def test_errors(self):
mesh = emg3d.TensorMesh([[2, 2], [2, 2], [2, 2]], origin=(-1, -1, -1))
survey = emg3d.Survey(
sources=emg3d.TxElectricDipole((-1.5, 0, 0, 0, 0)),
receivers=emg3d.RxElectricPoint((1.5, 0, 0, 0, 0)),
frequencies=1.0,
relative_error=0.01,
)
sim_inp = {
'survey': survey,
'gridding': 'same',
'receiver_interpolation': 'linear'
}
# Anisotropic models.
simulation = simulations.Simulation(model=emg3d.Model(mesh, 1, 2, 3),
**sim_inp)
with pytest.raises(NotImplementedError, match='for isotropic models'):
simulation.gradient
# Model with electric permittivity.
simulation = simulations.Simulation(model=emg3d.Model(mesh,
epsilon_r=3),
**sim_inp)
with pytest.raises(NotImplementedError, match='for el. permittivity'):
simulation.gradient
# Model with magnetic permeability.
simulation = simulations.Simulation(model=emg3d.Model(
mesh, mu_r=np.ones(mesh.shape_cells) * np.pi),
**sim_inp)
with pytest.raises(NotImplementedError, match='for magn. permeabili'):
simulation.gradient
def test_rel_abs_rec(self):
# Sources
sources = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.TxElectricDipole, ([0, 100, 200], 0, 0, 0, 0))
# Abs and rel Receivers
a_e_rec = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.RxElectricPoint, (1000 + np.arange(3) * 100, 0, -100, 0, 0))
r_e_rec = emg3d.surveys.txrx_coordinates_to_dict(emg3d.RxElectricPoint,
(1000, 0, -100, 0, 0),
relative=True)
a_h_rec = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.RxMagneticPoint, (1000 + np.arange(3) * 100, 0, -100, 0, 0))
r_h_rec = emg3d.surveys.txrx_coordinates_to_dict(emg3d.RxMagneticPoint,
(1000, 0, -100, 0, 0),
relative=True)
receivers = emg3d.surveys.txrx_lists_to_dict(
[a_e_rec, r_e_rec, a_h_rec, r_h_rec])
# Frequencies
frequencies = (1.0)
survey = emg3d.Survey(sources,
receivers,
frequencies,
name='TestSurv',
noise_floor=1e-15,
relative_error=0.05)
# Create a simple grid and model
grid = emg3d.TensorMesh(
[np.ones(32) * 250,
np.ones(16) * 500,
np.ones(16) * 500], np.array([-1250, -1250, -2250]))
model = emg3d.Model(grid, 1)
# Create a simulation, compute all fields.
simulation = simulations.Simulation(survey,
model,
name='TestSim',
max_workers=1,
solver_opts={
'maxit': 1,
'verb': 0,
'plain': True
},
gridding='same')
simulation.compute()
# Relative receivers must be same as corresponding absolute receivers
assert_allclose(
[simulation.data.synthetic[i, i, 0].data for i in range(3)],
simulation.data.synthetic[:, 3, 0].data)
assert_allclose(
[simulation.data.synthetic[i, i + 4, 0].data for i in range(3)],
simulation.data.synthetic[:, 7, 0].data)
def test_factor(self):
sources = emg3d.TxElectricDipole((0, 3000, -950, 0, 0))
receivers = emg3d.RxElectricPoint((0, 3000, -1000, 0, 0))
# Adjusted x-domain.
survey = emg3d.Survey(
self.sources, receivers, self.frequencies, noise_floor=1e-15,
relative_error=0.05)
gdict = meshes.estimate_gridding_opts({}, self.model, survey)
assert_allclose(gdict['domain']['x'], (-800, 800))
# Adjusted x-domain.
survey = emg3d.Survey(
sources, self.receivers, self.frequencies, noise_floor=1e-15,
relative_error=0.05)
gdict = meshes.estimate_gridding_opts({}, self.model, survey)
assert_allclose(gdict['domain']['y'], (1500, 3500))
def test_misfit():
data = 1
syn = 5
rel_err = 0.05
sources = emg3d.TxElectricDipole((0, 0, 0, 0, 0))
receivers = emg3d.RxElectricPoint((5, 0, 0, 0, 0))
survey = emg3d.Survey(
sources=sources,
receivers=receivers,
frequencies=100,
data=np.zeros((1, 1, 1)) + data,
relative_error=0.05,
)
grid = emg3d.TensorMesh([np.ones(10) * 2, [2, 2], [2, 2]], (-10, -2, -2))
model = emg3d.Model(grid, 1)
simulation = simulations.Simulation(survey=survey, model=model)
field = emg3d.Field(grid, dtype=np.float64)
field.field += syn
simulation._dict_efield['TxED-1']['f-1'] = field
simulation.data['synthetic'] = simulation.data['observed'] * 0 + syn
misfit = 0.5 * ((syn - data) / (rel_err * data))**2
def dummy():
pass
simulation.compute = dummy # => switch of compute()
assert_allclose(simulation.misfit, misfit)
# Missing noise_floor / std.
survey = emg3d.Survey(sources, receivers, 100)
simulation = simulations.Simulation(survey=survey, model=model)
with pytest.raises(ValueError, match="Either `noise_floor` or"):
simulation.misfit
def test_dict_serialize_deserialize():
frequency = 1.0
grid = emg3d.TensorMesh([[2, 2], [3, 4], [0.5, 2]], (0, 0, 0))
field = emg3d.Field(grid)
model = emg3d.Model(grid, 1)
tx_e_d = emg3d.TxElectricDipole((0, 1000, 0, 0, -900, -950))
tx_m_d = emg3d.TxMagneticDipole([[0, 0, -900], [1000, 0, -950]])
tx_e_w = emg3d.TxElectricWire(([[0, 0, 0], [1, 1, 1], [1, 0, 1]]))
rx_e_p = emg3d.RxElectricPoint((0, 1000, -950, 0, 20))
rx_m_p = emg3d.RxMagneticPoint((0, 1000, -950, 20, 0))
data = {
'Grid': grid,
'Model': model,
'Field': field,
}
if xarray:
survey = emg3d.Survey(
emg3d.surveys.txrx_lists_to_dict([tx_e_d, tx_m_d, tx_e_w]),
emg3d.surveys.txrx_lists_to_dict([rx_e_p, rx_m_p]),
frequency
)
simulation = emg3d.Simulation(survey, model, gridding='same')
data['Survey'] = survey
data['Simulation'] = simulation
# Get everything into a serialized dict.
out = io._dict_serialize(data)
# Get everything back.
io._nonetype_to_none(out)
keep = deepcopy(out)
io._dict_deserialize(out)
assert data.keys() == out.keys()
assert out['Field'] == field
assert out['Grid'] == grid
assert out['Model'] == model
if xarray:
assert out['Survey'].sources == survey.sources
assert (out['Simulation'].survey.receivers ==
simulation.survey.receivers)
del keep['Grid']['hx']
with pytest.warns(UserWarning, match="Could not de-serialize"):
io._dict_deserialize(keep)
class TestRun:
# Default values for run-tests
args_dict = {
'config': '.',
'nproc': 1,
'forward': False,
'misfit': False,
'gradient': True,
'path': None,
'survey': 'survey.npz',
'model': 'model.npz',
'output': 'output.npz',
'save': None,
'load': None,
'verbosity': 0,
'dry_run': True,
}
if xarray is not None:
# Create a tiny dummy survey.
data = np.ones((1, 17, 1))
data[0, 8:11, 0] = np.nan
sources = emg3d.TxElectricDipole((4125, 4000, 4000, 0, 0))
receivers = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.RxElectricPoint,
(np.arange(17) * 250 + 2000, 4000, 3950, 0, 0))
survey = emg3d.Survey(
name='CLI Survey',
sources=sources,
receivers=receivers,
frequencies=1,
noise_floor=1e-15,
relative_error=0.05,
data=data,
)
# Create a dummy grid and model.
xx = np.ones(16) * 500
grid = emg3d.TensorMesh([xx, xx, xx], origin=np.array([0, 0, 0]))
model = emg3d.Model(grid, 1.)
