def test_explosion_source(self):
target = gf.Target(interpolation='nearest_neighbor')
ex = gf.ExplosionSource(magnitude=5., volume_change=4., depth=5 * km)
with self.assertRaises(gf.DerivedMagnitudeError):
ex.validate()
ex = gf.ExplosionSource(depth=5 * km)
ex.validate()
self.assertEqual(ex.get_moment(), 1.0)
ex = gf.ExplosionSource(magnitude=3.0, depth=5 * km)
store = self.dummy_store()
with self.assertRaises(gf.DerivedMagnitudeError):
ex.get_volume_change()
volume_change = ex.get_volume_change(store, target)
with self.assertRaises(TypeError):
ex.get_volume_change(store,
gf.Target(interpolation='nearest_neighbour'))
ex = gf.ExplosionSource(volume_change=volume_change, depth=5 * km)
self.assertAlmostEqual(ex.get_magnitude(store, target), 3.0)
ex = gf.ExplosionSource(magnitude=3.0, depth=-5.)
with self.assertRaises(gf.DerivedMagnitudeError):
ex.get_volume_change(store, target)
def test_explosion_source(self):
target = gf.Target(interpolation='nearest_neighbor')
ex = gf.ExplosionSource(magnitude=5., volume_change=4., depth=5 * km)
with self.assertRaises(gf.DerivedMagnitudeError):
ex.validate()
ex = gf.ExplosionSource(depth=5 * km)
ex.validate()
self.assertEqual(ex.get_moment(), 1.0)
# magnitude input
magnitude = 3.
ex = gf.ExplosionSource(magnitude=magnitude, depth=5 * km)
store = self.dummy_store()
with self.assertRaises(gf.DerivedMagnitudeError):
ex.get_volume_change()
volume_change = ex.get_volume_change(store, target)
self.assertAlmostEqual(ex.get_magnitude(store, target), magnitude)
# validate with MT source
moment = ex.get_moment(store, target) * float(num.sqrt(2. / 3))
mt = gf.MTSource(mnn=moment, mee=moment, mdd=moment)
self.assertAlmostEqual(ex.get_magnitude(store, target),
mt.get_magnitude(store=store, target=target))
# discretized sources
d_ex = ex.discretize_basesource(store=store, target=target)
d_mt = mt.discretize_basesource(store=store, target=target)
d_ex_m6s = d_ex.get_source_terms('elastic10')
d_mt_m6s = d_mt.get_source_terms('elastic10')
numeq(d_ex_m6s, d_mt_m6s, 1e-20)
# interpolation method
with self.assertRaises(TypeError):
ex.get_volume_change(store,
gf.Target(interpolation='nearest_neighbour'))
# volume change input
ex = gf.ExplosionSource(volume_change=volume_change, depth=5 * km)
self.assertAlmostEqual(ex.get_magnitude(store, target), 3.0)
ex = gf.ExplosionSource(magnitude=3.0, depth=-5.)
with self.assertRaises(gf.DerivedMagnitudeError):
ex.get_volume_change(store, target)
def test_discretize_rect_source_stf(self):
store = self.dummy_homogeneous_store()
target = gf.Target(interpolation='nearest_neighbor')
stf = gf.HalfSinusoidSTF(duration=3.)
for source in [
gf.RectangularSource(depth=10 * km,
slip=0.5,
width=5 * km,
length=5 * km,
stf=stf,
stf_mode='pre'),
gf.RectangularSource(depth=10 * km,
magnitude=5.0,
width=5 * km,
length=5 * km,
decimation_factor=2,
stf=stf,
stf_mode='pre')
]:
dsource = source.discretize_basesource(store, target)
amplitudes = source._discretize(store, target)[2]
assert amplitudes[0] != amplitudes[1]
m1 = source.get_moment(store, target)
m2 = dsource.centroid().pyrocko_moment_tensor().scalar_moment()
assert abs(m1 - m2) < abs(m1 + m2) * 1e-6
def get_targets(self):
targets = []
for station in self.get_stations():
channel_data = []
channels = station.get_channels()
if channels:
for channel in channels:
channel_data.append(
[channel.name, channel.azimuth, channel.dip])
else:
for c_name in ['BHZ', 'BHE', 'BHN']:
channel_data.append([
c_name,
model.guess_azimuth_from_name(c_name),
model.guess_dip_from_name(c_name)
])
for c_name, c_azi, c_dip in channel_data:
target = gf.Target(codes=(station.network, station.station,
station.location, c_name),
quantity='displacement',
lat=station.lat,
lon=station.lon,
depth=station.depth,
store_id=self.store_id,
optimization='enable',
interpolation='nearest_neighbor',
azimuth=c_azi,
dip=c_dip)
targets.append(target)
return targets
def test_stf_pre_post(self):
store_dir = self.get_pulse_store_dir()
engine = gf.LocalEngine(store_dirs=[store_dir])
store = engine.get_store('pulse')
for duration in [0., 0.05, 0.1]:
trs = []
for mode in ['pre', 'post']:
source = gf.ExplosionSource(
time=store.config.deltat * 0.5,
depth=200.,
moment=1.0,
stf=gf.BoxcarSTF(duration=duration),
stf_mode=mode)
target = gf.Target(codes=('', 'STA', '', 'Z'),
north_shift=500.,
east_shift=0.,
store_id='pulse')
xtrs = engine.process(source, target).pyrocko_traces()
for tr in xtrs:
tr.set_codes(location='%3.1f_%s' % (duration, mode))
trs.append(tr)
tmin = max(tr.tmin for tr in trs)
tmax = min(tr.tmax for tr in trs)
for tr in trs:
tr.chop(tmin, tmax)
amax = max(num.max(num.abs(tr.ydata)) for tr in trs)
perc = num.max(num.abs(trs[0].ydata - trs[1].ydata) / amax) * 100.
if perc > 0.1:
logger.warn('test_stf_pre_post: max difference of %.1f %%' %
perc)
def get_modelling_targets(self, codes, lat, lon, depth, store_id,
backazimuth):
mtargets = []
for channel in self.channels:
target = gf.Target(quantity='displacement',
codes=codes + (channel, ),
lat=lat,
lon=lon,
depth=depth,
store_id=store_id)
if channel == 'R':
target.azimuth = backazimuth - 180.
target.dip = 0.
elif channel == 'T':
target.azimuth = backazimuth - 90.
target.dip = 0.
elif channel == 'Z':
target.azimuth = 0.
target.dip = -90.
mtargets.append(target)
return mtargets
def test_target_source_timing(self):
store_dir = self.get_pulse_store_dir()
engine = gf.LocalEngine(store_dirs=[store_dir])
for stime in [0., -160000., time.time()]:
source = gf.ExplosionSource(
depth=200.,
magnitude=4.,
time=stime)
targets = [
gf.Target(
codes=('', 'STA', '', component),
north_shift=500.,
tmin=source.time-300.,
tmax=source.time+300.,
east_shift=500.)
for component in 'ZNE'
]
response = engine.process(source, targets)
synthetic_traces = response.pyrocko_traces()
data = num.zeros(num.shape(synthetic_traces[0].ydata))
for tr in synthetic_traces:
data += tr.ydata
sum_data = num.sum(abs(tr.ydata))
assert sum_data > 1.0
def test_optimization(self):
store_dir = self.get_pulse_store_dir()
engine = gf.LocalEngine(store_dirs=[store_dir])
sources = [
gf.RectangularExplosionSource(time=0.0025,
depth=depth,
moment=1.0,
length=100.,
width=0.,
nucleation_x=-1)
for depth in [100., 200., 300.]
