def test_issue193(self):
"""
Test for issue #193: if non-contiguous array is written correctly.
"""
warnings.filterwarnings("ignore", "Detected non contiguous data")
# test all plugins with both read and write method
formats_write = \
set(_getEntryPoints('obspy.plugin.waveform', 'writeFormat'))
formats_read = \
set(_getEntryPoints('obspy.plugin.waveform', 'readFormat'))
formats = set.intersection(formats_write, formats_read)
# mseed will raise exception for int64 data, thus use int32 only
data = np.arange(10, dtype='int32')
# make array non-contiguous
data = data[::2]
tr = Trace(data=data)
for format in formats:
# XXX: skip SEGY and SU formats for now as they need some special
# headers.
if format in ['SEGY', 'SU', 'SEG2']:
continue
tempfile = NamedTemporaryFile().name
tr.write(tempfile, format)
if format == "Q":
tempfile = tempfile + ".QHD"
tr_test = read(tempfile, format)[0]
# clean up
os.remove(tempfile)
if format == 'Q':
os.remove(tempfile[:-4] + '.QBN')
os.remove(tempfile[:-4])
np.testing.assert_array_equal(tr.data, tr_test.data)
def test_issue193(self):
"""
Test for issue #193: if non-contiguous array is written correctly.
"""
warnings.filterwarnings("ignore", "Detected non contiguous data")
# test all plugins with both read and write method
formats_write = \
set(_getEntryPoints('obspy.plugin.waveform', 'writeFormat'))
formats_read = \
set(_getEntryPoints('obspy.plugin.waveform', 'readFormat'))
formats = set.intersection(formats_write, formats_read)
# mseed will raise exception for int64 data, thus use int32 only
data = np.arange(10, dtype='int32')
# make array non-contiguous
data = data[::2]
tr = Trace(data=data)
for format in formats:
# XXX: skip SEGY and SU formats for now as they need some special
# headers.
if format in ['SEGY', 'SU', 'SEG2']:
continue
tempfile = NamedTemporaryFile().name
tr.write(tempfile, format)
if format == "Q":
tempfile = tempfile + ".QHD"
tr_test = read(tempfile, format)[0]
# clean up
os.remove(tempfile)
if format == 'Q':
os.remove(tempfile[:-4] + '.QBN')
os.remove(tempfile[:-4])
np.testing.assert_array_equal(tr.data, tr_test.data)
def normalization(datapath):
filepath = datapath + '/predict/syn/Z/'
for i in tqdm(range(300), desc='processing'):
st = read(filepath + str(i) + '.sac')
tr = (st[0].data) / np.max(abs(st[0].data))
sacfile = Trace()
sacfile.data = tr[:]
sacfile.write(filepath + str(i) + ".sac", format="SAC")
def test_writeSACXYWithMinimumStats(self):
"""
Write SACXY with minimal stats header, no inhereted from SAC file
"""
tr = Trace()
tr.stats.delta = 0.01
tr.data = np.arange(0, 3000)
sac_file = NamedTemporaryFile().name
tr.write(sac_file, 'SACXY')
st = read(sac_file)
os.remove(sac_file)
self.assertEquals(st[0].stats.delta, 0.01)
self.assertEquals(st[0].stats.sampling_rate, 100.0)
def test_writeSACXYWithMinimumStats(self):
"""
Write SACXY with minimal stats header, no inhereted from SAC file
"""
tr = Trace()
tr.stats.delta = 0.01
tr.data = np.arange(0, 3000)
sac_file = NamedTemporaryFile().name
tr.write(sac_file, "SACXY")
st = read(sac_file)
os.remove(sac_file)
self.assertEquals(st[0].stats.delta, 0.01)
self.assertEquals(st[0].stats.sampling_rate, 100.0)
def test_writeSmallTrace(self):
"""
Tests writing Traces containing 0, 1 or 2 samples only.
"""
for format in ['SAC', 'SACXY']:
for num in range(0, 4):
tr = Trace(data=np.arange(num))
tempfile = NamedTemporaryFile().name
tr.write(tempfile, format=format)
# test results
st = read(tempfile, format=format)
self.assertEquals(len(st), 1)
self.assertEquals(len(st[0]), num)
os.remove(tempfile)
def test_writeSmallTrace(self):
"""
Tests writing Traces containing 0, 1 or 2 samples only.
