Mattak is a Greenlandic meal consisting of whale skin and blubber. Blubber is a store of energy. That's close enough to data storage...
Mattak is (will eventually be) a multilingual package containing readers and helpers for RNO-G in C++, Python (via both uproot and PyROOT) and maybe even JS (via rootjs). Writers are provided in C++ ( and Python via PyROOT) These are all in the same package so that they can be kept in concert with each other.
The Python interface for mattak can be installed by running:
pip install git+https://github.com/RNO-G/mattak.gitIn order to use the (faster) PyROOT backend, you need a working installation of ROOT. If no ROOT installation can be found, only the uproot backend will be installed.
All data is assumed to reside in a directory named ${RNO_G_DATA}, which in the C++ and Python readers is often accessed via an environmental variable. This may be a mounted directory, or could be an http directory (assuming the HTTP server it resides on supports byte ranges).
The general schema for ``run-associated" data (i.e., data taken synchronously with a run) is:
${RNO_G_DATA}/station${STATION_NUMBER}/run${RUN_NUMER}/${PACKET_TYPE}.root Config files for each run live in:
${RNO_G_DATA}/station${STATION_NUMBER}/run${RUN_NUMBER}/cfg And any auxilliary files we might generate will be under:
${RNO_G_DATA}/station${STATION_NUMBER}/run${RUNNUMBER}/aux Note that this might result in a lot of files in a directory.
Run-associated. This is all metadata associated with a single event, not including waveforms. This is kept separated because some operations need only the metadata and also because we can transfer all metadata but only a portion of waveforms
These are all waveforms associated with each event.
Asynchronous DAQ-related data (e.g. thresholds, scalers, etc.) recorded every once in a while asynchronous to events but still as part of a run.
Eventually we might have sensor data, calibration data, GNSS data and who knows what else in the same file tree. That will be defined later...