]
targetss = [[
gf.Target(codes=('', 'STA', opt, component),
north_shift=500.,
east_shift=125.,
depth=depth,
interpolation='multilinear',
optimization=opt) for component in 'ZNE'
for depth in [0., 5., 10]
] for opt in ('disable', 'enable')]
resps = [engine.process(sources, targets) for targets in targetss]
iters = [resp.iter_results() for resp in resps]
for i in xrange(len(sources) * len(targetss[0])):
s1, t1, tr1 = iters[0].next()
s2, t2, tr2 = iters[1].next()
self.assertEqual(tr1.data_len(), tr2.data_len())
self.assertEqual(tr1.tmin, tr2.tmin)
self.assertTrue(numeq(tr1.ydata, tr2.ydata, 0.0001))
def test_combine_dsources(self):
store = self.dummy_store()
dummy_target = gf.Target()
for S in gf.source_classes:
if not hasattr(S, 'discretize_basesource'):
continue
for lats in [[10., 10., 10.], [10., 11., 12.]]:
sources = [
default_source(S,
lat=lat,
lon=20.,
depth=1000.,
north_shift=500.,
east_shift=500.) for lat in lats
]
dsources = [
s.discretize_basesource(store, target=dummy_target)
for s in sources
]
DS = dsources[0].__class__
dsource = DS.combine(dsources)
assert dsource.nelements == sum(s.nelements for s in dsources)
def test_qssp_build_2020_rotational(self):
qssp.init(self.tmpdir,
'2020',
config_params=dict(stored_quantity='rotation',
source_depth_max=10e3,
distance_min=500e3,
distance_max=600e3))
store = gf.store.Store(self.tmpdir, 'r')
store.make_ttt()
qssp.build(self.tmpdir)
del store
engine = gf.LocalEngine(store_dirs=[self.tmpdir])
source = gf.DCSource(lat=0., lon=0., depth=10e3, magnitude=6.0)
targets = [
gf.Target(quantity='rotation',
codes=('', 'ROT', '', comp),
lat=0.,
lon=0.,
north_shift=500e3,
east_shift=100e3) for comp in 'NEZ'
]
engine.process(source, targets)
def main(n, depths, durations, noisy, noise_factor, velocity_model, long, tmin,
tmax, save_file, save_dir, _run):
engine = LocalEngine(store_dirs=[velocity_model])
target = gf.Target(quantity='displacement',
lat=0,
lon=long,
store_id=velocity_model,
codes=('NET', 'STA', 'LOC', 'E'),
tmin=tmin,
tmax=tmax)
df = createFocalMechanisms(n,
depths,
durations,
target,
engine,
noisy=noisy,
noise_factor=noise_factor)
if os.path.exists(save_dir) == False: os.mkdir(save_dir)
path = save_dir + save_file
df.to_pickle(path)
ex.add_artifact(path)
def test_pulse(self):
store_dir = self.get_pulse_store_dir()
engine = gf.LocalEngine(store_dirs=[store_dir])
sources = [
gf.ExplosionSource(
time=0.0,
depth=depth,
moment=moment)
for moment in (1.0, 2.0, 3.0) for depth in [100., 200., 300.]
]
targets = [
gf.Target(
codes=('', 'STA', '', component),
north_shift=500.,
east_shift=0.)
for component in 'ZNE'
]
pulse = engine.get_store_extra(None, 'pulse')
store = engine.get_store('pulse')
response = engine.process(sources=sources, targets=targets)
for source, target, tr in response.iter_results():
t = tr.get_xdata()
dist = math.sqrt((source.depth - target.depth)**2 +
source.distance_to(target)**2)
data = pulse.evaluate(dist, t-source.time)
phi = math.atan2((source.depth - target.depth),
source.distance_to(target)) * r2d
azi, bazi = source.azibazi_to(target)
data *= source.get_moment(store) * math.sqrt(2./3.)
if tr.channel.endswith('N'):
data *= math.cos(phi*d2r) * math.cos(azi*d2r)
elif tr.channel.endswith('E'):
data *= math.cos(phi*d2r) * math.sin(azi*d2r)
elif tr.channel.endswith('Z'):
data *= math.sin(phi*d2r)
tr2 = tr.copy(data=False)
tr2.set_ydata(data)
tr2.set_codes(location='X')
num.testing.assert_almost_equal(data, tr.ydata, 2)
def test_source_times(self):
store = self.dummy_store()
dummy_target = gf.Target()
for S in gf.source_classes:
if not hasattr(S, 'discretize_basesource'):
continue
for t in [0.0, util.str_to_time('2014-01-01 10:00:00')]:
source = default_source(S, time=t)
dsource = source.discretize_basesource(store,
target=dummy_target)
cent = dsource.centroid()
assert numeq(cent.time, t, 0.0001)
def test_process_timeseries(self):
engine = gf.LocalEngine(use_config=True)
sources = [
gf.ExplosionSource(
time=0.0,
depth=depth,
moment=moment)
for moment in [2., 4., 8.] for depth in [3000., 6000., 12000.]
]
targets = [
gf.Target(
codes=('', 'ST%d' % i, '', component),
north_shift=shift*km,
east_shift=0.,
tmin=tmin,
store_id='global_2s',
tmax=None if tmin is None else tmin+40.)
for component in 'ZNE' for i, shift in enumerate([100])
for tmin in [None, 5., 20.]
