def test_to_phase_defs(self):
pdefs = cake.to_phase_defs(['p,P', cake.PhaseDef('PP')])
assert len(pdefs) == 3
for pdef in pdefs:
assert isinstance(pdef, cake.PhaseDef)
pdefs = cake.to_phase_defs(cake.PhaseDef('PP'))
assert len(pdefs) == 1
for pdef in pdefs:
assert isinstance(pdef, cake.PhaseDef)
pdefs = cake.to_phase_defs('P,p')
assert len(pdefs) == 2
for pdef in pdefs:
assert isinstance(pdef, cake.PhaseDef)
def test_path(self):
mod = cake.load_model()
phase = cake.PhaseDef('P')
ray = mod.arrivals(phases=[phase], distances=[70.], zstart=100.)
z, x, t = ray[0].zxt_path_subdivided()
assert z[0].size == 681
def test_angles(self):
mod = cake.load_model()
data = [
[1.0*km, 1.0*km, 1.0*km, 90., 90., 'P'],
[1.0*km, 2.0*km, 1.0*km, 45., 135., 'P\\'],
[2.0*km, 1.0*km, 1.0*km, 135., 45., 'p'],
[1.0*km, 2.0*km, math.sqrt(3.)*km, 60., 120., 'P\\'],
[2.0*km, 1.0*km, math.sqrt(3.)*km, 120., 60., 'p']]
for (zstart, zstop, dist, takeoff_want, incidence_want, pdef_want) \
in data:
rays = mod.arrivals(
zstart=zstart,
zstop=zstop,
phases=[cake.PhaseDef(sphase)
for sphase in 'P,p,P\\,p\\'.split(',')],
distances=[dist*cake.m2d])
for ray in rays:
takeoff = round(ray.takeoff_angle())
incidence = round(ray.incidence_angle())
pdef = ray.used_phase().definition()
assert takeoff == takeoff_want
assert incidence == incidence_want
assert pdef == pdef_want
def t(self, phase_selection, z_dist):
''':param phase_selection: phase names speparated by vertical bars
:param z_dist: tuple with (depth, distance)
'''
if 'first' in phase_selection:
self.which = 'first'
if 'last' in phase_selection:
self.which = 'last'
if self.which:
phase_selection = self.strip(phase_selection)
z, dist = z_dist
if (phase_selection, dist, z) in self.arrivals.keys():
return self.arrivals[(phase_selection, dist, z)]
phases = [cake.PhaseDef(pid) for pid in phase_selection.split('|')]
arrivals = self.model.arrivals(distances=[dist * cake.m2d],
phases=phases,
zstart=z)
if arrivals == []:
logger.info('none of defined phases at d=%s, z=%s' % (dist, z))
return
else:
want = self.phase_selector(arrivals)
self.arrivals[(phase_selection, dist, z)] = want
return want
def convert_phase(phase):
if phase == "Pg":
phase = "P<(moho)"
if phase == "pg":
phase = "p<(moho)"
if phase == "Sg":
phase = "S<(moho)"
if phase == "sg":
phase = "s<(moho)"
if phase == "PG":
phase = "P>(moho)"
if phase == "pG":
phase = "p>(moho)"
if phase == "SG":
phase = "S>(moho)"
if phase == "sG":
phase = "s>(moho)"
if phase == "P*":
phase = "P"
if phase == "S*":
phase = "S"
if phase == "SmS":
phase = 'Sv(moho)s'
if phase == "PmP":
phase = 'Pv(moho)p'
if phase == "Pn":
phase = 'Pv_(moho)p'
if phase == "Sn":
phase = 'Sv_(moho)s'
cake_phase = cake.PhaseDef(phase)
return cake_phase
def calctakeoff(Station, Event, Config):
de = loc2degrees(Event, Station)
Phase = cake.PhaseDef('P')
arrivals = model.arrivals([de, de], phases=Phase, zstart=Event.depth * km)
return arrivals[0].takeoff_angle()
def traveltimes(self, phase, traces):
Logfile.red('Enter AUTOMATIC CROSSCORRELATION ')
Logfile.red('\n\n+++++++++++++++++++++++++++++++++++++++++++++++\n ')
T = []
Wdict = OrderedDict()
SNR = OrderedDict()
Config = self.Config
cfg = ConfigObj(dict=Config)
for i in self.StationMeta:
Logfile.red('read in %s ' % (i))
de = loc2degrees(self.Origin, i)
Phase = cake.PhaseDef(phase)
traveltime_model = cfg.Str('traveltime_model')
path = palantiri.__path__
model = cake.load_model(path[0] + '/data/' + traveltime_model)
if cfg.colesseo_input() is True:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=self.Origin.depth,
zstop=0.)
else:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=self.Origin.depth * km,
zstop=0.)
try:
ptime = arrivals[0].t
except Exception:
try:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=self.Origin.depth * km -
2.1)
ptime = arrivals[0].t
except Exception:
ptime = 0
T.append(ptime)
if ptime == 0:
Logfile.red('Available phases for station %s in\
range %f deegree' % (i, de))
Logfile.red('you tried phase %s' % (phase))
raise Exception("ILLEGAL: phase definition")
else:
tw = self.calculateTimeWindows(ptime)
if cfg.pyrocko_download() is True:
w, snr, found = self.readWaveformsCross_pyrocko(
i, tw, ptime, traces)
elif cfg.colesseo_input() is True:
w, snr = self.readWaveformsCross_colesseo(i, tw, ptime)
else:
w, snr = self.readWaveformsCross(i, tw, ptime)
Wdict[i.getName()] = w
SNR[i.getName()] = snr
Logfile.red('\n\n+++++++++++++++++++++++++++++++++++++++++++++++ ')
Logfile.red('Exit AUTOMATIC FILTER ')
return Wdict, SNR
def traveltime(station):
dist = event.distance_to(station)
arrivals = mod.arrivals(zstart=event.depth,
zstop=0.,
distances=[dist * cake.m2d],
phases=[cake.PhaseDef(self.phasename)])
if not arrivals:
raise NoArrival()
return arrivals[0].t
def make_reference_markers_cake(source, targets, model):
assert len(source) == 1
ref_marker = defaultdict(dict)
phases_start = ['p', 'P']
phases_start = [cake.PhaseDef(ph) for ph in phases_start]
phases_end = ['s', 'S']
phases_end = [cake.PhaseDef(ph) for ph in phases_end]
for s in source:
for target in targets:
dist = orthodrome.distance_accurate50m(s, target) * cake.m2d
tmin = min(model.arrivals([dist],
phases_start,
zstart=s.depth,
zstop=s.depth),
key=lambda x: x.t).t
tmax = min(model.arrivals([dist],
phases_end,
zstart=s.depth,
zstop=s.depth),
key=lambda x: x.t).t
tmin += s.time
tmax += s.time
assert tmin != tmax
m = gui_util.PhaseMarker(nslc_ids=target.codes,
tmin=tmin,
tmax=tmax,
kind=1,
event=source,
phasename='range')
ref_marker[s][target] = m
return ref_marker
def prep_data_batch(data_dir, store_id, stations=None, pre=0.5,
post=3, reference_event=None, min_len=420,
pick_sigma=0.02):
engine = LocalEngine(store_superdirs=['/home/asteinbe/gf_stores'])
store = engine.get_store(store_id)
mod = store.config.earthmodel_1d
gf_freq = store.config.sample_rate
cake_phase = cake.PhaseDef("P")
phase_list = [cake_phase]
events = []
waveforms = []
waveforms_shifted = []
events = scedc_util.scedc_fm_to_pyrocko(file)
labels = labels_from_events(events)
pathlist = Path(data_dir).glob('ev_0/')
for path in sorted(pathlist):
try:
targets = []
path = str(path)+"/"
event = model.load_events(path+"event.txt")[0]
traces_loaded = io.load(path+"traces.mseed")
stations_unsorted = model.load_stations(data_dir+"stations.pf")
for st in stations_unsorted:
st.dist = orthodrome.distance_accurate50m(st.lat, st.lon,
event.lat,
event.lon)
st.azi = orthodrome.azimuth(st.lat, st.lon, event.lat,
event.lon)
stations = sorted(stations_unsorted, key=lambda x: x.dist,
reverse=True)
traces_processed = []
traces = check_traces(traces_loaded, stations, min_len=min_len)
traces_processed, nsamples = wp.process_loaded_waveforms(traces,
stations,
event,
gf_freq,
mod,
pre, post)
events.append(event)
waveforms.append(traces_processed)
except:
pass
return waveforms, nsamples, events, waveforms_shifted
def print_arrivals(model,
distances=[],
phases=cake.PhaseDef('P'),
zstart=0.0,
zstop=0.0,
as_degrees=False):
headers = 'slow dist time take inci effi spre phase used'.split()
space = (7, 5, 6, 4, 4, 4, 4, 17, 17)
if as_degrees:
units = 's/deg deg s deg deg % %'.split()
else:
units = 's/km km s deg deg % %'.split()
hline = ' '.join(x.ljust(s) for (x, s) in zip(headers, space))
uline = ' '.join(('%s' % x).ljust(s) for (x, s) in zip(units, space))
print(hline)
print(uline)
print('-' * len(hline))
for ray in model.arrivals(distances=distances,
phases=phases,
zstart=zstart,
zstop=zstop):
if as_degrees:
sd = ray.x
slow = ray.p / cake.r2d
else:
sd = ray.x * (cake.d2r * cake.earthradius / cake.km)
slow = ray.p / (r2d * cake.d2m / cake.km)
su = '(%s)' % ray.path.used_phase(p=ray.p, eps=1.0).used_repr()
print(' '.join(
tuple(
mini_fmt(x, s).rjust(s)
for (x, s) in zip((slow, sd, ray.t, ray.takeoff_angle(),
ray.incidence_angle(), 100 *
ray.efficiency(), 100 * ray.spreading() *
ray.surface_sphere()), space)) +
tuple(x.ljust(17) for x in (ray.path.phase.definition(), su))))
def t(self, mod, z_dist, get_ray=False):
""":param phase_selection: phase names separated by vertical bars
:param z_dist: tuple with (depth, distance)
"""
z, dist = z_dist
if (dist, z) in self.arrivals.keys():
return self.return_time(self.arrivals[(dist, z)])
phases = [cake.PhaseDef(pid) for pid in self.phases]
arrivals = mod.arrivals(distances=[dist * cake.m2d], phases=phases, zstart=z)
if not arrivals:
logger.warn("no phase at d=%s, z=%s. (return fallback time)" % (dist, z))
want = None
else:
want = self.phase_selector(arrivals)
self.arrivals[(dist, z)] = want
if get_ray:
return want
else:
return self.return_time(want)
def wanted_phases(self):
try:
wanted = []
for iphase, name in enumerate(self._phase_names):
if getattr(self, 'wantphase_%i' % iphase):
if name in self._phases:
phases = self._phases[name]
else:
if name.startswith('~'):
phases = [cake.PhaseDef(name[1:])]
else:
phases = cake.PhaseDef.classic(name)
self._phases[name] = phases
for pha in phases:
pha.name = name
wanted.extend(phases)
except (cake.UnknownClassicPhase, cake.PhaseDefParseError) as e:
self.fail(str(e))
return wanted
def phasedef_or_horvel(x):
try:
return float(x)
except ValueError:
return cake.PhaseDef(x)
def calcTTTAdv(Config,
station,
Origin,
flag,
arrayname,
Xcorrshift=None,
Refshift=None):
phasename = ('%sphase') % (os.path.basename(arrayname))
cfg = ConfigObj(dict=Config)
dimX = cfg.Int('dimx')
dimY = cfg.Int('dimy')
gridspacing = cfg.Float('gridspacing')
o_lat = float(Origin['lat'])
o_lon = float(Origin['lon'])
o_depth = float(Origin['depth'])
oLator = o_lat + dimX / 2
oLonor = o_lon + dimY / 2
oLatul = 0
oLonul = 0
o_dip = 80.
plane = False
TTTGridMap = {}
LMINMAX = []
GridArray = {}
locStation = Location(station.lat, station.lon)
sdelta = loc2degrees(Location(o_lat, o_lon), locStation)
Phase = cake.PhaseDef(Config[phasename])
model = cake.load_model()
z = 0
if plane is True:
depth = np.linspace(0., 40., num=dimY)
for i in xrange(70):
oLatul = o_lat - ((dimX - 1) / 2) * gridspacing + i * gridspacing
if z == 0 and i == 0:
Latul = oLatul
o = 0
start_time = time.clock()
for j in xrange(40):
oLonul = o_lon - (
(dimY - 1) /
2) * gridspacing + j * gridspacing / np.cos(o_dip)
if o == 0 and j == 0: Lonul = oLonul
de = loc2degrees(Location(oLatul, oLonul), locStation)
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=depth[j] * km,
zstop=0.)
try:
ttime = arrivals[0].t
except:
try:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=depth[j] * km - 2.5,
zstop=depth[j] * km + 2.5,
refine=True)
ttime = arrivals[0].t
except:
tt = obs_TravelTimes(de, o_depth)
for k in tt:
if k['phase_name'] == 'P' or k['phase_name'] == (
'%sdiff') % (Config[phasename]):
ttime = k['time']
print "Something wrong with phase arrival too large\
distances choosen?"
