Metadata-Version: 1.1
Name: music22
Version: 0.0.5
Summary: A tool for musicological analysis from audio files. Now it is focused on modal music analysis : Scale analysis, tonic detection
Home-page: https://gitlab.com/AnasGhrab/music22
Author: Anas Ghrab
Author-email: anas.ghrab@gmail.com
License: MIT
Description: =================================================
        Music22: Modal Music Analysis
        =================================================
        
        Overview
        ========
        
        Music22 is a Python2 package for musicological analysis, especially modal music and melodies. The analysis is done from audio files.
        
        For now, it's main features are :
        
        * Fondamental frequencies extraction (using *PredominentMelody()* from **Essentia**);
        * Getting the main frequencies as peaks of the probability density function from frequencies;
        * Comparing PDFs using a correlation coefficient;
        * Getting a similarity matrix between melodies.
        
        Installation
        ============
        
        To use Music22, you need to manually install `Essentia`_. `In futur versions, it will be also possible to use` `TimeSide`_.
        
        Then, install Music22 with the following :
        
        .. code:: python
        	
        	pip install music22
        
        Or, if you have a GitLab account, using ``git``:
        
        .. code:: python
        
        	git clone https://gitlab.com/AnasGhrab/music22
        	python setup.py install
        
        
        .. _Essentia: http://essentia.upf.edu/
        .. _TimeSide: https://github.com/Parisson/TimeSide
        
        Basic Usage
        ===========
        
        To use Music22 :
        
        .. code:: python
        
        	from music22 import modalis,scale
        	path = "path/to/a/folder/with/audios/wav/files/"
        	Kchants = modalis.melodies(path,transpose='Yes',freqref=300)
        	
        Then you can
        
        .. code:: python
        
        	Kchants.pdf_show()
        	Kchants.matrix()
        	Kchants.melodies[0].scale
        		
        For more details, please read to the tutorial (in french) :
        
        http://nbviewer.ipython.org/github/AnasGhrab/music22/blob/master/docs/source/examples/barraq.ipynb
        
        Contact
        =======
        
        Homepage: http://anas.ghrab.tn
        
        Email:
        
         * Anas Ghrab <anas.ghrab@gmail.com>
        
        License
        =======
        
        GNU General Public License
        
        https://www.gnu.org/licenses/gpl-3.0.en.html
        
        https://gitlab.com/AnasGhrab/music22/blob/master/LICENSE
        
        Copyright (c) 2015-2017 Anas Ghrab
        
Keywords: musicology analysis from non-symbolic data
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Multimedia :: Sound/Audio :: Analysis
