r0 = 500 # radius of sphere
print(x0, y0, z0)
csph = (np.sqrt((mesh.gridCC[:, 0] - x0)**2. + (mesh.gridCC[:, 1] - y0)**2. +
(mesh.gridCC[:, 2] - z0)**2.)) < r0 # indicies of sphere
# sphere done =================================================================
print("Starting forward modeling")
start = clock()
# Define model Background
ln_sigback = 0.023 # chargeability
rx = getRxData() # rx locations
tx = getTxData() # tx locations
survey = generateSurvey(rx, tx, 45, 65) # create survey object
survey.getABMN_locations() # get locations
uniq = Utils.uniqueRows(
np.vstack((survey.a_locations, survey.b_locations, survey.m_locations,
survey.n_locations))) # row the locations
electrode_locations = uniq[0] # assign
actinds = Utils.surface2ind_topo(mesh, electrode_locations,
method='cubic') # active indicies
survey.drapeTopo(mesh, actinds) # drape topo
# ============================================================================
# Create model
mx = np.ones(mesh.nC) * 0.015 # chargeability
sigma = np.ones(mesh.nC) * 1. / 33000.
# create dipping structure parameters
theta = 45. * np.pi / 180. # dipping angle
x0_d = 374700.
x1_d = 375000.
y0_d = 6275850.
def from_ambn_locations_to_survey(
self, a_locations, b_locations, m_locations, n_locations,
survey_type=None, data_dc=None, data_ip=None, data_sip=None,
data_dc_type="volt", data_ip_type="volt", data_sip_type="volt",
fname=None, dimension=2, line_inds=None,
times_ip=None
):
"""
read A, B, M, N electrode location and data (V or apparent_resistivity)
"""
self.a_locations = a_locations.copy()
self.b_locations = b_locations.copy()
self.m_locations = m_locations.copy()
self.n_locations = n_locations.copy()
self.survey_type = survey_type
self.dimension = dimension
self.data_dc_type = data_dc_type
self.data_ip_type = data_ip_type
self.data_sip_type = data_sip_type
if times_ip is not None:
self.times_ip = times_ip
uniqSrc = Utils.uniqueRows(np.c_[self.a_locations, self.b_locations])
uniqElec = SimPEG.Utils.uniqueRows(
np.vstack(
(
self.a_locations, self.b_locations,
self.m_locations, self.n_locations
)
)
)
self.electrode_locations = uniqElec[0]
nSrc = uniqSrc[0].shape[0]
ndata = self.a_locations.shape[0]
if self.survey_layout == "SURFACE":
# 2D locations
srcLists = []
sort_inds = []
for iSrc in range(nSrc):
inds = uniqSrc[2] == iSrc
sort_inds.append(np.arange(ndata)[inds])
locsM = self.m_locations[inds, :]
locsN = self.n_locations[inds, :]
if dimension == 2:
if survey_type in ['dipole-dipole', 'pole-dipole']:
rx = Rx.Dipole_ky(locsM, locsN)
elif survey_type in ['dipole-pole', 'pole-pole']:
rx = Rx.Pole_ky(locsM)
elif dimension == 3:
if survey_type in ['dipole-dipole', 'pole-dipole']:
rx = Rx.Dipole(locsM, locsN)
elif survey_type in ['dipole-pole', 'pole-pole']:
rx = Rx.Pole(locsM)
else:
raise NotImplementedError()
if dimension == 2:
locA = uniqSrc[0][iSrc, :2]
locB = uniqSrc[0][iSrc, 2:]
elif dimension == 3:
locA = uniqSrc[0][iSrc, :3]
locB = uniqSrc[0][iSrc, 3:]
if survey_type in ['dipole-dipole', 'dipole-pole']:
src = Src.Dipole([rx], locA, locB)
elif survey_type in ['pole-dipole', 'pole-pole']:
src = Src.Pole([rx], locA)
srcLists.append(src)
self.sort_inds = np.hstack(sort_inds)
if dimension == 2:
survey = Survey_ky(srcLists)
elif dimension == 3:
survey = Survey(srcLists)
else:
raise NotImplementedError()
self.a_locations = self.a_locations[self.sort_inds, :]
self.b_locations = self.b_locations[self.sort_inds, :]
self.m_locations = self.m_locations[self.sort_inds, :]
self.n_locations = self.n_locations[self.sort_inds, :]
self.G = self.geometric_factor(survey)
if data_dc is not None:
self.data_dc = data_dc[self.sort_inds]
if data_ip is not None:
self.data_ip = data_ip[self.sort_inds]
if data_sip is not None:
self.data_sip = data_sip[self.sort_inds, :]
if line_inds is not None:
self.line_inds = line_inds[self.sort_inds]
# Here we ignore ... z-locations
self.n_data = survey.nD
midABx = (self.a_locations[:, 0] + self.b_locations[:, 0])*0.5
midMNx = (self.m_locations[:, 0] + self.n_locations[:, 0])*0.5
if dimension == 2:
z = abs(midABx-midMNx)*1./3.
