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ASAM MDF measurement data file parser

Project description

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

  • convert to different mdf version

  • export to Excel, HDF5 and CSV

  • 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

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)

Files used for benchmark:

  • 183 groups

  • 36424 channels

Open file

Time [ms]

RAM [MB]

asammdf 2.5.0 mdfv3

1009

289

asammdf 2.5.0 nodata mdfv3

663

118

mdfreader 0.2.5 mdfv3

3705

454

asammdf 2.5.0 mdfv4

2031

343

asammdf 2.5.0 nodata mdfv4

1690

161

mdfreader 0.2.5 mdfv4

42315

576

Save file

Time [ms]

RAM [MB]

asammdf 2.5.0 mdfv3

439

293

asammdf 2.5.0 nodata mdfv3

462

126

mdfreader 0.2.5 mdfv3

19759

1224

asammdf 2.5.0 mdfv4

691

354

asammdf 2.5.0 nodata mdfv4

712

174

mdfreader 0.2.5 mdfv4

17415

1686

Get all channels (36424 calls)

Time [ms]

RAM [MB]

asammdf 2.5.0 mdfv3

807

298

asammdf 2.5.0 nodata mdfv3

18500

132

mdfreader 0.2.5 mdfv3

36

454

asammdf 2.5.0 mdfv4

804

349

asammdf 2.5.0 nodata mdfv4

21315

171

mdfreader 0.2.5 mdfv4

49

577

Convert file

Time [ms]

RAM [MB]

asammdf 2.5.0 v3 to v4

5834

709

asammdf 2.5.0 v3 to v4 nodata

28427

494

asammdf 2.5.0 v4 to v3

5474

710

asammdf 2.5.0 v4 to v3 nodata

30423

638

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)

Files used for benchmark:

  • 183 groups

  • 36424 channels

Open file

Time [ms]

RAM [MB]

asammdf 2.5.0 mdfv3

821

371

asammdf 2.5.0 nodata mdfv3

653

191

mdfreader 0.2.5 mdfv3

2909

537

asammdf 2.5.0 mdfv4

1694

455

asammdf 2.5.0 nodata mdfv4

1297

260

mdfreader 0.2.5 mdfv4

31074

748

Save file

Time [ms]

RAM [MB]

asammdf 2.5.0 mdfv3

393

373

asammdf 2.5.0 nodata mdfv3

383

198

mdfreader 0.2.5 mdfv3

21464

1997

asammdf 2.5.0 mdfv4

586

465

asammdf 2.5.0 nodata mdfv4

550

275

mdfreader 0.2.5 mdfv4

19036

2795

Get all channels (36424 calls)

Time [ms]

RAM [MB]

asammdf 2.5.0 mdfv3

613

381

asammdf 2.5.0 nodata mdfv3

9161

207

mdfreader 0.2.5 mdfv3

28

536

asammdf 2.5.0 mdfv4

606

464

asammdf 2.5.0 nodata mdfv4

12403

275

mdfreader 0.2.5 mdfv4

40

748

Convert file

Time [ms]

RAM [MB]

asammdf 2.5.0 v3 to v4

4773

885

asammdf 2.5.0 v3 to v4 nodata

21903

605

asammdf 2.5.0 v4 to v3

4823

882

asammdf 2.5.0 v4 to v3 nodata

26090

740

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