fid.write('REF_MOD VALUE %e\n' % ref_mod)
fid.write('ALPHA DEFAULT\n')
fid.write('WEIGHT DEFAULT\n')
fid.write('STORE_ALL_MODELS FALSE\n')
fid.write('INVMODE SVD\n')
fid.write('USE_MREF TRUE\n')
fid.close()
print ii
os.chdir(inv_dir)
os.system('dcinv2d ' + inp_file)
#%%
#Load model
mout.append(DC.readUBC_DC2DModel(inv_dir + dsep + 'dcinv2d.con'))
dpre = DC.readUBC_DC2Dpre(inv_dir + dsep + 'dcinv2d.pre')
dout.append(dpre['DCsurvey'])
#DCpre.dobs = (DC2D.dobs - DCpre.dobs) / DC2D.std
#%% Add the extra
# Cycle through the lines and invert len(uniqueID)
fig = plt.figure(figsize=(8, 5))
ax1 = plt.subplot(1, 2, 1)
ax2 = plt.subplot(1, 2, 2)
def animate(ii):
fid.write('CHIFACT 1 %f\n' % chifact)
fid.write('TOPO DEFAULT %s \n')
fid.write('INIT_MOD VALUE %e\n' % (str_mod))
fid.write('REF_MOD VALUE %e\n' % (ref_mod))
fid.write('ALPHA VALUE %f %f %F\n' % (1. / dx**4., 1, 3))
fid.write('WEIGHT DEFAULT\n')
fid.write('STORE_ALL_MODELS FALSE\n')
fid.write('INVMODE CG\n')
fid.write('USE_MREF TRUE\n')
fid.close()
os.chdir(inv_dir)
os.system('dcinv2d ' + inp_file)
#Load model
minv = DC.readUBC_DC2DModel(inv_dir + dsep + 'dcinv2d.con')
#%% Compute DOI
# DOI = np.abs(invmod[0] - invmod[1]) / np.abs(refmod[0] - refmod[1])
# # Normalize between [0 1]
# DOI = DOI - np.min(DOI)
# DOI = (1.- DOI/np.max(DOI))
# DOI[DOI > cutoff] = 1
#
# plt.figure()
# plt.xlim([survey2D.srcList[0].loc[0][0]-a,survey2D.srcList[-1].rxList[-1].locs[-1][0][0]+a])
# plt.ylim([mesh2d.vectorNy[-1]-dl_len/2,mesh2d.vectorNy[-1]+2*dx])
# plt.gca().set_aspect('equal', adjustable='box')
#
# plt.pcolormesh(mesh2d.vectorNx,mesh2d.vectorNy,DOI,alpha=1)
# cbar = plt.colorbar(format = '%.2f',fraction=0.02)
def animate(ii):
removeFrame()
# Grab current line and
indx = np.where(lineID == ii)[0]
srcLeft = []
obs_l = []
srcRight = []
obs_r = []
obs = []
srcList = []
# Split the obs file into left and right
for jj in range(len(indx)):
# Grab corresponding data
obs = np.hstack([obs, dobs2D.dobs[dataID == indx[jj]]])
#std = dobs2D.std[dataID==indx[jj]]
srcList.append(dobs2D.srcList[indx[jj]])
Tx = dobs2D.srcList[indx[jj]].loc
Rx = dobs2D.srcList[indx[jj]].rxList[0].locs
# Create mid-point location
Cmid = (Tx[0][0] + Tx[1][0]) / 2
Pmid = (Rx[0][:, 0] + Rx[1][:, 0]) / 2
ileft = Pmid < Cmid
iright = Pmid >= Cmid
temp = np.zeros(len(ileft))
temp[ileft] = 1
obs_l = np.hstack([obs_l, temp])
temp = np.zeros(len(iright))
temp[iright] = 1
obs_r = np.hstack([obs_r, temp])
if np.any(ileft):
rx = DC.RxDipole(Rx[0][ileft, :], Rx[1][ileft, :])
srcLeft.append(DC.SrcDipole([rx], Tx[0], Tx[1]))
#std_l = np.hstack([std_l,std[ileft]])
if np.any(iright):
rx = DC.RxDipole(Rx[0][iright, :], Rx[1][iright, :])
srcRight.append(DC.SrcDipole([rx], Tx[0], Tx[1]))
#obs_r = np.hstack([obs_r,iright])
#std_r = np.hstack([std_r,std[iright]])
DC2D_full = DC.SurveyDC(srcList)
DC2D_full.dobs = np.asarray(obs)
DC2D_full.std = DC2D_full.dobs * 0.
