def test_get_acoustic_data():
# 1. case: 100% data coverage
start_time = datetime.datetime(2017,3,10,0,0,0)
end_time = datetime.datetime(2017,3,10,0,5,0)
node = 'PC01A'
data = hyd_request.get_acoustic_data(start_time, end_time, node)
assert type(data) == HydrophoneData
assert type(data.data) == np.ndarray
diff_start = abs((start_time - data.stats.starttime.datetime).microseconds)
diff_end = abs((end_time - data.stats.endtime.datetime).microseconds)
assert diff_start <= 100
assert diff_end <= 100
# 2. case: 0% data coverage
start_time = datetime.datetime(2017,10,10,15,30,0)
end_time = datetime.datetime(2017,10,10,15,35,0)
node = 'LJ01C'
data = hyd_request.get_acoustic_data(start_time, end_time, node, append=False)
assert data is None
# 3. case: partial data coverage (data available until 15:17:50)
start_time = datetime.datetime(2017,10,10,15,15,0)
end_time = datetime.datetime(2017,10,10,15,20,0)
node = 'LJ01C'
data = hyd_request.get_acoustic_data(start_time, end_time, node, append=False)
assert type(data) == HydrophoneData
assert type(data.data) == np.ndarray
diff_start = abs((start_time - data.stats.starttime.datetime).microseconds)
diff_end = abs((end_time - data.stats.endtime.datetime).microseconds)
assert diff_start <= 100
assert diff_end > 100
# 4. case: 0% data coverage for entire day (directory does not exists)
start_time = datetime.datetime(2019,11,1,0,0,0)
end_time = datetime.datetime(2019,11,1,0,5,0)
node = 'LJ01D'
data = hyd_request.get_acoustic_data(start_time, end_time, node, append=False)
assert data is None
def test_hydrophone_node_names():
node_arr = ['Oregon_Shelf_Base_Seafloor', 'Oregon_Slope_Base_Seafloor',
'Oregon_Slope_Base_Shallow', 'Axial_Base_Shallow',
'Oregon_Offshore_Base_Seafloor', 'Axial_Base_Seafloor']
node_id_arr = ['LJ01D', 'LJ01A', 'PC01A', 'PC03A', 'LJ01C', 'LJ03A']
starttime = datetime.datetime(2017,3,20,0,0,0) # time of first sample
endtime = datetime.datetime(2017,3,20,0,0,1) # time of last sample
for item in node_arr:
hyd_data = hyd_request.get_acoustic_data(starttime, endtime, node=item)
assert hyd_data.stats.location in node_id_arr
node_arr = ['Slope_Base', 'Southern_Hydrate', 'Axial_Base',
'Central_Caldera', 'Eastern_Caldera']
node_id_arr = ['HYSB1', 'HYS14', 'AXBA1', 'AXCC1', 'AXEC2']
for item in node_arr:
hyd_data = hyd_request.get_acoustic_data_LF(starttime, endtime, node=item)
assert hyd_data.stats.location in node_id_arr
# TODO: need to figure out how to do the OOI authentification on the GitHub VM
#def test_get_ctd_data():
# start = datetime.datetime(2016, 12, 17, 2, 0, 0)
# end = datetime.datetime(2016, 12, 17, 3, 0, 0)
# ctd_data = ctd_request.get_ctd_data(start, end, 'oregon_offshore', limit=120)
#
# assert type(ctd_data) == HydrophoneData
# assert len(ctd_data.raw_data) > 0
def test_hydrophone_node_names():
node_arr = [
"Oregon_Shelf_Base_Seafloor",
"Oregon_Slope_Base_Seafloor",
"Oregon_Slope_Base_Shallow",
"Axial_Base_Shallow",
"Oregon_Offshore_Base_Seafloor",
"Axial_Base_Seafloor",
]
node_id_arr = ["LJ01D", "LJ01A", "PC01A", "PC03A", "LJ01C", "LJ03A"]
starttime = datetime.datetime(2017, 3, 20, 0, 0, 0) # time of first sample
endtime = datetime.datetime(2017, 3, 20, 0, 0, 1) # time of last sample
for item in node_arr:
hyd_data = hyd_request.get_acoustic_data(starttime, endtime, node=item)
assert hyd_data.stats.location in node_id_arr
node_arr = [
"Slope_Base",
"Southern_Hydrate",
"Axial_Base",
"Central_Caldera",
"Eastern_Caldera",
]
node_id_arr = ["HYSB1", "HYS14", "AXBA1", "AXCC1", "AXEC2"]
for item in node_arr:
hyd_data = hyd_request.get_acoustic_data_LF(starttime, endtime, node=item)
assert hyd_data.stats.location in node_id_arr
def save_ooi_spectrograms(
start_time,
end_time,
segment_length=datetime.timedelta(minutes=5),
node="PC01A",
output_dir="spectrograms",
nfft=256,
):
"""
Creates spectrograms for each time segment in the specified time range.
Args:
`start_time`: `datetime.datetime`
`end_time`: `datetime.datetime`
`segment_length`: `datetime.timedelta`
`node`: One of the preset OOI nodes.
`output_dir`: Path to the output directory.
`nfft`: The number of data points used in each block for the FFT. A power 2 is most efficient.
Returns:
None
"""
while start_time < end_time:
segment_end = min(start_time + segment_length, end_time)
hydrophone_data = hydrophone_request.get_acoustic_data(start_time,
segment_end,
node,
verbose=True)
if hydrophone_data is None:
logging.info(
f"Could not get data from {start_time} to {segment_end}")
start_time = segment_end
continue
datestr = start_time.strftime("%Y-%m-%dT%H-%M-%S-%f")[:-3]
wav_name = f"{datestr}.wav"
hydrophone_data.wav_write(wav_name)
spec_fname = create_spec_name(wav_name, output_dir)
save_spectrogram(wav_name, spec_fname, nfft)
os.remove(wav_name)
start_time = segment_end