def test_Simulation2DCellCentered(self):
simDC = dc.Simulation2DCellCentered(
self.mesh,
sigmaMap=maps.IdentityMap(self.mesh),
solver=Solver,
survey=self.survey_dc,
)
data0 = simDC.dpred(self.sigma0)
datainf = simDC.dpred(self.sigmaInf)
data_full = (data0 - datainf) / datainf
simIP = ip.Simulation2DCellCentered(
self.mesh,
sigma=self.sigmaInf,
etaMap=maps.IdentityMap(self.mesh),
solver=Solver,
survey=self.survey_ip,
)
data = simIP.dpred(self.eta)
np.testing.assert_allclose(simIP._scale, simIP._sign / datainf)
err = np.linalg.norm(
(data - data_full) / data_full)**2 / data_full.size
if err > 0.05:
import matplotlib.pyplot as plt
plt.plot(data_full)
plt.plot(data, "k.")
plt.show()
self.assertLess(err, 0.05)
def test_Simulation2DCellCentered(self):
problemDC = dc.Simulation2DCellCentered(self.mesh,
survey=self.surveyDC,
rhoMap=maps.IdentityMap(
self.mesh))
problemDC.solver = Solver
data0 = problemDC.dpred(1.0 / self.sigma0)
finf = problemDC.fields(1.0 / self.sigmaInf)
datainf = problemDC.dpred(1.0 / self.sigmaInf, f=finf)
surveyIP = ip.Survey(self.source_lists_ip)
problemIP = ip.Simulation2DCellCentered(
self.mesh,
survey=surveyIP,
rho=1.0 / self.sigmaInf,
etaMap=maps.IdentityMap(self.mesh),
)
problemIP.solver = Solver
data_full = data0 - datainf
data = problemIP.dpred(self.eta)
err = np.linalg.norm(
(data - data_full) / data_full)**2 / data_full.size
if err < 0.05:
passed = True
print(">> IP forward test for Simulation2DCellCentered is passed")
else:
import matplotlib.pyplot as plt
passed = False
print(">> IP forward test for Simulation2DCellCentered is failed")
print(err)
plt.plot(data_full)
plt.plot(data, "k.")
plt.show()
self.assertTrue(passed)