def test_relcal_sts2_vs_unknown(self):
"""
Test relative calibration of unknown instrument vs STS2 in the same
time range. Window length is set to 20 s, smoothing rate to 10.
"""
st1 = read(os.path.join(self.path, 'ref_STS2'))
st2 = read(os.path.join(self.path, 'ref_unknown'))
calfile = os.path.join(self.path, 'STS2_simp.cal')
freq, amp, phase = relcalstack(st1, st2, calfile, 20, smooth=10,
save_data=False)
# read in the reference responses
un_resp = np.loadtxt(os.path.join(self.path, 'unknown.resp'))
kn_resp = np.loadtxt(os.path.join(self.path, 'STS2.refResp'))
# test if freq, amp and phase match the reference values
np.testing.assert_array_almost_equal(freq, un_resp[:, 0],
decimal=4)
np.testing.assert_array_almost_equal(freq, kn_resp[:, 0],
decimal=4)
np.testing.assert_array_almost_equal(amp, un_resp[:, 1],
decimal=4)
np.testing.assert_array_almost_equal(phase, un_resp[:, 2],
decimal=4)
def test_FDSN_network():
(options, args, parser) = command_parse()
input_dics = read_input_command(parser)
# Changing the input_dics values for testing
input_dics['min_date'] = '2011-03-01'
input_dics['max_date'] = '2011-03-20'
input_dics['min_mag'] = 8.9
input_dics['datapath'] = 'test_%s' % dir_name
input_dics['net'] = 'TA'
input_dics['sta'] = 'Z3*'
input_dics['cha'] = 'BHZ'
input_dics['req_parallel'] = 'Y'
input_dics['req_np'] = 4
events = get_Events(input_dics, 'event-based')
assert len(events) == 1
FDSN_network(input_dics, events)
st_raw = read(os.path.join(input_dics['datapath'],
'2011-03-01_2011-03-20',
'20110311_1',
'BH_RAW', '*'))
assert len(st_raw) == 7
st_wilber = read(os.path.join('tests', 'fdsn_waveforms', 'TA*'))
for sta in ['Z35A', 'Z37A', 'Z39A']:
tr_raw = st_raw.select(station=sta)[0]
tr_wilber = st_wilber.select(station=sta)[0]
tr_diff = abs(tr_raw.data - tr_wilber.data)
assert max(tr_diff) == 0.
def adj_sac_name(i, sta_name_i, yspec_in_names_i, path1):
"""
Adjusting SAC names
It is meant to be used in parallel
"""
if (yspec_in_names_i[0] - float(sta_name_i[5])) > 0.01:
print 'ERROR: Difference in latitude: %s' % (yspec_in_names_i[0] - float(sta_name_i[5]))
if (yspec_in_names_i[1] - float(sta_name_i[6])) > 0.01:
print 'ERROR: Difference in longitude: %s' % (yspec_in_names_i[1] - float(sta_name_i[6]))
for chan in ['BHE', 'BHN', 'BHZ']:
tr = read(os.path.join(path1, 'SAC', 'dis.RS' + '%02d' % (i+1) + '..' + chan))[0]
tr.write(os.path.join(path1, 'SAC_realName', 'grf.%s.%s.%s.x00.%s' % (sta_name_i[0], sta_name_i[1],
sta_name_i[2], chan)), format='SAC')
tr_new = read(os.path.join(path1, 'SAC_realName', 'grf.%s.%s.%s.x00.%s' % (sta_name_i[0], sta_name_i[1],
sta_name_i[2], chan)))[0]
tr_new.stats.network = sta_name_i[0]
tr_new.stats.station = sta_name_i[1]
tr_new.stats.location = sta_name_i[2]
tr_new.stats.channel = chan
tr_new.stats.sac.stla = float(sta_name_i[5])
tr_new.stats.sac.stlo = float(sta_name_i[6])
tr_new.stats.sac.stel = float(sta_name_i[7])
tr_new.stats.sac.stdp = float(sta_name_i[8])
tr_new.stats.sac.evla = float(sta_name_i[9])
tr_new.stats.sac.evlo = float(sta_name_i[10])
tr_new.stats.sac.evdp = float(sta_name_i[11])
tr_new.write(os.path.join(path1, 'SAC_realName', 'grf.%s.%s.%s.x00.%s' % (sta_name_i[0], sta_name_i[1],
sta_name_i[2], chan)),
format='SAC')
def test_issue341(self):
"""
Tests issue #341
Read/write of MiniSEED files with huge sampling rates/delta values.
"""
tempfile = NamedTemporaryFile().name
# 1 - sampling rate
st = read()
tr = st[0]
tr.stats.sampling_rate = 1000000000.0
tr.write(tempfile, format="MSEED")
# read again
st = read(tempfile)
self.assertEquals(st[0].stats.sampling_rate, 1000000000.0)
# 2 - delta
st = read()
tr = st[0]
tr.stats.delta = 10000000.0
tr.write(tempfile, format="MSEED")
# read again
st = read(tempfile)
self.assertAlmostEquals(st[0].stats.delta, 10000000.0, 0)
# clean up
os.remove(tempfile)
def getChannelWaveformFiles (network, station, location, channel, starttime, endtime, removeTrend, performInstrumentCorrection,applyScale,deconFilter1, deconFilter2, deconFilter3, deconFilter4, waterLevel, unit, client, fileTag):
#
# stream holds the final stream
#
thisStartTime = UTCDateTime(starttime)
thisEndTime = UTCDateTime(endtime)
stream = Stream()
streamIn = Stream()
try:
#
# read in the files to a stream
#
print "[INFO] checking:",fileTag
if performInstrumentCorrection:
streamIn = read(fileTag, starttime=thisStartTime, endtime=thisEndTime, nearest_sample=True, apply_calib=False )
else:
print "[INFO] Apply scaling"
streamIn = read(fileTag, starttime=thisStartTime, endtime=thisEndTime, nearest_sample=True, apply_calib=applyScale )
#print "STREAM IN",fileTag, starttime, endtime
except Exception, e:
print str(e)
print "[ERROR] client.get_waveforms",network, station, location, channel, starttime, endtime
return(None)
def test_writingSUFileWithNoHeader(self):
"""
If the trace has no trace.su attribute, one should still be able to
write a SeismicUnix file.
This is not recommended because most Trace.stats attributes will be
lost while writing SU.
"""
st = read()
del st[1:]
st[0].data = np.require(st[0].data, "float32")
outfile = NamedTemporaryFile().name
st.write(outfile, format="SU")
st2 = read(outfile)
os.remove(outfile)
# Compare new and old stream objects. All the other header attributes
# will not be set.
np.testing.assert_array_equal(st[0].data, st2[0].data)
self.assertEqual(st[0].stats.starttime, st2[0].stats.starttime)
self.assertEqual(st[0].stats.endtime, st2[0].stats.endtime)
self.assertEqual(st[0].stats.sampling_rate, st2[0].stats.sampling_rate)
# Writing and reading this new stream object should not change
# anything.
st2.write(outfile, format="SU")
st3 = read(outfile)
os.remove(outfile)
np.testing.assert_array_equal(st2[0].data, st3[0].data)
# Remove the su attributes because they will not be equal due to lazy
# header attributes.
del st2[0].stats.su
del st3[0].stats.su
self.assertEqual(st2[0].stats, st3[0].stats)
def test_xcorrPickCorrection(self):
"""
Test cross correlation pick correction on a set of two small local
earthquakes.
"""
st1 = read(os.path.join(self.path,
'BW.UH1._.EHZ.D.2010.147.a.slist.gz'))
st2 = read(os.path.join(self.path,
'BW.UH1._.EHZ.D.2010.147.b.slist.gz'))
tr1 = st1.select(component="Z")[0]
tr2 = st2.select(component="Z")[0]
t1 = UTCDateTime("2010-05-27T16:24:33.315000Z")
t2 = UTCDateTime("2010-05-27T16:27:30.585000Z")
dt, coeff = xcorrPickCorrection(t1, tr1, t2, tr2, 0.05, 0.2, 0.1)
self.assertAlmostEquals(dt, -0.014459080288833711)
self.assertAlmostEquals(coeff, 0.91542878457939791)
dt, coeff = xcorrPickCorrection(t2, tr2, t1, tr1, 0.05, 0.2, 0.1)
self.assertAlmostEquals(dt, 0.014459080288833711)
self.assertAlmostEquals(coeff, 0.91542878457939791)
dt, coeff = xcorrPickCorrection(t1, tr1, t2, tr2, 0.05, 0.2, 0.1,
filter="bandpass",
filter_options={'freqmin': 1, 'freqmax': 10})
self.assertAlmostEquals(dt, -0.013025086360067755)
self.assertAlmostEquals(coeff, 0.98279277273758803)
def computeSineCal(self):
try:
# Read in BH and BC
dataIN = read(self.dataInLoc)
dataOUT = read(self.dataOutLoc)
# Convert start date to UTC
stime = UTCDateTime(str(self.startdate))
# Trim data to only grab the sine calibration
dataIN.trim(starttime=stime, endtime=stime + self.cal_duration)
dataOUT.trim(starttime=stime, endtime=stime + self.cal_duration)
# Calculate RMS of both traces and divide
dataINRMS = math.sqrt(2.) * sum(numpy.square(dataIN[0].data))
dataINRMS /= float(dataIN[0].stats.npts)
dataOUTRMS = math.sqrt(2.) * sum(numpy.square(dataOUT[0].data))
dataINRMS /= float(dataOUT[0].stats.npts)
if(self.dbconn is not None):
# Write results to database
cur = self.dbconn.cursor()
cur.execute("""INSERT INTO tbl_310calresults (fk_calibrationid,
input_rms, output_rms, outchannel, coil_constant)
VALUES (""" + "'" + str(self.cal_id) + "', '" +
str(dataINRMS) + "', '" + str(dataOUTRMS) +
"', '" + str(self.outChannel) + "', '" +
str(dataINRMS / dataOUTRMS) + "')")
self.dbconn.commit()
else:
print('input rms = ' + str(dataINRMS) +
', output rms = ' + str(dataOUTRMS) +
', coil constant = ' + str(dataINRMS / dataOUTRMS))
except:
self.sinecal_logger.error("Unexpected error:", sys.exc_info()[0])
def test_allDataTypesAndEndiansInMultipleFiles(self):
"""
Tests writing all different types. This is an test which is independent
of the read method. Only the data part is verified.
"""
file = os.path.join(self.path, "data", \
"BW.BGLD.__.EHE.D.2008.001.first_record")
tempfile = NamedTemporaryFile().name
# Read the data and copy them
st = read(file)
data_copy = st[0].data.copy()
# Float64, Float32, Int32, Int24, Int16, Char
encodings = {5: "f8", 4: "f4", 3: "i4", 0: "S1", 1: "i2"}
byteorders = {0: '<', 1: '>'}
for byteorder, btype in byteorders.iteritems():
for encoding, dtype in encodings.iteritems():
# Convert data to floats and write them again
st[0].data = data_copy.astype(dtype)
st.write(tempfile, format="MSEED", encoding=encoding,
reclen=256, byteorder=byteorder)
# Read the first record of data without header not using ObsPy
s = open(tempfile, "rb").read()
data = np.fromstring(s[56:256], dtype=btype + dtype)
np.testing.assert_array_equal(data, st[0].data[:len(data)])
# Read the binary chunk of data with ObsPy
st2 = read(tempfile)
np.testing.assert_array_equal(st2[0].data, st[0].data)
os.remove(tempfile)
def test_issue390(self):
"""
Read all SAC headers if debug_headers flag is enabled.
"""
# 1 - binary SAC
tr = read(self.file, headonly=True, debug_headers=True)[0]
self.assertEqual(tr.stats.sac.nzyear, 1978)
self.assertEqual(tr.stats.sac.nzjday, 199)
self.assertEqual(tr.stats.sac.nzhour, 8)
self.assertEqual(tr.stats.sac.nzmin, 0)
self.assertEqual(tr.stats.sac.nzsec, 0)
self.assertEqual(tr.stats.sac.nzmsec, 0)
self.assertEqual(tr.stats.sac.delta, 1.0)
self.assertEqual(tr.stats.sac.scale, -12345.0)
self.assertEqual(tr.stats.sac.npts, 100)
self.assertEqual(tr.stats.sac.knetwk, '-12345 ')
self.assertEqual(tr.stats.sac.kstnm, 'STA ')
self.assertEqual(tr.stats.sac.kcmpnm, 'Q ')
# 2 - ASCII SAC
tr = read(self.filexy, headonly=True, debug_headers=True)[0]
self.assertEqual(tr.stats.sac.nzyear, -12345)
self.assertEqual(tr.stats.sac.nzjday, -12345)
self.assertEqual(tr.stats.sac.nzhour, -12345)
self.assertEqual(tr.stats.sac.nzmin, -12345)
self.assertEqual(tr.stats.sac.nzsec, -12345)
self.assertEqual(tr.stats.sac.nzmsec, -12345)
self.assertEqual(tr.stats.sac.delta, 1.0)
self.assertEqual(tr.stats.sac.scale, -12345.0)
self.assertEqual(tr.stats.sac.npts, 100)
self.assertEqual(tr.stats.sac.knetwk, '-12345 ')
self.assertEqual(tr.stats.sac.kstnm, 'sta ')
self.assertEqual(tr.stats.sac.kcmpnm, 'Q ')
def test_saveWaveformCompressed(self):
"""
Tests saving compressed and not unpacked bzip2 files to disk.
