asammdf is a fast parser/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 (Travis CI tests done with Python 2.7 and Python >= 3.5)

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
filter a subset of channels from original mdf file
cut measurement to specified time interval
convert to different mdf version
export to Excel, HDF5, Matlab and CSV
merge multiple files sharing the same internal structure
read and save mdf version 4.10 files containing zipped data blocks
split large data blocks (configurable size) for mdf version 4
disk space savings by compacting 1-dimensional integer channels (configurable)
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
files are loaded in RAM for fast operations
handle large files (exceeding the available RAM) 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
- usually a measurement will have channels from different sources at different rates
- the Signal class facilitates operations with such channels

Major features not implemented (yet)

for version 3
- functionality related to sample reduction block (but the class is defined)
for version 4
- handling of bus logging measurements
- handling of unfinished measurements (mdf 4)
- xml schema for TXBLOCK and MDBLOCK
- full support for remaining mdf 4 channel arrays types
- partial conversions
- event blocks
- channels with default X axis
- channels 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/master/examples.html

Documentation

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

Installation

asammdf is available on

github: https://github.com/danielhrisca/asammdf/
PyPI: https://pypi.org/project/asammdf/

   pip install 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

optional dependencies needed for exports

h5py : for HDF5 export
xlsxwriter : for Excel export
scipy : for Matlab .mat export

Benchmarks

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

jackjweinstein / asammdf