x = (midABx+midMNx)*0.5
self.grids = np.c_[x, z]
elif dimension == 3:
midABy = (self.a_locations[:, 1] + self.b_locations[:, 1])*0.5
midMNy = (self.m_locations[:, 1] + self.n_locations[:, 1])*0.5
z = np.sqrt((midABx-midMNx)**2 + (midABy-midMNy)**2) * 1./3.
x = (midABx+midMNx)*0.5
y = (midABy+midMNy)*0.5
self.grids = np.c_[x, y, z]
else:
raise Exception()
else:
raise NotImplementedError()
return survey
def run(plotIt=True, survey_type="pole-dipole"):
np.random.seed(1)
# Initiate I/O class for DC
IO = DC.IO()
# Obtain ABMN locations
fileName1 = "C:/Users/johnk/Projects/Seabridge/fmdataDC.con" # output mod
fileName1_ = "C:/Users/johnk/Projects/Seabridge/fmdataIP.chg" # output mod
fileName2 = "C:/Users/johnk/Projects/Seabridge/forwardmodel.msh" # in mesh
mesh = Mesh.TensorMesh._readUBC_3DMesh(fileName2) # Read in/create mesh
print("Starting forward modeling")
start = clock()
# Define model Background
rx = getRxData() # rx locations
tx = getTxData() # tx locations
survey_dc = generateSurvey(rx, tx, 45, 65) # create survey object
survey_dc.getABMN_locations() # get locations
# survey_dc = IO.from_ambn_locations_to_survey(
# survey_dc.a_locations, survey_dc.b_locations,
# survey_dc.m_locations, survey_dc.n_locations,
# survey_type, data_dc_type='volt', data_ip_type='volt'
# )
uniq = Utils.uniqueRows(np.vstack((survey_dc.a_locations,
survey_dc.b_locations,
survey_dc.m_locations,
survey_dc.n_locations)))
electrode_locations = uniq[0] # assign
actinds = Utils.surface2ind_topo(mesh,
electrode_locations,
method='cubic') # active indicies
survey_dc.drapeTopo(mesh, actinds) # drape topo
# =============================================================================
# create sphere for ice representation
x0 = (np.max(mesh.gridCC[:, 0]) +
np.min(mesh.gridCC[:, 0])) / 2. + 50 # x0 center point of sphere
y0 = (np.max(mesh.gridCC[:, 1]) +
np.min(mesh.gridCC[:, 1])) / 2. - 50 # y0 center point of sphere
z0 = 2350 # x0 center point of sphere
# (np.max(mesh.gridCC[:, 2]) + np.min(mesh.gridCC[:, 2])) / 2.
r0 = 500 # radius of sphere
print(x0, y0, z0)
csph = (np.sqrt((mesh.gridCC[:, 0] - x0)**2. +
(mesh.gridCC[:, 1] - y0)**2. +
(mesh.gridCC[:, 2] - z0)**2.)) < r0 # indicies of sphere
# sphere done =================================================================
# ============================================================================
# Create model
mx = np.ones(mesh.nC) * 0.020 # chargeability
sigma = np.ones(mesh.nC) * 1. / 15000.
