def test_io_dpred(self):
pp_data = Data(survey=self.pp_survey, dobs=self.dobs)
dpdp_data = Data(survey=self.dpdp_survey, dobs=self.dobs)
filename = "dpred.dc"
# Test for pole-pole
write_dcip3d_ubc(
filename, pp_data, "secondary_potential", "dpred", format_type="general"
)
data_loaded = read_dcip3d_ubc(filename, "secondary_potential")
os.remove(filename)
A = np.c_[
self.pp_survey.locations_a,
self.pp_survey.locations_b,
self.pp_survey.locations_m,
self.pp_survey.locations_n,
self.dobs,
]
B = np.c_[
data_loaded.survey.locations_a,
data_loaded.survey.locations_b,
data_loaded.survey.locations_m,
data_loaded.survey.locations_n,
data_loaded.dobs,
]
passed = np.all(np.isclose(A, B))
self.assertTrue(passed, True)
# Test for dipole-dipole
write_dcipoctree_ubc(
filename, dpdp_data, "volt", "dpred", format_type="general"
)
data_loaded = read_dcipoctree_ubc(filename, "volt")
os.remove(filename)
A = np.c_[
self.dpdp_survey.locations_a,
self.dpdp_survey.locations_b,
self.dpdp_survey.locations_m,
self.dpdp_survey.locations_n,
self.dobs,
]
B = np.c_[
data_loaded.survey.locations_a,
data_loaded.survey.locations_b,
data_loaded.survey.locations_m,
data_loaded.survey.locations_n,
data_loaded.dobs,
]
passed = np.all(np.isclose(A, B))
self.assertTrue(passed, True)
print("PREDICTED DATA FILE IO FOR DCIP3D PASSED")
def test_io_dobs(self):
pp_data = Data(survey=self.pp_survey,
dobs=self.dobs,
standard_deviation=self.std)
dpdp_data = Data(survey=self.dpdp_survey,
dobs=self.dobs,
standard_deviation=self.std)
filename = "dobs.dc"
# Test for pole-pole
write_dcip3d_ubc(filename,
pp_data,
"secondary_potential",
"dobs",
format_type="general")
data_loaded = read_dcip3d_ubc(filename, "secondary_potential")
os.remove(filename)
A = np.c_[self.pp_survey.a_locations, self.pp_survey.b_locations,
self.pp_survey.m_locations, self.pp_survey.n_locations,
self.dobs, self.std, ]
B = np.c_[data_loaded.survey.a_locations,
data_loaded.survey.b_locations,
data_loaded.survey.m_locations,
data_loaded.survey.n_locations, data_loaded.dobs,
data_loaded.standard_deviation, ]
passed = np.all(np.isclose(A, B))
self.assertTrue(passed, True)
# Test for dipole-dipole
write_dcipoctree_ubc(filename,
dpdp_data,
"volt",
"dobs",
format_type="general")
data_loaded = read_dcipoctree_ubc(filename, "volt")
os.remove(filename)
A = np.c_[self.dpdp_survey.a_locations, self.dpdp_survey.b_locations,
self.dpdp_survey.m_locations, self.dpdp_survey.n_locations,
self.dobs, self.std, ]
B = np.c_[data_loaded.survey.a_locations,
data_loaded.survey.b_locations,
data_loaded.survey.m_locations,
data_loaded.survey.n_locations, data_loaded.dobs,
data_loaded.standard_deviation, ]
passed = np.all(np.isclose(A, B))
self.assertTrue(passed, True)
print("OBSERVATIONS FILE IO FOR DCIP3D PASSED")
def test_io_survey(self):
pp_data = Data(survey=self.pp_survey)
dpdp_data = Data(survey=self.dpdp_survey)
filename = "survey.dc"
# Test for pole-pole
write_dcip3d_ubc(filename,
pp_data,
"secondary_potential",
"survey",
format_type="general")
data_loaded = read_dcip3d_ubc(filename, "secondary_potential")
os.remove(filename)
A = np.c_[self.pp_survey.a_locations, self.pp_survey.b_locations,
self.pp_survey.m_locations, self.pp_survey.n_locations, ]
B = np.c_[data_loaded.survey.a_locations,
data_loaded.survey.b_locations,
data_loaded.survey.m_locations,
data_loaded.survey.n_locations, ]
passed = np.all(np.isclose(A, B))
self.assertTrue(passed, True)
# Test for dipole-dipole
write_dcipoctree_ubc(filename,
dpdp_data,
"volt",
"survey",
format_type="general")
data_loaded = read_dcipoctree_ubc(filename, "volt")
os.remove(filename)
A = np.c_[self.dpdp_survey.a_locations, self.dpdp_survey.b_locations,
self.dpdp_survey.m_locations, self.dpdp_survey.n_locations, ]
B = np.c_[data_loaded.survey.a_locations,
data_loaded.survey.b_locations,
data_loaded.survey.m_locations,
data_loaded.survey.n_locations, ]
passed = np.all(np.isclose(A, B))
self.assertTrue(passed, True)
print("SURVEY FILE IO FOR DCIP3D PASSED")
def test_io_dobs(self):
data_object = Data(survey=self.survey,
dobs=self.dobs,
standard_deviation=self.std)
filename = "dpred.mag"
write_magnetics_3d_ubc(filename, data_object)
data_loaded = read_magnetics_3d_ubc(filename)
os.remove(filename)
