Python Filter Design Analysis Tool¶
pyFDA is a GUI tool in Python / Qt for analysing and designing discrete time filters.
- Python versions: 3.3 … 3.7
- All operating systems - there should be no OS specific requirements.
- numpy, scipy, matplotlib
Optional libraries: * docutils for rich text in documentation * xlwt and / or XlsxWriter for exporting filter coefficients as *.xls(x) files
- Filter design
- Design methods: Equiripple, Firwin, Moving Average, Bessel, Butterworth, Elliptic, Chebychev 1 and 2 (from scipy.signal and custom methods)
- Second-Order Sections are used in the filter design when available for more robust filter design and analysis
- Remember all specifications when changing between filter design methods
- Fine-tune manually the filter order and corner frequencies calculated by minimum order algorithms
- Filter coefficients and poles / zeroes can be displayed, edited and quantized in various formats
- Clearly structured User Interface
- only widgets needed for the currently selected design method are visible
- enter specifications as absolute or normalized frequencies resp. in dB or voltage / power ratios using expressions like exp(-pi/4 * 1j) (integrated library simpleeval <https://pypi.python.org/pypi/simpleeval>)
- enhanced matplotlib NavigationToolbar (nicer icons, additional functions)
- display help files (own / Python docstrings) as rich text
- tooltips for all control and entry widgets
- Graphical Analyses
- Magnitude response (lin / power / log) with optional display of specification bands, phase and an inset plot
- Phase response (wrapped / unwrapped)
- Group delay
- Pole / Zero plot
- Impulse response and step response (lin / log)
- 3D-Plots (|H(f)|, mesh, surface, contour) with optional pole / zero display
- Modular architecture, facilitating the implementation of new
filter design and analysis methods
- Filter design files not only contain the actual algorithm but also dictionaries specifying which parameters and standard widgets have to be displayed in the GUI.
- Special widgets needed by design methods (e.g. for choosing the window type in Firwin) are included in the filter design file, not in the main program
- Saving and loading
- Save and load filter designs in pickled and in numpy’s NPZ-format
- Export and import coefficients and poles/zeros as comma-separated values (CSV), in numpy’s NPY- and NPZ-formats, in Excel (R) or in Matlab (R) workspace format
- Export coefficients in FPGA vendor specific formats like Xilinx (R) COE-format
There is only one version of pyfda for all supported operating systems, Python and Qt versions. As there are no binaries included, you can simply install from the source.
If you use the Anaconda distribution, you can install / update pyfda from my Anaconda channel Chipmuenk using
conda install -c Chipmuenk pyfda
conda update -c Chipmuenk pyfda
Otherwise, you can 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 the specified path is the one your setup.py sits in. In this case, you need to have a local copy of the pyfda project, preferrably using git. Now you can edit your local copy, test it and e.g. push it to your own git fork.
In any case, the start script
pyfdax has been created in
<python>/Scripts which should be in your path. So, simply start
For development and debugging, you can also run pyFDA using
In : %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 : %run -m pyfda.input_widgets.input_pz # IPython or >> python -m pyfda.input_widgets.input_pz # plain python interpreter
- Layout and some parameters can be customized with the file
pyfda/pyfda_rc.py(within the install directory right now).
- Select which widgets and filters will be included, define a user
directory for integration of your own widgets in
- Control logging behaviour with