GridArray[(i, j)] = GridElem(oLatul, oLonul, depth[j], ttime,
de)
LMINMAX.append(ttime)
if int(Config['xcorr']) == 1:
ttime = ttime-float(Xcorrshift[station.getName()].shift)\
- Refshift
GridArray[(i, j)] = GridElem(oLatul, oLonul, o_depth, ttime,
de)
LMINMAX.append(ttime)
if ttime == 0:
print '\033[31mAvailable phases for station %s in range %f deegree\033[0m' % (
station, de)
print '\033[31m' + '|'.join(
[str(item['phase_name']) for item in tt]) + '\033[0m'
print '\033[31myou tried phase %s\033[0m' % (
Config[phasename])
raise Exception("\033[31mILLEGAL: phase definition\033[0m")
else:
for i in xrange(dimX):
oLatul = o_lat - ((dimX - 1) / 2) * gridspacing + i * gridspacing
if z == 0 and i == 0:
Latul = oLatul
o = 0
for j in xrange(dimY):
oLonul = o_lon - (
(dimY - 1) / 2) * gridspacing + j * gridspacing
if o == 0 and j == 0: Lonul = oLonul
de = loc2degrees(Location(oLatul, oLonul), locStation)
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=o_depth * km)
try:
ttime = arrivals[0].t
except:
try:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=o_depth * km - 2.5,
zstop=o_depth * km - 2.5,
refine=True)
ttime = arrivals[0].t
except:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=o_depth * km - 2.5,
zstop=0.,
refine=True)
ttime = arrivals[0].t
GridArray[(i, j)] = GridElem(oLatul, oLonul, o_depth, ttime,
de)
LMINMAX.append(ttime)
if int(Config['xcorr']) == 1:
ttime = ttime-float(Xcorrshift[station.getName()].shift)\
- Refshift
GridArray[(i, j)] = GridElem(oLatul, oLonul, o_depth, ttime,
de)
LMINMAX.append(ttime)
if ttime == 0:
print '\033[31mAvailable phases for station %s in range %f deegree\033[0m' % (
station, de)
print '\033[31m' + '|'.join(
[str(item['phase_name']) for item in tt]) + '\033[0m'
print '\033[31myou tried phase %s\033[0m' % (
Config[phasename])
raise Exception("\033[31mILLEGAL: phase definition\033[0m")
mint = min(LMINMAX)
maxt = max(LMINMAX)
TTTGridMap[station.getName()] = TTTGrid(o_depth, mint, maxt, Latul, Lonul,
oLator, oLonor, GridArray)
k = MinTMaxT(mint, maxt)
Basic.dumpToFile(str(flag) + '-ttt.pkl', TTTGridMap)
Basic.dumpToFile('minmax-' + str(flag) + '.pkl', k)
Basic.dumpToFile('station-' + str(flag) + '.pkl', station)
def plot(settings, show=False):
#align_phase = 'P(cmb)P<(icb)(cmb)p'
with_onset_line = False
fill = True
align_phase = 'P'
zoom_window = settings.zoom
ampl_scaler = '4*standard deviation'
quantity = settings.quantity
zstart, zstop, inkr = settings.depths.split(':')
test_depths = num.arange(
float(zstart) * km,
float(zstop) * km,
float(inkr) * km)
try:
traces = io.load(settings.trace_filename)
except FileLoadError as e:
logger.info(e)
return
event = model.load_events(settings.event_filename)
assert len(event) == 1
event = event[0]
event.depth = float(settings.depth) * 1000.
base_source = MTSource.from_pyrocko_event(event)
test_sources = []
for d in test_depths:
s = base_source.clone()
s.depth = float(d)
test_sources.append(s)
if settings.store_superdirs:
engine = LocalEngine(store_superdirs=settings.store_superdirs)
else:
engine = LocalEngine(use_config=True)
try:
store = engine.get_store(settings.store_id)
except seismosizer.NoSuchStore as e:
logger.info('%s ... skipping.' % e)
return
stations = model.load_stations(settings.station_filename)
station = filter(
lambda s: match_nslc('%s.%s.%s.*' % s.nsl(), traces[0].nslc_id),
stations)
assert len(station) == 1
station = station[0]
targets = [
station_to_target(station,
quantity=quantity,
store_id=settings.store_id)
]
try:
request = engine.process(targets=targets, sources=test_sources)
except seismosizer.NoSuchStore as e:
logger.info('%s ... skipping.' % e)
return
except meta.OutOfBounds as error:
if settings.force_nearest_neighbor:
logger.warning('%s Using nearest neighbor instead.' % error)
mod_targets = []
for t in targets:
closest_source = min(test_sources,
key=lambda s: s.distance_to(t))
farthest_source = max(test_sources,
key=lambda s: s.distance_to(t))
min_dist_delta = store.config.distance_min - closest_source.distance_to(
t)
max_dist_delta = store.config.distance_max - farthest_source.distance_to(
t)
if min_dist_delta < 0:
azi, bazi = closest_source.azibazi_to(t)
newlat, newlon = ortho.azidist_to_latlon(
t.lat, t.lon, azi, min_dist_delta * cake.m2d)
elif max_dist_delta < 0:
azi, bazi = farthest_source.azibazi_to(t)
newlat, newlon = ortho.azidist_to_latlon(
t.lat, t.lon, azi, max_dist_delta * cake.m2d)
t.lat, t.lon = newlat, newlon
mod_targets.append(t)
request = engine.process(targets=mod_targets, sources=test_sources)
else:
logger.error("%s: %s" % (error, ".".join(station.nsl())))
return
alldepths = list(test_depths)
depth_count = dict(zip(sorted(alldepths), range(len(alldepths))))
target_count = dict(
zip([t.codes[:3] for t in targets], range(len(targets))))
fig = plt.figure()
ax = fig.add_subplot(111)
maxz = max(test_depths)
minz = min(test_depths)
relative_scale = (maxz - minz) * 0.02
for s, t, tr in request.iter_results():
if quantity == 'velocity':
tr = integrate_differentiate(tr, 'differentiate')
onset = engine.get_store(t.store_id).t('begin',
(s.depth, s.distance_to(t)))
tr = settings.do_filter(tr)
if settings.normalize:
tr.set_ydata(tr.get_ydata() / num.max(abs(tr.get_ydata())))
ax.tick_params(axis='y',
which='both',
left='off',
right='off',
labelleft='off')
y_pos = s.depth
xdata = tr.get_xdata() - onset - s.time
tr_ydata = tr.get_ydata() * -1
visible = tr.chop(tmin=event.time + onset + zoom_window[0],
tmax=event.time + onset + zoom_window[1])
if ampl_scaler == 'trace min/max':
ampl_scale = float(max(abs(visible.get_ydata())))
elif ampl_scaler == '4*standard deviation':
ampl_scale = 4 * float(num.std(visible.get_ydata()))
else:
ampl_scale = 1.
ampl_scale /= settings.gain
ydata = (tr_ydata / ampl_scale) * relative_scale + y_pos
ax.plot(xdata, ydata, c='black', linewidth=1., alpha=1.)
if False:
ax.fill_between(xdata,
y_pos,
ydata,
where=ydata < y_pos,
color='black',
alpha=0.5)
ax.text(zoom_window[0] * 1.09,
y_pos,
'%1.1f' % (s.depth / 1000.),
horizontalalignment='right') #, fontsize=12.)
if False:
mod = store.config.earthmodel_1d
label = 'pP'
arrivals = mod.arrivals(phases=[cake.PhaseDef(label)],
distances=[s.distance_to(t) * cake.m2d],
zstart=s.depth)
try:
t = arrivals[0].t
ydata_absmax = num.max(num.abs(tr.get_ydata()))
marker_length = 0.5
x_marker = [t - onset] * 2
y = [
y_pos - (maxz - minz) * 0.025,
y_pos + (maxz - minz) * 0.025
]
ax.plot(x_marker, y, linewidth=1, c='blue')
ax.text(
x_marker[1] - x_marker[1] * 0.005,
y[1],
label,
#fontsize=12,
color='black',
verticalalignment='top',
horizontalalignment='right')
except IndexError:
logger.warning(
'no pP phase at d=%s z=%s stat=%s' %
(s.distance_to(t) * cake.m2d, s.depth, station.station))
pass
if len(traces) == 0:
raise Exception('No Trace found!')
if len(traces) > 1:
raise Exception('More then one trace provided!')
else:
onset = 0
tr = traces[0]
correction = float(settings.correction)
if quantity == 'displacement':
tr = integrate_differentiate(tr, 'integrate')
tr = settings.do_filter(tr)
onset = engine.get_store(targets[0].store_id).t(
'begin', (event.depth, s.distance_to(targets[0]))) + event.time
if settings.normalize:
tr.set_ydata(tr.get_ydata() / max(abs(tr.get_ydata())))
ax.tick_params(axis='y',
which='both',
left='off',
right='off',
labelleft='off')
y_pos = event.depth
xdata = tr.get_xdata() - onset + correction
tr_ydata = tr.get_ydata() * -1
visible = tr.chop(tmin=onset + zoom_window[0] + correction,
tmax=onset + zoom_window[1] + correction)
if ampl_scaler == 'trace min/max':
ampl_scale = float(max(abs(visible.get_ydata())))
elif ampl_scaler == '4*standard deviation':
ampl_scale = 4 * float(num.std(visible.get_ydata()))
else:
ampl_scale = 1.
ydata = (tr_ydata / ampl_scale * settings.gain *
settings.gain_record) * relative_scale + y_pos
ax.plot(xdata, ydata, c=settings.color, linewidth=1.)
ax.set_xlim(zoom_window)
zmax = max(test_depths)
zmin = min(test_depths)
zrange = zmax - zmin
ax.set_ylim((zmin - zrange * 0.2, zmax + zrange * 0.2))
ax.set_xlabel('Time [s]')
ax.text(0.0,
0.6,
'Source depth [km]',
rotation=90,
horizontalalignment='left',
transform=fig.transFigure) #, fontsize=12.)
