asammdf 2.0.0.post1

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 eays 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

• append new channels

• convert to different mdf version

Major features still not implemented

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

• mdf 3 channel dependency functionality

• functionality related to trigger blocks (but the class is defined)

• handling of unfinnished measurements (mdf 4)

• compressed data blocks for mdf >= 4.10

• mdf 4 attachment blocks

• mdf 4 channel arrays

• mdf 4 VLSD channels and SDBLOCKs

• xml schema for TXBLOCK and MDBLOCK

Usage

Check the examples folder for extended usage demo.

Documentation

http://asammdf.readthedocs.io/en/2.0.0/

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 formula based channel conversions

• blosc : optionally used for in memmory raw channel data compression

• matplotlib : for Signal plotting

Benchmarks

3.6.1 (v3.6.1:69c0db5, Mar 21 2017, 18:41:36) [MSC v.1900 64 bit (AMD64)]

Windows-7-6.1.7601-SP1

Intel64 Family 6 Model 94 Stepping 3, GenuineIntel

16 installed RAM

• nodata = MDF object created with load_measured_data=False (raw channel data no loaded into RAM)

• compression = MDF object created with compression=True (raw channel data loaded into RAM and compressed)

• noconvert = MDF object created with convertAfterRead=False

Files used for benchmark:

• 183 groups

• 36424 channels

Open file	Time [ms]	RAM [MB]
asammdf 2.0.0 mdfv3	721	352
asammdf 2.0.0 compression mdfv3	1008	275
asammdf 2.0.0 nodata mdfv3	641	199
mdfreader 0.2.5 mdfv3	2996	526
mdfreader 0.2.5 no convert mdfv3	2846	393
asammdf 2.0.0 mdfv4	1634	439
asammdf 2.0.0 compression mdfv4	1917	343
asammdf 2.0.0 nodata mdfv4	1594	274
mdfreader 0.2.5 mdfv4	31023	739
mdfreader 0.2.5 noconvert mdfv4	30693	609

Save file	Time [ms]	RAM [MB]
asammdf 2.0.0 mdfv3	472	353
asammdf 2.0.0 compression mdfv3	667	275
mdfreader 0.2.5 mdfv3	18910	2003
asammdf 2.0.0 mdfv4	686	447
asammdf 2.0.0 compression mdfv4	836	352
mdfreader 0.2.5 mdfv4	16631	2802

Get all channels	Time [ms]	RAM [MB]
asammdf 2.0.0 mdfv3	2492	362
asammdf 2.0.0 compression mdfv3	14474	285
asammdf 2.0.0 nodata mdfv3	9621	215
mdfreader 0.2.5 mdfv3	31	526
asammdf 2.0.0 mdfv4	2066	450
asammdf 2.0.0 compression mdfv4	16944	359
asammdf 2.0.0 nodata mdfv4	12364	292
mdfreader 0.2.5 mdfv4	39	739