DC2D_full.std[obs_l ==
1] = np.abs(DC2D_full.dobs[obs_l == 1]) * 0.02 + 2e-5
DC2D_full.std[obs_r ==
1] = np.abs(DC2D_full.dobs[obs_r == 1]) * 0.06 + 4e-5
DC2D_l = DC.SurveyDC(srcLeft)
DC2D_l.dobs = np.asarray(obs[obs_l == 1])
DC2D_l.std = np.abs(np.asarray(DC2D_l.dobs)) * 0.05 + 2e-5
DC2D_r = DC.SurveyDC(srcRight)
DC2D_r.dobs = np.asarray(obs[obs_r == 1])
DC2D_r.std = np.abs(np.asarray(DC2D_r.dobs)) * 0.05 + 2e-5
#DC.plot_pseudoSection(dobs2D,lineID, np.r_[0,1],'pdp')
id_lbe = int(DCsurvey.srcList[indx[jj]].loc[0][1])
mesh3d = Mesh.TensorMesh([hx, 1, hz],
x0=(-np.sum(padx) + np.min(srcMat[0][:, 0]),
id_lbe, np.max(srcMat[0][0, 2]) - np.sum(hz)))
Mesh.TensorMesh.writeUBC(mesh3d,
home_dir + dsep + 'Mesh' + str(id_lbe) + '.msh')
global ax1, ax2, ax3, ax5, ax6, fig
ax2 = plt.subplot(3, 2, 2)
ph = DC.plot_pseudoSection(DC2D_r, ax2, stype='pdp', colorbar=False)
ax2.set_title('Observed P-DP', fontsize=10)
plt.xlim([xmin, xmax])
plt.ylim([zmin, zmax])
plt.gca().set_aspect('equal', adjustable='box')
ax2.set_xticklabels([])
ax2.set_yticklabels([])
ax1 = plt.subplot(3, 2, 1)
DC.plot_pseudoSection(DC2D_l,
ax1,
stype='pdp',
clim=(ph[0].get_clim()[0], ph[0].get_clim()[1]),
colorbar=False)
ax1.set_title('Observed DP-P', fontsize=10)
plt.xlim([xmin, xmax])
plt.ylim([zmin, zmax])
plt.gca().set_aspect('equal', adjustable='box')
ax1.set_xticklabels([])
z = np.linspace(np.min(ph[2]), np.max(ph[2]), 5)
z_label = np.linspace(20, 1, 5)
ax1.set_yticks(map(int, z))
ax1.set_yticklabels(map(str, map(int, z_label)), size=8)
ax1.set_ylabel('n-spacing', fontsize=8)
#%% Add labels
bbox_props = dict(boxstyle="circle,pad=0.3", fc="r", ec="k", lw=1)
ax2.text(0.00,
1,
'A',
transform=ax2.transAxes,
ha="left",
va="center",
size=6,
bbox=bbox_props)
bbox_props = dict(boxstyle="circle,pad=0.3", fc="y", ec="k", lw=1)
ax2.text(0.1,
1,
'M',
transform=ax2.transAxes,
ha="left",
va="center",
size=6,
bbox=bbox_props)
bbox_props = dict(boxstyle="circle,pad=0.3", fc="g", ec="k", lw=1)
ax2.text(0.2,
1,
'N',
transform=ax2.transAxes,
ha="left",
va="center",
size=6,
bbox=bbox_props)
bbox_props = dict(boxstyle="circle,pad=0.3", fc="g", ec="k", lw=1)
ax1.text(0.00,
1,
'N',
transform=ax1.transAxes,
ha="left",
va="center",
size=6,
bbox=bbox_props)
bbox_props = dict(boxstyle="circle,pad=0.3", fc="y", ec="k", lw=1)
ax1.text(0.1,
1,
'M',
transform=ax1.transAxes,
ha="left",
va="center",
size=6,
bbox=bbox_props)
bbox_props = dict(boxstyle="circle,pad=0.3", fc="r", ec="k", lw=1)
ax1.text(0.2,
1,
'A',
transform=ax1.transAxes,
ha="left",
va="center",
size=6,
bbox=bbox_props)
# Run both left and right survey seperately
survey = DC2D_full