if fill:
ax.fill_between(xdata,
y_pos,
ydata,
where=ydata < y_pos,
color=settings.color,
alpha=0.5)
if with_onset_line:
ax.text(0.08, zmax + zrange * 0.1, align_phase, fontsize=14)
vline = ax.axvline(0., c='black')
vline.set_linestyle('--')
if settings.title:
params = {
'array-id': ''.join(station.nsl()),
'event_name': event.name,
'event_time': time_to_str(event.time)
}
ax.text(0.5,
1.05,
settings.title % params,
horizontalalignment='center',
transform=ax.transAxes)
if settings.auto_caption:
cax = fig.add_axes([0., 0., 1, 0.05], label='caption')
cax.axis('off')
cax.xaxis.set_visible(False)
cax.yaxis.set_visible(False)
if settings.quantity == 'displacement':
quantity_info = 'integrated velocity trace. '
if settings.quantity == 'velocity':
quantity_info = 'differentiated synthetic traces. '
if settings.quantity == 'restituted':
quantity_info = 'restituted traces. '
captions = {'filters': ''}
for f in settings.filters:
captions['filters'] += '%s-pass, order %s, f$_c$=%s Hz. ' % (
f.type, f.order, f.corner)
captions['quantity_info'] = quantity_info
captions['store_sampling'] = 1. / store.config.deltat
cax.text(
0,
0,
'Filters: %(filters)s f$_{GF}$=%(store_sampling)s Hz.\n%(quantity_info)s'
% captions,
fontsize=12,
transform=cax.transAxes)
plt.subplots_adjust(hspace=.4, bottom=0.15)
else:
plt.subplots_adjust(bottom=0.1)
ax.invert_yaxis()
if settings.save_as:
logger.info('save as: %s ' % settings.save_as)
options = settings.__dict__
options.update({'array-id': ''.join(station.nsl())})
fig.savefig(settings.save_as % options, dpi=160, bbox_inches='tight')
if show:
plt.show()
# We need a pyrocko.gf.Engine object which provides us with the traces
# extracted from the store. In this case we are going to use a local
# engine since we are going to query a local store.
engine = LocalEngine(store_superdirs=['/home/asteinbe/gf_stores'])
from silvertine import scenario
from pyrocko import model, cake, orthodrome
from silvertine.util.ref_mods import landau_layered_model
from silvertine.locate.locate1D import get_phases_list
mod = landau_layered_model()
scale = 2e-14
cake_phase = cake.PhaseDef("P")
phase_list = [cake_phase]
waveforms_events = []
waveforms_noise = []
stations = model.load_stations("stations.raw.txt")
nstations = len(stations)*3
noised = True
nevents = 1200
targets = []
for st in stations:
for cha in st.channels:
target = Target(
lat=st.lat,
lon=st.lon,
store_id=store_id,
interpolation='multilinear',
def call(self):
self.cleanup()
viewer = self.get_viewer()
events = [m.get_event() for m in self.get_selected_event_markers()]
for iev, ev in enumerate(events):
ev.name = '%05i' % iev
show_arrivals = False
filters = []
for ident in ['high', 'low']:
val = getattr(self, ident)
if val != None:
filters.append(trace.ButterworthResponse(corner=float(val),
order=4,
type=ident))
stations = self.get_stations()
traces = list(self.chopper_selected_traces(fallback=True, trace_selector=
viewer.trace_selector,
load_data=False))
traces = [tr for trs in traces for tr in trs ]
visible_nslcs = [tr.nslc_id for tr in traces]
stations = [x for x in stations if util.match_nslcs(
"%s.%s.%s.*" % x.nsl(), visible_nslcs)]
# TODO option to choose other models
mod = cake.load_model()
nevents = len(events)
pile = self.get_pile()
targets = make_targets(pile, stations)
if len(targets)==0:
self.fail("No station available")
ntargets = len(targets)
self.cc = num.zeros((ntargets, nevents, nevents), dtype=num.float)
self.similarity_matrix = SimilarityMatrix(targets=targets,
events=events,
filters=filters,
padding=float(self.tpad),
windowing_method=self.time_window_choice,
vmax=float(self.vmax),
vmin=float(self.vmin))
similarities = []
if self.save_traces :
figure_dir = self.input_directory(caption='Select directory to store images')
for itarget, target in enumerate(targets):
print((itarget+1.)/float(ntargets))
ok_filtered = []
markers = []
for iev, ev in enumerate(events):
dist = target.distance_to(ev)
if self.time_window_choice=='vmin/vmax':
tmin = ev.time + dist / self.vmax - self.tpad
tmax = ev.time + dist / self.vmin + self.tpad
elif self.time_window_choice=='P-phase':
d = dist*cake.m2d
z = ev.depth
t = self.phase_cache.get((mod, d, z), False)
if not t:
rays = mod.arrivals(
phases=[cake.PhaseDef(x) for x in 'p P'.split()],
distances=[d],
zstart=z)
t = rays[0].t
self.phase_cache[(mod, d, z)] = t
tmin = ev.time + t - self.tpad * 0.1
tmax = ev.time + t + self.tpad * 0.9
trs = pile.chopper(tmin=tmin,
tmax=tmax,
trace_selector=viewer.trace_selector,
want_incomplete=False)
tr = [t for trss in trs for t in trss if t.nslc_id==target.codes]
if len(tr)==0:
continue
elif len(tr)==1:
tr = tr[0]
else:
self.fail('Something went wrong')
if self.dt_wanted:
tr.downsample_to(self.dt_wanted)
tr2 = tr.copy()
for f in filters:
tr2 = tr2.transfer(transfer_function=f)
tr2.chop(tmin, tmax)
tr2.set_codes(location=ev.name+'f')
tr.chop(tmin, tmax)
tr.set_codes(location=ev.name+'r')
ok_filtered.append((iev, ev, tr2))
ok = ok_filtered
while ok:
(ia, a_ev, a_tr) = ok.pop()
for (ib, b_ev, b_tr) in ok:
relamp = 0.0
if a_tr is not None and b_tr is not None:
c_tr = trace.correlate(a_tr, b_tr, mode='full', normalization='normal')
t_center = c_tr.tmin+(c_tr.tmax-c_tr.tmin)/2.
c_tr_chopped = c_tr.chop(t_center-self.tdist, t_center+self.tdist, inplace=False)
t_mini, v_mini = c_tr_chopped.min()
t_maxi, v_maxi = c_tr_chopped.max()
b_tr_shifted = b_tr.copy()
if abs(v_mini) > abs(v_maxi):
v_cc = v_mini
time_lag = -t_mini
else:
time_lag = -t_maxi
v_cc = v_maxi
self.cc[itarget, ia, ib] = v_cc
b_tr_shifted.shift(time_lag)
if self.cc[itarget, ia, ib] != 0.0:
tmin = max(a_tr.tmin, b_tr_shifted.tmin)
tmax = min(a_tr.tmax, b_tr_shifted.tmax)
try:
a_tr_chopped = a_tr.chop(tmin, tmax, inplace=False)
b_tr_chopped = b_tr_shifted.chop(tmin, tmax)
except trace.NoData:
logger.warn('NoData %s'%a_tr_chopped)
continue
ya = a_tr_chopped.ydata
yb = b_tr_chopped.ydata
relamp = num.sum(ya*yb) / num.sum(ya**2)
if self.save_traces:
fig, axes = plt.subplots(3,1)
fig.suptitle('.'.join(target.codes))
axes[0].plot(a_tr_chopped.get_xdata(), a_tr_chopped.get_ydata())
axes[0].text(0, 1, "id: %s, time: %s" %(a_ev.name, util.time_to_str(a_ev.time)),
transform=axes[0].transAxes,
verticalalignment='top', horizontalalignment='left')
axes[1].plot(b_tr_chopped.get_xdata(), b_tr_chopped.get_ydata())
axes[1].text(0, 1, "id: %s, time: %s" %(b_ev.name, util.time_to_str(b_ev.time)),
transform=axes[1].transAxes,
verticalalignment='top', horizontalalignment='left')
axes[2].plot(c_tr.get_xdata(), c_tr.get_ydata())
axes[2].text(0, 1, 'cc_max: %1.4f' % v_cc,
transform=axes[2].transAxes,
verticalalignment='top', horizontalalignment='left')
fn = op.join(figure_dir, 'cc_T%s.E%s.E%s.png' % (itarget, ia, ib))
fig.savefig(fn, pad_inches=0.1, bbox_inches='tight', tight_layout=True)
sim = Similarity(
ievent=ia,
jevent=ib,
itarget=itarget,
cross_correlation=float(self.cc[itarget, ia, ib]),
relative_amplitude=float(relamp),
time_lag=float(-time_lag))
similarities.append(sim)
if self.show_results:
for itarget, target in enumerate(targets):
if not num.any(self.cc[itarget]):
continue
fig = self.pylab(get='figure')
fig.suptitle('.'.join(target.codes))
axes = fig.add_subplot(111)
axes.set_xlabel('Event number')
axes.set_ylabel('Event number')
mesh = axes.pcolormesh(self.cc[itarget,:,:], cmap='RdBu', vmin=-1.0, vmax=1.0)
cb = fig.colorbar(mesh, ax=axes)
cb.set_label('Max correlation coefficient')
fig.canvas.draw()
self.similarity_matrix.similarities = similarities
self.similarity_matrix.validate()
from pyrocko import cake
from numpy import arange, array
km = 1000.
# Load builtin 'prem-no-ocean' model ('.m': medium resolution variant)
#model = cake.load_model('prem-no-ocean.m')
model = cake.load_model(
'/Users/dmelgar/code/pyrocko/build/lib.macosx-10.6-x86_64-2.7/pyrocko/data/earthmodels/Nocal.nd'
)
# Source depth [m].
#source_depth = 300. * km
source_depth = 5.8
# Distances as a numpy array [deg].
distances = array([5, 10, 20, 50, 100]) * km * cake.m2d
# Define the phase to use.
Phase = cake.PhaseDef('P')
# calculate distances and arrivals and print them:
print 'distance [km] time [s]'
for arrival in model.arrivals(distances, phases=Phase, zstart=source_depth):
print '%13g %13g' % (arrival.x * cake.d2m / km, arrival.t)
def generate_test_data_grid(store_id,
store_dirs,
coordinates,
geometry_params,
pre=0.5,
post=3,
stations_input=None,
batch_loading=256,
paths_disks=None):
engine = LocalEngine(store_superdirs=[store_dirs])
store = engine.get_store(store_id)
mod = store.config.earthmodel_1d
cake_phase = cake.PhaseDef("P")
phase_list = [cake_phase]
waveforms_events = []
waveforms_events_uncut = []
waveforms_noise = []
sources = []
lats = coordinates[0]
lons = coordinates[1]
depths = coordinates[2]
if stations_input is None:
stations_unsorted = model.load_stations("data/stations.pf")
else:
stations_unsorted = model.load_stations(stations_input)
for st in stations_unsorted:
st.dist = orthodrome.distance_accurate50m(st.lat, st.lon, lats[0],
lons[0])
st.azi = orthodrome.azimuth(st.lat, st.lon, lats[0], lons[0])
stations = sorted(stations_unsorted, key=lambda x: x.dist, reverse=True)
targets = []
events = []
mean_lat = []
mean_lon = []
max_rho = 0.