"""
for format in ['SLIST', 'TSPAIR']:
for num in range(0, 4):
tr = Trace(data=np.arange(num))
tempfile = NamedTemporaryFile().name
tr.write(tempfile, format=format)
# test results
st = read(tempfile, format=format)
self.assertEquals(len(st), 1)
self.assertEquals(len(st[0]), num)
os.remove(tempfile)
def test_writeSmallTrace(self):
"""
Tests writing Traces containing 0, 1 or 2 samples only.
"""
for format in ['SH_ASC', 'Q']:
for num in range(0, 4):
tr = Trace(data=np.arange(num))
tempfile = NamedTemporaryFile().name
if format == 'Q':
tempfile += '.QHD'
tr.write(tempfile, format=format)
# test results
st = read(tempfile, format=format)
self.assertEquals(len(st), 1)
self.assertEquals(len(st[0]), num)
# Q files consist of two files - deleting additional file
if format == 'Q':
os.remove(tempfile[:-4] + '.QBN')
os.remove(tempfile[:-4])
os.remove(tempfile)
def test_issue376(self):
"""
Tests writing Traces containing 1 or 2 samples only.
"""
# one samples
tr = Trace(data=np.ones(1))
tempfile = NamedTemporaryFile().name
tr.write(tempfile, format="MSEED")
st = read(tempfile)
self.assertEquals(len(st), 1)
self.assertEquals(len(st[0]), 1)
os.remove(tempfile)
# two samples
tr = Trace(data=np.ones(2))
tempfile = NamedTemporaryFile().name
tr.write(tempfile, format="MSEED")
st = read(tempfile)
self.assertEquals(len(st), 1)
self.assertEquals(len(st[0]), 2)
os.remove(tempfile)
def test_issue376(self):
"""
Tests writing Traces containing 1 or 2 samples only.
"""
# one samples
tr = Trace(data=np.ones(1))
tempfile = NamedTemporaryFile().name
tr.write(tempfile, format="MSEED")
st = read(tempfile)
self.assertEquals(len(st), 1)
self.assertEquals(len(st[0]), 1)
os.remove(tempfile)
# two samples
tr = Trace(data=np.ones(2))
tempfile = NamedTemporaryFile().name
tr.write(tempfile, format="MSEED")
st = read(tempfile)
self.assertEquals(len(st), 1)
self.assertEquals(len(st[0]), 2)
os.remove(tempfile)
def y2m(file, path):
"""
yspec outputs to SAC format
"""
stationID = int(file.split('.')[-1])
chans = ['BHZ', 'BHN', 'BHE']
dat = np.loadtxt(file)
npts = len(dat[:,0])
for i, chan in enumerate(chans):
stats = {'network': 'SG',
'station': 'RS%02d' % stationID,
'location': '',
'channel': chan,
'npts': npts,
'sampling_rate': (npts - 1.)/(dat[-1,0] - dat[0,0]),
'starttime': t,
'mseed': {'dataquality': 'D'}}
traces = Trace(data=dat[:,1+i], header=stats)
traces.write(os.path.join(path, 'SAC', 'dis.%s.%s.%s' % (traces.stats.station, traces.stats.location,
traces.stats.channel)), format='SAC')
def test_writeSmallTrace(self):
"""
Tests writing Traces containing 0, 1 or 2 samples only.
"""
for format in ['SH_ASC', 'Q']:
for num in range(0, 4):
tr = Trace(data=np.arange(num))
tempfile = NamedTemporaryFile().name
if format == 'Q':
tempfile += '.QHD'
tr.write(tempfile, format=format)
# test results
st = read(tempfile, format=format)
self.assertEquals(len(st), 1)
self.assertEquals(len(st[0]), num)
# Q files consist of two files - deleting additional file
if format == 'Q':
os.remove(tempfile[:-4] + '.QBN')
os.remove(tempfile[:-4])
os.remove(tempfile)
def test_issue156(self):
"""
Test case for issue #156.
