asammdf 3.4.3

ASAM MDF measurement data file parser

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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)

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Status

	Travis CI	Coverage	Codacy	ReadTheDocs
master
development

PyPI	conda-forge

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 (concatenate) 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 files, 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/master/examples.html

Documentation

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

Contributing

Please have a look over the [contributing guidelines](https://github.com/danielhrisca/asammdf/blob/master/CONTRIBUTING.md)

Contributors

Thanks to all who contributed with commits to asammdf: * Julien Grave JulienGrv. * Jed Frey jed-frey. * Mihai yahym. * Jack Weinstein jacklev. * Isuru Fernando isuruf. * Felix Kohlgrüber fkohlgrueber.

Installation

asammdf is available on

• github: https://github.com/danielhrisca/asammdf/

• PyPI: https://pypi.org/project/asammdf/

• conda-forge: https://anaconda.org/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

Graphical results can be seen here at http://asammdf.readthedocs.io/en/master/benchmarks.html

Python 3 x64

Benchmark environment

• 3.6.4 (default, Jan 5 2018, 02:35:40) [GCC 7.2.1 20171224]

• Linux-4.15.0-1-MANJARO-x86_64-with-arch-Manjaro-Linux

• 4GB installed RAM

Notations used in the results

• full = asammdf MDF object created with memory=full (everything loaded into RAM)

• low = asammdf MDF object created with memory=low (raw channel data not loaded into RAM, but metadata loaded to RAM)

• minimum = asammdf MDF object created with memory=full (lowest possible RAM usage)

• compress = mdfreader mdf object created with compression=blosc

• noDataLoading = mdfreader mdf object read with noDataLoading=True

Files used for benchmark:

• 183 groups

• 36424 channels

Open file	Time [ms]	RAM [MB]
asammdf 3.0.0 full mdfv3	706	256
asammdf 3.0.0 low mdfv3	637	103
asammdf 3.0.0 minimum mdfv3	612	64
mdfreader 2.7.5 mdfv3	2201	414
mdfreader 2.7.5 compress mdfv3	1871	281
mdfreader 2.7.5 noDataLoading mdfv3	948	160
asammdf 3.0.0 full mdfv4	2599	296
asammdf 3.0.0 low mdfv4	2485	131
asammdf 3.0.0 minimum mdfv4	1376	64
mdfreader 2.7.5 mdfv4	5706	435
mdfreader 2.7.5 compress mdfv4	5453	303
mdfreader 2.7.5 noDataLoading mdfv4	3904	181

Save file	Time [ms]	RAM [MB]
asammdf 3.0.0 full mdfv3	468	258
asammdf 3.0.0 low mdfv3	363	110
asammdf 3.0.0 minimum mdfv3	919	80
mdfreader 2.7.5 mdfv3	6424	451
mdfreader 2.7.5 noDataLoading mdfv3	7364	510
mdfreader 2.7.5 compress mdfv3	6624	449
asammdf 3.0.0 full mdfv4	984	319
asammdf 3.0.0 low mdfv4	1028	156
asammdf 3.0.0 minimum mdfv4	2786	80
mdfreader 2.7.5 mdfv4	3355	460
mdfreader 2.7.5 noDataLoading mdfv4	5153	483
mdfreader 2.7.5 compress mdfv4	3773	457

Get all channels (36424 calls)	Time [ms]	RAM [MB]
asammdf 3.0.0 full mdfv3	1196	269
asammdf 3.0.0 low mdfv3	5230	121
asammdf 3.0.0 minimum mdfv3	6871	85
mdfreader 2.7.5 mdfv3	77	414
mdfreader 2.7.5 noDataLoading mdfv3	13036	195
mdfreader 2.7.5 compress mdfv3	184	281
asammdf 3.0.0 full mdfv4	1207	305
asammdf 3.0.0 low mdfv4	5613	144
asammdf 3.0.0 minimum mdfv4	7725	80
mdfreader 2.7.5 mdfv4	74	435
mdfreader 2.7.5 noDataLoading mdfv4	14140	207
mdfreader 2.7.5 compress mdfv4	171	307

Convert file	Time [ms]	RAM [MB]
asammdf 3.0.0 full v3 to v4	3712	565
asammdf 3.0.0 low v3 to v4	4091	228
asammdf 3.0.0 minimum v3 to v4	6740	126
asammdf 3.0.0 full v4 to v3	3787	571
asammdf 3.0.0 low v4 to v3	4546	222
asammdf 3.0.0 minimum v4 to v3	8369	115

Merge files	Time [ms]	RAM [MB]
asammdf 3.0.0 full v3	7297	975
asammdf 3.0.0 low v3	7766	282
asammdf 3.0.0 minimum v3	11363	163
mdfreader 2.7.5 mdfv3	13039	1301
mdfreader 2.7.5 compress mdfv3	12877	1298
mdfreader 2.7.5 noDataLoading mdfv3	12981	1421
asammdf 3.0.0 full v4	11313	1025
asammdf 3.0.0 low v4	12155	322
asammdf 3.0.0 minimum v4	18787	152
mdfreader 2.7.5 mdfv4	21423	1309
mdfreader 2.7.5 noDataLoading mdfv4	20142	1352
mdfreader 2.7.5 compress mdfv4	20600	1309