# create dipping structure parameters
theta = 45. * np.pi / 180. # dipping angle
x0_d = 374700.
x1_d = 375000.
y0_d = 6275850.
y0_1d = 500. * np.sin(theta) + y0_d
y1_d = 6275900.
y1_1d = 500. * np.sin(theta) + y1_d
z0_d = 1860.
z1_d = z0_d - (500. * np.cos(theta))
m_ = (z0_d - z1_d) / (y0_1d - y0_d) # slope of dip
# loop through mesh and assign dipping structure conductivity
for idx in range(mesh.nC):
if z1_d <= mesh.gridCC[idx, 2] <= z0_d:
if (x0_d <= mesh.gridCC[idx, 0] <= x1_d):
yslope1 = y0_d + (1. / m_) * (mesh.gridCC[idx, 2] - z0_d)
yslope2 = y1_d + (1. / m_) * (mesh.gridCC[idx, 2] - z0_d)
if yslope1 <= mesh.gridCC[idx, 1] <= yslope2:
mx[idx] = 0.03
sigma[idx] = 1. / 300.
# mx[csph] = ((0.025) *
# np.ones_like(mx[csph])) # set sphere values
mx[~actinds] = 1. / 1e8 # flag air values
# sigma[csph] = ((5000.) *
# np.ones_like(sigma[csph])) # set sphere values
sigma[~actinds] = 1. / 1e8 # flag air values
rho = 1. / sigma
stop = clock()
print(stop)
# plot results
# Show the true conductivity model
if plotIt:
ncy = mesh.nCy
ncz = mesh.nCz
ncx = mesh.nCx
mtrue = mx
print(mtrue.min(), mtrue.max())
clim = [0, 0.04]
fig, ax = plt.subplots(2, 2, figsize=(12, 6))
ax = Utils.mkvc(ax)
dat = mesh.plotSlice(((mx)), ax=ax[0], normal='Z', clim=clim,
ind=int(ncz / 2), pcolorOpts={"cmap": "jet"})
ax[0].plot(rx[:, 0], rx[:, 1], 'or')
ax[0].plot(tx[:, 0], tx[:, 1], 'dk')
mesh.plotSlice(((mx)), ax=ax[1], normal='Y', clim=clim,
ind=int(ncy / 2 + 2), pcolorOpts={"cmap": "jet"})
mesh.plotSlice(((mx)), ax=ax[2], normal='X', clim=clim,
ind=int(ncx / 2 + 4), pcolorOpts={"cmap": "jet"})
mesh.plotSlice(((mx)), ax=ax[3], normal='X', clim=clim,
ind=int(ncx / 2 + 8), pcolorOpts={"cmap": "jet"})
cbar_ax = fig.add_axes([0.82, 0.15, 0.05, 0.7])
cb = plt.colorbar(dat[0], ax=cbar_ax)
fig.subplots_adjust(right=0.85)
cb.set_label('V/V')
cbar_ax.axis('off')
plt.show()
mtrue = 1. / sigma
print(mtrue.min(), mtrue.max())
clim = [0, 20000]
fig, ax = plt.subplots(2, 2, figsize=(12, 6))
ax = Utils.mkvc(ax)
dat = mesh.plotSlice(((mtrue)), ax=ax[0], normal='Z', clim=clim,