for st in stations:
mean_lat.append(st.lat)
mean_lon.append(st.lon)
for cha in st.channels:
if cha.name is not "R" and cha.name is not "T" and cha.name is not "Z":
target = Target(lat=st.lat,
lon=st.lon,
store_id=store_id,
interpolation='multilinear',
quantity='displacement',
codes=st.nsl() + (cha.name, ))
targets.append(target)
strikes = geometry_params[0]
dips = geometry_params[1]
rakes = geometry_params[2]
vs = geometry_params[3]
ws = geometry_params[4]
grid_points = []
for lat in lats:
for lon in lons:
for depth in depths:
grid_points.append([lat, lon, depth])
ray.init(num_cpus=num_cpus - 1)
npm = len(lats) * len(lons) * len(depths)
npm_geom = len(strikes) * len(dips) * len(rakes)
results = ray.get([
get_parallel_mtqt.remote(i,
targets,
store_id,
post,
pre,
stations,
mod,
grid_points[i],
strikes,
dips,
rakes,
vs,
ws,
store_dirs,
batch_loading=batch_loading,
npm=npm_geom,
paths_disks=paths_disks)
for i in range(len(grid_points))
])
ray.shutdown()
return waveforms_events
def load_data(data_dir,
store_id,
stations=None,
pre=0.5,
post=3,
reference_event=None,
min_len=420,
error_t=None,
lat=None,
lon=None,
depth=None,
engine=None,
ev_id=None):
store = engine.get_store(store_id)
mod = store.config.earthmodel_1d
gf_freq = store.config.sample_rate
cake_phase = cake.PhaseDef("P")
phase_list = [cake_phase]
events = []
waveforms = []
waveforms_shifted = []
if ev_id is None:
pathlist = Path(data_dir).glob('ev_*/')
else:
pathlist = Path(data_dir).glob('ev_%s/' % ev_id)
for path in sorted(pathlist):
targets = []
path = str(path) + "/"
event = model.load_events(path + "event.txt")[0]
traces_loaded = io.load(path + "waveforms/rest/traces.mseed")
stations_unsorted = model.load_stations(data_dir + "stations.pf")
for st in stations_unsorted:
st.dist = orthodrome.distance_accurate50m(st.lat, st.lon,
event.lat, event.lon)
st.azi = orthodrome.azimuth(st.lat, st.lon, event.lat, event.lon)
stations = sorted(stations_unsorted,
key=lambda x: x.dist,
reverse=True)
traces_processed = []
if lat is not None:
event.lat = lat
event.lon = lon
event.depth = depth
traces = check_traces(traces_loaded,
stations,
min_len=min_len,
event=event)
if error_t is not None:
traces_shift = copy.deepcopy(traces)
traces_processed, nsamples = process_loaded_waveforms(
traces, stations, event, gf_freq, mod, pre, post)
if error_t is not None:
traces_processed_shifted = process_loaded_waveforms_shift(
traces_shift,
stations,
event,
gf_freq,
mod,
pre,
post,
shift_max=error_t)
waveforms_shifted.append(traces_processed_shifted)
events.append(event)
waveforms.append(traces_processed)
return waveforms, nsamples, events, waveforms_shifted
def calcTTTAdv_cube(Config,
station,
Origin,
flag,
arrayname,
Xcorrshift,
Refshift,
phase,
flag_rpe=False):
cfg = ConfigObj(dict=Config)
if flag_rpe is True:
dimX = cfg.Int('dimx_emp')
dimY = cfg.Int('dimy_emp')
dimZ = cfg.Int('dimz_emp')
else:
dimX = cfg.Int('dimx')
dimY = cfg.Int('dimy')
dimZ = cfg.Int('dimz')
orig_depth = float(Origin['depth'])
start, stop, step = cfg.String('depths').split(',')
start = orig_depth + float(start)
stop = orig_depth + float(stop)
depths = np.linspace(start, stop, num=dimZ)
gridspacing = cfg.config_geometry.gridspacing
traveltime_model = cfg_yaml.config.traveltime_model
o_lat = float(Origin['lat'])
o_lon = float(Origin['lon'])
oLator = o_lat + dimX / 2
oLonor = o_lon + dimY / 2
oLatul = 0
oLonul = 0
o_dip = 80.
plane = False
TTTGridMap = {}
LMINMAX = []
GridArray = {}
locStation = Location(station.lat, station.lon)
sdelta = loc2degrees(Location(o_lat, o_lon), locStation)
Phase = cake.PhaseDef(phase)
path = palantiri.__path__
model = cake.load_model(path[0] + '/data/' + traveltime_model)
for depth in depths:
o_depth = depth
for i in xrange(dimX):
oLatul = o_lat - ((dimX - 1) / 2) * gridspacing + i * gridspacing
if i == 0:
Latul = oLatul
o = 0
for j in xrange(dimY):
oLonul = o_lon - (
(dimY - 1) / 2) * gridspacing + j * gridspacing
if o == 0 and j == 0:
Lonul = oLonul
de = loc2degrees(Location(oLatul, oLonul), locStation)
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=o_depth * km)
try:
ttime = arrivals[0].t
except Exception:
try:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=o_depth * km,
zstop=o_depth * km,
refine=True)
ttime = arrivals[0].t
except Exception:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=o_depth * km - 2.5,
zstop=o_depth * km + 2.5,
refine=True)
ttime = arrivals[0].t
GridArray[(i, j, depth)] = GridElem(oLatul, oLonul, o_depth,
ttime, de)
LMINMAX.append(ttime)
if ttime == 0:
raise Exception("\033[31mILLEGAL: phase definition\033[0m")
mint = min(LMINMAX)
maxt = max(LMINMAX)
TTTGridMap[station.getName()] = TTTGrid(o_depth, mint, maxt, Latul, Lonul,
oLator, oLonor, GridArray)
k = MinTMaxT(mint, maxt)
if flag_rpe is True:
Basic.dumpToFile(str(flag) + '-ttt_emp.pkl', TTTGridMap)
Basic.dumpToFile('minmax-emp' + str(flag) + '.pkl', k)
Basic.dumpToFile('station-emp' + str(flag) + '.pkl', station)
else:
Basic.dumpToFile(str(flag) + '-ttt.pkl', TTTGridMap)
Basic.dumpToFile('minmax-' + str(flag) + '.pkl', k)
Basic.dumpToFile('station-' + str(flag) + '.pkl', station)
def call(self):
self.cleanup()
viewer = self.get_viewer()
master = viewer.get_active_event()
if master is None:
self.fail('no master event selected')
stations = list(viewer.stations.values())
stations.sort(key=lambda s: (s.network, s.station))
if not stations:
self.fail('no station information available')
# gather events to be processed
events = []
for m in viewer.markers:
if isinstance(m, EventMarker):
if m.kind == 0:
events.append(m.get_event())
events.sort(key=lambda ev: ev.time)
event_to_number = {}
for iev, ev in enumerate(events):
event_to_number[ev] = iev
if self.model_select.startswith('Global'):
model_key = 'global'
else:
model_key = master.lat, master.lon
if model_key != self.model_key:
if self.model_select.startswith('Global'):
self.model = cake.load_model()
else:
latlon = master.lat, master.lon
profile = crust2x2.get_profile(*latlon)
profile.set_layer_thickness(crust2x2.LWATER, 0.0)
self.model = cake.LayeredModel.from_scanlines(
cake.from_crust2x2_profile(profile))
self.model_key = model_key
phases = {
'P': ([cake.PhaseDef(x) for x in 'P p'.split()], 'Z'),
'S': ([cake.PhaseDef(x) for x in 'S s'.split()], 'NE'),
}
phasenames = list(phases.keys())
phasenames.sort()
# synthetic arrivals and ray geometry for master event
master_depth = master.depth
if self.master_depth_km is not None:
master_depth = self.master_depth_km * km
tt = {}
g = {}
for iphase, phasename in enumerate(phasenames):
for istation, station in enumerate(stations):
dist = orthodrome.distance_accurate50m(master, station)
azi = orthodrome.azimuth(master, station)
arrivals = self.model.arrivals(phases=phases[phasename][0],
distances=[dist * cake.m2d],
zstart=master_depth,
zstop=0.0)
if arrivals:
first = arrivals[0]
tt[station.network, station.station, phasename] = first.t
takeoff = first.takeoff_angle()
u = first.path.first_straight().u_in(first.endgaps)
g[iphase, istation] = num.array([
math.cos(azi * d2r) * math.sin(takeoff * d2r) * u,
math.sin(azi * d2r) * math.sin(takeoff * d2r) * u,
math.cos(takeoff * d2r) * u
])
# gather picks for each event
for ev in events:
picks = {}
for m2 in viewer.markers:
if isinstance(m2, PhaseMarker) and m2.kind == 0:
if m2.get_event() == ev:
net, sta, _, _ = m2.one_nslc()
picks[net, sta,
m2.get_phasename()] = (m2.tmax + m2.tmin) / 2.0
ev.picks = picks
# time corrections for extraction windows
dataobs = []
datasyn = []
for phasename in phasenames:
for station in stations:
nsp = station.network, station.station, phasename
datasyn.append(tt.get(nsp, None))
for ev in events:
if nsp in ev.picks:
ttobs = ev.picks[nsp] - ev.time
else:
ttobs = None
dataobs.append(ttobs)
ttsyn = num.array(datasyn, dtype=num.float).reshape(
(len(phasenames), len(stations)))
ttobs = num.array(dataobs, dtype=num.float).reshape(
(len(phasenames), len(stations), len(events)))
ttres = ttobs - ttsyn[:, :, num.newaxis]
tt_corr_event = num.nansum( ttres, axis=1) / \
num.nansum( num.isfinite(ttres), axis=1 )
tt_corr_event = num.where(num.isfinite(tt_corr_event), tt_corr_event,
0.)
ttres -= tt_corr_event[:, num.newaxis, :]
tt_corr_station = num.nansum( ttres, axis=2) / \
num.nansum( num.isfinite(ttres), axis=2 )
tt_corr_station = num.where(num.isfinite(tt_corr_station),
tt_corr_station, 0.)
ttres -= tt_corr_station[:, :, num.newaxis]
tevents_raw = num.array([ev.time for ev in events])
tevents_corr = tevents_raw + num.mean(tt_corr_event, axis=0)
# print timing information
print('timing stats')
for iphasename, phasename in enumerate(phasenames):
data = []
for ev in events:
iev = event_to_number[ev]
for istation, station in enumerate(stations):
nsp = station.network, station.station, phasename
if nsp in tt and nsp in ev.picks:
tarr = ev.time + tt[nsp]
tarr_ec = tarr + tt_corr_event[iphasename, iev]
tarr_ec_sc = tarr_ec + tt_corr_station[iphasename,
istation]
tobs = ev.picks[nsp]
data.append(
(tobs - tarr, tobs - tarr_ec, tobs - tarr_ec_sc))
if data:
data = num.array(data, dtype=num.float).T
print('event %10s %3s %3i %15.2g %15.2g %15.2g' %
((ev.name, phasename, data.shape[1]) +
tuple(num.mean(num.abs(x)) for x in data)))
else:
print('event %10s %3s no picks' % (ev.name, phasename))
# extract and preprocess waveforms
tpad = 0.0
for f in self.corner_highpass, self.corner_lowpass:
if f is not None:
tpad = max(tpad, 1.0 / f)
pile = self.get_pile()
waveforms = {}
for ev in events:
iev = event_to_number[ev]
markers = []
for iphasename, phasename in enumerate(phasenames):
for istation, station in enumerate(stations):
nsp = station.network, station.station, phasename
if nsp in tt:
tarr = ev.time + tt[nsp]
nslcs = [(station.network, station.station, '*', '*')]
marker = PhaseMarker(nslcs,
tarr,
tarr,
1,
event=ev,
phasename=phasename)
markers.append(marker)
tarr2 = tarr + tt_corr_station[iphasename, istation] + \
tt_corr_event[iphasename, iev]
marker = PhaseMarker(nslcs,
tarr2,
tarr2,
2,
event=ev,
phasename=phasename)
markers.append(marker)
tmin = tarr2 + self.tstart
tmax = tarr2 + self.tend
marker = PhaseMarker(nslcs,
tmin,
tmax,
3,
event=ev,
phasename=phasename)
markers.append(marker)
trs = pile.all(tmin,
tmax,
tpad=tpad,
trace_selector=lambda tr: tr.nslc_id[:2]
== nsp[:2],
want_incomplete=False)
trok = []
for tr in trs:
if num.all(tr.ydata[0] == tr.ydata):
continue
if self.corner_highpass:
tr.highpass(4, self.corner_highpass)
if self.corner_lowpass:
tr.lowpass(4, self.corner_lowpass)
tr.chop(tmin, tmax)
tr.set_location(ev.name)
#tr.shift( - (tmin - master.time) )
if num.all(num.isfinite(tr.ydata)):
trok.append(tr)
waveforms[nsp + (iev, )] = trok
self.add_markers(markers)
def get_channel(trs, cha):
for tr in trs:
if tr.channel == cha:
return tr
return None
nevents = len(events)
nstations = len(stations)
nphases = len(phasenames)
# correlate waveforms
coefs = num.zeros((nphases, nstations, nevents, nevents))
coefs.fill(num.nan)
tshifts = coefs.copy()
tshifts_picked = coefs.copy()
for iphase, phasename in enumerate(phasenames):
for istation, station in enumerate(stations):
nsp = station.network, station.station, phasename
for a in events:
ia = event_to_number[a]
for b in events:
ib = event_to_number[b]
if ia == ib:
continue
if nsp in a.picks and nsp in b.picks:
tshifts_picked[iphase,istation,ia,ib] = \
b.picks[nsp] - a.picks[nsp]
wa = waveforms[nsp + (ia, )]
wb = waveforms[nsp + (ib, )]
channels = list(set([tr.channel for tr in wa + wb]))
channels.sort()
tccs = []
for cha in channels:
if cha[-1] not in phases[phasename][1]:
continue
ta = get_channel(wa, cha)
tb = get_channel(wb, cha)
if ta is None or tb is None:
continue
tcc = trace.correlate(ta,
tb,
mode='full',
normalization='normal',
use_fft=True)
tccs.append(tcc)
if not tccs:
continue
tc = None
for tcc in tccs:
if tc is None:
tc = tcc
else:
tc.add(tcc)
tc.ydata *= 1. / len(tccs)
tmid = tc.tmin * 0.5 + tc.tmax * 0.5
tlen = (tc.tmax - tc.tmin) * 0.5
tc_cut = tc.chop(tmid - tlen * 0.5,
tmid + tlen * 0.5,
inplace=False)
tshift, coef = tc_cut.max()
if (tshift < tc.tmin + 0.5 * tc.deltat
or tc.tmax - 0.5 * tc.deltat < tshift):
continue
coefs[iphase, istation, ia, ib] = coef
tshifts[iphase, istation, ia, ib] = tshift
if self.show_correlation_traces:
tc.shift(master.time - (tc.tmax + tc.tmin) / 2.)
