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https://github.com/scottprahl/rigolwfm

Parsers for .wfm binary files created by a wide range of Rigol oscilloscopes
https://github.com/scottprahl/rigolwfm

kaitai-struct oscilloscope parser rigol

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Parsers for .wfm binary files created by a wide range of Rigol oscilloscopes

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RigolWFM

=========



by Scott Prahl



A utility to process Rigol oscilloscope ``.wfm`` files

------------------------------------------------------



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This project is intended to be a comprehensive resource for interpreting waveform ``.wmf`` files created by any Rigol oscilloscope.  Open source (and Rigol's own applications) that parse/convert Rigol's binary ``.wfm`` files are sadly balkanized: each program tends to support a single oscilloscope group and the available efforts are spread across a range of languages.



This project leverages a domain specific language (kaitai struct) to represent the binary files.  Once a binary file has been described in this text format, parsers can be generated for a wide range of languages (C++/STL, C#, Go, Java, JavaScript, Lua, Perl, PHP, Python, and Ruby).  



Documentation can be found at 



Installation

---------------



You can install locally using pip::

    

    pip install --user RigolWFM



or ``conda``::



    conda install -c conda-forge RigolWFM



or use immediately by clicking the Google Colaboratory button below



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  :target: https://colab.research.google.com/github/scottprahl/RigolWFM/blob/main

  :alt: Colab



or `analyze your files using the kaitai struct IDE `_ (you will need to manually upload the appropriate `.ksy` file and your `.wfm` to the IDE).  This allows one to interactively reverse engineer binary file formats directly in your browser.  This is super helpful for those Rigol ``.wfm`` formats that are undocumented or not parsing correctly.



Usage

-----



Once ``RigolWFM`` is installed, you can plot the signals from binary Rigol ``.wfm`` files by::



   import matplotlib.pyplot as plt

   import RigolWFM.wfm as rigol



   filename = 'example.wfm'

   scope = 'DS1000E'



   w = rigol.Wfm.from_file(filename, scope)

   w.plot()

   plt.show()



Alternatively, ``wfmconvert`` can be used from the command line.  For example, the following should convert all the DS1000E files in the current directory to the ``.csv`` format::



   prompt> wfmconvert E csv *.wfm



If you just wanted to convert channel 1 from a single file to ``.csv`` then::



   prompt> wfmconvert --channel 1 E csv DS1102E.wfm



If you wanted to a signal `.wav` file using the second channel waveform (for use with LTspice) then:: 



   prompt> wfmconvert --channel 2 E wav *.wfm



If you want to create a ``.wav`` file with channels one and four as signals (and autoscale for use with Audacity or Sigrok Pulseview)::



   prompt> wfmconvert --autoscale --channel 14 E wav *.wfm



Status

------



There is a bit of work remaining (testing, validation, repackaging) but there are binary file descriptions for ``.wfm`` files created by the following scopes:



* DS1000B tested 

* DS1000C tested (two files only)

* DS1000D tested (one file only)

* DS1000E tested

* DS1000Z tested, but with wonky voltage offsets

* DS2000 tested

* DS4000 tested

* DS6000 untested



Resources

---------



This has been a bit of an adventure.  In the process of nailing down the basic formats, I have gleaned information from a wide range of projects started by others.



* Shein's Pascal program 

* Wagenaars's Matlab script 

* Steele's C program 

* Blaicher's python code 

* Szkutnik's python code 

* Cat-Ion's python code 

* Šolc's python code 

* Contributions from 

* A LabView program I got from Rigol support

* Rigol's documentation of the 1000E, 1000Z, 2000, and 6000 file formats.



Source code repository

-------------------------------------------



    



License

-------

    BSD 3-clause -- see the file ``LICENSE`` for details.