https://github.com/nils-werner/mdct

A fast MDCT implementation using SciPy and FFTs
https://github.com/nils-werner/mdct

audio-analysis scientific-computing scipy signal-processing

Last synced: 1 day ago
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A fast MDCT implementation using SciPy and FFTs

• Host: GitHub
• URL: https://github.com/nils-werner/mdct
• Owner: nils-werner
• License: mit
• Created: 2016-05-23T10:37:27.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2022-06-18T21:26:07.000Z (over 2 years ago)
• Last Synced: 2024-10-31T08:42:04.770Z (8 days ago)
• Topics: audio-analysis, scientific-computing, scipy, signal-processing
• Language: Python
• Homepage: http://mdct.readthedocs.io/
• Size: 56.6 KB
• Stars: 50
• Watchers: 6
• Forks: 10
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-python-scientific-audio - MDCT - werner/mdct) [:package:](https://pypi.python.org/pypi/mdct) - MDCT transform. (Audio Related Packages)

README

        
MDCT

====

[![Build Status](https://travis-ci.org/nils-werner/mdct.svg?branch=master)](https://travis-ci.org/nils-werner/mdct)

[![Docs Status](https://readthedocs.org/projects/mdct/badge/?version=latest)](https://mdct.readthedocs.org/en/latest/)

A fast MDCT implementation using SciPy and FFTs

Installation

------------

As usual

    pip install mdct

## Dependencies

 - NumPy

 - SciPy

 - STFT

Usage

-----

    import mdct

    

    spectrum = mdct.mdct(sig)

**Also see the [docs](http://mdct.readthedocs.io/)**

References

----------

 - Implementation: Marina Bosi, Richard E. Goldberg and Leonardo Chiariglione, "Introduction to Digital Audio Coding and Standards", Kluwer Academic Publishers, 01 December, 2002.