"""
# 1
tr = Trace()
tr.stats.delta = 0.01
tr.data = np.arange(0, 3000)
sac_file = NamedTemporaryFile().name
tr.write(sac_file, "SAC")
st = read(sac_file)
os.remove(sac_file)
self.assertEquals(st[0].stats.delta, 0.01)
self.assertEquals(st[0].stats.sampling_rate, 100.0)
# 2
tr = Trace()
tr.stats.delta = 0.005
tr.data = np.arange(0, 2000)
sac_file = NamedTemporaryFile().name
tr.write(sac_file, "SAC")
st = read(sac_file)
os.remove(sac_file)
self.assertEquals(st[0].stats.delta, 0.005)
self.assertEquals(st[0].stats.sampling_rate, 200.0)
def test_issue156(self):
"""
Test case for issue #156.
"""
#1
tr = Trace()
tr.stats.delta = 0.01
tr.data = np.arange(0, 3000)
sac_file = NamedTemporaryFile().name
tr.write(sac_file, 'SAC')
st = read(sac_file)
os.remove(sac_file)
self.assertEquals(st[0].stats.delta, 0.01)
self.assertEquals(st[0].stats.sampling_rate, 100.0)
#2
tr = Trace()
tr.stats.delta = 0.005
tr.data = np.arange(0, 2000)
sac_file = NamedTemporaryFile().name
tr.write(sac_file, 'SAC')
st = read(sac_file)
os.remove(sac_file)
self.assertEquals(st[0].stats.delta, 0.005)
self.assertEquals(st[0].stats.sampling_rate, 200.0)
print "STACK"
corrc3 = stack(datac3, stack_method=p['stack_method'])
try:
os.makedirs('c3/%s/%s.%s/' % (staTarget1, comp1, comp2))
# os.makedirs('c1/%s/'%staTarget1)
except:
pass
t = Trace()
t.stats.station = 'c3'
t.stats.sampling_rate = p['df']
t.data = np.array(corrc3[::-1])
t.stats.starttime -= (len(corrc3) / 2) / p['df']
t.write('c3/%s/%s.%s/BO.c3.%s.%s.%s.mseed'%(staTarget1,\
comp1, comp2, namepairA_B, comp1, comp2), format='MSEED')
# t2 = Trace()
# t2.stats.station = 'c1'
# t2.stats.sampling_rate = df
# t2.data= np.array(aa)
# t2.stats.starttime -= ( len(aa) / 2 ) / df
# t2.write('c1/%s/c1.%s.mseed'%(staTarget1, pair), format='MSEED')
if __name__ == '__main__':
#staTarget1 = '235713'
#staTarget2 = '236977'
#depth = 0
t = time.time()
c3_from_bin(sys.argv[1:])
print 'It took :%s s' % (time.time() - t)
def savecorrs(correlation,phaseweight,n_stack,id1,id2,geoinf,\
corrname,corrtype,outdir,params=None,timestring='',startday=None,\
endday=None):
#==============================================================================
#- Write metadata info to sac header
#- Store results
#==============================================================================
tr=Trace(data=correlation)
tr.stats.sac={}
if startday == None:
startday=UTCDateTime(inp.startdate)
if endday == None:
endday=UTCDateTime(inp.enddate)
(lat1, lon1, lat2, lon2, dist, az, baz)=geoinf
# Add a preprocessing string:
prepstring = get_prepstring()
tr.stats.sampling_rate=inp.Fs[-1]
tr.stats.starttime=UTCDateTime(2000, 01, 01)-inp.max_lag*inp.Fs[-1]
tr.stats.network=id1.split('.')[0]
tr.stats.station=id1.split('.')[1]
