def gaTdem1dsen(datapoint, model1d, ix=None, modelChanged=True):
""" Compute the sensitivty matrix for a 1D layered earth model, optionally compute the responses for only the layers in ix """
# Unfortunately the code requires forward modelled data to compute the
# sensitivity if the model has changed since last time
if modelChanged:
E = Earth(model1d.par[:], model1d.thk[:-1])
G = Geometry(datapoint.z[0], datapoint.T.roll, datapoint.T.pitch,
datapoint.T.yaw, datapoint.loopOffset[0],
datapoint.loopOffset[1], datapoint.loopOffset[2],
datapoint.R.roll, datapoint.R.pitch, datapoint.R.yaw)
for i in range(datapoint.nSystems):
datapoint.system[i].forwardmodel(G, E)
if (ix is None
): # Generate a full matrix if the layers are not specified
ix = range(np.int(model1d.nCells[0]))
J = np.zeros([datapoint.nWindows, np.int(model1d.nCells[0])])
else: # Partial matrix for specified layers
J = np.zeros([datapoint.nWindows, np.size(ix)])
for j in range(datapoint.nSystems): # For each system
iSys = datapoint._systemIndices(j)
for i in range(np.size(ix)): # For the specified layers
tmp = datapoint.system[j].derivative(
datapoint.system[j].CONDUCTIVITYDERIVATIVE, ix[i] + 1)
# Store the necessary component
J[iSys, i] = -model1d.par[ix[i]] * tmp.SZ[:]
datapoint.J = J[datapoint.active, :]
return datapoint.J
def _BrodieForward(self, mod):
# Generate the Brodie Earth class
E = Earth(mod.par[:], mod.thk[:-1])
# Generate the Brodie Geometry class
G = Geometry(self.z[0], self.T.roll, self.T.pitch, self.T.yaw, -12.64,
0.0, 2.11, self.R.roll, self.R.pitch, self.R.yaw)
# Forward model the data for each system
iJ0 = 0
for i in range(self.nSystems):
iJ1 = iJ0 + self.sys[i].nwindows()
fm = self.sys[i].forwardmodel(G, E)
self.p[iJ0:iJ1] = -fm.SZ[:] # Store the necessary component
iJ0 = iJ1
def _BrodieForward(self, mod):
# Generate the Brodie Earth class
E = Earth(mod.par[:], mod.thk[:-1])
# Generate the Brodie Geometry class
G = Geometry(self.z[0], self.T.roll, self.T.pitch, self.T.yaw, -12.64,
0.0, 2.11, self.R.roll, self.R.pitch, self.R.yaw)
# Forward model the data for each system
for i in range(self.nSystems):
iSys = self._systemIndices(i)
fm = self.system[i].forwardmodel(G, E)
self._predictedData[
iSys] = -fm.SZ[:] # Store the necessary component
def gaTdem1dfwd(datapoint, model1d):
# Generate the Brodie Earth class
E = Earth(model1d.par[:], model1d.thk[:-1])
# Generate the Brodie Geometry class
G = Geometry(datapoint.z[0],
datapoint.transmitter.roll, datapoint.transmitter.pitch, datapoint.transmitter.yaw,
datapoint.loopOffset[0], datapoint.loopOffset[1], datapoint.loopOffset[2],
datapoint.receiver.roll, datapoint.receiver.pitch, datapoint.receiver.yaw)
# Forward model the data for each system
for i in range(datapoint.nSystems):
iSys = datapoint._systemIndices(i)
fm = datapoint.system[i].forwardmodel(G, E)
datapoint._predictedData[iSys] = -fm.SZ[:] # Store the necessary component
def fm_dlogc(self, mod):
# Generate the Brodie Earth class
E = Earth(mod.par[:], mod.thk[:-1])
# ####lg.debug('Parameters: '+str(mod.par))
# ####lg.debug('Thickness: '+str(mod.thk[:-1]))
# Generate the Brodie Geometry class
# ####lg.debug('Geometry: '+str([self.z[0],self.T.roll,self.T.pitch,self.T.yaw,-12.64,0.0,2.11,self.R.roll,self.R.pitch,self.R.yaw]))
G = Geometry(self.z[0], self.T.roll, self.T.pitch, self.T.yaw, -
