python-deltasigma

A port of the MATLAB Delta Sigma Toolbox based on free software and very little sleep

The python-deltasigma is a Python package to synthesize, simulate, scale and map to implementable topologies delta sigma modulators.

It aims to provide a 1:1 Python port of Richard Schreier's excellent MATLAB Delta Sigma Toolbox, the de facto standard tool for high-level delta sigma simulation, upon which it is very heavily based.

Homepage: python-deltasigma.io

Documentation: docs.python-deltasigma.io

Latest version: 0.2

Status

The fundamental functionality is available and working.

Secondary features such as "native" quadrature modulator support, PIS calculation or ESL are still work in progress. A list of functions and files is included in files.csv, updated with the current status.

Further functionality is expected to be completed in the next versions according to the ROADMAP.

Install

python-deltasigma runs on Linux, Mac OS X and Windows.

Installing requires Python 2.6+ or 3.3+, numpy, scipy (>= 0.11.0) and matplotlib.

Strongly recommended: Cython - for significantly faster delta sigma modulator simulations.

They are packaged by virtually all the major Linux distributions.

I do not run Windows, so I can't really provide more info (sorry), except that people tell me they manage to have a working setup.

When the dependencies are satisfied, run:

pip install deltasigma

to install the latest stable version from the Python Package Index (PYPI), or:

python setup.py install

if you're installing a development version from Git.

Extras

Install the sphinx package to build the documentation yourself.

The test suite requires setuptools, used to access the reference function outputs.

Testing can be automated with nose, issuing:

nosetests -v deltasigma

Documentation

In addition to the notebooks found in the examples/ directory, ported from the MATLAB Delta Sigma toolbox:

You can find the included package documentation online.
The original MATLAB Toolbox provides in-depth documentation, which is very useful to understand what the toolbox is capable of. See DSToolbox.pdf and OnePageStory.pdf (PDF warning).
The book:

Richard Schreier, Gabor C. Temes, Understanding Delta-Sigma Data Converters, ISBN: 978-0-471-46585-0, November 2004, Wiley-IEEE Press

is probably the most authoritative resource on the topic. Chapter 8-9 show how to use the MATLAB toolkit and the observations apply also to this Python port. Links on amazon, on the Wiley-IEEE press.

I am not affiliated with neither the sellers nor the authors.

How to contribute

I write this software in my free time, this is not funded research.

If you find this package useful, you are welcome to freely contribute to its development in one of the following ways.

Send a pull request my way

Pull requests are most gladly received!

There are only a few guidelines, which can be overridden every time it is reasonable to do so:

Please try to follow PEP8.
Try to keep the functions signature identical. Parameters with NaN/[] as default values have their default value replaced with None.
If a function has a varible number of return values, its Python port should implement the maximum number of return values.

Support python-deltasigma with a donation

I do not want your money. I develop this software because I enjoy it and because I use it myself.

If you wish to support the development of python-deltasigma and you wish to contribute monetarily, please donate to cancer research instead:

Consider sending me a mail afterwards, it makes for great motivation!

Licensing and copyright notice

The Python code here provided is a derivative work from the above toolkit and subject to the same license terms.

MATLAB is a registered trademark of The MathWorks, Inc.

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