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51 Commits
Author SHA1 Message Date
seogi_macbook a48224ed8b no message 2016-04-24 13:18:36 -07:00
seogi_macbook 2c09be9fc1 Working Mixed boundary conditions and testing ... 2016-04-21 14:44:37 -07:00
seogi_macbook 28005dde45 change minor bug for meshIO 2016-04-15 17:17:18 -07:00
seogi_macbook 35bac38c8b working on mixed BC 2016-04-14 22:41:47 -07:00
seogi_macbook 05e3b02b3a Merge branch 'dcip/dev' of https://github.com/simpeg/simpeg into dcip/dev 2016-04-13 16:52:44 -07:00
D Fournier 16c6cc8d74 Update speudo plot and allow app_res, app_con, volt 2016-04-06 22:17:34 -07:00
D Fournier f799733a9d Fix TwoSphere example and Utils.pseudoPlot 2016-04-06 14:43:33 -07:00
D Fournier 8b94cd4dfe Change flag for convertObs_DC3D_to_2D, which broke the example 2016-04-06 09:14:14 -07:00
D Fournier 09f3f7b55b Merge branch 'dev' into dcip/dev 2016-04-06 09:03:37 -07:00
D Fournier e646211e7d Review Utils.gen_DCIPsurvey ... lets keep it. 2016-04-06 08:55:52 -07:00
seogi_macbook fb1ff4e867 Merge branch 'dev' of https://github.com/simpeg/simpeg into dcip/dev 2016-04-05 21:50:03 -07:00
seogi_macbook a31319b46e Merge branch 'master' of https://github.com/simpeg/simpeg into dcip/dev 2016-04-05 21:49:38 -07:00
Lindsey Heagy d8aec96080 Merge branch 'master' into dev 2016-04-05 17:51:27 -07:00
Lindsey aad596a8cc Merge pull request #282 from simpeg/example/EM_FDEM_1D_Inversion/patch
Better list comprehension.
2016-04-05 17:41:05 -07:00
Rowan Cockett 8d6bd65923 Better list comprehension. 2016-04-05 14:26:45 -07:00
Lindsey 31d418bed8 Merge pull request #253 from simpeg/bug/opt/projected-gradient
Allow moving off bounds in projected gradient
2016-04-05 12:27:48 -07:00
Lindsey Heagy 5d9d746932 kwarg for stepping off bounds in projected gradient 2016-04-03 10:42:28 -07:00
Lindsey df3d32cb35 Merge pull request #269 from simpeg/feat/casingexample
Feat/casingexample
2016-04-02 08:47:25 -07:00
Lindsey Heagy b531c162a2 tab so we don't cut off the first characters in the docstring 2016-03-31 23:50:35 -07:00
Lindsey Heagy c7883673bf added the figshare doi link for the example 2016-03-31 09:36:55 -07:00
Lindsey Heagy b6438688d8 removed link for Schenkel paper (it seems to time-out) 2016-03-29 15:40:06 -07:00
Lindsey Heagy 824ce64c7e more descriptive titles 2016-03-29 14:56:56 -07:00
Lindsey Heagy 7aa5599211 improve the description 2016-03-29 14:41:45 -07:00
Lindsey Heagy fbec011983 typo fix 2016-03-29 14:29:39 -07:00
Lindsey Heagy 5fb8cdb88c example casing forward simulation to calculate vertical current 2016-03-29 13:00:37 -07:00
D Fournier fdc081970e Merge branch 'feat/sparse-regularization' into dcip/dev 2016-03-21 15:03:59 -07:00
D Fournier f92ff1301d Add reference model in compact term. 2016-03-17 18:45:09 -07:00
D Fournier d302a59b2c Change the projection from 3D to 2D 2016-03-16 11:43:25 -07:00
D Fournier ef467efce0 Small change to directive 2016-03-15 20:56:38 -07:00
D Fournier d226186c8e Add auto-beta adjustment. 2016-03-11 15:09:31 -08:00
D Fournier 38b4079f0b Move cell-based weights (i.e. distance weighting) inside regularization.
Fix gamma parameter update
TO DO: Check inversion print screen -> values don't match reality.
2016-03-11 11:40:47 -08:00
D Fournier 9d4e2488f3 Merge branch 'dcip/dev' of https://github.com/simpeg/simpeg into dcip/dev
Conflicts:
	SimPEG/DCIP/DCIPUtils.py
2016-03-10 14:33:06 -08:00
Lindsey Heagy 838035adae fixed indentation level on test_regularization 2016-03-10 14:30:43 -08:00
Lindsey Heagy ef4513bcd4 some cleanup inside of sparse regularization 2016-03-10 14:25:53 -08:00
D Fournier 4fefccc97d Add readPUBC_DC2Dpre 2016-03-10 14:25:27 -08:00
seogi_macbook 1946e1f69e minor change for plotting 2016-03-09 15:49:08 -08:00
Lindsey Heagy 33c9059e4e SparseRegularization --> Sparse 2016-03-08 16:40:02 -08:00
Lindsey Heagy d9b3c038c4 Merge branch 'dev' into feat/sparse-regularization
# Conflicts:
#	SimPEG/Regularization.py
#	SimPEG/Survey.py
2016-03-06 23:01:59 -08:00
Lindsey Heagy 2f8b8a36bf smoothModel --> mrefInSmooth 2016-03-02 09:46:50 -08:00
Lindsey Heagy 5e5c7ba0fb docs for regmesh, cellGrad--> cellDiff, faceDiv--> faceDiff for regmesh 2016-03-01 17:31:37 -08:00
D Fournier 6c33455d15 update Directive for sparse norm 2016-02-25 08:56:18 -08:00
D Fournier 7000699e38 Merge branch 'feat/sparse-regularization' of https://github.com/simpeg/simpeg into feat/sparse-regularization 2016-02-24 21:00:02 -08:00
D Fournier 63bf8b9e4d Add linear survey 2016-02-24 20:59:51 -08:00
Lindsey Heagy e3af1fd94e convert indActive to a bool if an integer list is provided 2016-02-24 20:28:09 -08:00
Lindsey Heagy 4e871a43a9 prototype of defining regularization mesh within Regularization.py for constructing operators for regularization that are not true differential operators 2016-02-24 18:03:42 -08:00
Lindsey Heagy b5f4d8e999 typo in Regularization.py 2016-02-19 17:43:50 -08:00
Lindsey Heagy e4a3e0a16d break out the Pac, Pafx, ... and make part of base regularization 2016-02-19 16:23:26 -08:00
Rowan Cockett 1c2fecf3a2 Add the IRLS Directive. 2016-02-16 22:07:33 -08:00
Rowan Cockett c10777a245 Addition of unitCellGrad. Possibly rename to cellGradStencil? 2016-02-16 22:00:12 -08:00
Rowan Cockett 05a85018de Create a Simple and a SparseRegularization class.
The SparseRegularization class allows implementation of p-q norms.
2016-02-16 21:59:08 -08:00
Rowan Cockett 8aa23c31de Allow moving off bounds in projected gradient.
The current implementation does not allow you to move off the
bounds (lower/upper) once you have gotten on them, this allows you
to move off of the bound.

Please note that more testing should be done to ensure that this does
not introduce oscillations into the optimization routine.
2016-02-16 21:53:31 -08:00
14 changed files with 1697 additions and 437 deletions
+162 -56
View File
@@ -169,7 +169,7 @@ def readUBC_DC2DModel(fileName):
return model
def plot_pseudoSection(DCsurvey, axs, stype):
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):
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
@@ -221,20 +221,43 @@ def plot_pseudoSection(DCsurvey, axs, stype):
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:
# 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 ])
rho = np.hstack([rho,leg])
ax = axs
@@ -242,26 +265,38 @@ def plot_pseudoSection(DCsurvey, axs, stype):
grid_x, grid_z = np.mgrid[np.min(midx):np.max(midx), np.min(midz):np.max(midz)]
grid_rho = griddata(np.c_[midx,midz], rho.T, (grid_x, grid_z), method='linear')
if clim == None:
vmin, vmax = rho.min(), rho.max()
else:
vmin, vmax = clim[0], clim[1]
plt.imshow(grid_rho.T, extent = (np.min(midx),np.max(midx),np.min(midz),np.max(midz)), origin='lower', alpha=0.8, vmin = np.min(rho), vmax = np.max(rho))
cbar = plt.colorbar(format = '%.2f',fraction=0.04,orientation="horizontal")
grid_rho = np.ma.masked_where(np.isnan(grid_rho), grid_rho)
ph = plt.pcolormesh(grid_x[:,0],grid_z[0,:],grid_rho.T, clim=(vmin, vmax))
cbar = plt.colorbar(format="$10^{%.1f}$",fraction=0.04,orientation="horizontal")
cmin,cmax = cbar.get_clim()
ticks = np.linspace(cmin,cmax,3)
cbar.set_ticks(ticks)
cbar.ax.tick_params(labelsize=10)
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
plt.scatter(midx,midz,s=50,c=rho.T)
ax.scatter(midx,midz,s=10,c=rho.T, vmin =vmin, vmax = vmax, clim=(vmin, vmax))
ax.set_xticklabels([])
#ax.set_xticklabels([])
#ax.set_yticklabels([])
ax.set_ylabel('Z')
ax.yaxis.tick_right()
ax.yaxis.set_label_position('right')
plt.gca().set_aspect('equal', adjustable='box')
return ax
return ph
def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
"""
@@ -361,16 +396,6 @@ def gen_DCIPsurvey(endl, mesh, stype, a, b, n):
srcClass = DC.SrcDipole([rxClass], M[ii,:],M[ii,:])
SrcList.append(srcClass)
#==============================================================================
# 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 stype == 'gradient':
# Gradient survey only requires Tx at end of line and creates a square
@@ -513,22 +538,22 @@ def writeUBC_DCobs(fileName, DCsurvey, dtype, stype):
fid.close()
def convertObs_DC3D_to_2D(DCsurvey,lineID):
def convertObs_DC3D_to_2D(DCsurvey,lineID, flag = 'local'):
"""
Read DC survey and data 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
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]
Assumes flat topo for now...
The Z value is preserved, but Y coordinates zeroed.
Input:
:param Tx, Rx
:param survey3D
Output:
:figure Tx2d, Rx2d
:figure survey2D
Edited Feb 17th, 2016
Edited April 6th, 2016
@author: dominiquef
@@ -570,25 +595,39 @@ def convertObs_DC3D_to_2D(DCsurvey,lineID):
Rx = DCsurvey.srcList[indx[ii]].rxList[0].locs
nrx = Rx[0].shape[0]
# Find A electrode along line
vec, r = r_unit(x0,Tx[ii][0,0:2])
A = stn_id(vecTx,vec,r)
if 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)
# 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):
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 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)
# Find all N electrodes along line
vec, r = r_unit(x0,Rx[1][kk,0:2])
N[kk] = stn_id(vecTx,vec,r)
elif flag == 'Yloc':
""" Flip the XY axis locs"""
A = Tx[ii][0,1]
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]])
@@ -604,16 +643,16 @@ def convertObs_DC3D_to_2D(DCsurvey,lineID):
def readUBC_DC3Dobs(fileName):
"""
Read UBC GIF DCIP 3D observation file and generate arrays for tx-rx location
Read UBC GIF DCIP 3D observation file and generate survey
Input:
:param fileName, path to the UBC GIF 3D obs file
Output:
:param rx, tx, d, wd
:param DCIPsurvey
:return
Created on Mon December 7th, 2015
Created on Mon April 6th, 2015
@author: dominiquef
@@ -688,6 +727,7 @@ def readUBC_DC3Dobs(fileName):
def readUBC_DC2Dobs(fileName):
"""
------- NEEDS TO BE UPDATED ------
Read UBC GIF 2D observation file and generate arrays for tx-rx location
Input:
@@ -735,6 +775,73 @@ def readUBC_DC2Dobs(fileName):
return tx, rx, d, wd
def readUBC_DC2Dpre(fileName):
"""
Read UBC GIF DCIP 2D observation file and generate arrays for tx-rx location
Input:
:param fileName, path to the UBC GIF 3D obs file
Output:
DCsurvey
:return
Created on Mon March 9th, 2016 << Doug's 70th Birthday !! >>
@author: dominiquef
"""
# Load file
obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!')