self.add_trace(tc)
#tshifts = tshifts_picked
coefssum_sta = num.nansum(coefs, axis=2) / num.sum(num.isfinite(coefs),
axis=2)
csum_sta = num.nansum(coefssum_sta, axis=2) / num.sum(
num.isfinite(coefssum_sta), axis=2)
for iphase, phasename in enumerate(phasenames):
for istation, station in enumerate(stations):
print('station %-5s %s %15.2g' %
(station.station, phasename, csum_sta[iphase, istation]))
coefssum = num.nansum(coefs, axis=1) / num.sum(num.isfinite(coefs),
axis=1)
csumevent = num.nansum(coefssum, axis=2) / num.sum(
num.isfinite(coefssum), axis=2)
above = num.where(num.isfinite(coefs), coefs >= self.min_corr, 0)
csumabove = num.sum(num.sum(above, axis=1), axis=2)
coefssum = num.ma.masked_invalid(coefssum)
print('correlation stats')
for iphase, phasename in enumerate(phasenames):
for ievent, event in enumerate(events):
print('event %10s %3s %8i %15.2g' %
(event.name, phasename, csumabove[iphase, ievent],
csumevent[iphase, ievent]))
# plot event correlation matrix
fframe = self.figure_frame()
fig = fframe.gcf()
for iphase, phasename in enumerate(phasenames):
p = fig.add_subplot(1, nphases, iphase + 1)
p.set_xlabel('Event number')
p.set_ylabel('Event number')
mesh = p.pcolormesh(coefssum[iphase])
cb = fig.colorbar(mesh, ax=p)
cb.set_label('Max correlation coefficient')
if self.save:
fig.savefig(self.output_filename(dir='correlation.pdf'))
fig.canvas.draw()
# setup and solve linear system
data = []
rows = []
weights = []
for iphase in range(nphases):
for istation in range(nstations):
for ia in range(nevents):
for ib in range(ia + 1, nevents):
k = iphase, istation, ia, ib
w = coefs[k]
if not num.isfinite(tshifts[k]) \
or not num.isfinite(w) or w < self.min_corr:
continue
row = num.zeros(nevents * 4)
row[ia * 4:ia * 4 + 3] = g[iphase, istation]
row[ia * 4 + 3] = -1.0
row[ib * 4:ib * 4 + 3] = -g[iphase, istation]
row[ib * 4 + 3] = 1.0
weights.append(w)
rows.append(row)
data.append(tshifts[iphase, istation, ia, ib])
nsamp = len(data)
for i in range(4):
row = num.zeros(nevents * 4)
row[i::4] = 1.
rows.append(row)
data.append(0.0)
if self.fix_depth:
for ievent in range(nevents):
row = num.zeros(nevents * 4)
row[ievent * 4 + 2] = 1.0
rows.append(row)
data.append(0.0)
a = num.array(rows, dtype=num.float)
d = num.array(data, dtype=num.float)
w = num.array(weights, dtype=num.float)
if self.weighting == 'equal':
w[:nsamp] = 1.0
elif self.weighting == 'linear':
pass
elif self.weighting == 'quadratic':
w[:nsamp] = w[:nsamp]**2
a[:nsamp, :] *= w[:, num.newaxis]
d[:nsamp] *= w[:nsamp]
x, residuals, rank, singular = num.linalg.lstsq(a, d)
x0 = num.zeros(nevents * 4)
x0[3::4] = tevents_corr
mean_abs_residual0 = num.mean(
num.abs((num.dot(a[:nsamp], x0) - d[:nsamp]) / w[:nsamp]))
mean_abs_residual = num.mean(
num.abs((num.dot(a[:nsamp], x) - d[:nsamp]) / w[:nsamp]))
print(mean_abs_residual0, mean_abs_residual)
# distorted solutions
npermutations = 100
noiseamount = mean_abs_residual
xdistorteds = []
for i in range(npermutations):
dnoisy = d.copy()
dnoisy[:nsamp] += num.random.normal(
size=nsamp) * noiseamount * w[:nsamp]
xdistorted, residuals, rank, singular = num.linalg.lstsq(a, dnoisy)
xdistorteds.append(xdistorted)
mean_abs_residual = num.mean(
num.abs(num.dot(a, xdistorted)[:nsamp] - dnoisy[:nsamp]))
tmean = num.mean([e.time for e in events])
north = x[0::4]
east = x[1::4]
down = x[2::4]
etime = x[3::4] + tmean
def plot_range(x):
mi, ma = num.percentile(x, [10., 90.])
ext = (ma - mi) / 5.
mi -= ext
ma += ext
return mi, ma
lat, lon = orthodrome.ne_to_latlon(master.lat, master.lon, north, east)
events_out = []
for ievent, event in enumerate(events):
event_out = model.Event(time=etime[ievent],
lat=lat[ievent],
lon=lon[ievent],
depth=down[ievent] + master_depth,
name=event.name)
mark = EventMarker(event_out, kind=4)
self.add_marker(mark)
events_out.append(event_out)
model.Event.dump_catalog(events_out, 'events.relocated.txt')
# plot results
ned_orig = []
for event in events:
n, e = orthodrome.latlon_to_ne(master, event)
d = event.depth
ned_orig.append((n, e, d))
ned_orig = num.array(ned_orig)
ned_orig[:, 0] -= num.mean(ned_orig[:, 0])
ned_orig[:, 1] -= num.mean(ned_orig[:, 1])
ned_orig[:, 2] -= num.mean(ned_orig[:, 2])
north0, east0, down0 = ned_orig.T
north2, east2, down2, time2 = num.hstack(xdistorteds).reshape(
(-1, 4)).T
fframe = self.figure_frame()
fig = fframe.gcf()
color_sym = (0.1, 0.1, 0.0)
color_scat = (0.3, 0.5, 1.0, 0.2)
d = u'\u0394 '
if not self.fix_depth:
p = fig.add_subplot(2, 2, 1, aspect=1.0)
else:
p = fig.add_subplot(1, 1, 1, aspect=1.0)
mi_north, ma_north = plot_range(north)
mi_east, ma_east = plot_range(east)
mi_down, ma_down = plot_range(down)
p.set_xlabel(d + 'East [km]')
p.set_ylabel(d + 'North [km]')
p.plot(east2 / km, north2 / km, '.', color=color_scat, markersize=2)
p.plot(east / km, north / km, '+', color=color_sym)
p.plot(east0 / km, north0 / km, 'x', color=color_sym)
p0 = p
for i, ev in enumerate(events):
p.text(east[i] / km, north[i] / km, ev.name, clip_on=True)
if not self.fix_depth:
p = fig.add_subplot(2, 2, 2, sharey=p0, aspect=1.0)
p.set_xlabel(d + 'Depth [km]')
p.set_ylabel(d + 'North [km]')
p.plot(down2 / km,
north2 / km,
'.',
color=color_scat,
markersize=2)
p.plot(down / km, north / km, '+', color=color_sym)
for i, ev in enumerate(events):
p.text(down[i] / km, north[i] / km, ev.name, clip_on=True)
p1 = p
p = fig.add_subplot(2, 2, 3, sharex=p0, aspect=1.0)
p.set_xlabel(d + 'East [km]')
p.set_ylabel(d + 'Depth [km]')
p.plot(east2 / km, down2 / km, '.', color=color_scat, markersize=2)
p.plot(east / km, down / km, '+', color=color_sym)
for i, ev in enumerate(events):
p.text(east[i] / km, down[i] / km, ev.name, clip_on=True)
p.invert_yaxis()
p2 = p
p0.set_xlim(mi_east / km, ma_east / km)
p0.set_ylim(mi_north / km, ma_north / km)
if not self.fix_depth:
p1.set_xlim(mi_down / km, ma_down / km)
p2.set_ylim(mi_down / km, ma_down / km)
if self.save:
fig.savefig(self.output_filename(dir='locations.pdf'))
fig.canvas.draw()
def plot(settings, show=False):
# align_phase = 'P(cmb)P<(icb)(cmb)p'
with_onset_line = False
fill = True
align_phase = "P"
zoom_window = list(settings.zoom)
ampl_scaler = "4*standard deviation"
quantity = settings.quantity
zstart, zstop, inkr = settings.depths.split(":")
test_depths = num.arange(
float(zstart) * km,
float(zstop) * km,
float(inkr) * km)
try:
traces = io.load(settings.trace_filename)
except FileLoadError as e:
logger.info(e)
return
event = model.load_events(settings.event_filename)
assert len(event) == 1
event = event[0]
event.depth = float(settings.depth) * 1000.0
base_source = MTSource.from_pyrocko_event(event)
test_sources = []
for d in test_depths:
s = base_source.clone()
s.depth = float(d)
test_sources.append(s)
if settings.store_superdirs:
engine = LocalEngine(store_superdirs=settings.store_superdirs)
else:
engine = LocalEngine(use_config=True)
try:
store = engine.get_store(settings.store_id)
except seismosizer.NoSuchStore as e:
logger.info("%s ... skipping." % e)
return
stations = model.load_stations(settings.station_filename)
station = list(
filter(lambda s: match_nslc("%s.%s.%s.*" % s.nsl(), traces[0].nslc_id),
stations))
assert len(station) == 1
station = station[0]
targets = [
station_to_target(station,
quantity=quantity,
store_id=settings.store_id)
]
try:
request = engine.process(targets=targets, sources=test_sources)
except seismosizer.NoSuchStore as e:
logger.info("%s ... skipping." % e)
return
except meta.OutOfBounds as error:
if settings.force_nearest_neighbor:
logger.warning("%s Using nearest neighbor instead." % error)
mod_targets = []
for t in targets:
closest_source = min(test_sources,
key=lambda s: s.distance_to(t))
farthest_source = max(test_sources,
key=lambda s: s.distance_to(t))
min_dist_delta = store.config.distance_min - closest_source.distance_to(
t)
max_dist_delta = (store.config.distance_max -
farthest_source.distance_to(t))
if min_dist_delta < 0:
azi, bazi = closest_source.azibazi_to(t)
newlat, newlon = ortho.azidist_to_latlon(
t.lat, t.lon, azi, min_dist_delta * cake.m2d)
elif max_dist_delta < 0:
azi, bazi = farthest_source.azibazi_to(t)
newlat, newlon = ortho.azidist_to_latlon(
t.lat, t.lon, azi, max_dist_delta * cake.m2d)
t.lat, t.lon = newlat, newlon
mod_targets.append(t)
request = engine.process(targets=mod_targets, sources=test_sources)
else:
logger.error("%s: %s" % (error, ".".join(station.nsl())))
return
alldepths = list(test_depths)
fig = plt.figure()
ax = fig.add_subplot(111)
maxz = max(test_depths)
minz = min(test_depths)
relative_scale = (maxz - minz) * 0.02
for s, t, tr in request.iter_results():
if quantity == "velocity":
tr = integrate_differentiate(tr, "differentiate")
onset = engine.get_store(t.store_id).t("begin",
(s.depth, s.distance_to(t)))
tr = settings.do_filter(tr)
if settings.normalize:
tr.set_ydata(tr.get_ydata() / num.max(abs(tr.get_ydata())))
ax.tick_params(axis="y",
which="both",
left="off",
right="off",
labelleft="off")
y_pos = s.depth
xdata = tr.get_xdata() - onset - s.time
tr_ydata = tr.get_ydata() * -1
visible = tr.chop(
tmin=event.time + onset + zoom_window[0],
tmax=event.time + onset + zoom_window[1],
)
if ampl_scaler == "trace min/max":
ampl_scale = float(max(abs(visible.get_ydata())))
elif ampl_scaler == "4*standard deviation":
ampl_scale = 4 * float(num.std(visible.get_ydata()))
else:
ampl_scale = 1.0
ampl_scale /= settings.gain
ydata = (tr_ydata / ampl_scale) * relative_scale + y_pos
ax.plot(xdata, ydata, c="black", linewidth=1.0, alpha=1.0)
if False:
ax.fill_between(xdata,
y_pos,
ydata,
where=ydata < y_pos,
color="black",
alpha=0.5)
ax.text(
zoom_window[0] * 1.09,
y_pos,
"%1.1f" % (s.depth / 1000.0),
horizontalalignment="right",
) # , fontsize=12.)
