def test_sacpaz_from_dataless(self):
# The following dictionary is extracted from a datalessSEED
# file
pazdict = {
"sensitivity": 2516580000.0,
"digitizer_gain": 1677720.0,
"seismometer_gain": 1500.0,
"zeros": [0j, 0j],
"gain": 59198800.0,
"poles": [
(-0.037010000000000001 + 0.037010000000000001j),
(-0.037010000000000001 - 0.037010000000000001j),
(-131 + 467.30000000000001j),
(-131 - 467.30000000000001j),
(-251.30000000000001 + 0j),
],
}
tr = Trace()
# This file was extracted from the datalessSEED file using rdseed
pazfile = os.path.join(os.path.dirname(__file__), "data", "SAC_PZs_NZ_HHZ_10")
attach_paz(tr, pazfile, todisp=False)
sacconstant = pazdict["digitizer_gain"] * pazdict["seismometer_gain"] * pazdict["gain"]
np.testing.assert_almost_equal(tr.stats.paz["gain"] / 1e17, sacconstant / 1e17, decimal=6)
# pole-zero files according to the SAC convention are in displacement
self.assertEqual(len(tr.stats.paz["zeros"]), 3)
def test_sacpaz_from_dataless(self):
# The following dictionary is extracted from a datalessSEED
# file
pazdict = {
'sensitivity':
2516580000.0,
'digitizer_gain':
1677720.0,
'seismometer_gain':
1500.0,
'zeros': [0j, 0j],
'gain':
59198800.0,
'poles': [(-0.037010000000000001 + 0.037010000000000001j),
(-0.037010000000000001 - 0.037010000000000001j),
(-131 + 467.30000000000001j),
(-131 - 467.30000000000001j), (-251.30000000000001 + 0j)]
}
tr = Trace()
# This file was extracted from the datalessSEED file using rdseed
pazfile = os.path.join(os.path.dirname(__file__), 'data',
'SAC_PZs_NZ_HHZ_10')
attach_paz(tr, pazfile, todisp=False)
sacconstant = pazdict['digitizer_gain'] * \
pazdict['seismometer_gain'] * pazdict['gain']
np.testing.assert_almost_equal(tr.stats.paz['gain'] / 1e17,
sacconstant / 1e17,
decimal=6)
# pole-zero files according to the SAC convention are in displacement
self.assertEqual(len(tr.stats.paz['zeros']), 3)
def test_attach_paz_diff_order(self):
pazfile = os.path.join(os.path.dirname(__file__), "data", "NZCRLZ_HHZ10.pz")
tr = Trace()
attach_paz(tr, pazfile)
np.testing.assert_array_almost_equal(tr.stats.paz["gain"], 7.4592e-2, decimal=6)
self.assertEqual(len(tr.stats.paz["zeros"]), 5)
self.assertEqual(len(tr.stats.paz["poles"]), 4)
def test_attach_paz_diff_order(self):
pazfile = os.path.join(os.path.dirname(__file__),
'data', 'NZCRLZ_HHZ10.pz')
tr = Trace()
attach_paz(tr, pazfile)
np.testing.assert_array_almost_equal(tr.stats.paz['gain'],
7.4592e-2, decimal=6)
self.assertEqual(len(tr.stats.paz['zeros']), 5)
self.assertEqual(len(tr.stats.paz['poles']), 4)
def test_SacInstCorrection(self):
# SAC recommends to taper the transfer function if a pure
# deconvolution is done instead of simulating a different
# instrument. This test checks the difference between the
# result from removing the instrument response using SAC or
# ObsPy. Visual inspection shows that the traces are pretty
# much identical but differences remain (rms ~ 0.042). Haven't
# found the cause for those, yet. One possible reason is the
# floating point arithmetic of SAC vs. the double precision
# arithmetic of Python. However differences still seem to be
# too big for that.
pzf = os.path.join(self.path, 'SAC_PZs_KARC_BHZ')
sacf = os.path.join(self.path, 'KARC.LHZ.SAC.asc.gz')
testsacf = os.path.join(self.path, 'KARC_corrected.sac.asc.gz')
plow = 160.