# Pre-allocate
srcLists = []
Rx = []
d = []
zflag = True # Flag for z value provided
for ii in range(obsfile.shape[0]):
if not obsfile[ii]:
continue
# First line is transmitter with number of receivers
temp = (np.fromstring(obsfile[ii], dtype=float,sep=' ').T)
# Check if z value is provided, if False -> nan
if len(temp)==5:
tx = np.r_[temp[0],np.nan,np.nan,temp[1],np.nan,np.nan]
zflag = False
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])
Rx = DC.RxDipole(rx[:,:3],rx[:,3:])
srcLists.append( DC.SrcDipole( [Rx], tx[:3],tx[3:]) )
# Create survey class
survey = DC.SurveyDC(srcLists)
survey.dobs = np.asarray(d)
return {'DCsurvey':survey}
def readUBC_DC2DMesh(fileName):
"""
Read UBC GIF 2DTensor mesh and generate 2D Tensor mesh in simpeg
@@ -928,7 +1035,6 @@ def getSrc_locs(DCsurvey):
srcMat = np.zeros((DCsurvey.nSrc,2,3))
for ii in range(DCsurvey.nSrc):
print np.asarray(DCsurvey.srcList[ii].loc).shape
srcMat[ii,:,:] = np.asarray(DCsurvey.srcList[ii].loc)
return srcMat
+62 -3
View File
@@ -216,7 +216,7 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
# Save the data.
ms = self.reg.Ws * ( self.reg.mapping * (self.invProb.curModel - self.reg.mref) )
phi_ms = 0.5*ms.dot(ms)
if self.reg.smoothModel == True:
if self.reg.mrefInSmooth == True:
mref = self.reg.mref
else:
mref = 0
@@ -249,7 +249,7 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
# Save the data.
ms = self.reg.Ws * ( self.reg.mapping * (self.invProb.curModel - self.reg.mref) )
phi_ms = 0.5*ms.dot(ms)
if self.reg.smoothModel == True:
if self.reg.mrefInSmooth == True:
mref = self.reg.mref
else:
mref = 0
@@ -271,7 +271,6 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
np.savez('{:s}-{:03d}'.format(self.fileName,self.opt.iter), iter=self.opt.iter, beta=self.invProb.beta, phi_d=self.invProb.phi_d, phi_m=self.invProb.phi_m, phi_ms=phi_ms, phi_mx=phi_mx, phi_my=phi_my, phi_mz=phi_mz,f=self.opt.f, m=self.invProb.curModel,dpred=self.invProb.dpred)
# class UpdateReferenceModel(Parameter):
# mref0 = None
@@ -283,3 +282,63 @@ class SaveOutputDictEveryIteration(_SaveEveryIteration):
# mref = self.mref0
# self.m_prev = self.invProb.m_current
# return mref
class update_IRLS(InversionDirective):
eps_min = None
factor = None
gamma = None
phi_m_last = None
phi_d_last = None
def initialize(self):
# Scale the regularization for changes in norm
if getattr(self, 'phi_m_last', None) is not None:
self.reg.gamma = 1.
phim_new = self.reg.eval(self.invProb.curModel)
self.gamma = self.phi_m_last / phim_new
self.reg.curModel = self.invProb.curModel
self.reg.gamma = self.gamma
if getattr(self, 'phi_d_last', None) is None:
self.phi_d_last = self.invProb.phi_d
def endIter(self):
# Cool the threshold parameter
if getattr(self, 'factor', None) is not None:
eps = self.reg.eps / self.factor
if getattr(self, 'eps_min', None) is not None:
self.reg.eps = np.max([self.eps_min,eps])
else:
self.reg.eps = eps
# Get phi_m at the end of current iteration
self.phi_m_last = self.invProb.phi_m_last
# Update the model used for the IRLS weights
self.reg.curModel = self.invProb.curModel
# Update the pre-conditioner
diagA = np.sum(self.prob.G**2.,axis=0) + self.invProb.beta*(self.reg.W.T*self.reg.W).diagonal() * (self.reg.mapping * np.ones(self.reg.curModel.size))**2.
PC = Utils.sdiag(diagA**-1.)
self.opt.approxHinv = PC
# Temporarely set gamma to 1.
self.reg.gamma = 1.
# Compute change in model objective function and update scaling
phim_new = self.reg.eval(self.invProb.curModel)
self.reg.gamma = self.phi_m_last / phim_new
# TO DO: Re-scale beta if too much change in misfit
self.invProb.beta = self.invProb.beta * self.phi_d_last / self.invProb.phi_d
#==============================================================================
# import pylab as plt
# plt.figure()
# ax = plt.subplot(221)
# self.prob.mesh.plotSlice(self.invProb.curModel, ax = ax, normal = 'Z', ind=-5, clim = (0, 0.005))
#==============================================================================
+48 -25
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.
@@ -52,14 +59,10 @@ 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 = 125
# Specify the survey type: "pdp" | "dpdp"
zlim = 100
# 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)]
@@ -77,12 +80,13 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
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)
#azm = np.arctan(dl_y/dl_x)
#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)))
@@ -145,16 +149,23 @@ 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))
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()
fig = plt.figure(figsize=(7,7))
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')
# Plot the location of the spheres for reference
circle1=plt.Circle((loc[0,0],loc[2,0]),radi[0],color='w',fill=False, lw=3)
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')
@@ -163,22 +174,34 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
ax = plt.subplot(2,1,2, aspect='equal')
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
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)
# Second plot for the predicted apparent resistivity data
ax2 = 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)
circle1=plt.Circle((loc[0,0],loc[2,0]),radi[0],color='w',fill=False, lw=3)
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
DC.plot_pseudoSection(survey2D,ax,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')
plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
ax2.set_title('Apparent Conductivity data')
plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
plt.show()
return fig, ax
+1 -2
View File
@@ -48,8 +48,7 @@ def run(plotIt=True):
freqs = np.logspace(1,3,10)
srcLoc = np.array([0., 0., 10.])
srcList = []
[srcList.append(EM.FDEM.Src.MagDipole([bzi],freq, srcLoc,orientation='Z')) for freq in freqs]
srcList = [EM.FDEM.Src.MagDipole([bzi],freq, srcLoc,orientation='Z') for freq in freqs]
survey = EM.FDEM.Survey(srcList)
prb = EM.FDEM.Problem_b(mesh, mapping=mapping)
@@ -0,0 +1,275 @@
from SimPEG import *
from SimPEG.EM import FDEM, Analytics, mu_0
import time
try:
from pymatsolver import MumpsSolver
solver = MumpsSolver
except Exception:
solver = SolverLU
pass
def run(plotIt=True):
"""
EM: Schenkel and Morrison Casing Model
======================================
Here we create and run a FDEM forward simulation to calculate the vertical
current inside a steel-cased. The model is based on the Schenkel and
Morrison Casing Model, and the results are used in a 2016 SEG abstract by
Yang et al.
- Schenkel, C.J., and H.F. Morrison, 1990, Effects of well casing on potential field measurements using downhole current sources: Geophysical prospecting, 38, 663-686.
The model consists of:
- Air: Conductivity 1e-8 S/m, above z = 0
- Background: conductivity 1e-2 S/m, below z = 0
- Casing: conductivity 1e6 S/m
- 300m long
- radius of 0.1m
- thickness of 6e-3m
Inside the casing, we take the same conductivity as the background.
We are using an EM code to simulate DC, so we use frequency low enough
that the skin depth inside the casing is longer than the casing length (f
= 1e-6 Hz). The plot produced is of the current inside the casing.
These results are shown in the SEG abstract by Yang et al., 2016: 3D DC
resistivity modeling of steel casing for reservoir monitoring using
equivalent resistor network. The solver used to produce these results and
achieve the CPU time of ~30s is Mumps, which was installed using pymatsolver_
.. _pymatsolver: https://github.com/rowanc1/pymatsolver
This example is on figshare: https://dx.doi.org/10.6084/m9.figshare.3126961.v1
If you would use this example for a code comparison, or build upon it, a
citation would be much appreciated!
"""
if plotIt:
import matplotlib.pylab as plt
# ------------------ MODEL ------------------
sigmaair = 1e-8 # air
sigmaback = 1e-2 # background
sigmacasing = 1e6 # casing
sigmainside = sigmaback # inside the casing
casing_t = 0.006 # 1cm thickness
casing_l = 300 # length of the casing
casing_r = 0.1
casing_a = casing_r - casing_t/2. # inner radius
casing_b = casing_r + casing_t/2. # outer radius
casing_z = np.r_[-casing_l,0.]
# ------------------ SURVEY PARAMETERS ------------------
freqs = np.r_[1e-6] #[1e-1, 1, 5] # frequencies
dsz = -300 # down-hole z source location
src_loc = np.r_[0.,0.,dsz]
inf_loc = np.r_[0.,0.,1e4]
print 'Skin Depth: ', [(500./np.sqrt(sigmaback*_)) for _ in freqs]
# ------------------ MESH ------------------
# fine cells near well bore
csx1, csx2 = 2e-3, 60.
pfx1, pfx2 = 1.3, 1.3
ncx1 = np.ceil(casing_b/csx1+2)
# pad nicely to second cell size
npadx1 = np.floor(np.log(csx2/csx1) / np.log(pfx1))
hx1a,hx1b = Utils.meshTensor([(csx1,ncx1)]),Utils.meshTensor([(csx1,npadx1,pfx1)])
dx1 = sum(hx1a)+sum(hx1b)
dx1 = np.floor(dx1/csx2)
hx1b *= (dx1*csx2 - sum(hx1a))/sum(hx1b)
# second chunk of mesh
dx2 = 300. # uniform mesh out to here
ncx2 = np.ceil((dx2 - dx1)/csx2)
npadx2 = 45
hx2a, hx2b = Utils.meshTensor([(csx2,ncx2)]), Utils.meshTensor([(csx2,npadx2,pfx2)])
hx = np.hstack([hx1a,hx1b,hx2a,hx2b])
# z-direction
csz = 0.05
nza = 10
ncz, npadzu, npadzd = np.int(np.ceil(np.diff(casing_z)[0]/csz))+10, 68, 68 # cell size, number of core cells, number of padding cells in the x- direction
hz = Utils.meshTensor([(csz,npadzd,-1.3), (csz,ncz), (csz,npadzu,1.3)]) # vector of cell widths in the z-direction
# Mesh
mesh = Mesh.CylMesh([hx,1.,hz], [0.,0.,-np.sum(hz[:npadzu+ncz-nza])])
print 'Mesh Extent xmax: %f,: zmin: %f, zmax: %f'%(mesh.vectorCCx.max(), mesh.vectorCCz.min(), mesh.vectorCCz.max())
print 'Number of cells', mesh.nC
if plotIt is True:
fig, ax = plt.subplots(1, 1, figsize=(6, 4))
ax.set_title('Simulation Mesh')
mesh.plotGrid(ax=ax)
plt.show()
# Put the model on the mesh
sigWholespace = sigmaback*np.ones((mesh.nC))
sigBack = sigWholespace.copy()
sigBack[mesh.gridCC[:,2] > 0.] = sigmaair
sigCasing = sigBack.copy()
iCasingZ = (mesh.gridCC[:,2] <= casing_z[1]) & (mesh.gridCC[:,2] >= casing_z[0])
iCasingX = (mesh.gridCC[:,0] >= casing_a) & (mesh.gridCC[:,0] <= casing_b)
iCasing = iCasingX & iCasingZ
sigCasing[iCasing] = sigmacasing
if plotIt is True:
# plotting parameters
xlim = np.r_[0., 0.2]
zlim = np.r_[-350., 10.]
clim_sig = np.r_[-8,6]
# plot models
fig, ax = plt.subplots(1,1,figsize=(4,4))
f = plt.colorbar(mesh.plotImage(np.log10(sigCasing),ax=ax)[0], ax=ax)
ax.grid(which='both')
ax.set_title('Log_10 (Sigma)')
ax.set_xlim(xlim)
ax.set_ylim(zlim)
f.set_clim(clim_sig)
plt.show()
# -------------- Sources --------------------
# Define Custom Current Sources
# surface source
sg_x = np.zeros(mesh.vnF[0],dtype=complex)
sg_y = np.zeros(mesh.vnF[1],dtype=complex)
sg_z = np.zeros(mesh.vnF[2],dtype=complex)
nza = 2 # put the wire two cells above the surface
ncin = 2
# vertically directed wire
sgv_indx = (mesh.gridFz[:,0] > casing_a) & (mesh.gridFz[:,0] < casing_a + csx1) # hook it up to casing at the surface
sgv_indz = (mesh.gridFz[:,2] <= +csz*nza) & (mesh.gridFz[:,2] >= -csz*2)
sgv_ind = sgv_indx & sgv_indz
sg_z[sgv_ind] = -1.
# horizontally directed wire
sgh_indx = (mesh.gridFx[:,0] > casing_a) & (mesh.gridFx[:,0] <= inf_loc[2])
sgh_indz = (mesh.gridFx[:,2] > csz*(nza-0.5)) & (mesh.gridFx[:,2] < csz*(nza+0.5))
sgh_ind = sgh_indx & sgh_indz
sg_x[sgh_ind] = -1.
sgv2_indx = (mesh.gridFz[:,0] >= mesh.gridFx[sgh_ind,0].max()) & (mesh.gridFz[:,0] <= inf_loc[2]*1.2) # hook it up to casing at the surface
sgv2_indz = (mesh.gridFz[:,2] <= +csz*nza) & (mesh.gridFz[:,2] >= -csz*2)
sgv2_ind = sgv2_indx & sgv2_indz
sg_z[sgv2_ind] = 1.
# assemble the source
sg = np.hstack([sg_x,sg_y,sg_z])
sg_p = [FDEM.Src.RawVec_e([],_,sg/mesh.area) for _ in freqs]
# downhole source
dg_x = np.zeros(mesh.vnF[0],dtype=complex)
dg_y = np.zeros(mesh.vnF[1],dtype=complex)
dg_z = np.zeros(mesh.vnF[2],dtype=complex)
# vertically directed wire
dgv_indx = (mesh.gridFz[:,0] < csx1) # go through the center of the well
dgv_indz = (mesh.gridFz[:,2] <= +csz*nza) & (mesh.gridFz[:,2] > dsz + csz/2.)
dgv_ind = dgv_indx & dgv_indz
dg_z[dgv_ind] = -1.
