Metadata-Version: 1.1
Name: pyroomacoustics
Version: 0.1.5
Summary: A simple framework for room acoustics and audio processing in Python.
Home-page: https://github.com/LCAV/pyroomacoustics
Author: Laboratory for Audiovisual Communications, EPFL
Author-email: fakufaku@gmail.ch
License: MIT
Description: Pyroomacoustics
        ===============
        
        .. image:: https://travis-ci.org/LCAV/pyroomacoustics.svg?branch=pypi-release
            :target: https://travis-ci.org/LCAV/pyroomacoustics
        .. image:: https://readthedocs.org/projects/pyroomacoustics/badge/?version=pypi-release
            :target: http://pyroomacoustics.readthedocs.io/en/pypi-release/
            :alt: Documentation Status
        
        Summary
        -------
        
        Pyroomacoustics is a software package aimed at the rapid development
        and testing of audio array processing algorithms. The content of the package
        can be divided into three main components: an intuitive Python object-oriented
        interface to quickly construct different simulation scenarios involving
        multiple sound sources and microphones in 2D and 3D rooms; a fast C
        implementation of the image source model for general polyhedral rooms to
        efficiently generate room impulse responses and simulate the propagation
        between sources and receivers; and finally, reference implementations of
        popular algorithms for beamforming, direction finding, and adaptive filtering.
        Together, they form a package with the potential to speed up the time to market
        of new algorithms by significantly reducing the implementation overhead in the
        performance evaluation step.
        
        Room Acoustics Simulation
        `````````````````````````
        
        Consider the following scenario.
        
          Suppose, for example, you wanted to produce a radio crime drama, and it
          so happens that, according to the scriptwriter, the story line absolutely must culminate
          in a satanic mass that quickly degenerates into a violent shootout, all taking place
          right around the altar of the higly reverberant acoustic environment of Oxford's
          Christ Church cathedral. To ensure that it sounds authentic, you asked the Dean of
          Christ Church for permission to record the final scene inside the cathedral, but
          somehow he fails to be convinced of the artistic merit of your production, and declines
          to give you permission. But recorded in a conventional studio, the scene sounds flat.
          So what do you do ?
        
          -- Schnupp, Nelken, and King, *Auditory Neuroscience*, 2010
        
        Faced with this difficult situation, **pyroomacoustics** can save the day by simulating
        the environment of the Christ Church cathedral!
        
        At the core of the package is a room impulse response generator based on the
        image source model that can handle
        
        * Convex and non-convex rooms
        * 2D/3D rooms
        
        Both a pure python implementation and a C accelerator are included for maximum
        speed and compatibility.
        
        The philosophy of the package is to abstract all necessary elements of
        an experiment using object oriented programming concept. Each of these elements
        is represented using a class and an experiment can be designed by combining
        these elements just as one would do in a real experiment.
        
        Let's imagine we want to simulate a delay and sum beamformer that uses a linear
        array with four microphones in a shoe box shaped room that contains only one
        source of sound. First, we create a room object, to which we add a microphone
        array object, and a sound source object. Then, the room object has methods
        to compute the RIR between source and receiver. The beamformer object then extends
        the microphone array class and has different methods to compute the weights, for
        example delay-and-sum weights. See the example below to get an idea of what the
        code looks like.
        
        The `Room` class allows in addition to process sound samples emitted by sources,
        effectively simulating the propagation of sound between sources and microphones.
        At the input of the microphone composing the beamformer, an STFT (short time
        Fourier transform) engine allows to quickly process the signals through the
        beamformer and evaluate the ouput.
        
        Reference Implementations
        `````````````````````````
        
        In addition to its core image source model simulation, **pyroomacoustics**
        also contains a number of reference implementations of popular audio processing
        algorithms for
        
        * beamforming
        * direction of arrival finding
        * adaptive filtering
        
        We use an object-oriented approach that allows to abstract the details of
        specific algorithms, making them easy to compare. Each algorithm is still
        finely tunable through optional parameters. In general, we have tried to
        pre-set good values for the tuning parameters so that a run with default value
        will in general produce reasonable results.
        
        Quick Install
        -------------
        
        Install the package with pip::
        
            $ pip install pyroomacoustics
        
        The requirements are::
        
        * numpy 
        * scipy 
        * matplotlib
        
        Example
        -------
        
        .. code-block:: python
        
            import numpy as np
            import matplotlib.pyplot as plt
            import pyroomacoustics as pra
        
            # Create a 4 by 6 metres shoe box room
            room = pra.ShoeBox([4,6])
        
            # Add a source somewhere in the room
            room.add_source([2.5, 4.5])
        
            # Create a linear array beamformer with 4 microphones
            # with angle 0 degrees and inter mic distance 10 cm
            R = pra.linear_2D_array([2, 1.5], 4, 0, 0.04) 
            room.add_microphone_array(pra.Beamformer(R, room.fs))
        
            # Now compute the delay and sum weights for the beamformer
            room.mic_array.rake_delay_and_sum_weights(room.sources[0][:1])
        
            # plot the room and resulting beamformer
            room.plot(freq=[1000, 2000, 4000, 8000], img_order=0)
            plt.show()
        
        Authors
        -------
        
        * Robin Scheibler
        * Ivan Dokmanić
        * Sidney Barthe
        * Eric Bezzam
        * Hanjie Pan
        
        How to contribute
        -----------------
        
        If you would like to contribute, please clone the
        `repository <http://github.com/LCAV/pyroomacoustics>`_ and send a pull request.
        
        Academic publications
        ---------------------
        
        This package was developped to support academic publications. The package
        contains implementations for doa algorithm and acoustic beamformers introduced
        in the following papers.
        
        * H\. Pan, R. Scheibler, I. Dokmanic, E. Bezzam and M. Vetterli. *FRIDA: FRI-based DOA estimation for arbitrary array layout*, ICASSP 2017, New Orleans, USA, 2017.
        * I\. Dokmanic, R. Scheibler and M. Vetterli. *Raking the Cocktail Party*, in IEEE Journal of Selected Topics in Signal Processing, vol. 9, num. 5, p. 825 - 836, 2015.
        * R\. Scheibler, I. Dokmanic and M. Vetterli. *Raking Echoes in the Time Domain*, ICASSP 2015, Brisbane, Australia, 2015. 
        
        License
        -------
        
        ::
        
          Copyright (c) 2014-2017 EPFL-LCAV
        
          Permission is hereby granted, free of charge, to any person obtaining a copy of
          this software and associated documentation files (the "Software"), to deal in
          the Software without restriction, including without limitation the rights to
          use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
          of the Software, and to permit persons to whom the Software is furnished to do
          so, subject to the following conditions:
        
          The above copyright notice and this permission notice shall be included in all
          copies or substantial portions of the Software.
        
          THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
          IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
          FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
          AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
          LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
          OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
          SOFTWARE.
        
        
Keywords: room acoustics signal processing doa beamforming adaptive
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Information Technology
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Multimedia :: Sound/Audio :: Speech
Classifier: Topic :: Multimedia :: Sound/Audio :: Analysis
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
