Skip to content

gvrlab/spectrum

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

86 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

SPECTRUM : Spectral Analysis in Python

https://pypip.in/d/spectrum/badge.png https://secure.travis-ci.org/cokelaer/spectrum.png https://coveralls.io/repos/cokelaer/spectrum/badge.png?branch=master https://landscape.io/github/cokelaer/spectrum/master/landscape.png https://badge.waffle.io/cokelaer/spectrum.png?label=ready&title=Ready
contributions:Please join https://github.com/cokelaer/spectrum
issues:Please use https://github.com/cokelaer/spectrum/issues

http://www.thomas-cokelaer.info/software/spectrum/html/_images/psd_all.png

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 for any issues/bugs/comments/contributions.

Some notebooks (external contributions)

About

Spectral Analysis in Python

Resources

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 92.7%
  • C 7.3%