def test_basic(self, tmpdir, capsys):
# Store survey and model.
self.survey.to_file(os.path.join(tmpdir, 'survey.npz'), verb=0)
emg3d.save(os.path.join(tmpdir, 'model.npz'),
model=self.model,
mesh=self.grid,
verb=0)
args_dict = self.args_dict.copy()
args_dict['path'] = tmpdir
args_dict['verbosity'] = -1
cli.run.simulation(args_dict)
args_dict = self.args_dict.copy()
args_dict['path'] = tmpdir
args_dict['config'] = 'bla'
args_dict['verbosity'] = 2
_, _ = capsys.readouterr()
with pytest.raises(SystemExit) as e:
cli.run.simulation(args_dict)
assert e.type == SystemExit
assert "* ERROR :: Config file not found: " in e.value.code
# Missing survey.
args_dict = self.args_dict.copy()
args_dict['path'] = tmpdir
args_dict['survey'] = 'wrong'
with pytest.raises(SystemExit) as e:
cli.run.simulation(args_dict)
assert e.type == SystemExit
assert "* ERROR :: Survey file not found: " in e.value.code
assert "wrong" in e.value.code
# Missing model.
args_dict = self.args_dict.copy()
args_dict['path'] = tmpdir
args_dict['model'] = 'phantommodel'
with pytest.raises(SystemExit) as e:
cli.run.simulation(args_dict)
assert e.type == SystemExit
assert "* ERROR :: Model file not found: " in e.value.code
assert "phantommodel" in e.value.code
# Missing output directory.
args_dict = self.args_dict.copy()
args_dict['path'] = tmpdir
args_dict['output'] = join('phantom', 'output', 'dir.npz')
args_dict['save'] = join('phantom', 'simulation', 'save.npz')
with pytest.raises(SystemExit) as e:
cli.run.simulation(args_dict)
assert e.type == SystemExit
assert "* ERROR :: Output directory does not exist: " in e.value.code
assert join("phantom", "output") in e.value.code
assert join("phantom", "simulation") in e.value.code
def test_run(self, tmpdir, capsys):
# Write a config file.
config = os.path.join(tmpdir, 'emg3d.cfg')
with open(config, 'w') as f:
f.write("[files]\n")
f.write("save=mysim.npz\n")
f.write("[solver_opts]\n")
f.write("sslsolver=False\n")
f.write("semicoarsening=False\n")
f.write("linerelaxation=False\n")
f.write("maxit=1\n")
# Store survey and model.
self.survey.to_file(os.path.join(tmpdir, 'survey.npz'), verb=1)
emg3d.save(os.path.join(tmpdir, 'model.npz'),
model=self.model,
mesh=self.grid,
verb=1)
# Run a dry run (to output.npz).
args_dict = self.args_dict.copy()
args_dict['config'] = os.path.join(tmpdir, 'emg3d.cfg')
args_dict['path'] = tmpdir
cli.run.simulation(args_dict)
# Actually run one iteration (to output2.npz).
args_dict = self.args_dict.copy()
args_dict['config'] = os.path.join(tmpdir, 'emg3d.cfg')
args_dict['path'] = tmpdir
args_dict['dry_run'] = False
args_dict['output'] = 'output2.npz'
cli.run.simulation(args_dict)
# Ensure dry_run returns same shaped data as the real thing.
res1 = emg3d.load(os.path.join(tmpdir, 'output.npz'))
res2 = emg3d.load(os.path.join(tmpdir, 'output2.npz'))
assert_allclose(res1['data'].shape, res2['data'].shape)
assert_allclose(res1['misfit'].shape, res2['misfit'].shape)
assert_allclose(res1['gradient'].shape, res2['gradient'].shape)
# Assert we can load the simulation
emg3d.Simulation.from_file(os.path.join(tmpdir, 'mysim.npz'))
assert res1['n_observations'] == np.isfinite(self.data).sum()
assert res2['n_observations'] == np.isfinite(self.data).sum()
# Actually run one iteration (to output2.npz).
args_dict = self.args_dict.copy()
args_dict['config'] = os.path.join(tmpdir, 'emg3d.cfg')
args_dict['path'] = tmpdir
args_dict['forward'] = True
args_dict['gradient'] = False
args_dict['dry_run'] = False
args_dict['output'] = 'output3.npz'
cli.run.simulation(args_dict)
res3 = emg3d.load(os.path.join(tmpdir, 'output3.npz'))
assert 'misfit' not in res3
assert 'gradient' not in res3
# Redo for misfit, loading existing simulation.
args_dict = self.args_dict.copy()
args_dict['config'] = os.path.join(tmpdir, 'emg3d.cfg')
args_dict['path'] = tmpdir
args_dict['forward'] = False
args_dict['misfit'] = True
args_dict['gradient'] = False
args_dict['dry_run'] = False
args_dict['load'] = 'mysim.npz'
args_dict['output'] = 'output3.npz'
cli.run.simulation(args_dict)
res3 = emg3d.load(os.path.join(tmpdir, 'output3.npz'))
assert 'misfit' in res3
assert 'gradient' not in res3
def test_data(self, tmpdir, capsys):
# Write a config file; remove_empty=False (default)
config = os.path.join(tmpdir, 'emg3d.cfg')
with open(config, 'w') as f:
f.write("[data]\n")
f.write("sources=TxED-1\n")
f.write("receivers=RxEP-05, RxEP-10, RxEP-02, RxEP-12, RxEP-06\n")
f.write("frequencies=f-1")
# Store survey and model.
self.survey.to_file(os.path.join(tmpdir, 'survey.npz'), verb=1)
emg3d.save(os.path.join(tmpdir, 'model.npz'),
model=self.model,
mesh=self.grid,
verb=1)
# Run a dry run (to output.npz).
args_dict = self.args_dict.copy()
args_dict['config'] = os.path.join(tmpdir, 'emg3d.cfg')
args_dict['path'] = tmpdir
cli.run.simulation(args_dict.copy())
# Ensure dry_run returns same shaped data as the real thing.
res = emg3d.load(os.path.join(tmpdir, 'output.npz'))
assert_allclose(res['data'].shape, (1, 5, 1))
assert res['n_observations'] == 4
# Append config file with: remove_empty=True
with open(config, 'a') as f:
f.write("\nremove_empty=True")
# Run a dry run (to output.npz).
cli.run.simulation(args_dict)
