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Remove unnecessary files for pull request

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D Fournier
2016-02-04 11:11:14 -08:00
parent 34acd4876b
commit e2f30ffbb6
61 changed files with 179 additions and 418973 deletions
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simpegDCIP/Dev/DC2D_Demo_HTML_anim.py
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import os
from SimPEG import *
import simpegDCIP as DC
import pylab as plt
from matplotlib import animation
from JSAnimation import HTMLWriter
import time
import re
#from readUBC_DC2DMesh import readUBC_DC2DMesh
#from readUBC_DC2DModel import readUBC_DC2DModel
#from readUBC_DC2DLoc import readUBC_DC2DLoc
#from convertObs_DC3D_to_2D import convertObs_DC3D_to_2D
#from readUBC_DC3Dobs import readUBC_DC3Dobs
#%%
home_dir = 'C:\\Users\\dominiquef.MIRAGEOSCIENCE\\ownCloud\\Research\\Modelling\\Synthetic\\Two_Sphere'
msh_file = 'Mesh_2D.msh'
mod_file = 'Model_2D.con'
obs_file = 'FWR_data3D.dat'
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
[Tx,Rx,d,wd] = DC.readUBC_DC3Dobs(home_dir + dsep + obs_file)
[Tx, Rx] = DC.convertObs_DC3D_to_2D(Tx,Rx)
#%% 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
# Change one corner to deal with nullspace
A[0,0] = 1
A = sp.csc_matrix(A)
start_time = time.time()
if re.match(slvr,'BiCGStab'):
# Create Jacobi Preconditioner
if re.match(pcdr,'Jacobi'):
dA = A.diagonal()
P = sp.spdiags(1/dA,0,A.shape[0],A.shape[0])
# Create Gauss-Seidel Preconditioner
elif re.match(pcdr,'Gauss-Seidel'):
LD = sp.tril(A,k=0)
#LDinv = sp.linalg.splu(LD)
elif re.match(slvr,'LU'):
# Factor A matrix
Ainv = sp.linalg.splu(A)
print("LU DECOMP--- %s seconds ---" % (time.time() - start_time))
#%% Create SimPEG objects
# Create sub-mesh for plotting
hx = mesh.hx
hy = mesh.hy
hx_sub = hx[padc:-padc]
hy_sub = hy[padc:]
mesh_sub = Mesh.TensorMesh([hx_sub,hy_sub],(mesh.vectorNx[padc], mesh.vectorNy[padc]))
model_sub = model.reshape(mesh.nCy,mesh.nCx)
model_sub = mkvc(model_sub[padc:,padc:-padc].T)
xx = mesh_sub.vectorCCx
yy = mesh_sub.vectorCCy
#%% Solve
#txii = range(50,1950,100)
#jx_CC_sub = np.zeros((len(txii),mesh_sub.nCx,mesh_sub.nCy))
#jy_CC_sub = np.zeros((len(txii),mesh_sub.nCx,mesh_sub.nCy))
fig = plt.figure(figsize=(10,5))
axs = plt.axes(ylim = (yy[0],yy[-1]+mesh.hy[-1]*2), xlim = (xx[0],xx[-1]))#
plt.tight_layout(pad=0.4, w_pad=0.5, h_pad=1.0)
plt.ylim(yy[0],yy[-1]+mesh.hy[-1]*2)
plt.xlim(xx[0],xx[-1])
#im1 = axs.pcolormesh([],[],[], alpha=0.75,extent = (xx[0],xx[-1],yy[-1],yy[0]),interpolation='nearest',vmin=-1e-2, vmax=1e-2)
#im2 = axs.pcolormesh([],[],[],alpha=0.2,extent = (xx[0],xx[-1],yy[-1],yy[0]),interpolation='nearest',cmap='gray')
im1 = axs.pcolormesh(mesh_sub.vectorCCx,mesh_sub.vectorCCy,np.zeros((mesh_sub.nCy,mesh_sub.nCx)), alpha=0.75,vmin=-1e-2, vmax=1e-2)
im2 = axs.pcolormesh(mesh_sub.vectorCCx,mesh_sub.vectorCCy,np.zeros((mesh_sub.nCy,mesh_sub.nCx)), alpha=0.75,vmin=-1e-2, vmax=1e-2)
im3 = axs.streamplot(xx, yy, np.zeros((mesh_sub.nCy,mesh_sub.nCx)), np.zeros((mesh_sub.nCy,mesh_sub.nCx)),color='k')
im4 = axs.scatter([],[], c='r', s=200)
im5 = axs.scatter([],[], c='r', s=200)
#==============================================================================
# def init():
# im1.set_data([[],[],[]])
# im2.set_data([[],[],[]])
#
# return [im1]+[im2]
#==============================================================================
def animate(ii):
#for ii in range(len(txii)):
removeStream()
tx = np.asarray(np.c_[Tx[ii],np.ones(Tx[ii].shape[0])*mesh.vectorNy[-1]-1])
inds = Utils.closestPoints(mesh, tx )
RHS = mesh.getInterpolationMat( tx , 'CC').T*( [-1,1] / mesh.vol[inds] )
if re.match(slvr,'BiCGStab'):
if re.match(pcdr,'Jacobi'):
dA = A.diagonal()
P = sp.spdiags(1/dA,0,A.shape[0],A.shape[0])
# Iterative Solve
phi = sp.linalg.bicgstab(P*A,P*RHS, tol=1e-5)
phi = mkvc(phi[0])
elif re.match(slvr,'LU'):
#Direct Solve
phi = Ainv.solve(RHS)
j = -Msig*Grad*phi
j_CC = mesh.aveF2CCV*j
# Compute charge density solving div*grad*phi
Q = -mesh.faceDiv*mesh.cellGrad*phi
jx_CC = j_CC[0:mesh.nC].reshape(mesh.nCy,mesh.nCx)
jy_CC = j_CC[mesh.nC:].reshape(mesh.nCy,mesh.nCx)
#%% Grab only the core for presentation
jx_CC_sub = jx_CC[padc:,padc:-padc]
jy_CC_sub = jy_CC[padc:,padc:-padc]
Q_sub = Q.reshape(mesh.nCy,mesh.nCx)
Q_sub = Q_sub[padc:,padc:-padc]
J_rho = np.sqrt(jx_CC_sub**2 + jy_CC_sub**2)
lw = np.log10(J_rho/J_rho.min())
#axs.imshow(Q_sub,alpha=0.75,extent = (xx[0],xx[-1],yy[-1],yy[0]),interpolation='nearest',vmin=-1e-2, vmax=1e-2)
#axs.imshow(np.log10(model_sub.reshape(mesh_sub.nCy,mesh_sub.nCx)),alpha=0.2,extent = (xx[0],xx[-1],yy[-1],yy[0]),interpolation='nearest',cmap='gray')
global im1
im1 = axs.pcolormesh(mesh_sub.vectorCCx,mesh_sub.vectorCCy,Q_sub, alpha=0.75,vmin=-1e-2, vmax=1e-2)
global im2
im2 = axs.pcolormesh(mesh_sub.vectorCCx,mesh_sub.vectorCCy,np.log10(model_sub.reshape(mesh_sub.nCy,mesh_sub.nCx)), alpha=0.25)
global im3
im3 = axs.streamplot(xx, yy, jx_CC_sub, jy_CC_sub,color='k',linewidth = lw,density=0.5)
global im4
im4 = axs.scatter(tx[0,0],mesh.vectorNy[-1], c='r', s=75, marker='v' )
global im5
im5 = axs.scatter(tx[1,0],mesh.vectorNy[-1], c='b', s=75, marker='v' )
#plt.show()
#im1.set_array(Q_sub)
#im2.set_array(np.log10(model_sub.reshape(mesh_sub.nCy,mesh_sub.nCx)))
#im2.set_array(mesh_sub.vectorCCx, mesh_sub.vectorCCy,jx_CC_sub.T,jy_CC_sub.T)
#return [im1] + [im2]
#%% Create widget
def removeStream():
global im1
im1.remove()
global im2
im2.remove()
global im3
im3.lines.remove()
axs.patches = []
global im4
im4.remove()
global im5
im5.remove()
#def viewInv(msh,iteration):
#, linewidth=lw.T
#%%
#interact(viewInv,msh = mesh_sub, iteration = IntSlider(min=0, max=len(txii)-1 ,step=1, value=0))
# set embed_frames=True to embed base64-encoded frames directly in the HTML
anim = animation.FuncAnimation(fig, animate,
frames=len(Tx), interval=5)
anim.save(home_dir + '\\animation.html', writer=HTMLWriter(embed_frames=True))
simpegDCIP/Dev/DC3D_Demo_TwoSpheres.py
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"""
Experimental script for the forward modeling of DC resistivity data
along survey lines defined by the user. The program loads in a 3D mesh
and model which is used to design pole-dipole or dipole-dipole survey
lines.
Uses SimPEG to generate the forward problem and compute the LU
factorization.
Calls DCIP2D for the inversion of a projected 2D section from the full
3D model.
Assumes flat topo for now...
Created on Mon December 7th, 2015
@author: dominiquef
"""
#%%
from SimPEG import *
import simpegDCIP as DC
import pylab as plt
from pylab import get_current_fig_manager
from scipy.interpolate import griddata
import time
import re
import numpy.matlib as npm
import scipy.interpolate as interpolation
#==============================================================================
# from readUBC_DC3Dobs import readUBC_DC3Dobs
# from readUBC_DC2DModel import readUBC_DC2DModel
# from writeUBC_DCobs import writeUBC_DCobs
# from plot_pseudoSection import plot_pseudoSection
# from gen_DCIPsurvey import gen_DCIPsurvey
# from convertObs_DC3D_to_2D import convertObs_DC3D_to_2D
#==============================================================================
from matplotlib.colors import LogNorm
import os
home_dir = 'C:\\Users\\dominiquef.MIRAGEOSCIENCE\\ownCloud\\Research\\Modelling\\Synthetic\\Two_Sphere'
dsep = '\\'
#from scipy.linalg import solve_banded
# Load UBC mesh 3D
mesh = Mesh.TensorMesh.readUBC(home_dir + '\Mesh_5m.msh')
#mesh = Utils.meshutils.readUBCTensorMesh(home_dir + '\MtIsa_20m.msh')
#mesh = Utils.meshutils.readUBCTensorMesh(home_dir + '\Mesh_50m.msh')
# Load model
#model = Utils.meshutils.readUBCTensorModel(home_dir + '\MtIsa_3D.con',mesh)
#model = Utils.meshutils.readUBCTensorModel(home_dir + '\Synthetic.con',mesh)
#model = Utils.meshutils.readUBCTensorModel(home_dir + '\Lalor_model_50m.con',mesh)
model = Mesh.TensorMesh.readModelUBC(mesh,home_dir + '\TwoSpheres.con')
#model = model**0 * 1e-2
# Specify survey type
stype = 'dpdp'
# Survey parameters
a = 30
b = 30
n = 20
# Forward solver
slvr = 'BiCGStab' #'LU'
# Preconditioner
pcdr = 'Jacobi'#
# Inversion parameter
pct = 0.01
flr = 1e-4
chifact = 100
ref_mod = 1e-2
# DOI threshold
cutoff = 0.8
#%% 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
# Change one corner to deal with nullspace
A[0,0] = 1
A = sp.csc_matrix(A)
start_time = time.time()
if re.match(slvr,'BiCGStab'):
# Create Jacobi Preconditioner
if re.match(pcdr,'Jacobi'):
dA = A.diagonal()
P = sp.spdiags(1/dA,0,A.shape[0],A.shape[0])
#LDinv = sp.linalg.splu(LD)
elif re.match(slvr,'LU'):
# Factor A matrix
Ainv = sp.linalg.splu(A)
print("LU DECOMP--- %s seconds ---" % (time.time() - start_time))
#%% Create survey
# Display top section
top = int(mesh.nCz)-1
plt.figure()
ax_prim = plt.subplot(1,1,1)
mesh.plotSlice(model, ind=top, normal='Z', grid=False, pcolorOpts={'alpha':0.5}, ax =ax_prim)
plt.xlim([423200,423750])
plt.ylim([546350,546650])
plt.gca().set_aspect('equal', adjustable='box')
plt.show()
cfm1=get_current_fig_manager().window
gin=[1]
# Keep creating sections until returns an empty ginput (press enter on figure)
#while bool(gin)==True:
# Bring back the plan view figure and pick points
cfm1.activateWindow()
plt.sca(ax_prim)
# Takes two points from ginput and create survey
#if re.match(stype,'gradient'):
gin = [(423230. , 546440.), (423715. , 546440.)]
#else:
#gin = plt.ginput(2, timeout = 0)
#==============================================================================
# if not gin:
# print 'SimPED - Simulation has ended with return'
# break
#==============================================================================
# Add z coordinate to all survey... assume flat
nz = mesh.vectorNz
var = np.c_[np.asarray(gin),np.ones(2).T*nz[-1]]
# Snap the endpoints to the grid. Easier to create 2D section.
indx = Utils.closestPoints(mesh, var )
endl = np.c_[mesh.gridCC[indx,0],mesh.gridCC[indx,1],np.ones(2).T*nz[-1]]
[Tx, Rx] = DC.gen_DCIPsurvey(endl, mesh, stype, a, b, n)
dl_len = np.sqrt( np.sum((endl[0,:] - endl[1,:])**2) )
dl_x = ( Tx[-1][0,1] - Tx[0][0,0] ) / dl_len
dl_y = ( Tx[-1][1,1] - Tx[0][1,0] ) / dl_len
azm = np.arctan(dl_y/dl_x)
# Plot stations along line
plt.scatter(Tx[0][0,:],Tx[0][1,:],s=20,c='g')
plt.scatter(Rx[0][:,0::3],Rx[0][:,1::3],s=20,c='y')
#%% Forward model data
data = []#np.zeros( nstn*nrx )
unct = []
problem = DC.ProblemDC_CC(mesh)
for ii in range(len(Tx)):
start_time = time.time()
# Select dipole locations for receiver
rxloc_M = np.asarray(Rx[ii][:,0:3])
rxloc_N = np.asarray(Rx[ii][:,3:])
# Number of receivers
nrx = rxloc_M.shape[0]
if not re.match(stype,'pdp'):
inds = Utils.closestPoints(mesh, np.asarray(Tx[ii]).T )
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*( [-1,1] / mesh.vol[inds] )
else:
# Create an "inifinity" pole
tx = np.squeeze(Tx[ii][:,0:1])
tinf = tx + np.array([dl_x,dl_y,0])*dl_len*2
inds = Utils.closestPoints(mesh, np.c_[tx,tinf].T)
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*( [-1] / mesh.vol[inds] )
# Solve for phi on pole locations
P1 = mesh.getInterpolationMat(rxloc_M, 'CC')
P2 = mesh.getInterpolationMat(rxloc_N, 'CC')
if re.match(slvr,'BiCGStab'):
if re.match(pcdr,'Jacobi'):
dA = A.diagonal()
P = sp.spdiags(1/dA,0,A.shape[0],A.shape[0])
# Iterative Solve
Ainvb = sp.linalg.bicgstab(P*A,P*RHS, tol=1e-5)
phi = mkvc(Ainvb[0])
elif re.match(slvr,'LU'):
#Direct Solve
phi = Ainv.solve(RHS)
# Compute potential at each electrode
dtemp = (P1*phi - P2*phi)*np.pi
data.append( dtemp )
unct.append( np.abs(dtemp) * pct + flr)
print("--- %s seconds ---" % (time.time() - start_time))
#%% Run 2D inversion if pdp or dpdp survey
# Otherwise just plot and apparent susceptibility map
if not re.match(stype,'gradient'):
#%% Write data file in UBC-DCIP3D format
DC.writeUBC_DCobs(home_dir+'\FWR_data3D.dat',Tx,Rx,data,unct,'3D')
#%% Load 3D data
[Tx, Rx, data, wd] = DC.readUBC_DC3Dobs(home_dir + '\FWR_data3D.dat')
#%% Convert 3D obs to 2D and write to file
[Tx2d, Rx2d] = DC.convertObs_DC3D_to_2D(Tx,Rx)
DC.writeUBC_DCobs(home_dir+'\FWR_3D_2_2D.dat',Tx2d,Rx2d,data,unct,'2D')
#%% Create a 2D mesh along axis of Tx end points and keep z-discretization
dx = np.min( [ np.min(mesh.hx), np.min(mesh.hy) ])
nc = np.ceil(dl_len/dx)+3
padx = dx*np.power(1.4,range(1,15))
# Creating padding cells
h1 = np.r_[padx[::-1], np.ones(nc)*dx , padx]
# Create mesh with 0 coordinate centerer on the ginput points in cell center
mesh2d = Mesh.TensorMesh([h1, mesh.hz], x0=(-np.sum(padx)-dx/2,mesh.x0[2]))
# Create array of points for interpolating from 3D to 2D mesh
xx = Tx[0][0,0] + mesh2d.vectorCCx * np.cos(azm)
yy = Tx[0][1,0] + mesh2d.vectorCCx * np.sin(azm)
zz = mesh2d.vectorCCy
[XX,ZZ] = np.meshgrid(xx,zz)
[YY,ZZ] = np.meshgrid(yy,zz)
xyz2d = np.c_[mkvc(XX),mkvc(YY),mkvc(ZZ)]
#plt.scatter(xx,yy,s=20,c='y')
F = interpolation.NearestNDInterpolator(mesh.gridCC,model)
m2D = np.reshape(F(xyz2d),[mesh2d.nCx,mesh2d.nCy]).T
#==============================================================================
# mesh2d = Mesh.TensorMesh([mesh.hx, mesh.hz], x0=(mesh.x0[0]-endl[0,0],mesh.x0[2]))
# m3D = np.reshape(model, (mesh.nCz, mesh.nCy, mesh.nCx))
# m2D = m3D[:,1,:]
#==============================================================================
#%%
plt.figure()
axs = plt.subplot(1,1,1)
plt.xlim([-dx,nc*dx+dx])
plt.ylim([mesh2d.vectorNy[-1]-dl_len/2,mesh2d.vectorNy[-1]+2*dx])
plt.gca().set_aspect('equal', adjustable='box')
circle1=plt.Circle((144,1500),50,color='w',fill=False, lw=3)
circle2=plt.Circle((344,1500),50,color='k',fill=False, lw=3)
axs.add_artist(circle1)
axs.add_artist(circle2)
plt.pcolormesh(mesh2d.vectorNx,mesh2d.vectorNy,np.log10(m2D))#axes = [mesh2d.vectorNx[0],mesh2d.vectorNx[-1],mesh2d.vectorNy[0],mesh2d.vectorNy[-1]])
cbar = plt.colorbar(format = '%.2f',fraction=0.02)
cmin,cmax = cbar.get_clim()
ticks = np.linspace(cmin,cmax,3)
cbar.set_ticks(ticks)
# Plot poles
plt.scatter(Tx2d[0][0],mesh2d.vectorNy[-1]+dx,s=50,c='r',marker='v')
plt.scatter(Tx2d[0][1],mesh2d.vectorNy[-1]+dx,s=50,c='b',marker='v')
plt.scatter(Rx2d[0][:,0],np.ones(Rx2d[0].shape[0])*mesh2d.vectorNy[-1]+dx,s=50,c='g')
#mesh2d.plotImage(mkvc(m2D), grid=True, ax=axs)
#%% Plot pseudo section
plt.figure()
axs = plt.subplot(1,1,1)
plt.xlim([-dx,nc*dx+dx])
plt.ylim([mesh2d.vectorNy[-1]-dl_len/2,mesh2d.vectorNy[-1]+2*dx])
plt.gca().set_aspect('equal', adjustable='box')
circle1=plt.Circle((144,1500),50,color='w',fill=False, lw=3)
circle2=plt.Circle((344,1500),50,color='k',fill=False, lw=3)
axs.add_artist(circle1)
axs.add_artist(circle2)
DC.plot_pseudoSection(Tx2d,Rx2d,data,nz[-1],stype)
plt.show()
#%% Run two inversions with different reference models and compute a DOI
invmod = []
refmod = []
plt.figure()
for jj in range(2):
# Create dcin2d inversion files and run
inv_dir = home_dir + '\Inv2D'
if not os.path.exists(inv_dir):
os.makedirs(inv_dir)
mshfile2d = 'Mesh_2D.msh'
modfile2d = 'Model_2D.con'
obsfile2d = 'FWR_3D_2_2D.dat'
inp_file = 'dcinv2d.inp'
# Export 2D mesh
fid = open(inv_dir + dsep + mshfile2d,'w')
fid.write('%i\n'% mesh2d.nCx)
fid.write('%f %f 1\n'% (mesh2d.vectorNx[0],mesh2d.vectorNx[1]))
np.savetxt(fid, np.c_[mesh2d.vectorNx[2:],np.ones(mesh2d.nCx-1)], fmt='\t %e %i',delimiter=' ',newline='\n')
fid.write('\n')
fid.write('%i\n'% mesh2d.nCy)
fid.write('%f %f 1\n'%( 0,mesh2d.hy[-1]))
np.savetxt(fid, np.c_[np.cumsum(mesh2d.hy[-2::-1])+mesh2d.hy[-1],np.ones(mesh2d.nCy-1)], fmt='\t %e %i',delimiter=' ',newline='\n')
fid.close()
# Export 2D model
fid = open(inv_dir + dsep + modfile2d,'w')
fid.write('%i %i\n'% (mesh2d.nCx,mesh2d.nCy))
np.savetxt(fid, mkvc(m2D[::-1,:].T), fmt='%e',delimiter=' ',newline='\n')
fid.close()
# Export data file
DC.writeUBC_DCobs(inv_dir + dsep + obsfile2d,Tx2d,Rx2d,data,unct,'2D')
# 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 %f\n'% chifact)
fid.write('TOPO DEFAULT %s \n')
fid.write('INIT_MOD DEFAULT\n')
fid.write('REF_MOD VALUE %e\n'% (ref_mod*(jj+1)))
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()
os.chdir(inv_dir)
os.system('dcinv2d ' + inp_file)
#Load model
minv = DC.readUBC_DC2DModel(inv_dir + dsep + 'dcinv2d.con')
axs = plt.subplot(2,1,jj+1)
plt.xlim([-dx,nc*dx+dx])
plt.ylim([mesh2d.vectorNy[-1]-dl_len/2,mesh2d.vectorNy[-1]+2*dx])
plt.gca().set_aspect('equal', adjustable='box')
minv = np.reshape(minv,(mesh2d.nCy,mesh2d.nCx))
#plt.pcolormesh(mesh2d.vectorNx,mesh2d.vectorNy,np.log10(m2D),alpha=0.5, cmap='gray')
circle1=plt.Circle((144,1500),50,color='w',fill=False, lw=3)
circle2=plt.Circle((344,1500),50,color='k',fill=False, lw=3)
axs.add_artist(circle1)
axs.add_artist(circle2)
axp = plt.pcolormesh(mesh2d.vectorNx,mesh2d.vectorNy,np.log10(minv),alpha=1,vmin = -2.25, vmax = -1.5)
plt.show()
if jj == 1:
plt.ylabel('(b)',rotation=360)
plt.xlabel('Distance (m)')
else:
plt.ylabel('(a)',rotation=360)
cbar = plt.colorbar(format = '%.2f',fraction=0.05,orientation='vertical',pad=0.02)
cmin,cmax = cbar.get_clim()
ticks = np.linspace(cmin,cmax,3)
cbar.set_ticks(ticks)
#cbar.set_ticklabels('%.2f')
invmod.append(minv)
refmod.append(ref_mod*(jj+1))
#%% 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([-dx,nc*dx+dx])
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)
#%% Replace alpha values from inversion
#rgba_plt = axp.get_facecolor()
#rgba_plt[:,3] = mkvc(DOI)/2
plt.figure()
axs = plt.subplot(1,1,1)
plt.xlim([-dx,nc*dx+dx])
plt.ylim([mesh2d.vectorNy[-1]-dl_len/2,mesh2d.vectorNy[-1]+2*dx])
plt.gca().set_aspect('equal', adjustable='box')
circle1=plt.Circle((144,1500),50,color='w',fill=False, lw=3)
circle2=plt.Circle((344,1500),50,color='k',fill=False, lw=3)
axs.add_artist(circle1)
axs.add_artist(circle2)
axs = plt.pcolor(mesh2d.vectorNx,mesh2d.vectorNy,np.log10(invmod[0]),edgecolor="none")
plt.draw()
cbar = plt.colorbar(format = '%.2f',fraction=0.02)
aa = axs.get_facecolors()
aa[:,3] = mkvc(DOI.T)
axs.set_facecolor(aa)
plt.draw()
#%% Othrwise it is a gradient array, plot surface of apparent resisitivty
elif re.match(stype,'gradient'):
rC1P1 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,0],Rx[0].shape[0], 1) - Rx[0][:,0:2])**2, axis=1 ))
rC2P1 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,1],Rx[0].shape[0], 1) - Rx[0][:,0:2])**2, axis=1 ))
rC1P2 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,1],Rx[0].shape[0], 1) - Rx[0][:,3:5])**2, axis=1 ))
rC2P2 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,0],Rx[0].shape[0], 1) - Rx[0][:,3:5])**2, axis=1 ))
rC1C2 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,0]-Tx[0][0:2,1],Rx[0].shape[0], 1) )**2, axis=1 ))
rP1P2 = np.sqrt( np.sum( (Rx[0][:,0:2] - Rx[0][:,3:5])**2, axis=1 ))
rho = np.abs(data[0]) * np.pi *((rC1P1)**2 / rP1P2)#/ ( 1/rC1P1 - 1/rC2P1 - 1/rC1P2 + 1/rC2P2 )
Pmid = (Rx[0][:,0:2] + Rx[0][:,3:5])/2
# Grid points
grid_x, grid_z = np.mgrid[np.min(Rx[0][:,[0,3]]):np.max(Rx[0][:,[0,3]]):a/10, np.min(Rx[0][:,[1,4]]):np.max(Rx[0][:,[1,4]]):a/10]
grid_rho = griddata(np.c_[Pmid[:,0],Pmid[:,1]], (abs(rho.T)), (grid_x, grid_z), method='linear')
#plt.subplot(2,1,2)
plt.imshow(grid_rho.T, extent = (np.min(grid_x),np.max(grid_x),np.min(grid_z),np.max(grid_z)) ,origin='lower')
var = 'Gradient Array - a-spacing: ' + str(a) + ' m'
plt.title(var)
plt.colorbar()
simpegDCIP/Dev/DC3D_fwr_MtIsa.py
-403
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@@ -1,403 +0,0 @@
"""
Experimental script for the forward modeling of DC resistivity data
along survey lines defined by the user. The program loads in a 3D mesh
and model which is used to design pole-dipole or dipole-dipole survey
lines.