]
response_sum = engine.process(sources=sources, targets=targets,
calc_timeseries=False, nthreads=1)
response_calc = engine.process(sources=sources, targets=targets,
calc_timeseries=True, nthreads=1)
for (source, target, tr), (source_n, target_n, tr_n) in zip(
response_sum.iter_results(), response_calc.iter_results()):
assert source is source_n
assert target is target_n
t1 = tr.get_xdata()
t2 = tr_n.get_xdata()
num.testing.assert_equal(t1, t2)
disp1 = tr.get_ydata()
disp2 = tr_n.get_ydata()
num.testing.assert_equal(disp1, disp2)
def test_pulse_decimate(self):
store_dir = self.get_pulse_store_dir()
store = gf.Store(store_dir)
store.make_decimated(2)
engine = gf.LocalEngine(store_dirs=[store_dir])
# pulse = engine.get_store_extra(None, 'pulse')
source = gf.ExplosionSource(
time=0.0,
depth=100.,
moment=1.0)
targets = [
gf.Target(
codes=('', 'STA', '%s' % sample_rate, component),
sample_rate=sample_rate,
north_shift=500.,
east_shift=0.)
for component in 'N'
for sample_rate in [None, store.config.sample_rate / 2.0]
]
response = engine.process(source, targets)
trs = []
for source, target, tr in response.iter_results():
tr.extend(0., 1.)
if target.sample_rate is None:
tr.downsample_to(2./store.config.sample_rate, snap=True)
trs.append(tr)
tmin = max(tr.tmin for tr in trs)
tmax = min(tr.tmax for tr in trs)
for tr in trs:
tr.chop(tmin, tmax)
num.testing.assert_almost_equal(
trs[0].ydata, trs[1].ydata, 2)
def test_discretize_rect_source(self):
store = self.dummy_homogeneous_store()
target = gf.Target(interpolation='nearest_neighbor')
for source in [
gf.RectangularSource(depth=10 * km,
slip=0.5,
width=5 * km,
length=5 * km),
gf.RectangularSource(depth=10 * km,
magnitude=5.0,
width=5 * km,
length=5 * km)
]:
dsource = source.discretize_basesource(store, target)
m1 = source.get_moment(store, target)
m2 = dsource.centroid().pyrocko_moment_tensor().scalar_moment()
assert abs(m1 - m2) < abs(m1 + m2) * 1e-6
def test_rect_source(self):
store = self.dummy_homogeneous_store()
rect1 = gf.RectangularSource(depth=10 * km,
magnitude=5.0,
width=5 * km,
length=5 * km)
rect2 = gf.RectangularSource(
depth=10 * km,
slip=pmt.magnitude_to_moment(5.0) /
(5 * km * 5 * km *
store.config.earthmodel_1d.material(10 * km).shear_modulus()),
width=5 * km,
length=5 * km)
self.assertAlmostEqual(
rect1.get_magnitude(),
rect2.get_magnitude(store,
gf.Target(interpolation='nearest_neighbor')))
def base_key(self):
# method returns STF name and the values
return (self.__class__.__name__, self.duration, self.anchor)
if __name__ == '__main__':
model = 'crust2_m5_hardtop_16Hz'
engine = LocalEngine(store_dirs=[model])
target = gf.Target(quantity='displacement',
lat=0,
lon=1,
store_id=model,
codes=('NET', 'STA', 'LOC', 'E'),
tmin=10,
tmax=75)
DC_tensors = [createMT_DC(mag) for mag in 4 * np.random.rand(1000)]
CLVD_tensors = [createMT_CLVD(mag) for mag in 4 * np.random.rand(1000)]
Iso_tensors = [createMT_Isotropic(mag) for mag in 4 * np.random.rand(1000)]
moment_tensors = DC_tensors + CLVD_tensors + Iso_tensors
def process(source, target):
trace = engine.process(source, [target]).pyrocko_traces()[0]
trace.ydata /= np.max(trace.ydata)
return trace
def test_make_params_bench(store, dim, ntargets, interpolation,
nthreads):
source = gf.RectangularSource(lat=0.,
lon=0.,
depth=10 * km,
north_shift=0.1,
east_shift=0.1,
width=dim,
length=dim)
targets = [
gf.Target(lat=random.random() * 10.,
lon=random.random() * 10.,
north_shift=0.1,
east_shift=0.1) for x in xrange(ntargets)
]
dsource = source.discretize_basesource(store, targets[0])
source_coords_arr = dsource.coords5()
mts_arr = dsource.m6s
receiver_coords_arr = num.empty((len(targets), 5))
for itarget, target in enumerate(targets):
receiver = target.receiver(store)
receiver_coords_arr[itarget, :] = \
[receiver.lat, receiver.lon, receiver.north_shift,
receiver.east_shift, receiver.depth]
ns = mts_arr.shape[0]
label = '_ns%04d_nt%04d_%s_np%02d' % (ns, len(targets),
interpolation, nthreads)
@benchmark.labeled('c%s' % label)
def make_param_c():
return store_ext.make_sum_params(store.cstore,
source_coords_arr, mts_arr,
receiver_coords_arr,
'elastic10', interpolation,
nthreads)
@benchmark.labeled('p%s' % label)
def make_param_python():
weights_c = []
irecords_c = []
for itar, target in enumerate(targets):
receiver = target.receiver(store)
dsource = source.discretize_basesource(store, target)
for i, (component, args, delays, weights) in \
enumerate(store.config.make_sum_params(
dsource, receiver)):
if len(weights_c) <= i:
weights_c.append([])
irecords_c.append([])
if interpolation == 'nearest_neighbor':
irecords = num.array(store.config.irecords(*args))
weights = num.array(weights)
else:
assert interpolation == 'multilinear'
irecords, ip_weights =\
store.config.vicinities(*args)
neach = irecords.size / args[0].size
weights = num.repeat(weights, neach) * ip_weights
delays = num.repeat(delays, neach)
weights_c[i].append(weights)
irecords_c[i].append(irecords)
for c in xrange(len(weights_c)):
weights_c[c] = num.concatenate([w for w in weights_c[c]])
irecords_c[c] = num.concatenate(
[ir for ir in irecords_c[c]])
return zip(weights_c, irecords_c)
rc = make_param_c()
rp = make_param_python()
logger.info(benchmark.__str__(header=False))
benchmark.clear()
# Comparing the results
if isinstance(store.config, gf.meta.ConfigTypeA):
idim = 4
elif isinstance(store.config, gf.meta.ConfigTypeB):
idim = 8
if interpolation == 'nearest_neighbor':
idim = 1
nsummands_scheme = [5, 5, 3] # elastic8
nsummands_scheme = [6, 6, 4] # elastic10
for i, nsummands in enumerate(nsummands_scheme):
for r in [0, 1]:
r_c = rc[i][r]
r_p = rp[i][r].reshape(ntargets, nsummands, ns * idim)
r_p = num.transpose(r_p, axes=[0, 2, 1])
num.testing.assert_almost_equal(r_c, r_p.flatten())
def _off_test_synthetic(self):
from pyrocko import gf
km = 1000.
nstations = 10
edepth = 5 * km
store_id = 'crust2_d0'
swin = 2.
