Présentation
Spectrum is a Python library that includes tools to estimate Power Spectral Densities. 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).
Methods available are based on Fourier transform, parametric methods or eigenvalues analysis. Although standard methods such as periodogram are available, less common methods are also implemented: (1) parametric methods based on Yule-Walker, BURG, MA and ARMA, covariance and modified covariance methods (2) Non-parametric methods based on eigen analysis (e.g., MUSIC) and minimum variance analysis (3) Multitapering method.
See Journal of Open Source Software for details or online documentation
Citation: Cokelaer et al., (2017). ‘Spectrum’: Spectral Analysis in Python. Journal of Open Source Software, 2(18), 348, doi:10.21105/joss.00348