"""
mseedfile = NamedTemporaryFile(suffix='.bz2').name
fseedfile = NamedTemporaryFile(suffix='.bz2').name
try:
# initialize client
client = Client()
start = UTCDateTime(2008, 1, 1, 0, 0)
end = start + 1
# MiniSEED
client.saveWaveform(mseedfile, 'GE', 'APE', '', 'BHZ', start, end,
unpack=False)
# check if compressed
self.assertEquals(open(mseedfile, 'rb').read(2), 'BZ')
# importing via read should work too
read(mseedfile)
# Full SEED
client.saveWaveform(fseedfile, 'GE', 'APE', '', 'BHZ', start, end,
format="FSEED", unpack=False)
# check if compressed
self.assertEquals(open(fseedfile, 'rb').read(2), 'BZ')
# importing via read should work too
read(fseedfile)
finally:
os.remove(mseedfile)
os.remove(fseedfile)
def GFSelectZ(stlat,stlon,hdir):
dist = locations2degrees(eplat,eplon,stlat,stlon)
dist_str = str(int(dist*10.)/2*2+1)#Some GFs have only odd dists.
#dist_str = str(int(dist*10.))#Some GFs have only odd dists.
dist_form = dist_str.zfill(4)
## Loading files
trPP = read(hdir + "PP/GF." + dist_form + ".SY.LHZ.SAC" )[0]
#trPP.data -= trPP.data[0]
trRR = read(hdir + "RR/GF." + dist_form + ".SY.LHZ.SAC" )[0]
#trRR.data -= trRR.data[0]
trRT = read(hdir + "RT/GF." + dist_form + ".SY.LHZ.SAC" )[0]
#trRT.data -= trRT.data[0]
trTT = read(hdir + "TT/GF." + dist_form + ".SY.LHZ.SAC" )[0]
#trTT.data -= trTT.data[0]
return trPP, trRR, trRT, trTT
def test_polarization(self):
self.mat = np.array([[1,0,0],[0,-1,1],[1,1,1]])
l1, l2, l3 = np.sqrt(2), 1, -np.sqrt(2)
expRect = 1 - (l2+l3)/(2*l1)
expPlan = 1 - (2*l3)/(l1+l2)
rect, plan, lambda_max = polarization_analysis(self.mat,plot=False)
self.assertAlmostEquals(lambda_max,l1,places=6)
self.assertAlmostEquals(rect,expRect,places=6)
self.assertAlmostEquals(plan,expPlan,places=6)
file = "/home/nadege/waveloc/data/Piton/2011-02-02/2011-02-02T00:00:00.YA.UV15.HHZ.filt.mseed"
cmin = utcdatetime.UTCDateTime("2011-02-02T00:58:47.720000Z")-15
cmax = utcdatetime.UTCDateTime("2011-02-02T00:58:47.720000Z")+135
ponset = 1400
st_z = read(file,starttime=cmin,endtime=cmax)
tr_z = st_z[0].data[ponset-10:ponset+30]
file_n = "%s/HHN/*%s*HHN*.filt.*"%(os.path.dirname(file),st_z[0].stats.station)
file_e = "%s/HHE/*%s*HHE*.filt.*"%(os.path.dirname(file),st_z[0].stats.station)
st_n = read(file_n,starttime=cmin,endtime=cmax)
st_e = read(file_e,starttime=cmin,endtime=cmax)
tr_n = st_n[0].data[ponset-10:ponset+30]
tr_e = st_e[0].data[ponset-10:ponset+30]
x=np.array([tr_z,tr_n,tr_e])
print tr_e.shape
mat = np.cov(x)
rect, plan, lambda_max = polarization_analysis(mat,plot=True)
from obspy.signal.polarization import eigval
leigenv1, leigenv2, leigenv3, rect, plan, dleigenv, drect, dplan = eigval(tr_e,tr_n,tr_z,[1,1,1,1,1])
print lambda_max
print leigenv1, leigenv2, leigenv3
def test_writeStreamViaObsPy(self):
"""
Write streams, i.e. multiple files via L{obspy.Trace}
"""
testdata = np.array([111, 111, 111, 111, 111, 109, 106, 103, 103,
110, 121, 132, 139])
testfile = NamedTemporaryFile().name
self.file = os.path.join(self.path, '3cssan.reg.8.1.RNON.wav')
tr = read(self.file, format='WAV')[0]
np.testing.assert_array_equal(tr.data[:13], testdata)
# write
st2 = Stream([Trace(), Trace()])
st2[0].data = tr.data.copy() # copy the data
st2[1].data = tr.data.copy() // 2 # be sure data are different
st2.write(testfile, format='WAV', framerate=7000)
# read without giving the WAV format option
base, ext = os.path.splitext(testfile)
testfile0 = "%s%03d%s" % (base, 0, ext)
testfile1 = "%s%03d%s" % (base, 1, ext)
tr30 = read(testfile0)[0]
tr31 = read(testfile1)[0]
self.assertEqual(tr30.stats, tr.stats)
self.assertEqual(tr31.stats, tr.stats)
np.testing.assert_array_equal(tr30.data[:13], testdata)
np.testing.assert_array_equal(tr31.data[:13], testdata // 2)
os.remove(testfile)
os.remove(testfile0)
os.remove(testfile1)
def test_022_check_content(self):
from obspy.core import read
from numpy.testing import assert_allclose
from ..api import connect, get_filters, get_station_pairs, \
get_components_to_compute
db = connect()
for filter in get_filters(db):
for components in get_components_to_compute(db):
for (sta1, sta2) in get_station_pairs(db):
pair = "%s_%s_%s_%s" % (sta1.net, sta1.sta,
sta2.net, sta2.sta)
tmp1 = os.path.join("STACKS",
"%02i" % filter.ref,
"001_DAYS",
components,
pair,
"2010-09-01.MSEED")
tmp2 = os.path.join("STACKS",
"%02i" % filter.ref,
"001_DAYS",
components,
pair,
"2010-09-01.SAC")
tmp1 = read(tmp1)
tmp2 = read(tmp2)
assert_allclose(tmp1[0].data, tmp2[0].data)
def test_readAndWriteViaObsPy(self):
"""
Read and Write files via L{obspy.Stream}
"""
# read trace
tr = read(self.file)[0]
# write comparison trace
st2 = Stream()
st2.traces.append(Trace())
tr2 = st2[0]
tr2.data = copy.deepcopy(tr.data)
tr2.stats = copy.deepcopy(tr.stats)
tempfile = NamedTemporaryFile().name
st2.write(tempfile, format="SAC")
# read comparison trace
tr3 = read(tempfile)[0]
os.remove(tempfile)
# check if equal
self.assertEqual(tr3.stats["station"], tr.stats["station"])
self.assertEqual(tr3.stats.npts, tr.stats.npts)
self.assertEqual(tr.stats["sampling_rate"], tr.stats["sampling_rate"])
self.assertEqual(tr.stats.get("channel"), tr.stats.get("channel"))
self.assertEqual(tr.stats.get("starttime"), tr.stats.get("starttime"))
self.assertEqual(tr.stats.sac.get("nvhdr"), tr.stats.sac.get("nvhdr"))
np.testing.assert_equal(tr.data, tr3.data)
def test_notUsedButGivenHeaders(self):
"""
Test case for #188
"""
tr1 = read(self.file)[0]
not_used = [
"xminimum",
"xmaximum",
"yminimum",
"ymaximum",
"unused6",
"unused7",
"unused8",
"unused9",
"unused10",
"unused11",
"unused12",
]
for i, header_value in enumerate(not_used):
tr1.stats.sac[header_value] = i
sac_file = NamedTemporaryFile().name
tr1.write(sac_file, "SAC")
tr2 = read(sac_file)[0]
os.remove(sac_file)
for i, header_value in enumerate(not_used):
self.assertEquals(int(tr2.stats.sac[header_value]), i)
def test_readGzip2File(self):
"""
Tests reading gzip compressed waveforms.
"""
path = os.path.dirname(__file__)
st1 = read(os.path.join(path, 'data', 'tspair.ascii.gz'))
st2 = read(os.path.join(path, 'data', 'tspair.ascii'))
self.assertTrue(st1 == st2)
def test_readBzip2File(self):
"""
Tests reading bzip2 compressed waveforms.
"""
path = os.path.dirname(__file__)
st1 = read(os.path.join(path, 'data', 'slist.ascii.bz2'))
st2 = read(os.path.join(path, 'data', 'slist.ascii'))
self.assertTrue(st1 == st2)
def test_read_seisanVsReference(self):
"""
Test for #970
"""
_file = os.path.join(self.path, "SEISAN_Bug", "2011-09-06-1311-36S.A1032_001BH_Z")
st = read(_file, format="SEISAN")
_file_ref = os.path.join(self.path, "SEISAN_Bug", "2011-09-06-1311-36S.A1032_001BH_Z_MSEED")
st_ref = read(_file_ref, format="MSEED")
self.assertTrue(np.allclose(st[0].data, st_ref[0].data))
def test_readXYwriteXYViaObspy(self):
"""
Write/Read files via L{obspy.Stream}
"""
tr = read(self.filexy, format="SACXY")[0]
tempfile = NamedTemporaryFile().name
tr.write(tempfile, format="SACXY")
tr1 = read(tempfile)[0]
os.remove(tempfile)
self.assertTrue(tr == tr1)
def test_FDSN_ARC_IC():
(options, args, parser) = command_parse()
input_dics = read_input_command(parser)
# Changing the input_dics values for testing
input_dics['min_date'] = '2011-03-01'
input_dics['max_date'] = '2011-03-20'
input_dics['min_mag'] = 8.9
input_dics['datapath'] = 'test_%s' % dir_name
input_dics['net'] = 'TA'
input_dics['sta'] = 'Z3*'
input_dics['cha'] = 'BHZ'
input_dics['req_parallel'] = 'Y'
input_dics['req_np'] = 4
FDSN_ARC_IC(input_dics, input_dics['fdsn_base_url'])
st_cor = read(os.path.join(input_dics['datapath'],
'2011-03-01_2011-03-20',
'20110311_1',
'BH', '*'))
assert len(st_cor) == 7
st_wilber = read(os.path.join('tests', 'fdsn_waveforms', 'TA*'))
paz_35 = {'gain': 5.714000e+08,
'sensitivity': 6.309070e+08,
'zeros': (0.0, 0.0, 0.0),
'poles': (-3.701000e-02+3.701000e-02j,
-3.701000e-02-3.701000e-02j,
-1.131000e+03+0.000000e+00j,
-1.005000e+03+0.000000e+00j,
-5.027000e+02+0.000000e+00j)}
for sta in ['Z35A', 'Z37A', 'Z39A']:
tr_cor = st_cor.select(station=sta)[0]
tr_wilber = st_wilber.select(station=sta)[0]
tr_wilber_corr = tr_wilber.copy()
tr_wilber_corr.detrend()
corr_wilber = seisSim(tr_wilber.data,
tr_wilber.stats.sampling_rate,
paz_remove=paz_35,
paz_simulate=None,
remove_sensitivity=True,
simulate_sensitivity=False,
water_level=600.,
zero_mean=True,
taper=True,
taper_fraction=0.05,
pre_filt=(0.008, 0.012, 3.0, 4.0),
pitsasim=False,
sacsim=True)
tr_wilber_corr.data = corr_wilber
tr_diff = abs(tr_cor.data - tr_wilber_corr.data)
# amplitude of the traces is in the order of 1e6 or so
assert max(tr_diff) < 0.00001
def test_read_seisan_vs_reference(self):
"""
Test for #970
"""
_file = os.path.join(self.path, 'SEISAN_Bug',
'2011-09-06-1311-36S.A1032_001BH_Z')
st = read(_file, format='SEISAN')
_file_ref = os.path.join(self.path, 'SEISAN_Bug',
'2011-09-06-1311-36S.A1032_001BH_Z_MSEED')
st_ref = read(_file_ref, format='MSEED')
self.assertTrue(np.allclose(st[0].data, st_ref[0].data))
def read_seed(DATAFILE, BYTEOFFSET):
"""Read a SEED or miniSEED 'sd' datatype.
"""
if BYTEOFFSET:
with open(DATAFILE, 'rb') as f0:
f0.seek(BYTEOFFSET)
f1 = StringIO(f0.read())
tr = read(f, format='MSEED')[0] #f1?
else:
tr = read(DATAFILE, format='MSEED')[0]
return tr.data
def get_results(session, station1, station2, filterid, components, dates, mov_stack=1, format="stack"):
export_format = get_config(session, "export_format")
if format == "stack":
stack = np.zeros(get_maxlag_samples(session))
i = 0
for date in dates:
daystack = os.path.join(
"STACKS",
"%02i" % filterid,
"%03i_DAYS" % mov_stack,
components,
"%s_%s" % (station1, station2),
str(date),
)
# logging.debug('reading: %s' % daystack)
if export_format == "BOTH":
daystack += ".MSEED"
elif export_format == "SAC":
daystack += ".SAC"
elif export_format == "MSEED":
daystack += ".MSEED"
try:
st = read(daystack)
if not np.any(np.isnan(st[0].data)) and not np.any(np.isinf(st[0].data)):
stack += st[0].data
i += 1
except:
pass
if i > 0:
return i, stack / i
else:
return 0, None
elif format == "matrix":
stack = np.zeros((len(dates), get_maxlag_samples(session))) * np.nan
i = 0
base = os.path.join(
"STACKS", "%02i" % filterid, "%03i_DAYS" % mov_stack, components, "%s_%s" % (station1, station2), "%s"
)
if export_format == "BOTH":
base += ".MSEED"
elif export_format == "SAC":
base += ".SAC"
elif export_format == "MSEED":
base += ".MSEED"
for j, date in enumerate(dates):
daystack = base % str(date)
try:
stack[j][:] = read(daystack)[0].data
i += 1
except:
pass
return i, stack
def test_readDos(self):
"""
Read file with dos newlines / encoding, that is
Line Feed (LF) and Carriage Return (CR)
see #355
"""
filedos = os.path.join(self.path, 'data',
'loc_RJOB20050831023349_first100_dos.z')
fileunix = os.path.join(self.path, 'data', 'loc_RJOB20050831023349.z')
st = read(filedos, verify_chksum=True)
st2 = read(fileunix, verify_chksum=True)
np.testing.assert_equal(st[0].data, st2[0].data[:100])
self.assertEqual(st[0].stats['station'], 'RJOB')
def test_enforceSteim2WithSteim1asEncoding(self):
"""
This tests whether the encoding kwarg overwrites the encoding in
trace.stats.mseed.encoding.