lwin = 9. * swin
ks = 1.0
kl = 1.0
kd = 3.0
engine = gf.get_engine()
snorths = (num.random.random(nstations) - 1.0) * 50 * km
seasts = (num.random.random(nstations) - 1.0) * 50 * km
targets = []
for istation, (snorths, seasts) in enumerate(zip(snorths, seasts)):
targets.append(
gf.Target(quantity='displacement',
codes=('', 's%03i' % istation, '', 'Z'),
north_shift=float(snorths),
east_shift=float(seasts),
store_id=store_id,
interpolation='multilinear'))
source = gf.DCSource(north_shift=50 * km,
east_shift=50 * km,
depth=edepth)
store = engine.get_store(store_id)
response = engine.process(source, targets)
trs = []
station_traces = defaultdict(list)
station_targets = defaultdict(list)
for source, target, tr in response.iter_results():
tp = store.t('any_P', source, target)
t = tp - 5 * tr.deltat + num.arange(11) * tr.deltat
if False:
gauss = trace.Trace(tmin=t[0],
deltat=tr.deltat,
ydata=num.exp(-((t - tp)**2) /
((2 * tr.deltat)**2)))
tr.ydata[:] = 0.0
tr.add(gauss)
trs.append(tr)
station_traces[target.codes[:3]].append(tr)
station_targets[target.codes[:3]].append(target)
station_stalta_traces = {}
for nsl, traces in station_traces.items():
etr = None
for tr in traces:
sqr_tr = tr.copy(data=False)
sqr_tr.ydata = tr.ydata**2
if etr is None:
etr = sqr_tr
else:
etr += sqr_tr
autopick.recursive_stalta(swin, lwin, ks, kl, kd, etr)
etr.set_codes(channel='C')
station_stalta_traces[nsl] = etr
trace.snuffle(trs + list(station_stalta_traces.values()))
deltat = trs[0].deltat
nnorth = 50
neast = 50
size = 200 * km
north = num.linspace(-size, size, nnorth)
north2 = num.repeat(north, neast)
east = num.linspace(-size, size, neast)
east2 = num.tile(east, nnorth)
depth = 5 * km
def tcal(target, i):
try:
return store.t(
'any_P',
gf.Location(north_shift=north2[i],
east_shift=east2[i],
depth=depth), target)
except gf.OutOfBounds:
return 0.0
nsls = sorted(station_stalta_traces.keys())
tts = num.fromiter((tcal(station_targets[nsl][0], i)
for i in range(nnorth * neast) for nsl in nsls),
dtype=num.float)
arrays = [
station_stalta_traces[nsl].ydata.astype(num.float) for nsl in nsls
]
offsets = num.array([
int(round(station_stalta_traces[nsl].tmin / deltat))
for nsl in nsls
],
dtype=num.int32)
shifts = -num.array([int(round(tt / deltat)) for tt in tts],
dtype=num.int32).reshape(nnorth * neast, nstations)
weights = num.ones((nnorth * neast, nstations))
print(shifts[25 * neast + 25] * deltat)
print(offsets.dtype, shifts.dtype, weights.dtype)
print('stack start')
mat, ioff = parstack(arrays, offsets, shifts, weights, 1)
print('stack stop')
mat = num.reshape(mat, (nnorth, neast))
from matplotlib import pyplot as plt
fig = plt.figure()
axes = fig.add_subplot(1, 1, 1, aspect=1.0)
axes.contourf(east / km, north / km, mat)
axes.plot(
g(targets, 'east_shift') / km,
g(targets, 'north_shift') / km, '^')
axes.plot(source.east_shift / km, source.north_shift / km, 'o')
plt.show()
def test_against_kiwi(self):
engine = gf.get_engine()
store_id = 'chile_70km_crust'
try:
store = engine.get_store(store_id)
except gf.NoSuchStore:
logger.warn('GF Store %s not available - skipping test' % store_id)
return
base_source = gf.RectangularSource(
depth=15*km,
strike=0.,
dip=90.,
rake=0.,
magnitude=4.5,
nucleation_x=-1.,
length=10*km,
width=0*km,
stf=gf.BoxcarSTF(duration=1.0))
base_event = base_source.pyrocko_event()
channels = 'NEZ'
nstations = 10
stations = []
targets = []
for istation in xrange(nstations):
dist = rand(40.*km, 900*km)
azi = rand(-180., 180.)
north_shift = dist * math.cos(azi*d2r)
east_shift = dist * math.sin(azi*d2r)
lat, lon = od.ne_to_latlon(0., 0., north_shift, east_shift)
sta = 'S%02i' % istation
station = model.Station(
'', sta, '',
lat=lat,
lon=lon)
station.set_channels_by_name('N', 'E', 'Z')
stations.append(station)
for cha in channels:
target = gf.Target(
codes=station.nsl() + (cha,),
lat=lat,
lon=lon,
quantity='displacement',
interpolation='multilinear',
optimization='enable',
store_id=store_id)
targets.append(target)
from tunguska import glue
nsources = 10
# nprocs_max = multiprocessing.cpu_count()
nprocs = 1
try:
seis = glue.start_seismosizer(
gfdb_path=op.join(store.store_dir, 'db'),
event=base_event,
stations=stations,
hosts=['localhost']*nprocs,
balance_method='123321',
effective_dt=0.5,
verbose=False)
ksource = to_kiwi_source(base_source)
seis.set_source(ksource)
recs = seis.get_receivers_snapshot(('syn',), (), 'plain')
trs = []
for rec in recs:
for tr in rec.get_traces():
tr.set_codes(channel=transchan[tr.channel])
trs.append(tr)
trs2 = engine.process(base_source, targets).pyrocko_traces()
trace.snuffle(trs + trs2)
seis.set_synthetic_reference()
for sourcetype in ['point', 'rect']:
sources = []
for isource in xrange(nsources):
m = pmt.MomentTensor.random_dc()
strike, dip, rake = map(float, m.both_strike_dip_rake()[0])
if sourcetype == 'point':
source = gf.RectangularSource(
north_shift=rand(-20.*km, 20*km),
east_shift=rand(-20.*km, 20*km),
depth=rand(10*km, 20*km),
nucleation_x=0.0,
nucleation_y=0.0,
strike=strike,
dip=dip,
rake=rake,
magnitude=rand(4.0, 5.0),
stf=gf.BoxcarSTF(duration=1.0))
elif sourcetype == 'rect':
source = gf.RectangularSource(
north_shift=rand(-20.*km, 20*km),
east_shift=rand(-20.*km, 20*km),
depth=rand(10*km, 20*km),
length=10*km,
width=5*km,
nucleation_x=-1.,
nucleation_y=0,
strike=strike,
dip=dip,
rake=rake,
magnitude=rand(4.0, 5.0),
stf=gf.BoxcarSTF(duration=1.0))
else:
assert False
sources.append(source)
for temperature in ['cold', 'hot']:
t0 = time.time()
resp = engine.process(sources, targets, nprocs=nprocs)
t1 = time.time()