Uses SimPEG to generate the forward problem and compute the LU
factorization.
Calls DCIP2D for the inversion of a projected 2D section from the full
3D model.
Assumes flat topo for now...
Created on Mon December 7th, 2015
@author: dominiquef
"""
#%%
from SimPEG import np, Utils, Mesh, mkvc, sp
import simpegDCIP as DC
import pylab as plt
from pylab import get_current_fig_manager
from scipy.interpolate import griddata
import time
import re
import numpy.matlib as npm
#from readUBC_DC3Dobs import readUBC_DC3Dobs
#from readUBC_DC2DModel import readUBC_DC2DModel
#from writeUBC_DCobs import writeUBC_DCobs
import scipy.interpolate as interpolation
#from plot_pseudoSection import plot_pseudoSection
#from gen_DCIPsurvey import gen_DCIPsurvey
#from convertObs_DC3D_to_2D import convertObs_DC3D_to_2D
import os
#home_dir = 'C:\\Users\\dominiquef.MIRAGEOSCIENCE\\ownCloud\\Research\\Modelling\\Synthetic\\Two_Sphere'
home_dir ='C:\Users\dominiquef.MIRAGEOSCIENCE\ownCloud\Research\MtIsa\Modeling'
dsep = '\\'
#from scipy.linalg import solve_banded
# Load UBC mesh 3D
#mesh = Utils.meshutils.readUBCTensorMesh(home_dir + '\Mesh_10m.msh')
mesh = Utils.meshutils.readUBCTensorMesh(home_dir + '\MtIsa_20m.msh')
#mesh = Utils.meshutils.readUBCTensorMesh(home_dir + '\Mesh_50m.msh')
# Load model
model = Utils.meshutils.readUBCTensorModel(home_dir + '\MtIsa_20m.con',mesh)
#model = Utils.meshutils.readUBCTensorModel(home_dir + '\Synthetic.con',mesh)
#model = Utils.meshutils.readUBCTensorModel(home_dir + '\Lalor_model_50m.con',mesh)
#model = Utils.meshutils.readUBCTensorModel(home_dir + '\TwoSpheres.con',mesh)
#model[model>1] = 0.08
#model = model**0 * 1e-2
# Specify survey type
stype = 'pdp'
# Survey parameters
a = 100
b = 100
n = 15
# Forward solver
slvr = 'BiCGStab' #'LU'
# Preconditioner
pcdr = 'Jacobi'#'Gauss-Seidel'#
# Inversion parameter
pct = 0.01
flr = 1e-4
chifact = 100
ref_mod = 1e-2
#%% 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
# Change one corner to deal with nullspace
A[0,0] = 1
A = sp.csc_matrix(A)
start_time = time.time()
if re.match(slvr,'BiCGStab'):
# Create Jacobi Preconditioner
if re.match(pcdr,'Jacobi'):
dA = A.diagonal()
P = sp.spdiags(1/dA,0,A.shape[0],A.shape[0])
# Create Gauss-Seidel Preconditioner
elif re.match(pcdr,'Gauss-Seidel'):
LD = sp.tril(A,k=0)
#LDinv = sp.linalg.splu(LD)
elif re.match(slvr,'LU'):
# Factor A matrix
Ainv = sp.linalg.splu(A)
print("LU DECOMP--- %s seconds ---" % (time.time() - start_time))
#%% Create survey
# Display top section
top = int(mesh.nCz)-1
plt.figure()
ax_prim = plt.subplot(1,1,1)
mesh.plotSlice(model, ind=top, normal='Z', grid=False, pcolorOpts={'alpha':0.5}, ax =ax_prim)
#plt.xlim([423000,424000])
#plt.ylim([546200,547000])
plt.gca().set_aspect('equal', adjustable='box')
plt.show()
cfm1=get_current_fig_manager().window
gin=[1]
# Keep creating sections until returns an empty ginput (press enter on figure)
#while bool(gin)==True:
# Bring back the plan view figure and pick points
cfm1.activateWindow()
plt.sca(ax_prim)
# Takes two points from ginput and create survey
#if re.match(stype,'gradient'):
gin = [(400.,12200.), (1800.,12200.)]
#else:
#gin = plt.ginput(2, timeout = 0)
#==============================================================================
# if not gin:
# print 'SimPED - Simulation has ended with return'
# break
#==============================================================================
# Add z coordinate to all survey... assume flat
nz = mesh.vectorNz
var = np.c_[np.asarray(gin),np.ones(2).T*nz[-1]]
# Snap the endpoints to the grid. Easier to create 2D section.
indx = Utils.closestPoints(mesh, var )
endl = np.c_[mesh.gridCC[indx,0],mesh.gridCC[indx,1],np.ones(2).T*nz[-1]]
[Tx, Rx] = DC.gen_DCIPsurvey(endl, mesh, stype, a, b, n)
dl_len = np.sqrt( np.sum((endl[0,:] - endl[1,:])**2) )
dl_x = ( Tx[-1][0,1] - Tx[0][0,0] ) / dl_len
dl_y = ( Tx[-1][1,1] - Tx[0][1,0] ) / dl_len
azm = np.arctan(dl_y/dl_x)
# Plot stations along line
plt.scatter(Tx[0][0,:],Tx[0][1,:],s=20,c='g')
plt.scatter(Rx[0][:,0::3],Rx[0][:,1::3],s=20,c='y')
#%% Forward model data
data = []#np.zeros( nstn*nrx )
unct = []
problem = DC.ProblemDC_CC(mesh)
for ii in range(len(Tx)):
start_time = time.time()
# Select dipole locations for receiver
rxloc_M = np.asarray(Rx[ii][:,0:3])
rxloc_N = np.asarray(Rx[ii][:,3:])
# Number of receivers
nrx = rxloc_M.shape[0]
if not re.match(stype,'pdp'):
inds = Utils.closestPoints(mesh, np.asarray(Tx[ii]).T )
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*( [-1,1] / mesh.vol[inds] )
else:
# Create an "inifinity" pole
tx = np.squeeze(Tx[ii][:,0:1])
tinf = tx + np.array([dl_x,dl_y,0])*dl_len*2
inds = Utils.closestPoints(mesh, np.c_[tx,tinf].T)
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*( [-1] / mesh.vol[inds] )
# Solve for phi on pole locations
P1 = mesh.getInterpolationMat(rxloc_M, 'CC')
P2 = mesh.getInterpolationMat(rxloc_N, 'CC')
if re.match(slvr,'BiCGStab'):
if re.match(pcdr,'Jacobi'):
dA = A.diagonal()
P = sp.spdiags(1/dA,0,A.shape[0],A.shape[0])
# Iterative Solve
Ainvb = sp.linalg.bicgstab(P*A,P*RHS, tol=1e-5)
# Create Gauss-Seidel Preconditioner
elif re.match(pcdr,'Gauss-Seidel'):
LD = sp.tril(A,k=0)
phi = mkvc(Ainvb[0])
elif re.match(slvr,'LU'):
#Direct Solve
phi = Ainv.solve(RHS)
# Compute potential at each electrode
dtemp = (P1*phi - P2*phi)*np.pi
data.append( dtemp )
unct.append( np.abs(dtemp) * pct + flr)
print("--- %s seconds ---" % (time.time() - start_time))
#%% Run 2D inversion if pdp or dpdp survey
# Otherwise just plot and apparent susceptibility map
if not re.match(stype,'gradient'):
#%% Write data file in UBC-DCIP3D format
DC.writeUBC_DCobs(home_dir+'\FWR_data3D.dat',Tx,Rx,data,unct,'3D')
#%% Load 3D data
[Tx, Rx, data, wd] = DC.readUBC_DC3Dobs(home_dir + '\FWR_data3D.dat')
#%% Convert 3D obs to 2D and write to file
[Tx2d, Rx2d] = DC.convertObs_DC3D_to_2D(Tx,Rx)
DC.writeUBC_DCobs(home_dir+'\FWR_3D_2_2D.dat',Tx2d,Rx2d,data,unct,'2D')
#%% Create a 2D mesh along axis of Tx end points and keep z-discretization
dx = np.min( [ np.min(mesh.hx), np.min(mesh.hy) ])
nc = np.ceil(dl_len/dx)+3
padx = dx*np.power(1.4,range(1,15))
# Creating padding cells
h1 = np.r_[padx[::-1], np.ones(nc)*dx , padx]
# Create mesh with 0 coordinate centerer on the ginput points in cell center
mesh2d = Mesh.TensorMesh([h1, mesh.hz], x0=(-np.sum(padx)-dx/2,mesh.x0[2]))
# Create array of points for interpolating from 3D to 2D mesh
xx = Tx[0][0,0] + mesh2d.vectorCCx * np.cos(azm)
yy = Tx[0][1,0] + mesh2d.vectorCCx * np.sin(azm)
zz = mesh2d.vectorCCy
[XX,ZZ] = np.meshgrid(xx,zz)
[YY,ZZ] = np.meshgrid(yy,zz)
xyz2d = np.c_[mkvc(XX),mkvc(YY),mkvc(ZZ)]
#plt.scatter(xx,yy,s=20,c='y')
F = interpolation.NearestNDInterpolator(mesh.gridCC,model)
m2D = np.reshape(F(xyz2d),[mesh2d.nCx,mesh2d.nCy]).T
#==============================================================================
# mesh2d = Mesh.TensorMesh([mesh.hx, mesh.hz], x0=(mesh.x0[0]-endl[0,0],mesh.x0[2]))
# m3D = np.reshape(model, (mesh.nCz, mesh.nCy, mesh.nCx))
# m2D = m3D[:,1,:]
#==============================================================================
plt.figure()
axs = plt.subplot(2,1,1)
plt.xlim([0,nc*dx])
plt.ylim([mesh2d.vectorNy[-1]-dl_len/2,mesh2d.vectorNy[-1]])
plt.gca().set_aspect('equal', adjustable='box')
plt.pcolormesh(mesh2d.vectorNx,mesh2d.vectorNy,np.log10(m2D),alpha=0.5, cmap='gray')#axes = [mesh2d.vectorNx[0],mesh2d.vectorNx[-1],mesh2d.vectorNy[0],mesh2d.vectorNy[-1]])
#mesh2d.plotImage(mkvc(m2D), grid=True, ax=axs)
#%% Plot pseudo section
DC.plot_pseudoSection(Tx2d,Rx2d,data,nz[-1],stype)
plt.colorbar
plt.show()
#%% Create dcin2d inversion files and run
inv_dir = home_dir + '\Inv2D'
if not os.path.exists(inv_dir):
os.makedirs(inv_dir)
mshfile2d = 'Mesh_2D.msh'
modfile2d = 'MtIsa_2D.con'
obsfile2d = 'FWR_3D_2_2D.dat'
inp_file = 'dcinv2d.inp'
# Export 2D mesh
fid = open(inv_dir + dsep + mshfile2d,'w')
fid.write('%i\n'% mesh2d.nCx)
fid.write('%f %f 1\n'% (mesh2d.vectorNx[0],mesh2d.vectorNx[1]))
np.savetxt(fid, np.c_[mesh2d.vectorNx[2:],np.ones(mesh2d.nCx-1)], fmt='\t %e %i',delimiter=' ',newline='\n')
fid.write('\n')
fid.write('%i\n'% mesh2d.nCy)
fid.write('%f %f 1\n'%( 0,mesh2d.hy[-1]))
np.savetxt(fid, np.c_[np.cumsum(mesh2d.hy[-2::-1])+mesh2d.hy[-1],np.ones(mesh2d.nCy-1)], fmt='\t %e %i',delimiter=' ',newline='\n')
fid.close()
# Export 2D model
fid = open(inv_dir + dsep + modfile2d,'w')
fid.write('%i %i\n'% (mesh2d.nCx,mesh2d.nCy))
np.savetxt(fid, mkvc(m2D[::-1,:].T), fmt='%e',delimiter=' ',newline='\n')
fid.close()
# Export data file
DC.writeUBC_DCobs(inv_dir + dsep + obsfile2d,Tx2d,Rx2d,data,unct,'2D')
# 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 %f\n'% chifact)
fid.write('TOPO DEFAULT %s \n')
fid.write('INIT_MOD DEFAULT\n')
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()
os.chdir(inv_dir)
os.system('dcinv2d ' + inp_file)
#%%
#Load model
minv = DC.readUBC_DC2DModel(inv_dir + dsep + 'dcinv2d.con')
#plt.figure()
axs = plt.subplot(2,1,2)
plt.xlim([0,nc*dx])
plt.ylim([mesh2d.vectorNy[-1]-dl_len/2,mesh2d.vectorNy[-1]])
plt.gca().set_aspect('equal', adjustable='box')
minv = np.reshape(minv,(mesh2d.nCy,mesh2d.nCx))
plt.pcolormesh(mesh2d.vectorNx,mesh2d.vectorNy,np.log10(m2D),alpha=0.5, cmap='gray')
plt.pcolormesh(mesh2d.vectorNx,mesh2d.vectorNy,np.log10(minv),alpha=0.5, clim=(np.min(np.log10(m2D)),np.max(np.log10(m2D))))
cbar = plt.colorbar(format = '%.2f',fraction=0.02)
cmin,cmax = cbar.get_clim()
ticks = np.linspace(cmin,cmax,3)
cbar.set_ticks(ticks)
#%% Othrwise it is a gradient array, plot surface of apparent resisitivty
elif re.match(stype,'gradient'):
rC1P1 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,0],Rx[0].shape[0], 1) - Rx[0][:,0:2])**2, axis=1 ))
rC2P1 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,1],Rx[0].shape[0], 1) - Rx[0][:,0:2])**2, axis=1 ))
rC1P2 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,0],Rx[0].shape[0], 1) - Rx[0][:,3:5])**2, axis=1 ))
rC2P2 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,1],Rx[0].shape[0], 1) - Rx[0][:,3:5])**2, axis=1 ))
rC1C2 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,0]-Tx[0][0:2,1],Rx[0].shape[0], 1) )**2, axis=1 ))
rP1P2 = np.sqrt( np.sum( (Rx[0][:,0:2] - Rx[0][:,3:5])**2, axis=1 ))
rho = np.abs(data[0]) *np.pi *2. / ( 1/rC1P1 - 1/rC2P1 - 1/rC1P2 + 1/rC2P2 )#*((rC1P1)**2 / rP1P2)#
Pmid = (Rx[0][:,0:2] + Rx[0][:,3:5])/2
# Grid points
grid_x, grid_z = np.mgrid[np.min(Rx[0][:,[0,3]]):np.max(Rx[0][:,[0,3]]):a/10, np.min(Rx[0][:,[1,4]]):np.max(Rx[0][:,[1,4]]):a/10]
grid_rho = griddata(np.c_[Pmid[:,0],Pmid[:,1]], (abs(rho.T)), (grid_x, grid_z), method='linear')
#plt.subplot(2,1,2)
plt.figure()
plt.imshow(grid_rho.T, extent = (np.min(grid_x),np.max(grid_x),np.min(grid_z),np.max(grid_z)) ,origin='lower')
var = 'Gradient Array - a-spacing: ' + str(a) + ' m'
plt.title(var)
plt.colorbar()
plt.contour(grid_x,grid_z,grid_rho, colors='k')
#%% Load tight model and plot
mesh = Utils.meshutils.readUBCTensorMesh(home_dir + '\MtIsa_5m.msh')
# Load model
model = Utils.meshutils.readUBCTensorModel(home_dir + '\MtIsa_5m.con',mesh)
model = model.reshape((mesh.nCz,mesh.nCx))
plt.figure()
plt.imshow(np.log10(model),extent = (125,375,0,75),origin='lower')
plt.colorbar(fraction=0.015)
simpegDCIP/Dev/DC3D_fwr_live.py
-85
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@@ -1,85 +0,0 @@
import os
home_dir = 'C:\Users\dominiquef.MIRAGEOSCIENCE\Documents\GIT\SimPEG\simpegdc\simpegDCIP\Dev'
os.chdir(home_dir)
#%%
from SimPEG import np, Utils, Mesh, mkvc, SolverLU
import simpegDCIP as DC
import pylab as plt
# Load UBC mesh 3D
mesh = Utils.meshutils.readUBCTensorMesh('Mesh_40m.msh')
# Load model
model = Utils.meshutils.readUBCTensorModel('Synthetic.con',mesh)
#%%
# Display top section
top = int(mesh.nCz)-1
mesh.plotSlice(model, ind=top, normal='Z', grid=True, pcolorOpts={'alpha':0.8})
ylim=(546000,546750)
xlim=(422900,423675)
# Takes two points from ginput and create survey
temp = plt.ginput(2)
# Add z coordinate
nz = mesh.vectorNz
endp = np.c_[np.asarray(temp),np.ones(2).T*nz[-1]]
# Create dipole survey receivers and plot
nrx = 10
ab = 40
a = 20
# Evenly distribute transmitters for now and put on surface
dplen = np.sqrt( np.sum((endp[1,:] - endp[0,:])**2) )
dp_x = ( endp[1,0] - endp[0,0] ) / dplen
dp_y = ( endp[1,1] - endp[0,1] ) / dplen
nstn = np.floor( dplen / ab )
stn_x = endp[0,0] + np.cumsum( np.ones(nstn)*dp_x*ab )
stn_y = endp[0,1] + np.cumsum( np.ones(nstn)*dp_y*ab )
plt.scatter(stn_x,stn_y,s=100, c='w')
M = np.c_[stn_x-a*dp_x, stn_y-a*dp_y, np.ones(nstn).T*nz[-1]]
N = np.c_[stn_x+a*dp_x, stn_y+a*dp_y, np.ones(nstn).T*nz[-1]]
plt.scatter(M[:,0],M[:,1],s=10,c='r')
plt.scatter(N[:,0],N[:,1],s=10,c='b')
#%% Create inversion parameter
Rx = DC.RxDipole(M,N)
Tx = DC.SrcDipole([Rx], tx[0,:],tx[1,:])
survey = DC.SurveyDC([Tx])
problem = DC.ProblemDC_CC(mesh)
problem.pair(survey)
problem.Solver = SolverLU
data = survey.dpred(model)
#Set boundary conditions
mesh.setCellGradBC('neumann')
Div = mesh.faceDiv
Grad = mesh.cellGradBC
Msig = Utils.sdiag(1./(mesh.aveF2CC.T*(1./model)))
A = Div*Msig*Grad
# Change one corner to deal with nullspace
A[0,0] = 1.
# Get the righthand side
RHS = problem.getRHS
# Solve for phi
phi = SolverLU(A)*-RHS
simpegDCIP/Dev/DC3D_fwr_live_test.py
-390
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@@ -1,390 +0,0 @@
"""
Experimental script for the forward modeling of DC resistivity data
along survey lines defined by the user. The program loads in a 3D mesh
and model which is used to design pole-dipole or dipole-dipole survey
lines.
Uses SimPEG to generate the forward problem and compute the LU
factorization.
Calls DCIP2D for the inversion of a projected 2D section from the full
3D model.
Assumes flat topo for now...