ind=int(ncz / 2 - 4), pcolorOpts={"cmap": "jet"})
ax[0].plot(rx[:, 0], rx[:, 1], 'or')
ax[0].plot(tx[:, 0], tx[:, 1], 'dk')
mesh.plotSlice(((mtrue)), ax=ax[1], normal='Y', clim=clim,
ind=int(ncy / 2), pcolorOpts={"cmap": "jet"})
mesh.plotSlice(((mtrue)), ax=ax[2], normal='X', clim=clim,
ind=int(ncx / 2 + 4), pcolorOpts={"cmap": "jet"})
mesh.plotSlice(((mtrue)), ax=ax[3], normal='X', clim=clim,
ind=int(ncx / 2 + 8), pcolorOpts={"cmap": "jet"})
cbar_ax = fig.add_axes([0.82, 0.15, 0.05, 0.7])
cb = plt.colorbar(dat[0], ax=cbar_ax)
fig.subplots_adjust(right=0.85)
cb.set_label('rho')
cbar_ax.axis('off')
plt.show()
# Use Exponential Map: m = log(rho)
actmap = Maps.InjectActiveCells(
mesh, indActive=actinds, valInactive=np.log(1e8)
)
mapping = Maps.ExpMap(mesh) * actmap
# Generate mtrue_dc for resistivity
mtrue_dc = np.log(rho[actinds])
# Generate 3D DC problem
# "CC" means potential is defined at center
prb = DC.Problem3D_CC(
mesh, rhoMap=mapping, storeJ=False,
Solver=Solver
)
# Pair problem with survey
try:
prb.pair(survey_dc)
except:
survey_dc.unpair()
prb.pair(survey_dc)
# Make synthetic DC data with 5% Gaussian noise
dtrue_dc = survey_dc.makeSyntheticData(mtrue_dc, std=0.05, force=True)
IO.data_dc = dtrue_dc
# Generate mtrue_ip for chargability
mtrue_ip = mx[actinds]
# Generate 3D DC problem
# "CC" means potential is defined at center
prb_ip = IP.Problem3D_CC(
mesh, etaMap=actmap, storeJ=False, rho=rho,
Solver=Solver
)
survey_ip = IP.from_dc_to_ip_survey(survey_dc, dim="3D")
prb_ip.pair(survey_ip)
dtrue_ip = survey_ip.makeSyntheticData(mtrue_ip, std=0.05)
IO.data_ip = dtrue_ip
# Show apparent resisitivty histogram
# if plotIt:
# fig = plt.figure(figsize=(10, 4))
# ax1 = plt.subplot(121)
# out = hist(np.log10(abs(IO.voltages)), bins=20)
# ax1.set_xlabel("log10 DC voltage (V)")
# ax2 = plt.subplot(122)
# out = hist(IO.apparent_resistivity, bins=20)
# ax2.set_xlabel("Apparent Resistivity ($\Omega$m)")
# plt.tight_layout()
# plt.show()
# Set initial model based upon histogram
m0_dc = np.ones(actmap.nP) * np.log(10000.)