# couple to the casing downhole
dgh_indx = mesh.gridFx[:,0] < casing_a + csx1
dgh_indz = (mesh.gridFx[:,2] < dsz + csz) & (mesh.gridFx[:,2] >= dsz)
dgh_ind = dgh_indx & dgh_indz
dg_x[dgh_ind] = 1.
# horizontal part at surface
dgh2_indx = mesh.gridFx[:,0] <= inf_loc[2]*1.2
dgh2_indz = sgh_indz.copy()
dgh2_ind = dgh2_indx & dgh2_indz
dg_x[dgh2_ind] = -1.
# vertical part at surface
dgv2_ind = sgv2_ind.copy()
dg_z[dgv2_ind] = 1.
# assemble the source
dg = np.hstack([dg_x,dg_y,dg_z])
dg_p = [FDEM.Src.RawVec_e([],_,dg/mesh.area) for _ in freqs]
# ------------ Problem and Survey ---------------
survey = FDEM.Survey(sg_p + dg_p)
mapping = [('sigma', Maps.IdentityMap(mesh))]
problem = FDEM.Problem_h(mesh, mapping=mapping)
problem.pair(survey)
# ------------- Solve ---------------------------
t0 = time.time()
fieldsCasing = problem.fields(sigCasing)
print 'Time to solve 2 sources', time.time() - t0
# Plot current
# current density
jn0 = fieldsCasing[dg_p,'j']
jn1 = fieldsCasing[sg_p,'j']
# current
in0 = [mesh.area*fieldsCasing[dg_p,'j'][:,i] for i in range(len(freqs))]
in1 = [mesh.area*fieldsCasing[sg_p,'j'][:,i] for i in range(len(freqs))]
in0 = np.vstack(in0).T
in1 = np.vstack(in1).T
# integrate to get z-current inside casing
inds_inx = (mesh.gridFz[:,0] >= casing_a) & (mesh.gridFz[:,0] <= casing_b)
inds_inz = (mesh.gridFz[:,2] >= dsz ) & (mesh.gridFz[:,2] <= 0)
inds_fz = inds_inx & inds_inz
indsx = [False]*mesh.nFx
inds = list(indsx) + list(inds_fz)
in0_in = in0[np.r_[inds]]
in1_in = in1[np.r_[inds]]
z_in = mesh.gridFz[inds_fz,2]
in0_in = in0_in.reshape([in0_in.shape[0]/3,3])
in1_in = in1_in.reshape([in1_in.shape[0]/3,3])
z_in = z_in.reshape([z_in.shape[0]/3,3])
I0 = in0_in.sum(1).real
I1 = in1_in.sum(1).real
z_in = z_in[:,0]
if plotIt is True:
fig, ax = plt.subplots(1,2,figsize=(12,4))
ax[0].plot(z_in,np.absolute(I0), z_in,np.absolute(I1))
ax[0].legend(['top casing', 'bottom casing'],loc='best')
ax[0].set_title('Magnitude of Vertical Current in Casing')
ax[1].semilogy(z_in,np.absolute(I0), z_in,np.absolute(I1))
ax[1].legend(['top casing', 'bottom casing'],loc='best')
ax[1].set_title('Magnitude of Vertical Current in Casing')
ax[1].set_ylim([1e-2, 1.])
plt.show()
if __name__ == '__main__':
run()
+1 -1
View File
@@ -100,7 +100,7 @@ def run(plotIt=True):
# Regularization - with a regularization mesh
regMesh = simpeg.Mesh.TensorMesh([m1d.hx[problem.mapping.sigmaMap.maps[-1].indActive]],m1d.x0)
reg = simpeg.Regularization.Tikhonov(regMesh)
reg.smoothModel = True
reg.mrefInSmooth = True
reg.alpha_s = 1e-7
reg.alpha_x = 1.
# Inversion problem
+2 -1
View File
@@ -5,6 +5,7 @@ import DC_Analytic_Dipole
import DC_Forward_PseudoSection
import EM_FDEM_1D_Inversion
import EM_FDEM_Analytic_MagDipoleWholespace
import EM_Schenkel_Morrison_Casing
import EM_TDEM_1D_Inversion
import FLOW_Richards_1D_Celia1990
import Forward_BasicDirectCurrent
@@ -19,7 +20,7 @@ import Mesh_Tensor_Creation
import MT_1D_ForwardAndInversion
import MT_3D_Foward
__examples__ = ["DC_Analytic_Dipole", "DC_Forward_PseudoSection", "EM_FDEM_1D_Inversion", "EM_FDEM_Analytic_MagDipoleWholespace", "EM_TDEM_1D_Inversion", "FLOW_Richards_1D_Celia1990", "Forward_BasicDirectCurrent", "Inversion_Linear", "Mesh_Basic_PlotImage", "Mesh_Basic_Types", "Mesh_Operators_CahnHilliard", "Mesh_QuadTree_Creation", "Mesh_QuadTree_FaceDiv", "Mesh_QuadTree_HangingNodes", "Mesh_Tensor_Creation", "MT_1D_ForwardAndInversion", "MT_3D_Foward"]
__examples__ = ["DC_Analytic_Dipole", "DC_Forward_PseudoSection", "EM_FDEM_1D_Inversion", "EM_FDEM_Analytic_MagDipoleWholespace", "EM_Schenkel_Morrison_Casing", "EM_TDEM_1D_Inversion", "FLOW_Richards_1D_Celia1990", "Forward_BasicDirectCurrent", "Inversion_Linear", "Mesh_Basic_PlotImage", "Mesh_Basic_Types", "Mesh_Operators_CahnHilliard", "Mesh_QuadTree_Creation", "Mesh_QuadTree_FaceDiv", "Mesh_QuadTree_HangingNodes", "Mesh_Tensor_Creation", "MT_1D_ForwardAndInversion", "MT_3D_Foward"]
##### AUTOIMPORTS #####
+109 -30
View File
@@ -307,24 +307,28 @@ class DiffOperators(object):
return BC
_cellGradBC_list = 'neumann'
def _cellGradStencil(self):
BC = self.setCellGradBC(self._cellGradBC_list)
n = self.vnC
if(self.dim == 1):
G = ddxCellGrad(n[0], BC[0])
elif(self.dim == 2):
G1 = sp.kron(speye(n[1]), ddxCellGrad(n[0], BC[0]))
G2 = sp.kron(ddxCellGrad(n[1], BC[1]), speye(n[0]))
G = sp.vstack((G1, G2), format="csr")
elif(self.dim == 3):
G1 = kron3(speye(n[2]), speye(n[1]), ddxCellGrad(n[0], BC[0]))
G2 = kron3(speye(n[2]), ddxCellGrad(n[1], BC[1]), speye(n[0]))
G3 = kron3(ddxCellGrad(n[2], BC[2]), speye(n[1]), speye(n[0]))
G = sp.vstack((G1, G2, G3), format="csr")
return G
def cellGrad():
doc = "The cell centered Gradient, takes you to cell faces."
def fget(self):
if(self._cellGrad is None):
BC = self.setCellGradBC(self._cellGradBC_list)
n = self.vnC
if(self.dim == 1):
G = ddxCellGrad(n[0], BC[0])
elif(self.dim == 2):
G1 = sp.kron(speye(n[1]), ddxCellGrad(n[0], BC[0]))
G2 = sp.kron(ddxCellGrad(n[1], BC[1]), speye(n[0]))
G = sp.vstack((G1, G2), format="csr")
elif(self.dim == 3):
G1 = kron3(speye(n[2]), speye(n[1]), ddxCellGrad(n[0], BC[0]))
G2 = kron3(speye(n[2]), ddxCellGrad(n[1], BC[1]), speye(n[0]))
G3 = kron3(ddxCellGrad(n[2], BC[2]), speye(n[1]), speye(n[0]))
G = sp.vstack((G1, G2, G3), format="csr")
G = self._cellGradStencil()
# Compute areas of cell faces & volumes
S = self.area
V = self.aveCC2F*self.vol # Average volume between adjacent cells
@@ -361,19 +365,24 @@ class DiffOperators(object):
_cellGradBC = None
cellGradBC = property(**cellGradBC())
def _cellGradxStencil(self):
BC = ['neumann', 'neumann']
n = self.vnC
if(self.dim == 1):
G1 = ddxCellGrad(n[0], BC)
elif(self.dim == 2):
G1 = sp.kron(speye(n[1]), ddxCellGrad(n[0], BC))
elif(self.dim == 3):
G1 = kron3(speye(n[2]), speye(n[1]), ddxCellGrad(n[0], BC))
return G1
def cellGradx():
doc = "Cell centered Gradient in the x dimension. Has neumann boundary conditions."
def fget(self):
if getattr(self, '_cellGradx', None) is None:
BC = ['neumann', 'neumann']
n = self.vnC
if(self.dim == 1):
G1 = ddxCellGrad(n[0], BC)
elif(self.dim == 2):
G1 = sp.kron(speye(n[1]), ddxCellGrad(n[0], BC))
elif(self.dim == 3):
G1 = kron3(speye(n[2]), speye(n[1]), ddxCellGrad(n[0], BC))
G1 = self._cellGradxStencil()
# Compute areas of cell faces & volumes
V = self.aveCC2F*self.vol
L = self.r(self.area/V, 'F','Fx', 'V')
@@ -382,17 +391,22 @@ class DiffOperators(object):
return locals()
cellGradx = property(**cellGradx())
def _cellGradyStencil(self):
if self.dim < 2: return None
BC = ['neumann', 'neumann']
n = self.vnC
if(self.dim == 2):
G2 = sp.kron(ddxCellGrad(n[1], BC), speye(n[0]))
elif(self.dim == 3):
G2 = kron3(speye(n[2]), ddxCellGrad(n[1], BC), speye(n[0]))
return G2
def cellGrady():
doc = "Cell centered Gradient in the x dimension. Has neumann boundary conditions."
def fget(self):
if self.dim < 2: return None
if getattr(self, '_cellGrady', None) is None:
BC = ['neumann', 'neumann']
n = self.vnC
if(self.dim == 2):
G2 = sp.kron(ddxCellGrad(n[1], BC), speye(n[0]))
elif(self.dim == 3):
G2 = kron3(speye(n[2]), ddxCellGrad(n[1], BC), speye(n[0]))
G2 = self._cellGradyStencil()
# Compute areas of cell faces & volumes
V = self.aveCC2F*self.vol
L = self.r(self.area/V, 'F','Fy', 'V')
@@ -401,14 +415,19 @@ class DiffOperators(object):
return locals()
cellGrady = property(**cellGrady())
def _cellGradzStencil(self):
if self.dim < 3: return None
BC = ['neumann', 'neumann']
n = self.vnC
G3 = kron3(ddxCellGrad(n[2], BC), speye(n[1]), speye(n[0]))
return G3
def cellGradz():
doc = "Cell centered Gradient in the x dimension. Has neumann boundary conditions."
def fget(self):
if self.dim < 3: return None
if getattr(self, '_cellGradz', None) is None:
BC = ['neumann', 'neumann']
n = self.vnC
G3 = kron3(ddxCellGrad(n[2], BC), speye(n[1]), speye(n[0]))
G3 = self._cellGradzStencil()
# Compute areas of cell faces & volumes
V = self.aveCC2F*self.vol
L = self.r(self.area/V, 'F','Fz', 'V')
@@ -565,7 +584,67 @@ class DiffOperators(object):
return Pbc, Pin, Pout
def getBCProjWF_simple(self, discretization='CC'):
"""
The weak form boundary condition projection matrices
when mixed boundary condition is used
"""
if discretization is not 'CC':
raise NotImplementedError('Boundary conditions only implemented for CC discretization.')