"""
file = os.path.join(self.path, "data",
"BW.BGLD.__.EHE.D.2008.001.first_record")
st = read(file)
self.assertEqual(st[0].stats.mseed.encoding, 'STEIM1')
tempfile = NamedTemporaryFile().name
st.write(tempfile, format='MSEED', encoding='STEIM2')
st2 = read(tempfile)
os.remove(tempfile)
self.assertEqual(st2[0].stats.mseed.encoding, 'STEIM2')
def test_readViaObsPy(self):
"""
Read files via L{obspy.Trace}
"""
testdata = np.array([64, 78, 99, 119, 123, 107,
72, 31, 2, 0, 30, 84, 141])
tr = read(self.file)[0]
self.assertEqual(tr.stats.npts, 2599)
self.assertEqual(tr.stats['sampling_rate'], 7000)
np.testing.assert_array_equal(tr.data[:13], testdata)
tr2 = read(self.file, format='WAV')[0]
self.assertEqual(tr2.stats.npts, 2599)
self.assertEqual(tr2.stats['sampling_rate'], 7000)
np.testing.assert_array_equal(tr.data[:13], testdata)
def test_issue289(self):
"""
Tests issue #289.
Reading MiniSEED using start-/endtime outside of data should result in
an empty Stream object.
"""
# 1
file = os.path.join(self.path, 'data', 'steim2.mseed')
st = read(file, starttime=UTCDateTime() - 10, endtime=UTCDateTime())
self.assertEqual(len(st), 0)
# 2
file = os.path.join(self.path, 'data', 'fullseed.mseed')
st = read(file, starttime=UTCDateTime() - 10, endtime=UTCDateTime())
self.assertEqual(len(st), 0)
def test_readWithMissingBlockette010(self):
"""
Reading a Full/Mini-SEED w/o blockette 010 but blockette 008.
"""
# 1 - Mini-SEED
file = os.path.join(self.path, 'data', 'blockette008.mseed')
tr = read(file)[0]
self.assertEqual('BW.PART..EHZ', tr.id)
self.assertEqual(1642, tr.stats.npts)
# 2 - full SEED
file = os.path.join(self.path, 'data',
'RJOB.BW.EHZ.D.300806.0000.fullseed')
tr = read(file)[0]
self.assertEqual('BW.RJOB..EHZ', tr.id)
self.assertEqual(412, tr.stats.npts)
from __future__ import print_function
from obspy.core import read, UTCDateTime
from obspy.core.util.geodetics import gps2DistAzimuth
from obspy.xseed import Parser
from math import log10
st = read("../data/LKBD.MSEED")
paz_wa = {
'sensitivity': 2800,
'zeros': [0j],
'gain': 1,
'poles': [-6.2832 - 4.7124j, -6.2832 + 4.7124j]
}
parser = Parser("../data/LKBD.dataless")
paz_le3d5s = parser.getPAZ("CH.LKBD..EHZ")
st.simulate(paz_remove=paz_le3d5s, paz_simulate=paz_wa, water_level=10)
t = UTCDateTime("2012-04-03T02:45:03")
st.trim(t, t + 50)
tr_n = st.select(component="N")[0]
ampl_n = max(abs(tr_n.data))
tr_e = st.select(component="E")[0]
ampl_e = max(abs(tr_e.data))
ampl = max(ampl_n, ampl_e)
sta_lat = 46.38703
sta_lon = 7.62714
def multiplex(filename):
st = read(filename)
for trace in st:
path = os.path.join(_mseed_search_folder,
str(trace.stats.starttime.year),
trace.stats.network, trace.stats.station,
('%s.D') % (trace.stats.channel))
create_dir(path)
diff = trace.stats.endtime.day - trace.stats.starttime.day
rangediff = diff + 1
if diff == 0:
d = obspy.core.utcdatetime.UTCDateTime(trace.stats.starttime)
finalname = DataDir.filename(trace, d)
filepath = os.path.join(path, finalname)
trace.write(filepath, format='MSEED', reclen=512)
elif diff >= 1:
for i in xrange(rangediff):
mult = 60 * 60 * 24 * i
if i == 0:
s1 = trace.stats.starttime
e1 = obspy.core.utcdatetime.UTCDateTime(year=s1.year,
month=s1.month,
day=s1.day,
hour=23,
minute=59,
second=59,
microsecond=999999)
else:
s1 = trace.stats.starttime + mult
s1 = obspy.core.utcdatetime.UTCDateTime(year=s1.year,
month=s1.month,
day=s1.day,
hour=0,
minute=0,
microsecond=00)
e1 = obspy.core.utcdatetime.UTCDateTime(year=s1.year,
month=s1.month,
day=s1.day,
hour=23,
minute=59,
second=59,
microsecond=999999)
if i == diff:
e1 = trace.stats.endtime
d = obspy.core.utcdatetime.UTCDateTime(s1)
finalname = DataDir.filename(trace, d)
filepath = os.path.join(path, finalname)
tr = trace.slice(s1, e1)
tr.write(filepath, format='MSEED', reclen=512)
print s1, ' to ', e1, jd, finalname, filepath
#endif
#endfor
#hs+
# "remove" unused channels
#
channels = []
for trace in st:
channels.append(
trace.stats.channel) # get all channels from trace list
channnels = sorted(channels)
group = [['BHE', 'BHN', 'BHZ'], ['BH1', 'BH2', 'BHZ'],
['HHE', 'HHN', 'HHZ']] # use only these
used = []
for chn in channels: # build channel sets
if len(used) > 0: break
for i in range(3):
if chn in group[i]:
used = group[i] # use this set
break
#endfor
trace = st[0]
path = os.path.join(_mseed_search_folder, str(trace.stats.starttime.year),
trace.stats.network, trace.stats.station)
for chn in channels:
if chn in used: continue
# replace unused channels(files) with magic number '4711'
dir = os.path.join(path, ('%s.D') % (chn))
if os.path.exists(dir):
files = os.listdir(dir)
line = '4711'
for file in files:
Basic.writeTextFile(os.path.join(dir, file), line)
ffile= open('Results_Swept_Sine' + sta,'w')
for idx, pair in enumerate(zip(chans,stimes)):
stime = pair[1] + 125.
chan = pair[0]
#stime = pair[1]
etime = stime + 225.
#etime = stime + 300.
datapath = 'newdata/output_raw/2017/XX/' + sta + '/' + chan + '.D/XX*'
st = read(datapath)
st.decimate(5)
st.decimate(2)
stRef = read('newdata/Tcmpct/gto.seed')
if chan == 'HHE':
stRef = stRef.select(channel='EH2')
elif chan == 'HHN':
stRef = stRef.select(channel='EH1')
else:
stRef = stRef.select(channel='EH0')
st += stRef
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Fri Sep 29 12:19:56 2017
@author: horas
"""
from obspy.core import read
#from scipy.integrate import simps
#import numpy as np
#import matplotlib.pylab as plt
#from obspy.core import stream
st = read("KRK_full.MSEED")
print st
print '\n'
print st[0].data
print '\n'
print type(st)
print '\n'
print st.traces
print '\n'
print st[0].stats
print '\n'
print st[0].stats.delta, '|', st[0].stats.endtime
print '\n'
print st
print st[0]
def get_streams_gema_old(networks,
stations,
starttime,
endtime,
only_vertical_channel=False,
local_dir_name=None):
if not local_dir_name:
local_dir_name = "%s/mount" % (os.getenv("HOME"))
r = requests.get(r'http://jsonip.com')
public_ip = r.json()['ip']
if (socket.gethostname() == 'maniedba') and (public_ip == "152.74.135.51"):
local_buffer = "/home/gema/seiscomp3/var/lib/seedlink/buffer"
local_archive = "/home/gema/seiscomp3/var/lib/archive "
else:
local_buffer = "%s/seiscomp_data_buffer" % (local_dir_name)
local_archive = "%s/seiscomp_data_archive" % (local_dir_name)
st = Stream()
if only_vertical_channel:
channels = "*Z"
else:
channels = "*"
# read archive directory
for network, station in zip(networks, stations):
this_day = starttime
while this_day <= endtime:
pattern = '%s/%s/%s/%s/%s.D' % (local_archive,
this_day.strftime("%Y"), network,
station, channels)
paths_ch = sorted(glob.glob(pattern))
for path in paths_ch:
pattern = "%s/*%s" % (path, this_day.strftime("%Y.%03j"))
msfile_list = glob.glob(pattern)
if len(msfile_list) > 0:
for msfile in msfile_list:
st += read(msfile,
starttime=starttime,
endtime=endtime)
this_day += 86400
gaps = st.get_gaps()
# read buffer directory
if UTCDateTime().now() - endtime <= 3600:
for network, station in zip(networks, stations):
path = '%s/%s/segments' % (local_buffer, station)
name_list = os.listdir(path)
full_list = [os.path.join(path, i) for i in name_list]
time_sorted_list = sorted(full_list, key=os.path.getmtime)
msfiles = time_sorted_list[-3::]
for msfile in msfiles:
st += read(msfile, starttime=starttime,
endtime=endtime).select(channel=channels)
if len(st) > 1:
st.merge(method=1,
interpolation_samples=-1,
fill_value='interpolate')
return st, gaps
def slice_from_reading(reading_path,
waveforms_path,
slice_duration=5,
archive_definitions=[],
output_level=0):
"""
Reads S-file on reading_path and slice relevant waveforms in waveforms_path
:param reading_path: string path to S-file
:param waveforms_path: string path to folder with waveform files
:param slice_duration: int duration of the slice in seconds
:param archive_definitions: list list of archive definition tuples (see utils/seisan_reader.py)
:param output_level: int 0 - min output, 5 - max output, default - 0
:return: -1 - corrupted file
[(obspy.core.trace.Trace, string)] - list of slice tuples: (slice, name of waveform file)
"""
if output_level >= 5:
logging.info('Reading file: ' + reading_path)
try:
events = nordic_reader.read_nordic(
reading_path,
True) # Events tuple: (event.Catalog, [waveforms file names])
except nordic_reader.NordicParsingError as error:
if output_level >= 2:
logging.warning('In ' + reading_path + ': ' + str(error))
return -1
except ValueError as error:
if output_level >= 2:
logging.warning('In ' + reading_path + ': ' + str(error))
return -1
except AttributeError as error:
if output_level >= 2:
logging.warning('In ' + reading_path + ': ' + str(error))
return -1
index = -1
slices = []
picks_line = "STAT SP IPHASW"
for event in events[0].events:
index += 1
f = open(reading_path)
l = [line.strip() for line in f]
id = None
picks_started = False
picks_amount = len(event.picks)
picks_read = 0
picks_distance = []
if config.seconds_high_precision:
start_seconds = []
for line in l:
if picks_started and picks_read < picks_amount and len(line) >= 74:
try:
dist = float(line[70:74])
except ValueError as e:
dist = None
picks_distance.append(dist)
if config.seconds_high_precision:
try:
seconds = float(line[21:27])
except ValueError as e:
seconds = None
start_seconds.append(seconds)
if len(line) > 73:
title = line[0:6]
if title == "ACTION":
id_title = line[56:59]
if id_title == "ID:":
id_str = line[59:73]
id = int(id_str)
if len(line) > 25:
if line[0:len(picks_line)] == picks_line:
picks_started = True
# Min magnitude check
if len(event.magnitudes) > 0:
if event.magnitudes[0].mag < config.min_magnitude:
continue
# Max depth check
if len(event.origins) > 0:
if event.origins[0].depth is None:
continue
if event.origins[0].depth > config.max_depth:
continue
try:
if len(event.picks) > 0: # Only for files with picks
if output_level >= 3:
logging.info('File: ' + reading_path + ' Event #' +
str(index) + ' Picks: ' +
str(len(event.picks)))
picks_index = -1
for pick in event.picks:
if output_level >= 3:
logging.info('\t' + str(pick))
picks_index += 1
if config.seconds_high_precision:
if picks_index < len(start_seconds):
start_seconds_pick = start_seconds[picks_index]
else:
start_seconds_pick = pick.time.second
print("OUT OF BOUNDS START SECONDS PICK")
print("FILE: " + reading_path)
print("PICKS: ")
for pick_print in event.picks:
print(str(pick_print))
else:
start_seconds_pick = pick.time.seconds
pick_time = UTCDateTime(pick.time.year, pick.time.month,
pick.time.day, pick.time.hour,
pick.time.minute,
start_seconds_pick)
if picks_index < len(picks_distance) and picks_distance[
picks_index] is not None:
if picks_distance[picks_index] > config.max_dist:
continue
# Check phase
if pick.phase_hint != 'S' and pick.phase_hint != 'P':
logging.info('\t' + 'Neither P nor S phase. Skipping.')
