irdl.get_sriracha

irdl.get_sriracha(scenario: str = 'SR1-D', dataset_split: str = None, path: str = PosixPath('/home/runner/.cache/irdl'), output_format: str = 'pyfar')

Download and extract the SRIRACHA database from DepositOnce.

DOI: 10.14279/depositonce-23943

Parameters:

scenariostr

Name of the scenario to download. One of 'SR1', 'SRA1', 'SR1-D', 'SRA1-D', 'SR2', 'SRA2', 'SR2-D', or 'SRA2-D'.

dataset_splitstr or None

Optional dataset split for full-plane scenarios. One of 'C1', 'C2', 'C3', 'C4', or None (default). Dense scenarios (ending in -D)do not have splits.

pathstr or pathlib.Path

Path to the directory where the data should be stored. Will be overwritten, if the environment variable IRDL_DATA_DIR is set. Default is the user cache directory.

output_formatstr

Output format of the returned data. Either 'pyfar' (default), 'hdf5', or 'numpy'.

Returns:

datadict or pathlib.Path

Returned data depends on output_format:

• 'pyfar': dict with keys 'impulse_response' (pyfar.Signal), 'source_coordinates' (pyfar.Coordinates), 'receiver_coordinates' (pyfar.Coordinates), and

• 'hdf5': pathlib.Path to the HDF5 file containing the data.

• 'numpy': dict with keys 'impulse_response' (numpy.ndarray), 'source_coordinates' (numpy.ndarray), 'receiver_coordinates' (numpy.ndarray), 'speed_of_sound' (numpy.ndarray), 'temperature' (numpy.ndarray), 'sampling_rate' (int), and optionally 'humidity' (numpy.ndarray).