tr.stats.location=id1.split('.')[2]
tr.stats.channel=id1.split('.')[3]
tr.stats.sac['kt2']=prepstring
tr.stats.sac['kt8']=corrtype
tr.stats.sac['user0']=n_stack
tr.stats.sac['user1']=inp.winlen
tr.stats.sac['user2']=inp.olap
tr.stats.sac['b']=-inp.max_lag
tr.stats.sac['e']=inp.max_lag
tr.stats.sac['kt0']=startday.strftime('%Y%j')
tr.stats.sac['kt1']=endday.strftime('%Y%j')
tr.stats.sac['iftype']=1
tr.stats.sac['stla']=lat1
tr.stats.sac['stlo']=lon1
tr.stats.sac['kevnm']=id2.split('.')[1]
tr.stats.sac['evla']=lat2
tr.stats.sac['evlo']=lon2
tr.stats.sac['dist']=dist
tr.stats.sac['az']=az
tr.stats.sac['baz']=baz
tr.stats.sac['kuser0']=id2.split('.')[0]
tr.stats.sac['kuser1']=id2.split('.')[2]
tr.stats.sac['kuser2']=id2.split('.')[3]
if params is not None:
tr.stats.sac['user3']=params[0]
tr.stats.sac['user4']=params[1]
tr.stats.sac['user5']=params[2]
tr.stats.sac['user6']=params[3]
tr.stats.sac['user7']=params[4]
tr.stats.sac['user8']=params[5]
#- open file and write correlation function
fileid=outdir+id1+'.'+id2+'.'+corrtype+'.'+\
corrname+timestring+'.SAC'
tr.write(fileid,format='SAC')
if phaseweight is not None:
fileid_cwt=outdir+id1+'.'+id2+'.'+corrtype+\
'.'+corrname+timestring+'.npy'
np.save(fileid_cwt,phaseweight)
def test_readThreadSafe(self):
"""
Tests for race conditions. Reading n_threads (currently 30) times
the same waveform file in parallel and compare the results which must
be all the same.
"""
data = np.arange(0, 500)
start = UTCDateTime(2009, 1, 13, 12, 1, 2, 999000)
formats = _getEntryPoints('obspy.plugin.waveform', 'writeFormat')
for format in formats:
# XXX: skip SEGY and SU formats for now as they need some special
# headers.
if format in ['SEGY', 'SU', 'SEG2']:
continue
dt = np.dtype("int")
if format in ('MSEED', 'GSE2'):
dt = "int32"
tr = Trace(data=data.astype(dt))
tr.stats.network = "BW"
tr.stats.station = "MANZ1"
tr.stats.location = "00"
tr.stats.channel = "EHE"
tr.stats.calib = 0.999999
tr.stats.delta = 0.005
tr.stats.starttime = start
# create waveform file with given format and byte order
outfile = NamedTemporaryFile().name
tr.write(outfile, format=format)
if format == 'Q':
outfile += '.QHD'
n_threads = 30
streams = []
def testFunction(streams):
st = read(outfile, format=format)
streams.append(st)
# Read the ten files at one and save the output in the just created
# class.
for _i in xrange(n_threads):
thread = threading.Thread(target=testFunction,
args=(streams,))
thread.start()
# Loop until all threads are finished.
start = time.time()
while True:
if threading.activeCount() == 1:
break
# Avoid infinite loop and leave after 120 seconds
# such a long time is needed for debugging with valgrind
elif time.time() - start >= 120:
msg = 'Not all threads finished!'
