def _km_to_deg_lat(kilometers):
"""
Convenience tool for converting km to degrees latitude.
"""
try:
degrees = kilometers2degrees(kilometers)
except Exception:
degrees = None
return degrees
def _km_to_deg_lon(kilometers, latitude):
"""
Convenience tool for converting km to degrees longitude.
latitude in degrees
"""
try:
degrees_lat = kilometers2degrees(kilometers)
except Exception:
return None
degrees_lon = degrees_lat / cos(radians(latitude))
return degrees_lon
def process(asdf_source, event_folder, output_path, min_magnitude, restart,
save_quality_plots):
"""
ASDF_SOURCE: Text file containing a list of paths to ASDF files
EVENT_FOLDER: Path to folder containing event files\n
OUTPUT_PATH: Output folder \n
"""
comm = MPI.COMM_WORLD
nproc = comm.Get_size()
rank = comm.Get_rank()
proc_workload = None
if (rank == 0):
def outputConfigParameters():
# output config parameters
fn = 'pick.%s.cfg' % (datetime.now().strftime('%Y-%m-%d-%H-%M-%S'))
fn = os.path.join(output_path, fn)
f = open(fn, 'w+')
f.write('Parameter Values:\n\n')
f.write('%25s\t\t: %s\n' % ('ASDF_SOURCE', asdf_source))
f.write('%25s\t\t: %s\n' % ('EVENT_FOLDER', event_folder))
f.write('%25s\t\t: %s\n' % ('OUTPUT_PATH', output_path))
f.write('%25s\t\t: %s\n' % ('MIN_MAGNITUDE', min_magnitude))
f.write('%25s\t\t: %s\n' %
('RESTART_MODE', 'TRUE' if restart else 'FALSE'))
f.write('%25s\t\t: %s\n' %
('SAVE_PLOTS', 'TRUE' if save_quality_plots else 'FALSE'))
f.close()
# end func
outputConfigParameters()
# end if
# ==================================================
# Create output-folder for snr-plots
# ==================================================
plot_output_folder = None
if (save_quality_plots):
plot_output_folder = os.path.join(output_path, 'plots')
if (rank == 0):
if (not os.path.exists(plot_output_folder)):
os.mkdir(plot_output_folder)
# end if
comm.Barrier()
# end if
# ==================================================
# Read catalogue and retrieve origin times
# ==================================================
cat = CatalogCSV(event_folder)
events = cat.get_events()
originTimestamps = cat.get_preferred_origin_timestamps()
# ==================================================
# Create lists of pickers for both p- and s-arrivals
# ==================================================
sigmalist = np.arange(8, 3, -1)
pickerlist_p = []
pickerlist_s = []
for sigma in sigmalist:
picker_p = aicdpicker.AICDPicker(t_ma=5,
nsigma=sigma,
t_up=1,
nr_len=5,
nr_coeff=2,
pol_len=10,
pol_coeff=10,
uncert_coeff=3)
picker_s = aicdpicker.AICDPicker(t_ma=15,
nsigma=sigma,
t_up=1,
nr_len=5,
nr_coeff=2,
pol_len=10,
pol_coeff=10,
uncert_coeff=3)
pickerlist_p.append(picker_p)
pickerlist_s.append(picker_s)
# end for
# ==================================================
# Define theoretical model
# Instantiate data-access object
# Retrieve estimated workload
# ==================================================
taupyModel = TauPyModel(model='iasp91')
fds = FederatedASDFDataSet(asdf_source, use_json_db=False, logger=None)
workload = getWorkloadEstimate(fds, originTimestamps)
# ==================================================
# Define output header and open output files
# depending on the mode of operation (fresh/restart)
# ==================================================
header = '#eventID originTimestamp mag originLon originLat originDepthKm net sta cha pickTimestamp stationLon stationLat az baz distance ttResidual snr qualityMeasureCWT domFreq qualityMeasureSlope bandIndex nSigma\n'
ofnp = os.path.join(output_path, 'p_arrivals.%d.txt' % (rank))
ofns = os.path.join(output_path, 's_arrivals.%d.txt' % (rank))
ofp = None
ofs = None
if (restart == False):
ofp = open(ofnp, 'w+')
ofs = open(ofns, 'w+')
ofp.write(header)
ofs.write(header)
else:
ofp = open(ofnp, 'a+')
ofs = open(ofns, 'a+')
# end if
progTracker = ProgressTracker(output_folder=output_path,
restart_mode=restart)
totalTraceCount = 0
for nc, sc, start_time, end_time in fds.local_net_sta_list():
day = 24 * 3600
dayCount = 0
curr = start_time
traceCountP = 0
pickCountP = 0
traceCountS = 0
pickCountS = 0
sw_start = datetime.now()
step = day
while (curr < end_time):
if (curr + step > end_time):
step = end_time - curr
# end if
eventIndices = (np.where((originTimestamps >= curr.timestamp) & \
(originTimestamps <= (curr + day).timestamp)))[0]
if (eventIndices.shape[0] > 0):
totalTraceCount += 1
stations = fds.get_stations(curr,
curr + day,
network=nc,
station=sc)
stations_zch = [s for s in stations
if 'Z' in s[3]] # only Z channels
stations_nch = [
s for s in stations if 'N' in s[3] or '1' in s[3]
] # only N channels
stations_ech = [
s for s in stations if 'E' in s[3] or '2' in s[3]
] # only E channels
for codes in stations_zch:
if (progTracker.increment()): pass
else: continue
st = fds.get_waveforms(codes[0],
codes[1],
codes[2],
codes[3],
curr,
curr + step,
automerge=True,
trace_count_threshold=200)
if (len(st) == 0): continue
dropBogusTraces(st)
slon, slat = codes[4], codes[5]
for ei in eventIndices:
event = events[ei]
po = event.preferred_origin
da = gps2dist_azimuth(po.lat, po.lon, slat, slon)
mag = None
if (event.preferred_magnitude):
mag = event.preferred_magnitude.magnitude_value
elif (len(po.magnitude_list)):
mag = po.magnitude_list[0].magnitude_value
if (mag == None): mag = np.NaN
if (np.isnan(mag) or mag < min_magnitude): continue
result = extract_p(
taupyModel,
pickerlist_p,
event,
slon,
slat,
st,
plot_output_folder=plot_output_folder)
if (result):
picklist, residuallist, snrlist, bandindex, pickerindex = result
arcdistance = kilometers2degrees(da[0] / 1e3)
for ip, pick in enumerate(picklist):
line = '%s %f %f %f %f %f ' \
'%s %s %s %f %f %f ' \
'%f %f %f ' \
'%f %f %f %f %f '\
'%d %d\n' % (event.public_id, po.utctime.timestamp, mag, po.lon, po.lat, po.depthkm,
codes[0], codes[1], codes[3], pick.timestamp, slon, slat,
da[1], da[2], arcdistance,
residuallist[ip], snrlist[ip, 0], snrlist[ip, 1], snrlist[ip, 2], snrlist[ip, 3],