Created on Mon December 7th, 2015
@author: dominiquef
"""
#%%
from SimPEG import np, Utils, Mesh, mkvc, sp
import simpegDCIP as DC
import pylab as plt
from pylab import get_current_fig_manager
from scipy.interpolate import griddata
import time
import re
import numpy.matlib as npm
#from readUBC_DC3Dobs import readUBC_DC3Dobs
#from readUBC_DC2DModel import readUBC_DC2DModel
#from writeUBC_DCobs import writeUBC_DCobs
import scipy.interpolate as interpolation
#from plot_pseudoSection import plot_pseudoSection
#from gen_DCIPsurvey import gen_DCIPsurvey
#from convertObs_DC3D_to_2D import convertObs_DC3D_to_2D
import os
#home_dir = 'C:\\Users\\dominiquef.MIRAGEOSCIENCE\\ownCloud\\Research\\Modelling\\Synthetic\\Two_Sphere'
home_dir ='C:\Users\dominiquef.MIRAGEOSCIENCE\Documents\GIT\SimPEG\simpegdc\simpegDCIP\Dev'
dsep = '\\'
#from scipy.linalg import solve_banded
# Load UBC mesh 3D
#mesh = Utils.meshutils.readUBCTensorMesh(home_dir + '\Mesh_10m.msh')
mesh = Utils.meshutils.readUBCTensorMesh(home_dir + '\MtIsa_20m.msh')
#mesh = Utils.meshutils.readUBCTensorMesh(home_dir + '\Mesh_50m.msh')
# Load model
model = Utils.meshutils.readUBCTensorModel(home_dir + '\MtIsa_3D.con',mesh)
#model = Utils.meshutils.readUBCTensorModel(home_dir + '\Synthetic.con',mesh)
#model = Utils.meshutils.readUBCTensorModel(home_dir + '\Lalor_model_50m.con',mesh)
#model = Utils.meshutils.readUBCTensorModel(home_dir + '\TwoSpheres.con',mesh)
#model = model**0 * 1e-2
# Specify survey type
stype = 'pdp'
# Survey parameters
a = 150
b = 150
n = 40
# Forward solver
slvr = 'BiCGStab' #'LU'
# Preconditioner
pcdr = 'Jacobi'#'Gauss-Seidel'#
# Inversion parameter
pct = 0.01
flr = 1e-4
chifact = 100
ref_mod = 1e-3
#%% 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
# Change one corner to deal with nullspace
A[0,0] = 1
A = sp.csc_matrix(A)
start_time = time.time()
if re.match(slvr,'BiCGStab'):
# Create Jacobi Preconditioner
if re.match(pcdr,'Jacobi'):
dA = A.diagonal()
P = sp.spdiags(1/dA,0,A.shape[0],A.shape[0])
# Create Gauss-Seidel Preconditioner
elif re.match(pcdr,'Gauss-Seidel'):
LD = sp.tril(A,k=0)
#LDinv = sp.linalg.splu(LD)
elif re.match(slvr,'LU'):
# Factor A matrix
Ainv = sp.linalg.splu(A)
print("LU DECOMP--- %s seconds ---" % (time.time() - start_time))
#%% Create survey
# Display top section
top = int(mesh.nCz)-1
plt.figure()
ax_prim = plt.subplot(1,1,1)
mesh.plotSlice(model, ind=top, normal='Z', grid=False, pcolorOpts={'alpha':0.5}, ax =ax_prim)
#plt.xlim([423000,424000])
#plt.ylim([546200,547000])
plt.gca().set_aspect('equal', adjustable='box')
plt.show()
cfm1=get_current_fig_manager().window
gin=[1]
# Keep creating sections until returns an empty ginput (press enter on figure)
#while bool(gin)==True:
# Bring back the plan view figure and pick points
cfm1.activateWindow()
plt.sca(ax_prim)
# Takes two points from ginput and create survey
#if re.match(stype,'gradient'):
#gin = [(425347, 6079766), (427792, 6081806)]
#else:
gin = plt.ginput(2, timeout = 0)
#==============================================================================
# if not gin:
# print 'SimPED - Simulation has ended with return'
# break
#==============================================================================
# Add z coordinate to all survey... assume flat
nz = mesh.vectorNz
var = np.c_[np.asarray(gin),np.ones(2).T*nz[-1]]
# Snap the endpoints to the grid. Easier to create 2D section.
indx = Utils.closestPoints(mesh, var )
endl = np.c_[mesh.gridCC[indx,0],mesh.gridCC[indx,1],np.ones(2).T*nz[-1]]
[Tx, Rx] = gen_DCIPsurvey(endl, mesh, stype, a, b, n)
dl_len = np.sqrt( np.sum((endl[0,:] - endl[1,:])**2) )
dl_x = ( Tx[-1][0,1] - Tx[0][0,0] ) / dl_len
dl_y = ( Tx[-1][1,1] - Tx[0][1,0] ) / dl_len
azm = np.arctan(dl_y/dl_x)
# Plot stations along line
plt.scatter(Tx[0][0,:],Tx[0][1,:],s=20,c='g')
plt.scatter(Rx[0][:,0::3],Rx[0][:,1::3],s=20,c='y')
#%% Forward model data
data = []#np.zeros( nstn*nrx )
unct = []
problem = DC.ProblemDC_CC(mesh)
for ii in range(len(Tx)):
start_time = time.time()
# Select dipole locations for receiver
rxloc_M = np.asarray(Rx[ii][:,0:3])
rxloc_N = np.asarray(Rx[ii][:,3:])
# Number of receivers
nrx = rxloc_M.shape[0]
if not re.match(stype,'pdp'):
inds = Utils.closestPoints(mesh, np.asarray(Tx[ii]).T )
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*( [-1,1] / mesh.vol[inds] )
else:
# Create an "inifinity" pole
tx = np.squeeze(Tx[ii][:,0:1])
tinf = tx + np.array([dl_x,dl_y,0])*dl_len*2
inds = Utils.closestPoints(mesh, np.c_[tx,tinf].T)
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*( [-1] / mesh.vol[inds] )
# Solve for phi on pole locations
P1 = mesh.getInterpolationMat(rxloc_M, 'CC')
P2 = mesh.getInterpolationMat(rxloc_N, 'CC')
if re.match(slvr,'BiCGStab'):
if re.match(pcdr,'Jacobi'):
dA = A.diagonal()
P = sp.spdiags(1/dA,0,A.shape[0],A.shape[0])
# Iterative Solve
Ainvb = sp.linalg.bicgstab(P*A,P*RHS, tol=1e-5)
# Create Gauss-Seidel Preconditioner
elif re.match(pcdr,'Gauss-Seidel'):
LD = sp.tril(A,k=0)
phi = mkvc(Ainvb[0])
elif re.match(slvr,'LU'):
#Direct Solve
phi = Ainv.solve(RHS)
# Compute potential at each electrode
dtemp = (P1*phi - P2*phi)*np.pi
data.append( dtemp )
unct.append( np.abs(dtemp) * pct + flr)
print("--- %s seconds ---" % (time.time() - start_time))
#%% Run 2D inversion if pdp or dpdp survey
# Otherwise just plot and apparent susceptibility map
if not re.match(stype,'gradient'):
#%% Write data file in UBC-DCIP3D format
writeUBC_DCobs(home_dir+'\FWR_data3D.dat',Tx,Rx,data,unct,'3D')
#%% Load 3D data
[Tx, Rx, data, wd] = readUBC_DC3Dobs(home_dir + '\FWR_data3D.dat')
#%% Convert 3D obs to 2D and write to file
[Tx2d, Rx2d] = convertObs_DC3D_to_2D(Tx,Rx)
writeUBC_DCobs(home_dir+'\FWR_3D_2_2D.dat',Tx2d,Rx2d,data,unct,'2D')
#%% Create a 2D mesh along axis of Tx end points and keep z-discretization
dx = np.min( [ np.min(mesh.hx), np.min(mesh.hy) ])
nc = np.ceil(dl_len/dx)+3
padx = dx*np.power(1.4,range(1,15))
# Creating padding cells
h1 = np.r_[padx[::-1], np.ones(nc)*dx , padx]
# Create mesh with 0 coordinate centerer on the ginput points in cell center
mesh2d = Mesh.TensorMesh([h1, mesh.hz], x0=(-np.sum(padx)-dx/2,mesh.x0[2]))
# Create array of points for interpolating from 3D to 2D mesh
xx = Tx[0][0,0] + mesh2d.vectorCCx * np.cos(azm)
yy = Tx[0][1,0] + mesh2d.vectorCCx * np.sin(azm)
zz = mesh2d.vectorCCy
[XX,ZZ] = np.meshgrid(xx,zz)
[YY,ZZ] = np.meshgrid(yy,zz)
xyz2d = np.c_[mkvc(XX),mkvc(YY),mkvc(ZZ)]
#plt.scatter(xx,yy,s=20,c='y')
F = interpolation.NearestNDInterpolator(mesh.gridCC,model)
m2D = np.reshape(F(xyz2d),[mesh2d.nCx,mesh2d.nCy]).T
#==============================================================================
# mesh2d = Mesh.TensorMesh([mesh.hx, mesh.hz], x0=(mesh.x0[0]-endl[0,0],mesh.x0[2]))
# m3D = np.reshape(model, (mesh.nCz, mesh.nCy, mesh.nCx))
# m2D = m3D[:,1,:]
#==============================================================================
plt.figure()
axs = plt.subplot(2,1,1)
plt.xlim([0,nc*dx])
plt.ylim([mesh2d.vectorNy[-1]-dl_len,mesh2d.vectorNy[-1]])
plt.gca().set_aspect('equal', adjustable='box')
plt.pcolormesh(mesh2d.vectorNx,mesh2d.vectorNy,np.log10(m2D),alpha=0.5, cmap='gray')#axes = [mesh2d.vectorNx[0],mesh2d.vectorNx[-1],mesh2d.vectorNy[0],mesh2d.vectorNy[-1]])
#mesh2d.plotImage(mkvc(m2D), grid=True, ax=axs)
#%% Plot pseudo section
plot_pseudoSection(Tx2d,Rx2d,data,nz[-1],stype)
plt.colorbar
plt.show()
#%% Create dcin2d inversion files and run
inv_dir = home_dir + '\Inv2D'
if not os.path.exists(inv_dir):
os.makedirs(inv_dir)
mshfile2d = 'Mesh_2D.msh'
modfile2d = 'MtIsa_2D.con'
obsfile2d = 'FWR_3D_2_2D.dat'
inp_file = 'dcinv2d.inp'
# Export 2D mesh
fid = open(inv_dir + dsep + mshfile2d,'w')
fid.write('%i\n'% mesh2d.nCx)
fid.write('%f %f 1\n'% (mesh2d.vectorNx[0],mesh2d.vectorNx[1]))
np.savetxt(fid, np.c_[mesh2d.vectorNx[2:],np.ones(mesh2d.nCx-1)], fmt='\t %e %i',delimiter=' ',newline='\n')
fid.write('\n')
fid.write('%i\n'% mesh2d.nCy)
fid.write('%f %f 1\n'%( 0,mesh2d.hy[-1]))
np.savetxt(fid, np.c_[np.cumsum(mesh2d.hy[-2::-1])+mesh2d.hy[-1],np.ones(mesh2d.nCy-1)], fmt='\t %e %i',delimiter=' ',newline='\n')
fid.close()
# Export 2D model
fid = open(inv_dir + dsep + modfile2d,'w')
fid.write('%i %i\n'% (mesh2d.nCx,mesh2d.nCy))
np.savetxt(fid, mkvc(m2D[::-1,:].T), fmt='%e',delimiter=' ',newline='\n')
fid.close()
# Export data file
writeUBC_DCobs(inv_dir + dsep + obsfile2d,Tx2d,Rx2d,data,unct,'2D')
# 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 %f\n'% chifact)
fid.write('TOPO DEFAULT %s \n')
fid.write('INIT_MOD DEFAULT\n')
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()
os.chdir(inv_dir)
os.system('dcinv2d ' + inp_file)
#%%
#Load model
minv = readUBC_DC2DModel(inv_dir + dsep + 'dcinv2d.con')
#plt.figure()
axs = plt.subplot(2,1,2)
plt.xlim([0,nc*dx])
plt.ylim([mesh2d.vectorNy[-1]-dl_len,mesh2d.vectorNy[-1]])
plt.gca().set_aspect('equal', adjustable='box')
minv = np.reshape(minv,(mesh2d.nCy,mesh2d.nCx))
plt.pcolormesh(mesh2d.vectorNx,mesh2d.vectorNy,np.log10(m2D),alpha=0.5, cmap='gray')
plt.pcolormesh(mesh2d.vectorNx,mesh2d.vectorNy,np.log10(minv),alpha=0.5, clim=(np.min(np.log10(m2D)),np.max(np.log10(m2D))))
cbar = plt.colorbar(format = '%.2f',fraction=0.02)
cmin,cmax = cbar.get_clim()
ticks = np.linspace(cmin,cmax,3)
cbar.set_ticks(ticks)
#%% Othrwise it is a gradient array, plot surface of apparent resisitivty
elif re.match(stype,'gradient'):
rC1P1 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,0],Rx[0].shape[0], 1) - Rx[0][:,0:2])**2, axis=1 ))
rC2P1 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,1],Rx[0].shape[0], 1) - Rx[0][:,0:2])**2, axis=1 ))
rC1P2 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,0],Rx[0].shape[0], 1) - Rx[0][:,3:5])**2, axis=1 ))
rC2P2 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,1],Rx[0].shape[0], 1) - Rx[0][:,3:5])**2, axis=1 ))
rC1C2 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,0]-Tx[0][0:2,1],Rx[0].shape[0], 1) )**2, axis=1 ))
rP1P2 = np.sqrt( np.sum( (Rx[0][:,0:2] - Rx[0][:,3:5])**2, axis=1 ))
rho = np.abs(data[0]) *np.pi *2. / ( 1/rC1P1 - 1/rC2P1 - 1/rC1P2 + 1/rC2P2 )#*((rC1P1)**2 / rP1P2)#
Pmid = (Rx[0][:,0:2] + Rx[0][:,3:5])/2
# Grid points
grid_x, grid_z = np.mgrid[np.min(Rx[0][:,[0,3]]):np.max(Rx[0][:,[0,3]]):a/10, np.min(Rx[0][:,[1,4]]):np.max(Rx[0][:,[1,4]]):a/10]
grid_rho = griddata(np.c_[Pmid[:,0],Pmid[:,1]], (abs(rho.T)), (grid_x, grid_z), method='linear')
#plt.subplot(2,1,2)
plt.figure()
plt.imshow(grid_rho.T, extent = (np.min(grid_x),np.max(grid_x),np.min(grid_z),np.max(grid_z)) ,origin='lower')
var = 'Gradient Array - a-spacing: ' + str(a) + ' m'
plt.title(var)
plt.colorbar()
plt.contour(grid_x,grid_z,grid_rho, colors='k')
simpegDCIP/Dev/DCIP2D_FWR/PDP/FWR_3D_2_2D.dat
-245
View File
@@ -1,245 +0,0 @@
! GENERAL FORMAT
0.000000e+00 0.000000e+00 4.000000e+01 8.000000e+01 4.536103e-01 4.636103e-03
0.000000e+00 0.000000e+00 8.000000e+01 1.200000e+02 1.956283e-01 2.056283e-03
0.000000e+00 0.000000e+00 1.200000e+02 1.600000e+02 9.661533e-02 1.066153e-03
0.000000e+00 0.000000e+00 1.600000e+02 2.000000e+02 5.443205e-03 1.544321e-04
0.000000e+00 0.000000e+00 2.000000e+02 2.400000e+02 2.977518e-03 1.297752e-04
0.000000e+00 0.000000e+00 2.400000e+02 2.800000e+02 3.113318e-03 1.311332e-04
0.000000e+00 0.000000e+00 2.800000e+02 3.200000e+02 7.216380e-03 1.721638e-04
0.000000e+00 0.000000e+00 3.200000e+02 3.600000e+02 6.475000e-03 1.647500e-04
0.000000e+00 0.000000e+00 3.600000e+02 4.000000e+02 4.750858e-03 1.475086e-04
4.000000e+01 4.000000e+01 8.000000e+01 1.200000e+02 4.737093e-01 4.837093e-03
4.000000e+01 4.000000e+01 1.200000e+02 1.600000e+02 1.933017e-01 2.033017e-03
4.000000e+01 4.000000e+01 1.600000e+02 2.000000e+02 9.625111e-03 1.962511e-04
4.000000e+01 4.000000e+01 2.000000e+02 2.400000e+02 4.710170e-03 1.471017e-04
4.000000e+01 4.000000e+01 2.400000e+02 2.800000e+02 4.146907e-03 1.414691e-04
4.000000e+01 4.000000e+01 2.800000e+02 3.200000e+02 9.014465e-03 1.901446e-04
4.000000e+01 4.000000e+01 3.200000e+02 3.600000e+02 7.875920e-03 1.787592e-04
4.000000e+01 4.000000e+01 3.600000e+02 4.000000e+02 5.711976e-03 1.571198e-04
4.000000e+01 4.000000e+01 4.000000e+02 4.400000e+02 6.259850e-04 1.062599e-04
8.000000e+01 8.000000e+01 1.200000e+02 1.600000e+02 4.956306e-01 5.056306e-03
8.000000e+01 8.000000e+01 1.600000e+02 2.000000e+02 2.048511e-02 3.048511e-04
8.000000e+01 8.000000e+01 2.000000e+02 2.400000e+02 8.575637e-03 1.857564e-04
8.000000e+01 8.000000e+01 2.400000e+02 2.800000e+02 6.032524e-03 1.603252e-04
8.000000e+01 8.000000e+01 2.800000e+02 3.200000e+02 1.189394e-02 2.189394e-04
8.000000e+01 8.000000e+01 3.200000e+02 3.600000e+02 9.982800e-03 1.998280e-04
8.000000e+01 8.000000e+01 3.600000e+02 4.000000e+02 7.117008e-03 1.711701e-04
8.000000e+01 8.000000e+01 4.000000e+02 4.400000e+02 7.649935e-04 1.076499e-04
8.000000e+01 8.000000e+01 4.400000e+02 4.800000e+02 6.193333e-04 1.061933e-04
1.200000e+02 1.200000e+02 1.600000e+02 2.000000e+02 5.597631e-02 6.597631e-04
1.200000e+02 1.200000e+02 2.000000e+02 2.400000e+02 1.877787e-02 2.877787e-04
1.200000e+02 1.200000e+02 2.400000e+02 2.800000e+02 9.908609e-03 1.990861e-04
1.200000e+02 1.200000e+02 2.800000e+02 3.200000e+02 1.676287e-02 2.676287e-04
1.200000e+02 1.200000e+02 3.200000e+02 3.600000e+02 1.319428e-02 2.319428e-04
1.200000e+02 1.200000e+02 3.600000e+02 4.000000e+02 9.156663e-03 1.915666e-04
1.200000e+02 1.200000e+02 4.000000e+02 4.400000e+02 9.579451e-04 1.095795e-04
1.200000e+02 1.200000e+02 4.400000e+02 4.800000e+02 7.568666e-04 1.075687e-04
1.200000e+02 1.200000e+02 4.800000e+02 5.200000e+02 6.080823e-04 1.060808e-04
1.600000e+02 1.600000e+02 2.000000e+02 2.400000e+02 4.265271e-02 5.265271e-04
1.600000e+02 1.600000e+02 2.400000e+02 2.800000e+02 1.691741e-02 2.691741e-04
1.600000e+02 1.600000e+02 2.800000e+02 3.200000e+02 2.380462e-02 3.380462e-04
1.600000e+02 1.600000e+02 3.200000e+02 3.600000e+02 1.727048e-02 2.727048e-04
1.600000e+02 1.600000e+02 3.600000e+02 4.000000e+02 1.158363e-02 2.158363e-04
1.600000e+02 1.600000e+02 4.000000e+02 4.400000e+02 1.175287e-03 1.117529e-04
1.600000e+02 1.600000e+02 4.400000e+02 4.800000e+02 9.042510e-04 1.090425e-04
1.600000e+02 1.600000e+02 4.800000e+02 5.200000e+02 7.129196e-04 1.071292e-04
1.600000e+02 1.600000e+02 5.200000e+02 5.600000e+02 5.684553e-04 1.056846e-04
2.000000e+02 2.000000e+02 2.400000e+02 2.800000e+02 3.101272e-02 4.101272e-04
2.000000e+02 2.000000e+02 2.800000e+02 3.200000e+02 3.293247e-02 4.293247e-04
2.000000e+02 2.000000e+02 3.200000e+02 3.600000e+02 2.118536e-02 3.118536e-04
2.000000e+02 2.000000e+02 3.600000e+02 4.000000e+02 1.354928e-02 2.354928e-04
2.000000e+02 2.000000e+02 4.000000e+02 4.400000e+02 1.328240e-03 1.132824e-04
2.000000e+02 2.000000e+02 4.400000e+02 4.800000e+02 9.951781e-04 1.099518e-04
2.000000e+02 2.000000e+02 4.800000e+02 5.200000e+02 7.713268e-04 1.077133e-04
2.000000e+02 2.000000e+02 5.200000e+02 5.600000e+02 6.080769e-04 1.060808e-04
2.000000e+02 2.000000e+02 5.600000e+02 6.000000e+02 4.818454e-04 1.048185e-04
2.400000e+02 2.400000e+02 2.800000e+02 3.200000e+02 6.649140e-02 7.649140e-04
2.400000e+02 2.400000e+02 3.200000e+02 3.600000e+02 3.258335e-02 4.258335e-04
2.400000e+02 2.400000e+02 3.600000e+02 4.000000e+02 1.854898e-02 2.854898e-04
2.400000e+02 2.400000e+02 4.000000e+02 4.400000e+02 1.680085e-03 1.168008e-04
2.400000e+02 2.400000e+02 4.400000e+02 4.800000e+02 1.185559e-03 1.118556e-04
2.400000e+02 2.400000e+02 4.800000e+02 5.200000e+02 8.847441e-04 1.088474e-04
2.400000e+02 2.400000e+02 5.200000e+02 5.600000e+02 6.804673e-04 1.068047e-04
2.400000e+02 2.400000e+02 5.600000e+02 6.000000e+02 5.302990e-04 1.053030e-04
2.400000e+02 2.400000e+02 6.000000e+02 6.400000e+02 4.148104e-04 1.041481e-04
2.800000e+02 2.800000e+02 3.200000e+02 3.600000e+02 1.578256e-01 1.678256e-03
2.800000e+02 2.800000e+02 3.600000e+02 4.000000e+02 6.200859e-02 7.200859e-04
2.800000e+02 2.800000e+02 4.000000e+02 4.400000e+02 4.339120e-03 1.433912e-04
2.800000e+02 2.800000e+02 4.400000e+02 4.800000e+02 2.478341e-03 1.247834e-04
2.800000e+02 2.800000e+02 4.800000e+02 5.200000e+02 1.605665e-03 1.160567e-04
2.800000e+02 2.800000e+02 5.200000e+02 5.600000e+02 1.123502e-03 1.112350e-04
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Parallelized with OpenMP. # of threads: 4
DCIP2D - Version 5 (BETA) 20110811: DCIPF2D
Developed by University of British Columbia
Geophysical Inversion Facility (UBC-GIF)
(C) Copyright 1992 - 2011, UBC-GIF,
Department of Earth and Ocean Sciences, UBC
http://www.eos.ubc.ca/research/ubcgif/
Distributed by:
Mira Geoscience Ltd.