raise Warning(msg)
break
else:
continue
# Compare all values which should be identical and clean up files
#for data in :
# np.testing.assert_array_equal(values, original)
os.remove(outfile)
if format == 'Q':
os.remove(outfile[:-4] + '.QBN')
os.remove(outfile[:-4])
def ncExtract(address):
"""
This function extract a station (data, response file, header) from a
netCDF file
: type rootgrp: netCDF4.Dataset
: param rootgrp: a netCDF version 4 group that contains one event
: type tr: class 'obspy.core.trace.Trace'
: param tr: the trace that will be extracted from the nc file
: type resp_read: str
: param resp_read: the whole response file of the trace in
one string format extracted from the info/respfile attribute
"""
global rootgrp
if not os.path.isdir(os.path.join(address, 'Resp_NC')):
os.mkdir(os.path.join(address, 'Resp_NC'))
if not os.path.isdir(os.path.join(address, 'BH_NC')):
os.mkdir(os.path.join(address, 'BH_NC'))
root_grps = rootgrp.groups
num_iter = 1
print "\n----------------------------"
print "Number of all available"
print "stations in the netCDF file:"
print len(root_grps)
print "----------------------------\n"
if not input['noaxisem'] == 'Y':
axi_open = open(os.path.join(address, 'STATIONS'), 'w')
axi_open.writelines(rootgrp.axisem[17:])
axi_open.close
for grp in root_grps:
print str(num_iter),
stgrp = root_grps[grp]
stdata = stgrp.variables['data'][:]
resp_read = stgrp.respfile
if not resp_read == 'NO RESPONSE FILE AVAILABLE':
resp_open = open(os.path.join(address, 'Resp_NC', 'RESP.' + stgrp.identity), 'w')
resp_open.writelines(resp_read)
resp_open.close
else:
print '\nNO RESPONSE FILE AVAILABLE for ' + stgrp.identity
ststats = {}
for key in range(0, len(eval(stgrp.headerK))):
ststats[eval(stgrp.headerK)[key]] = eval(stgrp.headerV)[key]
tr = Trace(stdata, ststats)
tr.write(os.path.join(address, 'BH_NC', stgrp.identity), format = 'SAC')
num_iter += 1
def test_readAndWrite(self):
"""
Tests read and write methods for all installed waveform plug-ins.
"""
data = np.arange(0, 2000)
start = UTCDateTime(2009, 1, 13, 12, 1, 2, 999000)
formats = _getEntryPoints('obspy.plugin.waveform', 'writeFormat')
for format in formats:
# XXX: skip SEGY and SU formats for now as they need some special
# headers.
if format in ['SEGY', 'SU', 'SEG2']:
continue
for native_byteorder in ['<', '>']:
for byteorder in ['<', '>', '=']:
# new trace object in native byte order
dt = np.dtype("int").newbyteorder(native_byteorder)
if format in ('MSEED', 'GSE2'):
# MiniSEED and GSE2 cannot write int64, enforce type
dt = "int32"
tr = Trace(data=data.astype(dt))
tr.stats.network = "BW"
tr.stats.station = "MANZ1"
tr.stats.location = "00"
tr.stats.channel = "EHE"
tr.stats.calib = 0.199999
tr.stats.delta = 0.005
tr.stats.starttime = start
# create waveform file with given format and byte order
outfile = NamedTemporaryFile().name
tr.write(outfile, format=format, byteorder=byteorder)
if format == 'Q':
outfile += '.QHD'
# read in again using auto detection
st = read(outfile)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# read in using format argument
st = read(outfile, format=format)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# read in using a StringIO instances, skip Q files as it
# needs multiple files
if format not in ['Q']:
# file handler without format
temp = open(outfile, 'rb')
st = read(temp)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# file handler with format
temp = open(outfile, 'rb')
st = read(temp, format=format)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# StringIO without format