if False:
mod = store.config.earthmodel_1d
label = "pP"
arrivals = mod.arrivals(
phases=[cake.PhaseDef(label)],
distances=[s.distance_to(t) * cake.m2d],
zstart=s.depth,
)
try:
t = arrivals[0].t
ydata_absmax = num.max(num.abs(tr.get_ydata()))
marker_length = 0.5
x_marker = [t - onset] * 2
y = [
y_pos - (maxz - minz) * 0.025,
y_pos + (maxz - minz) * 0.025
]
ax.plot(x_marker, y, linewidth=1, c="blue")
ax.text(
x_marker[1] - x_marker[1] * 0.005,
y[1],
label,
# fontsize=12,
color="black",
verticalalignment="top",
horizontalalignment="right",
)
except IndexError:
logger.warning(
"no pP phase at d=%s z=%s stat=%s" %
(s.distance_to(t) * cake.m2d, s.depth, station.station))
pass
if len(traces) == 0:
raise Exception("No Trace found!")
if len(traces) > 1:
raise Exception("More then one trace provided!")
else:
tr = traces[0]
correction = float(settings.correction)
if quantity == "displacement":
tr = integrate_differentiate(tr, "integrate")
tr = settings.do_filter(tr)
onset = (engine.get_store(targets[0].store_id).t(
"begin", (event.depth, s.distance_to(targets[0]))) + event.time)
if settings.normalize:
tr.set_ydata(tr.get_ydata() / max(abs(tr.get_ydata())))
ax.tick_params(axis="y",
which="both",
left="off",
right="off",
labelleft="off")
y_pos = event.depth
xdata = tr.get_xdata() - onset + correction
tr_ydata = tr.get_ydata() * -1
visible = tr.chop(
tmin=onset + zoom_window[0] + correction,
tmax=onset + zoom_window[1] + correction,
)
if ampl_scaler == "trace min/max":
ampl_scale = float(max(abs(visible.get_ydata())))
elif ampl_scaler == "4*standard deviation":
ampl_scale = 4 * float(num.std(visible.get_ydata()))
else:
ampl_scale = 1.0
ydata = (tr_ydata / ampl_scale * settings.gain *
settings.gain_record) * relative_scale + y_pos
ax.plot(xdata, ydata, c=settings.color, linewidth=1.0)
ax.set_xlim(zoom_window)
zmax = max(test_depths)
zmin = min(test_depths)
zrange = zmax - zmin
ax.set_ylim((zmin - zrange * 0.2, zmax + zrange * 0.2))
ax.set_xlabel("Time [s]")
ax.text(
0.0,
0.6,
"Source depth [km]",
rotation=90,
horizontalalignment="left",
transform=fig.transFigure,
) # , fontsize=12.)
if fill:
ax.fill_between(xdata,
y_pos,
ydata,
where=ydata < y_pos,
color=settings.color,
alpha=0.5)
if with_onset_line:
ax.text(0.08, zmax + zrange * 0.1, align_phase, fontsize=14)
vline = ax.axvline(0.0, c="black")
vline.set_linestyle("--")
if settings.title:
params = {
"array-id": "".join(station.nsl()),
"event_name": event.name,
"event_time": time_to_str(event.time),
}
ax.text(
0.5,
1.05,
settings.title % params,
horizontalalignment="center",
transform=ax.transAxes,
)
if settings.auto_caption:
cax = fig.add_axes([0.0, 0.0, 1, 0.05], label="caption")
cax.axis("off")
cax.xaxis.set_visible(False)
cax.yaxis.set_visible(False)
if settings.quantity == "displacement":
quantity_info = "integrated velocity trace. "
if settings.quantity == "velocity":
quantity_info = "differentiated synthetic traces. "
if settings.quantity == "restituted":
quantity_info = "restituted traces. "
captions = {"filters": ""}
for f in settings.filters:
captions["filters"] += "%s-pass, order %s, f$_c$=%s Hz. " % (
f.type,
f.order,
f.corner,
)
captions["quantity_info"] = quantity_info
captions["store_sampling"] = 1.0 / store.config.deltat
cax.text(
0,
0,
"Filters: %(filters)s f$_{GF}$=%(store_sampling)s Hz.\n%(quantity_info)s"
% captions,
fontsize=12,
transform=cax.transAxes,
)
plt.subplots_adjust(hspace=0.4, bottom=0.15)
else:
plt.subplots_adjust(bottom=0.1)
ax.invert_yaxis()
if settings.save_as:
logger.info("save as: %s " % settings.save_as)
options = settings.__dict__
options.update({"array-id": "".join(station.nsl())})
fig.savefig(settings.save_as % options, dpi=160, bbox_inches="tight")
if show:
plt.show()
def refTrigger(self, RefWaveform):
Config = self.Config
cfg = ConfigObj(dict=Config)
name = ('%s.%s.%s.%s') % (
RefWaveform[0].stats.network, RefWaveform[0].stats.station,
RefWaveform[0].stats.location, RefWaveform[0].stats.channel)
i = self.searchMeta(name, self.StationMeta)
de = loc2degrees(self.Origin, i)
ptime = 0
Phase = cake.PhaseDef('P')
model = cake.load_model()
if cfg.colesseo_input() == True:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=self.Origin.depth,
zstop=0.)
else:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=self.Origin.depth * km,
zstop=0.)
try:
ptime = arrivals[0].t
except:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=o_depth * km - 0.1)
ptime = arrivals[0].t
phasename = ('%sphase') % (os.path.basename(self.AF))
if ptime == 0:
print '\033[31mAvailable phases for reference station %s in range %f deegree\033[0m' % (
i, de)
print '\033[31m' + '|'.join(
[str(item['phase_name']) for item in tt]) + '\033[0m'
print '\033[31myou tried phase %s\033[0m' % (
self.Config[phasename])
raise Exception("\033[31mILLEGAL: phase definition\033[0m")
tw = self.calculateTimeWindows(ptime)
if cfg.pyrocko_download() == True:
stP = self.readWaveformsPicker_pyrocko(i, tw, self.Origin, ptime)
elif cfg.colesseo_input() == True:
stP = self.readWaveformsPicker_colos(i, tw, self.Origin, ptime)
else:
stP = self.readWaveformsPicker(i, tw, self.Origin, ptime)
refuntouchname = os.path.basename(self.AF) + '-refstation-raw.mseed'
stP.write(os.path.join(self.EventPath, refuntouchname),
format='MSEED',
byteorder='>')
stP.filter("bandpass",
freqmin=float(self.Config['refstationfreqmin']),
freqmax=float(self.Config['refstationfreqmax']))
stP.trim(tw['xcorrstart'], tw['xcorrend'])
trP = stP[0]
trP.stats.starttime = UTCDateTime(3600)
refname = os.path.basename(self.AF) + '-refstation-filtered.mseed'
trP.write(os.path.join(self.EventPath, refname),
format='MSEED',
byteorder='>')
sta = float(self.Config['refsta'])
lta = float(self.Config['reflta'])
cft = recSTALTA(trP.data, int(sta * trP.stats.sampling_rate),
int(lta * trP.stats.sampling_rate))
t = triggerOnset(cft, lta, sta)
try:
onset = t[0][0] / trP.stats.sampling_rate
print 'ONSET ', onset
except:
onset = self.mintforerun
trigger = trP.stats.starttime + onset
print 'TRIGGER ', trigger
print 'THEORETICAL: ', UTCDateTime(3600) + self.mintforerun
tdiff = (trP.stats.starttime + onset) - (UTCDateTime(3600) +
self.mintforerun)
print 'TDIFF: ', tdiff
refp = UTCDateTime(self.Origin.time) + ptime
reftriggeronset = refp + onset - self.mintforerun
if int(self.Config['autoxcorrcorrectur']) == 1:
try:
refmarkername = os.path.join(self.EventPath, ('%s-marker') %
(os.path.basename(self.AF)))
fobjrefmarkername = open(refmarkername, 'w')
fobjrefmarkername.write(
'# Snuffler Markers File Version 0.2\n')
fobjrefmarkername.write((
'phase: %s 0 %s None None None XWStart None False\n'
) % (tw['xcorrstart'].strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.write((
'phase: %s 0 %s None None None XWEnd None False\n'
) % (tw['xcorrend'].strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.write((
'phase: %s 1 %s None None None TheoP None False\n'
) % (refp.strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.write((
'phase: %s 3 %s None None None XTrig None False'
) % (reftriggeronset.strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.close()
cmd = 'snuffler %s --markers=%s&' % (os.path.join(
self.EventPath, refuntouchname), refmarkername)
os.system(cmd)
thrOn = float(self.Config['reflta']) # 4
thrOff = float(self.Config['refsta']) # 0.7
plotTrigger(trP, cft, thrOn, thrOff)
selection = float(
raw_input('Enter self picked phase in seconds: '))
tdiff = selection - self.mintforerun
refname = os.path.basename(self.AF) + '-shift.mseed'
trP.stats.starttime = trP.stats.starttime - selection
trP.write(os.path.join(self.EventPath, refname),
format='MSEED')
except:
selection = 0.
refname = os.path.basename(self.AF) + '-shift.mseed'
trP.stats.starttime = trP.stats.starttime - selection - self.mintforerun
trP.write(os.path.join(self.EventPath, refname),
format='MSEED')
'''
tdiff = 0
trigger = trP.stats.starttime
'''
To = Trigger(name, trigger, os.path.basename(self.AF), tdiff)
return tdiff, To
def traveltimes(self):
Logfile.red('Enter AUTOMATIC CROSSCORRELATION ')
Logfile.red(
'\n\n+++++++++++++++++++++++++++++++++++++++++++++++++++\n ')
T = []
Wdict = {}
SNR = {}
Config = self.Config
cfg = ConfigObj(dict=Config)
for i in self.StationMeta:
Logfile.red('read in %s ' % (i))
de = loc2degrees(self.Origin, i)
Phase = cake.PhaseDef('P')
model = cake.load_model()
if cfg.colesseo_input() == True:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=self.Origin.depth,
zstop=0.)
else:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=self.Origin.depth * km,
zstop=0.)
try:
ptime = arrivals[0].t
except:
try:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=self.Origin.depth * km -
2.1)
ptime = arrivals[0].t
except:
ptime = ptime
T.append(ptime)
if ptime == 0:
Logfile.red(
'Available phases for station %s in range %f deegree' %
(i, de))
Logfile.red('you tried phase %s' % (self.Config[phasename]))
raise Exception("ILLEGAL: phase definition")
tw = self.calculateTimeWindows(ptime)
# try:
if cfg.pyrocko_download() == True:
w, snr = self.readWaveformsCross_pyrocko(i, tw, ptime)
elif cfg.colesseo_input() == True:
w, snr = self.readWaveformsCross_colesseo(i, tw, ptime)
else:
w, snr = self.readWaveformsCross(i, tw, ptime)
Wdict[i.getName()] = w
SNR[i.getName()] = snr
# except:
# pass
Logfile.red(
'\n\n+++++++++++++++++++++++++++++++++++++++++++++++++++ ')
Logfile.red('Exit AUTOMATIC FILTER ')
return Wdict, SNR
def optparse(required=(),
optional=(),
args=sys.argv,
usage='%prog [options]',
descr=None):
want = required + optional
parser = OptionParser(prog='cake',
usage=usage,
description=descr.capitalize() + '.',
add_help_option=False,
formatter=util.BetterHelpFormatter())
parser.add_option('-h',
'--help',
action='help',
help='Show help message and exit.')
if 'phases' in want:
group = OptionGroup(
parser, 'Phases', '''
Seismic phase arrivals may be either specified as traditional phase names (e.g.
