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mdfr
ASAM mdf reader in rust Currently a personal project to learn rust from past experience with python (mdfreader). mdfr is currently able to be used from python interpreter (using pyO3) to read mdf 3.x and 4.x files. You can install it with 'pip install mdfr' command. Using rayon crate on many parts of the code allows to have faster parsing in a safe and easy way compared to python. To allow efficient data sharing with many other tools, mdfr stores the data using arrow2. Polars (pandas equivalent) use is therefore also straight forward. It can be used the following way with python interpreter: import mdfr # load file metadata in memory obj = mdfr.Mdf('path/to/file.mdf') # loads all data in memory obj.load_all_channels_data_in_memory() # loads a set of channels in memory, for instance in case there is not enough free memory or for performance obj.load_channels_data_in_memory({'Channel1', 'Channel2'}) # Returns the numpy array obj.get_channel_data('channel_name') # .get_channel_* methods to retrieve channel description, unit, related master name, type and data # .set_channel_* methods to modify channel description, unit, related master name, type and data # list of channels in file, or lists of channels grouped by master are available obj.get_master_channel_names_set() # To manipulate the file data (cut, resample, merge, etc.), it is possible to use polars: obj.get_polars_series('channel_name') # returns the a serie # to get complete dataframe including given channel: obj.get_polars_dataframe('channel_name') # add and remove channel obj.add_channel(channel_name, data, master_channel, master_type, master_flag, unit, description) # to plot a single channel with matplotlib: obj.plot('channel_name') # Export to parquet: obj.export_to_parquet('file_name', compression_option) # write to mdf4 file, compressed or not obj.write('file_name', conpression_flag)A C/C++ api is also available allowing to get list of channels, units, description and data using the Arrow CDataInterface. |
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