continue
if output_level >= 3:
logging.info('\t' + 'Slices:')
# Checking archives
found_archive = False
if len(archive_definitions) > 0:
station = pick.waveform_id.station_code
station_archives = seisan.station_archives(
archive_definitions, station)
channel_slices = []
for x in station_archives:
if x[4] <= pick_time:
if x[5] is not None and pick_time > x[5]:
continue
else:
archive_file_path = seisan.archive_path(
x, pick_time.year, pick_time.julday,
config.archives_path, output_level)
if os.path.isfile(archive_file_path):
try:
arch_st = read(archive_file_path)
except TypeError as error:
if output_level >= 2:
logging.warning(
'In ' + archive_file_path +
': ' + str(error))
return -1
# arch_st.normalize(global_max=config.global_max_normalizing) # remove that
# arch_st.filter("highpass", freq=config.highpass_filter_df) # remove that
# line later
for trace in arch_st:
pick_start_time = pick_time
if trace.stats.starttime > pick_time or pick_time + slice_duration >= trace.stats.endtime:
logging.info(
'\t\tArchive ' +
archive_file_path +
' does not cover required slice interval'
)
continue
shifted_time = pick_time - config.static_slice_offset
end_time = shifted_time + slice_duration
found_archive = True
trace_slice = trace.slice(
shifted_time, end_time)
if output_level >= 3:
logging.info('\t\t' +
str(trace_slice))
trace_file = x[0] + str(
x[4].year) + str(
x[4].julday
) + x[1] + x[2] + x[3]
event_id = x[0] + str(
x[4].year) + str(
x[4].julday) + x[2] + x[3]
slice_name_station_channel = (
trace_slice, trace_file, x[0],
x[1], event_id,
pick.phase_hint, id_str)
# print("ID " + str(id_str))
# if id_str == '20140413140958':
# print(x[0])
# if True:#x[0] == 'NKL':
# trace.integrate()
# trace_slice.integrate()
# trace.normalize()
# trace_slice.normalize()
# print('FOUND ID! NORMALIZED')
# print('ARCHIVE: ' + archive_file_path)
# print('FILE: ' + trace_file)
# print('SLICE: ' + str(trace_slice))
# print('TIME: ' + str(shifted_time) + ' till ' + str(end_time))
# print('TRACE: ' + str(trace))
# print('DATA: ' + str(trace_slice.data))
# trace_slice.filter("highpass", freq=config.highpass_filter_df)
# patho = "/seismo/seisan/WOR/chernykh/plots/part/"
# patho2 = "/seismo/seisan/WOR/chernykh/plots/whole/"
# plt.plot(trace_slice.data)
# plt.ylabel('Amplitude')
# plt.savefig(patho + trace_file)
# plt.figure()
# plt.plot(trace.data)
# plt.ylabel('Amplitude')
# plt.savefig(patho2 + trace_file)
# plt.figure()
if len(trace_slice.data) >= 400:
channel_slices.append(
slice_name_station_channel)
# Read and slice waveform
if found_archive:
if len(channel_slices) > 0:
slices.append(channel_slices)
continue
except ValueError as error:
if output_level >= 2:
logging.warning('In ' + reading_path + ': ' + str(error))
continue
return sort_slices(slices)
def test_issue296(self):
"""
Tests issue #296.
"""
tempfile = NamedTemporaryFile().name
# 1 - transform to np.float64 values
st = read()
for tr in st:
tr.data = tr.data.astype('float64')
# write a single trace automatically detecting encoding
st[0].write(tempfile, format="MSEED")
# write a single trace automatically detecting encoding
st.write(tempfile, format="MSEED")
# write a single trace with encoding 5
st[0].write(tempfile, format="MSEED", encoding=5)
# write a single trace with encoding 5
st.write(tempfile, format="MSEED", encoding=5)
# 2 - transform to np.float32 values
st = read()
for tr in st:
tr.data = tr.data.astype('float32')
# write a single trace automatically detecting encoding
st[0].write(tempfile, format="MSEED")
# write a single trace automatically detecting encoding
st.write(tempfile, format="MSEED")
# write a single trace with encoding 4
st[0].write(tempfile, format="MSEED", encoding=4)
# write a single trace with encoding 4
st.write(tempfile, format="MSEED", encoding=4)
# 3 - transform to np.int32 values
st = read()
for tr in st:
tr.data = tr.data.astype('int32')
# write a single trace automatically detecting encoding
st[0].write(tempfile, format="MSEED")
# write a single trace automatically detecting encoding
st.write(tempfile, format="MSEED")
# write a single trace with encoding 3
st[0].write(tempfile, format="MSEED", encoding=3)
# write the whole stream with encoding 3
st.write(tempfile, format="MSEED", encoding=3)
# write a single trace with encoding 10
st[0].write(tempfile, format="MSEED", encoding=10)
# write the whole stream with encoding 10
st.write(tempfile, format="MSEED", encoding=10)
# write a single trace with encoding 11
st[0].write(tempfile, format="MSEED", encoding=11)
# write the whole stream with encoding 11
st.write(tempfile, format="MSEED", encoding=11)
# 4 - transform to np.int16 values
st = read()
for tr in st:
tr.data = tr.data.astype('int16')
# write a single trace automatically detecting encoding
st[0].write(tempfile, format="MSEED")
# write a single trace automatically detecting encoding
st.write(tempfile, format="MSEED")
# write a single trace with encoding 1
st[0].write(tempfile, format="MSEED", encoding=1)
# write the whole stream with encoding 1
st.write(tempfile, format="MSEED", encoding=1)
# 5 - transform to ASCII values
st = read()
for tr in st:
tr.data = tr.data.astype('|S1')
# write a single trace automatically detecting encoding
st[0].write(tempfile, format="MSEED")
# write a single trace automatically detecting encoding
st.write(tempfile, format="MSEED")
# write a single trace with encoding 0
st[0].write(tempfile, format="MSEED", encoding=0)
# write the whole stream with encoding 0
st.write(tempfile, format="MSEED", encoding=0)
# cleanup
os.remove(tempfile)
def main(argv=sys.argv):
#Earth's parameters
#~ beta = 4.e3 #m/s
#~ rho = 3.e3 #kg/m^3
#~ mu = rho*beta*beta
PLotSt = [
"IU.TRQA.00.LHZ", "IU.LVC.00.LHZ", "II.NNA.00.LHZ", "IU.RAR.00.LHZ"
]
#PlotSubf = [143, 133, 123, 113, 103, 93,
# 83, 73, 63, 53]
PlotSubf = [6, 3]
#Set rup_vel = 0 to have a point source solution
RupVel = 2.1 #Chilean eq from Lay et al
t_h = 10. # Half duration for each sf
noiselevel = 0.0 # L1 norm level of noise
mu = 40e9
#W-Phase filter
corners = 4.
fmin = 0.001
fmax = 0.005
### Data from Chilean 2010 EQ (Same as W phase inv.)
strike = 18.
dip = 18.
rake = 104. # 109.
rakeA = rake + 45.
rakeB = rake - 45.
### Fault's grid parameters
nsx = 21 #Number of sf along strike
nsy = 11 #Number of sf along dip
flen = 600. #Fault's longitude [km] along strike
fwid = 300. #Fault's longitude [km] along dip
direc = 0 #Directivity 0 = bilateral
Min_h = 10. #Min depth of the fault
### Derivated parameters:
nsf = nsx * nsy
sflen = flen / float(nsx)
sfwid = fwid / float(nsy)
swp = [1, 0, 2] # useful to swap (lat,lon, depth)
mindist = flen * fwid # minimun dist to the hypcen (initializing)
###Chessboard
#weight = np.load("RealSol.npy")
weight = np.zeros(nsf)
weight[::2] = 1
#weight[::2] = 1
#~ weight[10]=15
#~ weight[5001]=10
#~ weight[3201]=2
## Setting dirs and reading files.
GFdir = "/home/roberto/data/GFS/"
workdir = os.path.abspath(".") + "/"
datadir = workdir + "DATA/"
tracesfilename = workdir + "goodtraces.dat"
tracesdir = workdir + "WPtraces/"
try:
reqfilename = glob.glob(workdir + '*.syn.req')[0]
except IndexError:
print "There is not *.syn.req file in the dir"
sys.exit()
basename = reqfilename.split("/")[-1][:-4]
if not os.path.exists(tracesfilename):
print tracesfilename, "does not exist."
exit()
if not os.path.exists(datadir):
os.makedirs(datadir)
if not os.path.exists(tracesdir):
os.makedirs(tracesdir)
tracesfile = open(tracesfilename)
reqfile = open(reqfilename)
trlist = readtraces(tracesfile)
eqdata = readreq(reqfile)
tracesfile.close()
reqfile.close()
####Hypocentre from
### http://earthquake.usgs.gov/earthquakes/eqinthenews/2010/us2010tfan/
cmteplat = -35.91 #-35.85#-36.03#-35.83
cmteplon = -72.73 #-72.72#-72.83# -72.67
cmtepdepth = 35.
eq_hyp = (cmteplat, cmteplon, cmtepdepth)
############
# Defining the sf system
grid, sblt = fault_grid('CL-2010',
cmteplat,
cmteplon,
cmtepdepth,
direc,
Min_h,
strike,
dip,
rake,
flen,
fwid,
nsx,
nsy,
Verbose=False,
ffi_io=True,
gmt_io=True)
print('CL-2010', cmteplat, cmteplon, cmtepdepth, direc, Min_h, strike, dip,
rake, flen, fwid, nsx, nsy)
print grid[0][1]
#sys.exit()
#This calculation is inside of the loop
#~ NP = [strike, dip, rake]
#~ M = np.array(NodalPlanetoMT(NP))
#~ Mp = np.sum(M**2)/np.sqrt(2)
#############################################################################
######Determining the sf closest to the hypocentre:
min_Dist_hyp_subf = flen * fwid
for subf in range(nsf):
sblat = grid[subf][1]
sblon = grid[subf][0]
sbdepth = grid[subf][2]
sf_hyp = (sblat, sblon, sbdepth)
Dist_hyp_subf = hypo2dist(eq_hyp, sf_hyp)
if Dist_hyp_subf < min_Dist_hyp_subf:
min_Dist_hyp_subf = Dist_hyp_subf
min_sb_hyp = sf_hyp
hyp_subf = subf
####Determining trimming times:
test_tr = read(GFdir + "H003.5/PP/GF.0001.SY.LHZ.SAC")[0]
t0 = test_tr.stats.starttime
TrimmingTimes = {} # Min. Distace from the fault to each station.
A = 0
for trid in trlist:
metafile = workdir + "DATA/" + "META." + trid + ".xml"
META = DU.getMetadataFromXML(metafile)[trid]
stlat = META['latitude']
stlon = META['longitude']
dist = locations2degrees(min_sb_hyp[0],min_sb_hyp[1],\
stlat,stlon)
parrivaltime = getTravelTimes(dist, min_sb_hyp[2])[0]['time']
ta = t0 + parrivaltime
tb = ta + round(15. * dist)
TrimmingTimes[trid] = (ta, tb)
###########################
DIST = []
# Ordering the stations in terms of distance
for trid in trlist:
metafile = workdir + "DATA/" + "META." + trid + ".xml"
META = DU.getMetadataFromXML(metafile)[trid]
lat = META['latitude']
lon = META['longitude']
trdist = locations2degrees(cmteplat, cmteplon, lat, lon)
DIST.append(trdist)
DistIndex = lstargsort(DIST)
trlist = [trlist[i] for i in DistIndex]
stdistribution = StDistandAzi(trlist, eq_hyp, workdir + "DATA/")
StDistributionPlot(stdistribution)
#exit()
#Main loop
for subf in range(nsf):
print subf
sflat = grid[subf][1]
sflon = grid[subf][0]
sfdepth = grid[subf][2]
#~ strike = grid[subf][3] #+ 360.
#~ dip = grid[subf][4]
#~ rake = grid[subf][5] #
NP = [strike, dip, rake]
NPA = [strike, dip, rakeA]
NPB = [strike, dip, rakeB]
M = np.array(NodalPlanetoMT(NP))
MA = np.array(NodalPlanetoMT(NPA))
MB = np.array(NodalPlanetoMT(NPB))
#Time delay is calculated as the time in which
#the rupture reach the subfault
sf_hyp = (sflat, sflon, sfdepth)
Dist_ep_subf = hypo2dist(eq_hyp, sf_hyp)
if Dist_ep_subf < mindist:
mindist = Dist_ep_subf
minsubf = subf
if RupVel == 0:
t_d = eqdata['time_shift']
else:
t_d = round(Dist_ep_subf / RupVel) #-59.
print sflat, sflon, sfdepth
# Looking for the best depth dir:
depth = []
depthdir = []
for file in os.listdir(GFdir):
if file[-2:] == ".5":
depthdir.append(file)
depth.append(float(file[1:-2]))
BestDirIndex = np.argsort(abs(sfdepth\
- np.array(depth)))[0]
hdir = GFdir + depthdir[BestDirIndex] + "/"
###
SYN = np.array([])
SYNA = np.array([])
SYNB = np.array([])
for trid in trlist:
metafile = workdir + "DATA/" + "META." + trid + ".xml"
META = DU.getMetadataFromXML(metafile)[trid]
lat = META['latitude']
lon = META['longitude']
#Subfault loop
#GFs Selection:
##Change to folloing loop
dist = locations2degrees(sflat, sflon, lat, lon)
azi = -np.pi / 180. * gps2DistAzimuth(lat, lon, sflat, sflon)[2]
trPPsy, trRRsy, trRTsy, trTTsy = \
GFSelectZ(hdir,dist)
trROT = MTrotationZ(azi, trPPsy, trRRsy, trRTsy, trTTsy)
orig = trROT[0].stats.starttime
dt = trROT[0].stats.delta
trianglen = 2. * int(t_h / dt) - 1.
