Skip to main content

The Large Time-Frequency Toolbox (LTFAT) in Python

Project description

The ltfatpy package is a partial Python port of the Large Time/Frequency Analysis Toolbox (LTFAT), a MATLAB®/Octave toolbox for working with time-frequency analysis and synthesis.

It is intended both as an educational and a computational tool.

The package provides a large number of linear transforms including Gabor transforms along with routines for constructing windows (filter prototypes) and routines for manipulating coefficients.

The original LTFAT Toolbox for MATLAB®/Octave is developed at CAHR, Technical University of Denmark, ARI, Austrian Academy of Sciences and I2M, Aix-Marseille Université.

The Python port is developed at LabEx Archimède, as a LIF (now LIS) and I2M project, Aix-Marseille Université.

This package, as well as the original LTFAT toolbox, is Free software, released under the GNU General Public License (GPLv3).

The latest version of ltfatpy can be downloaded from the following PyPI page.

The documentation is available here.

The development is done in this GitLab project, which provides the git repository managing the source code and where issues can be reported.

History

0.1.0 (2014-04-30)

Creation

1.0.0 (2015-12-15)

Based on ltfat commit 0f9c83d96b (version 2.1.0)

Authors

Denis Arrivault <contact.dev/A/lis-lab.fr> Florent Jaillet <contact.dev/A/lis-lab.fr>

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ltfatpy-1.0.16.tar.gz (29.0 MB view details)

Uploaded Source

File details

Details for the file ltfatpy-1.0.16.tar.gz.

File metadata

  • Download URL: ltfatpy-1.0.16.tar.gz
  • Upload date:
  • Size: 29.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.19.1 setuptools/40.4.3 requests-toolbelt/0.8.0 tqdm/4.27.0 CPython/3.6.6

File hashes

Hashes for ltfatpy-1.0.16.tar.gz
Algorithm Hash digest
SHA256 187e2fab9fa513be5af96b2d38f2d3cd4bad05981a762a155b583b4cefeec53b
MD5 718791a962cc60eddc4977c8700179ea
BLAKE2b-256 59bb0989c13844d1dacb569241bf84a77c2c325f095350d09e15f67e1ad72f51

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page