# Set uncertainty
# floor
eps_dc = 10**(-3.2)
# percentage
std_dc = 0.05
mopt_dc, pred_dc = DC.run_inversion(
m0_dc, survey_dc, actinds, mesh, std_dc, eps_dc,
use_sensitivity_weight=False)
# Convert obtained inversion model to resistivity
# rho = M(m), where M(.) is a mapping
rho_est = mapping * mopt_dc
# rho_est[~actinds] = np.nan
rho_true = rho.copy()
rho_true[~actinds] = np.nan
# write data to file
out_file = open(fileName1, "w")
for i in range(rho_est.size):
out_file.write("%0.5e\n" % rho_est[i])
# Set initial model based upon histogram
m0_ip = np.ones(actmap.nP) * 1e-10
# Set uncertainty
# floor
eps_ip = 10**(-4)
# percentage
std_ip = 0.05
# Clean sensitivity function formed with true resistivity
prb_ip._Jmatrix = None
# Input obtained resistivity to form sensitivity
prb_ip.rho = mapping * mopt_dc
mopt_ip, _ = IP.run_inversion(
m0_ip, survey_ip, actinds, mesh, std_ip, eps_ip,
upper=np.Inf, lower=0.,
use_sensitivity_weight=False)
# Convert obtained inversion model to chargeability
# charg = M(m), where M(.) is a mapping for cells below topography
charg_est = actmap * mopt_ip
# charg_est[~actinds] = np.nan
charg_true = charg.copy()
charg_true[~actinds] = np.nan
# write IP data to file
out_file = open(fileName1_, "w")
for i in range(charg_est.size):
out_file.write("%0.5e\n" % charg_est[i])
def from_ambn_locations_to_survey(
self, a_locations, b_locations, m_locations, n_locations,
survey_type=None, data_dc=None, data_ip=None, data_sip=None,
data_dc_type="volt", data_ip_type="volt", data_sip_type="volt",
fname=None, dimension=2, line_inds=None,
times_ip=None
):
"""
read A, B, M, N electrode location and data (V or apparent_resistivity)
"""
self.a_locations = a_locations.copy()
self.b_locations = b_locations.copy()
self.m_locations = m_locations.copy()
self.n_locations = n_locations.copy()
self.survey_type = survey_type
self.dimension = dimension
self.data_dc_type = data_dc_type
self.data_ip_type = data_ip_type
self.data_sip_type = data_sip_type
if times_ip is not None:
self.times_ip = times_ip
uniqSrc = Utils.uniqueRows(np.c_[self.a_locations, self.b_locations])
uniqElec = SimPEG.Utils.uniqueRows(
np.vstack(
(
self.a_locations, self.b_locations,
self.m_locations, self.n_locations
)
)
)
self.electrode_locations = uniqElec[0]
nSrc = uniqSrc[0].shape[0]
ndata = self.a_locations.shape[0]
if self.survey_layout == "SURFACE":
# 2D locations
srcLists = []
sort_inds = []
for iSrc in range(nSrc):
inds = uniqSrc[2] == iSrc
sort_inds.append(np.arange(ndata)[inds])
locsM = self.m_locations[inds, :]
locsN = self.n_locations[inds, :]
if dimension == 2:
if survey_type in ['dipole-dipole', 'pole-dipole']:
rx = Rx.Dipole_ky(locsM, locsN)
elif survey_type in ['dipole-pole', 'pole-pole']:
rx = Rx.Pole_ky(locsM)
elif dimension == 3:
if survey_type in ['dipole-dipole', 'pole-dipole']:
rx = Rx.Dipole(locsM, locsN)
elif survey_type in ['dipole-pole', 'pole-pole']:
rx = Rx.Pole(locsM)
else:
raise NotImplementedError()
if dimension == 2:
locA = uniqSrc[0][iSrc, :2]
locB = uniqSrc[0][iSrc, 2:]
elif dimension == 3:
locA = uniqSrc[0][iSrc, :3]
locB = uniqSrc[0][iSrc, 3:]
if survey_type in ['dipole-dipole', 'dipole-pole']:
src = Src.Dipole([rx], locA, locB)
elif survey_type in ['pole-dipole', 'pole-pole']:
src = Src.Pole([rx], locA)
srcLists.append(src)
self.sort_inds = np.hstack(sort_inds)
if dimension == 2:
survey = Survey_ky(srcLists)
elif dimension == 3:
survey = Survey(srcLists)
else:
raise NotImplementedError()
self.a_locations = self.a_locations[self.sort_inds, :]
self.b_locations = self.b_locations[self.sort_inds, :]
self.m_locations = self.m_locations[self.sort_inds, :]
self.n_locations = self.n_locations[self.sort_inds, :]
self.G = self.geometric_factor(survey)
if data_dc is not None:
self.data_dc = data_dc[self.sort_inds]
if data_ip is not None:
self.data_ip = data_ip[self.sort_inds]
if data_sip is not None:
self.data_sip = data_sip[self.sort_inds, :]
if line_inds is not None:
self.line_inds = line_inds[self.sort_inds]
# Here we ignore ... z-locations
self.n_data = survey.nD
midABx = (self.a_locations[:, 0] + self.b_locations[:, 0])*0.5
midMNx = (self.m_locations[:, 0] + self.n_locations[:, 0])*0.5
if dimension == 2:
z = abs(midABx-midMNx)*1./3.
