Skip to main content

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

    • 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

  • export to Excel, HDF5 and CSV

  • 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 append (reading and saving file with CDBLOCKs 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/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

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 = 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

Project details


Release history Release notifications | RSS feed

This version

2.4.2

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

asammdf-2.4.2.tar.gz (95.0 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page