def test_create_default(self):
d = mkdtemp(prefix='gfstore')
self.tempdirs.append(d)
ahfullgreen.init(d, None)
store = gf.Store(d)
store.make_ttt()
ahfullgreen.build(d)
def setUpClass(cls):
cls.cwd = os.getcwd()
cls.serve_dir = tempfile.mkdtemp(prefix='pyrocko')
ahfullgreen.init(cls.serve_dir, None)
cls.store = store.Store(cls.serve_dir, 'r')
cls.store.make_ttt()
cls.store_id = cls.store.config.id
ahfullgreen.build(cls.serve_dir)
cls.dl_dir = tempfile.mkdtemp(prefix='pyrocko')
os.chdir(cls.dl_dir)
def setUpClass(cls):
cls.cwd = os.getcwd()
cls.serve_dir = tempfile.mkdtemp(prefix='pyrocko')
ahfullgreen.init(cls.serve_dir, None)
cls.store = store.Store(cls.serve_dir, 'r')
cls.store.make_ttt()
cls.store_id = cls.store.config.id
ahfullgreen.build(cls.serve_dir)
cls.dl_dir = tempfile.mkdtemp(prefix='pyrocko')
os.chdir(cls.dl_dir)
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_homogeneous_scenario(self, config_type_class, component_scheme,
discretized_source_class):
if config_type_class.short_type == 'C' \
or component_scheme.startswith('poro'):
assert False
store_id = 'homogeneous_%s_%s' % (config_type_class.short_type,
component_scheme)
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_type = config_type_class.short_type
params = dict(id=store_id,
sample_rate=1000.,
modelling_code_id='ahfullgreen',
component_scheme=component_scheme,
earthmodel_1d=mod)
if store_type in ('A', 'B'):
params.update(source_depth_min=1. * km,
source_depth_max=2. * km,
source_depth_delta=0.5 * km,
distance_min=4. * km,
distance_max=6. * km,
distance_delta=0.5 * km)
if store_type == 'A':
params.update(receiver_depth=3. * km)
if store_type == 'B':
params.update(receiver_depth_min=2. * km,
receiver_depth_max=3. * km,
receiver_depth_delta=0.5 * km)
if store_type == 'C':
params.update(source_depth_min=1. * km,
source_depth_max=2. * km,
source_depth_delta=0.5 * km,
source_east_shift_min=1. * km,
source_east_shift_max=2. * km,
source_east_shift_delta=0.5 * km,
source_north_shift_min=2. * km,
source_north_shift_max=3. * km,
source_north_shift_delta=0.5 * km)
config = config_type_class(**params)
config.validate()
store_dir = mkdtemp(prefix=store_id)
self.tempdirs.append(store_dir)
gf.store.Store.create_editables(store_dir, config=config)
store = gf.store.Store(store_dir, 'r')
store.make_ttt()
store.close()
fomosto_ahfullgreen.build(store_dir, nworkers=1)
store = gf.store.Store(store_dir, 'r')
dsource_type = discretized_source_class.__name__
params = {}
if dsource_type == 'DiscretizedMTSource':
params.update(m6s=num.array([[1., 2., 3., 4., 5., 6.],
[1., 2., 3., 4., 5., 6.]]))
elif dsource_type == 'DiscretizedExplosionSource':
params.update(m0s=num.array([2., 2.]))
elif dsource_type == 'DiscretizedSFSource':
params.update(forces=num.array([[1., 2., 3.], [1., 2., 3.]]))
elif dsource_type == 'DiscretizedPorePressureSource':
params.update(pp=num.array([3., 3.]))