P, S, PP, PcP, ...) or in Cake's own syntax which is more powerful. Use the
--classic option, for traditional phase names. Use the --phase option if you
want to define phases in Cake's syntax.
''')
group.add_option(
'--phase',
'--phases',
dest='phases',
action="append",
default=[],
metavar='PHASE1,PHASE2,...',
help='''Comma separated list of seismic phases in Cake\'s syntax.
The definition of a seismic propagation path in Cake's phase syntax is a string
consisting of an alternating sequence of "legs" and "knees".
A "leg" represents seismic wave propagation without any conversions,
encountering only super-critical reflections. Legs are denoted by "P", "p",
"S", or "s". The capital letters are used when the take-off of the "leg" is
in downward direction, while the lower case letters indicate a take-off in
upward direction.
A "knee" is an interaction with an interface. It can be a mode conversion, a
reflection, or propagation as a headwave or diffracted wave.
* conversion is simply denoted as: "(INTERFACE)" or "DEPTH"
* upperside reflection: "v(INTERFACE)" or "vDEPTH"
* underside reflection: "^(INTERFACE)" or "^DEPTH"
* normal kind headwave or diffracted wave: "v_(INTERFACE)" or "v_DEPTH"
The interface may be given by name or by depth: INTERFACE is the name of an
interface defined in the model, DEPTH is the depth of an interface in [km] (the
interface closest to that depth is chosen). If two legs appear consecutively
without an explicit "knee", surface interaction is assumed.
The preferred standard interface names in cake are "conrad", "moho", "cmb"
(core-mantle boundary), and "cb" (inner core boundary).
The phase definition may end with a backslash "\\", to indicate that the ray
should arrive at the receiver from above instead of from below. It is possible
to restrict the maximum and minimum depth of a "leg" by appending
"<(INTERFACE)" or "<DEPTH" or ">(INTERFACE)" or ">DEPTH" after the leg
character, respectively.
When plotting rays or travel-time curves, the color can be set by appending
"{COLOR}" to the phase definition, where COLOR is the name of a color or an RGB
or RGBA color tuple in the format "R/G/B" or "R/G/B/A", respectively. The
values can be normalized to the range [0, 1] or to [0, 255]. The latter is only
assumed when any of the values given exceeds 1.0.
''')
group.add_option(
'--classic',
dest='classic_phases',
action='append',
default=[],
metavar='PHASE1,PHASE2,...',
help='''Comma separated list of seismic phases in classic
nomenclature. Run "cake list-phase-map" for a list of available
phase names. When plotting, color can be specified in the same way
as in --phases.''')
parser.add_option_group(group)
if 'model' in want:
group = OptionGroup(parser, 'Model')
group.add_option(
'--model',
dest='model_filename',
metavar='(NAME or FILENAME)',
help='Use builtin model named NAME or user model from file '
'FILENAME. By default, the "ak135-f-continental.m" model is '
'used. Run "cake list-models" for a list of builtin models.')
group.add_option(
'--format',
dest='model_format',
metavar='FORMAT',
choices=['nd', 'hyposat'],
default='nd',
help='Set model file format (available: nd, hyposat; default: '
'nd).')
group.add_option(
'--crust2loc',
dest='crust2loc',
metavar='LAT,LON',
help='Set model from CRUST2.0 profile at location (LAT,LON).')
group.add_option(
'--crust2profile',
dest='crust2profile',
metavar='KEY',
help='Set model from CRUST2.0 profile with given KEY.')
parser.add_option_group(group)
if any(x in want
for x in ('zstart', 'zstop', 'distances', 'sloc', 'rloc')):
group = OptionGroup(parser, 'Source-receiver geometry')
if 'zstart' in want:
group.add_option('--sdepth',
dest='sdepth',
type='float',
default=0.0,
metavar='FLOAT',
help='Source depth [km] (default: 0)')
if 'zstop' in want:
group.add_option('--rdepth',
dest='rdepth',
type='float',
default=0.0,
metavar='FLOAT',
help='Receiver depth [km] (default: 0)')
if 'distances' in want:
group.add_option('--distances',
dest='sdist',
metavar='DISTANCES',
help='Surface distances as "start:stop:n" or '
'"dist1,dist2,..." [km]')
group.add_option('--sloc',
dest='sloc',
metavar='LAT,LON',
help='Source location (LAT,LON).')
group.add_option('--rloc',
dest='rloc',
metavar='LAT,LON',
help='Receiver location (LAT,LON).')
parser.add_option_group(group)
if 'material' in want:
group = OptionGroup(
parser, 'Material',
'An isotropic elastic material may be specified by giving '
'a combination of some of the following options. ')
group.add_option('--vp',
dest='vp',
default=None,
type='float',
metavar='FLOAT',
help='P-wave velocity [km/s]')
group.add_option('--vs',
dest='vs',
default=None,
type='float',
metavar='FLOAT',
help='S-wave velocity [km/s]')
group.add_option('--rho',
dest='rho',
default=None,
type='float',
metavar='FLOAT',
help='density [g/cm**3]')
group.add_option('--qp',
dest='qp',
default=None,
type='float',
metavar='FLOAT',
help='P-wave attenuation Qp (default: 1456)')
group.add_option('--qs',
dest='qs',
default=None,
type='float',
metavar='FLOAT',
help='S-wave attenuation Qs (default: 600)')
group.add_option('--poisson',
dest='poisson',
default=None,
type='float',
metavar='FLOAT',
help='Poisson ratio')
group.add_option('--lambda',
dest='lame_lambda',
default=None,
type='float',
metavar='FLOAT',
help='Lame parameter lambda [GPa]')
group.add_option('--mu',
dest='lame_mu',
default=None,
type='float',
metavar='FLOAT',
help='Shear modulus [GPa]')
group.add_option('--qk',
dest='qk',
default=None,
type='float',
metavar='FLOAT',
help='Bulk attenuation Qk')
group.add_option('--qmu',
dest='qmu',
default=None,
type='float',
metavar='FLOAT',
help='Shear attenuation Qmu')
parser.add_option_group(group)
if any(x in want for x in ('vred', 'as_degrees', 'accuracy', 'slowness',
'interface', 'aspect', 'shade_model')):
group = OptionGroup(parser, 'General')
if 'vred' in want:
group.add_option('--vred',
dest='vred',
type='float',
metavar='FLOAT',
help='Velocity for time reduction in plot [km/s]')
if 'as_degrees' in want:
group.add_option(
'--degrees',
dest='as_degrees',
action='store_true',
default=False,
help='Distances are in [deg] instead of [km], velocities in '
'[deg/s] instead of [km/s], slownesses in [s/deg] '
'instead of [s/km].')
if 'accuracy' in want:
group.add_option('--accuracy',
dest='accuracy',
type='float',
metavar='MAXIMUM_RELATIVE_RMS',
default=0.002,
help='Set accuracy for model simplification.')
if 'slowness' in want:
group.add_option(
'--slowness',
dest='slowness',
type='float',
metavar='FLOAT',
default=0.0,
help='Select surface slowness [s/km] (default: 0)')
if 'interface' in want:
group.add_option('--interface',
dest='interface',
metavar='(NAME or DEPTH)',
help='Name or depth [km] of interface to select')
if 'aspect' in want:
group.add_option('--aspect',
dest='aspect',
type='float',
metavar='FLOAT',
help='Aspect ratio for plot')
if 'shade_model' in want:
group.add_option('--no-shade-model',
dest='shade_model',
action='store_false',
default=True,
help='Suppress shading of earth model layers')
parser.add_option_group(group)
if any(x in want for x in ('output_format', )):
group = OptionGroup(parser, 'Output')
if 'output_format' in want:
group.add_option(
'--output-format',
dest='output_format',
metavar='FORMAT',
default='textual',
choices=('textual', 'nd'),
help='Set model output format (available: textual, nd, '
'default: textual)')
parser.add_option_group(group)
if usage == 'cake help-options':
parser.print_help()
(options, args) = parser.parse_args(args)
if len(args) != 2:
parser.error(
'Cake arguments should look like "--option" or "--option=...".')
d = {}
as_degrees = False
if 'as_degrees' in want:
as_degrees = options.as_degrees
d['as_degrees'] = as_degrees
if 'accuracy' in want:
d['accuracy'] = options.accuracy
if 'output_format' in want:
d['output_format'] = options.output_format
if 'aspect' in want:
d['aspect'] = options.aspect
if 'shade_model' in want:
d['shade_model'] = options.shade_model
if 'phases' in want:
phases = []
phase_colors = {}
try:
for ss in options.phases:
for s in ss.split(','):
s = process_color(s, phase_colors)
phases.append(cake.PhaseDef(s))
for pp in options.classic_phases:
for p in pp.split(','):
p = process_color(p, phase_colors)
phases.extend(cake.PhaseDef.classic(p))
except (cake.PhaseDefParseError, cake.UnknownClassicPhase) as e:
parser.error(e)
if not phases and 'phases' in required:
s = process_color('P', phase_colors)
phases.append(cake.PhaseDef(s))
if phases:
d['phase_colors'] = phase_colors
d['phases'] = phases
if 'model' in want:
if options.model_filename:
d['model'] = cake.load_model(options.model_filename,
options.model_format)
if options.crust2loc or options.crust2profile:
if options.crust2loc:
try:
args = tuple(
[float(x) for x in options.crust2loc.split(',')])
except Exception:
parser.error('format for --crust2loc option is '
'"LATITUDE,LONGITUDE"')
elif options.crust2profile:
args = (options.crust2profile.upper(), )
else:
assert False
if 'model' in d:
d['model'] = d['model'].replaced_crust(args)
else:
from pyrocko import crust2x2
profile = crust2x2.get_profile(*args)
d['model'] = cake.LayeredModel.from_scanlines(
cake.from_crust2x2_profile(profile))
if 'vred' in want:
d['vred'] = options.vred
if d['vred'] is not None:
if not as_degrees:
d['vred'] *= r2d * cake.km / cake.earthradius
if 'distances' in want:
distances = None
if options.sdist:
if options.sdist.find(':') != -1:
ssn = options.sdist.split(':')
if len(ssn) != 3:
parser.error('format for distances is '
'"min_distance:max_distance:n_distances"')
distances = num.linspace(*map(float, ssn))
else:
distances = num.array(list(map(float,
options.sdist.split(','))),
dtype=num.float)
if not as_degrees:
distances *= r2d * cake.km / cake.earthradius
if options.sloc and options.rloc:
try:
slat, slon = tuple([float(x) for x in options.sloc.split(',')])
rlat, rlon = tuple([float(x) for x in options.rloc.split(',')])
except Exception:
parser.error('format for --sloc and --rloc options is '
'"LATITUDE,LONGITUDE"')
distance_sr = orthodrome.distance_accurate50m_numpy(
slat, slon, rlat, rlon)
distance_sr *= r2d / cake.earthradius
if distances is not None:
distances = num.concatenate((distances, [distance_sr]))
else:
distances = num.array([distance_sr], dtype=num.float)
if distances is not None:
d['distances'] = distances
else:
if 'distances' not in required:
d['distances'] = None
if 'slowness' in want:
d['slowness'] = options.slowness / cake.d2r
if not as_degrees:
d['slowness'] /= cake.km * cake.m2d
if 'interface' in want:
if options.interface:
try:
d['interface'] = float(options.interface) * cake.km
except ValueError:
d['interface'] = options.interface
else:
d['interface'] = None
if 'zstart' in want:
d['zstart'] = options.sdepth * cake.km
if 'zstop' in want:
d['zstop'] = options.rdepth * cake.km
if 'material' in want:
md = {}
userfactor = dict(vp=1000.,
vs=1000.,
rho=1000.,
qp=1.,
qs=1.,
qmu=1.,
qk=1.,
lame_lambda=1.0e9,
lame_mu=1.0e9,
poisson=1.)