DCIPF2D started on:12/09/2015 17:56:14
Reading input file: dcipf2d.inp
----------------------------------------------
FWD DC
MESH FILE Mesh_2D.msh
LOC LOC_X FWR_3D_2_2D.dat
TOPO DEFAULT
COND FILE MtIsa_2D.con
----------------------------------------------
electrode locations were read from: FWR_3D_2_2D.dat
# of current locations: 28
# of data: 216
mesh was read from: Mesh_2D.msh
# of cells: 85 x 45
total # of cells: 3825
# of active cells: 3825
# of wave values: 13
2.5000E-04 4.9901E-04 9.9606E-04 1.9882E-03 3.9685E-03 7.9213E-03 1.5811E-02 3.1560E-02 6.2996E-02 1.2574E-01 2.5099E-01 5.0099E-01 1.0000E+00
conductivity was read from file: MtIsa_2D.con
dc fwd cpu time: 0:00:00.19
total cpu time: 0:00:00.19
DCIPF2D ended on:12/09/2015 17:56:14
simpegDCIP/Dev/DCIP2D_FWR/PDP/obs_dc.dat
-217
View File
@@ -1,217 +0,0 @@
! Predicted data ! GENERAL FORMAT Last column are apparent conductivities.
0.0000000E+00 0.0000000E+00 4.0000000E+01 8.0000000E+01 4.37963E-01 4.54248E-03
0.0000000E+00 0.0000000E+00 8.0000000E+01 1.2000000E+02 1.62622E-01 4.07785E-03
0.0000000E+00 0.0000000E+00 1.2000000E+02 1.6000000E+02 7.69824E-02 4.30712E-03
0.0000000E+00 0.0000000E+00 1.6000000E+02 2.0000000E+02 4.38528E-03 4.53662E-02
0.0000000E+00 0.0000000E+00 2.0000000E+02 2.4000000E+02 2.46637E-03 5.37751E-02
0.0000000E+00 0.0000000E+00 2.4000000E+02 2.8000000E+02 2.74581E-03 3.45017E-02
0.0000000E+00 0.0000000E+00 2.8000000E+02 3.2000000E+02 6.51619E-03 1.09038E-02
0.0000000E+00 0.0000000E+00 3.2000000E+02 3.6000000E+02 5.91274E-03 9.34628E-03
0.0000000E+00 0.0000000E+00 3.6000000E+02 4.0000000E+02 4.36195E-03 1.01353E-02
4.0000000E+01 4.0000000E+01 8.0000000E+01 1.2000000E+02 4.63636E-01 4.29095E-03
4.0000000E+01 4.0000000E+01 1.2000000E+02 1.6000000E+02 1.61950E-01 4.09476E-03
4.0000000E+01 4.0000000E+01 1.6000000E+02 2.0000000E+02 7.91654E-03 4.18836E-02
4.0000000E+01 4.0000000E+01 2.0000000E+02 2.4000000E+02 3.92652E-03 5.06667E-02
4.0000000E+01 4.0000000E+01 2.4000000E+02 2.8000000E+02 3.64355E-03 3.64011E-02
4.0000000E+01 4.0000000E+01 2.8000000E+02 3.2000000E+02 8.11826E-03 1.16694E-02
4.0000000E+01 4.0000000E+01 3.2000000E+02 3.6000000E+02 7.18120E-03 9.89407E-03
4.0000000E+01 4.0000000E+01 3.6000000E+02 4.0000000E+02 5.23964E-03 1.05469E-02
4.0000000E+01 4.0000000E+01 4.0000000E+02 4.4000000E+02 5.79728E-04 7.62594E-02
8.0000000E+01 8.0000000E+01 1.2000000E+02 1.6000000E+02 4.82045E-01 4.12707E-03
8.0000000E+01 8.0000000E+01 1.6000000E+02 2.0000000E+02 1.74835E-02 3.79299E-02
8.0000000E+01 8.0000000E+01 2.0000000E+02 2.4000000E+02 7.15442E-03 4.63451E-02
8.0000000E+01 8.0000000E+01 2.4000000E+02 2.8000000E+02 5.20669E-03 3.82092E-02
8.0000000E+01 8.0000000E+01 2.8000000E+02 3.2000000E+02 1.05211E-02 1.26060E-02
8.0000000E+01 8.0000000E+01 3.2000000E+02 3.6000000E+02 8.95319E-03 1.05812E-02
8.0000000E+01 8.0000000E+01 3.6000000E+02 4.0000000E+02 6.42718E-03 1.10548E-02
8.0000000E+01 8.0000000E+01 4.0000000E+02 4.4000000E+02 6.98004E-04 7.91716E-02
8.0000000E+01 8.0000000E+01 4.4000000E+02 4.8000000E+02 5.71181E-04 7.74005E-02
1.2000000E+02 1.2000000E+02 1.6000000E+02 2.0000000E+02 5.63584E-02 3.52997E-02
1.2000000E+02 1.2000000E+02 2.0000000E+02 2.4000000E+02 1.61965E-02 4.09437E-02
1.2000000E+02 1.2000000E+02 2.4000000E+02 2.8000000E+02 8.43582E-03 3.93053E-02
1.2000000E+02 1.2000000E+02 2.8000000E+02 3.2000000E+02 1.45236E-02 1.36979E-02
1.2000000E+02 1.2000000E+02 3.2000000E+02 3.6000000E+02 1.15992E-02 1.14344E-02
1.2000000E+02 1.2000000E+02 3.6000000E+02 4.0000000E+02 8.11343E-03 1.16763E-02
1.2000000E+02 1.2000000E+02 4.0000000E+02 4.4000000E+02 8.58536E-04 8.27587E-02
1.2000000E+02 1.2000000E+02 4.4000000E+02 4.8000000E+02 6.86451E-04 8.05041E-02
1.2000000E+02 1.2000000E+02 4.8000000E+02 5.2000000E+02 5.56629E-04 7.94241E-02
1.6000000E+02 1.6000000E+02 2.0000000E+02 2.4000000E+02 4.17530E-02 4.76478E-02
1.6000000E+02 1.6000000E+02 2.4000000E+02 2.8000000E+02 1.45259E-02 4.56525E-02
1.6000000E+02 1.6000000E+02 2.8000000E+02 3.2000000E+02 2.02746E-02 1.63541E-02
1.6000000E+02 1.6000000E+02 3.2000000E+02 3.6000000E+02 1.48931E-02 1.33581E-02
1.6000000E+02 1.6000000E+02 3.6000000E+02 4.0000000E+02 1.00734E-02 1.31663E-02
1.6000000E+02 1.6000000E+02 4.0000000E+02 4.4000000E+02 1.03480E-03 9.15490E-02
1.6000000E+02 1.6000000E+02 4.4000000E+02 4.8000000E+02 8.06769E-04 8.80689E-02
1.6000000E+02 1.6000000E+02 4.8000000E+02 5.2000000E+02 6.42732E-04 8.59801E-02
1.6000000E+02 1.6000000E+02 5.2000000E+02 5.6000000E+02 5.16345E-04 8.56205E-02
2.0000000E+02 2.0000000E+02 2.4000000E+02 2.8000000E+02 3.10109E-02 6.41528E-02
2.0000000E+02 2.0000000E+02 2.8000000E+02 3.2000000E+02 2.84303E-02 2.33253E-02
2.0000000E+02 2.0000000E+02 3.2000000E+02 3.6000000E+02 1.81787E-02 1.82396E-02
2.0000000E+02 2.0000000E+02 3.6000000E+02 4.0000000E+02 1.17012E-02 1.70020E-02
2.0000000E+02 2.0000000E+02 4.0000000E+02 4.4000000E+02 1.16142E-03 1.14196E-01
2.0000000E+02 2.0000000E+02 4.4000000E+02 4.8000000E+02 8.82426E-04 1.07358E-01
2.0000000E+02 2.0000000E+02 4.8000000E+02 5.2000000E+02 6.91684E-04 1.02722E-01
2.0000000E+02 2.0000000E+02 5.2000000E+02 5.6000000E+02 5.49788E-04 1.00515E-01
2.0000000E+02 2.0000000E+02 5.6000000E+02 6.0000000E+02 4.38101E-04 1.00912E-01
2.4000000E+02 2.4000000E+02 2.8000000E+02 3.2000000E+02 6.63054E-02 3.00041E-02
2.4000000E+02 2.4000000E+02 3.2000000E+02 3.6000000E+02 2.86962E-02 2.31092E-02
2.4000000E+02 2.4000000E+02 3.6000000E+02 4.0000000E+02 1.61554E-02 2.05239E-02
2.4000000E+02 2.4000000E+02 4.0000000E+02 4.4000000E+02 1.47767E-03 1.34634E-01
2.4000000E+02 2.4000000E+02 4.4000000E+02 4.8000000E+02 1.05797E-03 1.25361E-01
2.4000000E+02 2.4000000E+02 4.8000000E+02 5.2000000E+02 7.99625E-04 1.18474E-01
2.4000000E+02 2.4000000E+02 5.2000000E+02 5.6000000E+02 6.20964E-04 1.14421E-01
2.4000000E+02 2.4000000E+02 5.6000000E+02 6.0000000E+02 4.87210E-04 1.13426E-01
2.4000000E+02 2.4000000E+02 6.0000000E+02 6.4000000E+02 3.82964E-04 1.15441E-01
2.8000000E+02 2.8000000E+02 3.2000000E+02 3.6000000E+02 1.70137E-01 1.16932E-02
2.8000000E+02 2.8000000E+02 3.6000000E+02 4.0000000E+02 5.51339E-02 1.20279E-02
2.8000000E+02 2.8000000E+02 4.0000000E+02 4.4000000E+02 3.74082E-03 8.86365E-02
2.8000000E+02 2.8000000E+02 4.4000000E+02 4.8000000E+02 2.14407E-03 9.27878E-02
2.8000000E+02 2.8000000E+02 4.8000000E+02 5.2000000E+02 1.40564E-03 9.43551E-02
2.8000000E+02 2.8000000E+02 5.2000000E+02 5.6000000E+02 9.95293E-04 9.51831E-02
2.8000000E+02 2.8000000E+02 5.6000000E+02 6.0000000E+02 7.34406E-04 9.67466E-02
2.8000000E+02 2.8000000E+02 6.0000000E+02 6.4000000E+02 5.53238E-04 9.98885E-02
2.8000000E+02 2.8000000E+02 6.4000000E+02 6.8000000E+02 4.21795E-04 1.04813E-01
3.2000000E+02 3.2000000E+02 3.6000000E+02 4.0000000E+02 2.84337E-01 6.99676E-03
3.2000000E+02 3.2000000E+02 4.0000000E+02 4.4000000E+02 1.39919E-02 4.73949E-02
3.2000000E+02 3.2000000E+02 4.4000000E+02 4.8000000E+02 6.43218E-03 5.15490E-02
3.2000000E+02 3.2000000E+02 4.8000000E+02 5.2000000E+02 3.62113E-03 5.49396E-02
3.2000000E+02 3.2000000E+02 5.2000000E+02 5.6000000E+02 2.30061E-03 5.76495E-02
3.2000000E+02 3.2000000E+02 5.6000000E+02 6.0000000E+02 1.57121E-03 6.02942E-02
3.2000000E+02 3.2000000E+02 6.0000000E+02 6.4000000E+02 1.11891E-03 6.35005E-02
3.2000000E+02 3.2000000E+02 6.4000000E+02 6.8000000E+02 8.17331E-04 6.76129E-02
3.2000000E+02 3.2000000E+02 6.8000000E+02 7.2000000E+02 6.08827E-04 7.26146E-02
3.6000000E+02 3.6000000E+02 4.0000000E+02 4.4000000E+02 4.74032E-02 4.19684E-02
3.6000000E+02 3.6000000E+02 4.4000000E+02 4.8000000E+02 1.54783E-02 4.28435E-02
3.6000000E+02 3.6000000E+02 4.8000000E+02 5.2000000E+02 7.33839E-03 4.51833E-02
3.6000000E+02 3.6000000E+02 5.2000000E+02 5.6000000E+02 4.20683E-03 4.72907E-02
3.6000000E+02 3.6000000E+02 5.6000000E+02 6.0000000E+02 2.68996E-03 4.93053E-02
3.6000000E+02 3.6000000E+02 6.0000000E+02 6.4000000E+02 1.83372E-03 5.16629E-02
3.6000000E+02 3.6000000E+02 6.4000000E+02 6.8000000E+02 1.29930E-03 5.46843E-02
3.6000000E+02 3.6000000E+02 6.8000000E+02 7.2000000E+02 9.45999E-04 5.84167E-02
3.6000000E+02 3.6000000E+02 7.2000000E+02 7.6000000E+02 7.05763E-04 6.26410E-02
4.0000000E+02 4.0000000E+02 4.4000000E+02 4.8000000E+02 3.81851E-02 5.20998E-02
4.0000000E+02 4.0000000E+02 4.8000000E+02 5.2000000E+02 1.36233E-02 4.86774E-02
4.0000000E+02 4.0000000E+02 5.2000000E+02 5.6000000E+02 6.80313E-03 4.87383E-02
4.0000000E+02 4.0000000E+02 5.6000000E+02 6.0000000E+02 4.01999E-03 4.94886E-02
4.0000000E+02 4.0000000E+02 6.0000000E+02 6.4000000E+02 2.61132E-03 5.07900E-02
4.0000000E+02 4.0000000E+02 6.4000000E+02 6.8000000E+02 1.79405E-03 5.28052E-02
4.0000000E+02 4.0000000E+02 6.8000000E+02 7.2000000E+02 1.27904E-03 5.55507E-02
4.0000000E+02 4.0000000E+02 7.2000000E+02 7.6000000E+02 9.39590E-04 5.88152E-02
4.0000000E+02 4.0000000E+02 7.6000000E+02 8.0000000E+02 7.10076E-04 6.22605E-02
4.4000000E+02 4.4000000E+02 4.8000000E+02 5.2000000E+02 2.91377E-02 6.82771E-02
4.4000000E+02 4.4000000E+02 5.2000000E+02 5.6000000E+02 1.04151E-02 6.36715E-02
4.4000000E+02 4.4000000E+02 5.6000000E+02 6.0000000E+02 5.29883E-03 6.25747E-02
4.4000000E+02 4.4000000E+02 6.0000000E+02 6.4000000E+02 3.18206E-03 6.25204E-02
4.4000000E+02 4.4000000E+02 6.4000000E+02 6.8000000E+02 2.09086E-03 6.34329E-02
4.4000000E+02 4.4000000E+02 6.8000000E+02 7.2000000E+02 1.45130E-03 6.52762E-02
4.4000000E+02 4.4000000E+02 7.2000000E+02 7.6000000E+02 1.04806E-03 6.77931E-02
4.4000000E+02 4.4000000E+02 7.6000000E+02 8.0000000E+02 7.82930E-04 7.05837E-02
4.4000000E+02 4.4000000E+02 8.0000000E+02 8.4000000E+02 6.02044E-04 7.34326E-02
4.8000000E+02 4.8000000E+02 5.2000000E+02 5.6000000E+02 2.76526E-02 7.19439E-02
4.8000000E+02 4.8000000E+02 5.6000000E+02 6.0000000E+02 9.58946E-03 6.91536E-02
4.8000000E+02 4.8000000E+02 6.0000000E+02 6.4000000E+02 4.78028E-03 6.93627E-02
4.8000000E+02 4.8000000E+02 6.4000000E+02 6.8000000E+02 2.83237E-03 7.02394E-02
4.8000000E+02 4.8000000E+02 6.8000000E+02 7.2000000E+02 1.84884E-03 7.17363E-02
4.8000000E+02 4.8000000E+02 7.2000000E+02 7.6000000E+02 1.28476E-03 7.37377E-02
4.8000000E+02 4.8000000E+02 7.6000000E+02 8.0000000E+02 9.35719E-04 7.59323E-02
4.8000000E+02 4.8000000E+02 8.0000000E+02 8.4000000E+02 7.07359E-04 7.81246E-02
4.8000000E+02 4.8000000E+02 8.4000000E+02 8.8000000E+02 5.44824E-04 8.11450E-02
5.2000000E+02 5.2000000E+02 5.6000000E+02 6.0000000E+02 2.71482E-02 7.32807E-02
5.2000000E+02 5.2000000E+02 6.0000000E+02 6.4000000E+02 9.24381E-03 7.17394E-02
5.2000000E+02 5.2000000E+02 6.4000000E+02 6.8000000E+02 4.53338E-03 7.31403E-02
5.2000000E+02 5.2000000E+02 6.8000000E+02 7.2000000E+02 2.65663E-03 7.48858E-02
5.2000000E+02 5.2000000E+02 7.2000000E+02 7.6000000E+02 1.72839E-03 7.67354E-02
5.2000000E+02 5.2000000E+02 7.6000000E+02 8.0000000E+02 1.20700E-03 7.84879E-02
5.2000000E+02 5.2000000E+02 8.0000000E+02 8.4000000E+02 8.87817E-04 8.00292E-02
5.2000000E+02 5.2000000E+02 8.4000000E+02 8.8000000E+02 6.72287E-04 8.22002E-02
5.2000000E+02 5.2000000E+02 8.8000000E+02 9.2000000E+02 4.38246E-04 1.00879E-01
5.6000000E+02 5.6000000E+02 6.0000000E+02 6.4000000E+02 2.69080E-02 7.39347E-02
5.6000000E+02 5.6000000E+02 6.4000000E+02 6.8000000E+02 9.06610E-03 7.31457E-02
5.6000000E+02 5.6000000E+02 6.8000000E+02 7.2000000E+02 4.40651E-03 7.52461E-02
5.6000000E+02 5.6000000E+02 7.2000000E+02 7.6000000E+02 2.57356E-03 7.73028E-02
5.6000000E+02 5.6000000E+02 7.6000000E+02 8.0000000E+02 1.68174E-03 7.88643E-02
5.6000000E+02 5.6000000E+02 8.0000000E+02 8.4000000E+02 1.18662E-03 7.98363E-02
5.6000000E+02 5.6000000E+02 8.4000000E+02 8.8000000E+02 8.76426E-04 8.10694E-02
5.6000000E+02 5.6000000E+02 8.8000000E+02 9.2000000E+02 5.64302E-04 9.79301E-02
5.6000000E+02 5.6000000E+02 9.2000000E+02 9.6000000E+02 9.98730E-05 4.42659E-01
6.0000000E+02 6.0000000E+02 6.4000000E+02 6.8000000E+02 2.67823E-02 7.42819E-02
6.0000000E+02 6.0000000E+02 6.8000000E+02 7.2000000E+02 8.97982E-03 7.38484E-02
6.0000000E+02 6.0000000E+02 7.2000000E+02 7.6000000E+02 4.35803E-03 7.60831E-02
6.0000000E+02 6.0000000E+02 7.6000000E+02 8.0000000E+02 2.55907E-03 7.77407E-02
6.0000000E+02 6.0000000E+02 8.0000000E+02 8.4000000E+02 1.69286E-03 7.83462E-02
6.0000000E+02 6.0000000E+02 8.4000000E+02 8.8000000E+02 1.20453E-03 7.86487E-02
6.0000000E+02 6.0000000E+02 8.8000000E+02 9.2000000E+02 7.61995E-04 9.32438E-02
6.0000000E+02 6.0000000E+02 9.2000000E+02 9.6000000E+02 1.33150E-04 4.15038E-01
6.0000000E+02 6.0000000E+02 9.6000000E+02 1.0000000E+03 1.43991E-04 3.07032E-01
6.4000000E+02 6.4000000E+02 6.8000000E+02 7.2000000E+02 2.67335E-02 7.44175E-02
6.4000000E+02 6.4000000E+02 7.2000000E+02 7.6000000E+02 8.96712E-03 7.39530E-02
6.4000000E+02 6.4000000E+02 7.6000000E+02 8.0000000E+02 4.38069E-03 7.56896E-02
6.4000000E+02 6.4000000E+02 8.0000000E+02 8.4000000E+02 2.61036E-03 7.62132E-02
6.4000000E+02 6.4000000E+02 8.4000000E+02 8.8000000E+02 1.75149E-03 7.57235E-02
6.4000000E+02 6.4000000E+02 8.8000000E+02 9.2000000E+02 1.07880E-03 8.78156E-02
6.4000000E+02 6.4000000E+02 9.2000000E+02 9.6000000E+02 1.85635E-04 3.82747E-01
6.4000000E+02 6.4000000E+02 9.6000000E+02 1.0000000E+03 1.85002E-04 2.98711E-01
6.4000000E+02 6.4000000E+02 1.0000000E+03 1.0400000E+03 1.85777E-04 2.37972E-01
6.8000000E+02 6.8000000E+02 7.2000000E+02 7.6000000E+02 2.67613E-02 7.43402E-02
6.8000000E+02 6.8000000E+02 7.6000000E+02 8.0000000E+02 9.03659E-03 7.33845E-02
6.8000000E+02 6.8000000E+02 8.0000000E+02 8.4000000E+02 4.48785E-03 7.38824E-02
6.8000000E+02 6.8000000E+02 8.4000000E+02 8.8000000E+02 2.73166E-03 7.28288E-02
6.8000000E+02 6.8000000E+02 8.8000000E+02 9.2000000E+02 1.61137E-03 8.23085E-02
6.8000000E+02 6.8000000E+02 9.2000000E+02 9.6000000E+02 2.71744E-04 3.48619E-01
6.8000000E+02 6.8000000E+02 9.6000000E+02 1.0000000E+03 2.46275E-04 2.88504E-01
6.8000000E+02 6.8000000E+02 1.0000000E+03 1.0400000E+03 2.41460E-04 2.28867E-01
6.8000000E+02 6.8000000E+02 1.0400000E+03 1.0800000E+03 1.81915E-04 2.43024E-01
7.2000000E+02 7.2000000E+02 7.6000000E+02 8.0000000E+02 2.68947E-02 7.39714E-02
7.2000000E+02 7.2000000E+02 8.0000000E+02 8.4000000E+02 9.22857E-03 7.18579E-02
7.2000000E+02 7.2000000E+02 8.4000000E+02 8.8000000E+02 4.71676E-03 7.02968E-02
7.2000000E+02 7.2000000E+02 8.8000000E+02 9.2000000E+02 2.58276E-03 7.70276E-02
7.2000000E+02 7.2000000E+02 9.2000000E+02 9.6000000E+02 4.23001E-04 3.13543E-01
7.2000000E+02 7.2000000E+02 9.6000000E+02 1.0000000E+03 3.40352E-04 2.78345E-01
7.2000000E+02 7.2000000E+02 1.0000000E+03 1.0400000E+03 3.23938E-04 2.19336E-01
7.2000000E+02 7.2000000E+02 1.0400000E+03 1.0800000E+03 2.37881E-04 2.32310E-01
7.2000000E+02 7.2000000E+02 1.0800000E+03 1.1200000E+03 1.75459E-04 2.51965E-01
7.6000000E+02 7.6000000E+02 8.0000000E+02 8.4000000E+02 2.72284E-02 7.30647E-02
7.6000000E+02 7.6000000E+02 8.4000000E+02 8.8000000E+02 9.66569E-03 6.86082E-02
7.6000000E+02 7.6000000E+02 8.8000000E+02 9.2000000E+02 4.59764E-03 7.21180E-02
7.6000000E+02 7.6000000E+02 9.2000000E+02 9.6000000E+02 7.18689E-04 2.76815E-01
7.6000000E+02 7.6000000E+02 9.6000000E+02 1.0000000E+03 4.92200E-04 2.69462E-01
7.6000000E+02 7.6000000E+02 1.0000000E+03 1.0400000E+03 4.50063E-04 2.10493E-01
7.6000000E+02 7.6000000E+02 1.0400000E+03 1.0800000E+03 3.19985E-04 2.22045E-01
7.6000000E+02 7.6000000E+02 1.0800000E+03 1.1200000E+03 2.30214E-04 2.40047E-01
7.6000000E+02 7.6000000E+02 1.1200000E+03 1.1600000E+03 1.64278E-04 2.69115E-01
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simpegDCIP/Dev/DCIP2D_FWR/dcipf2d.inp
-5
View File
@@ -1,5 +0,0 @@
