def st(data,
minfreq=0,
maxfreq=None,
samprate=None,
freqsamprate=1,
remove_edge=False,
analytic_signal=False,
factor=1):
if data.shape[0] <= 1 or len(data.shape) > 1:
raise TypeError('input data invalid ,please check!')
if not maxfreq and not samprate:
#regard signal as 1 second length
maxfreq = len(data) // 2
samprate = len(data)
if maxfreq and not samprate:
samprate = len(data)
if not maxfreq and samprate:
maxfreq = samprate // 2
orig = copy.copy(data)
st_res = np.zeros((int((maxfreq - minfreq) / freqsamprate) + 1, len(data)),
dtype='c8')
if remove_edge:
print(
'remove_edge selected; Remove trend with polynomial fit and taper!'
)
try:
from obspy.core import Trace
except ModuleNotFoundError:
print('Obspy not found ,please install Obspy!')
sys.exit()
tmp = Trace(data=orig)
tmp.detrend('polynomial', order=2)
tmp.taper(0.04)
orig = tmp.data
if analytic_signal:
print('analytic_signal selected; Calculating analytic signal!')
orig = signal.hilbert(orig)
vec = np.hstack((np.fft.fft(orig), np.fft.fft(orig)))
if minfreq == 0:
st_res[0] = np.mean(orig) * np.ones(len(data))
else:
st_res[0] = np.fft.ifft(vec[minfreq:minfreq + len(data)] *
g_window(len(data), minfreq, factor))
for i in range(freqsamprate, (maxfreq - minfreq) + 1, freqsamprate):
st_res[int(i / freqsamprate)] = np.fft.ifft(
vec[minfreq + i:minfreq + i + len(data)] *
g_window(len(data), minfreq + i, factor))
return st_res
def test_detrend(self):
"""
Test detrend method of trace
"""
t = np.arange(10)
data = 0.1 * t + 1.
tr = Trace(data=data.copy())
tr.detrend(type='simple')
np.testing.assert_array_almost_equal(tr.data, np.zeros(10))
tr.data = data.copy()
tr.detrend(type='linear')
np.testing.assert_array_almost_equal(tr.data, np.zeros(10))
data = np.zeros(10)
data[3:7] = 1.
tr.data = data.copy()
tr.detrend(type='simple')
np.testing.assert_almost_equal(tr.data[0], 0.)
np.testing.assert_almost_equal(tr.data[-1], 0.)
tr.data = data.copy()
tr.detrend(type='linear')
np.testing.assert_almost_equal(tr.data[0], -0.4)
np.testing.assert_almost_equal(tr.data[-1], -0.4)
def test_detrend(self):
"""
Test detrend method of trace
"""
t = np.arange(10)
data = 0.1 * t + 1.
tr = Trace(data=data.copy())
tr.detrend(type='simple')
np.testing.assert_array_almost_equal(tr.data, np.zeros(10))
tr.data = data.copy()
tr.detrend(type='linear')
np.testing.assert_array_almost_equal(tr.data, np.zeros(10))
data = np.zeros(10)
data[3:7] = 1.
tr.data = data.copy()
tr.detrend(type='simple')
np.testing.assert_almost_equal(tr.data[0], 0.)
np.testing.assert_almost_equal(tr.data[-1], 0.)
tr.data = data.copy()
tr.detrend(type='linear')
np.testing.assert_almost_equal(tr.data[0], -0.4)
np.testing.assert_almost_equal(tr.data[-1], -0.4)
def create_kiknet_acc(recid, path_kiknet_folder, fminNS2, fmaxNS2, fminEW2,
fmaxEW2):
"""
KiK-net acc are stored within Database_small.hdf5 file
"""
# Import libraries
import numpy as np
from obspy.core import Trace, UTCDateTime
import re
from obspy.signal import filter
# desc1 = ""
# desc2 = ""
time1 = []
time2 = []
inp_acc1 = []
inp_acc2 = []
npts1 = []
npts2 = []
for i in range(1, 3):
if i == 1:
comp = 'EW2'
fmin = fminEW2
fmax = fmaxEW2
elif i == 2:
comp = 'NS2'
fmin = fminNS2
fmax = fmaxNS2
file_acc = path_kiknet_folder + '/' + str(recid) + '/' + str(
recid) + '.' + comp
hdrnames = [
'Origin Time', 'Lat.', 'Long.', 'Depth. (km)', 'Mag.',
'Station Code', 'Station Lat.', 'Station Long.',
'Station Height(m)', 'Record Time', 'Sampling Freq(Hz)',
'Duration Time(s)', 'Dir.', 'Scale Factor', 'Max. Acc. (gal)',
'Last Correction', 'Memo.'
