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CHANGES.rst

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-----------------------------------
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* Add pip installation information.
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* Replace distribute_setup with ez_setup.
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* Change name to Time Encoding and Decoding Toolkit.
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Release 0.07 - (August 8, 2012)
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-------------------------------
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* Merge with utils toolbox.
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* Merge with utils toolkit.
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* Add docs for merged utilities.
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* Improve finding of includes/libraries needed to build bpa extension.
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* Download distribute for package installation if it isn't available.

CHANGES.utils.rst

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Change Log
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==========
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This change log contains the history of the Bionet Utils toolbox prior to its
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merger with the TED toolbox.
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This change log contains the history of the Bionet Utils toolkit prior to its
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merger with the TED toolkit.
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Release 0.017 - (September 19, 2011)
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------------------------------------

INSTALL.rst

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Obtaining the Latest Software
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-----------------------------
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The latest version of the Time Encoding and Decoding Toolbox can be
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The latest version of the Time Encoding and Decoding Toolkit can be
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downloaded from the Bionet Group's `code repository page
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<http://bionet.github.io/>`_.
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Prerequisites
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-------------
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The Python implementation of the Time Encoding and Decoding Toolbox
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The Python implementation of the Time Encoding and Decoding Toolkit
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requires that several software packages be present in order to be
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built and installed (older versions of these packages may work, but have not
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been tested):
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Building and Installation
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-------------------------
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To build and install the toolbox, download and unpack the source
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release and run::
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To build and install the toolkit, download and unpack the source release and
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run::
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python setup.py install
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from within the main directory in the release. Sample code
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demonstrating how to use the toolbox is located in the
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from within the main directory in the release. Sample code demonstrating how to
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use the toolkit is located in the
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``demos/`` subdirectory. If you have `pip <http://www.pip-installer.org>`_
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installed, you can install the latest package code directly from Github as
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follows::

README.rst

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.. -*- rst -*-
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Time Encoding and Decoding Toolbox
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Time Encoding and Decoding Toolkit
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==================================
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Package Description
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-------------------
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The Time Encoding and Decoding Toolbox contains Python implementations
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The Time Encoding and Decoding Toolkit contains Python implementations
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of algorithms designed to reversibly convert digitally sampled signals
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to and from a time-domain representation consisting of a series of
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time intervals between fixed-amplitude spikes. Sample code
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References
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----------
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The algorithms implemented in this toolbox are described in the papers
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The algorithms implemented in this toolkit are described in the papers
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listed in the attached BibTeX bibliography. Further research on
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time domain coding and processing may be obtained from the Bionet Group
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publication server [3]_.

bionet/ted/info.py

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#!/usr/bin/env python
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"""
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Time Encoding and Decoding Toolbox
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Time Encoding and Decoding Toolkit
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==================================
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Routines for converting finite-length, band-limited, digitally sampled

docs/source/conf.py

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# dir menu entry, description, category)
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texinfo_documents = [
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('index', 'TED', u'TED Documentation',
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u'Lev Givon', 'TED', 'Time Encoding and Decoding Toolbox.',
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u'Lev Givon', 'TED', 'Time Encoding and Decoding Toolkit.',
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'Miscellaneous'),
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]
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docs/source/index.rst

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.. -*- rst -*-
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Time Encoding and Decoding Toolbox
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Time Encoding and Decoding Toolkit
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==================================
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Introduction
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------------
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The Time Encoding and Decoding Toolbox (TED) is a library of Python
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The Time Encoding and Decoding Toolkit (TED) is a library of Python
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routines, classes, and demo programs that implement time encoding and
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decoding algorithms. A
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`MATLAB <http://www.mathworks.com/products/matlab/>`_ implementation of the

docs/source/machines.rst

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Time Encoding and Decoding Machines
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===================================
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The TED Toolbox provides implementations of a range of time encoding
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The TED Toolkit provides implementations of a range of time encoding
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and decoding machines. Brief descriptions of these machines are
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provided in the following pages, along with links to the relevant
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articles that describe them in more detail and documentation

docs/source/overview.rst

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---------------
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See the :doc:`publications <publications>` page for the list of articles whose
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algorithms are implemented in the toolbox. More literature on time encoding and
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algorithms are implemented in the toolkit. More literature on time encoding and
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decoding is available on the `Bionet publication server
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<http://www.bionet.ee.columbia.edu/publications/>`_.
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docs/source/publications.rst

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Publications
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============
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The Time Encoding and Decoding Toolbox implements algorithms from the following
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The Time Encoding and Decoding Toolkit implements algorithms from the following
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publications:
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|lazar_time_2004|_ A.A. Lazar, **Time Encoding with an Integrate-and-Fire

setup.py

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URL = 'http://bionet.github.io/ted.python/'
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MAINTAINER = 'Lev Givon'
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MAINTAINER_EMAIL = '[email protected]'
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DESCRIPTION = 'Time Encoding and Decoding Toolbox'
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DESCRIPTION = 'Time Encoding and Decoding Toolkit'
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DOWNLOAD_URL = URL
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LICENSE = 'BSD'
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CLASSIFIERS = [
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ext_modules = []
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if not(len(sys.argv) >= 2 and ('--help' in sys.argv[1:] or \
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sys.argv[1] in ('--help-commands', 'egg_info', '--version', 'clean'))):
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# Needed to build pyx files:
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from Cython.Distutils import build_ext
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['bionet/ted/bpa_cython.pyx'],
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[np.get_include()],
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libraries=['python' + get_python_version()])]
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metadata = dict(name = NAME,
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version = VERSION,
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author = AUTHOR,

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