x = (midABx+midMNx)*0.5
self.grids = np.c_[x, z]
elif dimension == 3:
midABy = (self.a_locations[:, 1] + self.b_locations[:, 1])*0.5
midMNy = (self.m_locations[:, 1] + self.n_locations[:, 1])*0.5
z = np.sqrt((midABx-midMNx)**2 + (midABy-midMNy)**2) * 1./3.
x = (midABx+midMNx)*0.5
y = (midABy+midMNy)*0.5
self.grids = np.c_[x, y, z]
else:
raise Exception()
else:
raise NotImplementedError()
return survey
def run(plotIt=True, survey_type="pole-dipole"):
np.random.seed(1)
# Initiate I/O class for DC
IO = DC.IO()
# Obtain ABMN locations
fileName1 = "/Users/juan/Documents/testData/fmdata-daf.con" # output mod
fileName2 = "/Users/juan/Documents/testData/forwardmodel.msh" # input mesh
mesh = Mesh.TensorMesh._readUBC_3DMesh(fileName2) # Read in/create mesh
print("Starting forward modeling")
start = clock()
# Define model Background
rx = getRxData() # rx locations
tx = getTxData() # tx locations
survey_dc = generateSurvey(rx, tx, 45, 55) # create survey object
survey_dc.survey_type = "pole-dipole"
survey_dc.getABMN_locations() # get locations
# survey_dc = IO.from_ambn_locations_to_survey(
# survey_dc.a_locations, survey_dc.b_locations,
# survey_dc.m_locations, survey_dc.n_locations,
# survey_type, data_dc_type='volt', data_ip_type='volt'
# )
uniq = Utils.uniqueRows(
np.vstack((survey_dc.a_locations, survey_dc.b_locations,
survey_dc.m_locations, survey_dc.n_locations)))
electrode_locations = uniq[0] # assign
actinds = Utils.surface2ind_topo(mesh, electrode_locations,
method='cubic') # active indicies
# survey_dc.drapeTopo(mesh, actinds)
IO.a_locations = survey_dc.a_locations.copy()
IO.b_locations = survey_dc.b_locations.copy()
IO.m_locations = survey_dc.m_locations.copy()
IO.n_locations = survey_dc.n_locations.copy() # drape topo
IO.data_dc_type = 'volt'
IO.G = IO.geometric_factor(survey_dc)
# =============================================================================
# create sphere for ice representation
x0 = (np.max(mesh.gridCC[:, 0]) +
np.min(mesh.gridCC[:, 0])) / 2. + 50 # x0 center point of sphere
y0 = (np.max(mesh.gridCC[:, 1]) +
np.min(mesh.gridCC[:, 1])) / 2. - 50 # y0 center point of sphere
z0 = 2350 # x0 center point of sphere
# (np.max(mesh.gridCC[:, 2]) + np.min(mesh.gridCC[:, 2])) / 2.
r0 = 500 # radius of sphere
print(x0, y0, z0)
csph = (np.sqrt((mesh.gridCC[:, 0] - x0)**2. +
(mesh.gridCC[:, 1] - y0)**2. +
(mesh.gridCC[:, 2] - z0)**2.)) < r0 # indicies of sphere
# sphere done =================================================================
# ============================================================================
# Create model
mx = np.ones(mesh.nC) * 0.018 # chargeability
sigma = np.ones(mesh.nC) * 1. / 15000.