bandindex, sigmalist[pickerindex])
ofp.write(line)
# end for
ofp.flush()
pickCountP += 1
# end if
if (len(stations_nch) == 0 and len(stations_ech) == 0):
result = extract_s(
taupyModel,
pickerlist_s,
event,
slon,
slat,
st,
None,
da[2],
plot_output_folder=plot_output_folder)
if (result):
picklist, residuallist, snrlist, bandindex, pickerindex = result
arcdistance = kilometers2degrees(da[0] / 1e3)
for ip, pick in enumerate(picklist):
line = '%s %f %f %f %f %f ' \
'%s %s %s %f %f %f ' \
'%f %f %f ' \
'%f %f %f %f %f ' \
'%d %d\n' % (event.public_id, po.utctime.timestamp, mag, po.lon, po.lat, po.depthkm,
codes[0], codes[1], codes[3], pick.timestamp, slon, slat,
da[1], da[2], arcdistance,
residuallist[ip], snrlist[ip, 0], snrlist[ip, 1], snrlist[ip, 2], snrlist[ip, 3],
bandindex, sigmalist[pickerindex])
ofs.write(line)
# end for
ofs.flush()
pickCountS += 1
# end if
# end if
# end for
traceCountP += len(st)
# end for
if (len(stations_nch) > 0
and len(stations_nch) == len(stations_ech)):
for codesn, codese in zip(stations_nch, stations_ech):
if (progTracker.increment()): pass
else: continue
stn = fds.get_waveforms(codesn[0],
codesn[1],
codesn[2],
codesn[3],
curr,
curr + step,
automerge=True,
trace_count_threshold=200)
ste = fds.get_waveforms(codese[0],
codese[1],
codese[2],
codese[3],
curr,
curr + step,
automerge=True,
trace_count_threshold=200)
dropBogusTraces(stn)
dropBogusTraces(ste)
if (len(stn) == 0): continue
if (len(ste) == 0): continue
slon, slat = codesn[4], codesn[5]
for ei in eventIndices:
event = events[ei]
po = event.preferred_origin
da = gps2dist_azimuth(po.lat, po.lon, slat, slon)
mag = None
if (event.preferred_magnitude):
mag = event.preferred_magnitude.magnitude_value
elif (len(po.magnitude_list)):
mag = po.magnitude_list[0].magnitude_value
if (mag == None): mag = np.NaN
if (np.isnan(mag) or mag < min_magnitude): continue
result = extract_s(
taupyModel,
pickerlist_s,
event,
slon,
slat,
stn,
ste,
da[2],
plot_output_folder=plot_output_folder)
if (result):
picklist, residuallist, snrlist, bandindex, pickerindex = result
arcdistance = kilometers2degrees(da[0] / 1e3)
for ip, pick in enumerate(picklist):
line = '%s %f %f %f %f %f ' \
'%s %s %s %f %f %f ' \
'%f %f %f ' \
'%f %f %f %f %f ' \
'%d %d\n' % (event.public_id, po.utctime.timestamp, mag, po.lon, po.lat, po.depthkm,
codesn[0], codesn[1], '00T', pick.timestamp, slon, slat,
da[1], da[2], arcdistance,
residuallist[ip], snrlist[ip, 0], snrlist[ip, 1], snrlist[ip, 2], snrlist[ip, 3],
bandindex, sigmalist[pickerindex])
ofs.write(line)
# end for
ofs.flush()
pickCountS += 1
# end if
# end for
traceCountS += (len(stn) + len(ste))
# end for
# end if
# end if
curr += step
dayCount += 1
# wend
sw_stop = datetime.now()
totalTime = (sw_stop - sw_start).total_seconds()
gc.collect()
print '(Rank %d: %5.2f%%, %d/%d) Processed %d traces and found %d p-arrivals and %d s-arrivals for ' \
'network %s station %s in %f s. Memory usage: %5.2f MB.' % \
(rank, (float(totalTraceCount) / float(workload) * 100) if workload > 0 else 100, totalTraceCount, workload,
traceCountP + traceCountS, pickCountP, pickCountS, nc, sc, totalTime,
round(psutil.Process().memory_info().rss / 1024. / 1024., 2))
# end for
ofp.close()
ofs.close()
print 'Processing complete on rank %d' % (rank)
del fds
def process(data_path, scratch_path, output_file_stem):
"""
DATA_PATH: input-folder which contains output from iloc_phase_ident.py \n
SCRATCH_PATH: scratch-folder \n
OUTPUT_FILE_STEM: output file stem \n
"""
comm = MPI.COMM_WORLD
nproc = comm.Get_size()
rank = comm.Get_rank()
# Fetch and distribute event-ids
eventIds = []
inventory = defaultdict(list)
if (rank==0):
files = recursive_glob(data_path, "*.txt")
for f in files:
d = np.genfromtxt(f, dtype=[('mstring','S100'),('mfloat','f8')], skip_header=1)
for item in np.atleast_1d(d):
if(item[1]>0): eventIds.append(item[0])
# end for
# end for
s = set(eventIds)
assert len(s) == len(eventIds), 'Duplicate event-ids found'
print (('Processing %d events..'%(len(eventIds))))
shuffle(eventIds)
eventIds = split_list(eventIds, nproc)
# fetch inventory
db = None
try:
db = MySQLdb.connect(host="localhost",
user="******",
passwd="sysop",
db="seiscomp3")
except:
raise Exception('Failed to connect to database')
# end try
c = db.cursor()
c.execute('select n.code, s.code, s.longitude, s.latitude from Network n, Station s where s._parent_oid=n._oid group by n.code, s.code')
rows = c.fetchall()
for row in rows:
inventory['%s.%s'%(row[0], row[1])] = [row[2], row[3]]
# end for
db.close()
#end if
eventIds = comm.scatter(eventIds, root = 0)
inventory = comm.bcast(inventory, root = 0)
pprocfile = open('%s/pproc.%d.txt'%(scratch_path, rank), 'w+')
sprocfile = open('%s/sproc.%d.txt'%(scratch_path, rank), 'w+')
allprocfile = open('%s/allproc.%d.txt'%(scratch_path, rank), 'w+')
for eid in tqdm(eventIds):
ofn = '%s/%s.xml'%(scratch_path, eid.split('/')[-1])
cmd = ['scxmldump -d mysql://sysop:sysop@localhost/seiscomp3 -E %s -PAMf -o %s'%
(eid, ofn)]
rc, _ = runprocess(cmd, get_results=False)
if(rc!=0):
print (('Error exporting event: %s'%(eid)))
else:
notFound = defaultdict(int)
cat = read_events(ofn, format='SC3ML')
linesp = []
liness = []
linesall = []
for e in cat.events:
po = e.preferred_origin()
# retrieve depth; some preferred origins don't have depth values
poDepth = po.depth
if(poDepth == None):
for o in e.origins:
if(o.depth): poDepth = o.depth
# end for
# end if
if(poDepth == None): continue
for a in po.arrivals:
try:
ncode = a.pick_id.get_referred_object().waveform_id.network_code
scode = a.pick_id.get_referred_object().waveform_id.station_code
ccode = a.pick_id.get_referred_object().waveform_id.channel_code
except:
continue
slon = None
slat = None
try:
slon, slat = inventory['%s.%s'%(ncode, scode)]
except:
notFound['%s.%s'%(ncode, scode)] += 1
continue
# end try
# get band-index and snr from comments
pick_attribs = defaultdict(lambda:-999.)
