*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 >= 3.6 (for Python 2.7, 3.4 and 3.5 see the 4.x.y releases)
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The main goals for this library are:
create new mdf files from scratch
append new channels
read unsorted MDF v3 and v4 files
read CAN bus logging files
extract CAN signals from anonymous CAN bus logging measurements
filter a subset of channels from original mdf file
cut measurement to specified time interval
convert to different mdf version
export to HDF5, Matlab (v4, v5 and v7.3), CSV and parquet
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 4 channel arrays with CNTemplate storage and one of the array types:
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)
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
for version 3
for version 4
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')
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
https://canlogger.csselectronics.com/canedge-getting-started/log-file-tools/asammdf-api/
http://asammdf.readthedocs.io/en/master
And a nicely written tutorial on the CSS Electronics site
Please have a look over the contributing guidelines
If you enjoy this library please consider making a donation to the numpy project.
Thanks to all who contributed with commits to asammdf:
asammdf is available on
pip install asammdf
# for the GUI
pip install asammdf[gui]
# or for anaconda
conda install -c conda-forge asammdfasammdf uses the following libraries
optional dependencies needed for exports
other optional dependencies