def projBC(n):
ij = ([0,n], [0,1])
vals = [0,0]
vals[0] = 1
vals[1] = 1
return sp.csr_matrix((vals, ij), shape=(n+1,2))
def projDirichlet(n, bc):
bc = checkBC(bc)
ij = ([0,n], [0,1])
vals = [0,0]
if(bc[0] == 'dirichlet'):
vals[0] = -1
if(bc[1] == 'dirichlet'):
vals[1] = 1
return sp.csr_matrix((vals, ij), shape=(n+1,2))
BC = [['dirichlet','dirichlet'],['dirichlet','dirichlet'],['dirichlet','dirichlet']]
n = self.vnC
indF = self.faceBoundaryInd
if(self.dim == 1):
Pbc = projDirichlet(n[0], BC[0])
B = projBC(n[0])
indF = indF[0] | indF[1]
Pbc = Pbc*sdiag(self.area[indF])
elif(self.dim == 2):
Pbc1 = sp.kron(speye(n[1]), projDirichlet(n[0], BC[0]))
Pbc2 = sp.kron(projDirichlet(n[1], BC[1]), speye(n[0]))
Pbc = sp.block_diag((Pbc1, Pbc2), format="csr")
B1 = sp.kron(speye(n[1]), projBC(n[0]))
B2 = sp.kron(projBC(n[1]), speye(n[0]))
B = sp.block_diag((B1, B2), format="csr")
indF = np.r_[(indF[0] | indF[1]), (indF[2] | indF[3])]
Pbc = Pbc*sdiag(self.area[indF])
elif(self.dim == 3):
Pbc1 = kron3(speye(n[2]), speye(n[1]), projDirichlet(n[0], BC[0]))
Pbc2 = kron3(speye(n[2]), projDirichlet(n[1], BC[1]), speye(n[0]))
Pbc3 = kron3(projDirichlet(n[2], BC[2]), speye(n[1]), speye(n[0]))
Pbc = sp.block_diag((Pbc1, Pbc2, Pbc3), format="csr")
B1 = kron3(speye(n[2]), speye(n[1]), projBC(n[0]))
B2 = kron3(speye(n[2]), projBC(n[1]), speye(n[0]))
B3 = kron3(projBC(n[2]), speye(n[1]), speye(n[0]))
B = sp.block_diag((B1, B2, B3), format="csr")
indF = np.r_[(indF[0] | indF[1]), (indF[2] | indF[3]), (indF[4] | indF[5])]
Pbc = Pbc*sdiag(self.area[indF])
return Pbc, B.T
# --------------- Averaging ---------------------
@property
+1 -1
View File
@@ -21,7 +21,7 @@ class TensorMeshIO(object):
if '*' in seg:
st = seg
sp = seg.split('*')
re = np.array(sp[0],dtype=int)*(' ' + sp[1])
re = int(sp[0])*(' ' + sp[1])
line = line.replace(st,re.strip())
return np.array(line.split(),dtype=float)
+17
View File
@@ -888,6 +888,8 @@ class ProjectedGNCG(BFGS, Minimize, Remember):
maxIterCG = 5
tolCG = 1e-1
stepOffBoundsFact = 0.1 # perturbation of the inactive set off the bounds
lower = -np.inf
upper = np.inf
@@ -990,4 +992,19 @@ class ProjectedGNCG(BFGS, Minimize, Remember):
cgFlag = 1
# End CG Iterations
# Take a gradient step on the active cells if exist
if temp != self.xc.size:
rhs_a = (Active) * -self.g
dm_i = max( abs( delx ) )
dm_a = max( abs(rhs_a) )
# perturb inactive set off of bounds so that they are included in the step
delx = delx + self.stepOffBoundsFact * (rhs_a * dm_i / dm_a)
# Only keep gradients going in the right direction on the active set
indx = ((self.xc<=self.lower) & (delx < 0)) | ((self.xc>=self.upper) & (delx > 0))
delx[indx] = 0.
return delx
+490 -269
View File
@@ -1,5 +1,289 @@
import Utils, Maps, Mesh, numpy as np, scipy.sparse as sp
class RegularizationMesh(object):
"""
**Regularization Mesh**
This contains the operators used in the regularization. Note that these
are not necessarily true differential operators, but are constructed from
a SimPEG Mesh.
:param Mesh mesh: problem mesh
:param numpy.array indActive: bool array, size nC, that is True where we have active cells. Used to reduce the operators so we regularize only on active cells
"""
def __init__(self, mesh, indActive=None):
self.mesh = mesh
assert indActive is None or indActive.dtype == 'bool', 'indActive needs to be None or a bool'
self.indActive = indActive
@property
def vol(self):
"""
reduced volume vector
:rtype: numpy.array
:return: reduced cell volume
"""
if getattr(self, '_vol', None) is None:
self._vol = self._Pac.T * self.mesh.vol
return self._vol
@property
def nC(self):
"""
reduced number of cells
:rtype: int
:return: number of cells being regularized
"""
if getattr(self, '_nC', None) is None:
if self.indActive is None:
self._nC = self.mesh.nC
else:
self._nC = sum(self.indActive)
return self._nC
@property
def dim(self):
"""
dimension of regularization mesh (1D, 2D, 3D)
:rtype: int
:return: dimension
"""
if getattr(self, '_dim', None) is None:
self._dim = self.mesh.dim
return self._dim
@property
def _Pac(self):
"""
projection matrix that takes from the reduced space of active cells to full modelling space (ie. nC x nindActive)
:rtype: scipy.sparse.csr_matrix
:return: active cell projection matrix
"""
if getattr(self, '__Pac', None) is None:
if self.indActive is None:
self.__Pac = Utils.speye(self.mesh.nC)
else:
self.__Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
return self.__Pac
@property
def _Pafx(self):
"""
projection matrix that takes from the reduced space of active x-faces to full modelling space (ie. nFx x nindActive_Fx )
:rtype: scipy.sparse.csr_matrix
:return: active face-x projection matrix
"""
if getattr(self, '__Pafx', None) is None:
if self.indActive is None:
self.__Pafx = Utils.speye(self.mesh.nFx)
else:
indActive_Fx = (self.mesh.aveFx2CC.T * self.indActive) == 1
self.__Pafx = Utils.speye(self.mesh.nFx)[:,indActive_Fx]
return self.__Pafx
@property
def _Pafy(self):
"""
projection matrix that takes from the reduced space of active y-faces to full modelling space (ie. nFy x nindActive_Fy )
:rtype: scipy.sparse.csr_matrix
:return: active face-y projection matrix
"""
if getattr(self, '__Pafy', None) is None:
if self.indActive is None:
self.__Pafy = Utils.speye(self.mesh.nFy)
else:
indActive_Fy = (self.mesh.aveFy2CC.T * self.indActive) == 1
self.__Pafy = Utils.speye(self.mesh.nFy)[:,indActive_Fy]
return self.__Pafy
@property
def _Pafz(self):
"""
projection matrix that takes from the reduced space of active z-faces to full modelling space (ie. nFz x nindActive_Fz )
:rtype: scipy.sparse.csr_matrix
:return: active face-z projection matrix
"""
if getattr(self, '__Pafz', None) is None:
if self.indActive is None:
self.__Pafz = Utils.speye(self.mesh.nFz)
else:
indActive_Fz = (self.mesh.aveFz2CC.T * self.indActive) == 1
self.__Pafz = Utils.speye(self.mesh.nFz)[:,indActive_Fz]
return self.__Pafz
@property
def aveFx2CC(self):
"""
averaging from active cell centers to active x-faces
:rtype: scipy.sparse.csr_matrix
:return: averaging from active cell centers to active x-faces
"""
if getattr(self, '_aveFx2CC', None) is None:
self._aveFx2CC = self._Pac.T * self.mesh.aveFx2CC * self._Pafx
return self._aveFx2CC
@property
def aveCC2Fx(self):
"""
averaging from active x-faces to active cell centers
:rtype: scipy.sparse.csr_matrix
:return: averaging matrix from active x-faces to active cell centers
"""
if getattr(self, '_aveCC2Fx', None) is None:
self._aveCC2Fx = Utils.sdiag(1./(self.aveFx2CC.T).sum(1)) * self.aveFx2CC.T
return self._aveCC2Fx
@property
def aveFy2CC(self):
"""
averaging from active cell centers to active y-faces
:rtype: scipy.sparse.csr_matrix
:return: averaging from active cell centers to active y-faces
"""
if getattr(self, '_aveFy2CC', None) is None:
self._aveFy2CC = self._Pac.T * self.mesh.aveFy2CC * self._Pafy
return self._aveFy2CC
@property
def aveCC2Fy(self):
"""
averaging from active y-faces to active cell centers
:rtype: scipy.sparse.csr_matrix
:return: averaging matrix from active y-faces to active cell centers
"""
if getattr(self, '_aveCC2Fy', None) is None:
self._aveCC2Fy = Utils.sdiag(1./(self.aveFy2CC.T).sum(1)) * self.aveFy2CC.T
return self._aveCC2Fy
@property
def aveFz2CC(self):
"""
averaging from active cell centers to active z-faces
:rtype: scipy.sparse.csr_matrix
:return: averaging from active cell centers to active z-faces
"""
if getattr(self, '_aveFz2CC', None) is None:
self._aveFz2CC = self._Pac.T * self.mesh.aveFz2CC * self._Pafz
return self._aveFz2CC
@property
def aveCC2Fz(self):
"""
averaging from active z-faces to active cell centers
:rtype: scipy.sparse.csr_matrix
:return: averaging matrix from active z-faces to active cell centers
"""
if getattr(self, '_aveCC2Fz', None) is None:
self._aveCC2Fz = Utils.sdiag(1./(self.aveFz2CC.T).sum(1)) * self.aveFz2CC.T
return self._aveCC2Fz
@property
def cellDiffx(self):
"""
cell centered difference in the x-direction
:rtype: scipy.sparse.csr_matrix
:return: differencing matrix for active cells in the x-direction
"""
if getattr(self, '_cellDiffx', None) is None:
self._cellDiffx = self._Pafx.T * self.mesh.cellGradx * self._Pac
return self._cellDiffx
@property
def cellDiffy(self):
"""
cell centered difference in the y-direction
:rtype: scipy.sparse.csr_matrix
:return: differencing matrix for active cells in the y-direction
"""
if getattr(self, '_cellDiffy', None) is None:
self._cellDiffy = self._Pafy.T * self.mesh.cellGrady * self._Pac
return self._cellDiffy
@property
def cellDiffz(self):
"""
cell centered difference in the z-direction
:rtype: scipy.sparse.csr_matrix
:return: differencing matrix for active cells in the z-direction
"""
if getattr(self, '_cellDiffz', None) is None:
self._cellDiffz = self._Pafz.T * self.mesh.cellGradz * self._Pac
return self._cellDiffz
@property
def faceDiffx(self):
"""
x-face differences
:rtype: scipy.sparse.csr_matrix
:return: differencing matrix for active faces in the x-direction
"""
if getattr(self, '_faceDiffx', None) is None:
self._faceDiffx = self._Pac.T * self.mesh.faceDivx * self._Pafx
return self._faceDiffx
@property
def faceDiffy(self):
"""
y-face differences
:rtype: scipy.sparse.csr_matrix
:return: differencing matrix for active faces in the y-direction
"""
if getattr(self, '_faceDiffy', None) is None:
self._faceDiffy = self._Pac.T * self.mesh.faceDivy * self._Pafy
return self._faceDiffy
@property
def faceDiffz(self):
"""
z-face differences
:rtype: scipy.sparse.csr_matrix
:return: differencing matrix for active faces in the z-direction
"""
if getattr(self, '_faceDiffz', None) is None:
self._faceDiffz = self._Pac.T * self.mesh.faceDivz * self._Pafz
return self._faceDiffz
@property
def cellDiffxStencil(self):
"""
cell centered difference stencil (no cell lengths include) in the x-direction
:rtype: scipy.sparse.csr_matrix
:return: differencing matrix for active cells in the x-direction
"""
if getattr(self, '_cellDiffxStencil', None) is None:
self._cellDiffxStencil = self._Pafx.T * self.mesh._cellGradxStencil() * self._Pac
return self._cellDiffxStencil
@property
def cellDiffyStencil(self):
"""
cell centered difference stencil (no cell lengths include) in the y-direction
:rtype: scipy.sparse.csr_matrix
:return: differencing matrix for active cells in the y-direction
"""
if self.dim < 2: return None
if getattr(self, '_cellDiffyStencil', None) is None:
self._cellDiffyStencil = self._Pafy.T * self.mesh._cellGradyStencil() * self._Pac
return self._cellDiffyStencil
@property
def cellDiffzStencil(self):
"""
cell centered difference stencil (no cell lengths include) in the y-direction
:rtype: scipy.sparse.csr_matrix
:return: differencing matrix for active cells in the y-direction
"""
if self.dim < 3: return None
if getattr(self, '_cellDiffzStencil', None) is None:
self._cellDiffzStencil = self._Pafz.T * self.mesh._cellGradzStencil() * self._Pac
return self._cellDiffzStencil
class BaseRegularization(object):
"""
**Base Regularization Class**
@@ -18,12 +302,16 @@ class BaseRegularization(object):
mapping = None #: A SimPEG.Map instance.
mesh = None #: A SimPEG.Mesh instance.
mref = None #: Reference model.
mref = None #: Reference model.
def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
Utils.setKwargs(self, **kwargs)
self.mesh = mesh
assert isinstance(mesh, Mesh.BaseMesh), "mesh must be a SimPEG.Mesh object."
if indActive is not None and indActive.dtype != 'bool':
tmp = indActive
indActive = np.zeros(mesh.nC, dtype=bool)
indActive[tmp] = True
self.regmesh = RegularizationMesh(mesh,indActive)
self.mapping = mapping or self.mapPair(mesh)
self.mapping._assertMatchesPair(self.mapPair)
self.indActive = indActive
@@ -55,8 +343,8 @@ class BaseRegularization(object):
@property
def W(self):
"""Full regularization weighting matrix W."""
return sp.identity(self.mapping.nP)
return sp.identity(self.regmesh.nC)
# self.regmesh._Pac.T * sp.identity(self.regmesh.nC) * self.regmesh._Pac # or do we want sp.identity(self.mesh.nC) or even just Utils.Identity() ?
