Skip to main content

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.

Metadata

Release files for pyfda 0.9.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pyfda 0.9.5
File Size Uploaded
pyfda-0.9.5.tar.gz 579.0 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for pyfda 0.9.5
File Interpreter ABI Platform
pyfda-0.9.5-py3-none-any.whl Python 3 none any Details

Total release size: 1.2 MB

Release files / pyfda-0.9.5.tar.gz

Download URL pyfda-0.9.5.tar.gz
Size 579.0 kB
Tags Source
SHA-256 checksum
How to use checksums
fab3e3f0772d7ae2d8510cae74224b3be095dfab05eb16847442a32a9df5b2d8
BLAKE2b-256 checksum
How to use checksums
c6ee3516c377553f729666d7ff9824eb266c768d81fda551c29049f831efa465
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.0.1 CPython/3.12.8

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Dec 22, 2024.

Transparency log

Release files / pyfda-0.9.5-py3-none-any.whl

Download URL pyfda-0.9.5-py3-none-any.whl
Size 660.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
72bcc7d9fa3d39b94758534525f47f3bcb4ff58fab1e1623d0085a6565286ea6
BLAKE2b-256 checksum
How to use checksums
bce86fe0fdf6ad87e2a459e3d4b857678a3dcc08a1691f55c18b4d18e94515e8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.0.1 CPython/3.12.8

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Dec 22, 2024.

Transparency log

Release history Release notifications | RSS feed

This release

0.9.5 This release

2 release files

0.9.4

2 release files

0.9.3

2 release files

0.9.2

2 release files

0.9.1

2 release files

0.9.0

2 release files

0.8.4

2 release files

0.8.3

2 release files

0.8.2

2 release files

0.8.1

2 release files

0.8.0

2 release files

0.7.1

2 release files

0.7.0

2 release files

0.6.1

1 release file

0.6.0

1 release file

0.5.3

1 release file

0.5.1

1 release file

0.5.0

1 release file

0.4.0

1 release file

0.3.1

1 release file

0.3.0

1 release file

0.2.1

1 release file

0.2

1 release file

0.1.5

1 release file

0.1.4

1 release file

0.1.3

1 release file

0.1.2

1 release file

0.1.1

1 release file

0.1

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page