FirstValid = int(trianglen / 2.) + 1 # to delete
window = triang(trianglen)
window /= np.sum(window)
#window = np.array([1.])
parrivaltime = getTravelTimes(dist, sfdepth)[0]['time']
t1 = TrimmingTimes[trid][0] - t_d
t2 = TrimmingTimes[trid][1] - t_d
for trR in trROT:
trR.data *= 10.**-21 ## To get M in Nm
trR.data -= trR.data[0]
AUX1 = len(trR)
trR.data = convolve(trR.data, window, mode='valid')
AUX2 = len(trR)
mean = np.mean(np.hstack((trR.data[0]*np.ones(FirstValid),\
trR.data[:60./trR.stats.delta*1.-FirstValid+1])))
#mean = np.mean(trR.data[:60])
trR.data -= mean
trR.data = bp.bandpassfilter(trR.data,len(trR), trR.stats.delta,\
corners , 1 , fmin, fmax)
t_l = dt * 0.5 * (AUX1 - AUX2)
trR.trim(t1 - t_l, t2 - t_l, pad=True, fill_value=trR.data[0]
) #We lost t_h due to the convolution
#~ for trR in trROT:
#~ trR.data *= 10.**-23 ## To get M in Nm
#~ trR.data -= trR.data[0]
#~ trR.data = convolve(trR.data,window,mode='same')
#~ #mean = np.mean(np.hstack((trR.data[0]*np.ones(FirstValid),\
#~ #trR.data[:60./trR.stats.delta*1.-FirstValid+1])))
#~ mean = np.mean(trR.data[:60])
#~ trR.data -= mean
#~ trR.data = bp.bandpassfilter(trR.data,len(trR), trR.stats.delta,\
#~ corners , 1 , fmin, fmax)
#~ trR.trim(t1,t2,pad=True, fill_value=trR.data[0])
trROT = np.array(trROT)
syn = np.dot(trROT.T, M)
synA = np.dot(trROT.T, MA)
synB = np.dot(trROT.T, MB)
SYN = np.append(SYN, syn)
SYNA = np.append(SYNA, synA)
SYNB = np.append(SYNB, synB)
print np.shape(A), np.shape(np.array([SYN]))
if subf == 0:
A = np.array([SYN])
AA = np.array([SYNA])
AB = np.array([SYNB])
else:
A = np.append(A, np.array([SYN]), 0)
AA = np.append(AA, np.array([SYNA]), 0)
AB = np.append(AB, np.array([SYNB]), 0)
AC = np.vstack((AA, AB))
print np.shape(AC)
print np.shape(weight)
B = np.dot(A.T, weight)
stsyn = Stream()
n = 0
Ntraces = {}
for trid in trlist:
spid = trid.split(".")
print trid
NMIN = 1. + (TrimmingTimes[trid][1] - TrimmingTimes[trid][0]) / dt
Ntraces[trid] = (n, NMIN + n)
trsyn = Trace(B[n:NMIN + n])
n += NMIN
trsyn.stats.network = spid[0]
trsyn.stats.station = spid[1]
trsyn.stats.location = spid[2]
trsyn.stats.channel = spid[3]
trsyn = AddNoise(trsyn, level=noiselevel)
#trsyn.stats.starttime =
stsyn.append(trsyn)
stsyn.write(workdir + "WPtraces/" + basename + ".decov.trim.mseed",
format="MSEED")
#####################################################
# Plotting:
#####################################################
#we are going to reflect the y axis later, so:
print minsubf
hypsbloc = [minsubf / nsy, -(minsubf % nsy) - 2]
#Creating the strike and dip axis:
StrikeAx = np.linspace(0, flen, nsx + 1)
DipAx = np.linspace(0, fwid, nsy + 1)
DepthAx = DipAx * np.sin(np.pi / 180. * dip) + Min_h
hlstrike = StrikeAx[hypsbloc[0]] + sflen * 0.5
hldip = DipAx[hypsbloc[1]] + sfwid * 0.5
hldepth = DepthAx[hypsbloc[1]] + sfwid * 0.5 * np.sin(np.pi / 180. * dip)
StrikeAx = StrikeAx - hlstrike
DipAx = DipAx - hldip
XX, YY = np.meshgrid(StrikeAx, DepthAx)
XX, ZZ = np.meshgrid(StrikeAx, DipAx)
sbarea = sflen * sfwid
SLIPS = weight.reshape(nsx, nsy).T #[::-1,:]
SLIPS /= mu * 1.e6 * sbarea
######Plot:#####################
plt.figure()
ax = host_subplot(111)
im = ax.pcolor(XX, YY, SLIPS, cmap="jet")
ax.set_ylabel('Depth [km]')
ax.set_ylim(DepthAx[-1], DepthAx[0])
# Creating a twin plot
ax2 = ax.twinx()
#im2 = ax2.pcolor(XX, ZZ, SLIPS[::-1,:], cmap="Greys")
im2 = ax2.pcolor(XX, ZZ, SLIPS[::-1, :], cmap="jet")
ax2.set_ylabel('Distance along the dip [km]')
ax2.set_xlabel('Distance along the strike [km]')
ax2.set_ylim(DipAx[0], DipAx[-1])
ax2.set_xlim(StrikeAx[0], StrikeAx[-1])
ax.axis["bottom"].major_ticklabels.set_visible(False)
ax2.axis["bottom"].major_ticklabels.set_visible(False)
ax2.axis["top"].set_visible(True)
ax2.axis["top"].label.set_visible(True)
divider = make_axes_locatable(ax)
cax = divider.append_axes("bottom", size="5%", pad=0.1)
cb = plt.colorbar(im, cax=cax, orientation="horizontal")
cb.set_label("Slip [m]")
ax2.plot([0], [0], '*', ms=225. / (nsy + 4))
ax2.set_xticks(ax2.get_xticks()[1:-1])
#ax.set_yticks(ax.get_yticks()[1:])
#ax2.set_yticks(ax2.get_yticks()[:-1])
#########Plotting the selected traces:
nsp = len(PLotSt) * len(PlotSubf)
plt.figure(figsize=(13, 11))
plt.title("Synthetics for rake = " + str(round(rake)))
mindis = []
maxdis = []
for i, trid in enumerate(PLotSt):
x = np.arange(0, Ntraces[trid][1] - Ntraces[trid][0], dt)
for j, subf in enumerate(PlotSubf):
y = A[subf, Ntraces[trid][0]:Ntraces[trid][1]]
if j == 0:
yy = y
else:
yy = np.vstack((yy, y))
maxdis.append(np.max(yy))
mindis.append(np.min(yy))
for i, trid in enumerate(PLotSt):
x = np.arange(0, Ntraces[trid][1] - Ntraces[trid][0], dt)
for j, subf in enumerate(PlotSubf):
y = A[subf, Ntraces[trid][0]:Ntraces[trid][1]]
plt.subplot2grid((len(PlotSubf), len(PLotSt)), (j, i))
plt.plot(x, y, linewidth=2.5)
if j == 0:
plt.title(trid)
fig = plt.gca()
fig.axes.get_yaxis().set_ticks([])
fig.set_ylabel(str(subf), rotation=0)
fig.set_xlim((x[0], x[-1]))
fig.set_ylim((mindis[i], maxdis[i]))
if subf != PlotSubf[-1]:
fig.axes.get_xaxis().set_ticks([])
plt.show()
def get_picks(reading_path, archive_definitions=[]):
"""
Reads S-file and slices waveforms for event
:param reading_path: path to S-file
:param archive_definitions: list of archive definitions
:return: list of lists of picks per station
"""
# Parse s-file and error checks
try:
events = nordic_reader.read_nordic(
reading_path,
True) # Events tuple: (event.Catalog, [waveforms file names]
except nordic_reader.NordicParsingError as e:
print("In {}: {}".format(reading_path, e)) # Throw exception?
return -1
except ValueError as e:
print("In {}: {}".format(reading_path, e)) # Throw exception?
return -1
except AttributeError as e:
print("In {}: {}".format(reading_path, e)) # Throw exception?
return -1
if len(events[0].events) != 1:
print("In {}: Events number is {}".format(
reading_path, len(events[0].events))) # Throw exception?
return -1
event = events[0].events[0]
if len(event.picks) == 0:
print("In {}: No picks!".format(reading_path)) # Throw exception?
return -1
# Parse S-file additional info
parsed_data = parse_s_file(reading_path, len(event.picks))
#print("Parsed data:", "{}".format(parsed_data), sep='\n')
event_id = parsed_data[0]
picks_dists = parsed_data[1]
picks_seconds = parsed_data[2]
# Min magnitude check
magnitude = None
if len(event.magnitudes) > 0:
magnitude = event.magnitudes[0].mag
# if event.magnitudes[0].mag < config.min_magnitude:
# print("In {}") Throw exception?
# return -1
# Max depth check
depth = None
if len(event.origins) > 0:
depth = event.origins[0].depth
# if event.origins[0].depth is None:
# print("In {}") Throw exception?
# return -1
# if event.origins[0].depth > config.max_depth:
# print("In {}") Throw exception?
# return -1
# else:
# print("In {}") Throw exception?
# return -1
# Picks slicing
index = -1
# List of picks: [[station, phase, distance, [archive_definition, archive_path, start, end, [archive trace slices]]]]
result_list = []
for pick in event.picks:
index += 1
# Get pick time
if config.seconds_high_precision:
if index < len(picks_seconds):
if picks_seconds[index] is not None:
pick_sec = picks_seconds[index]
else:
pick_sec = pick.time.second
else:
print(
"In {}: Index for picks is out of range for picks_seconds list!"
.format(reading_path)) # Throw exception?
return -1
else:
pick_sec = pick.time.second
time = UTCDateTime(pick.time.year, pick.time.month, pick.time.day,
pick.time.hour, pick.time.minute, pick_sec)
# Check pick distance
distance = None
if index < len(picks_dists):
distance = picks_dists[index]
# if picks_dists[index] is not None:
# if picks_dists[index] > config.max_dist:
# continue
# else:
# print("In {}") Throw exception?
# return -1
# Find pick in archives
station = pick.waveform_id.station_code
station_archives = seisan.station_archives(archive_definitions,
station)
archives_picks = [
] # [archive_definition, archive_path, start, end, [archive trace slices]]
for x in station_archives:
# Check if archive exists for current pick
if x[4] > time:
continue
if x[5] is not None and time + config.slice_duration - config.static_slice_offset > x[
5]:
continue
# Find archive
archive_path = seisan.archive_path(x, time.year, time.julday,
config.archives_path)
if not os.path.isfile(archive_path):
continue
try:
archive_st = read(archive_path)
except TypeError as e:
print("In {}: {}".format(reading_path, e)) # Throw exception?
return -1
# Get start and end time for pick
start_time = time - config.static_slice_offset
end_time = start_time + config.slice_duration
shifted_start_time = start_time # + time_shift
shifted_end_time = end_time # + time_shift
archive_picks_list = [] # [[start_time, end_time, trace_slice]]
for trace in archive_st:
if trace.stats.starttime > shifted_start_time or shifted_end_time >= trace.stats.endtime:
continue
trace_slice = trace.slice(shifted_start_time, shifted_end_time)
archive_picks_list.append([
trace_slice.stats.starttime, trace_slice.stats.endtime,
trace_slice
])
archives_picks.append([
x, archive_path, shifted_start_time, shifted_end_time, time,
archive_picks_list
])
result_list.append(
[station, pick.phase_hint, distance, archives_picks])
# [event_id, reading_path, magnitude, depth,
# [[station, phase, distance,
# [[archive_definition, archive_path, start, end, pick_time,
# [[start_time, end_time, archive_trace_slices]]
# ]]
# ]]
# ]
return [event_id, reading_path, magnitude, depth, result_list]
def preprocess(db, stations, comps, goal_day, params, responses=None):
"""
Fetches data for each ``stations`` and each ``comps`` using the
data_availability table in the database.
To correct for instrument responses, make sure to set ``remove_response``
to "Y" in the config and to provide the ``responses`` DataFrame.
:Example:
>>> from msnoise.api import connect, get_params, preload_instrument_responses
>>> from msnoise.preprocessing import preprocess
>>> db = connect()
>>> params = get_params(db)
>>> responses = preload_instrument_responses(db)
>>> st = preprocess(db, ["YA.UV06","YA.UV10"], ["Z",], "2010-09-01", params, responses)
>>> st
2 Trace(s) in Stream:
YA.UV06.00.HHZ | 2010-09-01T00:00:00.000000Z - 2010-09-01T23:59:59.950000Z | 20.0 Hz, 1728000 samples
YA.UV10.00.HHZ | 2010-09-01T00:00:00.000000Z - 2010-09-01T23:59:59.950000Z | 20.0 Hz, 1728000 samples
:type db: :class:`sqlalchemy.orm.session.Session`
:param db: A :class:`~sqlalchemy.orm.session.Session` object, as
obtained by :func:`msnoise.api.connect`.
:type stations: list of str
:param stations: a list of station names, in the format NET.STA.
:type comps: list of str
:param comps: a list of component names, in Z,N,E,1,2.
:type goal_day: str
:param goal_day: the day of data to load, ISO 8601 format: e.g. 2016-12-31.
:type params: class
:param params: an object containing the config parameters, as obtained by
:func:`msnoise.api.get_params`.
:type responses: :class:`pandas.DataFrame`
:param responses: a DataFrame containing the instrument responses, as
obtained by :func:`msnoise.api.preload_instrument_responses`.
:rtype: :class:`obspy.core.stream.Stream`
:return: A Stream object containing all traces.