if temperature == 'hot':
dur_pyrocko = t1 - t0
del resp
ksources = map(to_kiwi_source, sources)
for temperature in ['cold', 'hot']:
t0 = time.time()
seis.make_misfits_for_sources(
ksources, show_progress=False)
t1 = time.time()
if temperature == 'hot':
dur_kiwi = t1 - t0
print 'pyrocko %-5s %5.2fs %5.1fx' % (
sourcetype, dur_pyrocko, 1.0)
print 'kiwi %-5s %5.2fs %5.1fx' % (
sourcetype, dur_kiwi, dur_pyrocko/dur_kiwi)
finally:
seis.close()
del seis
def test_timeseries(store,
source,
dim,
ntargets,
interpolation,
nthreads,
niter=1,
random_itmin=False,
random_nsamples=False):
source = gf.RectangularSource(lat=0.,
lon=0.,
depth=3 * km,
length=dim,
width=dim,
anchor='top')
targets = [
gf.Target(lat=rstate.uniform(), lon=rstate.uniform())
for x in range(ntargets)
]
dsource = source.discretize_basesource(store, targets[0])
source_coords_arr = dsource.coords5()
mts_arr = dsource.m6s
receiver_coords_arr = num.empty((len(targets), 5))
for itarget, target in enumerate(targets):
receiver = target.receiver(store)
receiver_coords_arr[itarget, :] = \
[receiver.lat, receiver.lon, receiver.north_shift,
receiver.east_shift, receiver.depth]
nsources = mts_arr.shape[0]
delays = num.zeros(nsources)
itmin = num.zeros(ntargets, dtype=num.int32)
nsamples = num.full(ntargets, -1, dtype=num.int32)
if random_itmin:
itmin = num.random.randint(-20,
5,
size=ntargets,
dtype=num.int32)
if random_nsamples:
nsamples = num.random.randint(10,
100,
size=ntargets,
dtype=num.int32)
@benchmark.labeled('calc_timeseries-%s' % interpolation)
def calc_timeseries():
return store_ext.store_calc_timeseries(
store.cstore, source_coords_arr, mts_arr, delays,
receiver_coords_arr, 'elastic10', interpolation, itmin,
nsamples, nthreads)
@benchmark.labeled('sum_timeseries-%s' % interpolation)
def sum_timeseries():
results = []
for itarget, target in enumerate(targets):
params = store_ext.make_sum_params(
store.cstore, source_coords_arr, mts_arr,
target.coords5[num.newaxis, :].copy(), 'elastic10',
interpolation, nthreads)
for weights, irecords in params:
d = num.zeros(irecords.shape[0], dtype=num.float32)
r = store_ext.store_sum(store.cstore, irecords, d,
weights, int(itmin[itarget]),
int(nsamples[itarget]))
results.append(r)
return results
for _ in range(niter):
res_calc = calc_timeseries()
for _ in range(niter):
res_sum = sum_timeseries()
for c, s in zip(res_calc, res_sum):
num.testing.assert_equal(c[0], s[0], verbose=True)
for cc, cs in zip(c[1:-1], s[1:]):
continue
assert cc == cs
def test_qseis_vs_ahfull(self):
random.seed(23)
vp = 5.8 * km
vs = 3.46 * km
mod = cake.LayeredModel.from_scanlines(
cake.read_nd_model_str('''
0. %(vp)g %(vs)g 2.6 1264. 600.
20. %(vp)g %(vs)g 2.6 1264. 600.'''.lstrip() % dict(vp=vp / km, vs=vs / km)))
store_id_qseis = 'homogeneous_qseis'
store_id_ahfull = 'homogeneous_ahfull'
qsconf = qseis.QSeisConfig()
qsconf.qseis_version = '2006a'
textra = 5.0
qsconf.time_region = (gf.meta.Timing('{vel:%g}-%g' %
(vp / km, textra)),
gf.meta.Timing('{vel:%g}+%g' %
(vs / km, textra)))
qsconf.cut = (gf.meta.Timing('{vel:%g}-%g' % (vp / km, textra)),
gf.meta.Timing('{vel:%g}+%g' % (vs / km, textra)))
qsconf.relevel_with_fade_in = True
qsconf.fade = (gf.meta.Timing('{vel:%g}-%g' % (vp / km, textra)),
gf.meta.Timing('{vel:%g}-%g' % (vp / km, 0.)),
gf.meta.Timing('{vel:%g}+%g' % (vs / km, 0.)),
gf.meta.Timing('{vel:%g}+%g' % (vs / km, textra)))
qsconf.wavelet_duration_samples = 0.001
qsconf.sw_flat_earth_transform = 0
qsconf.filter_surface_effects = 1
qsconf.wavenumber_sampling = 5.
qsconf.aliasing_suppression_factor = 0.01
sample_rate = 10.
config = gf.meta.ConfigTypeA(
id=store_id_qseis,
sample_rate=sample_rate,
receiver_depth=0. * km,
source_depth_min=1. * km,
source_depth_max=19 * km,
source_depth_delta=6. * km,
distance_min=2. * km,
distance_max=20 * km,
distance_delta=2 * km,
modelling_code_id='qseis.2006a',
earthmodel_1d=mod,
tabulated_phases=[
gf.meta.TPDef(id='begin', definition='p,P,p\\,P\\'),
gf.meta.TPDef(id='end', definition='s,S,s\\,S\\'),
])
config.validate()
store_dir_qseis = mkdtemp(prefix=store_id_qseis)
self.tempdirs.append(store_dir_qseis)
gf.store.Store.create_editables(store_dir_qseis,
config=config,
extra={'qseis': qsconf})
store = gf.store.Store(store_dir_qseis, 'r')
store.make_ttt()
store.close()
try:
qseis.build(store_dir_qseis, nworkers=1)
except qseis.QSeisError as e:
if str(e).find('could not start qseis') != -1:
logger.warn('qseis not installed; '
'skipping test_pyrocko_gf_vs_qseis')
return
else:
raise
config = gf.meta.ConfigTypeA(
id=store_id_ahfull,
sample_rate=sample_rate,
receiver_depth=0. * km,
source_depth_min=1. * km,
source_depth_max=19 * km,
source_depth_delta=6. * km,
distance_min=2. * km,
distance_max=20 * km,
distance_delta=2 * km,
modelling_code_id='ahfullgreen',
earthmodel_1d=mod,
tabulated_phases=[
gf.meta.TPDef(id='begin', definition='p,P,p\\,P\\'),
gf.meta.TPDef(id='end', definition='s,S,s\\,S\\'),
])
config.validate()
store_dir_ahfull = mkdtemp(prefix=store_id_qseis)
self.tempdirs.append(store_dir_ahfull)
gf.store.Store.create_editables(store_dir_ahfull, config=config)
store = gf.store.Store(store_dir_ahfull, 'r')
store.make_ttt()
store.close()
ahfullgreen.build(store_dir_ahfull, nworkers=1)
sdepth = rand(config.source_depth_min, config.source_depth_max)
sdepth = round(
(sdepth - config.source_depth_min)
/ config.source_depth_delta) * config.source_depth_delta \
+ config.source_depth_min
source = gf.MTSource(lat=0., lon=0., depth=sdepth)
source.m6 = tuple(rand(-1., 1.) for x in range(6))
for ii in range(5):
azi = random.random() * 365.
