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Merge branch 'dcip/dev' into patch/sparse-dcip

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This commit is contained in:
D Fournier
2016-04-06 22:18:31 -07:00
parent 636d178fbf 16c6cc8d74
commit 6000034826
2 changed files with 80 additions and 54 deletions
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SimPEG/DCIP/DCIPUtils.py
+52 -28
View File
@@ -169,7 +169,7 @@ def readUBC_DC2DModel(fileName):
return model
def plot_pseudoSection(DCsurvey, axs, stype, dtype="appr",clim=None):
def plot_pseudoSection(DCsurvey, axs, stype='dpdp', dtype="appc", clim=None):
"""
Read list of 2D tx-rx location and plot a speudo-section of apparent
resistivity.
@@ -179,7 +179,7 @@ def plot_pseudoSection(DCsurvey, axs, stype, dtype="appr",clim=None):
Input:
:param d2D, z0
:switch stype -> Either 'pdp' (pole-dipole) | 'dpdp' (dipole-dipole)
:switch dtype=-> Either 'appr' (app. res) | 'appc' (app. con) | 'volt' (potential)
Output:
:figure scatter plot overlayed on image
@@ -221,25 +221,43 @@ def plot_pseudoSection(DCsurvey, axs, stype, dtype="appr",clim=None):
Cmid = (Tx[0][0] + Tx[1][0])/2
Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
# Compute pant leg of apparent rho
if stype == 'pdp':
leg = data * 2*np.pi * MA * ( MA + MN ) / MN
# Change output for dtype
if dtype == 'volt':
leg = np.log10(abs(1/leg))
rho = np.hstack([rho,data])
elif stype == 'dpdp':
leg = data * 2*np.pi / ( 1/MA - 1/MB - 1/NB + 1/NA )
else:
leg = np.log10(abs(1/leg))
# Compute pant leg of apparent rho
if stype == 'pdp':
leg = data * 2*np.pi * MA * ( MA + MN ) / MN
elif stype == 'dpdp':
leg = data * 2*np.pi / ( 1/MA - 1/MB - 1/NB + 1/NA )
else:
print """dtype must be 'pdp'(pole-dipole) | 'dpdp' (dipole-dipole) """
break
if dtype == 'appc':
leg = np.log10(abs(1./leg))
rho = np.hstack([rho,leg])
elif dtype == 'appr':
leg = np.log10(abs(leg))
rho = np.hstack([rho,leg])
else:
print """dtype must be 'appr' | 'appc' | 'volt' """
break
midx = np.hstack([midx, ( Cmid + Pmid )/2 ])
midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + z0 ])
#TODO ... let stick to list then finally convert to array.
if dtype =="appr":
rho = np.hstack([rho,leg])
elif dtype =="voltage":
rho = np.hstack([rho,data])
ax = axs
@@ -260,14 +278,20 @@ def plot_pseudoSection(DCsurvey, axs, stype, dtype="appr",clim=None):
ticks = np.linspace(cmin,cmax,3)
cbar.set_ticks(ticks)
cbar.ax.tick_params(labelsize=10)
cbar.set_label("App. Conductivity",size=12)
if dtype == 'appc':
cbar.set_label("App.Cond",size=12)
elif dtype == 'appr':
cbar.set_label("App.Res.",size=12)
elif dtype == 'volt':
cbar.set_label("Potential (V)",size=12)
# Plot apparent resistivity
ax.scatter(midx,midz,s=10,c=rho.T, vmin =vmin, vmax = vmax, clim=(vmin, vmax))
#ax.set_xticklabels([])
#ax.set_yticklabels([])
plt.gca().set_aspect('equal', adjustable='box')
@@ -516,7 +540,7 @@ def writeUBC_DCobs(fileName, DCsurvey, dtype, stype):
def convertObs_DC3D_to_2D(DCsurvey,lineID, flag = 'local'):
"""
Read DC survey and projects the coordinate system
Read DC survey and projects the coordinate system
according to the flag = 'Xloc' | 'Yloc' | 'local' (default)
In the 'local' system, station coordinates are referenced
to distance from the first srcLoc[0].loc[0]
@@ -575,19 +599,19 @@ def convertObs_DC3D_to_2D(DCsurvey,lineID, flag = 'local'):
# Find A electrode along line
vec, r = r_unit(x0,Tx[ii][0,0:2])
A = stn_id(vecTx,vec,r)
# Find B electrode along line
vec, r = r_unit(x0,Tx[ii][1,0:2])
B = stn_id(vecTx,vec,r)
M = np.zeros(nrx)
N = np.zeros(nrx)
for kk in range(nrx):
# Find all M electrodes along line
vec, r = r_unit(x0,Rx[0][kk,0:2])
M[kk] = stn_id(vecTx,vec,r)
# Find all N electrodes along line
vec, r = r_unit(x0,Rx[1][kk,0:2])
N[kk] = stn_id(vecTx,vec,r)
@@ -597,14 +621,14 @@ def convertObs_DC3D_to_2D(DCsurvey,lineID, flag = 'local'):
B = Tx[ii][1,1]
M = Rx[0][:,1]
N = Rx[1][:,1]
elif flag == 'Xloc':
""" Copy the rx-tx locs"""
A = Tx[ii][0,0]
B = Tx[ii][1,0]
M = Rx[0][:,0]
N = Rx[1][:,0]
Rx = DC.RxDipole(np.c_[M,np.zeros(nrx),Rx[0][:,2]],np.c_[N,np.zeros(nrx),Rx[1][:,2]])
srcLists.append( DC.SrcDipole( [Rx], np.asarray([A,0,Tx[ii][0,2]]),np.asarray([B,0,Tx[ii][1,2]]) ) )
@@ -796,15 +820,15 @@ def readUBC_DC2Dpre(fileName):
else:
tx = np.r_[temp[0],np.nan,temp[1],temp[2],np.nan,temp[3]]
if zflag:
rx = np.c_[temp[4],np.nan,temp[5],temp[6],np.nan,temp[7]]
else:
rx = np.c_[temp[2],np.nan,np.nan,temp[3],np.nan,np.nan]
# Check if there is data with the location
d.append(temp[-1])
@@ -817,7 +841,7 @@ def readUBC_DC2Dpre(fileName):
survey.dobs = np.asarray(d)
return {'DCsurvey':survey}
def readUBC_DC2DMesh(fileName):
"""
Read UBC GIF 2DTensor mesh and generate 2D Tensor mesh in simpeg
SimPEG/Examples/DC_Forward_PseudoSection.py
+28 -26
View File
@@ -2,19 +2,27 @@ from SimPEG import Mesh, Utils, np, sp
import SimPEG.DCIP as DC
import time
def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', dtype='appc', plotIt=True):
"""
DC Forward Simulation
=====================
Forward model conductive spheres in a half-space and plot a pseudo-section
Forward model two conductive spheres in a half-space and plot a
pseudo-section. Assumes an infinite line source and measures along the
center of the spheres.
