-dimensional vectors. It is now the default method for
          scattered sampling of encoders and evaluation points.
          The method can be manually switched back to ``nengolib.stats.Sobol()``.
          (`#153 <https://github.com/arvoelke/nengolib/pull/153>`_)
        - Added the ``nengolib.neuron.init_lif(sim, ens)`` helper function
          for initializing the neural state of a ``LIF`` ensemble, from within
          a simulator block, to represent ``0`` uniformly at the start.
          (`#156 <https://github.com/arvoelke/nengolib/pull/156>`_)
        - Added ``nengolib.synapses.LegendreDelay`` as an alternative to
          ``nengolib.synapses.PadeDelay`` -- it has an equivalent transfer function
          but a state-space realization corresponding to the shifted
          Legendre basis.
          The network ``nengolib.networks.RollingWindow`` support ``legendre=True``
          to make this system the default realization.
          (`#161 <https://github.com/arvoelke/nengolib/pull/161>`_)
        
        
        **Fixed**
        
        - Release no longer requires ``pytest``.
          (`#156 <https://github.com/arvoelke/nengolib/pull/156>`_)
        
        0.4.2 (May 18, 2018)
        ====================
        
        Tested against Nengo versions 2.1.0-2.7.0.
        
        **Added**
        
        - Solving for connection weights by accounting for the neural
          dynamics. To use, pass in ``nengolib.Temporal()`` to
          ``nengo.Connection`` for the ``solver`` parameter.
          Requires ``nengo>=2.5.0``.
          (`#137 <https://github.com/arvoelke/nengolib/pull/137>`_)
        
        0.4.1 (December 5, 2017)
        ========================
        
        Tested against Nengo versions 2.1.0-2.6.0.
        
        **Fixed**
        
        - Compatible with newest SciPy release (1.0.0).
          (`#130 <https://github.com/arvoelke/nengolib/pull/130>`_)
        
        0.4.0b (June 7, 2017)
        =====================
        
        Initial beta release of nengolib.
        Tested against Nengo versions 2.1.0-2.4.0.
        
Keywords: Neural Engineering Framework,Nengo,Dynamical Spiking Networks,Neural Dynamics,Reservoir Computing
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Framework :: Nengo
Classifier: Intended Audience :: Science/Research
Classifier: License :: Free for non-commercial use
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
