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carlkl / packages / spectrum 0.6.1

Spectrum Analysis Tools

  • License: LGPL
  • 13326 total downloads
  • Last upload: 8 years and 7 months ago

Installers

pip install

To install this package run one of the following:
pip install -i https://pypi.anaconda.org/carlkl/simple spectrum

Description

SPECTRUM : Spectral Analysis in Python

.. image:: https://badge.fury.io/py/spectrum.svg :target: https://badge.fury.io/py/spectrum.svg

.. image:: https://pypip.in/d/spectrum/badge.png :target: https://crate.io/packages/spectrum/

.. image:: https://secure.travis-ci.org/cokelaer/spectrum.png :target: http://travis-ci.org/cokelaer/spectrum

.. image:: https://coveralls.io/repos/cokelaer/spectrum/badge.png?branch=master :target: https://coveralls.io/r/cokelaer/spectrum?branch=master

.. image:: https://landscape.io/github/cokelaer/spectrum/master/landscape.png :target: https://landscape.io/github/cokelaer/spectrum/master

.. image:: https://badge.waffle.io/cokelaer/spectrum.png?label=ready&title=Ready :target: https://waffle.io/cokelaer/spectrum

:contributions: Please join https://github.com/cokelaer/spectrum :issues: Please use https://github.com/cokelaer/spectrum/issues

.. image:: http://www.thomas-cokelaer.info/software/spectrum/html/images/psdall.png :class: align-right :width: 50%

Spectrum contains tools to estimate Power Spectral Densities using methods based on Fourier transform, Parametric methods or eigenvalues analysis:

* The Fourier methods are based upon correlogram, periodogram and Welch estimates. Standard tapering windows (Hann, Hamming, Blackman) and more exotic ones are available (DPSS, Taylor, ...). 
* The parametric methods are based on Yule-Walker, BURG, MA and ARMA, covariance and modified covariance methods.
* Non-parametric methods based on eigen analysis (e.g., MUSIC) and minimum variance analysis are also implemented.
* Multitapering is also available

Installation

::

pip install spectrum

Contributions

Please see github <http://github.com/cokelaer/spectrum>_ for any issues/bugs/comments/contributions.

Some notebooks (external contributions)

  • http://nbviewer.ipython.org/gist/juhasch/5182528

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