@Utils.timeIt
def eval(self, m):
@@ -112,11 +400,10 @@ class BaseRegularization(object):
return mD.T * ( self.W.T * ( self.W * ( mD * v) ) )
class Tikhonov(BaseRegularization):
"""
"""
smoothModel = True #: SMOOTH and SMOOTH_MOD_DIF options
mrefInSmooth = True #: SMOOTH and SMOOTH_MOD_DIF options
alpha_s = Utils.dependentProperty('_alpha_s', 1e-6, ['_W', '_Ws'], "Smallness weight")
alpha_x = Utils.dependentProperty('_alpha_x', 1.0, ['_W', '_Wx'], "Weight for the first derivative in the x direction")
alpha_y = Utils.dependentProperty('_alpha_y', 1.0, ['_W', '_Wy'], "Weight for the first derivative in the y direction")
@@ -126,98 +413,58 @@ class Tikhonov(BaseRegularization):
alpha_zz = Utils.dependentProperty('_alpha_zz', 0.0, ['_W', '_Wzz'], "Weight for the second derivative in the z direction")
def __init__(self, mesh, mapping=None, indActive = None, **kwargs):
BaseRegularization.__init__(self, mesh, mapping=mapping, **kwargs)
self.indActive = indActive
BaseRegularization.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
@property
def Ws(self):
"""Regularization matrix Ws"""
if getattr(self,'_Ws', None) is None:
self._Ws = Utils.sdiag((self.mesh.vol*self.alpha_s)**0.5)
if self.indActive is not None:
Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
self._Ws = Pac.T * self._Ws * Pac
self._Ws = Utils.sdiag((self.regmesh.vol*self.alpha_s)**0.5)
return self._Ws
@property
def Wx(self):
"""Regularization matrix Wx"""
if getattr(self, '_Wx', None) is None:
Ave_x_vol = self.mesh.aveF2CC[:,:self.mesh.nFx].T*self.mesh.vol
self._Wx = Utils.sdiag((Ave_x_vol*self.alpha_x)**0.5)*self.mesh.cellGradx
if self.indActive is not None:
indActive_Fx = (self.mesh.aveFx2CC.T * self.indActive) == 1
Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
Pafx = Utils.speye(self.mesh.nFx)[:,indActive_Fx]
self._Wx = Pafx.T*self._Wx*Pac
Ave_x_vol = self.regmesh.aveCC2Fx * self.regmesh.vol
self._Wx = Utils.sdiag((Ave_x_vol*self.alpha_x)**0.5)*self.regmesh.cellDiffx
return self._Wx
@property
def Wy(self):
"""Regularization matrix Wy"""
if getattr(self, '_Wy', None) is None:
Ave_y_vol = self.mesh.aveF2CC[:,self.mesh.nFx:np.sum(self.mesh.vnF[:2])].T*self.mesh.vol
self._Wy = Utils.sdiag((Ave_y_vol*self.alpha_y)**0.5)*self.mesh.cellGrady
if self.indActive is not None:
indActive_Fy = (self.mesh.aveFy2CC.T * self.indActive) == 1
Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
Pafy = Utils.speye(self.mesh.nFy)[:,indActive_Fy]
self._Wy = Pafy.T*self._Wy*Pac
Ave_y_vol = self.regmesh.aveCC2Fy * self.regmesh.vol
self._Wy = Utils.sdiag((Ave_y_vol*self.alpha_y)**0.5)*self.regmesh.cellDiffy
return self._Wy
@property
def Wz(self):
"""Regularization matrix Wz"""
if getattr(self, '_Wz', None) is None:
Ave_z_vol = self.mesh.aveF2CC[:,np.sum(self.mesh.vnF[:2]):].T*self.mesh.vol
self._Wz = Utils.sdiag((Ave_z_vol*self.alpha_z)**0.5)*self.mesh.cellGradz
if self.indActive is not None:
indActive_Fz = (self.mesh.aveFz2CC.T * self.indActive) == 1
Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
Pafz = Utils.speye(self.mesh.nFz)[:,indActive_Fz]
self._Wz = Pafz.T*self._Wz*Pac
Ave_z_vol = self.regmesh.aveCC2Fz * self.regmesh.vol
self._Wz = Utils.sdiag((Ave_z_vol*self.alpha_z)**0.5)*self.regmesh.cellDiffz
return self._Wz
@property
def Wxx(self):
"""Regularization matrix Wxx"""
if getattr(self, '_Wxx', None) is None:
self._Wxx = Utils.sdiag((self.mesh.vol*self.alpha_xx)**0.5)*self.mesh.faceDivx*self.mesh.cellGradx
if self.indActive is not None:
Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
self._Wxx = Pac.T*self._Wxx*Pac
self._Wxx = Utils.sdiag((self.regmesh.vol*self.alpha_xx)**0.5)*self.regmesh.faceDiffx*self.regmesh.cellDiffx
return self._Wxx
@property
def Wyy(self):
"""Regularization matrix Wyy"""
if getattr(self, '_Wyy', None) is None:
self._Wyy = Utils.sdiag((self.mesh.vol*self.alpha_yy)**0.5)*self.mesh.faceDivy*self.mesh.cellGrady
if self.indActive is not None:
Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
self._Wyy = Pac.T*self._Wyy*Pac
self._Wyy = Utils.sdiag((self.regmesh.vol*self.alpha_yy)**0.5)*self.regmesh.faceDiffy*self.regmesh.cellDiffy
return self._Wyy
@property
def Wzz(self):
"""Regularization matrix Wzz"""
if getattr(self, '_Wzz', None) is None:
self._Wzz = Utils.sdiag((self.mesh.vol*self.alpha_zz)**0.5)*self.mesh.faceDivz*self.mesh.cellGradz
if self.indActive is not None:
Pac = Utils.speye(self.mesh.nC)[:,self.indActive]
self._Wzz = Pac.T*self._Wzz*Pac
self._Wzz = Utils.sdiag((self.regmesh.vol*self.alpha_zz)**0.5)*self.regmesh.faceDiffz*self.regmesh.cellDiffz
return self._Wzz
@property
@@ -225,9 +472,9 @@ class Tikhonov(BaseRegularization):
"""Full smoothness regularization matrix W"""
if getattr(self, '_Wsmooth', None) is None:
wlist = (self.Wx, self.Wxx)
if self.mesh.dim > 1:
if self.regmesh.dim > 1:
wlist += (self.Wy, self.Wyy)
if self.mesh.dim > 2:
if self.regmesh.dim > 2:
wlist += (self.Wz, self.Wzz)
self._Wsmooth = sp.vstack(wlist)
return self._Wsmooth
@@ -242,11 +489,11 @@ class Tikhonov(BaseRegularization):
@Utils.timeIt
def eval(self, m):
if self.smoothModel == True:
if self.mrefInSmooth == True:
r1 = self.Wsmooth * ( self.mapping * (m) )
r2 = self.Ws * ( self.mapping * (m - self.mref) )
return 0.5*(r1.dot(r1)+r2.dot(r2))
elif self.smoothModel == False:
elif self.mrefInSmooth == False:
r = self.W * ( self.mapping * (m - self.mref) )
return 0.5*r.dot(r)
@@ -268,7 +515,7 @@ class Tikhonov(BaseRegularization):
R(m) = \mathbf{W^\\top W (m-m_\\text{ref})}
"""
if self.smoothModel == True:
if self.mrefInSmooth == True:
mD1 = self.mapping.deriv(m)
mD2 = self.mapping.deriv(m - self.mref)
r1 = self.Wsmooth * ( self.mapping * (m))
@@ -276,249 +523,223 @@ class Tikhonov(BaseRegularization):
out1 = mD1.T * ( self.Wsmooth.T * r1 )
out2 = mD2.T * ( self.Ws.T * r2 )
out = out1+out2
elif self.smoothModel == False:
elif self.mrefInSmooth == False:
mD = self.mapping.deriv(m - self.mref)
r = self.W * ( self.mapping * (m - self.mref) )
out = mD.T * ( self.W.T * r )
return out
# <<<<<<< HEAD
# class Simple(BaseRegularization):
# """
# Only for tensor mesh
# """
class Simple(BaseRegularization):
"""
Only for tensor mesh
"""
# smoothModel = True #: SMOOTH and SMOOTH_MOD_DIF options
# alpha_s = Utils.dependentProperty('_alpha_s', 1.0, ['_W', '_Ws'], "Smallness weight")
# alpha_x = Utils.dependentProperty('_alpha_x', 1.0, ['_W', '_Wx'], "Weight for the first derivative in the x direction")
# alpha_y = Utils.dependentProperty('_alpha_y', 1.0, ['_W', '_Wy'], "Weight for the first derivative in the y direction")
# alpha_z = Utils.dependentProperty('_alpha_z', 1.0, ['_W', '_Wz'], "Weight for the first derivative in the z direction")
# alpha_xx = Utils.dependentProperty('_alpha_xx', 0.0, ['_W', '_Wxx'], "Weight for the second derivative in the x direction")
# alpha_yy = Utils.dependentProperty('_alpha_yy', 0.0, ['_W', '_Wyy'], "Weight for the second derivative in the y direction")
# alpha_zz = Utils.dependentProperty('_alpha_zz', 0.0, ['_W', '_Wzz'], "Weight for the second derivative in the z direction")
mrefInSmooth = True #: SMOOTH and SMOOTH_MOD_DIF options
alpha_s = Utils.dependentProperty('_alpha_s', 1.0, ['_W', '_Ws'], "Smallness weight")
alpha_x = Utils.dependentProperty('_alpha_x', 1.0, ['_W', '_Wx'], "Weight for the first derivative in the x direction")
alpha_y = Utils.dependentProperty('_alpha_y', 1.0, ['_W', '_Wy'], "Weight for the first derivative in the y direction")
alpha_z = Utils.dependentProperty('_alpha_z', 1.0, ['_W', '_Wz'], "Weight for the first derivative in the z direction")
wght = 1.