# Export data file
DC.writeUBC_DCobs(inv_dir + dsep + obsfile2d, survey, '2D', 'SIMPLE')
# Write input file
fid = open(inv_dir + dsep + inp_file, 'w')
fid.write('OBS LOC_X %s \n' % obsfile2d)
fid.write('MESH FILE %s \n' % mshfile2d)
fid.write('CHIFACT 1 \n')
fid.write('TOPO DEFAULT \n')
fid.write('INIT_MOD VALUE %e\n' % ini_mod)
fid.write('REF_MOD VALUE %e\n' % ref_mod)
fid.write('ALPHA VALUE %f %f %F\n' % (1. / dx**4., 1, 1))
fid.write('WEIGHT DEFAULT\n')
fid.write('STORE_ALL_MODELS FALSE\n')
fid.write('INVMODE SVD\n')
#fid.write('CG_PARAM 200 1e-4\n')
fid.write('USE_MREF FALSE\n')
#fid.write('BOUNDS VALUE 1e-4 1e+2\n')
fid.close()
os.chdir(inv_dir)
os.system('dcinv2d ' + inp_file)
#%% Load model and predicted data
minv = DC.readUBC_DC2DModel(inv_dir + dsep + 'dcinv2d.con')
minv = np.reshape(minv, (mesh2d.nCy, mesh2d.nCx))
Mesh.TensorMesh.writeModelUBC(
mesh3d, home_dir + dsep + 'Model' + str(id_lbe) + '.con', minv.T)
dpre = DC.readUBC_DC2Dpre(inv_dir + dsep + 'dcinv2d.pre')
DCpre = dpre['DCsurvey']
DCtemp = DC2D_l
DCtemp.dobs = DCpre.dobs[obs_l == 1]
ax5 = plt.subplot(3, 2, 3)
DC.plot_pseudoSection(DCtemp,
ax5,
stype='pdp',
clim=(ph[0].get_clim()[0], ph[0].get_clim()[1]),
colorbar=False)
ax5.set_title('Predicted', fontsize=10)
plt.xlim([xmin, xmax])
plt.ylim([zmin, zmax])
plt.gca().set_aspect('equal', adjustable='box')
ax5.set_xticklabels([])
z = np.linspace(np.min(ph[2]), np.max(ph[2]), 5)
z_label = np.linspace(20, 1, 5)
ax5.set_yticks(map(int, z))
ax5.set_yticklabels(map(str, map(int, z_label)), size=8)
ax5.set_ylabel('n-spacing', fontsize=8)
DCtemp = DC2D_r
DCtemp.dobs = DCpre.dobs[obs_r == 1]
ax6 = plt.subplot(3, 2, 4)
DC.plot_pseudoSection(DCtemp,
ax6,
stype='pdp',
clim=(ph[0].get_clim()[0], ph[0].get_clim()[1]),
colorbar=False)
ax6.set_title('Predicted', fontsize=10)
plt.xlim([xmin, xmax])
plt.ylim([zmin, zmax])
plt.gca().set_aspect('equal', adjustable='box')
ax6.set_xticklabels([])
ax6.set_yticklabels([])
pos = ax6.get_position()
cbarax = fig.add_axes([
pos.x0 + 0.325, pos.y0 + 0.2, pos.width * 0.1, pos.height * 0.5
]) ## the parameters are the specified position you set
cb = fig.colorbar(ph[0],
cax=cbarax,
orientation="vertical",
ax=ax6,
ticks=np.linspace(ph[0].get_clim()[0],
ph[0].get_clim()[1], 4),
format="$10^{%.1f}$")
cb.set_label("App. Cond. (S/m)", size=8)
ax3 = plt.subplot(3, 1, 3)
ax3.set_title('2-D Model (S/m)', fontsize=10)
ax3.set_xticks(map(int, x))
ax3.set_xticklabels(map(str, map(int, x)))
ax3.set_xlabel('Easting (m)', fontsize=8)
ax3.set_yticks(map(int, z))
ax3.set_yticklabels(map(str, map(int, z)), rotation='vertical')
ax3.set_ylabel('Depth (m)', fontsize=8)
plt.xlim([xmin, xmax])
