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pyFDA

Python Filter Design Analysis Tool

pyFDA is a GUI based tool in Python / Qt for analysing and designing discrete time filters. The capability for generating Verilog and VHDL code for the designed and quantized filters will be added in the next release.

https://github.com/chipmuenk/pyFDA/raw/master/images/pyFDA_screenshot_3.PNG

Prerequisites

Besides standard python libraries, the project requires the following libraries:

  • numpy
  • scipy
  • matplotlib
  • pyQt4 or pyQt5
  • Optional libraries:
    • docutils for rendering info text as rich text
    • xlwt and / or XlsxWriter for exporting filter coefficients as *.xls(x) files

Installing and starting pyFDA

>> pip install pyfda

or download the zip file 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 run it where you have installed the python source files using (for testing / development)

>> python setup.py develop

In both cases, start scripts pyfdax and pyfdax_no_term are created (with / without terminal).

For development, you can also run pyFDA using:

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

or run individual files from pyFDA 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 layout and some default paths can be customized using the file pyfda/pyfda_rc.py.

Features

  • Filter design
    • Design methods from scipy.signal: Equiripple, Firwin, Butterworth, Elliptic, Chebychev 1 and Chebychev 2
    • Remember all specifications when changing filter design methods
    • Fine-tune manually the filter order and corner frequencies calculated by minimum order algorithms
    • Compare filter designs for a given set of specifications and different design methods
    • Filter coefficients and poles / zeroes can be displayed, edited and quantized
  • Clearly structured GUI
    • only widgets needed for the currently selected design method are visible
    • enhanced matplotlib NavigationToolbar (nicer icons, additional functions)
  • Common interface for all filter design methods:
    • specify frequencies as absolute values or normalized to sampling or Nyquist frequency
    • specify ripple and attenuations in dB, as voltage or as power ratios
    • enter expressions like exp(-pi/4 * 1j) with the help of the library simpleeval (https://pypi.python.org/pypi/simpleeval) (included in source files)
  • 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
    • Filter design files can be added and edited without changing or even restarting the program
  • Saving and loading
    • Save and load filter designs in pickled and in numpy's NPZ-format
    • Export coefficients and poles/zeros as comma-separated values (CSV), in numpy's NPZ-format, in Excel (R) or in Matlab (R) workspace format
  • Display help files (own / Python docstrings) as rich text
  • Runs under Python 2.7 and Python 3.3 ... 3.5