def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
BaseRegularization.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
if isinstance(self.wght,float):
self.wght = np.ones(self.regmesh.nC) * self.wght
# def __init__(self, mesh, mapping=None, **kwargs):
# BaseRegularization.__init__(self, mesh, mapping=mapping, **kwargs)
@property
def Ws(self):
"""Regularization matrix Ws"""
if getattr(self,'_Ws', None) is None:
self._Ws = Utils.sdiag((self.regmesh.vol*self.alpha_s*self.wght)**0.5)
return self._Ws
@property
def Wx(self):
"""Regularization matrix Wx"""
if getattr(self, '_Wx', None) is None:
self._Wx = Utils.sdiag((self.regmesh.aveCC2Fx * self.regmesh.vol*self.alpha_x*(self.regmesh.aveCC2Fx*self.wght))**0.5)*self.regmesh.cellDiffxStencil
return self._Wx
@property
def Wy(self):
"""Regularization matrix Wy"""
if getattr(self, '_Wy', None) is None:
self._Wy = Utils.sdiag((self.regmesh.aveCC2Fy * self.regmesh.vol * self.alpha_y*(self.regmesh.aveCC2Fy*self.wght))**0.5)*self.regmesh.cellDiffyStencil
return self._Wy
@property
def Wz(self):
"""Regularization matrix Wz"""
if getattr(self, '_Wz', None) is None:
self._Wz = Utils.sdiag((self.regmesh.aveCC2Fz * self.regmesh.vol*self.alpha_z*(self.regmesh.aveCC2Fz*self.wght))**0.5)*self.regmesh.cellDiffzStencil
return self._Wz
@property
def Wsmooth(self):
"""Full smoothness regularization matrix W"""
if getattr(self, '_Wsmooth', None) is None:
wlist = (self.Wx,)
if self.regmesh.dim > 1:
wlist += (self.Wy,)
if self.regmesh.dim > 2:
wlist += (self.Wz,)
self._Wsmooth = sp.vstack(wlist)
return self._Wsmooth
@property
def W(self):
"""Full regularization matrix W"""
if getattr(self, '_W', None) is None:
wlist = (self.Ws, self.Wsmooth)
self._W = sp.vstack(wlist)
return self._W
@Utils.timeIt
def eval(self, m):
if self.mrefInSmooth == True:
r1 = self.Wsmooth * ( self.mapping * (m) )
r2 = self.Ws * ( self.mapping * (m - self.mref) )
return 0.5*(r1.dot(r1)+r2.dot(r2))
elif self.mrefInSmooth == False:
r = self.W * ( self.mapping * (m - self.mref) )
return 0.5*r.dot(r)
return phim
# @property
# def Ws(self):
# """Regularization matrix Ws"""
# if getattr(self,'_Ws', None) is None:
# self._Ws = Utils.sdiag((self.mesh.vol*self.alpha_s)**0.5)
# return self._Ws
@Utils.timeIt
def evalDeriv(self, m):
"""
# @property
# def Wx(self):
# """Regularization matrix Wx"""
# if getattr(self, '_Wx', None) is None:
# self._Wx = Utils.sdiag((self.mesh.vol*self.alpha_x)**0.5)*self.mesh.unitCellGradx
# return self._Wx
The regularization is:
# @property
# def Wy(self):
# """Regularization matrix Wy"""
# if getattr(self, '_Wy', None) is None:
# self._Wy = Utils.sdiag((self.mesh.vol*self.alpha_y)**0.5)*self.mesh.unitCellGrady
# return self._Wy
.. math::
# @property
# def Wz(self):
# """Regularization matrix Wz"""
# if getattr(self, '_Wz', None) is None:
# self._Wz = Utils.sdiag((self.mesh.vol*self.alpha_z)**0.5)*self.mesh.unitCellGradz
# return self._Wz
R(m) = \\frac{1}{2}\mathbf{(m-m_\\text{ref})^\\top W^\\top W(m-m_\\text{ref})}
# @property
# def Wxx(self):
# """Regularization matrix Wxx"""
# if getattr(self, '_Wxx', None) is None:
# self._Wxx = Utils.sdiag((self.mesh.vol*self.alpha_xx)**0.5)*self.mesh.faceDivx*self.mesh.cellGradx
# return self._Wxx
So the derivative is straight forward:
# @property
# def Wyy(self):
# """Regularization matrix Wyy"""
# if getattr(self, '_Wyy', None) is None:
# self._Wyy = Utils.sdiag((self.mesh.vol*self.alpha_yy)**0.5)*self.mesh.faceDivy*self.mesh.cellGrady
# return self._Wyy
.. math::
# @property
# def Wzz(self):
# """Regularization matrix Wzz"""
# if getattr(self, '_Wzz', None) is None:
# self._Wzz = Utils.sdiag((self.mesh.vol*self.alpha_zz)**0.5)*self.mesh.faceDivz*self.mesh.cellGradz
# return self._Wzz
R(m) = \mathbf{W^\\top W (m-m_\\text{ref})}
# @property
# def Wsmooth(self):
# """Full smoothness regularization matrix W"""
# if getattr(self, '_Wsmooth', None) is None:
# wlist = (self.Wx, self.Wxx)
# if self.mesh.dim > 1:
# wlist += (self.Wy, self.Wyy)
# if self.mesh.dim > 2:
# wlist += (self.Wz, self.Wzz)
# self._Wsmooth = sp.vstack(wlist)
# return self._Wsmooth
# @property
# def W(self):
# """Full regularization matrix W"""
# if getattr(self, '_W', None) is None:
# wlist = (self.Ws, self.Wsmooth)
# self._W = sp.vstack(wlist)
# return self._W
# @Utils.timeIt
# def eval(self, m):
# if self.smoothModel == True:
# r1 = self.Wsmooth * ( self.mapping * (m) )
# r2 = self.Ws * ( self.mapping * (m - self.mref) )
# return 0.5*(r1.dot(r1)+r2.dot(r2))
# elif self.smoothModel == False:
# r = self.W * ( self.mapping * (m - self.mref) )
# return 0.5*r.dot(r)
"""
if self.mrefInSmooth == True:
mD1 = self.mapping.deriv(m)
mD2 = self.mapping.deriv(m - self.mref)
r1 = self.Wsmooth * ( self.mapping * (m))
r2 = self.Ws * ( self.mapping * (m - self.mref) )
out1 = mD1.T * ( self.Wsmooth.T * r1 )
out2 = mD2.T * ( self.Ws.T * r2 )
out = out1+out2
elif self.mrefInSmooth == False:
mD = self.mapping.deriv(m - self.mref)
r = self.W * ( self.mapping * (m - self.mref) )
out = mD.T * ( self.W.T * r )
return out
# @Utils.timeIt
# def evalDeriv(self, m):
# """
class Sparse(Simple):
# The regularization is:
# set default values
eps = 1e-1
curModel = None # use a model to compute the weights
gamma = 1.
p = 0.
qx = 2.
qy = 2.
qz = 2.
wght = 1.
# .. math::
def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
Simple.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
if isinstance(self.wght,float):
self.wght = np.ones(self.regmesh.nC) * self.wght
# R(m) = \\frac{1}{2}\mathbf{(m-m_\\text{ref})^\\top W^\\top W(m-m_\\text{ref})}
@property
def Ws(self):
"""Regularization matrix Ws"""
if getattr(self, 'curModel', None) is None:
self.Rs = Utils.speye(self.regmesh.nC)
# So the derivative is straight forward:
# .. math::
# R(m) = \mathbf{W^\\top W (m-m_\\text{ref})}
# """
# if self.smoothModel == True:
# mD1 = self.mapping.deriv(m)
# mD2 = self.mapping.deriv(m - self.mref)
# r1 = self.Wsmooth * ( self.mapping * (m))
# r2 = self.Ws * ( self.mapping * (m - self.mref) )
# out1 = mD1.T * ( self.Wsmooth.T * r1 )
# out2 = mD2.T * ( self.Ws.T * r2 )
# out = out1+out2
# elif self.smoothModel == False:
# mD = self.mapping.deriv(m - self.mref)
# r = self.W * ( self.mapping * (m - self.mref) )
# out = mD.T * ( self.W.T * r )
# return out
# class SparseRegularization(Simple):
# eps = 1e-1
# m = None
# gamma = 1.
# p = 0.
# qx = 2.
# qy = 2.
# qz = 2.
# def __init__(self, mesh, mapping=None, **kwargs):
# Simple.__init__(self, mesh, mapping=mapping, **kwargs)
else:
f_m = self.curModel - self.reg.mref
self.rs = self.R(f_m , self.p)
#print "Min rs: " + str(np.max(self.rs)) + "Max rs: " + str(np.min(self.rs))
self.Rs = Utils.sdiag( self.rs )
return Utils.sdiag((self.regmesh.vol*self.alpha_s*self.gamma*self.wght)**0.5)*self.Rs
# @property
# def Wsmooth(self):
# """Full smoothness regularization matrix W"""
# if getattr(self, '_Wsmooth', None) is None:
# wlist = (self.Wx, self.Wxx)
# if self.mesh.dim > 1:
# wlist += (self.Wy, self.Wyy)
# if self.mesh.dim > 2:
# wlist += (self.Wz, self.Wzz)
# self._Wsmooth = sp.vstack(wlist)
# return self._Wsmooth
@property
def Wx(self):
"""Regularization matrix Wx"""
if getattr(self, 'curModel', None) is None:
self.Rx = Utils.speye(self.regmesh.cellDiffxStencil.shape[0])
# @property
# def W(self):
# """Full regularization matrix W"""
# if getattr(self, '_W', None) is None:
# wlist = (self.Ws, self.Wsmooth)
# self._W = sp.vstack(wlist)
# return self._W
else:
f_m = self.regmesh.cellDiffxStencil * self.curModel
self.rx = self.R( f_m , self.qx)
self.Rx = Utils.sdiag( self.rx )
# @property
# def Ws(self):
# """Regularization matrix Ws"""
# if getattr(self, 'm', None) is None:
# self.Rs = Utils.speye(self.mesh.nC)
return Utils.sdiag(( (self.regmesh.aveCC2Fx * self.regmesh.vol) *self.alpha_x*self.gamma*(self.regmesh.aveCC2Fx*self.wght))**0.5)*self.Rx*self.regmesh.cellDiffxStencil
# else:
# f_m = self.m
# self.rs = self.R(f_m , self.p, self.eps)
# #print "Min rs: " + str(np.max(self.rs)) + "Max rs: " + str(np.min(self.rs))
# self.Rs = Utils.sdiag( self.rs )
@property
def Wy(self):
"""Regularization matrix Wy"""
# self._Ws = Utils.sdiag((self.mesh.vol*self.alpha_s*self.gamma)**0.5)*self.Rs
if getattr(self, 'curModel', None) is None:
self.Ry = Utils.speye(self.regmesh.cellDiffyStencil.shape[0])
# return self._Ws
else:
f_m = self.regmesh.cellDiffyStencil * self.curModel
self.ry = self.R( f_m , self.qy)
self.Ry = Utils.sdiag( self.ry )
return Utils.sdiag(((self.regmesh.aveCC2Fy * self.regmesh.vol)*self.alpha_y*self.gamma*(self.regmesh.aveCC2Fy*self.wght))**0.5)*self.Ry*self.regmesh.cellDiffyStencil
# @property
# def Wx(self):
# """Regularization matrix Wx"""
@property
def Wz(self):
"""Regularization matrix Wz"""
# if getattr(self, 'm', None) is None:
# self.Rx = Utils.speye(self.mesh.unitCellGradx.shape[0])
if getattr(self, 'curModel', None) is None:
self.Rz = Utils.speye(self.regmesh.cellDiffzStencil.shape[0])
# else:
# f_m = self.mesh.unitCellGradx * self.m
# self.rx = self.R( f_m , self.qx, self.eps)
# self.Rx = Utils.sdiag( self.rx )
else:
f_m = self.regmesh.cellDiffzStencil * self.curModel
self.rz = self.R( f_m , self.qz)
self.Rz = Utils.sdiag( self.rz )
# if getattr(self, '_Wx', None) is None:
# self._Wx = Utils.sdiag((self.mesh.vol*self.alpha_x*self.gamma)**0.5)*self.Rx*self.mesh.unitCellGradx
# return self._Wx
return Utils.sdiag(((self.regmesh.aveCC2Fz * self.regmesh.vol)*self.alpha_z*self.gamma*(self.regmesh.aveCC2Fz*self.wght))**0.5)*self.Rz*self.regmesh.cellDiffzStencil
# @property
# def Wy(self):
# """Regularization matrix Wy"""
@property
def Wsmooth(self):
"""Full smoothness regularization matrix W"""
#if getattr(self, '_Wsmooth', None) is None:
wlist = (self.Wx,)
if self.regmesh.dim > 1:
wlist += (self.Wy,)
if self.regmesh.dim > 2:
wlist += (self.Wz,)
#self._Wsmooth = sp.vstack(wlist)
return sp.vstack(wlist)
# if getattr(self, 'm', None) is None:
# self.Ry = Utils.speye(self.mesh.unitCellGrady.shape[0])
@property
def W(self):
"""Full regularization matrix W"""
#if getattr(self, '_W', None) is None:
wlist = (self.Ws, self.Wsmooth)
#self._W = sp.vstack(wlist)
return sp.vstack(wlist)
def R(self, f_m , exponent):
# else:
# f_m = self.mesh.unitCellGrady * self.m
# self.ry = self.R( f_m , self.qy, self.eps)
# self.Ry = Utils.sdiag( self.ry )
eta = (self.eps**(1-exponent/2.))**0.5
r = eta / (f_m**2.+self.eps**2.)**((1-exponent/2.)/2.)
# if getattr(self, '_Wy', None) is None:
# self._Wy = Utils.sdiag((self.mesh.vol*self.alpha_y*self.gamma)**0.5)*self.Ry*self.mesh.unitCellGrady
# return self._Wy
# @property
# def Wz(self):
# """Regularization matrix Wz"""
# if getattr(self, 'm', None) is None:
# self.Rz = Utils.speye(self.mesh.unitCellGradz.shape[0])
# else:
# f_m = self.mesh.unitCellGradz * self.m
# self.rz = self.R( f_m , self.qz, self.eps)
# self.Rz = Utils.sdiag( self.rz )
# if getattr(self, '_Wz', None) is None:
# self._Wz = Utils.sdiag((self.mesh.vol*self.alpha_z*self.gamma)**0.5)*self.Rz*self.mesh.unitCellGradz
# return self._Wz
# def R(self, f_m , p, dec):
# eta = (self.eps**(1-p/2.))**0.5
# r = eta / (f_m**2.+self.eps**2.)**((1-p/2.)/2.)
# return r
# =======
# >>>>>>> 834de582844e8e1eac95819fbe03eed55dbeb001
return r
@@ -0,0 +1,58 @@
.. _examples_EM_Schenkel_Morrison_Casing:
.. --------------------------------- ..
.. ..
.. THIS FILE IS AUTO GENEREATED ..
.. ..
.. SimPEG/Examples/__init__.py ..
.. ..
.. --------------------------------- ..
EM: Schenkel and Morrison Casing Model
======================================
Here we create and run a FDEM forward simulation to calculate the vertical
current inside a steel-cased. The model is based on the Schenkel and
Morrison Casing Model, and the results are used in a 2016 SEG abstract by
Yang et al.
- Schenkel, C.J., and H.F. Morrison, 1990, Effects of well casing on potential field measurements using downhole current sources: Geophysical prospecting, 38, 663-686.
The model consists of:
- Air: Conductivity 1e-8 S/m, above z = 0
- Background: conductivity 1e-2 S/m, below z = 0
- Casing: conductivity 1e6 S/m
- 300m long
- radius of 0.1m
- thickness of 6e-3m
Inside the casing, we take the same conductivity as the background.
We are using an EM code to simulate DC, so we use frequency low enough
that the skin depth inside the casing is longer than the casing length (f
= 1e-6 Hz). The plot produced is of the current inside the casing.
These results are shown in the SEG abstract by Yang et al., 2016: 3D DC
resistivity modeling of steel casing for reservoir monitoring using
equivalent resistor network. The solver used to produce these results and
achieve the CPU time of ~30s is Mumps, which was installed using pymatsolver_
.. _pymatsolver: https://github.com/rowanc1/pymatsolver
This example is on figshare: https://dx.doi.org/10.6084/m9.figshare.3126961.v1
If you would use this example for a code comparison, or build upon it, a
citation would be much appreciated!
