Metadata-Version: 2.1
Name: spectrum
Version: 0.7.3
Summary: Spectrum Analysis Tools
Home-page: http://github.com/cokelaer/spectrum
Author: Thomas Cokelaer
Author-email: cokelaer@gmail.com
License: new BSD
Description: SPECTRUM : Spectral Analysis in Python
        ==========================================
        
        .. image:: https://badge.fury.io/py/spectrum.svg
            :target: https://pypi.python.org/pypi/spectrum
        
        .. image:: https://secure.travis-ci.org/cokelaer/spectrum.png
            :target: http://travis-ci.org/cokelaer/spectrum
        
        .. image:: https://coveralls.io/repos/cokelaer/spectrum/badge.png?branch=master 
            :target: https://coveralls.io/r/cokelaer/spectrum?branch=master 
        
        .. image:: https://landscape.io/github/cokelaer/spectrum/master/landscape.png
            :target: https://landscape.io/github/cokelaer/spectrum/master
        
        .. image:: https://anaconda.org/conda-forge/spectrum/badges/license.svg
           :target: https://anaconda.org/conda-forge/spectrum
        
        .. image:: https://anaconda.org/conda-forge/spectrum/badges/installer/conda.svg
           :target: https://conda.anaconda.org/conda-forge
        
        .. image:: https://anaconda.org/conda-forge/spectrum/badges/downloads.svg
           :target: https://anaconda.org/conda-forge/spectrum
        
        .. image:: http://joss.theoj.org/papers/e4e34e78e4a670f2ca9a6a97ce9d3b8e/status.svg
           :target: http://joss.theoj.org/papers/e4e34e78e4a670f2ca9a6a97ce9d3b8e
        
        
        
        :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/ 
        
        
        
        .. 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 --add 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.
        
        
        Some notebooks (external contributions)
        -------------------------------------------
        
        * http://nbviewer.ipython.org/gist/juhasch/5182528
        
Platform: Linux
Classifier: Development Status :: 1 - Planning
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Telecommunications Industry
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering
Provides-Extra: plot