12.615, 0.0, 2.16, self.R.roll, self.R.pitch, self.R.yaw)
# Forward model the data for each system
iJ0 = 0
for i in range(self.nSystems):
iJ1 = iJ0 + self.sys[i].nwindows()
dummy = self.sys[i].forward(G, E)
# self.p[iJ0:iJ1]=-fm.SZ[:]
# iJ0=iJ1
return fm
def _sensitivity1D(self, mod, ix=None, scale=False, modelChanged=True):
""" Compute the sensitivty matrix for a 1D layered earth model, optionally compute the responses for only the layers in ix """
# Unfortunately the code requires forward modelled data to compute the
# sensitivity if the model has changed since last time
if modelChanged:
E = Earth(mod.par[:], mod.thk[:-1])
G = Geometry(self.z[0], self.T.roll, self.T.pitch, self.T.yaw,
-12.64, 0.0, 2.11, self.R.roll, self.R.pitch,
self.R.yaw)
for i in range(self.nSystems):
self.sys[i].forwardmodel(G, E)
if (ix is None
): # Generate a full matrix if the layers are not specified
ix = range(mod.nCells[0])
J = np.zeros([self.nWindows, mod.nCells[0]])
else: # Partial matrix for specified layers
J = np.zeros([self.nWindows, len(ix)])
iJ0 = 0
for j in range(self.nSystems): # For each system
iJ1 = iJ0 + self.sys[j].nwindows()
for i in range(len(ix)): # For the specified layers
tmp = self.sys[j].derivative(
self.sys[j].CONDUCTIVITYDERIVATIVE, ix[i] + 1)
# Store the necessary component
J[iJ0:iJ1, i] = -mod.par[ix[i]] * tmp.SZ[:]
iJ0 = iJ1
if scale:
iJ0 = 0
for j in range(self.nSystems): # For each system
iJ1 = iJ0 + self.sys[j].nwindows()
for i in range(len(ix)): # For the specified layers
# Scale the sensitivity matix rows by the data weights if
# required
J[iJ0:iJ1, i] /= self.s[iJ0:iJ1]
iJ0 = iJ1
J = J[self.iActive, :]
return J
#Print the window times
S.windows.print();
if True:
#Plot the waveform and window positions
fig1 = plt.figure(1);
#S.waveform.print(); #Too much printing
S.waveform_windows_plot(fig1);
if display_plots: plt.show(fig1);
if save_pdfs: plt.savefig("figure1.pdf", dpi=300, facecolor='w', edgecolor='w', orientation='portrait', papertype=None, format=None, transparent=False, bbox_inches=None, pad_inches=0.1, frameon=None);
#Set the conductivity and thicknesses
conductivity = [0.01, 0.1, 0.001];
thickness = [40, 20];
E = Earth(conductivity,thickness);
E.print();
#Set the system geometry
G = Geometry(tx_height=35, txrx_dx = -12.62, txrx_dz = +2.16);
G.print();
#Run a few random forward models in a loop
t1=time.clock()
for i in range(10):
conductivity[0] = 10**(random.uniform(-3, 0));
conductivity[1] = 10**(random.uniform(-3, 0));
conductivity[2] = 10**(random.uniform(-3, 0));
thickness = [40, 20];
E = Earth(conductivity,thickness);
fm = S.forwardmodel(G,E);
plt.savefig("figure1.pdf",
dpi=300,
facecolor='w',
edgecolor='w',
orientation='portrait',
papertype=None,
format=None,
transparent=False,
bbox_inches=None,
pad_inches=0.1,
frameon=None)
#Set the conductivity and thicknesses
conductivity = [0.01, 0.1, 0.001]
thickness = [40, 20]
E = Earth(conductivity, thickness)
E.print()
#Set the system geometry
G = Geometry(tx_height=35, txrx_dx=-12.62, txrx_dz=+2.16)
G.print()
#Run a few random forward models in a loop
t1 = time.clock()
for i in range(10):
conductivity[0] = 10**(random.uniform(-3, 0))
conductivity[1] = 10**(random.uniform(-3, 0))
conductivity[2] = 10**(random.uniform(-3, 0))
thickness = [40, 20]
E = Earth(conductivity, thickness)
fm = S.forwardmodel(G, E)