rigolwfm

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

https://github.com/scottprahl/rigolwfm

Science Score: 46.0%

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Low similarity (12.2%) to scientific vocabulary

Keywords

kaitai-struct oscilloscope parser rigol

Keywords from Contributors

dispersion fibers modes noise optical refraction sellmeier waveguide

Last synced: 6 months ago · JSON representation

Repository

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

Basic Info

Host: GitHub
Owner: scottprahl
License: bsd-3-clause
Language: Python
Default Branch: main
Homepage:
Size: 44.5 MB

Statistics

Stars: 59
Watchers: 5
Forks: 8
Open Issues: 9
Releases: 23

Topics

kaitai-struct oscilloscope parser rigol

Created almost 6 years ago · Last pushed over 1 year ago

Metadata Files

Readme Changelog License Citation

README.rst

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RigolWFM
=========

by Scott Prahl

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

|pypi-badge| |github-badge| |conda-badge| |kaitaistruct| |zenodo-badge|

|license-badge| |test-badge| |docs-badge| |downloads-badge|

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

.. image:: https://colab.research.google.com/assets/colab-badge.svg
  :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.

Owner

Name: Scott Prahl
Login: scottprahl
Kind: user
Location: Portland, Oregon
Company: Oregon Institute of Technology

Website: http://omlc.org/~prahl
Repositories: 11
Profile: https://github.com/scottprahl

GitHub Events

Total

Issues event: 3
Watch event: 13
Issue comment event: 1

Last Year

Issues event: 3
Watch event: 13
Issue comment event: 1

Committers

Last synced: 7 months ago

All Time

Total Commits: 511
Total Committers: 9
Avg Commits per committer: 56.778
Development Distribution Score (DDS): 0.133

Past Year

Commits: 0
Committers: 0
Avg Commits per committer: 0.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
Scott Prahl	s**t@p**m	443
Work Prahl	p**l@b**u	37
Matthias Blaicher	m**s@b**m	20
James Pitts	j**m@c**m	4
GitHub Action	a**n@g**m	3
Tomaz Solc	t**c@t**g	1
Michael Stapelberg	s**g@g**m	1
Karl Palsson	k**p@t**u	1
Wouter van der Vinne	w**r@e**m	1

Committer Domains (Top 20 + Academic)

eazwind.com: 1 tweak.au: 1 google.com: 1 tablix.org: 1 github.com: 1 codeworker.com: 1 blaicher.com: 1 bme.ogi.edu: 1 prahls.com: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 19
Total pull requests: 10
Average time to close issues: 18 days
Average time to close pull requests: 15 days
Total issue authors: 14
Total pull request authors: 8
Average comments per issue: 4.32
Average comments per pull request: 0.9
Merged pull requests: 6
Bot issues: 0
Bot pull requests: 1

Past Year

Issues: 1
Pull requests: 0
Average time to close issues: 36 minutes
Average time to close pull requests: N/A
Issue authors: 1
Pull request authors: 0
Average comments per issue: 1.0
Average comments per pull request: 0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

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Top Authors

Issue Authors

scottprahl (5)
stapelberg (2)
benvanloock (1)
danbates2 (1)
goodjing50 (1)
svpcom (1)
JoetVer (1)
Phi1983 (1)
PeterGrace (1)
beta-tester (1)
mh- (1)
AlejandroBizzotto (1)
ziceva (1)
byzantic (1)

Pull Request Authors

scottprahl (2)
wvdv2002 (2)
jamespitts (1)
avian2 (1)
karlp (1)
brainstorm (1)
dependabot[bot] (1)
stapelberg (1)

Top Labels

Issue Labels

Pull Request Labels

bug (1) enhancement (1) dependencies (1)

Packages

Total packages: 1
Total downloads:
- pypi 334 last-month

Total dependent packages: 0
Total dependent repositories: 1
Total versions: 26
Total maintainers: 1

pypi.org: rigolwfm

Read and parse Rigol Oscilloscope WFM files

Homepage: https://github.com/scottprahl/RigolWFM.git
Documentation: https://rigolwfm.readthedocs.io/
License: BSD 3-clause
Latest release: 1.0.0
published over 2 years ago

Versions: 26
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 334 Last month

Rankings

Dependent packages count: 10.0%

Stargazers count: 10.2%

Forks count: 13.3%

Average: 14.0%

Downloads: 14.9%

Dependent repos count: 21.7%

Maintainers (1)

scott.prahl

Last synced: 6 months ago

Dependencies

docs/requirements.txt pypi

RigolWFM *
kaitaistruct *
matplotlib *
nbsphinx *
numpy *
sphinx-automodapi *
sphinx-rtd-theme *

requirements-dev.txt pypi

check-manifest * development
flake8 * development
kaitaistruct * development
ksylint * development
markupsafe ==2.0.1 development
matplotlib * development
nbconvert * development
nbformat * development
nbsphinx * development
numpy * development
pydocstyle * development
pylint * development
pyroma * development
pytest * development
rstcheck * development
sphinx-automodapi * development
sphinx-rtd-theme * development
tox * development
yamllint * development

requirements.txt pypi

kaitaistruct *
matplotlib *
numpy *

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rigolwfm

Science Score: 46.0%

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README.rst

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