phigh = 4.
fl1 = 1.0 / (plow + 0.0625 * plow)
fl2 = 1.0 / plow
fl3 = 1.0 / phigh
fl4 = 1.0 / (phigh - 0.25 * phigh)
#Uncomment the following to run the sac-commands
#that created the testing file
#if 1:
# import subprocess as sp
# p = sp.Popen('sac',shell=True,stdin=sp.PIPE)
# cd1 = p.stdin
# print >>cd1, "r %s"%sacf
# print >>cd1, "rmean"
# print >>cd1, "rtrend"
# print >>cd1, "taper type cosine width 0.03"
# print >>cd1, "transfer from polezero subtype %s to none \
# freqlimits %f %f %f %f" % (pzf, fl1, fl2, fl3, fl4)
# print >>cd1, "w over ./data/KARC_corrected.sac"
# print >>cd1, "quit"
# cd1.close()
# p.wait()
stats = {'network': 'KA', 'delta': 0.99999988079072466,
'station': 'KARC', 'location': 'S1',
'starttime': UTCDateTime(2001, 2, 13, 0, 0, 0, 993700),
'calib': 1.00868e+09, 'channel': 'BHZ'}
tr = Trace(np.loadtxt(sacf), stats)
attach_paz(tr, pzf, tovel=False)
tr.data = seisSim(tr.data, tr.stats.sampling_rate,
paz_remove=tr.stats.paz, remove_sensitivity=False,
pre_filt=(fl1, fl2, fl3, fl4))
data = np.loadtxt(testsacf)
# import matplotlib.pyplot as plt
# plt.plot(tr.data)
# plt.plot(data)
# plt.show()
rms = np.sqrt(np.sum((tr.data - data) ** 2) / \
np.sum(tr.data ** 2))
self.assertTrue(rms < 0.0421)
def test_SacInstCorrection(self):
# SAC recommends to taper the transfer function if a pure
# deconvolution is done instead of simulating a different
# instrument. This test checks the difference between the
# result from removing the instrument response using SAC or
# ObsPy. Visual inspection shows that the traces are pretty
# much identical but differences remain (rms ~ 0.042). Haven't
# found the cause for those, yet. One possible reason is the
# floating point arithmetic of SAC vs. the double precision
# arithmetic of Python. However differences still seem to be
# too big for that.
pzf = os.path.join(self.path, 'SAC_PZs_KARC_BHZ')
sacf = os.path.join(self.path, 'KARC.LHZ.SAC.asc.gz')
testsacf = os.path.join(self.path, 'KARC_corrected.sac.asc.gz')
plow = 160.
phigh = 4.