FWD DC
MESH FILE Mesh_2D.msh
LOC LOC_X FWR_3D_2_2D.dat
TOPO DEFAULT
COND FILE MtIsa_2D.con
simpegDCIP/Dev/DCIP3D_FWR/Mesh_20m.msh
-5
View File
@@ -1,5 +0,0 @@
104 21 45
-1565.00 10725 0
350 300 250 200 175 150 103.00 86.00 72.00 60.00 50.00 40.00 35.00 30.00 24.00 74*20.00 24.00 30.00 35.00 40.00 50.00 60.00 72.00 86.00 103.00 150 175 200 250 300 350
300 250 200 175 150 103.00 86.00 72.00 5*60 72.00 86.00 103.00 150 175 200 250 300
30*20 24.00 30.00 35.00 40.00 50.00 60.00 72.00 86.00 103.00 150 175 200 250 300 350
simpegDCIP/Dev/DCIP3D_FWR/MtIsa_3D.con
-98280
View File
File diff suppressed because it is too large Load Diff
simpegDCIP/Dev/DCIP3D_FWR/PDP/FWR_UBC3D_2_2D.dat
-245
View File
@@ -1,245 +0,0 @@
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simpegDCIP/Dev/DCIP3D_FWR/PDP/FWR_data3D.dat
-301
View File
@@ -1,301 +0,0 @@
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simpegDCIP/Dev/DCIP3D_FWR/PDP/dc3d.dat
-273
View File
@@ -1,273 +0,0 @@
! dc data
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simpegDCIP/Dev/DCIP3D_FWR/fwr.inp
-9
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@@ -1,9 +0,0 @@
dc
Mesh_20m.msh
OBS_LOC_3D.dat
MtIsa_3D.con
VALUE 0.0
null
0
1e-5
-1
simpegDCIP/Dev/FWR_3D_2_2D.dat
-55
View File
@@ -1,55 +0,0 @@
! GENERAL FORMAT
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simpegDCIP/Dev/FWR_data3D.dat
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simpegDCIP/Dev/Inv2D/FWR_3D_2_2D.dat
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simpegDCIP/Dev/Inv2D/MtIsa_2D.con
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simpegDCIP/Dev/Inv2D/dcinv2d.con
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1.00031E-02 1.00042E-02 1.00068E-02 1.00131E-02 1.00262E-02 1.00489E-02 1.00812E-02 1.01188E-02 1.01555E-02 1.01869E-02 1.02114E-02 1.02294E-02 1.02423E-02 1.02513E-02 1.02577E-02 1.02629E-02 1.02679E-02 1.02729E-02 1.02777E-02 1.02823E-02 1.02867E-02 1.02908E-02 1.02947E-02 1.02984E-02 1.03018E-02 1.03048E-02 1.03075E-02 1.03099E-02 1.03119E-02 1.03135E-02 1.03147E-02 1.03154E-02 1.03156E-02 1.03155E-02 1.03148E-02 1.03137E-02 1.03121E-02 1.03099E-02 1.03073E-02 1.03042E-02 1.03005E-02 1.02963E-02 1.02916E-02 1.02864E-02 1.02808E-02 1.02747E-02 1.02682E-02 1.02612E-02 1.02537E-02 1.02458E-02 1.02375E-02 1.02289E-02 1.02201E-02 1.02109E-02 1.02015E-02 1.01918E-02 1.01820E-02 1.01720E-02 1.01619E-02 1.01517E-02 1.01415E-02 1.01313E-02 1.01211E-02 1.01110E-02 1.01010E-02 1.00911E-02 1.00814E-02 1.00700E-02 1.00546E-02 1.00343E-02 1.00087E-02 9.97899E-03 9.94948E-03 9.92927E-03 9.92751E-03 9.94529E-03 9.96971E-03 9.98774E-03 9.99689E-03 1.00006E-02 1.00019E-02
1.00031E-02 1.00041E-02 1.00066E-02 1.00122E-02 1.00231E-02 1.00405E-02 1.00631E-02 1.00872E-02 1.01089E-02 1.01263E-02 1.01391E-02 1.01481E-02 1.01543E-02 1.01585E-02 1.01614E-02 1.01637E-02 1.01659E-02 1.01680E-02 1.01701E-02 1.01720E-02 1.01737E-02 1.01754E-02 1.01768E-02 1.01781E-02 1.01793E-02 1.01803E-02 1.01810E-02 1.01816E-02 1.01820E-02 1.01822E-02 1.01822E-02 1.01819E-02 1.01814E-02 1.01807E-02 1.01797E-02 1.01786E-02 1.01772E-02 1.01755E-02 1.01735E-02 1.01714E-02 1.01691E-02 1.01664E-02 1.01635E-02 1.01604E-02 1.01570E-02 1.01535E-02 1.01499E-02 1.01460E-02 1.01418E-02 1.01374E-02 1.01329E-02 1.01282E-02 1.01234E-02 1.01185E-02 1.01135E-02 1.01083E-02 1.01031E-02 1.00978E-02 1.00924E-02 1.00869E-02 1.00815E-02 1.00761E-02 1.00706E-02 1.00652E-02 1.00598E-02 1.00545E-02 1.00492E-02 1.00430E-02 1.00345E-02 1.00233E-02 1.00087E-02 9.99129E-03 9.97280E-03 9.95771E-03 9.95250E-03 9.96044E-03 9.97595E-03 9.98954E-03 9.99727E-03 1.00006E-02 1.00019E-02
1.00031E-02 1.00041E-02 1.00063E-02 1.00111E-02 1.00197E-02 1.00322E-02 1.00469E-02 1.00612E-02 1.00730E-02 1.00818E-02 1.00879E-02 1.00919E-02 1.00946E-02 1.00964E-02 1.00975E-02 1.00984E-02 1.00993E-02 1.01001E-02 1.01008E-02 1.01015E-02 1.01021E-02 1.01026E-02 1.01030E-02 1.01033E-02 1.01035E-02 1.01037E-02 1.01038E-02 1.01037E-02 1.01035E-02 1.01033E-02 1.01030E-02 1.01025E-02 1.01019E-02 1.01012E-02 1.01005E-02 1.00996E-02 1.00986E-02 1.00974E-02 1.00962E-02 1.00948E-02 1.00934E-02 1.00919E-02 1.00902E-02 1.00884E-02 1.00865E-02 1.00846E-02 1.00826E-02 1.00805E-02 1.00782E-02 1.00758E-02 1.00734E-02 1.00710E-02 1.00685E-02 1.00659E-02 1.00632E-02 1.00606E-02 1.00578E-02 1.00551E-02 1.00523E-02 1.00495E-02 1.00466E-02 1.00438E-02 1.00410E-02 1.00382E-02 1.00353E-02 1.00325E-02 1.00298E-02 1.00265E-02 1.00220E-02 1.00159E-02 1.00080E-02 9.99809E-03 9.98699E-03 9.97679E-03 9.97120E-03 9.97338E-03 9.98205E-03 9.99151E-03 9.99772E-03 1.00007E-02 1.00019E-02
1.00031E-02 1.00040E-02 1.00060E-02 1.00099E-02 1.00162E-02 1.00243E-02 1.00328E-02 1.00402E-02 1.00458E-02 1.00497E-02 1.00521E-02 1.00537E-02 1.00546E-02 1.00552E-02 1.00556E-02 1.00559E-02 1.00561E-02 1.00563E-02 1.00565E-02 1.00566E-02 1.00567E-02 1.00568E-02 1.00568E-02 1.00568E-02 1.00567E-02 1.00567E-02 1.00565E-02 1.00563E-02 1.00561E-02 1.00558E-02 1.00555E-02 1.00551E-02 1.00547E-02 1.00542E-02 1.00537E-02 1.00532E-02 1.00526E-02 1.00519E-02 1.00512E-02 1.00505E-02 1.00497E-02 1.00489E-02 1.00480E-02 1.00471E-02 1.00461E-02 1.00451E-02 1.00441E-02 1.00431E-02 1.00420E-02 1.00408E-02 1.00396E-02 1.00384E-02 1.00372E-02 1.00359E-02 1.00346E-02 1.00333E-02 1.00320E-02 1.00307E-02 1.00293E-02 1.00280E-02 1.00266E-02 1.00252E-02 1.00239E-02 1.00225E-02 1.00211E-02 1.00197E-02 1.00184E-02 1.00168E-02 1.00145E-02 1.00114E-02 1.00074E-02 1.00021E-02 9.99590E-03 9.98953E-03 9.98484E-03 9.98408E-03 9.98784E-03 9.99362E-03 9.99826E-03 1.00008E-02 1.00019E-02
1.00031E-02 1.00039E-02 1.00056E-02 1.00086E-02 1.00126E-02 1.00170E-02 1.00210E-02 1.00241E-02 1.00261E-02 1.00274E-02 1.00281E-02 1.00285E-02 1.00288E-02 1.00289E-02 1.00289E-02 1.00290E-02 1.00290E-02 1.00290E-02 1.00290E-02 1.00290E-02 1.00290E-02 1.00289E-02 1.00289E-02 1.00288E-02 1.00287E-02 1.00286E-02 1.00285E-02 1.00283E-02 1.00282E-02 1.00280E-02 1.00278E-02 1.00276E-02 1.00274E-02 1.00271E-02 1.00269E-02 1.00266E-02 1.00263E-02 1.00260E-02 1.00257E-02 1.00253E-02 1.00250E-02 1.00247E-02 1.00243E-02 1.00238E-02 1.00234E-02 1.00230E-02 1.00226E-02 1.00221E-02 1.00217E-02 1.00212E-02 1.00207E-02 1.00202E-02 1.00197E-02 1.00191E-02 1.00186E-02 1.00180E-02 1.00175E-02 1.00169E-02 1.00164E-02 1.00158E-02 1.00152E-02 1.00147E-02 1.00141E-02 1.00135E-02 1.00129E-02 1.00123E-02 1.00117E-02 1.00110E-02 1.00100E-02 1.00087E-02 1.00068E-02 1.00044E-02 1.00013E-02 9.99777E-03 9.99449E-03 9.99262E-03 9.99320E-03 9.99588E-03 9.99890E-03 1.00010E-02 1.00020E-02
1.00031E-02 1.00038E-02 1.00053E-02 1.00074E-02 1.00099E-02 1.00120E-02 1.00136E-02 1.00146E-02 1.00152E-02 1.00155E-02 1.00156E-02 1.00156E-02 1.00157E-02 1.00157E-02 1.00156E-02 1.00156E-02 1.00156E-02 1.00156E-02 1.00156E-02 1.00155E-02 1.00155E-02 1.00155E-02 1.00154E-02 1.00154E-02 1.00153E-02 1.00152E-02 1.00152E-02 1.00151E-02 1.00150E-02 1.00149E-02 1.00149E-02 1.00148E-02 1.00147E-02 1.00146E-02 1.00145E-02 1.00144E-02 1.00143E-02 1.00142E-02 1.00140E-02 1.00139E-02 1.00138E-02 1.00136E-02 1.00135E-02 1.00133E-02 1.00132E-02 1.00130E-02 1.00129E-02 1.00127E-02 1.00125E-02 1.00123E-02 1.00122E-02 1.00120E-02 1.00118E-02 1.00116E-02 1.00114E-02 1.00112E-02 1.00110E-02 1.00108E-02 1.00106E-02 1.00103E-02 1.00101E-02 1.00099E-02 1.00097E-02 1.00094E-02 1.00092E-02 1.00090E-02 1.00087E-02 1.00084E-02 1.00080E-02 1.00075E-02 1.00067E-02 1.00056E-02 1.00040E-02 1.00021E-02 9.99987E-03 9.99783E-03 9.99688E-03 9.99765E-03 9.99947E-03 1.00011E-02 1.00020E-02
simpegDCIP/Dev/Inv2D/dcinv2d.inp
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OBS LOC_X FWR_3D_2_2D.dat
MESH FILE Mesh_2D.msh
CHIFACT 1 100.000000
TOPO DEFAULT %s
INIT_MOD DEFAULT
REF_MOD VALUE 1.000000e-02
ALPHA DEFAULT
WEIGHT DEFAULT
STORE_ALL_MODELS FALSE
INVMODE SVD
USE_MREF TRUE
simpegDCIP/Dev/Inv2D/dcinv2d.log
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Parallelized with OpenMP. # of threads: 4
DCIP2D - Version 5 (BETA) 20110811: DCINV2D
Developed by University of British Columbia
Geophysical Inversion Facility (UBC-GIF)
(C) Copyright 1992 - 2011, UBC-GIF,
Department of Earth and Ocean Sciences, UBC
http://www.eos.ubc.ca/research/ubcgif/
Distributed by:
Mira Geoscience Ltd.
DCINV2D started on: 1/12/2016 21:07:02
Reading input file: dcinv2d.inp
----------------------------------------------
OBS LOC_X FWR_3D_2_2D.dat
MESH FILE Mesh_2D.msh
CHIFACT 1 100.000000
TOPO DEFAULT %s
INIT_MOD DEFAULT
REF_MOD VALUE 1.000000e-02
ALPHA DEFAULT
WEIGHT DEFAULT
STORE_ALL_MODELS FALSE
INVMODE SVD
USE_MREF TRUE
----------------------------------------------
maximum # of iterations: 100
data were read from: FWR_3D_2_2D.dat
# of current locations: 9
# of data: 45
chifact: 1.00000E+00
target misfit: 4.50000E+01
mesh was read from: Mesh_2D.msh
# of cells: 81 x 45
total # of cells: 3645
# of active cells: 3645
# of unique data locations: 9
# of wave values: 13
2.5000E-04 4.9901E-04 9.9606E-04 1.9882E-03 3.9685E-03 7.9213E-03 1.5811E-02 3.1560E-02 6.2996E-02 1.2574E-01 2.5099E-01 5.0099E-01 1.0000E+00
reference conductivity model is set to a constant: 1.000000E-02
initial model is set to the reference model.
using default length scales (Lx, Lz): ( 8.00000E+01, 8.00000E+01)
corresponding alpha (a_s, a_x, a_z): ( 1.56250E-04, 1.0000E+00, 1.0000E+00)
Using basis vectors and SVD.
reference model will be used in the derivative terms.
number of basis vectors: 17 + 3 + 1 = 21
init cpu time: 0:00:00.18
initial misfit = 2.57080E+05
init. model norm = 0.00000E+00
norm comp Ws = 0.00000E+00
norm comp Wx = 0.00000E+00
norm comp Wz = 0.00000E+00
Iteration 1
beta vs. misfit:
beta misfit
1.11493E+03 4.74485E+04
2.22985E+03 5.68364E+04
5.57463E+03 8.02516E+04
1.39366E+04 1.21526E+05
1.57750E+04 1.28279E+05
1.58488E+04 1.28536E+05
1.58499E+04 1.28540E+05
3.96247E+04 1.79392E+05
chosen beta = 1.58499E+04
target misfit = 1.28540E+05
achieved misfit = 1.28540E+05
model norm = 3.63297E+00
misfit change = 5.00000E-01
model norm change = 0.00000E+00
norm comp Ws = 2.88514E+00
norm comp Wx = 3.70226E-01
norm comp Wz = 3.77603E-01
iter cpu time: 0:00:01.81
Iteration 2
beta vs. misfit:
beta misfit
3.96247E+03 6.15053E+04
7.92494E+03 9.46707E+04
chosen beta = 4.25263E+03
target misfit = 6.42701E+04
achieved misfit = 6.42774E+04
model norm = 1.37169E+01
misfit change = 4.99943E-01
model norm change = 2.77567E+00
norm comp Ws = 1.06979E+01
norm comp Wx = 1.61088E+00
norm comp Wz = 1.40814E+00
iter cpu time: 0:00:00.83
Iteration 3
beta vs. misfit:
beta misfit
1.06316E+03 2.49833E+04
2.12631E+03 4.10044E+04
chosen beta = 1.51222E+03
target misfit = 3.21387E+04
achieved misfit = 3.17674E+04
model norm = 2.91306E+01
misfit change = 5.05777E-01
model norm change = 1.12370E+00
norm comp Ws = 2.19928E+01
norm comp Wx = 4.11507E+00
norm comp Wz = 3.02271E+00
iter cpu time: 0:00:00.64
Iteration 4
beta vs. misfit:
beta misfit
3.78054E+02 1.14051E+04
7.56108E+02 1.87488E+04
chosen beta = 6.00000E+02
target misfit = 1.58837E+04
achieved misfit = 1.56569E+04
model norm = 4.84312E+01
misfit change = 5.07137E-01
model norm change = 6.62554E-01
norm comp Ws = 3.49213E+01
norm comp Wx = 8.32898E+00
norm comp Wz = 5.18098E+00
iter cpu time: 0:00:01.47
Iteration 5
beta vs. misfit:
beta misfit
1.50000E+02 5.05151E+03
3.00000E+02 8.76679E+03
chosen beta = 2.60199E+02
target misfit = 7.82847E+03
achieved misfit = 7.79602E+03
model norm = 6.97577E+01
misfit change = 5.02073E-01
model norm change = 4.40344E-01
norm comp Ws = 4.74916E+01
norm comp Wx = 1.43993E+01
norm comp Wz = 7.86671E+00
iter cpu time: 0:00:01.41
Iteration 6
beta vs. misfit:
beta misfit
6.50498E+01 1.83324E+03
1.30100E+02 3.68412E+03
1.37599E+02 3.90387E+03
chosen beta = 1.37400E+02
target misfit = 3.89801E+03
achieved misfit = 3.89800E+03
model norm = 8.95751E+01
misfit change = 5.00001E-01
model norm change = 2.84090E-01
norm comp Ws = 5.75580E+01
norm comp Wx = 2.11440E+01
norm comp Wz = 1.08731E+01
iter cpu time: 0:00:01.02
Iteration 7
beta vs. misfit:
beta misfit
3.43499E+01 8.99667E+02
6.86999E+01 1.65819E+03
8.25106E+01 2.00613E+03
chosen beta = 8.02499E+01
target misfit = 1.94900E+03
achieved misfit = 1.94758E+03
model norm = 1.06566E+02
misfit change = 5.00364E-01
model norm change = 1.89686E-01
norm comp Ws = 6.57720E+01
norm comp Wx = 2.69488E+01
norm comp Wz = 1.38454E+01
iter cpu time: 0:00:01.00
Iteration 8
beta vs. misfit:
beta misfit
2.00625E+01 5.63946E+02
4.01250E+01 9.43655E+02
4.18598E+01 9.78372E+02
chosen beta = 4.16303E+01
target misfit = 9.73791E+02
achieved misfit = 9.73755E+02
model norm = 1.22904E+02
misfit change = 5.00019E-01
model norm change = 1.53314E-01
norm comp Ws = 7.39851E+01
norm comp Wx = 3.20341E+01
norm comp Wz = 1.68852E+01
iter cpu time: 0:00:01.08
Iteration 9
beta vs. misfit:
beta misfit
1.04076E+01 3.54740E+02
2.08152E+01 5.47348E+02
chosen beta = 1.72632E+01
target misfit = 4.86877E+02
achieved misfit = 4.81217E+02
model norm = 1.41185E+02
misfit change = 5.05813E-01
model norm change = 1.48742E-01
norm comp Ws = 8.27069E+01
norm comp Wx = 3.78831E+01
norm comp Wz = 2.05954E+01
iter cpu time: 0:00:00.62
Iteration 10
beta vs. misfit:
beta misfit
4.31579E+00 2.09965E+02
8.63158E+00 2.93092E+02
chosen beta = 5.72809E+00
target misfit = 2.40608E+02
achieved misfit = 2.34998E+02
model norm = 1.66836E+02
misfit change = 5.11659E-01
model norm change = 1.81682E-01
norm comp Ws = 9.43748E+01
norm comp Wx = 4.67077E+01
norm comp Wz = 2.57538E+01
iter cpu time: 0:00:01.14
Iteration 11
beta vs. misfit:
beta misfit
1.43202E+00 1.08765E+02
2.86405E+00 1.48776E+02
chosen beta = 1.69894E+00
target misfit = 1.17499E+02
achieved misfit = 1.13855E+02
model norm = 2.07214E+02
misfit change = 5.15505E-01
model norm change = 2.42021E-01
norm comp Ws = 1.10709E+02
norm comp Wx = 6.50107E+01
norm comp Wz = 3.14941E+01
iter cpu time: 0:00:01.18
Iteration 12
beta vs. misfit:
beta misfit
4.24735E-01 4.69288E+01
8.49470E-01 5.82083E+01
chosen beta = 7.90778E-01
target misfit = 5.69276E+01
achieved misfit = 5.61534E+01
model norm = 2.39426E+02
misfit change = 5.06799E-01
model norm change = 1.55454E-01
norm comp Ws = 1.22208E+02
norm comp Wx = 7.90861E+01
norm comp Wz = 3.81319E+01
iter cpu time: 0:00:01.10
Iteration 13
beta vs. misfit:
beta misfit
5.07840E-01 2.85576E+01
6.33710E-01 3.23824E+01
1.13145E+00 5.17204E+01
chosen beta = 9.52357E-01
target misfit = 4.50000E+01
achieved misfit = 4.40177E+01
model norm = 2.37754E+02
misfit change = 2.16117E-01
model norm change = -6.98309E-03
norm comp Ws = 1.26074E+02
norm comp Wx = 7.63269E+01
norm comp Wz = 3.53536E+01
iter cpu time: 0:00:00.88
Iteration 14
beta vs. misfit:
beta misfit
9.73609E-01 3.64390E+01
9.95336E-01 3.71506E+01
1.23871E+00 4.57613E+01
chosen beta = 1.21709E+00
target misfit = 4.50000E+01
achieved misfit = 4.49504E+01
model norm = 2.30537E+02
misfit change = -2.11895E-02
model norm change = -3.03571E-02
norm comp Ws = 1.26466E+02
norm comp Wx = 7.21243E+01
norm comp Wz = 3.19461E+01
iter cpu time: 0:00:00.89
Target misfit achieved. Minimizing model norm.
Iteration 15
beta vs. misfit:
beta misfit
1.21843E+00 3.86348E+01
1.21978E+00 3.86736E+01
1.44018E+00 4.53382E+01
chosen beta = 1.42896E+00
target misfit = 4.50000E+01
achieved misfit = 4.49850E+01
model norm = 2.28950E+02
misfit change = -7.69307E-04
model norm change = -6.88525E-03
norm comp Ws = 1.25759E+02
norm comp Wx = 6.90749E+01
norm comp Wz = 3.41159E+01
iter cpu time: 0:00:00.95
Exit at convergence.
