def atest__time_to_freq(self):
originalFreq, originalSignalFreq = time_to_freq(
originalTime, originalSignalTime, delta_time)
amplitudeSignalFreq = np.abs(originalSignalFreq)
for i in xrange(len(amplitudeSignalFreq)):
if amplitudeSignalFreq[i] > 1000: #spike detected
# check 1st signal
print('\nChecking 1st freq: %f' % f1)
if 0 < originalFreq[i] and originalFreq[i] < f2 / 2:
print('Current Freq Detected at 1st spike: %f' %
originalFreq[i])
self.assertTrue(f1 - 5 * delta_freq < originalFreq[i])
self.assertTrue(originalFreq[i] < (f1 + 5 * delta_freq))
# check 2nd signal
print('\nChecking 2nd freq: %f' % f2)
if f2 / 2 < originalFreq[i] and originalFreq[i] < f3 / 2:
print('Current Freq Detected at 2nd spike: %f' %
originalFreq[i])
self.assertTrue(f2 - 5 * delta_freq < originalFreq[i])
self.assertTrue(originalFreq[i] < (f2 + 5 * delta_freq))
# check 3rd signal
print('\nChecking 3rd freq: %f' % f3)
if 0.75 * f3 < originalFreq[i]:
print('Current Freq Detected at 3rd spike: %f' %
originalFreq[i])
self.assertTrue(f3 - 5 * delta_freq < originalFreq[i])
self.assertTrue(originalFreq[i] < (f3 + 5 * delta_freq))
def atest__filtering_time_freq(self):
filterType = 'bandpass'
lowFreq = 1.0
highFreq = 1.5
order = 2
originalFreq, originalSignalFreq = time_to_freq(
originalTime, originalSignalTime, delta_time)
filteredSignalTime, filteredSignalFreq, adjusted_w, adjusted_h = filtering_time_freq(
originalTime, originalSignalTime, delta_time, filterType, highFreq,
lowFreq, order)
filteredAmplitudeFreq = np.abs(filteredSignalFreq)
for i in xrange(len(filteredAmplitudeFreq)):
if filteredAmplitudeFreq[i] > 1000: #spike detected
if 0 < originalFreq[i]:
print('LOL %r' % originalFreq[i])
# only 3rd freq detected
self.assertTrue(f3 - delta_freq < originalFreq[i])
self.assertTrue(originalFreq[i] < f3 + delta_freq)
# NOT 1st freq
self.assertFalse(originalFreq[i] < f1 + 5 * delta_freq)
# NOT 2nd freq
self.assertFalse(originalFreq[i] < f2 + 5 * delta_freq)
def atest__time_to_freq(self):
originalFreq, originalSignalFreq = time_to_freq(originalTime, originalSignalTime, delta_time)
amplitudeSignalFreq = np.abs(originalSignalFreq)
for i in xrange(len(amplitudeSignalFreq)):
if amplitudeSignalFreq[i] > 1000: #spike detected
# check 1st signal
print('\nChecking 1st freq: %f' % f1)
if 0 < originalFreq[i] and originalFreq[i] < f2/2:
print('Current Freq Detected at 1st spike: %f' % originalFreq[i])
self.assertTrue(f1-5*delta_freq<originalFreq[i])
self.assertTrue(originalFreq[i]<(f1+5*delta_freq))
# check 2nd signal
print('\nChecking 2nd freq: %f' % f2)
if f2/2 < originalFreq[i] and originalFreq[i] < f3/2:
print('Current Freq Detected at 2nd spike: %f' % originalFreq[i])
self.assertTrue(f2-5*delta_freq<originalFreq[i])
self.assertTrue(originalFreq[i]<(f2+5*delta_freq))
# check 3rd signal
print('\nChecking 3rd freq: %f' % f3)
if 0.75*f3 < originalFreq[i]:
print('Current Freq Detected at 3rd spike: %f' % originalFreq[i])
self.assertTrue(f3-5*delta_freq<originalFreq[i])
self.assertTrue(originalFreq[i]<(f3+5*delta_freq))
def atest__filtering_time_freq(self):
filterType = 'bandpass'
lowFreq = 1.0
highFreq = 1.5
order = 2
originalFreq, originalSignalFreq = time_to_freq(originalTime, originalSignalTime, delta_time)
filteredSignalTime, filteredSignalFreq, adjusted_w, adjusted_h = filtering_time_freq(originalTime, originalSignalTime, delta_time, filterType, highFreq, lowFreq, order)
filteredAmplitudeFreq = np.abs(filteredSignalFreq)
for i in xrange(len(filteredAmplitudeFreq)):
if filteredAmplitudeFreq[i] > 1000: #spike detected
if 0<originalFreq[i]:
print('LOL %r' % originalFreq[i])
# only 3rd freq detected
self.assertTrue(f3-delta_freq < originalFreq[i])
self.assertTrue(originalFreq[i] < f3+delta_freq)
# NOT 1st freq
self.assertFalse(originalFreq[i] < f1+5*delta_freq)
# NOT 2nd freq
self.assertFalse(originalFreq[i] < f2+5*delta_freq)
def seisApplyFilter(saclist, filtParas):
'Filter seismograms by butterworth filter'
for sacdh in saclist:
origTimeT = sacdh.time
origDataT = sacdh.data
origTimeF, origDataF = ftr.time_to_freq(origTimeT, origDataT, sacdh.delta)
filtDataT, filtDataF, adjw, adjh = ftr.filtering_time_freq(origTimeT, origDataT, sacdh.delta, filtParas['band'], filtParas['highFreq'], filtParas['lowFreq'], filtParas['order'], filtParas['reversepass'])
sacdh.datamem = filtDataT
return
def seisApplyFilter(saclist, filtParas):
'Filter seismograms by butterworth filter'
for sacdh in saclist:
origTimeT = sacdh.time
origDataT = sacdh.data
origTimeF, origDataF = ftr.time_to_freq(origTimeT, origDataT,
sacdh.delta)
filtDataT, filtDataF, adjw, adjh = ftr.filtering_time_freq(
origTimeT, origDataT, sacdh.delta, filtParas['band'],
filtParas['highFreq'], filtParas['lowFreq'], filtParas['order'],
filtParas['reversepass'])
sacdh.datamem = filtDataT
return
