*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
# Status
| Continuous Integration | Coveralls | Codacy | ReadTheDocs |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| [](https://github.com/danielhrisca/asammdf/actions/workflows/main.yml) | [](https://coveralls.io/github/danielhrisca/asammdf?branch=master) | [](https://www.codacy.com/app/danielhrisca/asammdf?utm_source=github.com&utm_medium=referral&utm_content=danielhrisca/asammdf&utm_campaign=badger) | [](http://asammdf.readthedocs.io/en/master/?badge=stable) |
| PyPI | conda-forge |
| ----------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| [](https://badge.fury.io/py/asammdf) | [](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)
## Contributors
Thanks to all who contributed with commits to *asammdf*:
# 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
%package -n python3-asammdf
Summary: ASAM MDF measurement data file parser
Provides: python-asammdf
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
BuildRequires: python3-cffi
BuildRequires: gcc
BuildRequires: gdb
%description -n python3-asammdf
*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
# Status
| Continuous Integration | Coveralls | Codacy | ReadTheDocs |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| [](https://github.com/danielhrisca/asammdf/actions/workflows/main.yml) | [](https://coveralls.io/github/danielhrisca/asammdf?branch=master) | [](https://www.codacy.com/app/danielhrisca/asammdf?utm_source=github.com&utm_medium=referral&utm_content=danielhrisca/asammdf&utm_campaign=badger) | [](http://asammdf.readthedocs.io/en/master/?badge=stable) |
| PyPI | conda-forge |
| ----------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| [](https://badge.fury.io/py/asammdf) | [](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)
## Contributors
Thanks to all who contributed with commits to *asammdf*:
# 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
%package help
Summary: Development documents and examples for asammdf
Provides: python3-asammdf-doc
%description help
*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
# Status
| Continuous Integration | Coveralls | Codacy | ReadTheDocs |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| [](https://github.com/danielhrisca/asammdf/actions/workflows/main.yml) | [](https://coveralls.io/github/danielhrisca/asammdf?branch=master) | [](https://www.codacy.com/app/danielhrisca/asammdf?utm_source=github.com&utm_medium=referral&utm_content=danielhrisca/asammdf&utm_campaign=badger) | [](http://asammdf.readthedocs.io/en/master/?badge=stable) |
| PyPI | conda-forge |
| ----------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| [](https://badge.fury.io/py/asammdf) | [](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)
## Contributors
Thanks to all who contributed with commits to *asammdf*:
# 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
%prep
%autosetup -n asammdf-7.3.12
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-asammdf -f filelist.lst
%dir %{python3_sitearch}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Apr 11 2023 Python_Bot - 7.3.12-1
- Package Spec generated