A guided tour to get you started

Note

How to get data Data are stored (if not locally available to you) on the Hawaii nextcloud system

Data formats

GAPS employs a various number of data formats. There are

• .bin - (commonly called "binary" files (even though all GAPS data is stored in "binary" format)) - These files get written by the GSE system. These files contain everything sent to ground.

• tof.gaps - datafiles written by this library (gondola/liftof). These are used throughout the TOF system. This is a highly optimzied data format which allows to store the waveforms of the TOF system. This data will include monitoring data from the tof system.

• .gaps - datafiles written by this library, employing the caraspace system, which allows to merge the above .bin and .tof.gaps files in a very efficient way. This introduces a "vertical" merging, meaning that events with the same id from either of the streams will be stored together within a so-called "frame". For all GAPS rundata, .gaps files will be created as part of the data processing. Since these data are not calibrated, these are called "L0" data.

• .root - data with CERN's widely used "ROOT" library. These files typically

  contain reconstructed event data, where one or more of several different reconstruction algorithms are applied and are typically written throughout the SimpleDet library <https://uhhepvcs.phys.hawaii.edu/philipvd/SimpleDet>_.

How to read the data

For reading the L0 data, you can do the following

import gondola
# Set up a reader - For L0 data, we will need "CRReader"
reader = CRReader("/path/to/L0/data") # <- can be a single file
                                      # or a directory, it will
                                      # figure it out automatically

# The reader can count the number of frames in the files
# not every frame will correspond to event data, there is
# also monitoring
nframes = reader.count_frames()

# The reader acts as an iterator and can be looped over.
import tqdm # <- Just for the progressbar, can be omitted
for frame in tqdm.tqdm(reader, total=nframes):
    # the frame has an "index" showing the contents of the
    # frame. It is a dictionary string -> packet
    print (frame.index)
    # This allows to check if a frame contains a certain key
    if frame.has('TelemetryPacketType.NoGapsTriggerEvent'):
        ev = frame.get_telemetryevent() # no argument needed if this
                                          is unambiguous
        # if multiple events are in the frame, specify packet name
        ev = frame.get_telemetryevent('TelemetryPacketType.NoGapsTriggerEvent')
        ev.tof # <- packet TOF data for Telemetry
        ev.tracker # <- tracker hits

        ...