# Ensure dry_run returns same shaped data as the real thing.
res = emg3d.load(os.path.join(tmpdir, 'output.npz'))
assert_allclose(res['data'].shape, (1, 4, 1))
assert res['n_observations'] == 4
class TestGradient:
if xarray is not None:
# Create a simple mesh.
hx = np.ones(64) * 100
mesh = emg3d.TensorMesh([hx, hx, hx], origin=[0, 0, 0])
# Define a simple survey, including 1 el. & 1 magn. receiver
survey = emg3d.Survey(
sources=emg3d.TxElectricDipole((1680, 3220, 3210, 20, 5)),
receivers=[
emg3d.RxElectricPoint((4751, 3280, 3220, 33, 14)),
emg3d.RxMagneticPoint((4758, 3230, 3250, 15, 70)),
],
frequencies=1.0,
relative_error=0.01,
)
# Background Model
con_init = np.ones(mesh.shape_cells)
# Target Model 1: One Block
con_true = np.ones(mesh.shape_cells)
con_true[27:37, 27:37, 15:25] = 0.001
model_init = emg3d.Model(mesh, con_init, mapping='Conductivity')
model_true = emg3d.Model(mesh, con_true, mapping='Conductivity')
# mesh.plot_3d_slicer(con_true) # For debug / QC, needs discretize
sim_inp = {
'survey': survey,
'solver_opts': {
'plain': True,
'tol': 5e-5
}, # Red. tol 4 speed
'max_workers': 1,
'gridding': 'same',
'verb': 0,
'receiver_interpolation': 'linear',
}
# Compute data (pre-computed and passed to Survey above)
sim_data = simulations.Simulation(model=model_true, **sim_inp)
sim_data.compute(observed=True)
def test_errors(self):
mesh = emg3d.TensorMesh([[2, 2], [2, 2], [2, 2]], origin=(-1, -1, -1))
survey = emg3d.Survey(
sources=emg3d.TxElectricDipole((-1.5, 0, 0, 0, 0)),
receivers=emg3d.RxElectricPoint((1.5, 0, 0, 0, 0)),
frequencies=1.0,
relative_error=0.01,
)
sim_inp = {
'survey': survey,
'gridding': 'same',
'receiver_interpolation': 'linear'
}
# Anisotropic models.
simulation = simulations.Simulation(model=emg3d.Model(mesh, 1, 2, 3),
**sim_inp)
with pytest.raises(NotImplementedError, match='for isotropic models'):
simulation.gradient
# Model with electric permittivity.
simulation = simulations.Simulation(model=emg3d.Model(mesh,
epsilon_r=3),
**sim_inp)
with pytest.raises(NotImplementedError, match='for el. permittivity'):
simulation.gradient
# Model with magnetic permeability.
simulation = simulations.Simulation(model=emg3d.Model(
mesh, mu_r=np.ones(mesh.shape_cells) * np.pi),
**sim_inp)
with pytest.raises(NotImplementedError, match='for magn. permeabili'):
simulation.gradient
def test_as_vs_fd_gradient(self, capsys):
# Compute adjoint state misfit and gradient
sim = simulations.Simulation(model=self.model_init, **self.sim_inp)
data_misfit = sim.misfit
grad = sim.gradient
# For Debug / QC, needs discretize
# from matplotlib.colors import LogNorm, SymLogNorm
# mesh.plot_3d_slicer(
# grad.ravel('F'),
# pcolor_opts={
# 'cmap': 'RdBu_r',
# 'norm': SymLogNorm(linthresh=1e-2, base=10,
# vmin=-1e1, vmax=1e1)}
# )
# We test a random cell from the inline xz slice, where the grad > 3.
#
# The NRMSD is (should) be below 1 %. However, (a) close to the
# boundary, (b) in regions where the gradient is almost zero, and (c)
# in regions where the gradient changes sign the NRMSD can become
# large. This is mainly due to numerics, our coarse mesh, and the
# reduced tolerance (which we reduced for speed).
iy = 32
indices = np.argwhere(abs(grad[:, iy, :]) > 3)
ix, iz = indices[np.random.randint(indices.shape[0])]
nrmsd = alternatives.fd_vs_as_gradient((ix, iy, iz), self.model_init,
grad, data_misfit, self.sim_inp)
assert nrmsd < 0.3
@pytest.mark.skipif(discretize is None, reason="discretize not installed.")
@pytest.mark.skipif(h5py is None, reason="h5py not installed.")
def test_adjoint(self, tmpdir):
sim = simulations.Simulation(model=self.model_init,
file_dir=str(tmpdir),
**self.sim_inp)
v = np.random.rand(self.mesh.n_cells).reshape(self.mesh.shape_cells)
w = np.random.rand(self.survey.size).reshape(self.survey.shape)
wtJv = np.vdot(w, sim.jvec(v)).real
vtJtw = np.vdot(v, sim.jtvec(w).ravel('F'))
assert abs(wtJv - vtJtw) < 1e-10
@pytest.mark.skipif(discretize is None, reason="discretize not installed.")
@pytest.mark.skipif(h5py is None, reason="h5py not installed.")
def test_misfit(self, tmpdir):
sim = simulations.Simulation(model=self.model_init,
file_dir=str(tmpdir),
**self.sim_inp)
m0 = 2 * sim.model.property_x
def func2(x):
sim.model.property_x[...] = m0
return sim.jvec(x)
def func1(x):
sim.model.property_x[...] = x.reshape(sim.model.grid.shape_cells)
sim.clean('computed')
# Quick test that clean() removes the files
assert len(os.listdir(tmpdir)) == 0
sim.compute()
return sim.data.synthetic.data, func2
assert discretize.tests.check_derivative(
func1,
m0,
plotIt=False,
num=3,
)
def test_print_solver(self, capsys):
grid = emg3d.TensorMesh(h=[[(25, 10, -1.04), (25, 28), (25, 10, 1.04)],
[(50, 8, -1.03), (50, 16), (50, 8, 1.03)],
[(30, 8, -1.05), (30, 16), (30, 8, 1.05)]],
origin='CCC')
model = emg3d.Model(grid,
property_x=1.5,
property_y=1.8,
property_z=3.3,
mapping='Resistivity')
sources = emg3d.TxElectricDipole((0, 0, 0, 0, 0))
receivers = [
emg3d.RxElectricPoint((x, 0, 0, 0, 0)) for x in [-10000, 10000]
]
survey = emg3d.Survey(
name='Test',
sources=sources,
receivers=receivers,
frequencies=1.0,
noise_floor=1e-15,
relative_error=0.05,
)
inp = {
'name': 'Test',
'survey': survey,
'model': model,
'gridding': 'same'
}
sol = {
'sslsolver': False,
'semicoarsening': False,
'linerelaxation': False,
'maxit': 1
}
# Errors but verb=-1.
_, _ = capsys.readouterr() # empty
simulation = simulations.Simulation(verb=-1, **inp, solver_opts=sol)
simulation.compute()
out, _ = capsys.readouterr()
assert out == ""
# Errors with verb=0.
out = simulation.print_solver_info('efield', verb=0, return_info=True)