temp = StringIO.StringIO(open(outfile, 'rb').read())
st = read(temp)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# StringIO with format
temp = StringIO.StringIO(open(outfile, 'rb').read())
st = read(temp, format=format)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# cStringIO without format
temp = cStringIO.StringIO(open(outfile, 'rb').read())
st = read(temp)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# cStringIO with format
temp = cStringIO.StringIO(open(outfile, 'rb').read())
st = read(temp, format=format)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# check byte order
self.assertEquals(st[0].data.dtype.byteorder, '=')
# check meta data
# some formats do not contain a calibration factor
if format not in ['MSEED', 'WAV', 'TSPAIR', 'SLIST']:
self.assertAlmostEquals(st[0].stats.calib, 0.199999, 5)
else:
self.assertEquals(st[0].stats.calib, 1.0)
if format not in ['WAV']:
self.assertEquals(st[0].stats.starttime, start)
self.assertEquals(st[0].stats.endtime, start + 9.995)
self.assertEquals(st[0].stats.delta, 0.005)
self.assertEquals(st[0].stats.sampling_rate, 200.0)
# network/station/location/channel codes
if format in ['Q', 'SH_ASC', 'GSE2']:
# no network or location code in Q, SH_ASC, GSE2
self.assertEquals(st[0].id, ".MANZ1..EHE")
elif format not in ['WAV']:
self.assertEquals(st[0].id, "BW.MANZ1.00.EHE")
# remove temporary files
os.remove(outfile)
# Q files consist of two files - deleting additional file
if format == 'Q':
os.remove(outfile[:-4] + '.QBN')
os.remove(outfile[:-4])
# for ia, a in enumerate(gminor):
# # if ia >50:continue
# binfileA = [a]
# binfileB = [gmajor[ia]]
# c3 = c3_from_bin_fun(s1, s2, d, binfileA, binfileB)
# datac3 = np.vstack((datac3, c3))
# print np.shape(datac3)
#corrc3 = stack(datac3, stack_method='linear')
t = Trace()
t.stats.station = 'pc3'
t.stats.channel = '%03d' % day
t.stats.sampling_rate = df
t.data = np.array(c3[::-1])
t.stats.starttime -= (len(c3) / 2) / df
try:
os.makedirs('pc3/EE/%s/%s/' % (s1, s2))
except:
pass
t.write('pc3/EE/%s/%s/pc3.%s.%s.%03d.EE.mseed' % (s1, s2, s1, s2, day),
format='MSEED')
if __name__ == '__main__':
#staTarget1 = '235713'
#staTarget2 = '236977'
#depth = 0.
prestackc3(sys.argv[1:])
#EOF
def main():
db = connect()
logging.basicConfig(level=logging.INFO,
format='%(asctime)s [%(levelname)s] %(message)s',
datefmt='%Y-%m-%d %H:%M:%S')
logging.info('*** Starting: Compute SARA_RATIO ***')
while is_next_job(db, jobtype='SARA_RATIO'):
t0 = time.time()
jobs = get_next_job(db, jobtype='SARA_RATIO')
stations = []
pairs = []
refs = []
for job in jobs:
refs.append(job.ref)
pairs.append(job.pair)
netsta1, netsta2 = job.pair.split(':')
stations.append(netsta1)
stations.append(netsta2)
goal_day = job.day
stations = np.unique(stations)
logging.info("New SARA Job: %s (%i pairs with %i stations)" %
(goal_day, len(pairs), len(stations)))
logging.debug(
"Preloading all envelopes and applying site and sensitivity")
all = {}
for station in stations:
tmp = get_sara_param(db, station)
sensitivity = tmp.sensitivity
site_effect = tmp.site_effect
try:
tmp = read(
os.path.join("SARA", "ENV", station,
"%s.MSEED" % goal_day))
except:
logging.debug("Error reading %s:%s" % (station, goal_day))
continue
for trace in tmp:
trace.data /= (sensitivity * site_effect)
all[station] = tmp
logging.debug("Computing all pairs")
for job in jobs:
netsta1, netsta2 = job.pair.split(':')
net1, sta1 = netsta1.split(".")
net2, sta2 = netsta2.split(".")