"""
datafiles = {}
output = Stream()
MULTIPLEX = False
MULTIPLEX_files = {}
for station in stations:
datafiles[station] = {}
net, sta = station.split('.')
gd = datetime.datetime.strptime(goal_day, '%Y-%m-%d')
files = get_data_availability(db,
net=net,
sta=sta,
starttime=gd,
endtime=gd)
for comp in comps:
datafiles[station][comp] = []
for file in files:
if file.sta != "MULTIPLEX":
if file.comp[-1] not in comps:
continue
fullpath = os.path.join(file.path, file.file)
datafiles[station][file.comp[-1]].append(fullpath)
else:
MULTIPLEX = True
print("Mutliplex mode, reading the files")
fullpath = os.path.join(file.path, file.file)
multiplexed = sorted(glob.glob(fullpath))
for comp in comps:
for fn in multiplexed:
if fn in MULTIPLEX_files:
_ = MULTIPLEX_files[fn]
else:
# print("Reading %s" % fn)
_ = read(fn, format=params.archive_format or None)
traces = []
for tr in _:
if "%s.%s" % (
tr.stats.network, tr.stats.station
) in stations and tr.stats.channel[-1] in comps:
traces.append(tr)
del _
_ = Stream(traces=traces)
MULTIPLEX_files[fn] = _
datafiles[station][comp].append(_)
for istation, station in enumerate(stations):
net, sta = station.split(".")
for comp in comps:
files = eval("datafiles['%s']['%s']" % (station, comp))
if len(files) != 0:
logger.debug("%s.%s Reading %i Files" %
(station, comp, len(files)))
traces = []
for file in files:
if isinstance(file, Stream):
st = file.select(network=net,
station=sta,
component=comp).copy()
else:
try:
# print("Reading %s" % file)
# t= time.time()
st = read(file,
dytpe=np.float,
starttime=UTCDateTime(gd),
endtime=UTCDateTime(gd) + 86400,
station=sta,
format=params.archive_format or None)
# print("done in", time.time()-t)
except:
logger.debug("ERROR reading file %s" % file)
continue
for tr in st:
if len(tr.stats.channel) == 2:
tr.stats.channel += tr.stats.location
tr.stats.location = "00"
tmp = st.select(network=net, station=sta, component=comp)
if not len(tmp):
for tr in st:
tr.stats.network = net
st = st.select(network=net,
station=sta,
component=comp)
else:
st = tmp
for tr in st:
tr.data = tr.data.astype(np.float)
tr.stats.network = tr.stats.network.upper()
tr.stats.station = tr.stats.station.upper()
tr.stats.channel = tr.stats.channel.upper()
traces.append(tr)
del st
stream = Stream(traces=traces)
if not (len(stream)):
continue
f = io.BytesIO()
stream.write(f, format='MSEED')
f.seek(0)
stream = read(f, format="MSEED")
stream.sort()
# try:
# # HACK not super clean... should find a way to prevent the
# # same trace id with different sps to occur
# stream.merge(method=1, interpolation_samples=3, fill_value=None)
# except:
# logger.debug("Error while merging...")
# traceback.print_exc()
# continue
# stream = stream.split()
if not len(stream):
continue
logger.debug("%s Checking sample alignment" % stream[0].id)
for i, trace in enumerate(stream):
stream[i] = check_and_phase_shift(
trace, params.preprocess_taper_length)
logger.debug("%s Checking Gaps" % stream[0].id)
if len(getGaps(stream)) > 0:
max_gap = params.preprocess_max_gap * stream[
0].stats.sampling_rate
gaps = getGaps(stream)
while len(gaps):
too_long = 0
for gap in gaps:
if int(gap[-1]) <= max_gap:
try:
stream[gap[0]] = stream[gap[0]].__add__(
stream[gap[1]],
method=1,
fill_value="interpolate")
stream.remove(stream[gap[1]])
except:
stream.remove(stream[gap[1]])
break
else:
too_long += 1
if too_long == len(gaps):
break
gaps = getGaps(stream)
del gaps
stream = stream.split()
for tr in stream:
if tr.stats.sampling_rate < (params.goal_sampling_rate -
1):
stream.remove(tr)
taper_length = params.preprocess_taper_length # seconds
for trace in stream:
if trace.stats.npts < (4 * taper_length *
trace.stats.sampling_rate):
stream.remove(trace)
else:
trace.detrend(type="demean")
trace.detrend(type="linear")
trace.taper(max_percentage=None,
max_length=taper_length)
if not len(stream):
logger.debug(" has only too small traces, skipping...")
continue
for trace in stream:
logger.debug("%s Highpass at %.2f Hz" %
(trace.id, params.preprocess_highpass))
trace.filter("highpass",
freq=params.preprocess_highpass,
zerophase=True,
corners=4)
if trace.stats.sampling_rate != params.goal_sampling_rate:
logger.debug("%s Lowpass at %.2f Hz" %
(trace.id, params.preprocess_lowpass))
trace.filter("lowpass",
freq=params.preprocess_lowpass,
zerophase=True,
corners=8)
if params.resampling_method == "Resample":
logger.debug("%s Downsample to %.1f Hz" %
(trace.id, params.goal_sampling_rate))
trace.data = resample(
trace.data, params.goal_sampling_rate /
trace.stats.sampling_rate, 'sinc_fastest')
elif params.resampling_method == "Decimate":
decimation_factor = trace.stats.sampling_rate / params.goal_sampling_rate
if not int(decimation_factor) == decimation_factor:
logger.warning(
"%s CANNOT be decimated by an integer factor, consider using Resample or Lanczos methods"
" Trace sampling rate = %i ; Desired CC sampling rate = %i"
% (trace.id, trace.stats.sampling_rate,
params.goal_sampling_rate))
sys.stdout.flush()
sys.exit()
logger.debug("%s Decimate by a factor of %i" %
(trace.id, decimation_factor))
trace.data = trace.data[::int(decimation_factor)]
elif params.resampling_method == "Lanczos":
logger.debug("%s Downsample to %.1f Hz" %
(trace.id, params.goal_sampling_rate))
trace.data = np.array(trace.data)
trace.interpolate(
method="lanczos",
sampling_rate=params.goal_sampling_rate,
a=1.0)
trace.stats.sampling_rate = params.goal_sampling_rate
del trace
if params.remove_response:
logger.debug('%s Removing instrument response' %
stream[0].id)
response = responses[responses["channel_id"] ==
stream[0].id]
if len(response) > 1:
response = response[
response["start_date"] <= UTCDateTime(gd)]
if len(response) > 1:
response = response[
response["end_date"] >= UTCDateTime(gd)]
elif len(response) == 0:
logger.info("No instrument response information "
"for %s, skipping" % stream[0].id)
continue
try:
datalesspz = response["paz"].values[0]
except:
logger.error("Bad instrument response information "
"for %s, skipping" % stream[0].id)
continue
stream.simulate(
paz_remove=datalesspz,
remove_sensitivity=True,
pre_filt=params.response_prefilt,
paz_simulate=None,
)
for tr in stream:
tr.data = tr.data.astype(np.float32)
output += stream
del stream
del files
clean_scipy_cache()
del MULTIPLEX_files
return output
import glob
import time
import obspy
import numpy as np
from numpy import argmax
import matplotlib.pyplot as plt
#%% constants
shift = 100
step = 2
crite = 0.55 # REDUCED FROM V10
window = 45
fmin = 0.1
fmax = 10
#%% Read in sample waveforms with which to compare all waveforms
sample = read('/Users/william/Documents/lb01/14_330z.mseed')
trace = sample[0]
trace.detrend(type='demean')
trace.filter("bandpass", freqmin=fmin, freqmax=fmax)
#Explosion
start = sample[
0].stats.starttime + 2 * 60 * 60 + 22 * 60 + 12 #time window start - several s before Pwave arrival
end = start + window
trs = trace.slice(
starttime=start, endtime=end
) #cut out sample waveform with same window length as chosen event
trs_e = obspy.signal.filter.envelope(trs.data)
#print('reference waveform')
#trs.plot(type='relative',color='b', starttime=start , endtime=end)
#%%
etime = stime + 6. * 60. * 60.
length = 4 * 4096
overlap = 2 * 1024
f = open(
str(stime.year) + '_' + str(stime.julday).zfill(3) + '_' +
str(stime.hour).zfill(2) + '_' + str(stime.minute).zfill(2) +
'RESULTSLP', 'w')
for chan in chans:
st = Stream()
st += read('/tr1/telemetry_days/' + stas[0] + '/2016/2016_' +
str(stime.julday).zfill(3) + '/' + locs[0] + '_' + chan +
'.512.seed')
st += read('/tr1/telemetry_days/' + stas[1] + '/2016/2016_' +
str(stime.julday).zfill(3) + '/' + locs[1] + '_' + chan +
'.512.seed')
st += read('/tr1/telemetry_days/' + stas[2] + '/2016/2016_' +
str(stime.julday).zfill(3) + '/' + locs[2] + '_' + chan +
'.512.seed')
st.trim(starttime=stime, endtime=etime)
delta = st[0].stats.delta
instresp = computeresp(paz, delta, length)
(p11, fre1) = cp(st[0], st[0], length, overlap, delta)
ns_start, ns_end = 100.0, 400.0
sig_start, sig_end = 600, 800
back_az_vals = np.arange(-180.0, 180.0, 1.5)
trc_vel_vals = np.arange(250.0, 600.0, 2.5)
method="capon"
#p = mp.ProcessingPool(cpu_count() - 1)
p = Pool(cpu_count() - 1)
# ######################### #
# Read and #
# Filter Data #
# ######################### #
x, t, t0, geom = beamforming_new.stream_to_array_data(read(sac_glob))
M, N = x.shape
# ######################### #
# View Data #
# ######################### #
plt.figure(1)
for m in range(M):
plt.subplot(M, 1, m + 1)
plt.xlim([sig_start, sig_end])
plt.plot(t, x[m], '-k')
if m < (M - 1) : plt.setp(plt.subplot(M, 1, m + 1).get_xticklabels(), visible=False)
plt.show(block=False)
plt.figure(2)
plt.show(block=False)
def _cut_signal(trnm, dests, epsilon=1e-4):
"""
Return cut of positive & negative lags.
"""
I2 = read(trnm, format='SAC')[0]
# Check window length
sr = I2.stats.sampling_rate
bp, ep, en, bn = _cut_ends(I2)
tlen = ep - bp
if USE_CW and (tlen < PARAM['cut']['min_len']):
logger.debug(f'{basename(trnm)}: tlen = {tlen:.1f} s')
return {}
# SNR threshold on I2
sym = my.seis.sym_xc(I2)
try:
_snr = I2.stats.sac[KEY2SHD['snr']]
except (KeyError, AttributeError):
_snr = my.seis.snr(sym, **PARAM['snr'])
I2.stats.sac[KEY2SHD['snr']] = _snr
I2.write(trnm)
if _snr < PARAM['snr']['min']:
logger.debug(f'{basename(trnm)}: SNR = {_snr:.1f}')
return {}
# Check delta
_delta = I2.stats.delta
delta2 = PARAM['cut']['delta']
if abs(_delta - delta2) > epsilon:
logger.warning(f'Resample {trnm} (delta={_delta:g})')
I2.resample(sampling_rate=1 / delta2)
# Cut
if USE_CW:
sym.data = sym.data[int(bp * sr):]
sym.stats.sac.b = bp
sym.taper(max_percentage=0.05, type='hann', side='both')
if len(dests) == 1:
lags = [sym]
elif len(dests) == 2:
e = I2.stats.sac.e
plag = my.seis.sliced(I2, 0, e)
plag.stats.sac.b = 0
plag.stats.sac.e = e
nlag = my.seis.sliced(I2, -e, 0)
nlag.stats.sac.b = -e
nlag.stats.sac.e = 0
lags = [plag, nlag]
# 1-bit
if PARAM['preproc'].get('onebit', False):
for lag in lags:
lag.data = one_bit(lag.data)
# Whiten
if PARAM['preproc']['whiten'].get('val', False):
for lag in lags:
lag = whiten(lag, **PARAM['preproc']['whiten'])
# Mute
if USE_DW and getattr(PARAM['cut'], 'mute', True):
kwargs_mute = {
't1': bp,
't2': ep,
'sr': sr,
'precursor_only': PARAM['cut']['mute_prc_only'],
}
for i, lag in enumerate(lags):
# Negative lag
if i == 1:
lag.data = mute(lag.data[::-1], **kwargs_mute)[::-1]
else:
lag.data = mute(lag.data, **kwargs_mute)
d2l = {}
for lag, dest in zip(lags, dests):
d2l[dest] = lag
return d2l
vel = 1970
rho = 2400
R = 0.6
F = 2
win_len = 2.
example_events = [
20140718044958, 20140822015232, 20140910165727, 20140717144824
]
plt.figure(figsize=[6, 4])
for event in example_events:
for station in ['NOLF']:
name = 'Data/NOLF/GB.%s.%s.HHE.sac' % (station, event)
st = read(name)
name = 'Data/NOLF/GB.%s.%s.HHN.sac' % (station, event)
st += read(name)
s_arrival = st[0].stats.sac['t0']
print(st)
st_eq = st.copy()
start = st[0].stats.starttime
st_eq = st_eq.slice(start + s_arrival - 0.2,
start + s_arrival + win_len)
st_eq = st_eq.taper(type='cosine', max_percentage=0.05)
delta = st[0].stats.delta
sumnois3coh = []
s1n1 = []
s2n2 = []
s1s2n1n2 = []
#Slep width set here
slepwid = 0.025
slepper = 0.05
#As we will be making multiple figures in a loop, we need a counter
fignum = 1
#Reading in traces and setting phase lags and lowtimes/hightimes, also performing unnormalised cross correlations
#And pulling out phase coherence values
for j in range(0, len(biglist)):
stime = -100
#Copy traces so you don't overwrite them
trorig = read(lilist[j])
tr2orig = read(biglist[j])
listoff.append((lilist[j], biglist[j]))
tr = trorig.copy()
tr2 = tr2orig.copy()
#Applying processing to trace no. 2, this consists of a simple taper, filter and cut
arr1 = tr[0]
arr2 = tr2[0]
t71 = arr1.stats.sac.t7
t72 = arr2.stats.sac.t7
low2 = t72
temp = tr2[0].stats.starttime
hi2 = t72 + 200
tr2cop = tr2.copy()
tr2cop.trim(temp + (low2 * 0.01), temp + (hi2 * 0.01))
def _source_specifc_interferogram(trnm1, trnm2, rec1, rec2, src, lags,
**kwargs):
"""
Construct a source-specific interferogram (:math:`C_3`), i.e.,
interferogram of two :math:`I_2`.