assert "= Source TxED-1; Frequency 1.0 Hz = MAX. ITERATION REAC" in out
# Errors with verb=1.
_, _ = capsys.readouterr() # empty
simulation.print_solver_info('efield', verb=1)
out, _ = capsys.readouterr()
assert "= Source TxED-1; Frequency 1.0 Hz = 2.6e-02; 1; 0:00:" in out
# No errors; solver-verb 3.
simulation = simulations.Simulation(verb=1,
**inp,
solver_opts={'verb': 3})
simulation.compute()
out, _ = capsys.readouterr()
assert 'MG-cycle' in out
assert 'CONVERGED' in out
# No errors; solver-verb 0.
simulation = simulations.Simulation(verb=1,
**inp,
solver_opts={'verb': 0})
simulation.compute()
out, _ = capsys.readouterr()
assert "= Source TxED-1; Frequency 1.0 Hz = CONVERGED" in out
# Two sources, only compute 1, assure printing works.
sources = [emg3d.TxElectricDipole((x, 0, 0, 0, 0)) for x in [0, 10]]
survey = emg3d.Survey(
name='Test',
sources=sources,
receivers=receivers,
frequencies=1.0,
noise_floor=1e-15,
relative_error=0.05,
)
inp = {
'name': 'Test',
'survey': survey,
'model': model,
'gridding': 'same'
}
simulation = simulations.Simulation(**inp, solver_opts={'verb': 0})
_ = simulation.get_efield('TxED-2', 'f-1')
simulation.print_solver_info(verb=1)
out, _ = capsys.readouterr()
assert "= Source TxED-2; Frequency 1.0 Hz = CONVERGED" in out
def test_simulation_automatic(self, capsys):
# Create a simple survey
sources = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.TxElectricDipole, (0, [1000, 3000, 5000], -950, 0, 0))
receivers = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.RxElectricPoint,
([-3000, 0, 3000], [0, 3000, 6000], -1000, 0, 0))
frequencies = (0.1, 1.0, 10.0)
survey = emg3d.Survey(sources,
receivers,
frequencies,
name='Test',
noise_floor=1e-15,
relative_error=0.05)
# Create a simple grid and model
grid = emg3d.TensorMesh(
[np.ones(32) * 250,
np.ones(16) * 500,
np.ones(4) * 500], np.array([-1250, -1250, -2250]))
model = emg3d.Model(grid, 1)
# Create a simulation, compute all fields.
inp = {
'survey': survey,
'model': model,
'gridding_opts': {
'expand': [1, 0.5],
'seasurface': 0,
'verb': 1
}
}
b_sim = simulations.Simulation(name='both', gridding='both', **inp)
f_sim = simulations.Simulation(name='freq',
gridding='frequency',
**inp)
t_sim = simulations.Simulation(name='src', gridding='source', **inp)
s_sim = simulations.Simulation(name='single', gridding='single', **inp)
# Quick repr test.
assert " 24 x 24 (13,824) - 160 x 160 x 96 (2,457," in b_sim.__repr__()
assert " 24 x 24 (13,824) - 160 x 160 x 96 (2,457," in f_sim.__repr__()
assert "Source-dependent grids; 64 x 64 x 40 (163," in t_sim.__repr__()
assert "ources and frequencies; 64 x 64 x 40 (163," in s_sim.__repr__()
# Quick print_grid test:
_, _ = capsys.readouterr() # empty
b_sim.print_grid_info()
out, _ = capsys.readouterr()
assert "= Source: TxED-1; Frequency: 10.0 Hz =" in out
assert "== GRIDDING IN X ==" in out
assert b_sim.get_grid('TxED-1', 1.0).__repr__() in out
_, _ = capsys.readouterr() # empty
out = f_sim.print_grid_info(return_info=True)
out2, _ = capsys.readouterr()
assert out2 == ""
assert "= Source: all" in out
assert "== GRIDDING IN X ==" in out
assert f_sim.get_grid('TxED-3', 1.0).__repr__() in out
t_sim.print_grid_info()
out, _ = capsys.readouterr()
assert "; Frequency: all" in out
assert "== GRIDDING IN X ==" in out
assert t_sim.get_grid('TxED-1', 10.0).__repr__() in out
_, _ = capsys.readouterr() # empty
out = s_sim.print_grid_info(return_info=True)
out2, _ = capsys.readouterr()
assert out2 == ""
assert "= Source: all; Frequency: all =" in out
assert "== GRIDDING IN X ==" in out
assert s_sim.get_grid('TxED-3', 0.1).__repr__() in out
assert s_sim.print_grid_info(verb=-1) is None
# Grids: Middle source / middle frequency should be the same in all.
assert f_sim.get_grid('TxED-2', 1.0) == t_sim.get_grid('TxED-2', 1.0)
assert f_sim.get_grid('TxED-2', 1.0) == s_sim.get_grid('TxED-2', 1.0)
assert f_sim.get_grid('TxED-2', 1.0) == b_sim.get_grid('TxED-2', 1.0)
assert f_sim.get_model('TxED-2', 1.0) == t_sim.get_model('TxED-2', 1.0)
assert f_sim.get_model('TxED-2', 1.0) == s_sim.get_model('TxED-2', 1.0)
assert f_sim.get_model('TxED-2', 1.0) == b_sim.get_model('TxED-2', 1.0)
# Copy:
f_sim_copy = f_sim.copy()
assert (f_sim.get_grid('TxED-1',
1.0) == f_sim_copy.get_grid('TxED-1', 1.0))
assert 'expand' not in f_sim.gridding_opts.keys()
assert 'expand' not in f_sim_copy.gridding_opts.keys()
s_sim_copy = s_sim.copy()
assert (s_sim.get_grid('TxED-1',
1.0) == s_sim_copy.get_grid('TxED-1', 1.0))
assert 'expand' not in s_sim.gridding_opts.keys()
assert 'expand' not in s_sim_copy.gridding_opts.keys()
t_sim_copy = t_sim.copy()
assert (t_sim.get_grid('TxED-1',
1.0) == t_sim_copy.get_grid('TxED-1', 1.0))
assert 'expand' not in t_sim.gridding_opts.keys()
assert 'expand' not in t_sim_copy.gridding_opts.keys()
class TestSimulation():
if xarray is not None:
# Create a simple survey
# Sources: 1 Electric Dipole, 1 Magnetic Dipole, 1 Electric Wire.
s1 = emg3d.TxElectricDipole((0, 1000, -950, 0, 0))
s2 = emg3d.TxMagneticDipole((0, 3000, -950, 90, 0))
s3 = emg3d.TxElectricWire(([0, 4900, -950], [-20, 5000,
-950], [20, 5100, -950]))
sources = emg3d.surveys.txrx_lists_to_dict([s1, s2, s3])
# Receivers: 1 Electric Point, 1 Magnetic Point
e_rec = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.RxElectricPoint, (np.arange(6) * 1000, 0, -1000, 0, 0))
m_rec = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.RxMagneticPoint, (np.arange(6) * 1000, 0, -1000, 90, 0))
receivers = emg3d.surveys.txrx_lists_to_dict([e_rec, m_rec])
# Frequencies
frequencies = (1.0, 2.0)
survey = emg3d.Survey(sources,
receivers,
frequencies,
name='TestSurv',
noise_floor=1e-15,
relative_error=0.05)
# Create a simple grid and model
grid = emg3d.TensorMesh(
[np.ones(32) * 250,
np.ones(16) * 500,
np.ones(16) * 500], np.array([-1250, -1250, -2250]))
model = emg3d.Model(grid, 1)