pick = a.pick_id.get_referred_object()
for c in pick.comments:
if ('text' in list(c.keys())):
for item in c['text'].split(','):
k,v = item.split('=')
pick_attribs[k.strip()] = float(v)
# end for
# end if
# end for
# get az, baz and distance
da = gps2dist_azimuth(po.latitude, po.longitude, slat, slon)
# create row
#if(a.phase not in ['P', 'S']): continue
if(a.time_residual is None): continue
line = [eid, '{:<25s}',
po.time.timestamp, '{:f}',
e.magnitudes[0].mag if (len(e.magnitudes)) else -999, '{:f}',
po.longitude, '{:f}',
po.latitude, '{:f}',
poDepth/1e3, '{:f}',
ncode, '{:<5s}',
scode, '{:<5s}',
ccode, '{:<5s}',
pick.time.timestamp, '{:f}',
a.phase, '{:<5s}',
slon, '{:f}',
slat, '{:f}',
da[1], '{:f}',
da[2], '{:f}',
kilometers2degrees(da[0]/1e3), '{:f}',
a.time_residual, '{:f}',
pick_attribs['phasepapy_snr'], '{:f}',
pick_attribs['quality_measure_cwt'], '{:f}',
pick_attribs['dom_freq'], '{:f}',
pick_attribs['quality_measure_slope'], '{:f}',
int(pick_attribs['band_index']), '{:d}',
int(pick_attribs['nsigma']), '{:d}']
linesall.append(line)
if(a.phase == 'P' or a.phase == 'Pg'): linesp.append(line)
elif(a.phase == 'S' or a.phase == 'Sg'): liness.append(line)
# end for
# end for
for line in linesp:
lineout = ' '.join(line[1::2]).format(*line[::2])
pprocfile.write(lineout + '\n')
# end for
for line in liness:
lineout = ' '.join(line[1::2]).format(*line[::2])
sprocfile.write(lineout + '\n')
# end for
for line in linesall:
lineout = ' '.join(line[1::2]).format(*line[::2])
allprocfile.write(lineout + '\n')
# end for
if (len(notFound)): print (('Rank: %d'%(rank), notFound))
# end if
if (os.path.exists(ofn)): os.remove(ofn)
#break
# end for
pprocfile.close()
sprocfile.close()
allprocfile.close()
header = '#eventID originTimestamp mag originLon originLat originDepthKm net sta cha pickTimestamp phase stationLon stationLat az baz distance ttResidual snr qualityMeasureCWT domFreq qualityMeasureSlope bandIndex nSigma\n'
comm.barrier()
if(rank == 0):
ofp = open(output_file_stem + '.p.txt', 'w+')
ofs = open(output_file_stem + '.s.txt', 'w+')
ofall = open(output_file_stem + '.all.txt', 'w+')
ofp.write(header)
ofs.write(header)
ofall.write(header)
for i in range(nproc):
pfn = '%s/pproc.%d.txt'%(scratch_path, i)
sfn = '%s/sproc.%d.txt'%(scratch_path, i)
allfn = '%s/allproc.%d.txt'%(scratch_path, i)
lines = open(pfn, 'r').readlines()
for line in lines:
ofp.write(line)
# end for
lines = open(sfn, 'r').readlines()
for line in lines:
ofs.write(line)
# end for
lines = open(allfn, 'r').readlines()
for line in lines:
ofall.write(line)
# end for
if (os.path.exists(pfn)): os.remove(pfn)
if (os.path.exists(sfn)): os.remove(sfn)
if (os.path.exists(allfn)): os.remove(allfn)
# end for
ofp.close()
ofs.close()
ofall.close()
def _load_events(self):
self._load_events_helper()
cache = {}
notFound = defaultdict(int)
oEvents = []
missingStations = defaultdict(int)
for e in self.eventList:
if (e.preferred_origin and len(e.preferred_origin.arrival_list)):
cullList = []
for a in e.preferred_origin.arrival_list:
if (len(a.net)): continue
seedid = '%s.%s.%s.%s' % (a.net, a.sta, a.loc, a.cha)
newCode = None
if (seedid not in cache):
sc = a.sta
lonlat = self.isc_coords_dict[sc]
if (len(lonlat) == 0):
cullList.append(a)
continue
# end if
r = self.fdsn_inventory.getClosestStations(lonlat[0],
lonlat[1],
maxdist=1e3)
#if(a.sta=='KUM'): print a.net, a.sta, a.loc, a.cha, r
if (not r):
notFound[sc] += 1
else:
for cr in r[0]:
c = cr.split('.')[0]
newCode = c
# end for
# end if
if (newCode):
cache[seedid] = newCode
# end if
else:
newCode = cache[seedid]
# end if
if (newCode):
#print a.net, newCode
a.net = newCode
sc = self.fdsn_inventory.t[a.net][a.sta]
if (type(sc) == defaultdict):
cullList.append(a)
continue
# end if
da = gps2dist_azimuth(e.preferred_origin.lat,
e.preferred_origin.lon, sc[1],
sc[0])
dist = kilometers2degrees(da[0] / 1e3)
if (np.fabs(a.distance - dist) > 0.5):
cullList.append(a)
# end if
# end if
# end for
for c in cullList:
e.preferred_origin.arrival_list.remove(c)
# end if
# Create obspy event object
ci = OCreationInfo(author='GA',
creation_time=UTCDateTime(),
agency_id='GA-iteration-1')
oid = self.get_id()
origin = OOrigin(resource_id=OResourceIdentifier(id=oid),
time=UTCDateTime(e.preferred_origin.utctime),
longitude=e.preferred_origin.lon,
latitude=e.preferred_origin.lat,
depth=e.preferred_origin.depthkm * 1e3,
method_id=OResourceIdentifier(id='unknown'),
earth_model_id=OResourceIdentifier(id='iasp91'),
evaluation_mode='automatic',
creation_info=ci)
magnitude = OMagnitude(
resource_id=OResourceIdentifier(id=self.get_id()),
mag=e.preferred_magnitude.magnitude_value,
magnitude_type=e.preferred_magnitude.magnitude_type,
origin_id=OResourceIdentifier(id=oid),
creation_info=ci)
event = OEvent(resource_id=OResourceIdentifier(id=self.get_id()),
creation_info=ci,
event_type='earthquake')
event.origins = [origin]
event.magnitudes = [magnitude]
event.preferred_magnitude_id = magnitude.resource_id
event.preferred_origin_id = origin.resource_id
# Insert old picks
for a in e.preferred_origin.arrival_list:
if (type(self.fdsn_inventory.t[a.net][a.sta]) == defaultdict):
missingStations[a.net + '.' + a.sta] += 1
continue
# end if
oldPick = OPick(
resource_id=OResourceIdentifier(id=self.get_id()),
time=UTCDateTime(a.utctime),
waveform_id=OWaveformStreamID(network_code=a.net,
station_code=a.sta,
channel_code=a.cha),
methodID=OResourceIdentifier('unknown'),
phase_hint=a.phase,
evaluation_mode='automatic',
creation_info=ci)
oldArr = OArrival(resource_id=OResourceIdentifier(
id=oldPick.resource_id.id + "#"),
pick_id=oldPick.resource_id,
phase=oldPick.phase_hint,
distance=a.distance,
earth_model_id=OResourceIdentifier(
'quakeml:ga.gov.au/earthmodel/iasp91'),
creation_info=ci)
event.picks.append(oldPick)
event.preferred_origin().arrivals.append(oldArr)
# end for
# Insert our picks
opList = self.our_picks.picks[e.public_id]
if (len(opList)):
for op in opList:
if (type(self.fdsn_inventory.t[op[1]][op[2]]) ==
defaultdict):
missingStations[op[1] + '.' + op[2]] += 1
continue
# end if
newPick = OPick(
