def clip_signals(self):
max_time = max(self.time)
min_time = min(self.time)
if (max_time - min_time) < self.area_around_echo_size:
interval = range(np.searchsorted(self.time, min_time), np.searchsorted(self.time, max_time))
elif self.echo_time - self.area_around_echo_size/2 < min_time:
interval = range(np.searchsorted(self.time, min_time), int(np.searchsorted(self.time, min_time + self.area_around_echo_size)))
elif self.echo_time + self.area_around_echo_size/2 > max_time:
interval = range(int(np.searchsorted(self.time, (max_time - self.area_around_echo_size))), np.searchsorted(self.time, max_time))
else:
interval = range(int(np.searchsorted(self.time, self.echo_time - (self.area_around_echo_size/2))), int(np.searchsorted(self.time, self.echo_time + (self.area_around_echo_size/2))))
self.interval_near_echo = interval
self.time = self.time[interval]
self.signal = self.signal[interval]
self.seis = self.seis[interval]
self.phono = self.phono[interval]
self.signal = hb.bandpass_filter(time = self.time,
signal = self.signal,
freqmin = 59,
freqmax = 61)
self.seis = hb.bandpass_filter(time = self.time,
signal = self.seis,
freqmin = 59,
freqmax = 61)
self.phono = hb.bandpass_filter(time = self.time,
signal = self.phono,
freqmin = 59,
freqmax = 61)
self.signal = hb.lowpass_filter(time = self.time,
signal = self.signal,
cutoff_freq = 10)
self.seis = hb.lowpass_filter(time = self.time,
signal = self.seis,
cutoff_freq = 50)
# # if interval_number != sample_interval:
# # continue
# if interval_number != 1:
# continue
print("Interval: ", interval_number)
# Load Data
time, signal, seis1, seis2, phono1, phono2 = hb.load_file_data( files, folder_name,
dosage, file_number,
interval_number, preloaded_signal,
save_signal)
# Calculate Composite
lowpass_signal = hb.bandpass_filter(time = time,
signal = signal,
freqmin = 59,
freqmax = 61)
# Low-Pass filter under 10Hz
lowpass_signal = hb.lowpass_filter(time = time,
signal = lowpass_signal,
cutoff_freq = 50)
peaks = hb.get_peaks_for_composites(time = time,
signal = lowpass_signal,
dosage = dosage,
seis1 = seis1,
phono1 = phono1)
peaks.get_inital_statistics()
# hb.get_spectrum(time = time,
# signal = signal)
# Bandblock
if show_bandpass == True:
bandpass_signal = hb.lowpass_filter(time=time,
signal=signal,
cutoff_freq=10)
hb.get_fft(time=time, signal=bandpass_signal, plot=True)
# View Derivatives
if show_derivatives == True:
bandpass_signal = hb.bandpass_filter(time=time,
signal=signal,
freqmin=59,
freqmax=61)
hb.get_derivatives(signal=bandpass_signal, plot=True)
# Find Peaks
if show_peaks:
# Bandpass out 60 Hz
filtered_signal = hb.bandpass_filter(time=time,
signal=signal,
freqmin=59,
freqmax=61)
filtered_seis2 = hb.bandpass_filter(time=time,
signal=seis2,
freqmin=59,