def test_spectrum():
freq = np.logspace(-2, 2, 101)
moment = spectrum.moment_from_magnitude(6.7)
mod = spectrum.model((moment, 150), freq, 10, kappa=0.035)
np.testing.assert_allclose(mod[0], 0.21764373, atol=1e-5)
np.testing.assert_allclose(mod[50], 113.5025146, atol=1e-5)
np.testing.assert_allclose(mod[-1], 0.0032295, atol=1e-5)
def snr_check(tr,
mag,
threshold=3.0,
min_freq='f0',
max_freq=5.0,
f0_options={
'stress_drop': 10,
'shear_vel': 3.7,
'ceiling': 2.0,
'floor': 0.1
}):
"""
Check signal-to-noise ratio.
Requires noise/singal windowing to have succeeded.
Args:
tr (StationTrace):
Trace of data.
threshold (float):
Threshold SNR value.
min_freq (float or str):
Minimum frequency for threshold to be exeeded. If 'f0', then the
Brune corner frequency will be used.
max_freq (float):
Maximum frequency for threshold to be exeeded.
bandwidth (float):
Konno-Omachi smoothing bandwidth parameter.
f0_options (dict):
Dictionary of f0 options (see config file).
Returns:
trace: Trace with SNR check.
"""
if tr.hasCached('snr'):
snr_dict = tr.getCached('snr')
snr = np.array(snr_dict['snr'])
freq = np.array(snr_dict['freq'])
# If min_freq is 'f0', then compute Brune corner frequency
if min_freq == 'f0':
min_freq = brune_f0(moment_from_magnitude(mag),
f0_options['stress_drop'],
f0_options['shear_vel'])
if min_freq < f0_options['floor']:
min_freq = f0_options['floor']
if min_freq > f0_options['ceiling']:
min_freq = f0_options['ceiling']
# Check if signal criteria is met
mask = (freq >= min_freq) & (freq <= max_freq)
if np.any(mask):
min_snr = np.min(snr[mask])
else:
min_snr = 0
if min_snr < threshold:
tr.fail('Failed SNR check; SNR less than threshold.')
snr_conf = {
'threshold': threshold,
'min_freq': min_freq,
'max_freq': max_freq
}
tr.setParameter('snr_conf', snr_conf)
return tr
def snr_check(
tr,
mag,
threshold=3.0,
min_freq="f0",
max_freq=5.0,
f0_options={
"stress_drop": 10,
"shear_vel": 3.7,
"ceiling": 2.0,
"floor": 0.1
},
):
"""
Check signal-to-noise ratio.
Requires noise/singal windowing to have succeeded.
Args:
tr (StationTrace):
Trace of data.
threshold (float):
Threshold SNR value.
min_freq (float or str):
Minimum frequency for threshold to be exeeded. If 'f0', then the
Brune corner frequency will be used.
max_freq (float):
Maximum frequency for threshold to be exeeded.
bandwidth (float):
Konno-Omachi smoothing bandwidth parameter.
f0_options (dict):
Dictionary of f0 options (see config file).
Returns:
trace: Trace with SNR check.
"""
if tr.hasCached("snr"):
snr_dict = tr.getCached("snr")
snr = np.array(snr_dict["snr"])
freq = np.array(snr_dict["freq"])
# If min_freq is 'f0', then compute Brune corner frequency
if min_freq == "f0":
min_freq = brune_f0(
moment_from_magnitude(mag),
f0_options["stress_drop"],
f0_options["shear_vel"],
)
if min_freq < f0_options["floor"]:
min_freq = f0_options["floor"]
if min_freq > f0_options["ceiling"]:
min_freq = f0_options["ceiling"]
# Check if signal criteria is met
mask = (freq >= min_freq) & (freq <= max_freq)
if np.any(mask):
min_snr = np.min(snr[mask])
else:
min_snr = 0
if min_snr < threshold:
tr.fail("Failed SNR check; SNR less than threshold.")
snr_conf = {
"threshold": threshold,
"min_freq": min_freq,
"max_freq": max_freq
}
tr.setParameter("snr_conf", snr_conf)
return tr