def test_io_rhoa(self):
# Setup a dipole-dipole Survey
for survey_type, test_file, rhoa_file in zip(
["dipole-dipole", "pole-dipole", "dipole-pole", "pole-pole"],
[
"2sph_dipole_dipole.obs",
"2sph_pole_dipole.obs",
"2sph_dipole_pole.obs",
"2sph_pole_pole.obs",
],
[
"rhoA_GIF_dd.txt",
"rhoA_GIF_pd.txt",
"rhoA_GIF_dp.txt",
"rhoA_GIF_pp.txt",
],
):
print("\n Testing {} ... ".format(survey_type))
survey = utils.gen_DCIPsurvey(
self.xyz,
survey_type=survey_type,
dim=self.mesh.dim,
a=self.survey_a,
b=self.survey_b,
n=self.survey_n,
)
self.assertEqual(survey_type, survey.survey_type)
# Setup Problem with exponential mapping
expmap = maps.ExpMap(self.mesh)
problem = dc.Simulation3DCellCentered(
self.mesh, sigmaMap=expmap, survey=survey, bc_type="Neumann"
)
problem.solver = Solver
# Create synthetic data
dobs = problem.make_synthetic_data(self.model, relative_error=0.0)
dobs.eps = 1e-5
# Testing IO
surveyfile = os.path.sep.join([self.basePath, test_file])
utils.writeUBC_DCobs(
surveyfile, dobs, survey_type=survey_type, dim=3, format_type="GENERAL"
)
data2 = utils.readUBC_DC3Dobs(surveyfile)
self.assertTrue(np.allclose(mkvc(data2), mkvc(dobs)))
if self.plotIt:
import matplotlib.pyplot as plt
# Test Pseudosections plotting
fig, ax = plt.subplots(1, 1, figsize=(15, 3))
ax = utils.plot_pseudoSection(
survey,
ax,
survey_type=survey_type,
scale="log",
clim=None,
data_type="appResistivity",
pcolorOpts={"cmap": "viridis"},
data_location=True,
)
plt.show()
# Test the utils functions electrode_separations,
# source_receiver_midpoints, geometric_factor,
# apparent_resistivity all at once
rhoapp = utils.apparent_resistivity(
dobs, survey_type=survey_type, space_type="half-space", eps=0.0
)
rhoA_GIF_file = os.path.sep.join([self.basePath, rhoa_file])
rhoA_GIF = np.loadtxt(rhoA_GIF_file)
passed = np.allclose(rhoapp, rhoA_GIF)
self.assertTrue(passed)
print(" ... ok \n".format(survey_type))
# Predict the data by running the simulation. The data are the raw voltage in
# units of volts.
dpred_dc = dc_simulation.dpred(conductivity_model)
# Define a data object (required for pseudo-section plot)
dc_data = data.Data(dc_survey, dobs=dpred_dc)
# Plot apparent conductivity pseudo-section
fig = plt.figure(figsize=(12, 5))
ax1 = fig.add_axes([0.05, 0.05, 0.8, 0.9])
plot_pseudoSection(
dc_data,
ax=ax1,
survey_type="dipole-dipole",
data_type="appConductivity",
space_type="half-space",
scale="log",
pcolorOpts={"cmap": "viridis"},
)
ax1.set_title("Apparent Conductivity [S/m]")
plt.show()
#######################################################################
# Optional: Write out dpred
# -------------------------
#
# Write DC resistivity data, topography and true model
#