:param rec1: Name of the first receiver-station.
:param rec2: Name of the second receiver-station.
:param src: Name of the source-station.
:param lags: Use which lags for I3.
:param dir_src: If save source direction to SAC header.
"""
dest = get_fnm('C3', rec1, sta2=rec2, sta3=src, lags=lags)
if PARAM['skip']['C3'] and exists(dest):
logger.debug(f'{dest} already exists.')
if PARAM['write']['stack']:
return dest, read(dest, format='SAC')[0]
else:
return None, None
tr1 = DEST2LAG[trnm1]
tr2 = DEST2LAG[trnm2]
# Find common part
if USE_CW:
tr1, tr2 = overlap(tr1, tr2, lags)
# Flip negative lag
if PARAM['interferometry']['flip_nlag']:
flip_nlag(tr1, tr2, lags)
# Do interferometry
if USE_DW and PARAM['interferometry']['phase_shift']:
kwa_ps = {
'delta': tr1.stats.delta,
'dr': kwargs.get('dr'),
'per': kwargs.get('phprper'),
'pv': kwargs.get('phprvel'),
}
if CONV:
C3 = xc_ps(tr1, tr2, **kwa_ps, **PARAM['interferometry'])
elif CORR:
xc = my.seis.x_cor(tr1, tr2, **PARAM['interferometry'])
C3 = pick_lag(xc, kwargs.get('dir_src'))
C3 = phase_shift(data=C3, **kwa_ps)
else:
C3 = my.seis.x_cor(tr1, tr2, **PARAM['interferometry'])
if USE_DW and CORR and PARAM['interferometry']['pick_lag']:
C3 = pick_lag(C3, kwargs.get('dir_src'))
# Make header
b = -int(np.floor(C3.size / 2) / tr1.stats.delta)
if USE_CW:
if PARAM['interferometry'].get('Welch', False):
b = -PARAM['interferometry']['subwin']
if USE_DW:
if CONV or PARAM['interferometry']['pick_lag']:
b = 0
if PARAM['interferometry']['symmetric'] or CONV:
nsided = 1
else:
nsided = 2
header = my.seis.sachd(
**{
'b': b,
'e': int(b + C3.size * tr1.stats.delta),
'delta': tr1.stats.delta,
'npts': C3.size,
'kevnm': src,
'evlo': STNM2LOLA[src][0],
'evla': STNM2LOLA[src][1],
'knetwk': STA2NET[src],
'kstnm': rec2,
'stlo': STNM2LOLA[rec2][0],
'stla': STNM2LOLA[rec2][1],
'dist': kwargs.get('dist', DEF_SHD),
KEY2SHD['net_rec']: STA2NET[rec2], # to be consistent with I2
KEY2SHD['src_sta']: src,
KEY2SHD['src_net']: STA2NET[src],
KEY2SHD['nsided']: nsided,
KEY2SHD['dr']: kwargs.get('dr', DEF_SHD),
KEY2SHD['theta']: kwargs.get('theta', DEF_SHD),
KEY2SHD['dir_src']: kwargs.get('dir_src', DEF_SHD),
KEY2SHD['min_srdist']: kwargs.get('min_srdist', DEF_SHD),
})
# Make Trace
C3_tr = Trace(header=header, data=C3)
if USE_CW and PARAM['interferometry']['symmetric']:
C3_tr = my.seis.sym_xc(C3_tr)
if CONV and PARAM['interferometry'].get('trim_conv', True):
i = int(PARAM['cut']['te'] / PARAM['cut']['delta']) + 1
C3_tr.data = C3_tr.data[:i]
return dest, C3_tr
if not os.path.isfile(wavenptp_1) and os.path.isfile(wavenptp):
shutil.move(wavenptp, events_dir_back)
else:
print(wavenptp_1, "exist !")
if not os.path.isfile(waveeptp_1) and os.path.isfile(waveeptp):
shutil.move(waveeptp, events_dir_back)
else:
print(waveeptp_1, "exist !")
if not os.path.isfile(wavezptp_1) and os.path.isfile(wavezptp):
shutil.move(wavezptp, events_dir_back)
else:
print(wavezptp_1, "exist !")
try:
# read wave info
ste = read(waveedd_1)
tre = ste[0]
# tre.detrend('demean')
# tre.detrend('linear')
# tre.filter(type="bandpass",freqmin=0.2,freqmax=10.0,zerophase=True)
datatre = tre.data
# print(datatre)
dist = tre.stats.sac["dist"]
ptpe = tre.stats.sac["user0"]
lat = tre.stats.sac["evla"]
lon = tre.stats.sac["evlo"]
# print(ptpe)
stn = read(wavendd_1)
trn = stn[0]
datatrn = trn.data
def get_network_code_from_sacfile(self, station):
file = self.get_single_sacfile(station)[0]
stream = read(file)
trace = stream[0]
return trace.stats['network']
inventory = client.get_stations(network=net,
station=sta,
starttime=stime2,
endtime=stime2 + 24. * 60. * 60.,
level="response")
days = int(float(hours) / 24.) + 1
if days < 1:
days = 1
for day in range(days):
ctime = stime2 + 24. * 60. * 60. * day
string = '/msd/' + net + '_' + sta + '/' + str(ctime.year) + '/' + str(
ctime.julday).zfill(3) + '/'
#string = '/tr1/telemetry_days/' + net + '_' + sta + '/' + str(ctime.year) + '/*' + str(ctime.julday).zfill(3) + '/'
st += read(string + loc + '_LH*.seed')
if pcorr:
st += read(string + '30_LDO*.seed')
st.trim(starttime=stime2, endtime=stime2 + hours * 60. * 60.)
st.merge()
st.detrend('linear')
st.detrend('constant')
print(st)
st.merge()
print(st)
#st.decimate(10)
#st.decimate(10)
import numpy as np
import matplotlib.pyplot as plt
from obspy.core import read
# Read the seismogram
st = read("http://examples.obspy.org/RJOB_061005_072159.ehz.new")
# There is only one trace in the Stream object, let's work on that trace...
tr = st[0]
# Filtering with a lowpass on a copy of the original Trace
tr_filt = tr.copy()
tr_filt.filter('lowpass', freq=1.0, corners=2, zerophase=True)
# Now let's plot the raw and filtered data...
t = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)
plt.subplot(211)
plt.plot(t, tr.data, 'k')
plt.ylabel('Raw Data')
plt.subplot(212)
plt.plot(t, tr_filt.data, 'k')
plt.ylabel('Lowpassed Data')
plt.xlabel('Time [s]')
plt.suptitle(tr.stats.starttime)
plt.show()
def getobs(mseed_filename,
client,
event,
phases,
frq4,
windows,
stas,
stalocs,
picks=None,
delta_T={
'P': 1.,
'SH': 1.,
'R': 10.,
'L': 10.
},
taper=None,
adjtime=None):
# Connect to arclink server
#st = read('../mseed/mini.seed')
org = event.preferred_origin()
if org is None:
org = event.origins[0]
st = read(mseed_filename)
stobs = {'params': {'filter': frq4, 'windows': windows}}
syn = {}
torg = org.time
trngmx = 3600.
invout = None
# First do any requried time adjustments
if not adjtime is None:
for tr in st:
if not tr.stats.station in adjtime.keys():
continue
print 'Adjusting time for station %s by %g secs' % \
(tr.stats.station,adjtime[tr.stats.station])
tr.stats.starttime -= adjtime[tr.stats.station]
for phase in phases:
if not phase in stas.keys(): continue
stobs[phase] = Stream()
for sta in stas[phase]:
# If this is a body wave phase find the pick - skip if none found
if phase == 'P' or phase == 'SH':
sta_pick = None
# If no picks supplied then get them from events
if picks is None:
for pick in event.picks:
if pick.phase_hint == phase[0:1] and \
pick.waveform_id.station_code == sta:
sta_pick = pick
break
else: # Get them from picks - e.g. returned by get_isctimes
if sta in picks.keys() and phase[0:1] in picks[sta]:
sta_pick = Pick()
sta_pick.time = picks[sta][phase[0:1]]
if sta_pick is None:
print 'No %s pick found for station %s - skipping' % (
phase, sta)
continue
# Set location code if prescribed, otherwise use '00' (preferred)
if sta in stalocs.keys():
loc = stalocs[sta]
else:
loc = '00'
# Select the channels for this station - skip if none found
chans = st.select(station=sta, location=loc)
if len(chans) == 0: # if nothing for loc='00', try also with ''
loc = ''
chans = st.select(station=sta, location=loc)
if len(chans) == 0:
print 'No channels found for %s' % sta
continue
try:
inv = client.get_stations(network=chans[0].stats.network,
station=sta,
location=loc,
starttime=torg,
endtime=torg + 100.,
level='response')
except Exception as e:
warnings.warn(str(e))
print 'FDSNWS request failed for trace id %s - skipping' % sta
continue
try:
coordinates = inv[0].get_coordinates(chans[0].id)
except:
print 'No coordinates found for station %s, channel %s' % \
(sta,chans[0].id)
continue
dist, azm, bazm = gps2dist_azimuth(org['latitude'],
org['longitude'],
coordinates['latitude'],
coordinates['longitude'])
gcarc = locations2degrees(org['latitude'], org['longitude'],
coordinates['latitude'],
coordinates['longitude'])
if phase == 'R' or phase == 'P': # Rayleigh or P wave
try:
tr = st.select(station=sta, component='Z', location=loc)[0]
except IndexError:
print 'No vertical for %s:%s' % (sta, loc)
continue
try:
inv = client.get_stations(network=tr.stats.network,
station=sta,
channel=tr.stats.channel,
location=loc,
starttime=torg,
endtime=torg + 100.,
level='response')
except Exception as e:
warnings.warn(str(e))
print 'FDSNWS request failed for trace id %s - skipping' % tr.id
continue
tr = tr.copy()
tr.stats.response = inv[0].get_response(tr.id, torg)
tr.stats.coordinates = inv[0].get_coordinates(tr.id)
tr.remove_response(pre_filt=frq4[phase], output='DISP')
tr.stats.gcarc = gcarc
tr.stats.azimuth = azm
#t1 = minv[0].get_responeax(tr.stats.starttime,t+dist/rvmax)
#t2 = min(tr.stats.endtime ,t+dist/rvmin)
t1 = max(torg, tr.stats.starttime)
t2 = min(torg + trngmx, tr.stats.endtime)
tr.trim(starttime=t1, endtime=t2)
decim = int(0.01 + delta_T[phase] / tr.stats.delta)
ch = inv.select(station=sta, channel=tr.stats.channel)[0][0][0]
print tr.id,' ',tr.stats.sampling_rate,' decimated by ',decim,\
'sensitivity=',ch.response.instrument_sensitivity.value
if tr.stats.starttime - torg < 0.:
tr.trim(starttime=torg)
tr.decimate(factor=decim, no_filter=True)
tr.data *= 1.e6 # Convert to microns
elif phase == 'L' or phase == 'SH': # Love or SH wave
if len(chans.select(component='E')) != 0:
try:
tr1a = st.select(station=sta,
component='E',
location=loc)[0]
tr2a = st.select(station=sta,
component='N',
location=loc)[0]
except:
print 'Station %s does not have 2 horizontal componets -skipping' % sta
continue
elif len(chans.select(component='1')) != 0:
try:
tr1a = st.select(station=sta,
component='1',
location=loc)[0]
tr2a = st.select(station=sta,
component='2',
location=loc)[0]
except:
print 'Station %s does not have 2 horizontal componets -skipping' % sta
continue
tr1 = tr1a.copy()
tr1.data = tr1a.data.copy()
tr2 = tr2a.copy()
tr2.data = tr2a.data.copy()
ch1 = inv.select(station=sta,
channel=tr1.stats.channel)[0][0][0]
ch2 = inv.select(station=sta,
channel=tr2.stats.channel)[0][0][0]
tr1.stats.response = ch1.response
tr1.remove_response(pre_filt=frq4[phase], output='DISP')
tr2.stats.response = ch2.response
tr2.remove_response(pre_filt=frq4[phase], output='DISP')
strt = max(tr1.stats.starttime, tr2.stats.starttime)
endt = min(tr1.stats.endtime, tr2.stats.endtime)
tr1.trim(starttime=strt, endtime=endt)
tr2.trim(starttime=strt, endtime=endt)
# Rotate components first to ZNE
vert, north, east = rotate2zne(tr1.data, ch1.azimuth, 0.,
tr2.data, ch2.azimuth, 0.,
np.zeros(tr1.stats.npts), 0.,
0.)