dist = rand(config.distance_min, config.distance_max)
dist = round(dist / config.distance_delta) * config.distance_delta
dnorth = dist * math.cos(azi * d2r)
deast = dist * math.sin(azi * d2r)
targets = []
for cha in 'rtz':
target = gf.Target(quantity='displacement',
codes=('', '0000', 'PG', cha),
north_shift=dnorth,
east_shift=deast,
depth=config.receiver_depth,
store_id=store_id_ahfull)
dist = source.distance_to(target)
azi, bazi = source.azibazi_to(target)
if cha == 'r':
target.azimuth = bazi + 180.
target.dip = 0.
elif cha == 't':
target.azimuth = bazi - 90.
target.dip = 0.
elif cha == 'z':
target.azimuth = 0.
target.dip = 90.
targets.append(target)
runner = qseis.QSeisRunner()
conf = qseis.QSeisConfigFull()
conf.qseis_version = '2006a'
conf.receiver_distances = [dist / km]
conf.receiver_azimuths = [azi]
conf.receiver_depth = config.receiver_depth / km
conf.source_depth = source.depth / km
distance_3d_max = math.sqrt(config.distance_max**2 +
(config.source_depth_max -
config.source_depth_min)**2)
nsamples = trace.nextpow2(
int(
math.ceil(distance_3d_max / vs * 2.0 + 2. * textra) *
config.sample_rate))
conf.time_start = -textra
conf.time_window = (nsamples - 1) / config.sample_rate
conf.time_reduction_velocity = 0.0
conf.nsamples = nsamples
conf.source_mech = qseis.QSeisSourceMechMT(mnn=source.mnn,
mee=source.mee,
mdd=source.mdd,
mne=source.mne,
mnd=source.mnd,
med=source.med)
conf.earthmodel_1d = mod
conf.sw_flat_earth_transform = 0
conf.filter_surface_effects = 1
conf.wavenumber_sampling = 10.
conf.wavelet_duration_samples = 0.001
conf.aliasing_suppression_factor = 0.01
conf.validate()
runner.run(conf)
trs = runner.get_traces()
for tr in trs:
pass
tr.lowpass(4, config.sample_rate / 8., demean=False)
tr.highpass(4, config.sample_rate / 80.)
engine = gf.LocalEngine(
store_dirs=[store_dir_ahfull, store_dir_qseis])
trs2 = engine.process(source, targets).pyrocko_traces()
for tr in trs2:
tr.shift(config.deltat)
tr.lowpass(4, config.sample_rate / 8., demean=False)
tr.highpass(4, config.sample_rate / 80.)
# trace.snuffle(trs+trs2)
tmin = store.t('{vel:%g}' %
(vp / km), source, target) - textra * 0.2
tmax = store.t('{vel:%g}' %
(vs / km), source, target) + textra * 0.2
for tr in trs + trs2:
tr.chop(tmin, tmax)
denom = 0.0
for cha in 'rtz':
t1 = g(trs, cha)
t2 = g(trs2, cha)
denom += num.sum(t1.ydata**2) + num.sum(t2.ydata**2)
ds = []
for cha in 'rtz':
t1 = g(trs, cha)
t2 = g(trs2, cha)
ds.append(2.0 * num.sum((t1.ydata - t2.ydata)**2) / denom)
ds = num.array(ds)
# if not num.all(ds < 0.05):
# trace.snuffle(trs+trs2)
assert num.all(ds < 0.05)
def test_regional(self):
engine = gf.get_engine()
store_id = 'crust2_mf'
try:
engine.get_store(store_id)
except gf.NoSuchStore:
logger.warn('GF Store %s not available - skipping test' % store_id)
return
nsources = 10
nstations = 10
print 'cache source channels par wallclock seismograms_per_second'
nprocs_max = multiprocessing.cpu_count()
for sourcetype, channels in [
['point', 'Z'],
['point', 'NEZ'],
['rect', 'Z'],
['rect', 'NEZ']]:
for nprocs in [1, 2, 4, 8, 16, 32]:
if nprocs > nprocs_max:
continue
sources = []
for isource in xrange(nsources):
m = pmt.MomentTensor.random_dc()
strike, dip, rake = map(float, m.both_strike_dip_rake()[0])
if sourcetype == 'point':
source = gf.DCSource(
north_shift=rand(-20.*km, 20*km),
east_shift=rand(-20.*km, 20*km),
depth=rand(10*km, 20*km),
strike=strike,
dip=dip,
rake=rake,
magnitude=rand(4.0, 5.0))
elif sourcetype == 'rect':
source = gf.RectangularSource(
north_shift=rand(-20.*km, 20*km),
east_shift=rand(-20.*km, 20*km),
depth=rand(10*km, 20*km),
length=10*km,
width=5*km,
nucleation_x=0.,
nucleation_y=-1.,
strike=strike,
dip=dip,
rake=rake,
magnitude=rand(4.0, 5.0))
else:
assert False
sources.append(source)
targets = []
for istation in xrange(nstations):
dist = rand(40.*km, 900*km)
azi = rand(-180., 180.)
north_shift = dist * math.cos(azi*d2r)
east_shift = dist * math.sin(azi*d2r)
for cha in channels:
target = gf.Target(
codes=('', 'S%04i' % istation, '', cha),
north_shift=north_shift,
east_shift=east_shift,
quantity='displacement',
interpolation='multilinear',
optimization='enable',
store_id=store_id)
targets.append(target)
ntraces = len(targets) * len(sources)
for temperature in ['cold', 'hot']:
t0 = time.time()
resp = engine.process(sources, targets, nprocs=nprocs)
# print resp.stats
t1 = time.time()
duration = t1 - t0
sps = ntraces / duration
if temperature == 'hot':
if nprocs == 1:
sps_ref = sps
print '%-5s %-6s %-8s %3i %9.3f %12.1f %12.1f' % (
temperature, sourcetype, channels, nprocs, t1-t0,
sps, sps/sps_ref)
del resp
def test_rect_source(self):
store = self.dummy_homogeneous_store()
depth = 10 * km
# shear
rect1 = gf.RectangularSource(depth=10 * km,
magnitude=5.0,
width=5 * km,
length=5 * km)
rect2 = gf.RectangularSource(
depth=depth,
slip=pmt.magnitude_to_moment(5.0) /
(5 * km * 5 * km *
store.config.earthmodel_1d.material(depth).shear_modulus()),
width=5 * km,
length=5 * km)
self.assertAlmostEqual(
rect1.get_magnitude(),
rect2.get_magnitude(store,
gf.Target(interpolation='nearest_neighbor')))
# tensile
rect3 = gf.RectangularSource(depth=depth,
magnitude=5.0,
width=5 * km,
length=5 * km,
opening_fraction=1.)
rect4 = gf.RectangularSource(
depth=depth,
slip=pmt.magnitude_to_moment(5.0) /
(5 * km * 5 * km *
store.config.earthmodel_1d.material(depth).bulk()),
width=5 * km,
length=5 * km,
opening_fraction=1.)
