asammdf 2.3.2

ASAM MDF measurement data file parser

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

asammdf supports both MDF version 3 and 4 formats.

asammdf works on Python 2.7, and Python >= 3.4

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

Features

• read sorted and unsorted MDF v3 and v4 files

• files are loaded in RAM for fast operations

  • for low memory computers or for large data files there is the option to load only the metadata and leave the raw channel data (the samples) unread; this of course will mean slower channel data access speed

• 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 measuremetn will have channels from different sources at different rates

  • the Signal class facilitates operations with such channels

• remove data group by index or by specifing a channel name inside the target data group

• create new mdf files from scratch

• append new channels

• filter a subset of channels from original mdf file

• convert to different mdf version

• add and extract attachments

• mdf 4.10 zipped blocks

• mdf 4 structure channels

Major features still not implemented

• functionality related to sample reduction block (but the class is defined)

• mdf 3 channel dependency save and append (only reading is implemented)

• handling of unfinnished measurements (mdf 4)

• mdf 4 channel arrays

• xml schema for TXBLOCK and MDBLOCK

Usage

Check the examples folder for extended usage demo.

Documentation

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

Installation

asammdf is available on

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

• PyPI: https://pypi.org/project/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

• pandas : for DataFrame export

Benchmarks

Python 3 x86

Benchmark environment

• 3.6.1 (v3.6.1:69c0db5, Mar 21 2017, 17:54:52) [MSC v.1900 32 bit (Intel)]

• Windows-10-10.0.14393-SP0

• Intel64 Family 6 Model 94 Stepping 3, GenuineIntel

• 16GB installed RAM

Notations used in the results

• nodata = MDF object created with load_measured_data=False (raw channel data not loaded into RAM)

• compression = MDF object created with compression=True/blosc

• compression bcolz 6 = MDF object created with compression=6

• noDataLoading = MDF object read with noDataLoading=True

Files used for benchmark: * 183 groups * 36424 channels

Open file	Time [ms]	RAM [MB]
asammdf 2.3.2 mdfv3	980	288
asammdf 2.3.2 nodata mdfv3	670	118
mdfreader 0.2.5 mdfv3	3776	455
asammdf 2.3.2 mdfv4	2071	342
asammdf 2.3.2 nodata mdfv4	1610	160
mdfreader 0.2.5 mdfv4	43559	578

Save file	Time [ms]	RAM [MB]
asammdf 2.3.2 mdfv3	406	291
asammdf 2.3.2 nodata mdfv3	432	125
mdfreader 0.2.5 mdfv3	19623	1224
asammdf 2.3.2 mdfv4	691	351
asammdf 2.3.2 nodata mdfv4	734	169
mdfreader 0.2.5 mdfv4	17657	1687

Get all channels (36424 calls)	Time [ms]	RAM [MB]
asammdf 2.3.2 mdfv3	963	298
asammdf 2.3.2 nodata mdfv3	19059	132
mdfreader 0.2.5 mdfv3	34	455
asammdf 2.3.2 mdfv4	868	349
asammdf 2.3.2 nodata mdfv4	20434	171
mdfreader 0.2.5 mdfv4	54	578

Python 3 x64

Benchmark environment

• 3.6.2 (v3.6.2:5fd33b5, Jul 8 2017, 04:57:36) [MSC v.1900 64 bit (AMD64)]

• Windows-10-10.0.14393-SP0

• Intel64 Family 6 Model 94 Stepping 3, GenuineIntel

• 16GB installed RAM

Notations used in the results

• nodata = MDF object created with load_measured_data=False (raw channel data not loaded into RAM)

• compression = MDF object created with compression=blosc

• compression bcolz 6 = MDF object created with compression=6

• noDataLoading = MDF object read with noDataLoading=True

Files used for benchmark: * 183 groups * 36424 channels

Open file	Time [ms]	RAM [MB]
asammdf 2.3.2 mdfv3	831	371
asammdf 2.3.2 nodata mdfv3	609	190
mdfreader 0.2.5 mdfv3	3083	536
asammdf 2.3.2 mdfv4	1710	455
asammdf 2.3.2 nodata mdfv4	1349	260
mdfreader 0.2.5 mdfv4	30847	748

Save file	Time [ms]	RAM [MB]
asammdf 2.3.2 mdfv3	348	371
asammdf 2.3.2 nodata mdfv3	343	197
mdfreader 0.2.5 mdfv3	21244	1997
asammdf 2.3.2 mdfv4	530	462
asammdf 2.3.2 nodata mdfv4	522	272
mdfreader 0.2.5 mdfv4	19594	2795

Get all channels (36424 calls)	Time [ms]	RAM [MB]
asammdf 2.3.2 mdfv3	681	383
asammdf 2.3.2 nodata mdfv3	9175	209
mdfreader 0.2.5 mdfv3	29	537
asammdf 2.3.2 mdfv4	599	464
asammdf 2.3.2 nodata mdfv4	12191	273
mdfreader 0.2.5 mdfv4	38	748