Iterations performed: 15
total cpu time: 0:00:16.25
DCINV2D ended on: 1/12/2016 21:07:18
simpegDCIP/Dev/Inv2D/dcinv2d.out
-19
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@@ -1,19 +0,0 @@
15 iter data misfit model norm beta
0 2.57080E+05 0.00000E+00 0.00000E+00
1 1.28540E+05 3.63297E+00 1.58499E+04
2 6.42774E+04 1.37169E+01 4.25263E+03
3 3.17674E+04 2.91306E+01 1.51222E+03
4 1.56569E+04 4.84312E+01 6.00000E+02
5 7.79602E+03 6.97577E+01 2.60199E+02
6 3.89800E+03 8.95751E+01 1.37400E+02
7 1.94758E+03 1.06566E+02 8.02499E+01
8 9.73755E+02 1.22904E+02 4.16303E+01
9 4.81217E+02 1.41185E+02 1.72632E+01
10 2.34998E+02 1.66836E+02 5.72809E+00
11 1.13855E+02 2.07214E+02 1.69894E+00
12 5.61534E+01 2.39426E+02 7.90778E-01
13 4.40177E+01 2.37754E+02 9.52357E-01
14 4.49504E+01 2.30537E+02 1.21709E+00
15 4.49850E+01 2.28950E+02 1.42896E+00
4.50000E+01 target misfit
45 number of data
simpegDCIP/Dev/Inv2D/dcinv2d.pre
-46
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@@ -1,46 +0,0 @@
! Predicted data ! GENERAL FORMAT
0.0000000E+00 0.0000000E+00 2.0000000E+02 3.0000000E+02 8.31819E-02
0.0000000E+00 0.0000000E+00 3.0000000E+02 4.0000000E+02 4.41288E-03
0.0000000E+00 0.0000000E+00 4.0000000E+02 5.0000000E+02 1.23515E-02
0.0000000E+00 0.0000000E+00 5.0000000E+02 6.0000000E+02 2.09881E-03
0.0000000E+00 0.0000000E+00 6.0000000E+02 7.0000000E+02 7.28316E-04
0.0000000E+00 0.0000000E+00 7.0000000E+02 8.0000000E+02 5.24885E-04
0.0000000E+00 0.0000000E+00 8.0000000E+02 9.0000000E+02 3.56979E-04
0.0000000E+00 0.0000000E+00 9.0000000E+02 1.0000000E+03 2.71240E-04
0.0000000E+00 0.0000000E+00 1.0000000E+03 1.1000000E+03 1.71849E-04
1.0000000E+02 1.0000000E+02 3.0000000E+02 4.0000000E+02 8.00012E-03
1.0000000E+02 1.0000000E+02 4.0000000E+02 5.0000000E+02 1.75080E-02
1.0000000E+02 1.0000000E+02 5.0000000E+02 6.0000000E+02 2.81046E-03
1.0000000E+02 1.0000000E+02 6.0000000E+02 7.0000000E+02 9.20650E-04
1.0000000E+02 1.0000000E+02 7.0000000E+02 8.0000000E+02 6.40887E-04
1.0000000E+02 1.0000000E+02 8.0000000E+02 9.0000000E+02 4.28101E-04
1.0000000E+02 1.0000000E+02 9.0000000E+02 1.0000000E+03 3.19325E-04
1.0000000E+02 1.0000000E+02 1.0000000E+03 1.1000000E+03 1.97133E-04
2.0000000E+02 2.0000000E+02 4.0000000E+02 5.0000000E+02 3.00094E-02
2.0000000E+02 2.0000000E+02 5.0000000E+02 6.0000000E+02 4.17179E-03
2.0000000E+02 2.0000000E+02 6.0000000E+02 7.0000000E+02 1.23020E-03
2.0000000E+02 2.0000000E+02 7.0000000E+02 8.0000000E+02 8.09705E-04
2.0000000E+02 2.0000000E+02 8.0000000E+02 9.0000000E+02 5.26566E-04
2.0000000E+02 2.0000000E+02 9.0000000E+02 1.0000000E+03 3.82914E-04
2.0000000E+02 2.0000000E+02 1.0000000E+03 1.1000000E+03 2.28587E-04
3.0000000E+02 3.0000000E+02 5.0000000E+02 6.0000000E+02 7.27481E-03
3.0000000E+02 3.0000000E+02 6.0000000E+02 7.0000000E+02 1.78177E-03
3.0000000E+02 3.0000000E+02 7.0000000E+02 8.0000000E+02 1.07707E-03
3.0000000E+02 3.0000000E+02 8.0000000E+02 9.0000000E+02 6.74696E-04
3.0000000E+02 3.0000000E+02 9.0000000E+02 1.0000000E+03 4.74671E-04
3.0000000E+02 3.0000000E+02 1.0000000E+03 1.1000000E+03 2.71808E-04
4.0000000E+02 4.0000000E+02 6.0000000E+02 7.0000000E+02 3.37547E-03
4.0000000E+02 4.0000000E+02 7.0000000E+02 8.0000000E+02 1.52487E-03
4.0000000E+02 4.0000000E+02 8.0000000E+02 9.0000000E+02 8.67080E-04
4.0000000E+02 4.0000000E+02 9.0000000E+02 1.0000000E+03 5.71693E-04
4.0000000E+02 4.0000000E+02 1.0000000E+03 1.1000000E+03 3.07672E-04
5.0000000E+02 5.0000000E+02 7.0000000E+02 8.0000000E+02 6.64946E-03
5.0000000E+02 5.0000000E+02 8.0000000E+02 9.0000000E+02 2.83925E-03
5.0000000E+02 5.0000000E+02 9.0000000E+02 1.0000000E+03 1.50341E-03
5.0000000E+02 5.0000000E+02 1.0000000E+03 1.1000000E+03 6.31242E-04
6.0000000E+02 6.0000000E+02 8.0000000E+02 9.0000000E+02 4.28770E-03
6.0000000E+02 6.0000000E+02 9.0000000E+02 1.0000000E+03 2.02291E-03
6.0000000E+02 6.0000000E+02 1.0000000E+03 1.1000000E+03 7.75855E-04
7.0000000E+02 7.0000000E+02 9.0000000E+02 1.0000000E+03 3.85090E-03
7.0000000E+02 7.0000000E+02 1.0000000E+03 1.1000000E+03 1.15357E-03
8.0000000E+02 8.0000000E+02 1.0000000E+03 1.1000000E+03 2.22667E-03
simpegDCIP/Dev/Inv2D/dcinv2d_0.pre
-46
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@@ -1,46 +0,0 @@
! Predicted data ! GENERAL FORMAT Last column are apparent conductivities.
0.0000000E+00 0.0000000E+00 2.0000000E+02 3.0000000E+02 2.63497E-02 1.00668E-02
0.0000000E+00 0.0000000E+00 3.0000000E+02 4.0000000E+02 1.31837E-02 1.00601E-02
0.0000000E+00 0.0000000E+00 4.0000000E+02 5.0000000E+02 7.93784E-03 1.00251E-02
0.0000000E+00 0.0000000E+00 5.0000000E+02 6.0000000E+02 5.30187E-03 1.00062E-02
0.0000000E+00 0.0000000E+00 6.0000000E+02 7.0000000E+02 3.79075E-03 9.99646E-03
0.0000000E+00 0.0000000E+00 7.0000000E+02 8.0000000E+02 2.84529E-03 9.98863E-03
0.0000000E+00 0.0000000E+00 8.0000000E+02 9.0000000E+02 2.21518E-03 9.97881E-03
0.0000000E+00 0.0000000E+00 9.0000000E+02 1.0000000E+03 1.77462E-03 9.96491E-03
0.0000000E+00 0.0000000E+00 1.0000000E+03 1.1000000E+03 1.45107E-03 9.97103E-03
1.0000000E+02 1.0000000E+02 3.0000000E+02 4.0000000E+02 2.64919E-02 1.00128E-02
1.0000000E+02 1.0000000E+02 4.0000000E+02 5.0000000E+02 1.32352E-02 1.00209E-02
1.0000000E+02 1.0000000E+02 5.0000000E+02 6.0000000E+02 7.96229E-03 9.99429E-03
1.0000000E+02 1.0000000E+02 6.0000000E+02 7.0000000E+02 5.31543E-03 9.98068E-03
1.0000000E+02 1.0000000E+02 7.0000000E+02 8.0000000E+02 3.79921E-03 9.97417E-03
1.0000000E+02 1.0000000E+02 8.0000000E+02 9.0000000E+02 2.85122E-03 9.96784E-03
1.0000000E+02 1.0000000E+02 9.0000000E+02 1.0000000E+03 2.21994E-03 9.95742E-03
1.0000000E+02 1.0000000E+02 1.0000000E+03 1.1000000E+03 1.77401E-03 9.96831E-03
2.0000000E+02 2.0000000E+02 4.0000000E+02 5.0000000E+02 2.65164E-02 1.00036E-02
2.0000000E+02 2.0000000E+02 5.0000000E+02 6.0000000E+02 1.32488E-02 1.00106E-02
2.0000000E+02 2.0000000E+02 6.0000000E+02 7.0000000E+02 7.97076E-03 9.98368E-03
2.0000000E+02 2.0000000E+02 7.0000000E+02 8.0000000E+02 5.32136E-03 9.96956E-03
2.0000000E+02 2.0000000E+02 8.0000000E+02 9.0000000E+02 3.80396E-03 9.96173E-03
2.0000000E+02 2.0000000E+02 9.0000000E+02 1.0000000E+03 2.85567E-03 9.95231E-03
2.0000000E+02 2.0000000E+02 1.0000000E+03 1.1000000E+03 2.21779E-03 9.96706E-03
3.0000000E+02 3.0000000E+02 5.0000000E+02 6.0000000E+02 2.65249E-02 1.00004E-02
3.0000000E+02 3.0000000E+02 6.0000000E+02 7.0000000E+02 1.32547E-02 1.00062E-02
3.0000000E+02 3.0000000E+02 7.0000000E+02 8.0000000E+02 7.97549E-03 9.97775E-03
3.0000000E+02 3.0000000E+02 8.0000000E+02 9.0000000E+02 5.32580E-03 9.96125E-03
3.0000000E+02 3.0000000E+02 9.0000000E+02 1.0000000E+03 3.80888E-03 9.94888E-03
3.0000000E+02 3.0000000E+02 1.0000000E+03 1.1000000E+03 2.85172E-03 9.96611E-03
4.0000000E+02 4.0000000E+02 6.0000000E+02 7.0000000E+02 2.65296E-02 9.99858E-03
4.0000000E+02 4.0000000E+02 7.0000000E+02 8.0000000E+02 1.32592E-02 1.00028E-02
4.0000000E+02 4.0000000E+02 8.0000000E+02 9.0000000E+02 7.98040E-03 9.97162E-03
4.0000000E+02 4.0000000E+02 9.0000000E+02 1.0000000E+03 5.33212E-03 9.94944E-03
4.0000000E+02 4.0000000E+02 1.0000000E+03 1.1000000E+03 3.80236E-03 9.96593E-03
5.0000000E+02 5.0000000E+02 7.0000000E+02 8.0000000E+02 2.65345E-02 9.99673E-03
5.0000000E+02 5.0000000E+02 8.0000000E+02 9.0000000E+02 1.32655E-02 9.99807E-03
5.0000000E+02 5.0000000E+02 9.0000000E+02 1.0000000E+03 7.98964E-03 9.96008E-03
5.0000000E+02 5.0000000E+02 1.0000000E+03 1.1000000E+03 5.32134E-03 9.96960E-03
6.0000000E+02 6.0000000E+02 8.0000000E+02 9.0000000E+02 2.65437E-02 9.99326E-03
6.0000000E+02 6.0000000E+02 9.0000000E+02 1.0000000E+03 1.32806E-02 9.98668E-03
6.0000000E+02 6.0000000E+02 1.0000000E+03 1.1000000E+03 7.97063E-03 9.98384E-03
7.0000000E+02 7.0000000E+02 9.0000000E+02 1.0000000E+03 2.65717E-02 9.98273E-03
7.0000000E+02 7.0000000E+02 1.0000000E+03 1.1000000E+03 1.32427E-02 1.00153E-02
8.0000000E+02 8.0000000E+02 1.0000000E+03 1.1000000E+03 2.64774E-02 1.00183E-02
simpegDCIP/Dev/Inv2D/sensitivity.txt
-46
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@@ -1,46 +0,0 @@
81 45
1.00411E-13 3.10408E-13 9.74717E-13 3.09564E-12 9.68504E-12 2.91605E-11 8.35615E-11 2.28263E-10 6.04123E-10 1.61401E-09 4.67374E-09 1.58647E-08 6.23317E-08 2.35358E-07 1.71041E-08 2.08590E-07 1.56029E-07 1.46650E-07 1.72752E-07 1.54926E-07 1.77390E-07 2.03028E-07 2.69140E-07 4.10395E-07 1.29687E-07 7.93598E-07 2.97657E-07 1.28094E-07 7.80834E-08 7.94358E-08 1.06544E-07 6.15537E-08 7.23303E-08 1.38411E-07 8.59111E-08 1.68916E-07 1.64240E-07 1.58717E-07 1.44871E-07 1.00497E-07 1.53571E-07 1.14875E-07 1.03632E-07 9.31407E-08 4.54508E-08 5.91715E-08 3.66679E-08 6.10459E-08 1.23422E-07 6.11907E-08 8.25315E-08 6.19628E-08 8.25261E-08 1.49285E-07 7.23998E-08 1.14387E-07 8.11571E-08 6.93066E-08 7.27982E-08 5.00166E-08 1.01158E-07 5.96975E-08 4.37654E-08 4.14493E-08 3.33156E-08 6.30583E-08 3.86673E-08 2.63025E-08 1.28371E-08 7.03143E-09 2.55569E-09 6.86395E-10 2.47006E-10 1.07284E-10 4.64772E-11 1.87670E-11 6.99064E-12 2.43083E-12 8.12035E-13 2.70167E-13 9.04729E-14
1.00408E-13 3.10389E-13 9.74598E-13 3.09493E-12 9.68107E-12 2.91394E-11 8.34535E-11 2.27725E-10 6.01411E-10 1.59939E-09 4.58076E-09 1.50821E-08 5.37357E-08 1.45015E-07 9.49187E-08 3.64320E-08 2.63448E-08 4.94770E-08 6.85655E-08 7.00921E-08 5.92742E-08 6.09382E-08 4.59596E-08 9.87180E-08 2.28836E-07 4.66832E-07 1.96472E-07 6.17388E-08 3.68928E-08 7.81857E-08 6.83590E-08 3.70845E-08 2.61880E-08 3.78832E-08 3.43796E-08 8.14050E-08 1.25510E-07 1.28215E-07 8.53512E-08 2.97777E-08 6.74204E-08 7.99932E-08 7.90362E-08 5.79363E-08 2.71734E-08 3.44196E-08 2.90110E-08 4.29354E-08 7.81656E-08 3.22896E-08 2.56389E-08 2.96368E-08 4.22860E-08 6.50714E-08 3.97379E-08 3.15747E-08 3.02920E-08 2.68593E-08 2.63743E-08 3.31479E-08 4.64930E-08 3.35157E-08 2.40778E-08 1.98269E-08 2.25180E-08 2.99855E-08 2.16250E-08 1.19611E-08 3.79368E-09 5.30861E-09 2.42064E-09 6.74309E-10 2.45568E-10 1.07010E-10 4.64139E-11 1.87527E-11 6.98765E-12 2.43026E-12 8.11935E-13 2.70151E-13 9.04706E-14
1.00403E-13 3.10352E-13 9.74361E-13 3.09352E-12 9.67313E-12 2.90971E-11 8.32379E-11 2.26652E-10 5.96028E-10 1.57061E-09 4.40228E-09 1.37248E-08 4.29042E-08 9.30852E-08 9.29476E-08 7.55456E-08 5.93963E-08 4.76051E-08 4.12935E-08 3.65352E-08 3.71970E-08 5.21912E-08 8.02057E-08 1.21892E-07 1.86496E-07 2.35135E-07 1.04732E-07 4.22783E-08 4.65762E-08 7.58073E-08 7.79331E-08 5.75407E-08 3.61509E-08 2.56255E-08 3.04573E-08 5.36578E-08 9.24811E-08 9.80266E-08 6.17923E-08 2.36365E-08 3.82806E-08 5.03284E-08 5.12491E-08 3.73919E-08 2.34194E-08 2.60215E-08 2.90466E-08 2.45768E-08 3.72154E-08 2.46155E-08 1.95316E-08 1.83760E-08 1.99613E-08 2.36885E-08 2.06672E-08 1.50154E-08 1.45427E-08 1.58183E-08 1.70564E-08 1.86277E-08 2.16690E-08 1.97339E-08 1.67292E-08 1.43288E-08 1.38128E-08 1.49270E-08 1.10184E-08 5.71202E-09 3.08046E-09 4.21637E-09 2.22842E-09 6.53757E-10 2.42850E-10 1.06473E-10 4.62878E-11 1.87241E-11 6.98166E-12 2.42911E-12 8.11735E-13 2.70119E-13 9.04659E-14
1.00395E-13 3.10297E-13 9.74007E-13 3.09140E-12 9.66126E-12 2.90340E-11 8.29162E-11 2.25056E-10 5.88072E-10 1.52870E-09 4.15246E-09 1.20281E-08 3.25763E-08 6.12733E-08 7.24227E-08 7.24351E-08 6.89739E-08 6.44213E-08 6.06043E-08 5.88049E-08 6.12468E-08 7.02526E-08 8.55137E-08 1.01379E-07 1.17435E-07 1.10049E-07 5.93222E-08 3.57569E-08 4.43427E-08 6.79194E-08 7.87981E-08 6.57704E-08 4.31389E-08 2.76129E-08 2.75646E-08 4.19311E-08 6.75913E-08 7.21313E-08 4.69404E-08 2.17775E-08 2.38212E-08 3.41662E-08 3.39607E-08 2.71160E-08 2.20754E-08 2.36058E-08 2.62335E-08 2.39947E-08 2.08291E-08 1.86009E-08 1.69637E-08 1.56636E-08 1.45648E-08 1.45218E-08 1.31646E-08 1.11608E-08 1.04547E-08 1.10253E-08 1.18592E-08 1.22029E-08 1.25574E-08 1.22845E-08 1.09972E-08 9.27076E-09 8.52098E-09 8.26660E-09 6.25092E-09 3.63958E-09 2.74981E-09 3.36581E-09 2.00653E-09 6.28282E-10 2.39092E-10 1.05685E-10 4.60999E-11 1.86812E-11 6.97267E-12 2.42739E-12 8.11435E-13 2.70071E-13 9.04589E-14
1.00384E-13 3.10223E-13 9.73535E-13 3.08858E-12 9.64549E-12 2.89501E-11 8.24901E-11 2.22953E-10 5.77686E-10 1.47517E-09 3.85028E-09 1.02301E-08 2.40819E-08 4.09946E-08 5.15113E-08 5.66371E-08 5.89699E-08 5.94047E-08 5.89331E-08 5.84650E-08 5.93855E-08 6.22206E-08 6.78377E-08 7.13474E-08 6.93776E-08 5.69048E-08 3.70412E-08 2.95279E-08 3.94982E-08 5.92464E-08 7.22061E-08 6.40885E-08 4.40738E-08 2.78255E-08 2.51527E-08 3.40307E-08 4.93936E-08 5.18882E-08 3.56867E-08 2.04985E-08 1.83801E-08 2.24585E-08 2.41321E-08 2.17185E-08 1.94928E-08 2.06288E-08 2.24118E-08 2.28724E-08 2.02549E-08 1.76004E-08 1.56231E-08 1.40811E-08 1.27921E-08 1.17500E-08 1.06340E-08 9.42140E-09 8.66731E-09 8.58213E-09 8.57312E-09 8.46942E-09 8.19420E-09 7.86826E-09 7.17032E-09 5.95046E-09 5.55749E-09 5.19157E-09 4.13317E-09 2.91236E-09 2.33485E-09 2.69307E-09 1.77544E-09 6.00266E-10 2.34548E-10 1.04670E-10 4.58521E-11 1.86242E-11 6.96069E-12 2.42509E-12 8.11034E-13 2.70007E-13 9.04495E-14
1.00371E-13 3.10131E-13 9.72945E-13 3.08506E-12 9.62578E-12 2.88456E-11 8.19609E-11 2.20358E-10 5.65059E-10 1.41203E-09 3.51764E-09 8.52308E-09 1.76652E-08 2.78171E-08 3.52435E-08 4.02390E-08 4.36436E-08 4.55593E-08 4.62885E-08 4.61935E-08 4.58570E-08 4.59609E-08 4.64599E-08 4.56144E-08 4.14404E-08 3.34164E-08 2.49965E-08 2.53810E-08 3.47950E-08 5.06486E-08 6.17827E-08 5.69160E-08 4.16721E-08 2.78329E-08 2.33998E-08 2.81598E-08 3.63162E-08 3.71243E-08 2.70011E-08 1.91329E-08 1.63397E-08 1.47793E-08 1.66401E-08 1.65319E-08 1.60060E-08 1.71740E-08 1.88635E-08 1.96484E-08 1.89244E-08 1.69428E-08 1.49295E-08 1.32093E-08 1.17339E-08 1.04676E-08 9.36066E-09 8.39593E-09 7.61931E-09 7.12654E-09 6.73969E-09 6.24094E-09 5.73430E-09 5.35322E-09 4.79423E-09 4.16788E-09 3.88162E-09 3.63303E-09 3.07894E-09 2.47285E-09 2.04204E-09 2.17776E-09 1.55221E-09 5.71028E-10 2.29430E-10 1.03448E-10 4.55470E-11 1.85534E-11 6.94577E-12 2.42222E-12 8.10534E-13 2.69927E-13 9.04378E-14
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9.45853E-14 2.72125E-13 7.45882E-13 1.88587E-12 4.18208E-12 7.79999E-12 1.21503E-11 1.62390E-11 1.93759E-11 2.14256E-11 2.26089E-11 2.32274E-11 2.35214E-11 2.36446E-11 2.36846E-11 2.36824E-11 2.36510E-11 2.35896E-11 2.34974E-11 2.33739E-11 2.32184E-11 2.30306E-11 2.28102E-11 2.25570E-11 2.22711E-11 2.19526E-11 2.16015E-11 2.12185E-11 2.08098E-11 2.04768E-11 2.01119E-11 1.97157E-11 1.92889E-11 1.88326E-11 1.83480E-11 1.78363E-11 1.72988E-11 1.67370E-11 1.61527E-11 1.55476E-11 1.49235E-11 1.42823E-11 1.36260E-11 1.29566E-11 1.22763E-11 1.15871E-11 1.09034E-11 1.02289E-11 9.56282E-12 8.93731E-12 8.47900E-12 8.08176E-12 7.84549E-12 7.69854E-12 7.65803E-12 7.62033E-12 7.58228E-12 7.55754E-12 7.51848E-12 7.46030E-12 7.38393E-12 7.31582E-12 7.24615E-12 7.17996E-12 7.11762E-12 7.06398E-12 7.01976E-12 6.97063E-12 6.92949E-12 6.95132E-12 7.06851E-12 7.44475E-12 7.81153E-12 7.79631E-12 6.84191E-12 5.02678E-12 3.00325E-12 1.47319E-12 6.20516E-13 2.37118E-13 8.53487E-14
9.29105E-14 2.61903E-13 6.90857E-13 1.64355E-12 3.36904E-12 5.77987E-12 8.35514E-12 1.05216E-11 1.20107E-11 1.28718E-11 1.32952E-11 1.34641E-11 1.35040E-11 1.34871E-11 1.34506E-11 1.34024E-11 1.33400E-11 1.32630E-11 1.31712E-11 1.30646E-11 1.29431E-11 1.28064E-11 1.26547E-11 1.24880E-11 1.23064E-11 1.21100E-11 1.18991E-11 1.16737E-11 1.14343E-11 1.12059E-11 1.09970E-11 1.07744E-11 1.05384E-11 1.02894E-11 1.00281E-11 9.75498E-12 9.47048E-12 9.17526E-12 8.87002E-12 8.55550E-12 8.23245E-12 7.90159E-12 7.56370E-12 7.21963E-12 6.87023E-12 6.51634E-12 6.15882E-12 5.80525E-12 5.45640E-12 5.10952E-12 4.77615E-12 4.53732E-12 4.30485E-12 4.17421E-12 4.04644E-12 4.01937E-12 3.99302E-12 3.97821E-12 3.95837E-12 3.94710E-12 3.92761E-12 3.90021E-12 3.87555E-12 3.85423E-12 3.83325E-12 3.81803E-12 3.80569E-12 3.79848E-12 3.79650E-12 3.84150E-12 3.95655E-12 4.26273E-12 4.64846E-12 4.89623E-12 4.61056E-12 3.68796E-12 2.41122E-12 1.28282E-12 5.74791E-13 2.28312E-13 8.38727E-14
9.06671E-14 2.48805E-13 6.24443E-13 1.37534E-12 2.56476E-12 4.00741E-12 5.35705E-12 6.35734E-12 6.95622E-12 7.24368E-12 7.34172E-12 7.34416E-12 7.30730E-12 7.26003E-12 7.21523E-12 7.16992E-12 7.11836E-12 7.06049E-12 6.99628E-12 6.92573E-12 6.84883E-12 6.76561E-12 6.67607E-12 6.58027E-12 6.47830E-12 6.37025E-12 6.25618E-12 6.13622E-12 6.01050E-12 5.87921E-12 5.74374E-12 5.62936E-12 5.50959E-12 5.38460E-12 5.25460E-12 5.11977E-12 4.98031E-12 4.83645E-12 4.68844E-12 4.53655E-12 4.38104E-12 4.22217E-12 4.06024E-12 3.89553E-12 3.72835E-12 3.55900E-12 3.38781E-12 3.21509E-12 3.04115E-12 2.87034E-12 2.70128E-12 2.53193E-12 2.37434E-12 2.25785E-12 2.14781E-12 2.07037E-12 2.00737E-12 1.96590E-12 1.95374E-12 1.94469E-12 1.93651E-12 1.92894E-12 1.92424E-12 1.91643E-12 1.91099E-12 1.90857E-12 1.90707E-12 1.90928E-12 1.91667E-12 1.94195E-12 2.01744E-12 2.19623E-12 2.49199E-12 2.79163E-12 2.84879E-12 2.50718E-12 1.82182E-12 1.07161E-12 5.19628E-13 2.17034E-13 8.18944E-14
8.76274E-14 2.32052E-13 5.45719E-13 1.08871E-12 1.80554E-12 2.52935E-12 3.10601E-12 3.47319E-12 3.65506E-12 3.71442E-12 3.70935E-12 3.67777E-12 3.63984E-12 3.60461E-12 3.57520E-12 3.54764E-12 3.51773E-12 3.48549E-12 3.45089E-12 3.41395E-12 3.37468E-12 3.33309E-12 3.28920E-12 3.24301E-12 3.19457E-12 3.14392E-12 3.09106E-12 3.03606E-12 2.97895E-12 2.91978E-12 2.85862E-12 2.79551E-12 2.73051E-12 2.66370E-12 2.60454E-12 2.54603E-12 2.48580E-12 2.42392E-12 2.36046E-12 2.29551E-12 2.22913E-12 2.16141E-12 2.09243E-12 2.02228E-12 1.95106E-12 1.87886E-12 1.80576E-12 1.73188E-12 1.65730E-12 1.58213E-12 1.50647E-12 1.43040E-12 1.35405E-12 1.27941E-12 1.20552E-12 1.13158E-12 1.06482E-12 1.01509E-12 9.68017E-13 9.24674E-13 8.96954E-13 8.72307E-13 8.54023E-13 8.48478E-13 8.45922E-13 8.42764E-13 8.39459E-13 8.38982E-13 8.44741E-13 8.55990E-13 8.83681E-13 9.55281E-13 1.10925E-12 1.33704E-12 1.52295E-12 1.51613E-12 1.26106E-12 8.44907E-13 4.54188E-13 2.02613E-13 7.92114E-14
8.36871E-14 2.11997E-13 4.60601E-13 8.15381E-13 1.17142E-12 1.43328E-12 1.58758E-12 1.66071E-12 1.68239E-12 1.67669E-12 1.65967E-12 1.64019E-12 1.62233E-12 1.60750E-12 1.59582E-12 1.58528E-12 1.57415E-12 1.56245E-12 1.55015E-12 1.53727E-12 1.52380E-12 1.50973E-12 1.49507E-12 1.47981E-12 1.46395E-12 1.44749E-12 1.43044E-12 1.41279E-12 1.39454E-12 1.37571E-12 1.35628E-12 1.33627E-12 1.31567E-12 1.29450E-12 1.27277E-12 1.25046E-12 1.22761E-12 1.20420E-12 1.18027E-12 1.15580E-12 1.13082E-12 1.10534E-12 1.07936E-12 1.05292E-12 1.02601E-12 1.00195E-12 9.78502E-13 9.54632E-13 9.30349E-13 9.05668E-13 8.80605E-13 8.55175E-13 8.29397E-13 8.03290E-13 7.76874E-13 7.50167E-13 7.23191E-13 6.95967E-13 6.68518E-13 6.40865E-13 6.13031E-13 5.85039E-13 5.56915E-13 5.28682E-13 5.00433E-13 4.73117E-13 4.45755E-13 4.13820E-13 3.84114E-13 3.45355E-13 3.18491E-13 3.24929E-13 3.61710E-13 4.47700E-13 6.15733E-13 7.72106E-13 7.87687E-13 6.27249E-13 3.83284E-13 1.85351E-13 7.57304E-14
simpegDCIP/Dev/JSAnimation/IPython_display.py
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from .html_writer import HTMLWriter
from matplotlib.animation import Animation
import matplotlib.pyplot as plt
import tempfile
import random
import os
__all__ = ['anim_to_html', 'display_animation']
class _NameOnlyTemporaryFile(object):
"""A context-managed temporary file which is not opened.