# create dipping structure parameters
theta = 45. * np.pi / 180. # dipping angle
x0_d = 374700.
x1_d = 375000.
y0_d = 6275850.
y0_1d = 900. * np.sin(theta) + y0_d
y1_d = 6275900.
y1_1d = 900. * np.sin(theta) + y1_d
z0_d = 1900.
z1_d = z0_d - (900. * np.cos(theta))
m_ = (z0_d - z1_d) / (y0_1d - y0_d) # slope of dip
# loop through mesh and assign dipping structure conductivity
for idx in range(mesh.nC):
if z1_d <= mesh.gridCC[idx, 2] <= z0_d:
if (x0_d <= mesh.gridCC[idx, 0] <= x1_d):
yslope1 = y0_d + (1. / m_) * (mesh.gridCC[idx, 2] - z0_d)
yslope2 = y1_d + (1. / m_) * (mesh.gridCC[idx, 2] - z0_d)
if yslope1 <= mesh.gridCC[idx, 1] <= yslope2:
mx[idx] = 0.035
sigma[idx] = 1. / 300.
# mx[csph] = ((0.025) *
# np.ones_like(mx[csph])) # set sphere values
mx[~actinds] = 1. / 1e8 # flag air values
# sigma[csph] = ((5000.) *
# np.ones_like(sigma[csph])) # set sphere values
sigma[~actinds] = 1. / 1e8 # flag air values
rho = 1. / sigma
stop = clock()
print(stop)
# plot results
# Show the true conductivity model
if plotIt:
ncy = mesh.nCy
ncz = mesh.nCz
ncx = mesh.nCx
print(mesh.nC)
clim = [0, 0.04]
fig, ax = plt.subplots(2, 2, figsize=(12, 6))
ax = Utils.mkvc(ax)
dat = mesh.plotSlice(((mx)),
ax=ax[0],
normal='Z',
clim=clim,
ind=int(ncz / 2 - 14),
pcolorOpts={"cmap": "jet"})
ax[0].plot(rx[:, 0], rx[:, 1], 'or')
ax[0].plot(tx[:, 0], tx[:, 1], 'dk')
mesh.plotSlice(((mx)),
ax=ax[1],
normal='Y',
clim=clim,
ind=int(ncy / 2 + 2),
pcolorOpts={"cmap": "jet"})
mesh.plotSlice(((mx)),
ax=ax[2],
normal='X',
clim=clim,
ind=int(ncx / 2 + 4),
pcolorOpts={"cmap": "jet"})
mesh.plotSlice(((mx)),
ax=ax[3],
normal='X',
clim=clim,
ind=int(ncx / 2 + 8),
pcolorOpts={"cmap": "jet"})
cbar_ax = fig.add_axes([0.82, 0.15, 0.05, 0.7])
cb = plt.colorbar(dat[0], ax=cbar_ax)
fig.subplots_adjust(right=0.85)
cb.set_label('V/V')
cbar_ax.axis('off')
plt.show()
