SPECTRUM : Spectral Analysis in Python
==========================================
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: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/
:Citation: Cokelaer et al, (2017), 'Spectrum': Spectral Analysis in Python, Journal of Open Source Software, 2(18), 348, doi:10.21105/joss.00348
.. image:: http://www.thomas-cokelaer.info/software/spectrum/html/_images/psd_all.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
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).
Quick Installation
=====================
**spectrum** is available on Pypi::
pip install spectrum
and **conda**::
conda config --append channels conda-forge
conda install spectrum
To install the **conda** executable itself, please see https://www.continuum.io/downloads .
Contributions
==================
Please see `github <http://github.com/cokelaer/spectrum>`_ for any issues/bugs/comments/contributions.
Changelog (summary)
===================
========== ============================================================
release description
========== ============================================================
0.9.0 * handles new numpy API (keeping back compatiblity).
* included https://github.com/cokelaer/spectrum/pull/73
thanks to @butala contribution to speed up fft.
* fix rho calculation in burg algo thanks to contri
https://github.com/cokelaer/spectrum/pull/82 from @cl445
* remove warnings/deprecation related to pkgresources, numpy
and scipy.
* ran black through entire code.
0.8.1 * move CI to github actions
* include python 3.9 support
* include PR from tikuma-lshhsc contributor to speedup
eigenfre module
* fix deprecated warnings
========== ============================================================
Some notebooks (external contributions)
-------------------------------------------
* http://nbviewer.ipython.org/gist/juhasch/5182528
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"description": "SPECTRUM : Spectral Analysis in Python\n==========================================\n\n.. image:: https://badge.fury.io/py/spectrum.svg\n :target: https://pypi.python.org/pypi/spectrum\n\n.. image:: https://github.com/cokelaer/spectrum/actions/workflows/main.yml/badge.svg?branch=master\n :target: https://github.com/cokelaer/spectrum/actions/workflows/main.yml\n\n.. image:: https://coveralls.io/repos/cokelaer/spectrum/badge.png?branch=master\n :target: https://coveralls.io/r/cokelaer/spectrum?branch=master\n\n.. image:: https://anaconda.org/conda-forge/spectrum/badges/license.svg\n :target: https://anaconda.org/conda-forge/spectrum\n\n.. image:: https://anaconda.org/conda-forge/spectrum/badges/installer/conda.svg\n :target: https://conda.anaconda.org/conda-forge\n\n.. image:: https://anaconda.org/conda-forge/spectrum/badges/downloads.svg\n :target: https://anaconda.org/conda-forge/spectrum\n\n.. image:: http://joss.theoj.org/papers/e4e34e78e4a670f2ca9a6a97ce9d3b8e/status.svg\n :target: http://joss.theoj.org/papers/e4e34e78e4a670f2ca9a6a97ce9d3b8e\n\n\n\n:contributions: Please join https://github.com/cokelaer/spectrum\n:contributors: https://github.com/cokelaer/spectrum/graphs/contributors\n:issues: Please use https://github.com/cokelaer/spectrum/issues\n:documentation: http://pyspectrum.readthedocs.io/\n:Citation: Cokelaer et al, (2017), 'Spectrum': Spectral Analysis in Python, Journal of Open Source Software, 2(18), 348, doi:10.21105/joss.00348\n\n\n\n.. image:: http://www.thomas-cokelaer.info/software/spectrum/html/_images/psd_all.png\n :class: align-right\n :width: 50%\n\n**Spectrum** contains tools to estimate Power Spectral Densities using methods based on Fourier transform, Parametric methods or eigenvalues analysis:\n\n * 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, ...).\n * The parametric methods are based on Yule-Walker, BURG, MA and ARMA, covariance and modified covariance methods.\n * Non-parametric methods based on eigen analysis (e.g., MUSIC) and minimum variance analysis are also implemented.\n * Multitapering is also available\n\n\nThe targetted audience is diverse. Although the use of power spectrum of a\nsignal is fundamental in electrical engineering (e.g. radio communications,\nradar), it has a wide range of applications from cosmology (e.g., detection of\ngravitational waves in 2016), to music (pattern detection) or biology (mass\nspectroscopy).\n\n\nQuick Installation\n=====================\n\n**spectrum** is available on Pypi::\n\n pip install spectrum\n\nand **conda**::\n\n conda config --append channels conda-forge\n conda install spectrum\n\nTo install the **conda** executable itself, please see https://www.continuum.io/downloads .\n\nContributions\n==================\n\nPlease see `github <http://github.com/cokelaer/spectrum>`_ for any issues/bugs/comments/contributions.\n\nChangelog (summary)\n===================\n\n========== ============================================================\nrelease description\n========== ============================================================\n0.9.0 * handles new numpy API (keeping back compatiblity).\n * included https://github.com/cokelaer/spectrum/pull/73\n thanks to @butala contribution to speed up fft.\n * fix rho calculation in burg algo thanks to contri\n https://github.com/cokelaer/spectrum/pull/82 from @cl445\n * remove warnings/deprecation related to pkgresources, numpy\n and scipy.\n * ran black through entire code.\n0.8.1 * move CI to github actions\n * include python 3.9 support\n * include PR from tikuma-lshhsc contributor to speedup\n eigenfre module\n * fix deprecated warnings\n========== ============================================================\n\n\n\nSome notebooks (external contributions)\n-------------------------------------------\n\n* http://nbviewer.ipython.org/gist/juhasch/5182528\n",
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