for k in userfactor.keys():
if getattr(options, k) is not None:
md[k] = getattr(options, k) * userfactor[k]
if not (bool('lame_lambda' in md) == bool('lame_mu' in md)):
parser.error('lambda and mu must be specified both.')
if 'lame_lambda' in md and 'lame_mu' in md:
md['lame'] = md.pop('lame_lambda'), md.pop('lame_mu')
if md:
try:
d['material'] = cake.Material(**md)
except cake.InvalidArguments as e:
parser.error(str(e))
for k in list(d.keys()):
if k not in want:
del d[k]
for k in required:
if k not in d:
if k == 'model':
d['model'] = cake.load_model('ak135-f-continental.m')
elif k == 'distances':
d['distances'] = num.linspace(10*cake.km, 100*cake.km, 10) \
/ cake.earthradius * r2d
elif k == 'phases':
d['phases'] = list(map(cake.PhaseDef, 'Pp'))
else:
parser.error('missing %s' % k)
return Anon(d)
axes.set_xlim(-1.1, 1.1)
axes.set_ylim(-1.1, 1.1)
projection = 'lambert'
beachball.plot_beachball_mpl(mt,
axes,
position=(0., 0.),
size=2.0,
color_t=(0.3, 0.3, 0.8),
projection=projection,
size_units='data')
for rlat, rlon in rlatlons:
distance = orthodrome.distance_accurate50m(slat, slon, rlat, rlon)
rays = mod.arrivals(phases=cake.PhaseDef('P'),
zstart=sdepth,
zstop=rdepth,
distances=[distance * cake.m2d])
if not rays:
continue
takeoff = rays[0].takeoff_angle()
azi = orthodrome.azimuth(slat, slon, rlat, rlon)
# to spherical coordinates, r, theta, phi in radians
rtp = num.array([[1., num.deg2rad(takeoff), num.deg2rad(90. - azi)]])
# to 3D coordinates (x, y, z)
points = beachball.numpy_rtp2xyz(rtp)
def refTrigger(self, RefWaveform, phase, cfg_yaml):
Config = self.Config
cfg = ConfigObj(dict=Config)
name = ('%s.%s.%s.%s') % (RefWaveform[0].stats.network,
RefWaveform[0].stats.station,
RefWaveform[0].stats.location,
RefWaveform[0].stats.channel)
i = self.searchMeta(name, self.StationMeta)
de = loc2degrees(self.Origin, i)
ptime = 0
Phase = cake.PhaseDef(phase)
model = cake.load_model()
if cfg_yaml.config_data.colesseo_input is True:
arrivals = model.arrivals([de, de], phases=Phase,
zstart=self.Origin.depth, zstop=0.)
else:
arrivals = model.arrivals([de, de], phases=Phase,
zstart=self.Origin.depth*km, zstop=0.)
try:
ptime = arrivals[0].t
except Exception:
arrivals = model.arrivals([de, de], phases=Phase,
zstart=self.Origin.depth*km-0.1)
ptime = arrivals[0].t
if ptime == 0:
raise Exception("\033[31mILLEGAL: phase definition\033[0m")
tw = self.calculateTimeWindows(ptime)
if cfg_yaml.config_data.pyrocko_download is True:
stP = self.readWaveformsPicker_pyrocko(i, tw, self.Origin, ptime,
cfg_yaml)
elif cfg_yaml.config_data.colesseo_input is True:
stP = self.readWaveformsPicker_colos(i, tw, self.Origin, ptime,
cfg_yaml)
else:
stP = self.readWaveformsPicker(i, tw, self.Origin, ptime, cfg_yaml)
refuntouchname = os.path.basename(self.AF)+'-refstation-raw.mseed'
stP.write(os.path.join(self.EventPath, refuntouchname), format='MSEED',
byteorder='>')
stP.filter("bandpass",
freqmin=float(cfg_yaml.config_xcorr.refstationfreqmin),
freqmax=float(cfg_yaml.config_xcorr.refstationfreqmax))
stP.trim(tw['xcorrstart'], tw['xcorrend'])
trP = stP[0]
trP.stats.starttime = UTCDateTime(3600)
refname = os.path.basename(self.AF)+'-refstation-filtered.mseed'
trP.write(os.path.join(self.EventPath, refname), format='MSEED',
byteorder='>')
sta = float(cfg_yaml.config_xcorr.refsta)
lta = float(cfg_yaml.config_xcorr.reflta)
cft = recSTALTA(trP.data, int(sta * trP.stats.sampling_rate),
int(lta * trP.stats.sampling_rate))
t = triggerOnset(cft, lta, sta)
try:
onset = t[0][0] / trP.stats.sampling_rate
except Exception:
onset = self.mintforerun
trigger = trP.stats.starttime+onset
tdiff = (trP.stats.starttime + onset)-(UTCDateTime(3600)
+ self.mintforerun)
refp = UTCDateTime(self.Origin.time)+ptime
reftriggeronset = refp+onset-self.mintforerun
if cfg_yaml.config_xcorr.autoxcorrcorrectur is True:
refmarkername = os.path.join(self.EventPath,
('%s-marker') % (os.path.basename(
self.AF)))
fobjrefmarkername = open(refmarkername, 'w')
fobjrefmarkername.write('# Snuffler Markers File Version\
0.2\n')
fobjrefmarkername.write(('phase: %s 0 %s None None None XWStart None False\n') % (tw['xcorrstart'].strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.write(('phase: %s 0 %s None None None XWEnd None False\n') % (tw['xcorrend'].strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.write(('phase: %s 1 %s None None None TheoP None False\n') % (refp.strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.write(('phase: %s 3 %s None None None XTrig None False') % (reftriggeronset.strftime('%Y-%m-%d %H:%M:%S.%f'), name))
fobjrefmarkername.close()
cmd = 'snuffler %s --markers=%s&' % (os.path.join(
self.EventPath,
refuntouchname),
refmarkername)
os.system(cmd)
thrOn = float(self.Config['reflta'])
thrOff = float(self.Config['refsta'])
plotTrigger(trP, cft, thrOn, thrOff)
selection = float(input('Enter self picked phase in seconds: '))
tdiff = selection-self.mintforerun
refname = os.path.basename(self.AF)+'-shift.mseed'
trP.stats.starttime = trP.stats.starttime - selection
trP.write(os.path.join(self.EventPath, refname),
format='MSEED')
'''
tdiff = 0
trigger = trP.stats.starttime
'''
To = Trigger(name, trigger, os.path.basename(self.AF), tdiff)
return tdiff, To
def calcTTTAdv(cfg,
station,
Origin,
flag,
arrayname,
Xcorrshift,
Refshift,
phase,
flag_rpe=False):
if flag_rpe is True:
dimX = cfg.config_geometry.dimx_emp
dimY = cfg.config_geometry.dimy_emp
else:
dimX = cfg.config_geometry.dimx
dimY = cfg.config_geometry.dimy
gridspacing = cfg.config_geometry.gridspacing
o_lat = float(Origin['lat'])
o_lon = float(Origin['lon'])
o_depth = float(Origin['depth'])
oLator = o_lat + dimX / 2
oLonor = o_lon + dimY / 2
oLatul = 0
oLonul = 0
o_dip = 80.
plane = False
TTTGridMap = {}
LMINMAX = []
GridArray = {}
locStation = Location(station.lat, station.lon)
sdelta = loc2degrees(Location(o_lat, o_lon), locStation)
Phase = cake.PhaseDef(phase)
path = palantiri.__path__
traveltime_model = cfg.config.traveltime_model
model = cake.load_model(path[0] + '/data/' + traveltime_model)
z = 0
if plane is True:
depth = np.linspace(0., 40., num=dimY)
for i in xrange(70):
oLatul = o_lat - ((dimX - 1) / 2) * gridspacing + i * gridspacing
if z == 0 and i == 0:
Latul = oLatul
o = 0
start_time = time.clock()
for j in xrange(40):
oLonul = o_lon - (
(dimY - 1) /
2) * gridspacing + j * gridspacing / np.cos(o_dip)
if o == 0 and j == 0:
Lonul = oLonul
de = loc2degrees(Location(oLatul, oLonul), locStation)
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=depth[j] * km,
zstop=0.)
try:
ttime = arrivals[0].t
except Exception:
try:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=depth[j] * km - 2.5,
zstop=depth[j] * km + 2.5,
refine=True)
ttime = arrivals[0].t
except Exception:
tt = obs_TravelTimes(de, o_depth)
for k in tt:
if k['phase_name'] == 'P' or k['phase_name'] == (
'%sdiff') % (Config[phasename]):
ttime = k['time']
print("Something wrong with phase arrival, too large\
distances choosen?")
GridArray[(i, j)] = GridElem(oLatul, oLonul, depth[j], ttime,
de)
LMINMAX.append(ttime)
if ttime == 0:
raise Exception("\033[31mILLEGAL: phase definition\033[0m")
else:
for i in xrange(dimX):
oLatul = o_lat - ((dimX - 1) / 2) * gridspacing + i * gridspacing
if z == 0 and i == 0:
Latul = oLatul
o = 0
for j in xrange(dimY):
oLonul = o_lon - (
(dimY - 1) / 2) * gridspacing + j * gridspacing
if o == 0 and j == 0:
Lonul = oLonul
de = loc2degrees(Location(oLatul, oLonul), locStation)
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=o_depth * km)
try:
ttime = arrivals[0].t
except:
try:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=o_depth * km,
zstop=o_depth * km,
refine=True)
ttime = arrivals[0].t
except:
arrivals = model.arrivals([de, de],
phases=Phase,
zstart=o_depth * km - 2.5,
zstop=o_depth * km + 2.5,
refine=True)
ttime = arrivals[0].t
GridArray[(i, j)] = GridElem(oLatul, oLonul, o_depth, ttime,
de)
LMINMAX.append(ttime)
if ttime == 0:
raise Exception("\033[31mILLEGAL: phase definition\033[0m")
mint = min(LMINMAX)
maxt = max(LMINMAX)
TTTGridMap[station.getName()] = TTTGrid(o_depth, mint, maxt, Latul, Lonul,
oLator, oLonor, GridArray)
k = MinTMaxT(mint, maxt)
if flag_rpe is True:
Basic.dumpToFile(str(flag) + '-ttt_emp.pkl', TTTGridMap)
Basic.dumpToFile('minmax-emp' + str(flag) + '.pkl', k)
Basic.dumpToFile('station-emp' + str(flag) + '.pkl', station)
else:
Basic.dumpToFile(str(flag) + '-ttt.pkl', TTTGridMap)
Basic.dumpToFile('minmax-' + str(flag) + '.pkl', k)
Basic.dumpToFile('station-' + str(flag) + '.pkl', station)
