Skip to main content

Design and analyse discrete time DSP filters with a user-friendly GUI tool. Fixpoint filters in time and frequency domain, too.

Project description

pyfda

Python Filter Design Analysis Tool

pyfda is a GUI based tool in Python / Qt for analysing and designing discrete time filters. Fixpoint implementations (for some filter types) can be simulated.

For more info see the Github Repo and the documentation at readthedocs.org.

Screenshot

Prerequisites

  • Python versions: 3.7 ... 3.11
  • All operating systems, no OS specific requirements.
  • Libraries:
    • (Py)Qt5
    • numpy
    • scipy
    • matplotlib: 2.1 or higher

Optional libraries:

  • docutils for rich text in documentation
  • xlwt and / or XlsxWriter for exporting filter coefficients as *.xls(x) files

Installing pyfda

Self-executing archives are available for Windows and OS X at https://github.com/chipmuenk/pyfda/releases which do not require a Python installation. Under Linux, pyfda can be installed as a flatpak.

Otherwise, installation is straight forward: There is only one version of pyfda for all supported operating systems, no compilation is required:

pip

Install from PyPI using

> pip install pyfda

or upgrade using

> pip install pyfda -U

or install locally using

> pip install -e <YOUR_PATH_TO_PYFDA>

where <YOUR_PATH_TO_PYFDA> specifies the path of setup.py without including setup.py. In this case, you need to have a local copy of the pyfda project, preferrably obtained using git and pip install only creates the start script.

setup.py

You could also download the zip file from Github and extract it to a directory of your choice. Install it either to your <python>/Lib/site-packages subdirectory using

> python setup.py install

or just create a link to where you have copied the python source files (for testing / development) using

> python setup.py develop

Starting pyfda

In any case, the start script pyfdax has been created in <python>/Scripts which should be in your path. So, simply start pyfda using

> pyfdax

For development and debugging, you can also run pyfda using

In [1]: %run -m pyfda.pyfdax # IPython or
> python -m pyfda.pyfdax    # plain python interpreter

All individual files from pyfda can be run using e.g.

In [2]: %run -m pyfda.input_widgets.input_pz    # IPython or 
> python -m pyfda.input_widgets.input_pz       # plain python interpreter

Customization

The location of the following two configuration files (copied to user space) can be checked via the tab Files -> About:

  • Logging verbosity can be controlled via the file pyfda_log.conf
  • Widgets and filters can be enabled / disabled via the file pyfda.conf. You can also define one or more user directories containing your own widgets and / or filters.

Layout and some default paths can be customized using the file pyfda/pyfda_rc.py, right now you have to edit that file at its original location.

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

pyfda-0.9.3.tar.gz (574.0 kB view details)

Uploaded Source

Built Distribution

pyfda-0.9.3-py3-none-any.whl (656.5 kB view details)

Uploaded Python 3

File details

Details for the file pyfda-0.9.3.tar.gz.

File metadata

  • Download URL: pyfda-0.9.3.tar.gz
  • Upload date:
  • Size: 574.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for pyfda-0.9.3.tar.gz
Algorithm Hash digest
SHA256 919e6530927aec6a4e2242704cdbf0696ab85104dc5a7396cae2c913a51bcfdf
MD5 fb301036fde5fea0a52ec6b32f56361b
BLAKE2b-256 e848020a4b36a49baa478bebf91d77409919d8cfd828dd26e825c4670f165f2d

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyfda-0.9.3.tar.gz:

Publisher: publish_pypi.yml on chipmuenk/pyfda

Attestations:

File details

Details for the file pyfda-0.9.3-py3-none-any.whl.

File metadata

  • Download URL: pyfda-0.9.3-py3-none-any.whl
  • Upload date:
  • Size: 656.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for pyfda-0.9.3-py3-none-any.whl
Algorithm Hash digest
SHA256 607bb6f81bb068ee4491446a94a73d8bcf4afde1aa485bd34c7f6ecc7275bd60
MD5 7738be743e356af1affa581df2fc7ce3
BLAKE2b-256 e83c7fa292eef321ad6440300ec9ce69d8a813afecd93a018692d42275bdf09c

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyfda-0.9.3-py3-none-any.whl:

Publisher: publish_pypi.yml on chipmuenk/pyfda

Attestations:

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