resource_id=OResourceIdentifier(id=self.get_id()),
time=UTCDateTime(op[0]),
waveform_id=OWaveformStreamID(network_code=op[1],
station_code=op[2],
channel_code=op[3]),
methodID=OResourceIdentifier('phasepapy/aicd'),
backazimuth=op[-1],
phase_hint=op[4],
evaluation_mode='automatic',
comments=op[6],
creation_info=ci)
newArr = OArrival(
resource_id=OResourceIdentifier(
id=newPick.resource_id.id + "#"),
pick_id=newPick.resource_id,
phase=newPick.phase_hint,
azimuth=op[-2],
distance=op[-3],
time_residual=op[5],
time_weight=1.,
earth_model_id=OResourceIdentifier(
'quakeml:ga.gov.au/earthmodel/iasp91'),
creation_info=ci)
event.picks.append(newPick)
event.preferred_origin().arrivals.append(newArr)
# end for
# end if
quality = OOriginQuality(
associated_phase_count=len(e.preferred_origin.arrival_list) +
len(self.our_picks.picks[e.public_id]),
used_phase_count=len(e.preferred_origin.arrival_list) +
len(self.our_picks.picks[e.public_id]))
event.preferred_origin().quality = quality
oEvents.append(event)
# end for // loop over e
#print notFound
print self.rank, missingStations
cat = OCatalog(events=oEvents)
ofn = self.output_path + '/%d.xml' % (self.rank)
cat.write(ofn, format='SC3ML')
def write_antelope_db(db_path, origin, arrival, site, algorithm, auth_name):
'''
Creates an Antelope database from csv data so that Antelope utilities
can be applied to the data. The assoc file contains the required
information to relate an event to it's picks.
Parameters
----------
db_path : str
The path to the directory where you would like to create the database
origin : pd.DataFrame()
A DataFrame with the following columns:
- lat: A column of floats describing latitude information.
- lon: A column of floats describing longitude information.
- depth: A column of floats describing depth information.
- datetime: A str of the form %Y-%m-%d %H:%M:%S.%f
- quality: A float describing the number of picks used in the
location calculation
- orid: A column of unique identifiers for origin. Has corresponding
entries in the arrival table
arrival : pd.DAtaFrame()
A dataframe with the following columns:
- sta: A str describing the station name
- datetime: A str of the form %Y-%m-%d %H:%M:%S.%f
- phase: A str describing the phase type of a given arrival, must be P
or S
- orid: The origin that each arrival corresponds to. Has corresponding
entries in the origin table
site : pd.DataFrame()
A DataFrame with the following columns:
- sta: A str describing the station name
- lat : A float describing the latitude of the station
- lon : A float describing the longitude of the station
algorithm : str
The name of the algorithm used to calculate earthquake location.
auth_name : str
The name of the author of the database. I would suggest using the agency you
are affiliated with.
Returns
-------
None :
Returns nothing as the purpose of this function is to create database files
that can be used by Antelope.
'''
if os.path.exists(db_path):
pass
else:
os.mkdir(db_path)
#Resets the index's of the DataFrames so that the index can be used to iterate
origin.reset_index(inplace=True, drop=True)
arrival.reset_index(inplace=True, drop=True)
origin["epoch_time"] = origin.datetime.apply(str_to_epoch)
arrival["epoch_time"] = arrival.datetime.apply(str_to_epoch)
origin_file = open(db_path + 'db.origin', 'w')
arrival_file = open(db_path + 'db.arrival', 'w')
assoc_file = open(db_path + 'db.assoc', 'w')
event_file = open(db_path + 'db.event', 'w')
origerr_file = open(db_path + 'db.origerr', 'w')
ts = datetime.now().timestamp()
t = round(ts, 5)
arid = 1
#Loops over all the origins
for i in range(len(origin.index)):
#Prints a line to the origin file with the correct formatting
origin_file.write(
'%9.4f %9.4f %9.4f %17.5f %8d %8d %8d %4d %4d %4d %8d '
'%8d %-2s %-4s %9.4f %-s %7.2f %8d %7.2f %8d %7.2f %8d '
'%-15s %-15s %8d %17.5f\n' %
(origin.lat[i], origin.lon[i], origin.depth[i],
origin.epoch_time[i], i + 1, i + 1, -1, origin.nass[i],
origin.ndef[i], -1, -1, -1, '-', '-', -999, '-', -999, -1, -999,
-1, -999, -1, algorithm, algorithm + ':' + auth_name, -1, t))
#Prints a line to the event file with the correct formatting
event_file.write('%8d %-15s %8d %-15s %8d %17.5f\n' %
(i + 1, '-', -1, 'S-SNAP:PGC', -1, t))
#Prints a line to the origerr file with the correct formatting
#=============================================================
#orid, sxx, syy, szz, stt, sxy, sxz, syz, stx, sty, stz, sdobs,
#smajax, sminax, strike, sdepth, stime, conf, lddate
#=============================================================
origerr_file.write(
'%8d %15.4f %15.4f %15.4f %15.4f %15.4f %15.4f '
'%15.4f %15.4f %15.4f %15.4f %9.4f %9.4f %9.4f %6.2f %9.4f '
'%8.2f %5.3f %8d %17.5f\n' %
(i + 1, -999999999.9999, -999999999.9999, -999999999.9999,
-999999999.9999, -999999999.9999, -999999999.9999,
-999999999.9999, -999999999.9999, -999999999.9999,
-999999999.9999, -1.0000, -1.0000, -1.0000, -1.00, -1.0000, -1.00,
0.000, -1, t))
tmp_orid = origin.orid[i]
tmp_arrival = arrival[arrival.orid == tmp_orid]
ev_lat = origin.lat[i]
ev_lon = origin.lon[i]
for j in tmp_arrival.index: #range(len(tmp_arrival.index)):
sta = arrival.sta[j]
sta_lat = site.lat[site.sta == sta].iloc[0]
sta_lon = site.lon[site.sta == sta].iloc[0]
sta_coords = (sta_lat, sta_lon)
ev_coords = (ev_lat, ev_lon)
dist = geodesic(sta_coords, ev_coords).km
delta = kilometers2degrees(dist)
if arrival.phase[j] == 'S' and sta in [
'NBC8', 'NBC7', 'TD009', 'TD002'
]:
chan = 'HH1'
elif arrival.phase[j] == 'S' and sta not in [
'NBC8', 'NBC7', 'TD009', 'TD002'
]:
chan = 'HHE'
elif arrival.phase[j] == 'P':
chan = 'HHZ'
#Prints a line to the arrival file with correct formatting
arrival_file.write(
'%-6s %17.5f %8d %8d %8d %8d %-8s %-8s %s %6.3f %7.2f %7.2f %7.2f '
'%7.2f %7.2f %7.3f %10.1f %7.2f %7.2f %s %-2s %10d %s %-16s %7d %17.5f\n'
% (arrival.sta[j], arrival.epoch_time[j], arid, -1, -1, -1,
chan, arrival.phase[j], '-', -1.000, -1.0, -1.0, -1.0, -1.0,
-1.0, -1.0, -1.0, -1.0, -999.00, '-', '-', -1, '-',
'S-SNAP:PGC', -1, t))
#Prints a line to the assoc file with correct formatting.
