SPECTRUM : Spectral Analysis in Python
- contributions:
Please join https://github.com/cokelaer/spectrum
- contributors:
- issues:
Please use https://github.com/cokelaer/spectrum/issues
- documentation:
- Citation:
Cokelaer et al, (2017), ‘Spectrum’: Spectral Analysis in Python, Journal of Open Source Software, 2(18), 348, doi:10.21105/joss.00348
Overview
Spectrum contains tools to estimate Power Spectral Densities using methods based on Fourier transform, parametric methods or eigenvalues analysis:
Fourier-based methods: correlogram, periodogram and Welch estimates. Standard tapering windows (Hann, Hamming, Blackman) and more exotic ones are available (DPSS, Taylor, …).
Parametric methods: Yule-Walker, BURG, MA and ARMA, covariance and modified covariance methods.
Non-parametric (eigenanalysis) methods: MUSIC and minimum variance analysis.
Multitapering (MTM).
The targeted 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), to music (pattern detection) or biology (mass spectroscopy).
Quick Start
The example below creates a cosine signal buried in white noise and estimates its power spectral density using a simple periodogram:
from spectrum import Periodogram, data_cosine
# generate a 1024-sample cosine at 200 Hz (amplitude 0.1) buried in white noise
data = data_cosine(N=1024, A=0.1, sampling=1024, freq=200)
# create the periodogram object and plot
p = Periodogram(data, sampling=1024)
p.plot(marker='o')All PSD classes share the same interface: instantiate the object, run the estimation (or let it run lazily on first access), then call p.plot(). The functional API is also available for all methods when a quick result is needed without a full object.
See the documentation for a complete tutorial, API reference and gallery of examples.
Installation
spectrum is available on PyPI:
pip install spectrum
and on conda-forge:
conda install -c conda-forge spectrum
To install conda itself, see https://docs.conda.io/en/latest/miniconda.html.
Contributions
Please see GitHub for any issues, bugs, comments or contributions.
Changelog (summary)
release |
description |
|---|---|
0.10.0 |
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0.9.0 |
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0.8.1 |
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Some notebooks (external contributions)
1 maintainer
Metadata
1 maintainer
Release files for spectrum 0.10.0
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