Spectrum: a Spectral Analysis Library in Python

Spectrum is a Python library that contains tools to estimate Power Spectral Densities 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.
• Finally, Multitapering combines several orthogonal tapering windows.

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The targetted audience is diverse. Although the use of power spectrum of a signal is fundamental in electrical engineering (e.g. radio communications, radar), it has a wide range of applications from cosmology (e.g., detection of gravitational waves in 2016), to music (pattern detection) or biology (mass spectroscopy).

contributions:Please join https://github.com/cokelaer/spectrum contributors:https://github.com/cokelaer/spectrum/graphs/contributors issues:Please use https://github.com/cokelaer/spectrum/issues documentation:http://pyspectrum.readthedocs.io/

Installation

conda install spectrum

Examples

Visit our example gallery or jump to the main documentation