self.assertAlmostEqual(
rect3.get_magnitude(),
rect4.get_magnitude(store,
gf.Target(interpolation='nearest_neighbor')))
# mixed
of = -0.4
rect5 = gf.RectangularSource(depth=depth,
magnitude=5.0,
width=5 * km,
length=5 * km,
opening_fraction=of)
rect6 = gf.RectangularSource(
depth=depth,
slip=pmt.magnitude_to_moment(5.0) /
(5 * km * 5 * km *
(store.config.earthmodel_1d.material(depth).bulk() * abs(of) +
store.config.earthmodel_1d.material(depth).shear_modulus() *
(1 - abs(of)))),
width=5 * km,
length=5 * km,
opening_fraction=of)
self.assertAlmostEqual(
rect5.get_magnitude(),
rect6.get_magnitude(store,
gf.Target(interpolation='nearest_neighbor')))
source.m6 = tuple(rand(-1., 1.) for x in xrange(6))
for ii in xrange(5):
azi = random.random() * 365.
dist = rand(config.distance_min, config.distance_max)
dist = round(dist / config.distance_delta) * config.distance_delta
dnorth = dist * math.cos(azi * d2r)
deast = dist * math.sin(azi * d2r)
targets = []
for cha in 'rtz':
target = gf.Target(quantity='displacement',
codes=('', '0000', 'PG', cha),
north_shift=dnorth,
east_shift=deast,
depth=config.receiver_depth,
store_id=store_id_ahfull)
dist = source.distance_to(target)
azi, bazi = source.azibazi_to(target)
if cha == 'r':
target.azimuth = bazi + 180.
target.dip = 0.
elif cha == 't':
target.azimuth = bazi - 90.
target.dip = 0.
elif cha == 'z':
target.azimuth = 0.
target.dip = 90.
def get_plain_targets(self, engine, source):
d = dict((k, getattr(self, k)) for k in gf.Target.T.propnames)
return [gf.Target(**d)]
def model(
engine,
store_id,
magnitude_min, magnitude_max,
moment_tensor,
stress_drop_min, stress_drop_max,
rupture_velocity_min, rupture_velocity_max,
depth_min, depth_max,
distance_min, distance_max,
measures,
nsources=400,
nreceivers=1,
apply_source_response_via_spectra=True,
debug=True):
d2r = math.pi / 180.
components = set()
for measure in measures:
if not measure.components:
raise Exception('no components given in measurement rule')
for component in measure.components:
components.add(component)
components = list(components)
data = []
nerrors = 0
traces_debug = []
markers_debug = []
for isource in xrange(nsources):
magnitude = num.random.uniform(
magnitude_min, magnitude_max)
stress_drop = num.random.uniform(
stress_drop_min, stress_drop_max)
rupture_velocity = num.random.uniform(
rupture_velocity_min, rupture_velocity_max)
radius = (pmt.magnitude_to_moment(magnitude) * 7./16. /
stress_drop)**(1./3.)
duration = 1.5 * radius / rupture_velocity
if moment_tensor is None:
mt = pmt.MomentTensor.random_dc(magnitude=magnitude)
else:
mt = copy.deepcopy(moment_tensor)
mt.magnitude = magnitude
depth = num.random.uniform(depth_min, depth_max)
if apply_source_response_via_spectra:
source = gf.MTSource(
m6=mt.m6(),
depth=depth)
extra_responses = [
wmeasure.BruneResponse(duration=duration)]
else:
source = gf.MTSource(
m6=mt.m6(),
depth=depth,
stf=gf.HalfSinusoidSTF(effective_duration=duration))
extra_responses = []
for ireceiver in xrange(nreceivers):
angle = num.random.uniform(0., 360.)
distance = num.exp(num.random.uniform(
math.log(distance_min), math.log(distance_max)))
targets = []
for comp in components:
targets.append(gf.Target(
quantity='displacement',
codes=('', '%i_%i' % (isource, ireceiver), '', comp),
north_shift=distance*math.cos(d2r*angle),
east_shift=distance*math.sin(d2r*angle),
depth=0.,
store_id=store_id))
resp = engine.process(source, targets)
amps = []
for measure in measures:
comp_to_tt = {}
for (source, target, tr) in resp.iter_results():
comp_to_tt[target.codes[-1]] = (target, tr)
targets, trs = zip(*(
comp_to_tt[c] for c in measure.components))
try:
result = wmeasure.evaluate(
engine, source, targets, trs,
extra_responses,
debug=debug)
if not debug:
amps.append(result)
else:
amp, trs, marker = result
amps.append(amp)
traces_debug.extend(trs)
markers_debug.append(marker)
except wmeasure.AmplitudeMeasurementFailed:
nerrors += 1
amps.append(None)
data.append([magnitude, duration, depth, distance] + amps)
if debug:
trace.snuffle(traces_debug, markers=markers_debug)
return num.array(data, dtype=num.float)
def test_pyrocko_gf_vs_qseis(self):
random.seed(2017)
mod = cake.LayeredModel.from_scanlines(
cake.read_nd_model_str('''
0. 5.8 3.46 2.6 1264. 600.
20. 5.8 3.46 2.6 1264. 600.
20. 6.5 3.85 2.9 1283. 600.
35. 6.5 3.85 2.9 1283. 600.
mantle
35. 8.04 4.48 3.58 1449. 600.
77.5 8.045 4.49 3.5 1445. 600.
77.5 8.045 4.49 3.5 180.6 75.
120. 8.05 4.5 3.427 180. 75.
120. 8.05 4.5 3.427 182.6 76.06
165. 8.175 4.509 3.371 188.7 76.55
210. 8.301 4.518 3.324 201. 79.4
210. 8.3 4.52 3.321 336.9 133.3
410. 9.03 4.871 3.504 376.5 146.1
410. 9.36 5.08 3.929 414.1 162.7
660. 10.2 5.611 3.918 428.5 172.9
660. 10.79 5.965 4.229 1349. 549.6'''.lstrip()))
store_dir = mkdtemp(prefix='gfstore')
self.tempdirs.append(store_dir)
qsconf = qseis.QSeisConfig()
qsconf.qseis_version = '2006a'
qsconf.time_region = (gf.meta.Timing('0'), gf.meta.Timing('end+100'))
qsconf.cut = (gf.meta.Timing('0'), gf.meta.Timing('end+100'))
qsconf.wavelet_duration_samples = 0.001
qsconf.sw_flat_earth_transform = 0
config = gf.meta.ConfigTypeA(id='qseis_test',
sample_rate=0.25,
receiver_depth=0. * km,
source_depth_min=10 * km,
source_depth_max=10 * km,
source_depth_delta=1 * km,
distance_min=550 * km,
distance_max=560 * km,
distance_delta=1 * km,
modelling_code_id='qseis.2006a',
earthmodel_1d=mod,
tabulated_phases=[
gf.meta.TPDef(
id='begin',
definition='p,P,p\\,P\\'),
gf.meta.TPDef(id='end',
definition='2.5'),
])
config.validate()
gf.store.Store.create_editables(store_dir,
config=config,
extra={'qseis': qsconf})
store = gf.store.Store(store_dir, 'r')
store.make_ttt()
store.close()
try:
qseis.build(store_dir, nworkers=1)
except qseis.QSeisError as e:
if str(e).find('could not start qseis') != -1:
logger.warn('qseis not installed; '
'skipping test_pyrocko_gf_vs_qseis')
return
else:
raise
source = gf.MTSource(lat=0., lon=0., depth=10. * km)
source.m6 = tuple(random.random() * 2. - 1. for x in range(6))
azi = random.random() * 365.