radial, transverse = rotate_ne_rt(north, east, bazm)
tr = Trace(header=tr1.stats, data=transverse)
tr2 = Trace(header=tr2.stats, data=radial)
tr.stats.channel = tr.stats.channel[:-1] + 'T'
# Change one of the invout channels to end in 'T'
net = inv[-1]
stn = net[0]
chn = stn[0]
chn.code = chn.code[:-1] + 'T'
#
tr.stats.gcarc = gcarc
tr.stats.azimuth = azm
decim = int(0.01 + delta_T[phase] / tr.stats.delta)
print tr.id, ' ', tr.stats.sampling_rate, ' decimated by ', decim
print '%s: sensitivity=%g, azimuth=%g, dip=%g' % (
ch1.code, ch1.response.instrument_sensitivity.value,
ch1.azimuth, ch1.dip)
print '%s: sensitivity=%g, azimuth=%g, dip=%g' % (
ch2.code, ch2.response.instrument_sensitivity.value,
ch2.azimuth, ch2.dip)
if tr.stats.starttime - torg < 0.:
tr.trim(starttime=torg)
tr2.trim(starttime=torg)
tr.decimate(factor=decim, no_filter=True)
tr2.decimate(factor=decim, no_filter=True)
tr.radial = 1.e6 * tr2.data
tr.stats.coordinates = coordinates
tr.data *= 1.e6 # Convert to microns
if phase == 'R' or phase == 'L': # Window according to group velocity window
gwin = windows[phase]
tbeg, tend = (dist * .001 / gwin[1], dist * .001 / gwin[0])
tr.trim(torg + tbeg, torg + tend)
elif phase == 'P' or phase == 'SH': # Window by times before and after pick
tbef, taft = windows[phase]
tr.trim(sta_pick.time - tbef, sta_pick.time + taft)
idx = int(0.5 + tbef / tr.stats.delta)
avg = tr.data[:idx].mean()
tr.data -= avg
if not taper is None:
itp = int(taper * tr.stats.npts)
for i in range(tr.stats.npts - itp, tr.stats.npts):
tr.data[i] *= 0.5 * (1. + mt.cos(
mt.pi * (i - (tr.stats.npts - itp)) / float(itp)))
tr.stats.pick = sta_pick
stobs[phase].append(tr)
# Appen station inventory to invout
if invout is None:
invout = inv
else:
invout += inv
# Pickle to file
return stobs, invout
def read_in_traces(self, file_list):
running_stream = Stream()
for file in file_list:
running_stream += read(file)
return running_stream
if not mseed_files:
pass # XXX print/mail warning
inst = cornFreq2Paz(1.0)
nfft = 4194304 # next nfft of 5h
last_endtime = 0
last_id = "--"
trigger_list = []
summary = []
summary.append("#" * 79)
for file in mseed_files:
summary.append(file)
try:
st = read(file, "MSEED")
T1 = UTCDateTime("2010-09-20T00:00:00") # XXX
T2 = UTCDateTime("2010-09-20T04:00:00") # XXX
st.trim(T1, T2) # XXX
#st.trim(endtime=st[0].stats.starttime+5000) # XXX
st.merge(-1)
st.sort()
summary.append(str(st))
except:
summary.append("skipped!")
continue
for tr in st:
stats = tr.stats
for parser in parsers:
try:
tr.stats.paz = parser.getPAZ(tr.id, tr.stats.starttime)
#!/usr/bin/env python3
from obspy.core import read
from numpy import sqrt
t1_hamming = read('t100.hamming.taper.sac')
t1_hanning = read('t100.hanning.taper.sac')
t1_cosine = read('t100.cosine.taper.sac')
t2_hamming = read('t101.hamming.taper.sac')
t2_hanning = read('t101.hanning.taper.sac')
t2_cosine = read('t101.cosine.taper.sac')
cline1 = ''
for i in range(len(t1_hamming[0].data)):
cline1 = cline1 + '%.8lf, %.8lf, %.8lf\n' % (t1_hamming[0].data[i],
t1_hanning[0].data[i],
pow(t1_cosine[0].data[i], 1))
print(cline1)
of = open('../taper100.all.txt', 'w')
of.write(cline1)
of.close()
cline2 = ''
for i in range(len(t2_hamming[0].data)):
cline2 = cline2 + '%.8lf, %.8lf, %.8lf\n' % (t2_hamming[0].data[i],
t2_hanning[0].data[i],
pow(t2_cosine[0].data[i], 1))
print(cline2)
of = open('../taper101.all.txt', 'w')
of.write(cline2)
of.close()
"""
if len(k)!=0:
tmp = Inf
x[k] = tmp(len(k))
k = np.where(((b > 0) & (p > 0) & (p < 1)))[0]
#~ print k
if len(k)!=0:
pk = p[k]
bk = b[k]
#~ print pk, bk
x[k] = np.sqrt((-2*bk ** 2) * np.log(1 - pk))
return x
if __name__ == "__main__":
#~ from scipy.io.matlab import loadmat
#~ v1 = loadmat(r"C:\Users\tlecocq\Documents\Tom's Share\Pack Kurtogram\Pack Kurtogram V3\VOIE1.mat")
#~ x = v1['v1']
from obspy.core import read
st = read(os.path.join(r'C:\Users\thomas\Desktop\3069','*.UCC.DOU..HHZ.D.MSEED'))
#~ st.plot()
st.merge()
Fs = st[0].stats.sampling_rate
x = st[0].data[600*Fs:720*Fs]
#~ x = st[0].data
nlevel= 7
c = Fast_Kurtogram(x, nlevel, Fs)
def main(comps=None):
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s [%(levelname)s] %(message)s',
datefmt='%Y-%m-%d %H:%M:%S')
logging.info('*** Starting: Compute MWCS ***')
db = connect()
if comps == None:
components_to_compute = get_components_to_compute(db)
else:
components_to_compute = comps
mov_stack = get_config(db, "mov_stack")
if mov_stack.count(',') == 0:
mov_stacks = [
int(mov_stack),
]
else:
mov_stacks = [int(mi) for mi in mov_stack.split(',')]
goal_sampling_rate = float(get_config(db, "cc_sampling_rate"))
maxlag = float(get_config(db, "maxlag"))
# First we reset all DTT jobs to "T"odo if the REF is new for a given pair
for station1, station2 in get_station_pairs(db, used=True):
sta1 = "%s.%s" % (station1.net, station1.sta)
sta2 = "%s.%s" % (station2.net, station2.sta)
pair = "%s:%s" % (sta1, sta2)
if is_dtt_next_job(db, jobtype='DTT', ref=pair):
logging.info(
"We will recompute all MWCS based on the new REF for %s" %
pair)
reset_dtt_jobs(db, pair)
update_job(db, "REF", pair, jobtype='DTT', flag='D')
logging.debug('Ready to compute')
# Then we compute the jobs
outfolders = []
while is_dtt_next_job(db, flag='T', jobtype='DTT'):
pair, days, refs = get_dtt_next_job(db, flag='T', jobtype='DTT')
logging.info("There are MWCS jobs for some days to recompute for %s" %
pair)
for f in get_filters(db, all=False):
filterid = int(f.ref)
for components in components_to_compute:
ref_name = pair.replace('.', '_').replace(':', '_')
rf = os.path.join("STACKS", "%02i" % filterid, "REF",
components, ref_name + ".MSEED")
ref = read(rf)[0].data
for day in days:
for mov_stack in mov_stacks:
df = os.path.join("STACKS", "%02i" % filterid,
"%03i_DAYS" % mov_stack, components,
ref_name,
str(day) + ".MSEED")
if os.path.isfile(df):
cur = read(df)[0].data
logging.debug(
'Processing MWCS for: %s.%s.%02i - %s - %02i days'
% (ref_name, components, filterid, day,
mov_stack))
output = mwcs(cur, ref, f.mwcs_low, f.mwcs_high,
goal_sampling_rate, -maxlag,
f.mwcs_wlen, f.mwcs_step)
outfolder = os.path.join('MWCS', "%02i" % filterid,
"%03i_DAYS" % mov_stack,
components, ref_name)
if outfolder not in outfolders:
if not os.path.isdir(outfolder):
os.makedirs(outfolder)
outfolders.append(outfolder)
np.savetxt(
os.path.join(outfolder, "%s.txt" % str(day)),
output)
del output, cur
for day in days:
update_job(db, day, pair, jobtype='DTT', flag='D')
logging.info('*** Finished: Compute MWCS ***')
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Fri Sep 29 12:19:56 2017
@author: horas
"""
from obspy.core import read
from scipy.integrate import simps
import numpy as np
#import matplotlib.pylab as plt
#from obspy.core import stream
st = read ("DNP_full.MSEED")
print st
print '\n'
print st[0].data
print '\n'
print type(st)
print '\n'
print st.traces
print '\n'
print st[0].stats
print '\n'
print st[0].stats.delta, '|', st[0].stats.endtime
print '\n'
print st
print st[0]
def Read_event(Year,jJul,Hour,Second,Station, plot):
"""return a stream containing the 3 traces N, Z,E of an event calib =1
* input :
- station: station considered ex : '1'
- year : year of the event ex 15
- jJul : julian day
- Hour : hour of the event ex '08
- plot : if True plot will be shown '
*output :
-st : type : stream ; Stream containing the 3 traces ENZ
* exemples :
1. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Station, Year,jJul, Hour = ConvertDatestr(B[j])
==> (Station, Year,jJul, Hour) = ('2', '15', '001', '00')
st = Read_event(Year,jJul,Hour,12, Station, True)
2. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
for j in [1,222344,222345]:
Station, Year,jJul, Hour = ConvertDatestr(B[j])
print ConvertDatestr(B[j])
if not os.path.exists('/home/claire/PHD/Working/Data/Wangrong_seismic_data/20%s/R%s.02/GSW0%s.%s.%s.%s.00.00.BHN.SAC'%(Year,jJul,Station,Year,jJul,str(Hour))) :
print 'file not existing' , jJul, Hour
continue
Read_event(Year,jJul,Hour,12, Station, True)
"""
#0. Uniformise file format for file reading ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if int(Second)>=3600 :
print Second
h = int(Second)//3600
Hour=int(Hour)+h
Second = int(Second)%3600
if int(Hour)>23 :
jJul = str(jJul+ 1)
Hour = str(int(Hour-24))
else :
jJul = str(int(jJul))
if Hour<10 :
Hour = '0'+str(Hour)
if int(jJul)<10:
jJul = '00'+str(jJul)
elif int(jJul)<100:
jJul = '0'+str(jJul)
#1. reading files ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
st = Stream()
trE = read('/home/burtin/DATA/LinTianShan/Seismic_Data/20%s/R%s.02/GSW0%s.%s.%s.%s.00.00.BHE.SAC'%(Year,jJul,Station,Year,jJul,str(Hour)))[0]
trE.stats.calib = 1
st.append(trE)
trN = read('/home/burtin/DATA/LinTianShan/Seismic_Data/20%s/R%s.02/GSW0%s.%s.%s.%s.00.00.BHN.SAC'%(Year,jJul,Station,Year,jJul,str(Hour)))[0]
trN.stats.calib = 1
st.append(trN)
trZ = read('/home/burtin/DATA/LinTianShan/Seismic_Data/20%s/R%s.02/GSW0%s.%s.%s.%s.00.00.BHZ.SAC'%(Year,jJul,Station,Year,jJul,str(Hour)))[0]
trZ.stats.calib = 1
st.append(trZ)
#2. Plotting waveform~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if plot == True :
fig = plt.figure()
fig.canvas.set_window_title('Waveform_%s_%s'%(jJul, Hour))
st.plot(fig=fig)
return st
def calc_derivatives(Tmin, Tmax, station, comp, derivatives_folder,
out_folder):
derivatives_folder = derivatives_folder.split("kernels")[0]
lines = open(
derivatives_folder.split("kernels")[0] + "/kernels_info.txt",
"r").readlines()
delta_x = float(lines[0].split()[2])
delta_y = float(lines[1].split()[2])
delta_z = float(lines[2].split()[2])
delta_components = [
"xp",
"yp",
"zp",
"xm",
"ym",
"zm",
"xpyp",
"xpym",
"xmyp",
"xmym",
"xpzp",
"xpzm",
"xmzp",
"xmzm",
"ypzp",
"ypzm",
"ymzp",
"ymzm",
"point_source",
]
derivative_list = [
"dSdx",
"dSdy",
"dSdz",
"dS2dx2",
"dS2dy2",
"dS2dz2",
"dSdxdy",
"dSdxdz",
"dSdydz",
]
tr = {}
dS = {}
for del_comp in delta_components:
folder = f"{derivatives_folder}{del_comp}/"
tr_tmp = read(f"{folder}*{station}.MX{comp}.sem.sac")[0]
tr_tmp.detrend("demean")
tr_tmp.filter("bandpass",
freqmin=1 / Tmax,
freqmax=1 / Tmin,
corners=4,
zerophase=True)
tr[del_comp, station] = tr_tmp
for der_comp in derivative_list:
dS[der_comp] = tr["point_source", station].copy()
# First derivatives
dS["dSdx"].data = (tr["xp", station].data -
tr["xm", station].data) / (2 * delta_x)
dS["dSdy"].data = (tr["yp", station].data -
tr["ym", station].data) / (2 * delta_y)
dS["dSdz"].data = (tr["zp", station].data -
tr["zm", station].data) / (2 * delta_z)
# Second derivatives
dS["dS2dx2"].data = (tr["xp", station].data -
2 * tr["point_source", station].data +
tr["xm", station].data) / ((delta_x)**2)
dS["dS2dy2"].data = (tr["yp", station].data -
2 * tr["point_source", station].data +
tr["ym", station].data) / ((delta_y)**2)
dS["dS2dz2"].data = (tr["zp", station].data -
2 * tr["point_source", station].data +
tr["zm", station].data) / ((delta_z)**2)
dS["dSdxdy"].data = (tr["xpyp", station].data - tr["xpym", station].data -
tr["xmyp", station].data +
tr["xmym", station].data) / (4 * delta_x * delta_y)
dS["dSdxdz"].data = (tr["xpzp", station].data - tr["xpzm", station].data -
tr["xmzp", station].data +
tr["xmzm", station].data) / (4 * delta_x * delta_z)
dS["dSdydz"].data = (tr["ypzp", station].data - tr["ypzm", station].data -
tr["ymzp", station].data +
tr["ymzm", station].data) / (4 * delta_y * delta_z)
for der_comp in derivative_list:
dS[der_comp].interpolate(sampling_rate=0.5, method="linear")
dS[der_comp].write(
f"{out_folder}/{station}_{comp}_{der_comp}.sac",
format="SAC",
)
plt.plot(dS[der_comp].times(), dS[der_comp].data, color="black")
dS[der_comp].plot(
outfile=f"{out_folder}/{station}_{comp}_{der_comp}.png")
plt.close()
return
