def remove_resp(self, trace, paz=None):
# removing response...
if paz:
# ...using paz:
if trace.stats.sampling_rate > 10.0:
# decimating large trace, else fft crashes
factor = int(np.ceil(trace.stats.sampling_rate / 10))
trace.decimate(factor=factor, no_filter=True)
trace.simulate(paz_remove=paz,
paz_simulate=obspy.signal.cornFreq2Paz(0.01),
remove_sensitivity=True,
simulate_sensitivity=True,
nfft_pow2=True)
else:
# ...using StationXML:
# first band-pass to downsample data before removing response
# (else remove_response() method is slow or even hangs)
trace.filter(type="bandpass",
freqmin=self.freqmin,
freqmax=self.freqmax,
corners=self.corners,
zerophase=self.zerophase)
psutils.resample(trace, dt_resample=self.period_resample)
trace.remove_response(output="VEL", zero_mean=True)
return trace
def time_norm(self, trace, trcopy):
# normalization of the signal by the running mean
# in the earthquake frequency band
trcopy.filter(type="bandpass",
freqmin=self.freqmin_earthquake,
freqmax=self.freqmax_earthquake,
corners=self.corners,
zerophase=self.zerophase)
# decimating trace
psutils.resample(trcopy, self.period_resample)
# Time-normalization weights from smoothed abs(data)
# Note that trace's data can be a masked array
halfwindow = int(round(self.window_time*trcopy.stats.sampling_rate/2))
mask = ~trcopy.data.mask if np.ma.isMA(trcopy.data) else None
tnorm_w = psutils.moving_avg(np.abs(trcopy.data),
halfwindow=halfwindow,
mask=mask)
if np.ma.isMA(trcopy.data):
# turning time-normalization weights into a masked array
s = "[warning: {}.{} trace's data is a masked array]"
print s.format(trace.stats.network, trace.stats.station),
tnorm_w = np.ma.masked_array(tnorm_w, trcopy.data.mask)
if np.any((tnorm_w == 0.0) | np.isnan(tnorm_w)):
# illegal normalizing value -> skipping trace
raise pserrors.CannotPreprocess("Zero or NaN normalisation \
weight")
# time-normalization
trace.data /= tnorm_w
return trace
def trace_downsample(self, trace):
# downsampling trace if not already done
if abs(1.0 / trace.stats.sampling_rate - self.period_resample) > EPS:
psutils.resample(trace, dt_resample=self.period_resample)
return trace
def remove_resp(self, trace, paz=None):
# removing response...
if paz:
# ...using paz:
if trace.stats.sampling_rate > 10.0:
# decimating large trace, else fft crashes
factor = int(np.ceil(trace.stats.sampling_rate / 10))
trace.decimate(factor=factor, no_filter=True)
trace.simulate(paz_remove=paz,
paz_simulate=obspy.signal.cornFreq2Paz(0.01),
remove_sensitivity=True,
simulate_sensitivity=True,
nfft_pow2=True)
else:
# ...using StationXML:
# first band-pass to downsample data before removing response
# (else remove_response() method is slow or even hangs)
trace.filter(type="bandpass",
freqmin=self.freqmin,
freqmax=self.freqmax,
corners=self.corners,
zerophase=self.zerophase)
psutils.resample(trace, dt_resample=self.period_resample)
trace.remove_response(output="VEL", zero_mean=True)
return trace
def time_norm(self, trace, trcopy):
# normalization of the signal by the running mean
# in the earthquake frequency band
trcopy.filter(type="bandpass",
freqmin=self.freqmin_earthquake,
freqmax=self.freqmax_earthquake,
corners=self.corners,
zerophase=self.zerophase)
# decimating trace
psutils.resample(trcopy, self.period_resample)
# Time-normalization weights from smoothed abs(data)
# Note that trace's data can be a masked array
halfwindow = int(
round(self.window_time * trcopy.stats.sampling_rate / 2))
mask = ~trcopy.data.mask if np.ma.isMA(trcopy.data) else None
tnorm_w = psutils.moving_avg(np.abs(trcopy.data),
halfwindow=halfwindow,
mask=mask)
if np.ma.isMA(trcopy.data):
# turning time-normalization weights into a masked array
s = "[warning: {}.{} trace's data is a masked array]"
print s.format(trace.stats.network, trace.stats.station),
tnorm_w = np.ma.masked_array(tnorm_w, trcopy.data.mask)
if np.any((tnorm_w == 0.0) | np.isnan(tnorm_w)):
# illegal normalizing value -> skipping trace
raise pserrors.CannotPreprocess("Zero or NaN normalisation \
weight")
# time-normalization
trace.data /= tnorm_w
return trace
def trace_downsample(self, trace):
# downsampling trace if not already done
if abs(1.0 / trace.stats.sampling_rate - self.period_resample) > EPS:
psutils.resample(trace, dt_resample=self.period_resample)
return trace