The file should be accessible by name on any system.
Parameters
----------
suffix : string
The suffix of the temporary file (default = '')
prefix : string
The prefix of the temporary file (default = '_tmp_')
hash_length : string
The length of the random hash. The size of the hash space will
be 16 ** hash_length (default=8)
seed : integer
the seed for the random number generator. If not specified, the
system time will be used as a seed.
absolute : boolean
If true, return an absolute path to a temporary file in the current
working directory.
Example
-------
>>> with _NameOnlyTemporaryFile(seed=0, absolute=False) as f:
... print(f)
...
_tmp_d82c07cd
>>> os.path.exists('_tmp_d82c07cd') # file removed after context
False
"""
def __init__(self, prefix='_tmp_', suffix='', hash_length=8,
seed=None, absolute=True):
rng = random.Random(seed)
self.name = '%s%0*x%s' % (prefix, hash_length,
rng.getrandbits(4 * hash_length), suffix)
if absolute:
self.name = os.path.abspath(self.name)
def __enter__(self):
return self
def __exit__(self, *exc_info):
if os.path.exists(self.name):
os.remove(self.name)
def anim_to_html(anim, fps=None, embed_frames=True, default_mode='loop'):
"""Generate HTML representation of the animation"""
if fps is None and hasattr(anim, '_interval'):
# Convert interval in ms to frames per second
fps = 1000. / anim._interval
plt.close(anim._fig)
if hasattr(anim, "_html_representation"):
return anim._html_representation
else:
# tempfile can't be used here: we need a filename, and this
# fails on windows. Instead, we use a custom filename generator
#with tempfile.NamedTemporaryFile(suffix='.html') as f:
with _NameOnlyTemporaryFile(suffix='.html') as f:
anim.save(f.name, writer=HTMLWriter(fps=fps,
embed_frames=embed_frames,
default_mode=default_mode))
html = open(f.name).read()
anim._html_representation = html
return html
def display_animation(anim, **kwargs):
"""Display the animation with an IPython HTML object"""
from IPython.display import HTML
return HTML(anim_to_html(anim, **kwargs))
# This is the magic that makes animations display automatically in the
# IPython notebook. The _repr_html_ method is a special method recognized
# by IPython.
Animation._repr_html_ = anim_to_html
simpegDCIP/Dev/JSAnimation/__init__.py
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@@ -1 +0,0 @@
from .html_writer import HTMLWriter
simpegDCIP/Dev/JSAnimation/examples.py
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import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
from JSAnimation import IPython_display
def basic_animation(frames=100, interval=30):
"""Plot a basic sine wave with oscillating amplitude"""
fig = plt.figure()
ax = plt.axes(xlim=(0, 10), ylim=(-2, 2))
line, = ax.plot([], [], lw=2)
x = np.linspace(0, 10, 1000)
def init():
line.set_data([], [])
return line,
def animate(i):
y = np.cos(i * 0.02 * np.pi) * np.sin(x - i * 0.02 * np.pi)
line.set_data(x, y)
return line,
return animation.FuncAnimation(fig, animate, init_func=init,
frames=frames, interval=interval)
def lorenz_animation(N_trajectories=20, rseed=1, frames=200, interval=30):
"""Plot a 3D visualization of the dynamics of the Lorenz system"""
from scipy import integrate
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.colors import cnames
def lorentz_deriv(coords, t0, sigma=10., beta=8./3, rho=28.0):
"""Compute the time-derivative of a Lorentz system."""
x, y, z = coords
return [sigma * (y - x), x * (rho - z) - y, x * y - beta * z]
# Choose random starting points, uniformly distributed from -15 to 15
np.random.seed(rseed)
x0 = -15 + 30 * np.random.random((N_trajectories, 3))
# Solve for the trajectories
t = np.linspace(0, 2, 500)
x_t = np.asarray([integrate.odeint(lorentz_deriv, x0i, t)
for x0i in x0])
# Set up figure & 3D axis for animation
fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1], projection='3d')
ax.axis('off')
# choose a different color for each trajectory
colors = plt.cm.jet(np.linspace(0, 1, N_trajectories))
# set up lines and points
lines = sum([ax.plot([], [], [], '-', c=c)
for c in colors], [])
pts = sum([ax.plot([], [], [], 'o', c=c, ms=4)
for c in colors], [])
# prepare the axes limits
ax.set_xlim((-25, 25))
ax.set_ylim((-35, 35))
ax.set_zlim((5, 55))
# set point-of-view: specified by (altitude degrees, azimuth degrees)
ax.view_init(30, 0)
# initialization function: plot the background of each frame
def init():
for line, pt in zip(lines, pts):
line.set_data([], [])
line.set_3d_properties([])
pt.set_data([], [])
pt.set_3d_properties([])
return lines + pts
# animation function: called sequentially
def animate(i):
# we'll step two time-steps per frame. This leads to nice results.
i = (2 * i) % x_t.shape[1]
for line, pt, xi in zip(lines, pts, x_t):
x, y, z = xi[:i + 1].T
line.set_data(x, y)
line.set_3d_properties(z)
pt.set_data(x[-1:], y[-1:])
pt.set_3d_properties(z[-1:])
ax.view_init(30, 0.3 * i)
fig.canvas.draw()
return lines + pts
return animation.FuncAnimation(fig, animate, init_func=init,
frames=frames, interval=interval)
simpegDCIP/Dev/JSAnimation/html_writer.py
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import os
import sys
import random
import string
import warnings
if sys.version_info < (3, 0):
from cStringIO import StringIO as InMemory
else:
from io import BytesIO as InMemory
from matplotlib.animation import writers, FileMovieWriter
from base64 import b64encode
ICON_DIR = os.path.join(os.path.dirname(__file__), 'icons')
class _Icons(object):
"""This class is a container for base64 representations of the icons"""
icons = ['first', 'prev', 'reverse', 'pause', 'play', 'next', 'last']
def __init__(self, icon_dir=ICON_DIR, extension='png'):
self.icon_dir = icon_dir
self.extension = extension
for icon in self.icons:
setattr(self, icon,
self._load_base64('{0}.{1}'.format(icon, extension)))
def _load_base64(self, filename):
data = open(os.path.join(self.icon_dir, filename), 'rb').read()
return 'data:image/{0};base64,{1}'.format(self.extension,
b64encode(data).decode('ascii'))
JS_INCLUDE = """
<script language="javascript">
/* Define the Animation class */
function Animation(frames, img_id, slider_id, interval, loop_select_id){
this.img_id = img_id;
this.slider_id = slider_id;
this.loop_select_id = loop_select_id;
this.interval = interval;
this.current_frame = 0;
this.direction = 0;
this.timer = null;
this.frames = new Array(frames.length);
for (var i=0; i<frames.length; i++)
{
this.frames[i] = new Image();
this.frames[i].src = frames[i];
}
document.getElementById(this.slider_id).max = this.frames.length - 1;
this.set_frame(this.current_frame);
}
Animation.prototype.get_loop_state = function(){
var button_group = document[this.loop_select_id].state;
for (var i = 0; i < button_group.length; i++) {
var button = button_group[i];
if (button.checked) {
return button.value;
}
}
return undefined;
}
Animation.prototype.set_frame = function(frame){
this.current_frame = frame;
document.getElementById(this.img_id).src = this.frames[this.current_frame].src;
document.getElementById(this.slider_id).value = this.current_frame;
}
Animation.prototype.next_frame = function()
{
this.set_frame(Math.min(this.frames.length - 1, this.current_frame + 1));
}
Animation.prototype.previous_frame = function()
{
this.set_frame(Math.max(0, this.current_frame - 1));
}
Animation.prototype.first_frame = function()
{
this.set_frame(0);
}
Animation.prototype.last_frame = function()
{
this.set_frame(this.frames.length - 1);
}
Animation.prototype.slower = function()
{
this.interval /= 0.7;
if(this.direction > 0){this.play_animation();}
else if(this.direction < 0){this.reverse_animation();}
}
Animation.prototype.faster = function()
{
this.interval *= 0.7;
if(this.direction > 0){this.play_animation();}
else if(this.direction < 0){this.reverse_animation();}
}
Animation.prototype.anim_step_forward = function()
{
this.current_frame += 1;
if(this.current_frame < this.frames.length){
this.set_frame(this.current_frame);
}else{
var loop_state = this.get_loop_state();
if(loop_state == "loop"){
this.first_frame();
}else if(loop_state == "reflect"){
this.last_frame();
this.reverse_animation();
}else{
this.pause_animation();
this.last_frame();
}
}
}
Animation.prototype.anim_step_reverse = function()
{
this.current_frame -= 1;
if(this.current_frame >= 0){
this.set_frame(this.current_frame);
}else{
var loop_state = this.get_loop_state();
if(loop_state == "loop"){
this.last_frame();
}else if(loop_state == "reflect"){
this.first_frame();
this.play_animation();
}else{
this.pause_animation();
this.first_frame();
}
}
}
Animation.prototype.pause_animation = function()
{
this.direction = 0;
if (this.timer){
clearInterval(this.timer);
this.timer = null;
}
}
Animation.prototype.play_animation = function()
{
this.pause_animation();
this.direction = 1;
var t = this;
if (!this.timer) this.timer = setInterval(function(){t.anim_step_forward();}, this.interval);
}
Animation.prototype.reverse_animation = function()
{
this.pause_animation();
this.direction = -1;
var t = this;
if (!this.timer) this.timer = setInterval(function(){t.anim_step_reverse();}, this.interval);
}
</script>
"""
DISPLAY_TEMPLATE = """
<div class="animation" align="center">
<img id="_anim_img{id}">
<br>
<input id="_anim_slider{id}" type="range" style="width:350px" name="points" min="0" max="1" step="1" value="0" onchange="anim{id}.set_frame(parseInt(this.value));"></input>
<br>
<button onclick="anim{id}.slower()">&#8211;</button>
<button onclick="anim{id}.first_frame()"><img class="anim_icon" src="{icons.first}"></button>
<button onclick="anim{id}.previous_frame()"><img class="anim_icon" src="{icons.prev}"></button>
<button onclick="anim{id}.reverse_animation()"><img class="anim_icon" src="{icons.reverse}"></button>
<button onclick="anim{id}.pause_animation()"><img class="anim_icon" src="{icons.pause}"></button>
<button onclick="anim{id}.play_animation()"><img class="anim_icon" src="{icons.play}"></button>
<button onclick="anim{id}.next_frame()"><img class="anim_icon" src="{icons.next}"></button>
<button onclick="anim{id}.last_frame()"><img class="anim_icon" src="{icons.last}"></button>
<button onclick="anim{id}.faster()">+</button>
<form action="#n" name="_anim_loop_select{id}" class="anim_control">
<input type="radio" name="state" value="once" {once_checked}> Once </input>
<input type="radio" name="state" value="loop" {loop_checked}> Loop </input>
<input type="radio" name="state" value="reflect" {reflect_checked}> Reflect </input>
</form>
</div>
<script language="javascript">
/* Instantiate the Animation class. */
/* The IDs given should match those used in the template above. */
(function() {{
var img_id = "_anim_img{id}";
var slider_id = "_anim_slider{id}";
var loop_select_id = "_anim_loop_select{id}";
var frames = new Array({Nframes});
{fill_frames}
/* set a timeout to make sure all the above elements are created before
the object is initialized. */
setTimeout(function() {{
anim{id} = new Animation(frames, img_id, slider_id, {interval}, loop_select_id);
}}, 0);
}})()
</script>
"""
INCLUDED_FRAMES = """
for (var i=0; i<{Nframes}; i++){{
frames[i] = "{frame_dir}/frame" + ("0000000" + i).slice(-7) + ".{frame_format}";
}}
"""
def _included_frames(frame_list, frame_format):
"""frame_list should be a list of filenames"""
return INCLUDED_FRAMES.format(Nframes=len(frame_list),
frame_dir=os.path.dirname(frame_list[0]),
frame_format=frame_format)
def _embedded_frames(frame_list, frame_format):
"""frame_list should be a list of base64-encoded png files"""
template = ' frames[{0}] = "data:image/{1};base64,{2}"\n'
embedded = "\n"
for i, frame_data in enumerate(frame_list):
embedded += template.format(i, frame_format,
frame_data.replace('\n', '\\\n'))
return embedded
@writers.register('html')
class HTMLWriter(FileMovieWriter):
# we start the animation id count at a random number: this way, if two
# animations are meant to be included on one HTML page, there is a
# very small chance of conflict.
rng = random.Random()
exec_key = 'animation.ffmpeg_path'
args_key = 'animation.ffmpeg_args'
supported_formats = ['png', 'jpeg', 'tiff', 'svg']
@classmethod
def new_id(cls):
#return '%16x' % cls.rng.getrandbits(64)
return ''.join(cls.rng.choice(string.ascii_uppercase)
for x in range(16))
def __init__(self, fps=30, codec=None, bitrate=None, extra_args=None,
metadata=None, embed_frames=False, default_mode='loop'):
self.embed_frames = embed_frames
self.default_mode = default_mode.lower()
if self.default_mode not in ['loop', 'once', 'reflect']:
self.default_mode = 'loop'
warnings.warn("unrecognized default_mode: using 'loop'")
self._saved_frames = list()
super(HTMLWriter, self).__init__(fps, codec, bitrate,
extra_args, metadata)
def setup(self, fig, outfile, dpi, frame_dir=None):
if os.path.splitext(outfile)[-1] not in ['.html', '.htm']:
raise ValueError("outfile must be *.htm or *.html")
if not self.embed_frames:
if frame_dir is None:
frame_dir = outfile.rstrip('.html') + '_frames'
if not os.path.exists(frame_dir):
os.makedirs(frame_dir)
frame_prefix = os.path.join(frame_dir, 'frame')
else:
frame_prefix = None
super(HTMLWriter, self).setup(fig, outfile, dpi,
frame_prefix, clear_temp=False)
def grab_frame(self, **savefig_kwargs):
if self.embed_frames:
suffix = '.' + self.frame_format
f = InMemory()
self.fig.savefig(f, format=self.frame_format,
dpi=self.dpi, **savefig_kwargs)
f.seek(0)
self._saved_frames.append(b64encode(f.read()).decode('ascii'))
else:
return super(HTMLWriter, self).grab_frame(**savefig_kwargs)
def _run(self):
# make a ducktyped subprocess standin
# this is called by the MovieWriter base class, but not used here.
class ProcessStandin(object):
returncode = 0
def communicate(self):
return ('', '')
self._proc = ProcessStandin()
# save the frames to an html file
if self.embed_frames:
fill_frames = _embedded_frames(self._saved_frames,
self.frame_format)
else:
# temp names is filled by FileMovieWriter
fill_frames = _included_frames(self._temp_names,
self.frame_format)
mode_dict = dict(once_checked='',
loop_checked='',
reflect_checked='')
mode_dict[self.default_mode + '_checked'] = 'checked'
interval = int(1000. / self.fps)
with open(self.outfile, 'w') as of:
of.write(JS_INCLUDE)
of.write(DISPLAY_TEMPLATE.format(id=self.new_id(),
Nframes=len(self._temp_names),
fill_frames=fill_frames,
interval=interval,
icons=_Icons(),
**mode_dict))
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simpegDCIP/Dev/Mesh_20m.msh
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53 53 30
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19*20.00 28.00 40.00 52.00 67.00 52.00 67.00 88.00 114.00 193.00 250.00 300.00
simpegDCIP/Dev/MtIsa_20m.msh
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104 21 45
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300 250 200 175 150 103.00 86.00 72.00 5*60 72.00 86.00 103.00 150 175 200 250 300
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simpegDCIP/Dev/MtIsa_3D.con
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simpegDCIP/Dev/SimPEG_FWR/FWR_3D_2_2D.dat
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simpegDCIP/Dev/SimPEG_FWR/FWR_data_3D.dat
-212
View File
@@ -1,212 +0,0 @@
GENERAL FORMAT
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simpegDCIP/Dev/SimPEG_FWR/Mesh_20m.msh
-5
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@@ -1,5 +0,0 @@
104 21 57
-1565.00 10725 0
350 300 250 200 175 150 103.00 86.00 72.00 60.00 50.00 40.00 35.00 30.00 24.00 74*20.00 24.00 30.00 35.00 40.00 50.00 60.00 72.00 86.00 103.00 150 175 200 250 300 350
300 250 200 175 150 103.00 86.00 72.00 5*60 72.00 86.00 103.00 150 175 200 250 300
20*10.00 12 16 20*20 24.00 30.00 35.00 40.00 50.00 60.00 72.00 86.00 103.00 150 175 200 250 300 350
simpegDCIP/Dev/SimPEG_FWR/MtIsa_3D.con
-124488
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File diff suppressed because it is too large Load Diff
simpegDCIP/Dev/Synthetic.con
-84270
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File diff suppressed because it is too large Load Diff
simpegDCIP/Dev/Workspace/convertObs_DC3D_to_2D.py
-44
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@@ -1,44 +0,0 @@
def convertObs_DC3D_to_2D(Tx,Rx):
from SimPEG import np
import numpy.matlib as npm
"""
Read list of 3D Tx Rx location and change coordinate system to distance
along line assuming all data is acquired along line
First transmitter pole is assumed to be at the origin
Assumes flat topo for now...