# Create a simulation, compute all fields.
simulation = simulations.Simulation(survey,
model,
name='TestSim',
max_workers=1,
solver_opts={
'maxit': 1,
'verb': 0,
'sslsolver': False,
'linerelaxation': False,
'semicoarsening': False
},
gridding='same')
# Do first one single and then all together.
simulation.get_efield('TxED-1', 'f-1')
simulation.compute(observed=True, min_offset=1100)
def test_same(self):
assert self.simulation.get_model('TxMD-2', 'f-1') == self.model
assert self.simulation.get_grid('TxEW-3', 1.0) == self.grid
def test_fields(self, capsys):
# Check sfield
sfield = emg3d.get_source_field(self.grid,
self.survey.sources['TxEW-3'],
frequency=1.0)
# Check efield
efield, info = emg3d.solve(self.model, sfield,
**self.simulation.solver_opts)
assert self.simulation.get_efield('TxEW-3', 'f-1') == efield
# See a single one
self.simulation._dict_efield['TxEW-3'][1.0] = None
_, _ = capsys.readouterr()
self.simulation.get_efield('TxEW-3', 1.0)
info = self.simulation.get_efield_info('TxEW-3', 1.0)
assert 'MAX. ITERATION REACHED, NOT CONVERGED' in info['exit_message']
# Check hfield
hfield = emg3d.get_magnetic_field(self.model, efield)
assert self.simulation.get_hfield('TxEW-3', 1.0) == hfield
s_hfield = self.simulation.get_hfield('TxEW-3', 1.0)
assert s_hfield == hfield
assert_allclose(
self.simulation._dict_efield_info['TxEW-3']['f-1']['abs_error'],
info['abs_error'])
assert_allclose(
self.simulation._dict_efield_info['TxEW-3']['f-1']['rel_error'],
info['rel_error'])
exit = self.simulation._dict_efield_info['TxEW-3']['f-1']['exit']
assert exit == info['exit'] == 1
# First hfield, ensure efield/hfield get computed.
sim = self.simulation.copy(what='all')
sim._dict_efield['TxEW-3']['f-1'] = None
sim.get_hfield('TxEW-3', 'f-1')
assert sim._dict_efield['TxEW-3']['f-1'] is not None
def test_responses(self):
# Check min_offset were switched-off
assert_allclose(self.simulation.data.observed[0, 0, 0].data, np.nan)
assert_allclose(self.simulation.data.observed[0, 6, 0].data, np.nan)
# Get efield responses
e_resp = self.simulation.get_efield('TxMD-2', 1.0).get_receiver(
self.survey.receivers.values())
assert_allclose(self.simulation.data.synthetic[1, :6, 0].data,
e_resp[:6],
atol=1e-16)
# Get hfield responses
m_resp = self.simulation.get_hfield('TxMD-2', 1.0).get_receiver(
self.survey.receivers.values())
assert_allclose(self.simulation.data.synthetic[1, 6:, 0].data,
m_resp[6:],
atol=1e-16)
def test_errors(self):
with pytest.raises(TypeError, match='Unexpected '):
simulations.Simulation(self.survey,
self.model,
unknown=True,
name='Test2')
# gridding='same' with gridding_opts.
with pytest.raises(TypeError, match="`gridding_opts` is not permitt"):
simulations.Simulation(self.survey,
self.model,
name='Test',
gridding='same',
gridding_opts={'bummer': True})
# expand without seasurface
with pytest.raises(KeyError, match="is required if"):
simulations.Simulation(self.survey,
self.model,
name='Test',
gridding='single',
gridding_opts={'expand': [1, 2]})
def test_reprs(self):
test = self.simulation.__repr__()
assert "Simulation «TestSim»" in test
assert "Survey «TestSurv»: 3 sources; 12 receivers; 2 frequenc" in test
assert "Model: resistivity; isotropic; 32 x 16 x 16 (8,192)" in test
assert "Gridding: Same grid as for model" in test
test = self.simulation._repr_html_()
assert "Simulation «TestSim»" in test
assert "Survey «TestSurv»: 3 sources; 12 receivers; 2" in test
assert "Model: resistivity; isotropic; 32 x 16 x 16 (8,192)" in test
assert "Gridding: Same grid as for model" in test
def test_copy(self, tmpdir):
with pytest.raises(TypeError, match="Unrecognized `what`: nothing"):
self.simulation.copy('nothing')
sim2 = self.simulation.copy()
assert self.simulation.name == sim2.name
assert self.simulation.survey.sources == sim2.survey.sources
assert_allclose(
self.simulation.get_efield('TxED-1', 1.0).field,
sim2.get_efield('TxED-1', 1.0).field)
# Also check to_file()/from_file().
sim_dict = self.simulation.to_dict('all')
sim2 = simulations.Simulation.from_dict(sim_dict.copy())
assert self.simulation.name == sim2.name
assert self.simulation.survey.name == sim2.survey.name
assert self.simulation.max_workers == sim2.max_workers
assert self.simulation.gridding == sim2.gridding
assert self.simulation.model == sim2.model
del sim_dict['survey']
with pytest.raises(KeyError, match="'survey'"):
simulations.Simulation.from_dict(sim_dict)
# Also check to_file()/from_file().
self.simulation.to_file(tmpdir + '/test.npz', what='all')
sim2 = simulations.Simulation.from_file(tmpdir + '/test.npz')
assert self.simulation.name == sim2.name
assert self.simulation.survey.name == sim2.survey.name
assert self.simulation.max_workers == sim2.max_workers
assert self.simulation.gridding == sim2.gridding
assert self.simulation.model == sim2.model
sim9 = simulations.Simulation.from_file(tmpdir + '/test.npz', verb=-1)
assert sim2.name == sim9[0].name
assert 'Data loaded from' in sim9[1]
# Clean and ensure it is empty
sim3 = self.simulation.copy()
sim3.clean('all')
assert sim3._dict_efield['TxMD-2']['f-1'] is None
assert sim3._dict_efield_info['TxMD-2']['f-1'] is None
with pytest.raises(TypeError, match="Unrecognized `what`: nothing"):
sim3.clean('nothing')
def test_dicts_provided(self):
grids = self.simulation._dict_grid.copy()
# dict
sim1 = simulations.Simulation(self.survey,
self.model,
gridding='dict',
gridding_opts=grids,
name='Test2')
m1 = sim1.get_model('TxEW-3', 1.0)
g1 = sim1.get_grid('TxEW-3', 1.0)
# provide
sim2 = simulations.Simulation(self.survey,
self.model,
name='Test2',
gridding='input',
gridding_opts=grids['TxEW-3']['f-1'])
m2 = sim2.get_model('TxEW-3', 1.0)
g2 = sim2.get_grid('TxEW-3', 1.0)
assert m1 == m2
assert g1 == g2
# to/from_dict
sim1copy = sim1.copy()
sim2copy = sim2.copy()
m1c = sim1copy.get_model('TxEW-3', 1.0)
g1c = sim1copy.get_grid('TxEW-3', 1.0)
m2c = sim2copy.get_model('TxEW-3', 1.0)
g2c = sim2copy.get_grid('TxEW-3', 1.0)
assert m1 == m1c
assert g1 == g1c
assert m2 == m2c
assert g2 == g2c
def test_grid_provided(self):
# Check bad grid
hx = np.ones(17) * 20
grid = emg3d.TensorMesh([hx, hx, hx], (0, 0, 0))
with pytest.warns(UserWarning, match='optimal for MG solver. Good n'):
simulations.Simulation(self.survey,
self.model,
gridding='input',
gridding_opts=grid)
def test_synthetic(self):
sim = self.simulation.copy()
sim._dict_efield = sim._dict_initiate # Reset
sim.compute(observed=True, add_noise=False)
assert_allclose(sim.data.synthetic, sim.data.observed)
assert sim.survey.size == sim.data.observed.size
def test_input_gradient(self):
