Skip to content

Fast Python reader and editor for ASAM MDF / MF4 (Measurement Data Format) files

License

Notifications You must be signed in to change notification settings

kasuteru/asammdf

 
 

Repository files navigation

asammdf is a fast parser and editor for ASAM (Associtation for Standardisation of Automation and Measuring Systems) MDF (Measurement Data Format) files.

asammdf supports MDF versions 2 (.dat), 3 (.mdf) and 4 (.mf4).

asammdf works on Python 2.7, and Python >= 3.4

asammdf was tested succesfully on both Linux and Windows

Status

! Travis CI Coverage Codacy ReadTheDocs
master Build Status Codacy Badge Codacy Badge Documentation Status
development Build Status Codacy Badge Codacy Badge Documentation Status
PyPI conda-forge
PyPI version conda-forge version

Project goals

The main goals for this library are:

  • to be faster than the other Python based mdf libraries
  • to have clean and easy to understand code base
  • to have minimal 3-rd party dependencies

Features

  • create new mdf files from scratch

  • append new channels

  • read unsorted MDF v3 and v4 files

  • read CAN bus logging files

  • filter a subset of channels from original mdf file

  • cut measurement to specified time interval

  • convert to different mdf version

  • export to pandas, Excel, HDF5, Matlab (v4, v5 and v7.3) and CSV

  • merge multiple files sharing the same internal structure

  • read and save mdf version 4.10 files containing zipped data blocks

  • space optimizations for saved files (no duplicated blocks)

  • split large data blocks (configurable size) for mdf version 4

  • full support (read, append, save) for the following map types (multidimensional array channels):

    • mdf version 3 channels with CDBLOCK

    • mdf version 4 structure channel composition

    • mdf version 4 channel arrays with CNTemplate storage and one of the array types:

      • 0 - array
      • 1 - scaling axis
      • 2 - look-up
  • add and extract attachments for mdf version 4

  • handle large files (for example merging two fileas, each with 14000 channels and 5GB size, on a RaspberryPi) using memory = minimum argument

  • extract channel data, master channel and extra channel information as Signal objects for unified operations with v3 and v4 files

  • time domain operation using the Signal class

    • Pandas data frames are good if all the channels have the same time based
    • a measurement will usually have channels from different sources at different rates
    • the Signal class facilitates operations with such channels
  • graphical interface to visualize channels and perform operations with the files

Major features not implemented (yet)

  • for version 3

    • functionality related to sample reduction block
  • for version 4

    • functionality related to sample reduction block
    • handling of channel hierarchy
    • full handling of bus logging measurements
    • handling of unfinished measurements (mdf 4)
    • full support for remaining mdf 4 channel arrays types
    • xml schema for MDBLOCK
    • full handling of event blocks
    • channels with default X axis
    • chanenls with reference to attachment

Usage

   from asammdf import MDF
   
   mdf = MDF('sample.mdf')
   speed = mdf.get('WheelSpeed')
   speed.plot()
   
   important_signals = ['WheelSpeed', 'VehicleSpeed', 'VehicleAcceleration']
   # get short measurement with a subset of channels from 10s to 12s 
   short = mdf.filter(important_signals).cut(start=10, stop=12)
   
   # convert to version 4.10 and save to disk
   short.convert('4.10').save('important signals.mf4')
   
   # plot some channels from a huge file
   efficient = MDF('huge.mf4', , memory='minimum')
   for signal in efficient.select(['Sensor1', 'Voltage3']):
       signal.plot()
   

Check the examples folder for extended usage demo, or the documentation http://asammdf.readthedocs.io/en/develoment/examples.html

Documentation

http://asammdf.readthedocs.io/en/develoment

Contributing

Please have a look over the contributing guidelines

Contributors

Thanks to all who contributed with commits to asammdf:

Installation

asammdf is available on

   pip install asammdf
   # or for anaconda
   conda install -c conda-forge asammdf 

Dependencies

asammdf uses the following libraries

  • numpy : the heart that makes all tick
  • numexpr : for algebraic and rational channel conversions
  • matplotlib : for Signal plotting
  • wheel : for installation in virtual environments
  • pandas : for DataFrame export
  • canmatrix : to handle CAN bus logging measurements

optional dependencies needed for exports

  • h5py : for HDF5 export
  • xlsxwriter : for Excel export
  • scipy : for Matlab v4 and v5 .mat export
  • hdf5storage : for Matlab v7.3 .mat export

other optional dependencies

  • chardet : to detect non-standard unicode encodings
  • PyQt4 or PyQt5 : for GUI tool
  • pyqtgraph : for GUI tool

Benchmarks

http://asammdf.readthedocs.io/en/develoment/benchmarks.html

About

Fast Python reader and editor for ASAM MDF / MF4 (Measurement Data Format) files

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 100.0%