asammdf 2.5.2

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

• handle large files (exceeding the available RAM) using load_measured_data = False 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 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

• cut measurement to specified time interval

• convert to different mdf version

• export to Excel, HDF5 and CSV

• merge multiple files sharing the same internal structure

• add and extract attachments

• mdf 4.10 zipped blocks

• mdf 4 structure 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 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/latest

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

• wheel : for installation in virtual environments

optional dependencies needed for exports

• pandas : for DataFrame export

• h5py : for HDF5 export

• xlsxwriter : for Excel 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 = asammdf MDF object created with load_measured_data=False (raw channel data not loaded into RAM)

• compression = mdfreader mdf object created with compression=blosc

• compression bcolz 6 = mdfreader mdf object created with compression=6

• noDataLoading = mdfreader mdf object read with noDataLoading=True

Files used for benchmark:

• 183 groups

• 36424 channels

Open file	Time [ms]	RAM [MB]
asammdf 2.5.2 mdfv3	951	289
asammdf 2.5.2 nodata mdfv3	667	119
mdfreader 0.2.5 mdfv3	3628	454
asammdf 2.5.2 mdfv4	2142	343
asammdf 2.5.2 nodata mdfv4	1585	161
mdfreader 0.2.5 mdfv4	42997	577

Save file	Time [ms]	RAM [MB]
asammdf 2.5.2 mdfv3	530	293
asammdf 2.5.2 nodata mdfv3	457	126
mdfreader 0.2.5 mdfv3	19931	1225
asammdf 2.5.2 mdfv4	705	354
asammdf 2.5.2 nodata mdfv4	707	175
mdfreader 0.2.5 mdfv4	17803	1686

Get all channels (36424 calls)	Time [ms]	RAM [MB]
asammdf 2.5.2 mdfv3	865	298
asammdf 2.5.2 nodata mdfv3	18442	132
mdfreader 0.2.5 mdfv3	36	454
asammdf 2.5.2 mdfv4	803	349
asammdf 2.5.2 nodata mdfv4	20397	171
mdfreader 0.2.5 mdfv4	48	577

Convert file	Time [ms]	RAM [MB]
asammdf 2.5.2 v3 to v4	5824	690
asammdf 2.5.2 v3 to v4 nodata	28060	486
asammdf 2.5.2 v4 to v3	5591	710
asammdf 2.5.2 v4 to v3 nodata	30169	638

Merge files	Time [ms]	RAM [MB]
asammdf 2.5.2 v3	13152	1226
asammdf 2.5.2 v3 nodata	53144	348
asammdf 2.5.2 v4	15031	1296
asammdf 2.5.2 v4 nodata	60374	389

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

• compression = mdfreader mdf object created with compression=blosc

• compression bcolz 6 = mdfreader mdf object created with compression=6

• noDataLoading = mdfreader mdf object read with noDataLoading=True

Files used for benchmark:

• 183 groups

• 36424 channels

Open file	Time [ms]	RAM [MB]
asammdf 2.5.2 mdfv3	832	372
asammdf 2.5.2 nodata mdfv3	615	191
mdfreader 0.2.5 mdfv3	2876	537
asammdf 2.5.2 mdfv4	1690	455
asammdf 2.5.2 nodata mdfv4	1289	260
mdfreader 0.2.5 mdfv4	30755	748

Save file	Time [ms]	RAM [MB]
asammdf 2.5.2 mdfv3	393	373
asammdf 2.5.2 nodata mdfv3	452	198
mdfreader 0.2.5 mdfv3	21409	1997
asammdf 2.5.2 mdfv4	552	465
asammdf 2.5.2 nodata mdfv4	563	275
mdfreader 0.2.5 mdfv4	18899	2795

Get all channels (36424 calls)	Time [ms]	RAM [MB]
asammdf 2.5.2 mdfv3	633	381
asammdf 2.5.2 nodata mdfv3	8703	207
mdfreader 0.2.5 mdfv3	29	537
asammdf 2.5.2 mdfv4	633	464
asammdf 2.5.2 nodata mdfv4	12241	274
mdfreader 0.2.5 mdfv4	40	748

Convert file	Time [ms]	RAM [MB]
asammdf 2.5.2 v3 to v4	4504	856
asammdf 2.5.2 v3 to v4 nodata	21983	592
asammdf 2.5.2 v4 to v3	4731	883
asammdf 2.5.2 v4 to v3 nodata	26840	740

Merge files	Time [ms]	RAM [MB]
asammdf 2.5.2 v3	10572	1428
asammdf 2.5.2 v3 nodata	31014	519
asammdf 2.5.2 v4	12852	1558
asammdf 2.5.2 v4 nodata	41054	610