# Create another mesh, so there will be a difference.
newgrid = emg3d.TensorMesh(
[np.ones(16) * 500,
np.ones(8) * 1000,
np.ones(8) * 1000], np.array([-1250, -1250, -2250]))
simulation = simulations.Simulation(self.survey,
self.model,
max_workers=1,
solver_opts={
'maxit': 1,
'verb': 0,
'sslsolver': False,
'linerelaxation': False,
'semicoarsening': False
},
gridding='input',
gridding_opts=newgrid,
name='TestX')
with pytest.warns(UserWarning, match='Receiver responses were obtain'):
grad = simulation.gradient
with pytest.warns(UserWarning, match='Receiver responses were obtain'):
vec = simulation.data.residual.data.copy()
vec *= simulation.data.weights.data
jtvec = simulation.jtvec(vec)
assert_allclose(grad, jtvec)
jvec = simulation.jvec(np.ones(newgrid.n_cells))
assert jvec.shape == simulation.data.observed.data.shape
# Ensure the gradient has the shape of the model, not of the input.
assert grad.shape == self.model.shape
sim2 = simulation.to_dict(what='all', copy=True)
sim3 = simulation.to_dict(what='plain', copy=True)
assert 'residual' in sim2['survey']['data'].keys()
assert 'residual' not in sim3['survey']['data'].keys()
simulation.clean('all') # Should remove 'residual', 'bfield-dicts'
sim5 = simulation.to_dict('all')
assert 'residual' not in sim5['survey']['data'].keys()
assert '_dict_bfield' not in sim5.keys()
def test_simulation_automatic(self, capsys):
# Create a simple survey
sources = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.TxElectricDipole, (0, [1000, 3000, 5000], -950, 0, 0))
receivers = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.RxElectricPoint,
([-3000, 0, 3000], [0, 3000, 6000], -1000, 0, 0))
frequencies = (0.1, 1.0, 10.0)
survey = emg3d.Survey(sources,
receivers,
frequencies,
name='Test',
noise_floor=1e-15,
relative_error=0.05)
# Create a simple grid and model
grid = emg3d.TensorMesh(
[np.ones(32) * 250,
np.ones(16) * 500,
np.ones(4) * 500], np.array([-1250, -1250, -2250]))
model = emg3d.Model(grid, 1)
# Create a simulation, compute all fields.
inp = {
'survey': survey,
'model': model,
'gridding_opts': {
'expand': [1, 0.5],
'seasurface': 0,
'verb': 1
}
}
b_sim = simulations.Simulation(name='both', gridding='both', **inp)
f_sim = simulations.Simulation(name='freq',
gridding='frequency',
**inp)
t_sim = simulations.Simulation(name='src', gridding='source', **inp)
s_sim = simulations.Simulation(name='single', gridding='single', **inp)
# Quick repr test.
assert " 24 x 24 (13,824) - 160 x 160 x 96 (2,457," in b_sim.__repr__()
assert " 24 x 24 (13,824) - 160 x 160 x 96 (2,457," in f_sim.__repr__()
assert "Source-dependent grids; 64 x 64 x 40 (163," in t_sim.__repr__()
assert "ources and frequencies; 64 x 64 x 40 (163," in s_sim.__repr__()
# Quick print_grid test:
_, _ = capsys.readouterr() # empty
b_sim.print_grid_info()
out, _ = capsys.readouterr()
assert "= Source: TxED-1; Frequency: 10.0 Hz =" in out
assert "== GRIDDING IN X ==" in out
assert b_sim.get_grid('TxED-1', 1.0).__repr__() in out
_, _ = capsys.readouterr() # empty
out = f_sim.print_grid_info(return_info=True)
out2, _ = capsys.readouterr()
assert out2 == ""
assert "= Source: all" in out
assert "== GRIDDING IN X ==" in out
assert f_sim.get_grid('TxED-3', 1.0).__repr__() in out
t_sim.print_grid_info()
out, _ = capsys.readouterr()
assert "; Frequency: all" in out
assert "== GRIDDING IN X ==" in out
assert t_sim.get_grid('TxED-1', 10.0).__repr__() in out
_, _ = capsys.readouterr() # empty
out = s_sim.print_grid_info(return_info=True)
out2, _ = capsys.readouterr()
assert out2 == ""
assert "= Source: all; Frequency: all =" in out
assert "== GRIDDING IN X ==" in out
assert s_sim.get_grid('TxED-3', 0.1).__repr__() in out
assert s_sim.print_grid_info(verb=-1) is None
# Grids: Middle source / middle frequency should be the same in all.
assert f_sim.get_grid('TxED-2', 1.0) == t_sim.get_grid('TxED-2', 1.0)
assert f_sim.get_grid('TxED-2', 1.0) == s_sim.get_grid('TxED-2', 1.0)
assert f_sim.get_grid('TxED-2', 1.0) == b_sim.get_grid('TxED-2', 1.0)
assert f_sim.get_model('TxED-2', 1.0) == t_sim.get_model('TxED-2', 1.0)
assert f_sim.get_model('TxED-2', 1.0) == s_sim.get_model('TxED-2', 1.0)
assert f_sim.get_model('TxED-2', 1.0) == b_sim.get_model('TxED-2', 1.0)
# Copy:
f_sim_copy = f_sim.copy()
assert (f_sim.get_grid('TxED-1',
1.0) == f_sim_copy.get_grid('TxED-1', 1.0))
assert 'expand' not in f_sim.gridding_opts.keys()
assert 'expand' not in f_sim_copy.gridding_opts.keys()
s_sim_copy = s_sim.copy()
assert (s_sim.get_grid('TxED-1',
1.0) == s_sim_copy.get_grid('TxED-1', 1.0))
assert 'expand' not in s_sim.gridding_opts.keys()
assert 'expand' not in s_sim_copy.gridding_opts.keys()
t_sim_copy = t_sim.copy()
assert (t_sim.get_grid('TxED-1',
1.0) == t_sim_copy.get_grid('TxED-1', 1.0))
assert 'expand' not in t_sim.gridding_opts.keys()
assert 'expand' not in t_sim_copy.gridding_opts.keys()
def test_print_solver(self, capsys):
grid = emg3d.TensorMesh(h=[[(25, 10, -1.04), (25, 28), (25, 10, 1.04)],
[(50, 8, -1.03), (50, 16), (50, 8, 1.03)],
[(30, 8, -1.05), (30, 16), (30, 8, 1.05)]],
origin='CCC')
model = emg3d.Model(grid,
property_x=1.5,
property_y=1.8,
property_z=3.3,
mapping='Resistivity')
sources = emg3d.TxElectricDipole((0, 0, 0, 0, 0))
receivers = [
emg3d.RxElectricPoint((x, 0, 0, 0, 0)) for x in [-10000, 10000]
]
survey = emg3d.Survey(
name='Test',
sources=sources,
receivers=receivers,
frequencies=1.0,
noise_floor=1e-15,
relative_error=0.05,
)
inp = {
'name': 'Test',
'survey': survey,
'model': model,
'gridding': 'same'
