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asammdf-7.3.9


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توضیحات

ASAM MDF measurement data file parser
ویژگی مقدار
سیستم عامل -
نام فایل asammdf-7.3.9
نام asammdf
نسخه کتابخانه 7.3.9
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Daniel Hrisca
ایمیل نویسنده daniel.hrisca@gmail.com
آدرس صفحه اصلی https://github.com/danielhrisca/asammdf
آدرس اینترنتی https://pypi.org/project/asammdf/
مجوز LGPLv3+
<img align=left src="https://raw.githubusercontent.com/danielhrisca/asammdf/master/asammdf.png" width="128" height="128" /> <p align=center> *asammdf* is a fast parser and editor for ASAM (Association for Standardization 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 >= 3.8 </p> <img align=left src="https://raw.githubusercontent.com/danielhrisca/asammdf/master/gui.png"/> # Status | Continuous Integration | Coveralls | Codacy | ReadTheDocs | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------- | | [![continuous integration](https://github.com/danielhrisca/asammdf/actions/workflows/main.yml/badge.svg?branch=master)](https://github.com/danielhrisca/asammdf/actions/workflows/main.yml) | [![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 and LIN bus logging files * extract CAN and LIN signals from anonymous 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 (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 * experimental support for MDF v4.20 column oriented storage * 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 and LIN bus logging are implemented with the ability to *get* signals defined in the attached CAN/LIN database (.arxml or .dbc). Signals can also be extracted from an anonymous bus logging measurement by providing a CAN or LIN database (.dbc or .arxml) * handling of unfinished measurements (mdf 4): finalization is attempted when the file is loaded, however the not all the finalization steps are supported * 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 transferred 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 default X axis is ignored and the channel group's master channel is used * attachment encryption/decryption using user provided encryption/decryption functions; this is not part of the MDF v4 spec and is only supported by this library # 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 https://canlogger.csselectronics.com/canedge-getting-started/log-file-tools/asammdf-api/ # Documentation http://asammdf.readthedocs.io/en/master And a nicely written tutorial on the [CSS Electronics site](https://canlogger.csselectronics.com/canedge-getting-started/log-file-tools/asammdf-gui/) # 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://numfocus.org/donate-to-numpy) or to [danielhrisca using liberapay](https://liberapay.com/danielhrisca/donate) <noscript><a href="https://liberapay.com/danielhrisca/donate"><img alt="Donate using Liberapay" src="https://liberapay.com/assets/widgets/donate.svg"></a></noscript> ## Contributors Thanks to all who contributed with commits to *asammdf*: <a href="https://github.com/danielhrisca/asammdf/graphs/contributors"> <img src="https://contrib.rocks/image?repo=danielhrisca/asammdf" /> </a> # 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 # for the GUI pip install asammdf[gui] # or for anaconda conda install -c conda-forge asammdf ``` In case a wheel is not present for you OS/Python versions and you lack the proper compiler setup to compile the c-extension code, then you can simply copy-paste the package code to your site-packages. In this way the python fallback code will be used instead of the compiled c-extension code. # 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/LIN bus logging measurements * natsort * lxml : for canmatrix arxml support * lz4 : to speed up the disk IO performance * python-dateutil : measurement start time handling optional dependencies needed for exports * h5py : for HDF5 export * hdf5storage : for Matlab v7.3 .mat export * fastparquet : for parquet export * scipy: for Matlab v4 and v5 .mat export other optional dependencies * PySide6 : for GUI tool * pyqtgraph : for GUI tool and Signal plotting * matplotlib : as fallback for Signal plotting * cChardet : to detect non-standard Unicode encodings * chardet : to detect non-standard Unicode encodings * pyqtlet2 : for the GPS window * isal : for faster zlib compression/decompression * fsspec : access files stored in the cloud # Benchmarks http://asammdf.readthedocs.io/en/master/benchmarks.html


نیازمندی

مقدار نام
>=0.8 canmatrix[arxml,dbc]
- lz4
- numexpr
>=1.23.0 numpy
- pandas
- typing-extensions
- python-dateutil
- isal
==2.1.5 cChardet
- chardet
- cryptography
- keyring
- fastparquet
- h5py
>=0.1.17 hdf5storage
- python-snappy
- scipy
- fsspec
- lxml
- natsort
- psutil
- PySide6
>=0.12.4 pyqtgraph
>=0.8.0 pyqtlet2
- numexpr3


زبان مورد نیاز

مقدار نام
>=3.8 Python


نحوه نصب


نصب پکیج whl asammdf-7.3.9:

    pip install asammdf-7.3.9.whl


نصب پکیج tar.gz asammdf-7.3.9:

    pip install asammdf-7.3.9.tar.gz