snorth = 2.0 * km
seast = 2.0 * km
sdepth = 1.0 * km
rnorth = snorth + 3. * km
reast = seast + 4. * km
rdepth = 3.0 * km
t0 = 10.0 * store.config.deltat
dsource = discretized_source_class(
times=num.array([t0, t0 + 5. * store.config.deltat]),
north_shifts=num.array([snorth, snorth]),
east_shifts=num.array([seast, seast]),
depths=num.array([sdepth, sdepth]),
**params)
receiver = gf.Receiver(north_shift=rnorth,
east_shift=reast,
depth=rdepth)
components = gf.component_scheme_to_description[
component_scheme].provided_components
for seismogram in (store.seismogram, store.seismogram_old):
for interpolation in ('nearest_neighbor', 'multilinear'):
trs1 = []
for component, gtr in seismogram(
dsource, receiver, components,
interpolation=interpolation).iteritems():
tr = gtr.to_trace('', 'STA', '', component)
trs1.append(tr)
trs2 = make_traces_homogeneous(
dsource, receiver,
store.config.earthmodel_1d.require_homogeneous(),
store.config.deltat, '', 'STA', 'a')
tmin = max(tr.tmin for tr in trs1 + trs2)
tmax = min(tr.tmax for tr in trs1 + trs2)
for tr in trs1 + trs2:
tr.chop(tmin, tmax)
assert tr.data_len() > 2
trs1.sort(key=lambda tr: tr.channel)
trs2.sort(key=lambda tr: tr.channel)
denom = 0.0
for t1, t2 in zip(trs1, trs2):
assert t1.channel == t2.channel
denom += num.sum(t1.ydata**2) + num.sum(t2.ydata**2)
ds = []
for t1, t2 in zip(trs1, trs2):
ds.append(2.0 * num.sum((t1.ydata - t2.ydata)**2) / denom)
ds = num.array(ds)
if component_scheme == 'elastic8':
limit = 1e-2
else:
limit = 1e-6
if not num.all(ds < limit):
print ds
trace.snuffle(trs1 + trs2)
assert num.all(ds < limit)
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 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
def _test_homogeneous_scenario(
self,
config_type_class,
component_scheme,
discretized_source_class):
if config_type_class.short_type == 'C' \
or component_scheme.startswith('poro'):
assert False
store_id = 'homogeneous_%s_%s' % (
config_type_class.short_type, component_scheme)
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_type = config_type_class.short_type
params = dict(
id=store_id,
sample_rate=1000.,
modelling_code_id='ahfullgreen',
component_scheme=component_scheme,
earthmodel_1d=mod)
if store_type in ('A', 'B'):
params.update(
source_depth_min=1.*km,
source_depth_max=2.*km,
source_depth_delta=0.5*km,
distance_min=4.*km,
distance_max=6.*km,
distance_delta=0.5*km)
if store_type == 'A':
params.update(
receiver_depth=3.*km)
if store_type == 'B':
params.update(
receiver_depth_min=2.*km,
receiver_depth_max=3.*km,
receiver_depth_delta=0.5*km)
if store_type == 'C':
params.update(
source_depth_min=1.*km,
source_depth_max=2.*km,
source_depth_delta=0.5*km,
source_east_shift_min=1.*km,
source_east_shift_max=2.*km,
source_east_shift_delta=0.5*km,
source_north_shift_min=2.*km,
source_north_shift_max=3.*km,
source_north_shift_delta=0.5*km)
config = config_type_class(**params)
config.validate()
store_dir = mkdtemp(prefix=store_id)
self.tempdirs.append(store_dir)
gf.store.Store.create_editables(store_dir, config=config)
store = gf.store.Store(store_dir, 'r')
store.make_ttt()
store.close()
fomosto_ahfullgreen.build(store_dir, nworkers=1)
store = gf.store.Store(store_dir, 'r')
dsource_type = discretized_source_class.__name__
params = {}
if dsource_type == 'DiscretizedMTSource':
params.update(
m6s=num.array([
[1., 2., 3., 4., 5., 6.],
[1., 2., 3., 4., 5., 6.]]))
elif dsource_type == 'DiscretizedExplosionSource':
params.update(
m0s=num.array([2., 2.]))
elif dsource_type == 'DiscretizedSFSource':
params.update(
forces=num.array([[1., 2., 3.], [1., 2., 3.]]))
elif dsource_type == 'DiscretizedPorePressureSource':
params.update(
pp=num.array([3., 3.]))
snorth = 2.0*km
seast = 2.0*km
sdepth = 1.0*km
rnorth = snorth + 3.*km
reast = seast + 4.*km
rdepth = 3.0*km
t0 = 10.0 * store.config.deltat
dsource = discretized_source_class(
times=num.array([t0, t0+5.*store.config.deltat]),
north_shifts=num.array([snorth, snorth]),
east_shifts=num.array([seast, seast]),
depths=num.array([sdepth, sdepth]),
**params)
receiver = gf.Receiver(
north_shift=rnorth,
east_shift=reast,
depth=rdepth)
components = gf.component_scheme_to_description[
component_scheme].provided_components
for seismogram in (store.seismogram, store.seismogram_old):
for interpolation in ('nearest_neighbor', 'multilinear'):
trs1 = []
for component, gtr in seismogram(
dsource, receiver, components,
interpolation=interpolation).items():
tr = gtr.to_trace('', 'STA', '', component)
trs1.append(tr)
trs2 = _make_traces_homogeneous(
dsource, receiver,
store.config.earthmodel_1d.require_homogeneous(),
store.config.deltat, '', 'STA', 'a')
tmin = max(tr.tmin for tr in trs1+trs2)
tmax = min(tr.tmax for tr in trs1+trs2)
for tr in trs1+trs2:
tr.chop(tmin, tmax)
assert tr.data_len() > 2
trs1.sort(key=lambda tr: tr.channel)
trs2.sort(key=lambda tr: tr.channel)
denom = 0.0
for t1, t2 in zip(trs1, trs2):
assert t1.channel == t2.channel
denom += num.sum(t1.ydata**2) + num.sum(t2.ydata**2)
ds = []
for t1, t2 in zip(trs1, trs2):
ds.append(2.0 * num.sum((t1.ydata - t2.ydata)**2) / denom)
ds = num.array(ds)
if component_scheme == 'elastic8':
limit = 1e-2
else:
limit = 1e-6
if not num.all(ds < limit):
print(ds)
trace.snuffle(trs1+trs2)
assert num.all(ds < limit)