assoc_file.write(
'%8d %8d %-6s %-8s %4.2f %8.3f %7.2f %7.2f %8.3f '
'%-s %7.1f %-s %-7.2f %-s %7.1f %6.3f %-15s %8d %17.5f\n' %
(arid, i + 1, arrival.sta[j], arrival.phase[j], 9.99, delta,
-1, -1, -999.000, 'd', -999.0, '-', -999, '-', -999.0, 1, '-',
-1, t))
arid += 1
origin_file.close()
arrival_file.close()
assoc_file.close()
event_file.close()
return None
def process(data_path, inventory_file, scratch_path, output_file_stem):
"""
DATA_PATH: input-folder
Inventory: FDSN inventory
SCRATCH_PATH: scratch-folder
OUTPUT_FILE_STEM: output file stem
"""
comm = MPI.COMM_WORLD
nproc = comm.Get_size()
rank = comm.Get_rank()
# Fetch and distribute xml files
inventory = defaultdict(list)
files = []
if (rank == 0):
files = recursive_glob(data_path, "*.xml")
files = split_list(files, nproc)
inv = read_inventory(inventory_file)
for n in inv.networks:
for s in n.stations:
inventory['%s.%s' % (n.code, s.code)] = [
s.longitude, s.latitude, s.elevation
]
# end for
# end for
# end if
inventory = comm.bcast(inventory, root=0)
files = comm.scatter(files, root=0)
pprocfile = open('%s/pproc.%d.txt' % (scratch_path, rank), 'w+')
sprocfile = open('%s/sproc.%d.txt' % (scratch_path, rank), 'w+')
for file in files:
cat = read_events(file, format='SC3ML')
notFound = defaultdict(int)
linesp = []
liness = []
for e in tqdm(cat.events, desc='Rank: %d' % (rank)):
po = e.preferred_origin()
# retrieve depth; some preferred origins don't have depth values
poDepth = po.depth
if (poDepth == None):
for o in e.origins:
if (o.depth): poDepth = o.depth
# end for
# end if
if (poDepth == None): continue
for a in po.arrivals:
try:
ncode = a.pick_id.get_referred_object(
).waveform_id.network_code
scode = a.pick_id.get_referred_object(
).waveform_id.station_code
ccode = a.pick_id.get_referred_object(
).waveform_id.channel_code
except:
continue
slon = None
slat = None
try:
slon, slat = inventory[ncode][scode]
except:
notFound['%s.%s' % (ncode, scode)] += 1
continue
# end try
# get band-index and snr from comments
pick_attribs = defaultdict(lambda: -999.)
pick = a.pick_id.get_referred_object()
for c in pick.comments:
if ('text' in c.keys()):
for item in c['text'].split(','):
k, v = item.split('=')
pick_attribs[k.strip()] = float(v)
# end for
# end if
# end for
# get az, baz and distance
da = gps2dist_azimuth(po.latitude, po.longitude, slat, slon)
# create row
if (a.phase not in ['P', 'S']): continue
if (a.time_residual is None): continue
line = [
e.resource_id, '{:<25s}', po.time.timestamp, '{:f}',
e.magnitudes[0].mag if (len(e.magnitudes)) else -999,
'{:f}', po.longitude, '{:f}', po.latitude, '{:f}',
poDepth / 1e3, '{:f}', ncode, '{:<5s}', scode, '{:<5s}',
ccode, '{:<5s}', pick.time.timestamp, '{:f}', a.phase,
'{:<5s}', slon, '{:f}', slat, '{:f}', da[1], '{:f}', da[2],
'{:f}',
kilometers2degrees(da[0] / 1e3), '{:f}', a.time_residual,
'{:f}', pick_attribs['phasepapy_snr'], '{:f}',
pick_attribs['quality_measure_cwt'], '{:f}',
pick_attribs['dom_freq'], '{:f}',
pick_attribs['quality_measure_slope'], '{:f}',
int(pick_attribs['band_index']), '{:d}',
int(pick_attribs['nsigma']), '{:d}'
]
if (a.phase == 'P'): linesp.append(line)
elif (a.phase == 'S'): liness.append(line)
# end for
# end for
for line in linesp:
lineout = ' '.join(line[1::2]).format(*line[::2])
pprocfile.write(lineout + '\n')
# end for
for line in liness:
lineout = ' '.join(line[1::2]).format(*line[::2])
sprocfile.write(lineout + '\n')
# end for
if (len(notFound)): print 'Rank: %d' % (rank), notFound
# end for
pprocfile.close()
sprocfile.close()
header = '#eventID originTimestamp mag originLon originLat originDepthKm net sta cha pickTimestamp phase stationLon stationLat az baz distance ttResidual snr qualityMeasureCWT domFreq qualityMeasureSlope bandIndex nSigma\n'
comm.barrier()
if (rank == 0):
ofp = open(output_file_stem + '.p.txt', 'w+')
ofs = open(output_file_stem + '.s.txt', 'w+')
ofp.write(header)
ofs.write(header)
for i in range(nproc):
pfn = '%s/pproc.%d.txt' % (scratch_path, i)
sfn = '%s/sproc.%d.txt' % (scratch_path, i)
lines = open(pfn, 'r').readlines()
for line in lines:
ofp.write(line)
# end for
lines = open(sfn, 'r').readlines()
for line in lines:
ofs.write(line)
# end for
if (os.path.exists(pfn)): os.remove(pfn)
if (os.path.exists(sfn)): os.remove(sfn)
# end for
ofp.close()
ofs.close()
def process(asdf_source, event_folder, output_path, min_magnitude):
"""
ASDF_SOURCE: Text file containing a list of paths to ASDF files
EVENT_FOLDER: Path to folder containing event files\n
OUTPUT_PATH: Output folder \n
"""
comm = MPI.COMM_WORLD
nproc = comm.Get_size()
rank = comm.Get_rank()
proc_workload = None
if (rank == 0):
def outputConfigParameters():
# output config parameters
fn = 'pick.%s.cfg' % (
UTCDateTime.now().strftime("%y-%m-%d.T%H.%M"))
fn = os.path.join(output_path, fn)
f = open(fn, 'w+')
f.write('Parameters Values:\n\n')
f.write('%25s\t\t: %s\n' % ('ASDF_SOURCE', asdf_source))
f.write('%25s\t\t: %s\n' % ('EVENT_FOLDER', event_folder))
f.write('%25s\t\t: %s\n' % ('OUTPUT_PATH', output_path))
f.close()
# end func
outputConfigParameters()
# end if
cat = CatalogCSV(event_folder)
events = cat.get_events()
originTimestamps = cat.get_preferred_origin_timestamps()
# ==========================================
#picker = fbpicker.FBPicker(t_long=5, freqmin=0.1, mode='std', t_ma=20, nsigma=8, \
# t_up=1, nr_len=5, nr_coeff=2, pol_len=10, pol_coeff=10, uncert_coeff=3)
picker_p = aicdpicker.AICDPicker(t_ma=5,