.. plot::
from SimPEG import Examples
Examples.EM_Schenkel_Morrison_Casing.run()
.. literalinclude:: ../../SimPEG/Examples/EM_Schenkel_Morrison_Casing.py
:language: python
:linenos:
+75 -49
View File
@@ -5,6 +5,8 @@ from scipy.sparse.linalg import dsolve
import inspect
TOL = 1e-20
testReg = True
testRegMesh = True
class RegularizationTests(unittest.TestCase):
@@ -16,44 +18,82 @@ class RegularizationTests(unittest.TestCase):
mesh3 = Mesh.TensorMesh([hx, hy, hz])
self.meshlist = [mesh1,mesh2, mesh3]
def test_regularization(self):
for R in dir(Regularization):
r = getattr(Regularization, R)
if not inspect.isclass(r): continue
if not issubclass(r, Regularization.BaseRegularization):
continue
if testReg:
def test_regularization(self):
for R in dir(Regularization):
r = getattr(Regularization, R)
if not inspect.isclass(r): continue
if not issubclass(r, Regularization.BaseRegularization):
continue
for i, mesh in enumerate(self.meshlist):
print 'Testing %iD'%mesh.dim
mapping = r.mapPair(mesh)
reg = r(mesh, mapping=mapping)
m = np.random.rand(mapping.nP)
reg.mref = np.ones_like(m)*np.mean(m)
print 'Check: phi_m (mref) = %f' %reg.eval(reg.mref)
passed = reg.eval(reg.mref) < TOL
self.assertTrue(passed)
print 'Check:', R
passed = Tests.checkDerivative(lambda m : [reg.eval(m), reg.evalDeriv(m)], m, plotIt=False)
self.assertTrue(passed)
print 'Check 2 Deriv:', R
passed = Tests.checkDerivative(lambda m : [reg.evalDeriv(m), reg.eval2Deriv(m)], m, plotIt=False)
self.assertTrue(passed)
def test_regularization_ActiveCells(self):
for R in dir(Regularization):
r = getattr(Regularization, R)
if not inspect.isclass(r): continue
if not issubclass(r, Regularization.BaseRegularization):
continue
for i, mesh in enumerate(self.meshlist):
print 'Testing Active Cells %iD'%(mesh.dim)
if mesh.dim == 1:
indActive = Utils.mkvc(mesh.gridCC <= 0.8)
elif mesh.dim == 2:
indActive = Utils.mkvc(mesh.gridCC[:,-1] <= 2*np.sin(2*np.pi*mesh.gridCC[:,0])+0.5)
elif mesh.dim == 3:
indActive = Utils.mkvc(mesh.gridCC[:,-1] <= 2*np.sin(2*np.pi*mesh.gridCC[:,0])+0.5 * 2*np.sin(2*np.pi*mesh.gridCC[:,1])+0.5)
mapping = Maps.IdentityMap(nP=indActive.nonzero()[0].size)
for indAct in [indActive, indActive.nonzero()[0]]: # test both bool and integers
reg = r(mesh, mapping=mapping, indActive=indAct)
m = np.random.rand(mesh.nC)[indAct]
reg.mref = np.ones_like(m)*np.mean(m)
print 'Check: phi_m (mref) = %f' %reg.eval(reg.mref)
passed = reg.eval(reg.mref) < TOL
self.assertTrue(passed)
print 'Check:', R
passed = Tests.checkDerivative(lambda m : [reg.eval(m), reg.evalDeriv(m)], m, plotIt=False)
self.assertTrue(passed)
print 'Check 2 Deriv:', R
passed = Tests.checkDerivative(lambda m : [reg.evalDeriv(m), reg.eval2Deriv(m)], m, plotIt=False)
self.assertTrue(passed)
if testRegMesh:
def test_regularizationMesh(self):
for i, mesh in enumerate(self.meshlist):
print 'Testing %iD'%mesh.dim
mapping = r.mapPair(mesh)
reg = r(mesh, mapping=mapping)
m = np.random.rand(mapping.nP)
reg.mref = np.ones_like(m)*np.mean(m)
print 'Check: phi_m (mref) = %f' %reg.eval(reg.mref)
passed = reg.eval(reg.mref) < TOL
self.assertTrue(passed)
print 'Check:', R
passed = Tests.checkDerivative(lambda m : [reg.eval(m), reg.evalDeriv(m)], m, plotIt=False)
self.assertTrue(passed)
print 'Check 2 Deriv:', R
passed = Tests.checkDerivative(lambda m : [reg.evalDeriv(m), reg.eval2Deriv(m)], m, plotIt=False)
self.assertTrue(passed)
def test_regularization_ActiveCells(self):
for R in dir(Regularization):
r = getattr(Regularization, R)
if not inspect.isclass(r): continue
if not issubclass(r, Regularization.BaseRegularization):
continue
for i, mesh in enumerate(self.meshlist):
print 'Testing Active Cells %iD'%(mesh.dim)
# mapping = r.mapPair(mesh)
# reg = r(mesh, mapping=mapping)
# m = np.random.rand(mapping.nP)
if mesh.dim == 1:
indAct = Utils.mkvc(mesh.gridCC <= 0.8)
@@ -62,23 +102,9 @@ class RegularizationTests(unittest.TestCase):
elif mesh.dim == 3:
indAct = Utils.mkvc(mesh.gridCC[:,-1] <= 2*np.sin(2*np.pi*mesh.gridCC[:,0])+0.5 * 2*np.sin(2*np.pi*mesh.gridCC[:,1])+0.5)
mapping = Maps.IdentityMap(nP=indAct.nonzero()[0].size)
regmesh = Regularization.RegularizationMesh(mesh, indActive=indAct)
reg = r(mesh, mapping=mapping, indActive=indAct)
m = np.random.rand(mesh.nC)[indAct]
reg.mref = np.ones_like(m)*np.mean(m)
print 'Check: phi_m (mref) = %f' %reg.eval(reg.mref)
passed = reg.eval(reg.mref) < TOL
self.assertTrue(passed)
print 'Check:', R
passed = Tests.checkDerivative(lambda m : [reg.eval(m), reg.evalDeriv(m)], m, plotIt=False)
self.assertTrue(passed)
print 'Check 2 Deriv:', R
passed = Tests.checkDerivative(lambda m : [reg.evalDeriv(m), reg.eval2Deriv(m)], m, plotIt=False)
self.assertTrue(passed)
assert (regmesh.vol == mesh.vol[indAct]).all()
if __name__ == '__main__':
+396
View File
@@ -0,0 +1,396 @@
import numpy as np
import scipy.sparse as sp
import unittest
import matplotlib.pyplot as plt
from SimPEG import *
MESHTYPES = ['uniformTensorMesh']
def getxBCyBC(mesh, alpha, beta, gamma):
# def getxBCyBC(mesh, alpha, beta, gamma):
"""
"""
if mesh.dim == 1: #1D
if (len(alpha) != 2 or len(beta) != 2 or len(gamma) != 2):
raise Exception("Lenght of list, alpha should be 2")
fCCxm,fCCxp = mesh.cellBoundaryInd
nBC = fCCxm.sum()+fCCxp.sum()
h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
xBC_xm = 0.5*a_xm
xBC_xp = 0.5*a_xp/b_xp
yBC_xm = 0.5*(1.-b_xm)
yBC_xp = 0.5*(1.-1./b_xp)
xBC = np.r_[xBC_xm, xBC_xp]
yBC = np.r_[yBC_xm, yBC_xp]
elif mesh.dim == 2: #2D
if (len(alpha) != 4 or len(beta) != 4 or len(gamma) != 4):
raise Exception("Lenght of list, alpha should be 4")
fCCxm,fCCxp,fCCym,fCCyp = mesh.cellBoundaryInd
fxm,fxp,fym,fyp = mesh.faceBoundaryInd
nBC = fCCxm.sum()+fCCxp.sum()+fCCxm.sum()+fCCxp.sum()
h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
h_ym, h_yp = mesh.gridCC[fCCym], mesh.gridCC[fCCyp]
alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
alpha_ym, beta_ym, gamma_ym = alpha[2], beta[2], gamma[2]
alpha_yp, beta_yp, gamma_yp = alpha[3], beta[3], gamma[3]
h_xm, h_xp = mesh.gridCC[fCCxm,0], mesh.gridCC[fCCxp,0]
h_ym, h_yp = mesh.gridCC[fCCym,1], mesh.gridCC[fCCyp,1]
a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
a_ym = gamma_ym/(0.5*alpha_ym-beta_ym/h_ym)
b_ym = (0.5*alpha_ym+beta_ym/h_ym)/(0.5*alpha_ym-beta_ym/h_ym)
a_yp = gamma_yp/(0.5*alpha_yp-beta_yp/h_yp)
b_yp = (0.5*alpha_yp+beta_yp/h_yp)/(0.5*alpha_yp-beta_yp/h_yp)
xBC_xm = 0.5*a_xm
xBC_xp = 0.5*a_xp/b_xp
yBC_xm = 0.5*(1.-b_xm)
yBC_xp = 0.5*(1.-1./b_xp)
xBC_ym = 0.5*a_ym
xBC_yp = 0.5*a_yp/b_yp
yBC_ym = 0.5*(1.-b_ym)
yBC_yp = 0.5*(1.-1./b_yp)
sortindsfx = np.argsort(np.r_[np.arange(mesh.nFx)[fxm], np.arange(mesh.nFx)[fxp]])
sortindsfy = np.argsort(np.r_[np.arange(mesh.nFy)[fym], np.arange(mesh.nFy)[fyp]])
xBC_x = np.r_[xBC_xm, xBC_xp][sortindsfx]
xBC_y = np.r_[xBC_ym, xBC_yp][sortindsfy]
yBC_x = np.r_[yBC_xm, yBC_xp][sortindsfx]
yBC_y = np.r_[yBC_ym, yBC_yp][sortindsfy]
xBC = np.r_[xBC_x, xBC_y]
yBC = np.r_[yBC_x, yBC_y]
elif mesh.dim == 3: #3D
if (len(alpha) != 6 or len(beta) != 6 or len(gamma) != 6):
raise Exception("Lenght of list, alpha should be 6")
fCCxm,fCCxp,fCCym,fCCyp,fCCzm,fCCzp = mesh.cellBoundaryInd
fxm,fxp,fym,fyp,fzm,fzp = mesh.faceBoundaryInd
nBC = fCCxm.sum()+fCCxp.sum()+fCCxm.sum()+fCCxp.sum()
h_xm, h_xp = mesh.gridCC[fCCxm], mesh.gridCC[fCCxp]
h_ym, h_yp = mesh.gridCC[fCCym], mesh.gridCC[fCCyp]
h_zm, h_zp = mesh.gridCC[fCCzm], mesh.gridCC[fCCzp]
alpha_xm, beta_xm, gamma_xm = alpha[0], beta[0], gamma[0]
alpha_xp, beta_xp, gamma_xp = alpha[1], beta[1], gamma[1]
alpha_ym, beta_ym, gamma_ym = alpha[2], beta[2], gamma[2]
alpha_yp, beta_yp, gamma_yp = alpha[3], beta[3], gamma[3]
alpha_zm, beta_zm, gamma_zm = alpha[2], beta[2], gamma[2]
alpha_zp, beta_zp, gamma_zp = alpha[3], beta[3], gamma[3]
h_xm, h_xp = mesh.gridCC[fCCxm,0], mesh.gridCC[fCCxp,0]
h_ym, h_yp = mesh.gridCC[fCCym,1], mesh.gridCC[fCCyp,1]
h_zm, h_zp = mesh.gridCC[fCCzm,2], mesh.gridCC[fCCzp,2]
a_xm = gamma_xm/(0.5*alpha_xm-beta_xm/h_xm)
b_xm = (0.5*alpha_xm+beta_xm/h_xm)/(0.5*alpha_xm-beta_xm/h_xm)
a_xp = gamma_xp/(0.5*alpha_xp-beta_xp/h_xp)
b_xp = (0.5*alpha_xp+beta_xp/h_xp)/(0.5*alpha_xp-beta_xp/h_xp)
a_ym = gamma_ym/(0.5*alpha_ym-beta_ym/h_ym)
b_ym = (0.5*alpha_ym+beta_ym/h_ym)/(0.5*alpha_ym-beta_ym/h_ym)
a_yp = gamma_yp/(0.5*alpha_yp-beta_yp/h_yp)
b_yp = (0.5*alpha_yp+beta_yp/h_yp)/(0.5*alpha_yp-beta_yp/h_yp)
a_zm = gamma_zm/(0.5*alpha_zm-beta_zm/h_zm)
b_zm = (0.5*alpha_zm+beta_zm/h_zm)/(0.5*alpha_zm-beta_zm/h_zm)
a_zp = gamma_zp/(0.5*alpha_zp-beta_zp/h_zp)
b_zp = (0.5*alpha_zp+beta_zp/h_zp)/(0.5*alpha_zp-beta_zp/h_zp)
xBC_xm = 0.5*a_xm
xBC_xp = 0.5*a_xp/b_xp
yBC_xm = 0.5*(1.-b_xm)
yBC_xp = 0.5*(1.-1./b_xp)
xBC_ym = 0.5*a_ym
xBC_yp = 0.5*a_yp/b_yp
yBC_ym = 0.5*(1.-b_ym)
yBC_yp = 0.5*(1.-1./b_yp)
xBC_zm = 0.5*a_zm
xBC_zp = 0.5*a_zp/b_zp
yBC_zm = 0.5*(1.-b_zm)
yBC_zp = 0.5*(1.-1./b_zp)
sortindsfx = np.argsort(np.r_[np.arange(mesh.nFx)[fxm], np.arange(mesh.nFx)[fxp]])
sortindsfy = np.argsort(np.r_[np.arange(mesh.nFy)[fym], np.arange(mesh.nFy)[fyp]])
sortindsfz = np.argsort(np.r_[np.arange(mesh.nFz)[fzm], np.arange(mesh.nFz)[fzp]])
xBC_x = np.r_[xBC_xm, xBC_xp][sortindsfx]
xBC_y = np.r_[xBC_ym, xBC_yp][sortindsfy]
xBC_z = np.r_[xBC_zm, xBC_zp][sortindsfz]
yBC_x = np.r_[yBC_xm, yBC_xp][sortindsfx]
yBC_y = np.r_[yBC_ym, yBC_yp][sortindsfy]
yBC_z = np.r_[yBC_zm, yBC_zp][sortindsfz]
xBC = np.r_[xBC_x, xBC_y, xBC_z]
yBC = np.r_[yBC_x, yBC_y, yBC_z]
return xBC, yBC
class Test1D_InhomogeneousMixed(Tests.OrderTest):
name = "1D - Mixed"
meshTypes = MESHTYPES
meshDimension = 1
expectedOrders = 2
meshSizes = [4, 8, 16, 32]
def getError(self):
#Test function
phi_fun = lambda x: np.cos(np.pi*x)
j_fun = lambda x: np.pi*np.sin(np.pi*x)
phi_deriv = lambda x: -j_fun(x)
q_fun = lambda x: (np.pi**2)*np.cos(np.pi*x)
xc_ana = phi_fun(self.M.gridCC)
q_ana = q_fun(self.M.gridCC)
j_ana = j_fun(self.M.gridFx)
# Get boundary locations
vecN = self.M.vectorNx
vecC = self.M.vectorCCx
# Setup Mixed B.C (alpha, beta, gamma)
alpha_xm, alpha_xp = 1., 1.