Input:
:param Tx, Rx
Output:
:figure Tx2d, Rx2d
Created on Mon December 7th, 2015
@author: dominiquef
"""
Tx2d = []
Rx2d = []
for ii in range(len(Tx)):
if ii == 0:
endp = Tx[0][0:2,0]
nrx = Rx[ii].shape[0]
rP1 = np.sqrt( np.sum( ( endp - Tx[ii][0:2,0] )**2 , axis=0))
rP2 = np.sqrt( np.sum( ( endp - Tx[ii][0:2,1] )**2 , axis=0))
rC1 = np.sqrt( np.sum( ( npm.repmat(endp.T,nrx,1) - Rx[ii][:,0:2] )**2 , axis=1))
rC2 = np.sqrt( np.sum( ( npm.repmat(endp.T,nrx,1) - Rx[ii][:,3:5] )**2 , axis=1))
Tx2d.append( np.r_[rP1, rP2] )
Rx2d.append( np.c_[rC1, rC2] )
#np.savetxt(fid, data, fmt='%e',delimiter=' ',newline='\n')
return Tx2d, Rx2d
simpegDCIP/Dev/Workspace/gen_DCIPsurvey.py
-149
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@@ -1,149 +0,0 @@
def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
from SimPEG import np
import re
"""
Load in endpoints and survey specifications to generate Tx, Rx location
stations.
Assumes flat topo for now...
Input:
:param endl -> input endpoints [x1, y1, z1, x2, y2, z2]
:object mesh -> SimPEG mesh object
:switch stype -> "dpdp" (dipole-dipole) | "pdp" (pole-dipole)
: param a, n -> pole seperation, number of rx dipoles per tx
Output:
:param Tx, Rx -> List objects for each tx location
Lines: P1x, P1y, P1z, P2x, P2y, P2z
Created on Wed December 9th, 2015
@author: dominiquef
"""
def xy_2_r(x1,x2,y1,y2):
r = np.sqrt( np.sum((x2 - x1)**2 + (y2 - y1)**2) )
return r
## Evenly distribute electrodes and put on surface
# Mesure survey length and direction
dl_len = xy_2_r(endl[0,0],endl[1,0],endl[0,1],endl[1,1])
dl_x = ( endl[1,0] - endl[0,0] ) / dl_len
dl_y = ( endl[1,1] - endl[0,1] ) / dl_len
nstn = np.floor( dl_len / a )
# Compute discrete pole location along line
stn_x = endl[0,0] + np.array(range(int(nstn)))*dl_x*a
stn_y = endl[0,1] + np.array(range(int(nstn)))*dl_y*a
# Create line of P1 locations
M = np.c_[stn_x, stn_y, np.ones(nstn).T*mesh.vectorNz[-1]]
# Create line of P2 locations
N = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
## Build list of Tx-Rx locations depending on survey type
# Dipole-dipole: Moving tx with [a] spacing -> [AB a MN1 a MN2 ... a MNn]
# Pole-dipole: Moving pole on one end -> [A a MN1 a MN2 ... MNn a B]
Tx = []
Rx = []
if not re.match(stype,'gradient'):
for ii in range(0, int(nstn)-1):
if re.match(stype,'dpdp'):
tx = np.c_[M[ii,:],N[ii,:]]
elif re.match(stype,'pdp'):
tx = np.c_[M[ii,:],M[ii,:]]
#Rx.append(np.c_[M[ii+1:indx,:],N[ii+1:indx,:]])
# Current elctrode seperation
AB = xy_2_r(tx[0,1],endl[1,0],tx[1,1],endl[1,1])
# Number of receivers to fit
nstn = np.min([np.floor( (AB - b) / a ) , n])
# Check if there is enough space, else break the loop
if nstn <= 0:
continue
# Compute discrete pole location along line
stn_x = N[ii,0] + dl_x*b + np.array(range(int(nstn)))*dl_x*a
stn_y = N[ii,1] + dl_y*b + np.array(range(int(nstn)))*dl_y*a
# Create receiver poles
# Create line of P1 locations
P1 = np.c_[stn_x, stn_y, np.ones(nstn).T*mesh.vectorNz[-1]]
# Create line of P2 locations
P2 = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
Rx.append(np.c_[P1,P2])
Tx.append(tx)
#==============================================================================
# elif re.match(stype,'dpdp'):
#
# for ii in range(0, int(nstn)-2):
#
# indx = np.min([ii+n+1,nstn])
# Tx.append(np.c_[M[ii,:],N[ii,:]])
# Rx.append(np.c_[M[ii+2:indx,:],N[ii+2:indx,:]])
#==============================================================================
elif re.match(stype,'gradient'):
# Gradient survey only requires Tx at end of line and creates a square
# grid of receivers at in the middle at a pre-set minimum distance
Tx.append(np.c_[M[0,:],N[-1,:]])
# Get the edge limit of survey area
min_x = endl[0,0] + dl_x * b
min_y = endl[0,1] + dl_y * b
max_x = endl[1,0] - dl_x * b
max_y = endl[1,1] - dl_y * b
box_l = np.sqrt( (min_x - max_x)**2 + (min_y - max_y)**2 )
box_w = box_l/2.
nstn = np.floor( box_l / a )
# Compute discrete pole location along line
stn_x = min_x + np.array(range(int(nstn)))*dl_x*a
stn_y = min_y + np.array(range(int(nstn)))*dl_y*a
# Define number of cross lines
nlin = int(np.floor( box_w / a ))
lind = range(-nlin,nlin+1)
ngrad = nstn * len(lind)
rx = np.zeros([ngrad,6])
for ii in range( len(lind) ):
# Move line in perpendicular direction by dipole spacing
lxx = stn_x - lind[ii]*a*dl_y
lyy = stn_y + lind[ii]*a*dl_x
M = np.c_[ lxx, lyy , np.ones(nstn).T*mesh.vectorNz[-1]]
N = np.c_[ lxx+a*dl_x, lyy+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]]
rx[(ii*nstn):((ii+1)*nstn),:] = np.c_[M,N]
Rx.append(rx)
else:
print """stype must be either 'pdp', 'dpdp' or 'gradient'. """
return Tx, Rx
simpegDCIP/Dev/Workspace/plot_pseudoSection.py
-68
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@@ -1,68 +0,0 @@
def plot_pseudoSection(Tx,Rx,data,z0, stype):
from SimPEG import np, mkvc
from scipy.interpolate import griddata
from matplotlib.colors import LogNorm
import pylab as plt
import re
"""
Read list of 2D tx-rx location and plot a speudo-section of apparent
resistivity.
Assumes flat topo for now...
Input:
:param d2D, z0
:switch stype -> Either 'pdp' (pole-dipole) | 'dpdp' (dipole-dipole)
Output:
:figure scatter plot overlayed on image
Created on Mon December 7th, 2015
@author: dominiquef
"""
#d2D = np.asarray(d2D)
midl = []
midz = []
rho = []
for ii in range(len(Tx)):
# Get distances between each poles
rC1P1 = np.abs(Tx[ii][0] - Rx[ii][:,0])
rC2P1 = np.abs(Tx[ii][1] - Rx[ii][:,0])
rC1P2 = np.abs(Tx[ii][1] - Rx[ii][:,1])
rC2P2 = np.abs(Tx[ii][0] - Rx[ii][:,1])
rP1P2 = np.abs(Rx[ii][:,1] - Rx[ii][:,0])
# Compute apparent resistivity
if re.match(stype,'pdp'):
rho = np.hstack([rho, data[ii] * 2*np.pi * rC1P1 * ( rC1P1 + rP1P2 ) / rP1P2] )
elif re.match(stype,'dpdp'):
rho = np.hstack([rho, data[ii] * 2*np.pi / ( 1/rC1P1 - 1/rC2P1 - 1/rC1P2 + 1/rC2P2 ) ])
Cmid = (Tx[ii][0] + Tx[ii][1])/2
Pmid = (Rx[ii][:,0] + Rx[ii][:,1])/2
midl = np.hstack([midl, ( Cmid + Pmid )/2 ])
midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + z0 ])
# Grid points
grid_x, grid_z = np.mgrid[np.min(midl):np.max(midl), np.min(midz):np.max(midz)]
grid_rho = griddata(np.c_[midl,midz], np.log10(abs(1/rho.T)), (grid_x, grid_z), method='linear')
#plt.subplot(2,1,2)
plt.imshow(grid_rho.T, extent = (np.min(midl),np.max(midl),np.min(midz),np.max(midz)), origin='lower', alpha=0.8)
cbar = plt.colorbar(format = '%.2f',fraction=0.02)
cmin,cmax = cbar.get_clim()
ticks = np.linspace(cmin,cmax,3)
cbar.set_ticks(ticks)
# Plot apparent resistivity
plt.scatter(midl,midz,s=50,c=np.log10(abs(1/rho.T)))
simpegDCIP/Dev/Workspace/readUBC_DC2DLoc.py
-57
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@@ -1,57 +0,0 @@
def readUBC_DC2DLoc(fileName):
from SimPEG import np
"""
Read UBC GIF 2D observation file and generate arrays for tx-rx location
Input:
:param fileName, path to the UBC GIF 2D model file
Output:
:param rx, tx
:return
Created on Thu Nov 12 13:14:10 2015
@author: dominiquef
"""
# Open fileand skip header... assume that we know the mesh already
#==============================================================================
# fopen = open(fileName,'r')
# lines = fopen.readlines()
# fopen.close()
#==============================================================================
# Load file
obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
# Check first line and figure out if 2D or 3D file format
line = np.array(obsfile[0].split(),dtype=float)
tx_A = []
tx_B = []
rx_M = []
rx_N = []
d = []
wd = []
for ii in range(obsfile.shape[0]):
# If len==3, then simple format where tx-rx is listed on each line
if len(line) == 4:
temp = np.fromstring(obsfile[ii], dtype=float,sep=' ')
tx_A = np.hstack((tx_A,temp[0]))
tx_B = np.hstack((tx_B,temp[1]))
rx_M = np.hstack((rx_M,temp[2]))
rx_N = np.hstack((rx_N,temp[3]))
rx = np.transpose(np.array((rx_M,rx_N)))
tx = np.transpose(np.array((tx_A,tx_B)))
return tx, rx, d, wd
simpegDCIP/Dev/Workspace/readUBC_DC2DMesh.py
-70
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@@ -1,70 +0,0 @@
def readUBC_DC2DMesh(fileName):
from SimPEG import np
"""
Read UBC GIF 2DTensor mesh and generate 2D Tensor mesh in simpeg
Input:
:param fileName, path to the UBC GIF mesh file
Output:
:param SimPEG TensorMesh 2D object
:return
Created on Thu Nov 12 13:14:10 2015
@author: dominiquef
"""
# Open file
fopen = open(fileName,'r')
# Read down the file and unpack dx vector
def unpackdx(fid,nrows):
for ii in range(nrows):
line = fid.readline()
var = np.array(line.split(),dtype=float)
if ii==0:
x0= var[0]
xvec = np.ones(int(var[2])) * (var[1] - var[0]) / int(var[2])
xend = var[1]
else:
xvec = np.hstack((xvec,np.ones(int(var[1])) * (var[0] - xend) / int(var[1])))
xend = var[0]
return x0, xvec
#%% Start with dx block
# First line specifies the number of rows for x-cells
line = fopen.readline()
nl = np.array(line.split(),dtype=float)
[x0, dx] = unpackdx(fopen,nl)
#%% Move down the file until reaching the z-block
line = fopen.readline()
if not line:
line = fopen.readline()
#%% End with dz block
# First line specifies the number of rows for z-cells
line = fopen.readline()
nl = np.array(line.split(),dtype=float)
[z0, dz] = unpackdx(fopen,nl)
# Flip z0 to be the bottom of the mesh for SimPEG
z0 = z0 - sum(dz)
dz = dz[::-1]
#%% Make the mesh using SimPEG
from SimPEG import Mesh
tensMsh = Mesh.TensorMesh([dx,dz],(x0, z0))
return tensMsh
simpegDCIP/Dev/Workspace/readUBC_DC2DModel.py
-56
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@@ -1,56 +0,0 @@
def readUBC_DC2DModel(fileName):
from SimPEG import np, mkvc
"""
Read UBC GIF 2DTensor model and generate 2D Tensor model in simpeg
Input:
:param fileName, path to the UBC GIF 2D model file
Output:
:param SimPEG TensorMesh 2D object
:return
Created on Thu Nov 12 13:14:10 2015
@author: dominiquef
"""
# Open fileand skip header... assume that we know the mesh already
obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
dim = np.array(obsfile[0].split(),dtype=float)
temp = np.array(obsfile[1].split(),dtype=float)
if len(temp) > 1:
model = np.zeros(dim)
for ii in range(len(obsfile)-1):
mm = np.array(obsfile[ii+1].split(),dtype=float)
model[:,ii] = mm
model = model[:,::-1]
else:
if len(obsfile[1:])==1:
mm = np.array(obsfile[1:].split(),dtype=float)
else:
mm = np.array(obsfile[1:],dtype=float)
# Permute the second dimension to flip the order
model = mm.reshape(dim[1],dim[0])
model = model[::-1,:]
model = np.transpose(model, (1, 0))
model = mkvc(model)
return model
simpegDCIP/Dev/Workspace/readUBC_DC3Dobs.py
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def readUBC_DC3Dobs(fileName):
from SimPEG import np
"""
Read UBC GIF DCIP 3D observation file and generate arrays for tx-rx location
Input:
:param fileName, path to the UBC GIF 3D obs file
Output:
:param rx, tx, d, wd
:return
Created on Mon December 7th, 2015
@author: dominiquef
"""
# Load file
obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
# Pre-allocate
Tx = []
Rx = []
d = []
wd = []
# Countdown for number of obs/tx
count = 0
for ii in range(obsfile.shape[0]):
if not obsfile[ii]:
continue
# First line is transmitter with number of receivers
if count==0:
temp = (np.fromstring(obsfile[ii], dtype=float,sep=' ').T)
count = int(temp[-1])
temp = np.reshape(temp[0:-1],[2,3]).T
Tx.append(temp)
rx = []
continue
temp = np.fromstring(obsfile[ii], dtype=float,sep=' ')
rx.append(temp)
count = count -1
# Reach the end of
if count == 0:
temp = np.asarray(rx)
Rx.append(temp[:,0:6])
# Check for data + uncertainties
if temp.shape[1]==8:
d.append(temp[:,6])
wd.append(temp[:,7])
# Check for data only
elif temp.shape[1]==7:
d.append(temp[:,6])
return Tx, Rx, d, wd
simpegDCIP/Dev/Workspace/writeUBC_DCobs.py
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def writeUBC_DCobs(fileName,Tx,Rx,d,wd, dtype):
from SimPEG import np, mkvc
import re
"""
Read UBC GIF DCIP 3D observation file and generate arrays for tx-rx location
Input:
:param fileName, path to the UBC GIF 3D obs file
Output:
:param rx, tx, d, wd
:return
Created on Mon December 7th, 2015
@author: dominiquef
"""
fid = open(fileName,'w')
fid.write('! GENERAL FORMAT\n')
for ii in range(len(Tx)):
tx = np.asarray(Tx[ii])
rx = np.asarray(Rx[ii])
nrx = rx.shape[0]
fid.write('\n')
if re.match(dtype,'2D'):
for jj in range(nrx):
fid.writelines("%e " % ii for ii in mkvc(tx))
fid.writelines("%e " % ii for ii in mkvc(rx[jj]))
fid.write('%e %e\n'% (d[ii][jj],wd[ii][jj]))
#np.savetxt(fid, np.c_[ rx ,np.asarray(d[ii]), np.asarray(wd[ii]) ], fmt='%e',delimiter=' ',newline='\n')
elif re.match(dtype,'3D'):
fid.write('\n')
fid.writelines("%e " % ii for ii in mkvc(tx))
fid.write('%i\n'% nrx)
np.savetxt(fid, np.c_[ rx ,np.asarray(d[ii]), np.asarray(wd[ii]) ], fmt='%e',delimiter=' ',newline='\n')
fid.close()
simpegDCIP/Dev/animation.html
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simpegDCIP/Dev/dcipf2d.inp
-5
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FWD DC
MESH FILE Mesh_2D.msh
LOC LOC_X OBS_LOC.dat
TOPO DEFAULT
COND FILE MtIsa_2D.con
simpegDCIP/Dev/obs2d_East.loc
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simpegDCIP/Examples/DC_PseudoSection_Simulation.py
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from SimPEG import *
import simpegDCIP as DC
import scipy.interpolate as interpolation
import matplotlib.pyplot as plt
import time
import re
def run(loc=np.c_[[-50.,0.,-50.],[50.,0.,-50.]], sig=np.r_[1e-2,1e-1,1e-3], radi=np.r_[25.,25.], param = np.r_[30.,30.,5], stype = 'dpdp', plotIt=True):
"""
DC Forward Simulation
Forward model conductive spheres in a half-space and plot a pseudo-section
Created on Mon Feb 01 19:28:06 2016
@fourndo
"""
# First we need to create a mesh and a model.
# This is our mesh
dx = 5.
hxind = [(dx,15,-1.3), (dx, 75), (dx,15,1.3)]
hyind = [(dx,15,-1.3), (dx, 10), (dx,15,1.3)]
hzind = [(dx,15,-1.3),(dx, 15)]
mesh = Mesh.TensorMesh([hxind, hyind, hzind], 'CCN')
# Set background conductivity
model = np.ones(mesh.nC) * sig[0]
# First anomaly
ind = Utils.ModelBuilder.getIndicesSphere(loc[:,0],radi[0],mesh.gridCC)
model[ind] = sig[1]
# Second anomaly
ind = Utils.ModelBuilder.getIndicesSphere(loc[:,1],radi[1],mesh.gridCC)
model[ind] = sig[2]
# Get index of the center
indy = int(mesh.nCy/2)
# Plot the model for reference
# Define core mesh extent
xlim = 200
zlim = 125
# Specify the survey type: "pdp" | "dpdp"
# Then specify the end points of the survey. Let's keep it simple for now and survey above the anomalies, top of the mesh
ends = [(-175,0),(175,0)]
ends = np.c_[np.asarray(ends),np.ones(2).T*mesh.vectorNz[-1]]
# Snap the endpoints to the grid. Easier to create 2D section.
indx = Utils.closestPoints(mesh, ends )
locs = np.c_[mesh.gridCC[indx,0],mesh.gridCC[indx,1],np.ones(2).T*mesh.vectorNz[-1]]
# We will handle the geometry of the survey for you and create all the combination of tx-rx along line
[Tx, Rx] = DC.gen_DCIPsurvey(locs, mesh, stype, param[0], param[1], param[2])
# Define some global geometry
dl_len = np.sqrt( np.sum((locs[0,:] - locs[1,:])**2) )
dl_x = ( Tx[-1][0,1] - Tx[0][0,0] ) / dl_len
dl_y = ( Tx[-1][1,1] - Tx[0][1,0] ) / dl_len
azm = np.arctan(dl_y/dl_x)
#Set boundary conditions
mesh.setCellGradBC('neumann')
# Define the differential operators needed for the DC problem
Div = mesh.faceDiv
Grad = mesh.cellGrad
Msig = Utils.sdiag(1./(mesh.aveF2CC.T*(1./model)))
A = Div*Msig*Grad
# Change one corner to deal with nullspace
A[0,0] = 1
A = sp.csc_matrix(A)
# We will solve the system iteratively, so a pre-conditioner is helpful
# This is simply a Jacobi preconditioner (inverse of the main diagonal)
dA = A.diagonal()
P = sp.spdiags(1/dA,0,A.shape[0],A.shape[0])
# Now we can solve the system for all the transmitters
# We want to store the data
data = []
# There is probably a more elegant way to do this, but we can just for-loop through the transmitters
for ii in range(len(Tx)):
start_time = time.time() # Let's time the calculations
#print("Transmitter %i / %i\r" % (ii+1,len(Tx)))
# Select dipole locations for receiver
rxloc_M = np.asarray(Rx[ii][:,0:3])
rxloc_N = np.asarray(Rx[ii][:,3:])
# For usual cases "dpdp" or "gradient"
if not re.match(stype,'pdp'):
inds = Utils.closestPoints(mesh, np.asarray(Tx[ii]).T )
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*( [-1,1] / mesh.vol[inds] )
else:
# Create an "inifinity" pole
tx = np.squeeze(Tx[ii][:,0:1])
tinf = tx + np.array([dl_x,dl_y,0])*dl_len*2
inds = Utils.closestPoints(mesh, np.c_[tx,tinf].T)
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*( [-1] / mesh.vol[inds] )
# Iterative Solve
Ainvb = sp.linalg.bicgstab(P*A,P*RHS, tol=1e-5)
# We now have the potential everywhere
phi = mkvc(Ainvb[0])
# Solve for phi on pole locations
P1 = mesh.getInterpolationMat(rxloc_M, 'CC')
P2 = mesh.getInterpolationMat(rxloc_N, 'CC')
# Compute the potential difference
dtemp = (P1*phi - P2*phi)*np.pi
data.append( dtemp )
print '\rTransmitter {0} of {1} -> Time:{2} sec'.format(ii,len(Tx),time.time()- start_time),
print 'Transmitter {0} of {1}'.format(ii,len(Tx))
print 'Forward completed'
# Let's just convert the 3D format into 2D (distance along line) and plot
[Tx2d, Rx2d] = DC.convertObs_DC3D_to_2D(Tx,Rx)
# Here is an example for the first tx-rx array
if plotIt:
fig = plt.figure()
ax = plt.subplot(2,1,1, aspect='equal')
mesh.plotSlice(np.log10(model), ax =ax, normal = 'Y', ind = indy,grid=True)
ax.set_title('E-W section at '+str(mesh.vectorCCy[indy])+' m')
plt.gca().set_aspect('equal', adjustable='box')
plt.scatter(Tx[0][0,:],Tx[0][2,:],s=40,c='g', marker='v')
plt.scatter(Rx[0][:,0::3],Rx[0][:,2::3],s=40,c='y')
plt.xlim([-xlim,xlim])
plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
ax = plt.subplot(2,1,2, aspect='equal')
# Plot the location of the spheres for reference
circle1=plt.Circle((loc[0,0]-Tx[0][0,0],loc[2,0]),radi[0],color='w',fill=False, lw=3)
circle2=plt.Circle((loc[0,1]-Tx[0][0,0],loc[2,1]),radi[1],color='k',fill=False, lw=3)
ax.add_artist(circle1)
ax.add_artist(circle2)
# Add the speudo section
DC.plot_pseudoSection(Tx2d,Rx2d,data,mesh.vectorNz[-1],stype)
plt.scatter(Tx2d[0][:],Tx[0][2,:],s=40,c='g', marker='v')
plt.scatter(Rx2d[0][:],Rx[0][:,2::3],s=40,c='y')
plt.plot(np.r_[Tx2d[0][0],Rx2d[-1][-1,-1]],np.ones(2)*mesh.vectorNz[-1], color='k')
plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
plt.show()
return fig, ax
if __name__ == '__main__':
run()