nsigma=8,
t_up=1,
nr_len=5,
nr_coeff=2,
pol_len=10,
pol_coeff=10,
uncert_coeff=3)
picker_s = aicdpicker.AICDPicker(t_ma=15,
nsigma=8,
t_up=1,
nr_len=5,
nr_coeff=2,
pol_len=10,
pol_coeff=10,
uncert_coeff=3)
taupyModel = TauPyModel(model='iasp91')
fds = FederatedASDFDataSet(asdf_source, use_json_db=False, logger=None)
workload = getWorkloadEstimate(fds, originTimestamps)
header = '#eventID originTimestamp mag originLon originLat originDepthKm net sta cha pickTimestamp stationLon stationLat az baz distance ttResidual snr bandIndex\n'
ofnp = os.path.join(output_path, 'p_arrivals.%d.txt' % (rank))
ofp = open(ofnp, 'w+')
ofns = os.path.join(output_path, 's_arrivals.%d.txt' % (rank))
ofs = open(ofns, 'w+')
ofp.write(header)
ofs.write(header)
totalTraceCount = 0
for nc, sc, start_time, end_time in fds.local_net_sta_list():
day = 24 * 3600
dayCount = 0
curr = start_time
traceCountP = 0
pickCountP = 0
traceCountS = 0
pickCountS = 0
sw_start = datetime.now()
step = day
while (curr < end_time):
if (curr + step > end_time):
step = end_time - curr
# end if
eventIndices = (np.where((originTimestamps >= curr.timestamp) & \
(originTimestamps <= (curr + day).timestamp)))[0]
if (eventIndices.shape[0] > 0):
totalTraceCount += 1
stations = fds.get_stations(curr,
curr + day,
network=nc,
station=sc)
stations_zch = [s for s in stations
if 'Z' in s[3]] # only Z channels
stations_nch = [
s for s in stations if 'N' in s[3] or '1' in s[3]
] # only N channels
stations_ech = [
s for s in stations if 'E' in s[3] or '2' in s[3]
] # only E channels
for codes in stations_zch:
st = fds.get_waveforms(codes[0],
codes[1],
codes[2],
codes[3],
curr,
curr + step,
automerge=True,
trace_count_threshold=200)
if (len(st) == 0): continue
dropBogusTraces(st)
slon, slat = codes[4], codes[5]
for ei in eventIndices:
event = events[ei]
po = event.preferred_origin
da = gps2dist_azimuth(po.lat, po.lon, slat, slon)
mag = None
if (event.preferred_magnitude):
mag = event.preferred_magnitude.magnitude_value
elif (len(po.magnitude_list)):
mag = po.magnitude_list[0].magnitude_value
if (mag == None): mag = np.NaN
if (np.isnan(mag) or mag < min_magnitude): continue
result = extract_p(taupyModel, picker_p, event, slon,
slat, st)
if (result):
pick, residual, snr, bi = result
line = '%s %f %f %f %f %f ' \
'%s %s %s %f %f %f ' \
'%f %f %f ' \
'%f %f %d\n' % (event.public_id, po.utctime.timestamp, mag, po.lon, po.lat, po.depthkm,
codes[0], codes[1], codes[3], pick.timestamp, slon, slat,
da[1], da[2], kilometers2degrees(da[0]/1e3),
residual, snr, bi)
ofp.write(line)
pickCountP += 1
# end if
if (len(stations_nch) == 0 and len(stations_ech) == 0):
result = extract_s(taupyModel, picker_s, event,
slon, slat, st, None, da[2])
if (result):
pick, residual, snr, bi = result
line = '%s %f %f %f %f %f ' \
'%s %s %s %f %f %f ' \
'%f %f %f ' \
'%f %f %d\n' % (event.public_id, po.utctime.timestamp, mag, po.lon, po.lat, po.depthkm,
codes[0], codes[1], codes[3], pick.timestamp, slon, slat,
da[1], da[2], kilometers2degrees(da[0] / 1e3),
residual, snr, bi)
ofs.write(line)
pickCountS += 1
# end if
# end if
# end for
traceCountP += len(st)
# end for
if (len(stations_nch) > 0
and len(stations_nch) == len(stations_ech)):
for codesn, codese in zip(stations_nch, stations_ech):
stn = fds.get_waveforms(codesn[0],
codesn[1],
codesn[2],
codesn[3],
curr,
curr + step,
automerge=True,
trace_count_threshold=200)
ste = fds.get_waveforms(codese[0],
codese[1],
codese[2],
codese[3],
curr,
curr + step,
automerge=True,
trace_count_threshold=200)
dropBogusTraces(stn)
dropBogusTraces(ste)
if (len(stn) == 0): continue
if (len(ste) == 0): continue
slon, slat = codesn[4], codesn[5]
for ei in eventIndices:
event = events[ei]
po = event.preferred_origin
da = gps2dist_azimuth(po.lat, po.lon, slat, slon)
mag = None
if (event.preferred_magnitude):
mag = event.preferred_magnitude.magnitude_value
elif (len(po.magnitude_list)):
mag = po.magnitude_list[0].magnitude_value
if (mag == None): mag = np.NaN
if (np.isnan(mag) or mag < min_magnitude): continue
result = extract_s(taupyModel, picker_s, event,
slon, slat, stn, ste, da[2])
if (result):
pick, residual, snr, bi = result
line = '%s %f %f %f %f %f ' \
'%s %s %s %f %f %f ' \
'%f %f %f ' \
'%f %f %d\n' % (event.public_id, po.utctime.timestamp, mag, po.lon, po.lat, po.depthkm,
codesn[0], codesn[1], '00T', pick.timestamp, slon, slat,
da[1], da[2], kilometers2degrees(da[0] / 1e3),
residual, snr, bi)
ofs.write(line)
pickCountS += 1
# end if
# end for
traceCountS += (len(stn) + len(ste))
# end for
# end if
# end if
curr += step
dayCount += 1
# wend
sw_stop = datetime.now()
totalTime = (sw_stop - sw_start).total_seconds()
gc.collect()
print '(Rank %d: %5.2f%%, %d/%d) Processed %d traces and found %d p-arrivals and %d s-arrivals for ' \
'network %s station %s in %f s. Memory usage: %5.2f MB.' % \
(rank, (float(totalTraceCount) / float(workload) * 100) if workload > 0 else 100, totalTraceCount, workload,
traceCountP + traceCountS, pickCountP, pickCountS, nc, sc, totalTime,
round(psutil.Process().memory_info().rss / 1024. / 1024., 2))
# end for
ofp.close()
ofs.close()
print 'Processing complete on rank %d' % (rank)
del fds
def beach_map(m, event, stlo, stla, distance, show, format, zoom_level=8):
"""
Plot beach ball on a map
Function to plot stations and focal mechanisms on a Stamen terrain background.