dist = 553. * km
dnorth = dist * math.cos(azi * d2r)
deast = dist * math.sin(azi * d2r)
targets = []
for cha in 'rtz':
target = gf.Target(quantity='displacement',
codes=('', '0000', 'PG', cha),
north_shift=dnorth,
east_shift=deast,
depth=config.receiver_depth,
store_id='qseis_test')
dist = source.distance_to(target)
azi, bazi = source.azibazi_to(target)
if cha == 'r':
target.azimuth = bazi + 180.
target.dip = 0.
elif cha == 't':
target.azimuth = bazi - 90.
target.dip = 0.
elif cha == 'z':
target.azimuth = 0.
target.dip = 90.
targets.append(target)
runner = qseis.QSeisRunner()
conf = qseis.QSeisConfigFull()
conf.qseis_version = '2006a'
conf.receiver_distances = [dist / km]
conf.receiver_azimuths = [azi]
conf.source_depth = source.depth / km
conf.time_start = 0.0
conf.time_window = 508.
conf.time_reduction_velocity = 0.0
conf.nsamples = 128
conf.source_mech = qseis.QSeisSourceMechMT(mnn=source.mnn,
mee=source.mee,
mdd=source.mdd,
mne=source.mne,
mnd=source.mnd,
med=source.med)
conf.earthmodel_1d = mod
conf.sw_flat_earth_transform = 0
runner.run(conf)
trs = runner.get_traces()
for tr in trs:
tr.shift(-config.deltat)
tr.snap(interpolate=True)
tr.lowpass(4, 0.05)
tr.highpass(4, 0.01)
engine = gf.LocalEngine(store_dirs=[store_dir])
def process_wrap(nthreads=0):
@benchmark.labeled('pyrocko.gf.process (nthreads-%d)' % nthreads)
def process(nthreads):
return engine.process(source, targets, nthreads=nthreads)\
.pyrocko_traces()
return process(nthreads)
for nthreads in range(1, cpu_count() + 1):
trs2 = process_wrap(nthreads)
# print benchmark
for tr in trs2:
tr.snap(interpolate=True)
tr.lowpass(4, 0.05)
tr.highpass(4, 0.01)
# trace.snuffle(trs+trs2)
for cha in 'rtz':
t1 = g(trs, cha)
t2 = g(trs2, cha)
tmin = max(t1.tmin, t2.tmin)
tmax = min(t1.tmax, t2.tmax)
t1.chop(tmin, tmax)
t2.chop(tmin, tmax)
d = 2.0 * num.sum((t1.ydata - t2.ydata)**2) / \
(num.sum(t1.ydata**2) + num.sum(t2.ydata**2))
assert d < 0.05
def call(self):
'''Main work routine of the snuffling.'''
self.cleanup()
# get time range visible in viewer
viewer = self.get_viewer()
event = viewer.get_active_event()
if event:
event, stations = self.get_active_event_and_stations(
missing='warn')
else:
# event = model.Event(lat=self.lat, lon=self.lon)
event = model.Event(lat=0., lon=0.)
stations = []
stations = self.get_stations()
s2c = {}
for traces in self.chopper_selected_traces(fallback=True,
mode='visible'):
for tr in traces:
net, sta, loc, cha = tr.nslc_id
ns = net, sta
if ns not in s2c:
s2c[ns] = set()
s2c[ns].add((loc, cha))
if not stations:
stations = []
for (lat, lon) in [(5., 0.), (-5., 0.)]:
s = model.Station(station='(%g, %g)' % (lat, lon),
lat=lat,
lon=lon)
stations.append(s)
viewer.add_stations(stations)
for s in stations:
ns = s.nsl()[:2]
if ns not in s2c:
s2c[ns] = set()
for cha in 'NEZ':
s2c[ns].add(('', cha))
source = gf.RectangularSource(time=event.time + self.time,
lat=event.lat,
lon=event.lon,
north_shift=self.north_km * km,
east_shift=self.east_km * km,
depth=self.depth_km * km,
magnitude=self.magnitude,
strike=self.strike,
dip=self.dip,
rake=self.rake,
length=self.length,
width=self.width,
nucleation_x=self.nucleation_x,
velocity=self.velocity,
stf=self.get_stf())
source.regularize()
m = EventMarker(source.pyrocko_event())
self.add_marker(m)
targets = []
if self.store_id == '<not loaded yet>':
self.fail('Select a GF Store first')
for station in stations:
nsl = station.nsl()
if nsl[:2] not in s2c:
continue
for loc, cha in s2c[nsl[:2]]:
target = gf.Target(codes=(station.network, station.station,
loc + '-syn', cha),
quantity='displacement',
lat=station.lat,
lon=station.lon,
depth=station.depth,
store_id=self.store_id,
optimization='enable',
interpolation='nearest_neighbor')
_, bazi = source.azibazi_to(target)
if cha.endswith('T'):
dip = 0.
azi = bazi + 270.
elif cha.endswith('R'):
dip = 0.
azi = bazi + 180.
elif cha.endswith('1'):
dip = 0.
azi = 0.
elif cha.endswith('2'):
dip = 0.
azi = 90.
else:
dip = None
azi = None
target.azimuth = azi
target.dip = dip
targets.append(target)
req = gf.Request(sources=[source], targets=targets)
req.regularize()
try:
resp = self.get_engine().process(req)
except (gf.meta.OutOfBounds, gf.store_ext.StoreExtError) as e:
self.fail(e)
traces = resp.pyrocko_traces()
if self.waveform_type.startswith('Velocity'):
for tr in traces:
tr.set_ydata(num.diff(tr.ydata) / tr.deltat)
elif self.waveform_type.startswith('Acceleration'):
for tr in traces:
tr.set_ydata(num.diff(num.diff(tr.ydata)) / tr.deltat**2)
if self.waveform_type.endswith('[nm]') or \
self.waveform_type.endswith('[nm/s]') or \
self.waveform_type.endswith('[nm/s^2]'):
for tr in traces:
tr.set_ydata(tr.ydata * 1e9)
self.add_traces(traces)