]
acc_data = []
time = []
with open(file_acc, 'r') as f:
content = f.readlines()
counter = 0
for line in content:
if counter < 17:
if not line.startswith(hdrnames[counter]):
sys.exit("Expected line to start with %s but got %s " %
(hdrnames[counter], line))
else:
flds = line.split()
if (counter == 0):
origin_time = flds[2] + ' ' + flds[3]
origin_time = UTCDateTime.strptime(origin_time,
'%Y/%m/%d %H:%M:%S')
# All times are in Japanese standard time which is 9 hours ahead of UTC
origin_time -= 9 * 3600.
elif (counter == 1):
lat = float(flds[1])
elif (counter == 2):
lon = float(flds[1])
elif (counter == 3):
dp = float(flds[2])
elif (counter == 4):
mag = float(flds[1])
elif (counter == 5):
stnm = flds[2]
elif (counter == 6):
stla = float(flds[2])
elif (counter == 7):
stlo = float(flds[2])
elif (counter == 8):
stel = float(flds[2])
elif (counter == 9):
record_time = flds[2] + ' ' + flds[3]
# A 15 s delay is added to the record time by the
# the K-NET and KiK-Net data logger
record_time = UTCDateTime.strptime(record_time,
'%Y/%m/%d %H:%M:%S') - 15.0
# All times are in Japanese standard time which is 9 hours ahead of UTC
record_time -= 9 * 3600.
elif (counter == 10):
freqstr = flds[2]
m = re.search('[0-9]*', freqstr)
freq = int(m.group())
elif (counter == 11):
duration = float(flds[2])
elif (counter == 12):
channel = flds[1].replace('-', '')
kiknetcomps = {
'1': 'NS1',
'2': 'EW1',
'3': 'UD1',
'4': 'NS2',
'5': 'EW2',
'6': 'UD2'
}
if channel.strip() in kiknetcomps.keys(
): # kiknet directions are 1-6
channel = kiknetcomps[channel.strip()]
elif (counter == 13):
eqn = flds[2]
num, denom = eqn.split('/')
num = float(re.search('[0-9]*', num).group())
denom = float(denom)
# convert the calibration from gal to m/s^2
calib = 0.01 * num / denom
elif (counter == 14):
accmax = float(flds[3])
elif (counter == 15):
last_correction = flds[2] + ' ' + flds[3]
last_correction = UTCDateTime.strptime(last_correction,
'%Y/%m/%d %H:%M:%S')
# All times are in Japanese standard time which is 9 hours ahead of UTC
last_correction -= 9 * 3600.
elif counter > 16:
data = str(line).split()
for value in data:
a = float(value)
acc_data.append(a)
counter = counter + 1
data = np.array(acc_data)
tr = Trace(data)
tr.detrend("linear")
tr.taper(max_percentage=0.05, type='cosine', side='both')
filter_order = 4
pad = np.zeros(int(round(1.5 * filter_order / fmin * freq)))
tr.data = np.concatenate([pad, tr.data, pad])
fN = freq / 2
if fmax < fN:
tr.data = filter.bandpass(tr.data,
freqmin=fmin,
freqmax=fmax,
df=freq,
corners=4,
zerophase=True)
else:
tr.data = filter.highpass(tr.data,
freq=fmin,
df=freq,
corners=4,
zerophase=True)
tr.data = tr.data[len(pad):len(tr.data) - len(pad)]
tr.data = tr.data * calib / 9.81 #in g
npts = len(tr.data)
time = []
for j in range(0, npts):
t = j * 1 / freq
time.append(t)
time = np.asarray(time)
if i == 1:
inp_acc1 = tr.data
npts1 = npts
time1 = time
if i == 2:
inp_acc2 = tr.data
npts2 = npts
time2 = time
return time1, time2, inp_acc1, inp_acc2, npts1, npts2