:param m: focal mechanisms, refer to :func:`~tdmtpy.image.beach` function
for the supported formats.
:type m: list
:param event: event origin time, longitude and latitude, refer to :class:`~tdmtpy.configure.Configure`
for details.
:type event: dict
:param stlo: station longitudes
:type stlo: list or :class:`~numpy.ndarray`
:param stla: station latitudes.
:type stla: list or :class:`~numpy.ndarray`
:param distance: source-receiver distance.
:type distance: list or :class:`~numpy.ndarray`
:param show: Turn on interactive display.
:type show: bool
:param format: figure file format.
:type format: str
:param zoom_level: background image tile zoom level. Default is ``8``.
:type zoom_level: int
"""
# Turn interactive plotting off
plt.ioff(
) # only display plots when called, save figure without displaying in ipython
# Calculate image extent based on epicentral distance
width = kilometers2degrees(0.5 * max(distance))
height = kilometers2degrees(0.5 * max(distance))
lat1 = min(stla) - height
lat2 = max(stla) + height
lon1 = min(stlo) - width
lon2 = max(stlo) + width
data_crs = ccrs.PlateCarree()
evlo = event["longitude"]
evla = event["latitude"]
point = (evlo, evla)
stamen_terrain = cimgt.Stamen('terrain-background')
projection = stamen_terrain.crs
fig = plt.figure(dpi=dpi)
fig.set_size_inches(8.5, 11)
if format != "png":
ax = fig.add_subplot(1, 1, 1, projection=projection,
rasterized=True) # axes coordinates
else:
ax = fig.add_subplot(1, 1, 1,
projection=projection) # axes coordinates
ax.set_extent([lon1, lon2, lat1, lat2])
ax.add_image(stamen_terrain, zoom_level)
# Add tick labels
g1 = ax.gridlines(crs=data_crs, draw_labels=True)
g1.top_labels = False
# Plot stations
ax.plot(stlo,
stla,
marker="^",
color="black",
markersize=8,
linestyle="",
transform=data_crs)
# Plot beach ball on map
x, y = projection.transform_point(*point, src_crs=data_crs)
bb = beach(m,
xy=(x, y),
facecolor="red",
width=135,
show_iso=True,
axes=ax)
ax.add_collection(bb)
# Add title
ax.set_title(event["datetime"])
outfile = "map.%s" % format
fig.savefig(outfile, format=format, bbox_inches="tight")
if show:
plt.show()
else:
plt.close(fig)
def _load_events(self):
self._load_events_helper()
cache = {}
notFound = defaultdict(int)
oEvents = []
missingStations = defaultdict(int)
lines = []
for e in tqdm(self.eventList, desc='Rank %d' % (self.rank)):
if (e.preferred_origin and len(e.preferred_origin.arrival_list)):
cullList = []
for a in e.preferred_origin.arrival_list:
if (len(a.net)): continue
seedid = '%s.%s.%s.%s' % (a.net, a.sta, a.loc, a.cha)
newCode = None
if (seedid not in cache):
sc = a.sta
lonlat = self.isc_coords_dict[sc]
if (len(lonlat) == 0):
cullList.append(a)
continue
# end if
r = self.fdsn_inventory.getClosestStation(
lonlat[0], lonlat[1], maxdist=1e3) # 1km
#if(a.sta=='KUM'): print a.net, a.sta, a.loc, a.cha, r
if (not r):
notFound[sc] += 1
else:
c = r[0].split('.')[0]
newCode = c
# end if
if (newCode):
cache[seedid] = newCode
# end if
else:
newCode = cache[seedid]
# end if
if (newCode):
#print a.net, newCode
a.net = newCode
sc = self.fdsn_inventory.t[a.net][a.sta]
if (type(sc) == defaultdict):
cullList.append(a)
continue
# end if
da = gps2dist_azimuth(e.preferred_origin.lat,
e.preferred_origin.lon, sc[1],
sc[0])
dist = kilometers2degrees(da[0] / 1e3)
if (np.fabs(a.distance - dist) > 0.5):
#print ([e.preferred_origin.lon, e.preferred_origin.lat, sc[0], sc[1]])
cullList.append(a)
# end if
# end if
# end for
for c in cullList:
e.preferred_origin.arrival_list.remove(c)
# end if
# Create obspy event object
ci = OCreationInfo(author='GA',
creation_time=UTCDateTime(),
agency_id='GA-iteration-1')
oid = self.get_id()
origin = OOrigin(resource_id=OResourceIdentifier(id=oid),
time=UTCDateTime(e.preferred_origin.utctime),
longitude=e.preferred_origin.lon,
latitude=e.preferred_origin.lat,
depth=e.preferred_origin.depthkm * 1e3,
method_id=OResourceIdentifier(id='unknown'),
earth_model_id=OResourceIdentifier(id='iasp91'),
evaluation_mode='automatic',
creation_info=ci)
magnitude = OMagnitude(
resource_id=OResourceIdentifier(id=self.get_id()),
mag=e.preferred_magnitude.magnitude_value,
magnitude_type=e.preferred_magnitude.magnitude_type,
origin_id=OResourceIdentifier(id=oid),
creation_info=ci)
event = OEvent(
resource_id=OResourceIdentifier(id=str(e.public_id)),
creation_info=ci,
event_type='earthquake')
event.origins = [origin]
event.magnitudes = [magnitude]
event.preferred_magnitude_id = magnitude.resource_id
event.preferred_origin_id = origin.resource_id
# Insert old picks
if (not self.discard_old_picks):
for a in e.preferred_origin.arrival_list:
if (type(self.fdsn_inventory.t[a.net][a.sta]) ==
defaultdict):
missingStations[a.net + '.' + a.sta] += 1