fl1 = 1.0 / (plow + 0.0625 * plow)
fl2 = 1.0 / plow
fl3 = 1.0 / phigh
fl4 = 1.0 / (phigh - 0.25 * phigh)
#Uncomment the following to run the sac-commands
#that created the testing file
#if 1:
# import subprocess as sp
# p = sp.Popen('sac',shell=True,stdin=sp.PIPE)
# cd1 = p.stdin
# print >>cd1, "r %s"%sacf
# print >>cd1, "rmean"
# print >>cd1, "rtrend"
# print >>cd1, "taper type cosine width 0.03"
# print >>cd1, "transfer from polezero subtype %s to none \
# freqlimits %f %f %f %f" % (pzf, fl1, fl2, fl3, fl4)
# print >>cd1, "w over ./data/KARC_corrected.sac"
# print >>cd1, "quit"
# cd1.close()
# p.wait()
stats = {'network': 'KA', 'delta': 0.99999988079072466,
'station': 'KARC', 'location': 'S1',
'starttime': UTCDateTime(2001, 2, 13, 0, 0, 0, 993700),
'calib': 1.00868e+09, 'channel': 'BHZ'}
tr = Trace(np.loadtxt(sacf), stats)
attach_paz(tr, pzf, tovel=False)
tr.data = seisSim(tr.data, tr.stats.sampling_rate,
paz_remove=tr.stats.paz, remove_sensitivity=False,
pre_filt=(fl1, fl2, fl3, fl4))
data = np.loadtxt(testsacf)
# import matplotlib.pyplot as plt
# plt.plot(tr.data)
# plt.plot(data)
# plt.show()
rms = np.sqrt(np.sum((tr.data - data) ** 2) /
np.sum(tr.data ** 2))
self.assertTrue(rms < 0.0421)
def removeInstrument(st, args):
if (args.sim == 'PZs'):
# prefilters
f = args.flim.split()
f0 = eval(f[0])
f1 = eval(f[1])
f2 = eval(f[2])
f3 = eval(f[3])
toPurge = [] # station to purge if no Paz found
for i in range(len(st)):
# attach poles and zeros instrument
if (args.dva == '1'):
try:
attach_paz(st[i], st[i].stats.PZs_file, todisp=False)
except:
print "No appropriate PZs file found for station " + st[
i].stats.station, st[i].stats.channel, st[
i].stats.network
toPurge.append(st[i].stats.station)
else:
try:
attach_paz(st[i], st[i].stats.PZs_file, tovel=True)
except:
print "No appropriate PZs file found for station " + st[
i].stats.station, st[i].stats.channel, st[
i].stats.network
toPurge.append(st[i].stats.station)
# remove stations if len(toPurge>0)
if len(toPurge) > 0:
st = purgeListStation(st, toPurge, 'r')
print "Check if station/channel/network/location of the PZs files and the same string within loaded binary files "
print "do correspond. It may occour for instance that the headers strings of the waveform files (e.g. sac, fseed) "
print "do not agrees with the same strings of the PZs name files. For instance the name of the network. "
print "If these strings do not correspond, modify the name of the PZs files or the header values of the waveforms"
print "You may also choose to remove this station using the option --purge (see help for details)"
# now do remove
for i in range(len(st)):
# remove instrument to displacement
# st[i].data=detrend(st[i].data)
st[i].data = seisSim(st[i].data,st[i].stats.sampling_rate,paz_remove=st[i].stats.paz, \
taper=True, taper_fraction=0.050, pre_filt=(f0,f1,f2,f3)) #,water_level=60.0)
# from meters to centimeters
st[i].data = st[i].data * 100
return st
def removeInstrument(st,args):
if(args.sim == 'PZs'):
# prefilters
f = args.flim.split()
f0 = eval(f[0])
f1 = eval(f[1])
f2 = eval(f[2])
f3 = eval(f[3])
toPurge= [] # station to purge if no Paz found
for i in range(len(st)):
# attach poles and zeros instrument
if(args.dva=='1'):
try:
attach_paz(st[i], st[i].stats.PZs_file,todisp=False)
except:
print "No appropriate PZs file found for station " + st[i].stats.station,st[i].stats.channel,st[i].stats.network
toPurge.append(st[i].stats.station)
else:
try:
attach_paz(st[i], st[i].stats.PZs_file,tovel=True)
except:
print "No appropriate PZs file found for station " + st[i].stats.station,st[i].stats.channel,st[i].stats.network
toPurge.append(st[i].stats.station)
# remove stations if len(toPurge>0)
if len(toPurge) > 0:
st = purgeListStation(st,toPurge,'r')
print "Check if station/channel/network/location of the PZs files and the same string within loaded binary files "
print "do correspond. It may occour for instance that the headers strings of the waveform files (e.g. sac, fseed) "
print "do not agrees with the same strings of the PZs name files. For instance the name of the network. "
print "If these strings do not correspond, modify the name of the PZs files or the header values of the waveforms"
print "You may also choose to remove this station using the option --purge (see help for details)"
# now do remove
for i in range(len(st)):
# remove instrument to displacement
# st[i].data=detrend(st[i].data)
st[i].data = seisSim(st[i].data,st[i].stats.sampling_rate,paz_remove=st[i].stats.paz, \
taper=True, taper_fraction=0.050, pre_filt=(f0,f1,f2,f3)) #,water_level=60.0)
# from meters to centimeters
st[i].data = st[i].data * 100
return st
def test_sacpaz_from_resp(self):
# The following two files were both extracted from a dataless
# seed file using rdseed
respfile = os.path.join(os.path.dirname(__file__),
'data', 'RESP.NZ.CRLZ.10.HHZ')
sacpzfile = os.path.join(os.path.dirname(__file__),
'data', 'SAC_PZs_NZ_CRLZ_HHZ')