beta_xm, beta_xp = 1., 1.
alpha = np.r_[alpha_xm, alpha_xp]
beta = np.r_[beta_xm, beta_xp]
vecN = self.M.vectorNx
vecC = self.M.vectorCCx
phi_bc = phi_fun(vecN[[0,-1]])
phi_deriv_bc = phi_deriv(vecN[[0,-1]])
gamma = alpha*phi_bc + beta*phi_deriv_bc
x_BC, y_BC = getxBCyBC(self.M, alpha, beta, gamma)
sigma = np.ones(self.M.nC)
Mfrho = self.M.getFaceInnerProduct(1./sigma)
MfrhoI = self.M.getFaceInnerProduct(1./sigma, invMat=True)
V = Utils.sdiag(self.M.vol)
Div = V*self.M.faceDiv
P_BC, B = self.M.getBCProjWF_simple()
q = q_fun(self.M.gridCC)
M = B*self.M.aveCC2F
G = Div.T - P_BC*Utils.sdiag(y_BC)*M
# Mrhoj = D.T V phi + P_BC*Utils.sdiag(y_BC)*M phi - P_BC*x_BC
rhs = V*q + Div*MfrhoI*P_BC*x_BC
A = Div*MfrhoI*G
if self.myTest == 'xc':
#TODO: fix the null space
Ainv = Solver(A)
xc = Ainv*rhs
err = np.linalg.norm((xc-xc_ana), np.inf)
else:
NotImplementedError
return err
def test_order(self):
print "==== Testing Mixed boudary conduction for CC-problem ===="
self.name = "1D"
self.myTest = 'xc'
self.orderTest()
class Test2D_InhomogeneousMixed(Tests.OrderTest):
name = "2D - Mixed"
meshTypes = MESHTYPES
meshDimension = 2
expectedOrders = 2
meshSizes = [4, 8, 16, 32]
def getError(self):
#Test function
phi_fun = lambda x: np.cos(np.pi*x[:,0])*np.cos(np.pi*x[:,1])
j_funX = lambda x: +np.pi*np.sin(np.pi*x[:,0])*np.cos(np.pi*x[:,1])
j_funY = lambda x: +np.pi*np.cos(np.pi*x[:,0])*np.sin(np.pi*x[:,1])
phideriv_funX = lambda x: -j_funX(x)
phideriv_funY = lambda x: -j_funY(x)
q_fun = lambda x: +2*(np.pi**2)*phi_fun(x)
xc_ana = phi_fun(self.M.gridCC)
q_ana = q_fun(self.M.gridCC)
jX_ana = j_funX(self.M.gridFx)
jY_ana = j_funY(self.M.gridFy)
j_ana = np.r_[jX_ana,jY_ana]
# Get boundary locations
fxm,fxp,fym,fyp = self.M.faceBoundaryInd
gBFxm = self.M.gridFx[fxm,:]
gBFxp = self.M.gridFx[fxp,:]
gBFym = self.M.gridFy[fym,:]
gBFyp = self.M.gridFy[fyp,:]
# Setup Mixed B.C (alpha, beta, gamma)
alpha_xm, alpha_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
beta_xm, beta_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
alpha_ym, alpha_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
beta_ym, beta_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
phi_bc_xm, phi_bc_xp = phi_fun(gBFxm), phi_fun(gBFxp)
phi_bc_ym, phi_bc_yp = phi_fun(gBFym), phi_fun(gBFyp)
phiderivX_bc_xm, phiderivX_bc_xp = phideriv_funX(gBFxm), phideriv_funX(gBFxp)
phiderivY_bc_ym, phiderivY_bc_yp = phideriv_funY(gBFym), phideriv_funY(gBFyp)
gamma_fun = lambda alpha, beta, phi, phi_deriv: alpha*phi + beta*phi_deriv
gamma_xm = gamma_fun(alpha_xm, beta_xm, phi_bc_xm, phiderivX_bc_xm)
gamma_xp = gamma_fun(alpha_xp, beta_xp, phi_bc_xp, phiderivX_bc_xp)
gamma_ym = gamma_fun(alpha_ym, beta_ym, phi_bc_ym, phiderivY_bc_ym)
gamma_yp = gamma_fun(alpha_yp, beta_yp, phi_bc_yp, phiderivY_bc_yp)
alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp]
beta = [beta_xm, beta_xp, beta_ym, beta_yp]
gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp]
x_BC, y_BC = getxBCyBC(self.M, alpha, beta, gamma)
sigma = np.ones(self.M.nC)
Mfrho = self.M.getFaceInnerProduct(1./sigma)
MfrhoI = self.M.getFaceInnerProduct(1./sigma, invMat=True)
V = Utils.sdiag(self.M.vol)
Div = V*self.M.faceDiv
P_BC, B = self.M.getBCProjWF_simple()
q = q_fun(self.M.gridCC)
M = B*self.M.aveCC2F
G = Div.T - P_BC*Utils.sdiag(y_BC)*M
rhs = V*q + Div*MfrhoI*P_BC*x_BC
A = Div*MfrhoI*G
if self.myTest == 'xc':
Ainv = Solver(A)
xc = Ainv*rhs
err = np.linalg.norm((xc-xc_ana), np.inf)
else:
NotImplementedError
return err
def test_order(self):
print "==== Testing Mixed boudary conduction for CC-problem ===="
self.name = "2D"
self.myTest = 'xc'
self.orderTest()
class Test3D_InhomogeneousMixed(Tests.OrderTest):
name = "3D - Mixed"
meshTypes = MESHTYPES
meshDimension = 3
expectedOrders = 2
meshSizes = [4, 8, 16]
def getError(self):
#Test function
phi_fun = lambda x: np.cos(np.pi*x[:,0])*np.cos(np.pi*x[:,1])*np.cos(np.pi*x[:,2])
j_funX = lambda x: +np.pi*np.sin(np.pi*x[:,0])*np.cos(np.pi*x[:,1])*np.cos(np.pi*x[:,2])
j_funY = lambda x: +np.pi*np.cos(np.pi*x[:,0])*np.sin(np.pi*x[:,1])*np.cos(np.pi*x[:,2])
j_funZ = lambda x: +np.pi*np.cos(np.pi*x[:,0])*np.cos(np.pi*x[:,1])*np.sin(np.pi*x[:,2])
phideriv_funX = lambda x: -j_funX(x)
phideriv_funY = lambda x: -j_funY(x)
phideriv_funZ = lambda x: -j_funZ(x)
q_fun = lambda x: 3*(np.pi**2)*phi_fun(x)
xc_ana = phi_fun(self.M.gridCC)
q_ana = q_fun(self.M.gridCC)
jX_ana = j_funX(self.M.gridFx)
jY_ana = j_funY(self.M.gridFy)
j_ana = np.r_[jX_ana,jY_ana,jY_ana]
# Get boundary locations
fxm,fxp,fym,fyp,fzm,fzp = self.M.faceBoundaryInd
gBFxm = self.M.gridFx[fxm,:]
gBFxp = self.M.gridFx[fxp,:]
gBFym = self.M.gridFy[fym,:]
gBFyp = self.M.gridFy[fyp,:]
gBFzm = self.M.gridFz[fzm,:]
gBFzp = self.M.gridFz[fzp,:]
# Setup Mixed B.C (alpha, beta, gamma)
alpha_xm, alpha_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
beta_xm, beta_xp = np.ones_like(gBFxm[:,0]), np.ones_like(gBFxp[:,0])
alpha_ym, alpha_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
beta_ym, beta_yp = np.ones_like(gBFym[:,1]), np.ones_like(gBFyp[:,1])
alpha_zm, alpha_zp = np.ones_like(gBFzm[:,1]), np.ones_like(gBFzp[:,1])
beta_zm, beta_zp = np.ones_like(gBFzm[:,1]), np.ones_like(gBFzp[:,1])
phi_bc_xm, phi_bc_xp = phi_fun(gBFxm), phi_fun(gBFxp)
phi_bc_ym, phi_bc_yp = phi_fun(gBFym), phi_fun(gBFyp)
phi_bc_zm, phi_bc_zp = phi_fun(gBFzm), phi_fun(gBFzp)
phiderivX_bc_xm, phiderivX_bc_xp = phideriv_funX(gBFxm), phideriv_funX(gBFxp)
phiderivY_bc_ym, phiderivY_bc_yp = phideriv_funY(gBFym), phideriv_funY(gBFyp)
phiderivY_bc_zm, phiderivY_bc_zp = phideriv_funY(gBFzm), phideriv_funY(gBFzp)
gamma_fun = lambda alpha, beta, phi, phi_deriv: alpha*phi + beta*phi_deriv
gamma_xm = gamma_fun(alpha_xm, beta_xm, phi_bc_xm, phiderivX_bc_xm)
gamma_xp = gamma_fun(alpha_xp, beta_xp, phi_bc_xp, phiderivX_bc_xp)
gamma_ym = gamma_fun(alpha_ym, beta_ym, phi_bc_ym, phiderivY_bc_ym)
gamma_yp = gamma_fun(alpha_yp, beta_yp, phi_bc_yp, phiderivY_bc_yp)
gamma_zm = gamma_fun(alpha_zm, beta_zm, phi_bc_zm, phiderivY_bc_zm)
gamma_zp = gamma_fun(alpha_zp, beta_zp, phi_bc_zp, phiderivY_bc_zp)
alpha = [alpha_xm, alpha_xp, alpha_ym, alpha_yp, alpha_zm, alpha_zp]
beta = [beta_xm, beta_xp, beta_ym, beta_yp, beta_zm, beta_zp]
gamma = [gamma_xm, gamma_xp, gamma_ym, gamma_yp, gamma_zm, gamma_zp]
x_BC, y_BC = getxBCyBC(self.M, alpha, beta, gamma)
sigma = np.ones(self.M.nC)
Mfrho = self.M.getFaceInnerProduct(1./sigma)
MfrhoI = self.M.getFaceInnerProduct(1./sigma, invMat=True)
V = Utils.sdiag(self.M.vol)
Div = V*self.M.faceDiv
P_BC, B = self.M.getBCProjWF_simple()
q = q_fun(self.M.gridCC)
M = B*self.M.aveCC2F
G = Div.T - P_BC*Utils.sdiag(y_BC)*M
rhs = V*q + Div*MfrhoI*P_BC*x_BC
A = Div*MfrhoI*G
if self.myTest == 'xc':
#TODO: fix the null space
Ainv = Solver(A)
xc = Ainv*rhs
err = np.linalg.norm((xc-xc_ana), np.inf)
else:
NotImplementedError
return err
def test_order(self):
print "==== Testing Mixed boudary conduction for CC-problem ===="
self.name = "3D"
self.myTest = 'xc'
self.orderTest()
if __name__ == '__main__':
unittest.main()