{ "info": { "author": "QU Lab / Christoph Hohnerlein", "author_email": "christoph.hohnerlein@qu.tu-berlin.de", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Programming Language :: Python :: 3.5", "Topic :: Multimedia :: Sound/Audio" ], "description": "Sound Field Analysis toolbox for Python\n=======================================\n\nThe *sound\\_field\\_analysis* toolbox (short: *sfa*) is a Python port of\nthe `Sound Field Analysis Toolbox (SOFiA) toolbox`_, originally by\nBenjamin Bernsch\u00fctz\\ `[1]`_. The main goal of the *sfa* toolbox is to\nanalyze, visualize and process sound field data recorded by spherical\nmicrophone arrays. Furthermore, various types of test-data may be\ngenerated to evaluate the implemented functions.\n\nThe package is pure python and PEP8 compliant (except line-length).\nPlease expect things to be slow for now and for the API to break, as the\ndevelopment is still very much ongoing.\n\nRequirements\n------------\n\nWe use Python 3.5 for development. Chances are that earlier version will\nwork too but this is currently untested.\n\nThe following external libraries are required:\n\n- `NumPy`_\n- `SciPy`_\n- `Plotly`_ (for plotting)\n\nInstallation\n------------\nYou can simply install *sfa* through pip (``pip install sound_field_analysis``).\n\nWe highly recommend the `Anaconda`_ python environment. Once installed,\nyou can use the following steps to create a new environment with the\n*sfa* toolbox.\n\n#. Create a new environment:\n ``conda create --name sfa numpy scipy plotly``\n#. Activate this environment:\n ``source activate sfa``\n#. Install from pypi:\n ``pip install sound_field_analysis``\n\nSoon, you may also install directly from the `conda-forge`_ channel using\n``conda install -c conda-forge sound_field_analysis``.\n\nDocumentation\n-------------\n\nPlease find the full documentation over at\nhttps://qulab.github.io/sound_field_analysis-py/!\n\nExamples\n--------\n\nThe following examples are available as Jupyter notebooks, either\nstatically on `github`_ or interactively on `nbviewer`_. You can of\ncourse also simply download the examples and run them locally!\n\nAE1: Ideal plane wave\n~~~~~~~~~~~~~~~~~~~~~\n\nIdeal unity plane wave simulation and 3D plot.\n\n`View interactively on nbviewer `__\n\n|AE1_img|_\n\n.. |AE1_img| image:: examples/img/AE1_shape.png?raw=true\n.. _AE1_img: http://nbviewer.jupyter.org/github/QULab/sound_field_analysis-py/blob/master/examples/AE1_IdealPlaneWave.ipynb\n\n\nAE3: Measured plane wave\n~~~~~~~~~~~~~~~~~~~~~~~~\n\nA measured plane wave from AZ=180\u00b0, EL=90\u00b0 in the anechoic chamber using\na cardioid mic.\n\n`View interactively on nbviewer `__\n\n|AE3_img|_\n\n.. |AE3_img| image:: examples/img/AE3_shape.png?raw=true\n.. _AE3_img: http://nbviewer.jupyter.org/github/QULab/sound_field_analysis-py/blob/master/examples/AE3_MeasuredWave.ipynb\n\nAE6: Impulse response of ideal plane wave\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nImpulse Response reconstruction on a simulated ideal unity plane wave\n\n`View interactively on nbviewer `__\n\n|AE6_img|_\n\n.. |AE6_img| image:: examples/img/AE6_IdealPlaneWave_ImpResp.png?raw=true\n.. _AE6_img: http://nbviewer.jupyter.org/github/QULab/sound_field_analysis-py/blob/master/examples/AE6_IdealPlaneWave_ImpResp.ipynb\n\n\n\nAE7: Impulse response of sampled plane wave\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nImpulse response reconstruction on a simulated sampled unity plane wave\n\n`View interactively on nbviewer `__\n\n|AE7_img|_\n\n.. |AE7_img| image:: examples/img/AE7_SampledPlaneWave_ImpResp.png?raw=true\n.. _AE7_img: http://nbviewer.jupyter.org/github/QULab/sound_field_analysis-py/blob/master/examples/AE7_SampledPlaneWave_ImpResp.ipynb\n\nReferences\n^^^^^^^^^^\nThe *sound_field_analysis* toolbox is based on the Matlab/C++ `Sound Field Analysis Toolbox (SOFiA) toolbox`_ by Benjamin Bernsch\u00fctz. For more information you may refer to the original publication:\n\n[1] `Bernsch\u00fctz, B., P\u00f6rschmann, C., Spors, S., and Weinzierl, S. (2011). SOFiA Sound Field Analysis Toolbox. Proceedings of the ICSA International Conference on Spatial Audio `_\n\nThe Lebedev grid generation was adapted from an implementation by `Richard P. Muller `_.\n\n\n.. _Sound Field Analysis Toolbox (SOFiA) toolbox: http://audiogroup.web.th-koeln.de/SOFiA_wiki/WELCOME.html\n.. _[1]: #references\n.. _NumPy: http://www.numpy.org\n.. _SciPy: http://www.scipy.org\n.. _Plotly: https://plot.ly/python/\n.. _Anaconda: https://www.continuum.io/downloads\n.. _conda-forge: https://conda-forge.github.io\n.. _github: examples/\n.. _nbviewer: http://nbviewer.jupyter.org/github/QULab/sound_field_analysis-py/tree/master/examples/\n", "description_content_type": null, "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://qulab.github.io/sound_field_analysis-py/", "keywords": "sound field analysis spherical microphone array", "license": "GPLv3", "maintainer": "", "maintainer_email": "", "name": "sound_field_analysis", "package_url": "https://pypi.org/project/sound_field_analysis/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/sound_field_analysis/", "project_urls": { "Homepage": "https://qulab.github.io/sound_field_analysis-py/" }, "release_url": "https://pypi.org/project/sound_field_analysis/0.3/", "requires_dist": [ "numpy", "scipy", "plotly; 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