continue
# end if
oldPick = OPick(
resource_id=OResourceIdentifier(id=self.get_id()),
time=UTCDateTime(a.utctime),
waveform_id=OWaveformStreamID(network_code=a.net,
station_code=a.sta,
channel_code=a.cha),
methodID=OResourceIdentifier('unknown'),
phase_hint=a.phase,
evaluation_mode='automatic',
creation_info=ci)
oldArr = OArrival(
resource_id=OResourceIdentifier(
id=oldPick.resource_id.id + "#"),
pick_id=oldPick.resource_id,
phase=oldPick.phase_hint,
distance=a.distance,
earth_model_id=OResourceIdentifier(
'quakeml:ga.gov.au/earthmodel/iasp91'),
creation_info=ci)
event.picks.append(oldPick)
event.preferred_origin().arrivals.append(oldArr)
# polulate list for text output
line = [
str(e.public_id), '{:<25s}',
e.preferred_origin.utctime.timestamp, '{:f}',
e.preferred_magnitude.magnitude_value, '{:f}',
e.preferred_origin.lon, '{:f}', e.preferred_origin.lat,
'{:f}', e.preferred_origin.depthkm, '{:f}', a.net,
'{:<5s}', a.sta, '{:<5s}', a.cha, '{:<5s}',
a.utctime.timestamp, '{:f}', a.phase, '{:<5s}',
self.fdsn_inventory.t[a.net][a.sta][0], '{:f}',
self.fdsn_inventory.t[a.net][a.sta][1], '{:f}', -999,
'{:f}', -999, '{:f}', a.distance, '{:f}', -999, '{:f}',
-999, '{:f}', -999, '{:f}', -999, '{:f}', -999, '{:f}',
-999, '{:d}', -999, '{:d}'
]
lines.append(line)
# end for
# end if
# Insert our picks
opList = self.our_picks.picks[e.public_id]
if (len(opList)):
for op in opList:
if (type(self.fdsn_inventory.t[op[1]][op[2]]) ==
defaultdict):
missingStations[op[1] + '.' + op[2]] += 1
continue
# end if
newPick = OPick(
resource_id=OResourceIdentifier(id=self.get_id()),
time=UTCDateTime(op[0]),
waveform_id=OWaveformStreamID(network_code=op[1],
station_code=op[2],
channel_code=op[3]),
methodID=OResourceIdentifier('phasepapy/aicd'),
backazimuth=op[-1],
phase_hint=op[4],
evaluation_mode='automatic',
comments=[
OComment(
text='phasepapy_snr = ' + str(op[6][0]) +
', quality_measure_cwt = ' + str(op[6][1]) +
', dom_freq = ' + str(op[6][2]) +
', quality_measure_slope = ' + str(op[6][3]) +
', band_index = ' + str(op[6][4]) +
', nsigma = ' + str(op[6][5]),
force_resource_id=False)
],
creation_info=ci)
newArr = OArrival(
resource_id=OResourceIdentifier(
id=newPick.resource_id.id + "#"),
pick_id=newPick.resource_id,
phase=newPick.phase_hint,
azimuth=op[-2],
distance=op[-3],
time_residual=op[5],
time_weight=1.,
earth_model_id=OResourceIdentifier(
'quakeml:ga.gov.au/earthmodel/iasp91'),
creation_info=ci)
event.picks.append(newPick)
event.preferred_origin().arrivals.append(newArr)
# polulate list for text output
line = [
str(e.public_id), '{:<25s}',
e.preferred_origin.utctime.timestamp, '{:f}',
e.preferred_magnitude.magnitude_value, '{:f}',
e.preferred_origin.lon, '{:f}', e.preferred_origin.lat,
'{:f}', e.preferred_origin.depthkm, '{:f}', op[1],
'{:<5s}', op[2], '{:<5s}', op[3], '{:<5s}',
UTCDateTime(op[0]).timestamp, '{:f}', op[4], '{:<5s}',
op[10], '{:f}', op[9], '{:f}', op[12], '{:f}', op[13],
'{:f}', op[11], '{:f}', op[5], '{:f}', op[6][0],
'{:f}', op[6][1], '{:f}', op[6][2], '{:f}', op[6][3],
'{:f}',
int(op[6][4]), '{:d}',
int(op[6][5]), '{:d}'
]
lines.append(line)
# end for
# end if
quality= OOriginQuality(associated_phase_count= len(e.preferred_origin.arrival_list) * \
int(self.discard_old_picks) + \
len(self.our_picks.picks[e.public_id]),
used_phase_count=len(e.preferred_origin.arrival_list) * \
int(self.discard_old_picks) + \
len(self.our_picks.picks[e.public_id]))
event.preferred_origin().quality = quality
if (len(self.our_picks.picks[e.public_id]) == 0
and self.discard_old_picks):
continue
# end if
oEvents.append(event)
# end for // loop over e
if (len(missingStations)):
for k, v in missingStations.items():
self.logger.warning('Missing station %s: %d picks' % (k, v))
# end for
# end if
# write xml output
if (len(oEvents)):
cat = OCatalog(events=oEvents)
ofn = self.output_path + '/%d.xml' % (self.rank)
cat.write(ofn, format='SC3ML')
# end if
# write text output
procfile = open('%s/proc.%d.txt' % (self.output_path, self.rank), 'w+')
for line in lines:
lineout = ' '.join(line[1::2]).format(*line[::2])
procfile.write(lineout + '\n')
# end for
procfile.close()
# combine text output
header = '#eventID originTimestamp mag originLon originLat originDepthKm net sta cha pickTimestamp phase stationLon stationLat az baz distance ttResidual snr qualityMeasureCWT domFreq qualityMeasureSlope bandIndex nSigma\n'
self.comm.barrier()
if (self.rank == 0):
of = open('%s/ensemble.txt' % (self.output_path), 'w+')
of.write(header)
for i in range(self.nproc):
fn = '%s/proc.%d.txt' % (self.output_path, i)
lines = open(fn, 'r').readlines()
for line in lines:
of.write(line)
# end for
if (os.path.exists(fn)): os.remove(fn)
# end for
of.close()