passed = np.all(
np.isclose(
np.c_[self.survey.receiver_locations, self.dobs, self.std],
np.c_[data_loaded.survey.receiver_locations, data_loaded.dobs,
data_loaded.standard_deviation, ],
))
self.assertTrue(passed, True)
passed = np.all(
np.isclose(
self.survey.source_field.parameters,
data_loaded.survey.source_field.parameters,
))
self.assertTrue(passed, True)
print("OBSERVED DATA FILE IO FOR MAG3D PASSED")
def test_io_dpred(self):
data_object = Data(survey=self.survey, dobs=self.dobs)
filename = "dpred.mag"
write_mag3d_ubc(filename, data_object)
data_loaded = read_mag3d_ubc(filename)
os.remove(filename)
passed = np.all(
np.isclose(
np.c_[self.survey.receiver_locations, self.dobs],
np.c_[data_loaded.survey.receiver_locations, data_loaded.dobs],
)
)
self.assertTrue(passed, True)
passed = np.all(
np.isclose(
self.survey.source_field.parameters,
data_loaded.survey.source_field.parameters,
)
)
self.assertTrue(passed, True)
print("PREDICTED DATA FILE IO FOR MAG3D PASSED")
def test_io_survey(self):
data_object = Data(survey=self.survey)
filename = "survey.mag"
write_mag3d_ubc(filename, data_object)
data_loaded = read_mag3d_ubc(filename)
os.remove(filename)
passed = np.all(
np.isclose(
self.survey.receiver_locations, data_loaded.survey.receiver_locations
)
)
self.assertTrue(passed, True)
passed = np.all(
np.isclose(
self.survey.source_field.parameters,
data_loaded.survey.source_field.parameters,
)
)
self.assertTrue(passed, True)
print("SURVEY FILE IO FOR MAG3D PASSED")
def test_io_dobs(self):
data_object = Data(
survey=self.survey, dobs=self.dobs, standard_deviation=self.std
)
filename = "dpred.gg"
write_gg3d_ubc(filename, data_object)
data_loaded = read_gg3d_ubc(filename)
os.remove(filename)
passed = np.all(
np.isclose(
self.survey.receiver_locations, data_loaded.survey.receiver_locations
)
)
self.assertTrue(passed, True)
passed = np.all(np.isclose(self.dobs, data_loaded.dobs))
self.assertTrue(passed, True)
passed = np.all(np.isclose(self.std, data_loaded.standard_deviation))
self.assertTrue(passed, True)
print("OBSERVED DATA FILE IO FOR GG3D PASSED")
def test_io_survey(self):
data_object = Data(survey=self.survey)
filename = "survey.grv"
write_gravity_3d_ubc(filename, data_object)
data_loaded = read_gravity_3d_ubc(filename)
os.remove(filename)
passed = np.all(
np.isclose(self.survey.receiver_locations,
data_loaded.survey.receiver_locations))
self.assertTrue(passed, True)
print("SURVEY FILE IO FOR GRAV3D PASSED")
def test_io_dpred(self):
data_object = Data(survey=self.survey, dobs=self.dobs)
filename = "dpred.grv"
write_gravity_3d_ubc(filename, data_object)
data_loaded = read_gravity_3d_ubc(filename)
os.remove(filename)
passed = np.all(
np.isclose(
np.c_[self.survey.receiver_locations, self.dobs],
np.c_[data_loaded.survey.receiver_locations, data_loaded.dobs],
))
self.assertTrue(passed, True)
print("PREDICTED DATA FILE IO FOR GRAV3D PASSED")
def run_inversion_cg(
self,
maxIter=60,
m0=0.0,
mref=0.0,
percentage=5,
floor=0.1,
chifact=1,
beta0_ratio=1.0,
coolingFactor=1,
coolingRate=1,
alpha_s=1.0,
alpha_x=1.0,
use_target=False,
):
sim = self.get_simulation()
data = Data(sim.survey,
dobs=self.data,
relative_error=percentage,
noise_floor=floor)
self.uncertainty = data.uncertainty
m0 = np.ones(self.M) * m0
mref = np.ones(self.M) * mref
reg = regularization.Tikhonov(self.mesh,
alpha_s=alpha_s,
alpha_x=alpha_x,
mref=mref)
dmis = data_misfit.L2DataMisfit(data=data, simulation=sim)
opt = optimization.InexactGaussNewton(maxIter=maxIter, maxIterCG=20)
opt.remember("xc")
opt.tolG = 1e-10
opt.eps = 1e-10
invProb = inverse_problem.BaseInvProblem(dmis, reg, opt)
save = directives.SaveOutputEveryIteration()
beta_schedule = directives.BetaSchedule(coolingFactor=coolingFactor,
coolingRate=coolingRate)
target = directives.TargetMisfit(chifact=chifact)
if use_target:
directs = [
directives.BetaEstimate_ByEig(beta0_ratio=beta0_ratio),
beta_schedule,
target,
save,
]
else:
directs = [
directives.BetaEstimate_ByEig(beta0_ratio=beta0_ratio),
beta_schedule,
save,
]
inv = inversion.BaseInversion(invProb, directiveList=directs)
mopt = inv.run(m0)
model = opt.recall("xc")
model.append(mopt)
pred = []
for m in model:
pred.append(sim.dpred(m))
return model, pred, save
