------------ Introduction ------------ 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 ======== * 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 pandas, 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 files, 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 base * a measurement will usually have channels from different sources at different rates * the *Signal* class facilitates operations with such channels Major features not implemented (yet) ==================================== * for version 3 * functionality related to sample reduction block: the sample reduction blocks are simply ignored * for version 4 * functionality related to sample reduction block: the sample 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): 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 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 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 (preferably the latest develop branch code) * 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 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 .. code:: python pip install asammdf # 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. Contributing & Support ====================== Please have a look over the `contributing guidelines `_ If you enjoy this library please consider making a donation to the `numpy project `_ or to `danielhrisca using liberapay `_ Contributors ------------ Thanks to all who contributed with commits to *asammdf* ## Contributors Thanks to all who contributed with commits to *asammdf*: .. raw:: html