*asammdf* is a fast parser and editor for ASAM (Associtation for Standardisation of Automation and Measuring Systems) MDF (Measurement Data Format) files. *asammdf* supports MDF versions 2 (.dat), 3 (.mdf) and 4 (.mf4). *asammdf* works on Python >= 3.6 (for Python 2.7, 3.4 and 3.5 see the 4.x.y releases)
# Status ! | Travis CI | Appveyor | CoverAlls | Codacy | ReadTheDocs --|--|--|--|--|-- master | [![Build Status](https://travis-ci.org/danielhrisca/asammdf.svg?branch=)](https://travis-ci.org/danielhrisca/asammdf) | [![Build status](https://ci.appveyor.com/api/projects/status/racx048r4cnwa2lg/branch/master?svg=true)](https://ci.appveyor.com/project/danielhrisca/asammdf/branch/master) | [![Coverage Status](https://coveralls.io/repos/github/danielhrisca/asammdf/badge.svg?branch=master)](https://coveralls.io/github/danielhrisca/asammdf?branch=master) | [![Codacy Badge](https://api.codacy.com/project/badge/Grade/a3da21da90ca43a5b72fc24b56880c99?branch=master)](https://www.codacy.com/app/danielhrisca/asammdf?utm_source=github.com&utm_medium=referral&utm_content=danielhrisca/asammdf&utm_campaign=badger) | [![Documentation Status](http://readthedocs.org/projects/asammdf/badge/?version=master)](http://asammdf.readthedocs.io/en/master/?badge=stable) | PyPI| conda-forge --|-- [![PyPI version](https://badge.fury.io/py/asammdf.svg)](https://badge.fury.io/py/asammdf) | [![conda-forge version](https://anaconda.org/conda-forge/asammdf/badges/version.svg)](https://anaconda.org/conda-forge/asammdf) # 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 * to have minimal 3-rd party dependencies # Features * create new mdf files from scratch * append new channels * read unsorted MDF v3 and v4 files * read CAN bus logging files * extract CAN signals from anonymous CAN bus logging measurements * filter a subset of channels from original mdf file * cut measurement to specified time interval * convert to different mdf version * export to HDF5, Matlab (v4, v5 and v7.3), CSV and parquet * merge multiple files sharing the same internal structure * read and save mdf version 4.10 files containing zipped data blocks * space optimizations for saved files (no duplicated blocks) * split large data blocks (configurable size) for mdf version 4 * full support (read, append, save) for the following map types (multidimensional array channels): * mdf version 3 channels with CDBLOCK * mdf version 4 structure channel composition * mdf version 4 channel arrays with CNTemplate storage and one of the array types: * 0 - array * 1 - scaling axis * 2 - look-up * add and extract attachments for mdf version 4 * handle large files (for example merging two fileas, each with 14000 channels and 5GB size, on a RaspberryPi) * 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 * a measurement will usually have channels from different sources at different rates * the *Signal* class facilitates operations with such channels * graphical interface to visualize channels and perform operations with the files # Major features not implemented (yet) * for version 3 * functionality related to sample reduction block: the samples reduction blocks are simply ignored * for version 4 * functionality related to sample reduction block: the samples reduction blocks are simply ignored * handling of channel hierarchy: channel hierarchy is ignored * full handling of bus logging measurements: currently only CAN bus logging is implemented with the ability to *get* signals defined in the attached CAN database (.arxml or .dbc). Signals can also be extracted from an anonymous CAN logging measurement by providing a CAN database (.dbc or .arxml) * handling of unfinished measurements (mdf 4): warnings are logged based on the unfinished status flags but no further steps are taken to sanitize the measurement * full support for remaining mdf 4 channel arrays types * xml schema for MDBLOCK: most metadata stored in the comment blocks will not be available * full handling of event blocks: events are transfered to the new files (in case of calling methods that return new *MDF* objects) but no new events can be created * channels with default X axis: the defaukt X axis is ignored and the channel group's master channel is used # Usage ```python from asammdf import MDF mdf = MDF('sample.mdf') speed = mdf.get('WheelSpeed') speed.plot() important_signals = ['WheelSpeed', 'VehicleSpeed', 'VehicleAcceleration'] # get short measurement with a subset of channels from 10s to 12s short = mdf.filter(important_signals).cut(start=10, stop=12) # convert to version 4.10 and save to disk short.convert('4.10').save('important signals.mf4') # plot some channels from a huge file efficient = MDF('huge.mf4') for signal in efficient.select(['Sensor1', 'Voltage3']): signal.plot() ``` Check the *examples* folder for extended usage demo, or the documentation http://asammdf.readthedocs.io/en/master/examples.html # Documentation http://asammdf.readthedocs.io/en/master # Contributing & Support Please have a look over the [contributing guidelines](CONTRIBUTING.md) If you enjoy this library please consider making a donation to the [numpy project](https://www.flipcause.com/secure/cause_pdetails/MzUwMQ==). ## Contributors Thanks to all who contributed with commits to *asammdf*: * Julien Grave [JulienGrv](https://github.com/JulienGrv) * Jed Frey [jed-frey](https://github.com/jed-frey) * Mihai [yahym](https://github.com/yahym) * Jack Weinstein [jackjweinstein](https://github.com/jackjweinstein) * Isuru Fernando [isuruf](https://github.com/isuruf) * Felix Kohlgrüber [fkohlgrueber](https://github.com/fkohlgrueber) * Stanislav Frolov [stanifrolov](https://github.com/stanifrolov) * Thomas Kastl [kasuteru](https://github.com/kasuteru) * venden [venden](https://github.com/venden) * Marat K. [kopytjuk](https://github.com/kopytjuk>) * freakatzz [freakatzz](https://github.com/freakatzz) # Installation *asammdf* is available on * github: https://github.com/danielhrisca/asammdf/ * PyPI: https://pypi.org/project/asammdf/ * conda-forge: https://anaconda.org/conda-forge/asammdf ```shell pip install asammdf # or for anaconda conda install -c conda-forge asammdf ``` To start development on your own GitHub: - [Forking a repository allows you to freely experiment with changes without affecting the original project.](https://help.github.com/en/articles/fork-a-repo) - Clone your repository and make changes. - [Create a pull request to propose and collaborate on changes to a repository.](https://help.github.com/en/articles/creating-a-pull-request) - [Sync a fork of a repository to keep it up-to-date with the upstream repository.](https://help.github.com/en/articles/syncing-a-fork) Programmatically: ``` export GITHUB_USER=example git clone git@github.com:${GITHUB_USER}/asammdf.git cd asammdf git remote add upstream https://github.com/danielhrisca/asammdf.git git fetch upstream git rebase upstream/master ``` # Dependencies asammdf uses the following libraries * numpy : the heart that makes all tick * numexpr : for algebraic and rational channel conversions * wheel : for installation in virtual environments * pandas : for DataFrame export * canmatrix : to handle CAN bus logging measurements * natsort * cChardet : to detect non-standard unicode encodings * lxml : for canmatrix arxml support optional dependencies needed for exports * h5py : for HDF5 export * scipy : for Matlab v4 and v5 .mat export * hdf5storage : for Matlab v7.3 .mat export * fastparquet : for parquet export other optional dependencies * PyQt5 : for GUI tool * pyqtgraph : for GUI tool and Signal plotting (preferably the latest develop branch code) * matplotlib : as fallback for Signal plotting # Benchmarks http://asammdf.readthedocs.io/en/master/benchmarks.html