Nengolib

Latest version: v0.5.2

Safety actively analyzes 613734 Python packages for vulnerabilities to keep your Python projects secure.

Scan your dependencies

Page 1 of 2

0.5.3

==================

0.5.2

==========================

**Fixed**

- Solved an issue where scipy.misc imports were relocated.
(`182 <https://github.com/arvoelke/nengolib/pull/182>`_)

0.5.1

======================

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

=====================

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

====================

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

========================

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>`_)

Page 1 of 2

© 2024 Safety CLI Cybersecurity Inc. All Rights Reserved.