}
sol = {
'sslsolver': False,
'semicoarsening': False,
'linerelaxation': False,
'maxit': 1
}
# Errors but verb=-1.
_, _ = capsys.readouterr() # empty
simulation = simulations.Simulation(verb=-1, **inp, solver_opts=sol)
simulation.compute()
out, _ = capsys.readouterr()
assert out == ""
# Errors with verb=0.
out = simulation.print_solver_info('efield', verb=0, return_info=True)
assert "= Source TxED-1; Frequency 1.0 Hz = MAX. ITERATION REAC" in out
# Errors with verb=1.
_, _ = capsys.readouterr() # empty
simulation.print_solver_info('efield', verb=1)
out, _ = capsys.readouterr()
assert "= Source TxED-1; Frequency 1.0 Hz = 2.6e-02; 1; 0:00:" in out
# No errors; solver-verb 3.
simulation = simulations.Simulation(verb=1,
**inp,
solver_opts={'verb': 3})
simulation.compute()
out, _ = capsys.readouterr()
assert 'MG-cycle' in out
assert 'CONVERGED' in out
# No errors; solver-verb 0.
simulation = simulations.Simulation(verb=1,
**inp,
solver_opts={'verb': 0})
simulation.compute()
out, _ = capsys.readouterr()
assert "= Source TxED-1; Frequency 1.0 Hz = CONVERGED" in out
# Two sources, only compute 1, assure printing works.
sources = [emg3d.TxElectricDipole((x, 0, 0, 0, 0)) for x in [0, 10]]
survey = emg3d.Survey(
name='Test',
sources=sources,
receivers=receivers,
frequencies=1.0,
noise_floor=1e-15,
relative_error=0.05,
)
inp = {
'name': 'Test',
'survey': survey,
'model': model,
'gridding': 'same'
}
simulation = simulations.Simulation(**inp, solver_opts={'verb': 0})
_ = simulation.get_efield('TxED-2', 'f-1')
simulation.print_solver_info(verb=1)
out, _ = capsys.readouterr()
assert "= Source TxED-2; Frequency 1.0 Hz = CONVERGED" in out
def test_rel_abs_rec(self):
# Sources
sources = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.TxElectricDipole, ([0, 100, 200], 0, 0, 0, 0))
# Abs and rel Receivers
a_e_rec = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.RxElectricPoint, (1000 + np.arange(3) * 100, 0, -100, 0, 0))
r_e_rec = emg3d.surveys.txrx_coordinates_to_dict(emg3d.RxElectricPoint,
(1000, 0, -100, 0, 0),
relative=True)
a_h_rec = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.RxMagneticPoint, (1000 + np.arange(3) * 100, 0, -100, 0, 0))
r_h_rec = emg3d.surveys.txrx_coordinates_to_dict(emg3d.RxMagneticPoint,
(1000, 0, -100, 0, 0),
relative=True)
receivers = emg3d.surveys.txrx_lists_to_dict(
[a_e_rec, r_e_rec, a_h_rec, r_h_rec])
# Frequencies
frequencies = (1.0)
survey = emg3d.Survey(sources,
receivers,
frequencies,
name='TestSurv',
noise_floor=1e-15,
relative_error=0.05)
# Create a simple grid and model
grid = emg3d.TensorMesh(
[np.ones(32) * 250,
np.ones(16) * 500,
np.ones(16) * 500], np.array([-1250, -1250, -2250]))
model = emg3d.Model(grid, 1)
# Create a simulation, compute all fields.
simulation = simulations.Simulation(survey,
model,
name='TestSim',
max_workers=1,
solver_opts={
'maxit': 1,
'verb': 0,
'plain': True
},
gridding='same')
simulation.compute()
# Relative receivers must be same as corresponding absolute receivers
assert_allclose(
[simulation.data.synthetic[i, i, 0].data for i in range(3)],
simulation.data.synthetic[:, 3, 0].data)
assert_allclose(
[simulation.data.synthetic[i, i + 4, 0].data for i in range(3)],
simulation.data.synthetic[:, 7, 0].data)
class TestEstimateGriddingOpts():
if xarray is not None:
# Create a simple survey
sources = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.TxElectricDipole,
(0, [1000, 3000, 5000], -950, 0, 0))
receivers = emg3d.surveys.txrx_coordinates_to_dict(
emg3d.RxElectricPoint,
(np.arange(11)*500, 2000, -1000, 0, 0))
frequencies = (0.1, 10.0)
survey = emg3d.Survey(
sources, receivers, frequencies, noise_floor=1e-15,
relative_error=0.05)
# Create a simple grid and model
grid = meshes.TensorMesh(
[np.ones(32)*250, np.ones(16)*500, np.ones(16)*500],
np.array([-1250, -1250, -2250]))
model = emg3d.Model(grid, 0.1, np.ones(grid.shape_cells)*10)
model.property_y[5, 8, 3] = 100000 # Cell at source center
def test_empty_dict(self):
gdict = meshes.estimate_gridding_opts({}, self.model, self.survey)
assert gdict['frequency'] == 1.0
assert gdict['mapping'] == self.model.map.name
assert_allclose(gdict['center'], (0, 3000, -950))
assert_allclose(gdict['domain']['x'], (-500, 5500))
assert_allclose(gdict['domain']['y'], (600, 5400))
assert_allclose(gdict['domain']['z'], (-3651, -651))
assert_allclose(gdict['properties'], [100000, 10, 10, 10, 10, 10, 10])
def test_mapping_vector(self):
gridding_opts = {
'mapping': "LgConductivity",
'vector': 'xZ',
}
gdict = meshes.estimate_gridding_opts(
gridding_opts, self.model, self.survey)
assert_allclose(
gdict['properties'],
np.log10(1/np.array([100000, 10, 10, 10, 10, 10, 10])),
atol=1e-15)
assert_allclose(gdict['vector']['x'], self.grid.nodes_x)
assert gdict['vector']['y'] is None
assert_allclose(gdict['vector']['z'], self.grid.nodes_z)
def test_vector_domain_distance(self):
gridding_opts = {
'vector': 'Z',
'domain': (None, [-1000, 1000], None),
'distance': [[5, 10], None, None],
}
gdict = meshes.estimate_gridding_opts(
gridding_opts, self.model, self.survey)
assert gdict['vector']['x'] == gdict['vector']['y'] is None
assert_allclose(gdict['vector']['z'], self.model.grid.nodes_z)
assert gdict['domain']['x'] is None
assert gdict['domain']['y'] == [-1000, 1000]
assert gdict['domain']['z'] == [self.model.grid.nodes_z[0],
self.model.grid.nodes_z[-1]]
assert gdict['distance']['x'] == [5, 10]
assert gdict['distance']['y'] == gdict['distance']['z'] is None
# As dict
gridding_opts = {
'vector': 'Z',
'domain': {'x': None, 'y': [-1000, 1000], 'z': None},
'distance': {'x': [5, 10], 'y': None, 'z': None},
}
gdict = meshes.estimate_gridding_opts(
gridding_opts, self.model, self.survey)
assert gdict['vector']['x'] == gdict['vector']['y'] is None
assert_allclose(gdict['vector']['z'], self.model.grid.nodes_z)
assert gdict['domain']['x'] is None
assert gdict['domain']['y'] == [-1000, 1000]
assert gdict['domain']['z'] == [self.model.grid.nodes_z[0],
self.model.grid.nodes_z[-1]]
assert gdict['distance']['x'] == [5, 10]
assert gdict['distance']['y'] == gdict['distance']['z'] is None
def test_pass_along(self):
gridding_opts = {
'vector': {'x': None, 'y': 1, 'z': None},
'stretching': [1.2, 1.3],
'seasurface': -500,
'cell_numbers': [10, 20, 30],
'lambda_factor': 0.8,
'max_buffer': 10000,
'min_width_limits': ([20, 40], [20, 40], [20, 40]),
'min_width_pps': 4,
'verb': -1,
}
gdict = meshes.estimate_gridding_opts(
gridding_opts.copy(), self.model, self.survey)