trace = Trace()
if netsta1 not in all or netsta2 not in all:
update_job(db,
job.day,
job.pair,
'SARA_RATIO',
'D',
ref=job.ref)
continue
tmp = Stream()
for tr in all[netsta1]:
tmp += tr
for tr in all[netsta2]:
tmp += tr
# tmp = Stream(traces=[all[netsta1], all[netsta2]])
# print(tmp)
tmp.merge()
tmp = make_same_length(tmp)
tmp.merge(fill_value=np.nan)
if len(tmp) > 1:
trace.data = tmp.select(network=net1, station=sta1)[0].data / \
tmp.select(network=net2, station=sta2)[0].data
trace.stats.starttime = tmp[0].stats.starttime
trace.stats.delta = tmp[0].stats.delta
env_output_dir = os.path.join('SARA', 'RATIO',
job.pair.replace(":", "_"))
if not os.path.isdir(env_output_dir):
os.makedirs(env_output_dir)
trace.write(os.path.join(env_output_dir, goal_day + '.MSEED'),
format="MSEED",
encoding="FLOAT32")
update_job(db, job.day, job.pair, 'SARA_RATIO', 'D', ref=job.ref)
del tmp
logging.info("Done. It took %.2f seconds" % (time.time() - t0))
def ncExtract(address):
"""
This function extract a station (data, response file, header) from a
netCDF file
: type rootgrp: netCDF4.Dataset
: param rootgrp: a netCDF version 4 group that contains one event
: type tr: class 'obspy.core.trace.Trace'
: param tr: the trace that will be extracted from the nc file
: type resp_read: str
: param resp_read: the whole response file of the trace in
one string format extracted from the info/respfile attribute
"""
global rootgrp
if not os.path.isdir(os.path.join(address, 'Resp_NC')):
os.mkdir(os.path.join(address, 'Resp_NC'))
if not os.path.isdir(os.path.join(address, 'BH_NC')):
os.mkdir(os.path.join(address, 'BH_NC'))
root_grps = rootgrp.groups
num_iter = 1
print "\n----------------------------"
print "Number of all available"
print "stations in the netCDF file:"
print len(root_grps)
print "----------------------------\n"
if not input['noaxisem'] == 'Y':
axi_open = open(os.path.join(address, 'STATIONS'), 'w')
axi_open.writelines(rootgrp.axisem[17:])
axi_open.close
for grp in root_grps:
print str(num_iter),
stgrp = root_grps[grp]
stdata = stgrp.variables['data'][:]
resp_read = stgrp.respfile
if not resp_read == 'NO RESPONSE FILE AVAILABLE':
resp_open = open(
os.path.join(address, 'Resp_NC', 'RESP.' + stgrp.identity),
'w')
resp_open.writelines(resp_read)
resp_open.close
else:
print '\nNO RESPONSE FILE AVAILABLE for ' + stgrp.identity
ststats = {}
for key in range(0, len(eval(stgrp.headerK))):
ststats[eval(stgrp.headerK)[key]] = eval(stgrp.headerV)[key]
tr = Trace(stdata, ststats)
tr.write(os.path.join(address, 'BH_NC', stgrp.identity), format='SAC')
num_iter += 1
def test_readAndWrite(self):
"""
Tests read and write methods for all installed waveform plug-ins.
"""
data = np.arange(0, 2000)
start = UTCDateTime(2009, 1, 13, 12, 1, 2, 999000)
formats = _getEntryPoints('obspy.plugin.waveform', 'writeFormat')
for format in formats:
# XXX: skip SEGY and SU formats for now as they need some special
# headers.
if format in ['SEGY', 'SU', 'SEG2']:
continue
for native_byteorder in ['<', '>']:
for byteorder in ['<', '>', '=']:
# new trace object in native byte order
dt = np.dtype("int").newbyteorder(native_byteorder)
if format in ('MSEED', 'GSE2'):
# MiniSEED and GSE2 cannot write int64, enforce type
dt = "int32"
tr = Trace(data=data.astype(dt))
tr.stats.network = "BW"
tr.stats.station = "MANZ1"
tr.stats.location = "00"
tr.stats.channel = "EHE"
tr.stats.calib = 0.199999
tr.stats.delta = 0.005
tr.stats.starttime = start
# create waveform file with given format and byte order
outfile = NamedTemporaryFile().name
tr.write(outfile, format=format, byteorder=byteorder)
if format == 'Q':
outfile += '.QHD'
# read in again using auto detection
st = read(outfile)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# read in using format argument
st = read(outfile, format=format)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# read in using a StringIO instances, skip Q files as it
# needs multiple files
if format not in ['Q']:
# file handler without format
temp = open(outfile, 'rb')
st = read(temp)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# file handler with format