# print(mtrue.min(), mtrue.max())
# clim = [0, 20000]
# fig, ax = plt.subplots(2, 2, figsize=(12, 6))
# ax = Utils.mkvc(ax)
# dat = mesh.plotSlice(((mtrue)), ax=ax[0], normal='Z', clim=clim,
# ind=int(ncz / 2 - 4), pcolorOpts={"cmap": "jet"})
# ax[0].plot(rx[:, 0], rx[:, 1], 'or')
# mesh.plotSlice(((mtrue)), ax=ax[1], normal='Y', clim=clim,
# ind=int(ncy / 2), pcolorOpts={"cmap": "jet"})
# mesh.plotSlice(((mtrue)), ax=ax[2], normal='X', clim=clim,
# ind=int(ncx / 2 + 4), pcolorOpts={"cmap": "jet"})
# mesh.plotSlice(((mtrue)), ax=ax[3], normal='X', clim=clim,
# ind=int(ncx / 2 + 8), pcolorOpts={"cmap": "jet"})
# cbar_ax = fig.add_axes([0.82, 0.15, 0.05, 0.7])
# cb = plt.colorbar(dat[0], ax=cbar_ax)
# fig.subplots_adjust(right=0.85)
# cb.set_label('rho')
# cbar_ax.axis('off')
# plt.show()
# print(error.size, survey_ip.obs.size)
# error = np.asarray(survey_ip.dobs) * (np.random.randint(-1, 2, survey_ip.dobs) / 20.)
# survey_ip.dobs = survey_ip.dobs + error
# Use Exponential Map: m = log(rho)
actmap = Maps.InjectActiveCells(mesh,
indActive=actinds,
valInactive=np.log(1e8))
mapping = Maps.ExpMap(mesh) * actmap
# Generate mtrue_dc for resistivity
mtrue_dc = np.log(rho[actinds])
# Generate 3D DC problem
# "CC" means potential is defined at center
prb = DC.Problem3D_CC(mesh, rhoMap=mapping, storeJ=False, Solver=Solver)
# Pair problem with survey
# try:
prb.pair(survey_dc)
# except:
# survey_dc.unpair()
# prb.pair(survey_dc)
survey_dc.dpred(mtrue_dc)
# Make synthetic DC data with 5% Gaussian noise
dtrue_dc = survey_dc.makeSyntheticData(mtrue_dc, std=0.05, force=True)
IO.data_dc = dtrue_dc
# Generate mtrue_ip for chargability
mtrue_ip = mx[actinds]
# Generate 3D DC problem
# "CC" means potential is defined at center
prb_ip = IP.Problem3D_CC(mesh,
etaMap=actmap,
storeJ=False,
rho=rho,
Solver=Solver)
survey_ip = IP.from_dc_to_ip_survey(survey_dc, dim="3D")
survey_ip.survey_type = "pole-dipole"
survey_ip.getABMN_locations()
prb_ip.pair(survey_ip)
survey_ip.dpred(mtrue_ip)
dtrue_ip = survey_ip.makeSyntheticData(mtrue_ip, std=0.05)
survey_ip.std = np.ones_like(dtrue_ip) * 0.05
survey_ip.eps = np.ones_like(dtrue_ip) * 10**(-4)
IO.data_ip = dtrue_ip
DC.Utils.writeUBC_DCobs("fmip.obs", survey_ip, 3, 'GENERAL', 'pole-dipole')
from SimPEG import SolverLU as Solver
# filename = "/Users/juan/Documents/testData/KSA/3D_QC_Preliminary.DAT"
filename1 = "/Users/juan/Documents/testData/KSA/ksa3D-DC.con"
filenameObs = "/Users/juan/Documents/testData/KSA/ksa3D-IP.obs"
fileName2 = "/Users/juan/Documents/testData/Mesh.msh"
mesh = Mesh.TensorMesh._readUBC_3DMesh(fileName2)
rho_est = mesh._readModelUBC_3D(mesh, filename1)
# patch = tools.loadDias(filename)
survey_ip = DC.Utils.readUBC_DC3Dobs(filenameObs)
survey_ip.survey_type = "dipole-dipole"
# survey_ip.data_dc_type = 'volt'
survey_ip.getABMN_locations()
uniq = Utils.uniqueRows(
np.vstack((survey_ip.a_locations, survey_ip.b_locations,
survey_ip.m_locations, survey_ip.n_locations)))
electrode_locations = uniq[0] # assign
actinds = Utils.surface2ind_topo(mesh, electrode_locations,
method='cubic') # active indicies
survey_ip.drapeTopo(mesh, actinds)
# Use Exponential Map: m = log(rho)
actmap = Maps.InjectActiveCells(mesh,
indActive=actinds,
valInactive=np.log(1e8))
mapping = Maps.ExpMap(mesh) * actmap
# ip inversion =======================================
prb_ip = IP.Problem3D_CC(mesh,
etaMap=actmap,