# This is a rather lengthy test, in which the
# poles, zeros and the gain of each instrument response file
# are converted into the corresponding velocity frequency response
# function which have to be sufficiently close. Possibly due to
# different truncations in the RESP-formatted and SAC-formatted
# response files the frequency response functions are not identical.
tr1 = Trace()
tr2 = Trace()
attach_resp(tr1, respfile, torad=True, todisp=False)
attach_paz(tr2, sacpzfile, torad=False, tovel=True)
p1 = tr1.stats.paz.poles
z1 = tr1.stats.paz.zeros
g1 = tr1.stats.paz.gain
t_samp = 0.01
n = 32768
fy = 1 / (t_samp * 2.0)
# start at zero to get zero for offset/ DC of fft
f = np.arange(0, fy + fy / n, fy / n) # arange should includes fy
w = f * 2 * np.pi
s = 1j * w
a1 = np.poly(p1)
b1 = g1 * np.poly(z1)
h1 = np.polyval(b1, s) / np.polyval(a1, s)
h1 = np.conj(h1)
h1[-1] = h1[-1].real + 0.0j
p2 = tr2.stats.paz.poles
z2 = tr2.stats.paz.zeros
g2 = tr2.stats.paz.gain
a2 = np.poly(p2)
b2 = g2 * np.poly(z2)
h2 = np.polyval(b2, s) / np.polyval(a2, s)
h2 = np.conj(h2)
h2[-1] = h2[-1].real + 0.0j
amp1 = abs(h1)
amp2 = abs(h2)
phase1 = np.unwrap(np.arctan2(-h1.imag, h1.real))
phase2 = np.unwrap(np.arctan2(-h2.imag, h2.real))
np.testing.assert_almost_equal(phase1, phase2, decimal=4)
rms = np.sqrt(np.sum((amp1 - amp2) ** 2) /
np.sum(amp2 ** 2))
self.assertTrue(rms < 2.02e-06)
self.assertTrue(tr1.stats.paz.t_shift, 0.4022344)
def test_attach_paz(self):
fvelhz = io.StringIO("""ZEROS 3
-5.032 0.0
POLES 6
-0.02365 0.02365
-0.02365 -0.02365
-39.3011 0.
-7.74904 0.
-53.5979 21.7494
-53.5979 -21.7494
CONSTANT 2.16e18""")
tr = Trace()
attach_paz(tr, fvelhz, torad=True, todisp=True)
np.testing.assert_array_almost_equal(tr.stats.paz['zeros'][0],
- 31.616988, decimal=6)
self.assertEqual(len(tr.stats.paz['zeros']), 4)
def addPazStats(st, dir, sfiles):
# loop over sac files to find stations
for i in range(len(st)):
sta = st[i].stats['station']
cha = st[i].stats['channel']
net = st[i].stats['network']
filename = 'SAC.PZs.' + net + '.' + sta + '.' + cha
new = dir + os.sep + filename
# here an empty file results into erroro
# test if file is empty before
try:
if os.stat(new)[6] > 3:
# now test if Constant is there
for line in open(new):
if "CONSTANT" in line:
attach_paz(st[i],new)
else:
print "Empty Paz file ",new
except:
print "file ",new," not found"
return st