plt.ylim([zmin / 2, zmax])
plt.gca().set_aspect('equal', adjustable='box')
ph2 = plt.pcolormesh(mesh2d.vectorNx,
mesh2d.vectorNy,
np.log10(minv),
vmin=vmin,
vmax=vmax)
plt.gca().tick_params(axis='both', which='major', labelsize=8)
plt.draw()
for ss in range(survey.nSrc):
Tx = survey.srcList[ss].loc[0]
plt.scatter(Tx[0], mesh2d.vectorNy[-1] + 10, s=10)
pos = ax3.get_position()
ax3.set_position([pos.x0 + 0.025, pos.y0, pos.width, pos.height])
pos = ax3.get_position()
cbarax = fig.add_axes([
pos.x0 + 0.65, pos.y0 + 0.01, pos.width * 0.05, pos.height * 0.75
]) ## the parameters are the specified position you set
cb = fig.colorbar(ph2,
cax=cbarax,
orientation="vertical",
ax=ax4,
ticks=np.linspace(vmin, vmax, 4),
format="$10^{%.1f}$")
cb.set_label("Conductivity (S/m)", size=8)
pos = ax1.get_position()
ax1.set_position([pos.x0 + 0.03, pos.y0, pos.width, pos.height])
pos = ax5.get_position()
ax5.set_position([pos.x0 + 0.03, pos.y0, pos.width, pos.height])
pos = ax2.get_position()
ax2.set_position([pos.x0 - 0.03, pos.y0, pos.width, pos.height])
pos = ax6.get_position()
ax6.set_position([pos.x0 - 0.03, pos.y0, pos.width, pos.height])
#%% Add the extra
bbox_props = dict(boxstyle="rarrow,pad=0.3", fc="w", ec="k", lw=2)
ax2.text(0.01, (float(ii) + 1.) / (len(uniqueID) + 2),
'N: ' + str(id_lbe),
transform=fig.transFigure,
ha="left",
va="center",
size=8,
bbox=bbox_props)
mrk_props = dict(boxstyle="square,pad=0.3", fc="w", ec="k", lw=2)
ax2.text(0.01,
0.9,
'Line ID#',
transform=fig.transFigure,
ha="left",
va="center",
size=8,
bbox=mrk_props)
mrk_props = dict(boxstyle="square,pad=0.3", fc="b", ec="k", lw=2)
for jj in range(len(uniqueID)):
ax2.text(0.1, (float(jj) + 1.) / (len(uniqueID) + 2),
".",
transform=fig.transFigure,
ha="right",
va="center",
size=8,
bbox=mrk_props)
mrk_props = dict(boxstyle="square,pad=0.3", fc="r", ec="k", lw=2)
ax2.text(0.1, (float(ii) + 1.) / (len(uniqueID) + 2),
".",
transform=fig.transFigure,
ha="right",
va="center",
size=8,
bbox=mrk_props)
dsep = '\\'
# Forward solver
slvr = 'BiCGStab' #'LU'
# Preconditioner
pcdr = 'Jacobi' #'Gauss-Seidel'#
# Number of padding cells to remove from plotting
padc = 15
# Load UBC mesh 2D
mesh = DC.readUBC_DC2DMesh(home_dir + dsep + msh_file)
# Load model
model = DC.readUBC_DC2DModel(home_dir + dsep + mod_file)
# load obs file
dcfile = DC.readUBC_DC3Dobs(home_dir + dsep + obs_file)
survey = dcfile['DCsurvey']
survey2D = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc), 'Xloc')
#%% Create system
#Set boundary conditions
mesh.setCellGradBC('neumann')
Div = mesh.faceDiv
Grad = mesh.cellGrad
Msig = Utils.sdiag(1./(mesh.aveF2CC.T*(1./model)))
A = Div*Msig*Grad