Welcome to asammdf’s documentation!¶
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¶
create new mdf files from scratch
append new channels
read unsorted MDF v3 and v4 files
filter a subset of channels from original mdf file
cut measurement to specified time interval
convert to different mdf version
export to Excel, HDF5, Matlab and CSV
merge multiple files sharing the same internal structure
read and save mdf version 4.10 files containing zipped data blocks
split large data blocks (configurable size) for mdf version 4
disk space savings by compacting 1-dimensional integer channels (configurable)
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
files are loaded in RAM for fast operations
handle large files (exceeding the available RAM) using load_measured_data = False argument
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 measurement will 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 (but the class is defined)
for version 4
- handling of bus logging measurements
- handling of unfinnished measurements (mdf 4)
- full support for remaining mdf 4 channel arrays types
- xml schema for TXBLOCK and MDBLOCK
- partial conversions
- event blocks
Dependencies¶
asammdf uses the following libraries
- numpy : the heart that makes all tick
- numexpr : for algebraic and rational channel conversions
- matplotlib : for Signal plotting
- wheel : for installation in virtual environments
optional dependencies needed for exports
- pandas : for DataFrame export
- h5py : for HDF5 export
- xlsxwriter : for Excel export
- scipy : for Matlab .mat export
Benchmarks¶
asammdf relies heavily on dict objects. Starting with Python 3.6 the dict objects are more compact and ordered (implementation detail); asammdf uses takes advantage of those changes so for best performance it is advised to use Python >= 3.6.