# Check that all parameters passed unchanged.
gdict2 = {k: gdict[k] for k, _ in gridding_opts.items()}
# Except the tuple, which should be a dict now
gridding_opts['min_width_limits'] = {
'x': gridding_opts['min_width_limits'][0],
'y': gridding_opts['min_width_limits'][1],
'z': gridding_opts['min_width_limits'][2]
}
assert helpers.compare_dicts(gdict2, gridding_opts)
def test_factor(self):
sources = emg3d.TxElectricDipole((0, 3000, -950, 0, 0))
receivers = emg3d.RxElectricPoint((0, 3000, -1000, 0, 0))
# Adjusted x-domain.
survey = emg3d.Survey(
self.sources, receivers, self.frequencies, noise_floor=1e-15,
relative_error=0.05)
gdict = meshes.estimate_gridding_opts({}, self.model, survey)
assert_allclose(gdict['domain']['x'], (-800, 800))
# Adjusted x-domain.
survey = emg3d.Survey(
sources, self.receivers, self.frequencies, noise_floor=1e-15,
relative_error=0.05)
gdict = meshes.estimate_gridding_opts({}, self.model, survey)
assert_allclose(gdict['domain']['y'], (1500, 3500))
def test_error(self):
with pytest.raises(TypeError, match='Unexpected gridding_opts'):
_ = meshes.estimate_gridding_opts(
{'what': True}, self.model, self.survey)
class TestSaveLoad:
frequency = 1.0
grid = emg3d.TensorMesh([[2, 2], [3, 4], [0.5, 2]], (0, 0, 0))
field = emg3d.Field(grid)
model = emg3d.Model(grid, 1)
tx_e_d = emg3d.TxElectricDipole((0, 1000, 0, 0, -900, -950))
tx_m_d = emg3d.TxMagneticDipole([[0, 0, -900], [1000, 0, -950]])
tx_e_w = emg3d.TxElectricWire(([[0, 0, 0], [1, 1, 1], [1, 0, 1]]))
rx_e_p = emg3d.RxElectricPoint((0, 1000, -950, 0, 20))
rx_m_p = emg3d.RxMagneticPoint((0, 1000, -950, 20, 0))
a = np.arange(10.)
b = 1+5j
data = {
'Grid': grid,
'Model': model,
'Field': field,
'a': a,
'b': b,
}
if xarray:
survey = emg3d.Survey(
emg3d.surveys.txrx_lists_to_dict([tx_e_d, tx_m_d, tx_e_w]),
emg3d.surveys.txrx_lists_to_dict([rx_e_p, rx_m_p]),
frequency
)
simulation = emg3d.Simulation(survey, model, gridding='same')
data['Survey'] = survey
data['Simulation'] = simulation
def test_npz(self, tmpdir, capsys):
io.save(tmpdir+'/test.npz', **self.data)
outstr, _ = capsys.readouterr()
assert 'Data saved to «' in outstr
assert emg3d.__version__ in outstr
# Save it with other verbosity.
_, _ = capsys.readouterr()
io.save(tmpdir+'/test.npz', **self.data, verb=0)
outstr, _ = capsys.readouterr()
assert outstr == ""
out = io.save(tmpdir+'/test.npz', **self.data, verb=-1)
assert 'Data saved to «' in out
# Load it.
out_npz = io.load(str(tmpdir+'/test.npz'), allow_pickle=True)
outstr, _ = capsys.readouterr()
assert 'Data loaded from «' in outstr
assert 'test.npz' in outstr
assert emg3d.__version__ in outstr
assert out_npz['Model'] == self.model
assert_allclose(out_npz['a'], self.a)
assert out_npz['b'] == self.b
assert_allclose(self.field.fx, out_npz['Field'].fx)
assert_allclose(self.grid.cell_volumes, out_npz['Grid'].cell_volumes)
# Load it with other verbosity.
_, _ = capsys.readouterr()
out = io.load(tmpdir+'/test.npz', verb=0)
outstr, _ = capsys.readouterr()
assert outstr == ""
out, out_str = io.load(tmpdir+'/test.npz', verb=-1)
assert 'Data loaded from «' in out_str
def test_h5(self, tmpdir):
if h5py:
io.save(tmpdir+'/test.h5', **self.data)
out_h5 = io.load(str(tmpdir+'/test.h5'))
assert out_h5['Model'] == self.model
assert_allclose(out_h5['a'], self.a)
assert out_h5['b'] == self.b
assert_allclose(self.field.fx, out_h5['Field'].fx)
assert_allclose(self.grid.cell_volumes,
out_h5['Grid'].cell_volumes)
else:
with pytest.warns(UserWarning, match='emg3d: This feature requir'):
io.save(tmpdir+'/test.h5', grid=self.grid)
def test_json(self, tmpdir):
io.save(tmpdir+'/test.json', **self.data)
out_json = io.load(str(tmpdir+'/test.json'))
assert out_json['Model'] == self.model
assert_allclose(out_json['a'], self.a)
assert out_json['b'] == self.b
assert_allclose(self.field.fx, out_json['Field'].fx)
assert_allclose(self.grid.cell_volumes, out_json['Grid'].cell_volumes)
def test_warnings(self, tmpdir, capsys):
# Check message from loading another file
data = io._dict_serialize({'meshes': self.grid})
fdata = io._dict_flatten(data)
np.savez_compressed(tmpdir+'/test2.npz', **fdata)
_ = io.load(str(tmpdir+'/test2.npz'), allow_pickle=True)
outstr, _ = capsys.readouterr()
assert "[version/format/date unknown; not created by emg" in outstr
# Unknown keyword.
with pytest.raises(TypeError, match="Unexpected "):
io.load('ttt.npz', stupidkeyword='a')
# Unknown extension.
with pytest.raises(ValueError, match="Unknown extension '.abc'"):
io.save(tmpdir+'/testwrongextension.abc', something=1)
with pytest.raises(ValueError, match="Unknown extension '.abc'"):
io.load(tmpdir+'/testwrongextension.abc')