Make sure calculating Ml only from reliable onset times.
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14
autoPyLoT.py
14
autoPyLoT.py
@ -346,9 +346,10 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
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WAscaling[2]))
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WAscaling[2]))
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evt = local_mag.updated_event(magscaling)
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evt = local_mag.updated_event(magscaling)
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net_ml = local_mag.net_magnitude(magscaling)
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net_ml = local_mag.net_magnitude(magscaling)
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print("Network local magnitude: %4.1f" % net_ml.mag)
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if net_ml:
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print("Network local magnitude scaled with:")
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print("Network local magnitude: %4.1f" % net_ml.mag)
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print("%f * Ml + %f" % (magscaling[0], magscaling[1]))
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print("Network local magnitude scaled with:")
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print("%f * Ml + %f" % (magscaling[0], magscaling[1]))
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else:
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else:
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print("autoPyLoT: No NLLoc-location file available!")
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print("autoPyLoT: No NLLoc-location file available!")
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print("No source parameter estimation possible!")
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print("No source parameter estimation possible!")
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@ -421,9 +422,10 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
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WAscaling[2]))
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WAscaling[2]))
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evt = local_mag.updated_event(magscaling)
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evt = local_mag.updated_event(magscaling)
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net_ml = local_mag.net_magnitude(magscaling)
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net_ml = local_mag.net_magnitude(magscaling)
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print("Network local magnitude: %4.1f" % net_ml.mag)
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if net_ml:
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print("Network local magnitude scaled with:")
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print("Network local magnitude: %4.1f" % net_ml.mag)
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print("%f * Ml + %f" % (magscaling[0], magscaling[1]))
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print("Network local magnitude scaled with:")
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print("%f * Ml + %f" % (magscaling[0], magscaling[1]))
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else:
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else:
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print("autoPyLoT: No NLLoc-location file available! Stop iteration!")
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print("autoPyLoT: No NLLoc-location file available! Stop iteration!")
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locflag = 9
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locflag = 9
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@ -15,7 +15,7 @@ from pylot.core.pick.utils import getsignalwin, crossings_nonzero_all, \
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from pylot.core.util.utils import common_range, fit_curve
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from pylot.core.util.utils import common_range, fit_curve
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from scipy import integrate, signal
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from scipy import integrate, signal
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from scipy.optimize import curve_fit
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from scipy.optimize import curve_fit
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import pdb
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def richter_magnitude_scaling(delta):
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def richter_magnitude_scaling(delta):
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distance = np.array([0, 10, 20, 25, 30, 35, 40, 45, 50, 60, 70, 75, 85, 90, 100, 110,
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distance = np.array([0, 10, 20, 25, 30, 35, 40, 45, 50, 60, 70, 75, 85, 90, 100, 110,
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120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 230, 240, 250,
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120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 230, 240, 250,
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@ -266,6 +266,10 @@ class LocalMagnitude(Magnitude):
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for a in self.arrivals:
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for a in self.arrivals:
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if a.phase not in 'sS':
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if a.phase not in 'sS':
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continue
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continue
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# make sure calculating Ml only from reliable onsets
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# NLLoc: time_weight = 0 => do not use onset!
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if a.time_weight == 0:
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continue
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pick = a.pick_id.get_referred_object()
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pick = a.pick_id.get_referred_object()
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station = pick.waveform_id.station_code
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station = pick.waveform_id.station_code
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wf = select_for_phase(self.stream.select(
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wf = select_for_phase(self.stream.select(
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@ -365,7 +369,7 @@ class MomentMagnitude(Magnitude):
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if a.phase not in 'pP':
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if a.phase not in 'pP':
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continue
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continue
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# make sure calculating Mo only from reliable onsets
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# make sure calculating Mo only from reliable onsets
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# NLLOc: time_weight = 0 => do not use onset!
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# NLLoc: time_weight = 0 => do not use onset!
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if a.time_weight == 0:
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if a.time_weight == 0:
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continue
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continue
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pick = a.pick_id.get_referred_object()
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pick = a.pick_id.get_referred_object()
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