INPUT:
loc = Location of spheres [[x1,y1,z1],[x2,y2,z2]]
radi = Radius of spheres [r1,r2]
param = Conductivity of background and two spheres [m0,m1,m2]
stype = survey type "pdp" (pole dipole) or "dpdp" (dipole dipole)
dtype = Data type "appr" (app res) | "appc" (app cond) | "volt" (potential)
Created by @fourndo on Mon Feb 01 19:28:06 2016
"""
assert stype in ['pdp', 'dpdp'], "Source type (stype) must be pdp or dpdp (pole dipole or dipole dipole)"
assert dtype in ['appr', 'appc', 'volt'], "Data type (dtype) must be appr (app res) or appc (app cond) or volt (potential)"
if loc is None:
loc = np.c_[[-50.,0.,-50.],[50.,0.,-50.]]
@@ -27,7 +35,6 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
# First we need to create a mesh and a model.
# This is our mesh
dx = 5.
@@ -52,15 +59,11 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
# Get index of the center
indy = int(mesh.nCy/2)
# Plot the model for reference
# Define core mesh extent
xlim = 200
zlim = 100
# 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]]
@@ -82,7 +85,8 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
#Set boundary conditions
mesh.setCellGradBC('neumann')
# Define the differential operators needed for the DC problem
# Define the linear system needed for the DC problem. We assume an infitite
# line source for simplicity.
Div = mesh.faceDiv
Grad = mesh.cellGrad
Msig = Utils.sdiag(1./(mesh.aveF2CC.T*(1./model)))
@@ -145,10 +149,9 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
print 'Forward completed'
# Let's just convert the 3D format into 2D (distance along line) and plot
# [Tx2d, Rx2d] = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc))
survey2D = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc) , 'Xloc')
survey2D.dobs =np.hstack(data)
# Here is an example for the first tx-rx array
if plotIt:
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(7,7))
@@ -158,29 +161,29 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
circle2=plt.Circle((loc[0,1],loc[2,1]),radi[1],color='k',fill=False, lw=3)
ax.add_artist(circle1)
ax.add_artist(circle2)
dat = mesh.plotSlice(np.log10(model), ax =ax, normal = 'Y',
ind = indy,grid=True, clim = np.log10([sig.min(),sig.max()]))
ax.set_title('3-D model')
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])
pos = ax.get_position()
pos = ax.get_position()
ax.set_position([pos.x0 , pos.y0 + 0.025 , pos.width, pos.height])
pos = ax.get_position()
cbarax = fig.add_axes([pos.x0 , pos.y0 + 0.025 , pos.width, pos.height * 0.04]) ## the parameters are the specified position you set
cbarax = fig.add_axes([pos.x0 , pos.y0 + 0.025 , pos.width, pos.height * 0.04]) ## the parameters are the specified position you set
cb = fig.colorbar(dat[0],cax=cbarax, orientation="horizontal",
ax = ax, ticks=np.linspace(np.log10(sig.min()),
np.log10(sig.max()), 3), format="$10^{%.1f}$")
cb.set_label("Conductivity (S/m)",size=12)
cb.ax.tick_params(labelsize=12)
cb.ax.tick_params(labelsize=12)
# Second plot for the predicted apparent resistivity data
ax2 = plt.subplot(2,1,2, aspect='equal')
@@ -189,16 +192,15 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
circle2=plt.Circle((loc[0,1],loc[2,1]),radi[1],color='k',fill=False, lw=3)
ax2.add_artist(circle1)
ax2.add_artist(circle2)
# Add the speudo section
dat = DC.plot_pseudoSection(survey2D,ax2,stype)
dat = DC.plot_pseudoSection(survey2D,ax2,stype=stype, dtype = dtype)
# 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')
ax2.set_title('Apparent Conductivity data')
ax2.set_title('Apparent Conductivity data')
plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
plt.show()