temp = open(outfile, 'rb')
st = read(temp, format=format)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# StringIO without format
temp = StringIO.StringIO(open(outfile, 'rb').read())
st = read(temp)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# StringIO with format
temp = StringIO.StringIO(open(outfile, 'rb').read())
st = read(temp, format=format)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# cStringIO without format
temp = cStringIO.StringIO(open(outfile, 'rb').read())
st = read(temp)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# cStringIO with format
temp = cStringIO.StringIO(open(outfile, 'rb').read())
st = read(temp, format=format)
self.assertEquals(len(st), 1)
self.assertEquals(st[0].stats._format, format)
# check byte order
self.assertEquals(st[0].data.dtype.byteorder, '=')
# check meta data
# some formats do not contain a calibration factor
if format not in ['MSEED', 'WAV', 'TSPAIR', 'SLIST']:
self.assertAlmostEquals(st[0].stats.calib, 0.199999, 5)
else:
self.assertEquals(st[0].stats.calib, 1.0)
if format not in ['WAV']:
self.assertEquals(st[0].stats.starttime, start)
self.assertEquals(st[0].stats.endtime, start + 9.995)
self.assertEquals(st[0].stats.delta, 0.005)
self.assertEquals(st[0].stats.sampling_rate, 200.0)
# network/station/location/channel codes
if format in ['Q', 'SH_ASC', 'GSE2']:
# no network or location code in Q, SH_ASC, GSE2
self.assertEquals(st[0].id, ".MANZ1..EHE")
elif format not in ['WAV']:
self.assertEquals(st[0].id, "BW.MANZ1.00.EHE")
# remove temporary files
os.remove(outfile)
# Q files consist of two files - deleting additional file
if format == 'Q':
os.remove(outfile[:-4] + '.QBN')
os.remove(outfile[:-4])
else:
for ia, a in enumerate(gminor):
# if ia >50:continue
binfileA = [a]
binfileB = [gmajor[ia]]
c3 = c3_from_bin_fun(s1, s2, d, binfileA, binfileB)
datac3 = np.vstack((datac3, c3))
print np.shape(datac3)
corrc3 = stack(datac3, stack_method='linear')
t = Trace()
t.stats.station = 'pc3'
t.stats.sampling_rate = df
t.data = np.array(corrc3[::-1])
t.stats.starttime -= (len(corrc3) / 2) / df
if sorted:
t.write('pc3/prestackc3.%s.%s.mseed' % (s1, s2), format='MSEED')
else:
t.write('pc3/random_prestackc3.%s.%s.mseed' % (s1, s2), format='MSEED')
if __name__ == '__main__':
#staTarget1 = '235713'
#staTarget2 = '236977'
#depth = 0.
prestackc3(sys.argv[1:])
#EOF
def test_readThreadSafe(self):
"""
Tests for race conditions. Reading n_threads (currently 30) times
the same waveform file in parallel and compare the results which must
be all the same.
"""
data = np.arange(0, 500)
start = UTCDateTime(2009, 1, 13, 12, 1, 2, 999000)
formats = _getEntryPoints('obspy.plugin.waveform', 'writeFormat')
for format in formats:
# XXX: skip SEGY and SU formats for now as they need some special
# headers.
if format in ['SEGY', 'SU', 'SEG2']:
continue
dt = np.dtype("int")
if format in ('MSEED', 'GSE2'):
dt = "int32"
tr = Trace(data=data.astype(dt))
tr.stats.network = "BW"
tr.stats.station = "MANZ1"
tr.stats.location = "00"
tr.stats.channel = "EHE"
tr.stats.calib = 0.999999
tr.stats.delta = 0.005
tr.stats.starttime = start
# create waveform file with given format and byte order
outfile = NamedTemporaryFile().name
tr.write(outfile, format=format)
if format == 'Q':
outfile += '.QHD'
n_threads = 30
streams = []
def testFunction(streams):
st = read(outfile, format=format)
streams.append(st)
# Read the ten files at one and save the output in the just created
# class.
for _i in xrange(n_threads):
thread = threading.Thread(target=testFunction,
args=(streams, ))
thread.start()
# Loop until all threads are finished.
start = time.time()
while True:
if threading.activeCount() == 1:
break
# Avoid infinite loop and leave after 120 seconds
# such a long time is needed for debugging with valgrind
elif time.time() - start >= 120:
msg = 'Not all threads finished!'
raise Warning(msg)
break
else:
continue
# Compare all values which should be identical and clean up files
#for data in :
# np.testing.assert_array_equal(values, original)
os.remove(outfile)
if format == 'Q':
os.remove(outfile[:-4] + '.QBN')
os.remove(outfile[:-4])
