Skip to main content

Collection of dsp algorithms to be used for analysis of audio signals

Project description

docs/logo/logo.png
Documentation Status License Python version PyPI version

Readme

This is a toolbox in form of a python package that contains algorithms to be used in dsp (digital signal processing) research projects.

This is kind of a “sandbox” project with many different experimental implementations across a variety of DSP-related topics. Some parts are more thoroughly tested and validated than others, so “caution” is advised. Please feel free to reach out in case you find bugs or want to talk about certain functionality.

It is under active development and it will take some time until it reaches a certain level of maturity. Beware that backwards compatibility is not an actual concern and significant changes to the API might come in the future. If you find some implementations interesting or useful, please feel free to use it for your projects and expand or change functionalities.

Getting Started

Check out the examples for some basic examples of the dsptoolbox package and refer to the documentation for the complete description of classes and functions.

Installation

Use pip to install dsptoolbox

$ pip install dsptoolbox

# Or this for activating numba parallelization
$ pip install "dsptoolbox[use-numba]"

(Requires Python 3.11 or higher)

In order to install the package successfully using Linux, you need to install PortAudio manually, since installing sounddevice will not do it automatically. To do this, run the following commands on your console:

$ sudo apt-get install libasound-dev libportaudio2 libsndfile1

If this does not work properly for some reason, refer to the documentation for sounddevice or PortAudio.

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

dsptoolbox-0.8.tar.gz (244.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dsptoolbox-0.8-py3-none-any.whl (290.4 kB view details)

Uploaded Python 3

File details

Details for the file dsptoolbox-0.8.tar.gz.

File metadata

  • Download URL: dsptoolbox-0.8.tar.gz
  • Upload date:
  • Size: 244.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.3

File hashes

Hashes for dsptoolbox-0.8.tar.gz
Algorithm Hash digest
SHA256 450cabdb1e79623c8be0e1b58fa69796fb0c109570178f643fe9d64458215cfb
MD5 77cf231496921e10b70357040c0cb94f
BLAKE2b-256 c5108c4a4e99a5c9e0f4ea18dac4ca7e6eb16caa3530bffbd08782c6349d114d

See more details on using hashes here.

File details

Details for the file dsptoolbox-0.8-py3-none-any.whl.

File metadata

  • Download URL: dsptoolbox-0.8-py3-none-any.whl
  • Upload date:
  • Size: 290.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.3

File hashes

Hashes for dsptoolbox-0.8-py3-none-any.whl
Algorithm Hash digest
SHA256 d5d89e70ef1725df4e0629be2abd918278b6c446a464df7ddc1d4968ef1376f0
MD5 0e9ba2c7722564a036962ab5016956e3
BLAKE2b-256 619be4907ebbf319cd944a13191578816edf2869a61bda0a6c69ab9270426e3a

See more details on using hashes here.

Supported by

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