def run(plotIt=True, nFreq=1):
"""
MT: 3D: Forward
===============
Forward model 3D MT data.
"""
# Make a mesh
M = simpeg.Mesh.TensorMesh([[(100,5,-1.5),(100.,10),(100,5,1.5)],[(100,5,-1.5),(100.,10),(100,5,1.5)],[(100,5,1.6),(100.,10),(100,3,2)]], x0=['C','C',-3529.5360])
# Setup the model
conds = [1e-2,1]
sig = simpeg.Utils.ModelBuilder.defineBlock(M.gridCC,[-1000,-1000,-400],[1000,1000,-200],conds)
sig[M.gridCC[:,2]>0] = 1e-8
sig[M.gridCC[:,2]<-600] = 1e-1
sigBG = np.zeros(M.nC) + conds[0]
sigBG[M.gridCC[:,2]>0] = 1e-8
## Setup the the survey object
# Receiver locations
rx_x, rx_y = np.meshgrid(np.arange(-500,501,50),np.arange(-500,501,50))
rx_loc = np.hstack((simpeg.Utils.mkvc(rx_x,2),simpeg.Utils.mkvc(rx_y,2),np.zeros((np.prod(rx_x.shape),1))))
# Make a receiver list
rxList = []
for loc in rx_loc:
# NOTE: loc has to be a (1,3) np.ndarray otherwise errors accure
for rx_orientation in ['xx','xy','yx','yy']:
rxList.append(NSEM.Rx.Point_impedance3D(simpeg.mkvc(loc,2).T,rx_orientation, 'real'))
rxList.append(NSEM.Rx.Point_impedance3D(simpeg.mkvc(loc,2).T,rx_orientation, 'imag'))
for rx_orientation in ['zx','zy']:
rxList.append(NSEM.Rx.Point_tipper3D(simpeg.mkvc(loc,2).T,rx_orientation, 'real'))
rxList.append(NSEM.Rx.Point_tipper3D(simpeg.mkvc(loc,2).T,rx_orientation, 'imag'))
# Source list
srcList =[]
for freq in np.logspace(3,-3,nFreq):
srcList.append(NSEM.Src.Planewave_xy_1Dprimary(rxList,freq))
# Survey MT
survey = NSEM.Survey(srcList)
## Setup the problem object
problem = NSEM.Problem3D_ePrimSec(M, sigmaPrimary=sigBG)
problem.pair(survey)
problem.Solver = Solver
# Calculate the data
fields = problem.fields(sig)
dataVec = survey.eval(fields)
# Make the data
mtData = NSEM.Data(survey,dataVec)
# Add plots
if plotIt:
pass
def setUp(self):
cs = 25.
hx = [(cs, 0, -1.3), (cs, 21), (cs, 0, 1.3)]
hy = [(cs, 0, -1.3), (cs, 21), (cs, 0, 1.3)]
hz = [(cs, 0, -1.3), (cs, 20)]
mesh = Mesh.TensorMesh([hx, hy, hz], x0="CCN")
blkind0 = Utils.ModelBuilder.getIndicesSphere(
np.r_[-100., -100., -200.], 75., mesh.gridCC
)
blkind1 = Utils.ModelBuilder.getIndicesSphere(
np.r_[100., 100., -200.], 75., mesh.gridCC
)
sigma = np.ones(mesh.nC)*1e-2
eta = np.zeros(mesh.nC)
tau = np.ones_like(sigma)*1.
eta[blkind0] = 0.1
eta[blkind1] = 0.1
tau[blkind0] = 0.1
tau[blkind1] = 0.01
x = mesh.vectorCCx[(mesh.vectorCCx > -155.) & (mesh.vectorCCx < 155.)]
y = mesh.vectorCCx[(mesh.vectorCCy > -155.) & (mesh.vectorCCy < 155.)]
Aloc = np.r_[-200., 0., 0.]
Bloc = np.r_[200., 0., 0.]
M = Utils.ndgrid(x-25., y, np.r_[0.])
N = Utils.ndgrid(x+25., y, np.r_[0.])
times = np.arange(10)*1e-3 + 1e-3
rx = SIP.Rx.Dipole(M, N, times)
src = SIP.Src.Dipole([rx], Aloc, Bloc)
survey = SIP.Survey([src])
wires = Maps.Wires(('eta', mesh.nC), ('taui', mesh.nC))
problem = SIP.Problem3D_N(
mesh,
sigma=sigma,
etaMap=wires.eta,
tauiMap=wires.taui
)
problem.Solver = Solver
problem.pair(survey)
mSynth = np.r_[eta, 1./tau]
survey.makeSyntheticData(mSynth)
# Now set up the problem to do some minimization
dmis = DataMisfit.l2_DataMisfit(survey)
reg = Regularization.Tikhonov(mesh)
opt = Optimization.InexactGaussNewton(
maxIterLS=20, maxIter=10, tolF=1e-6,
tolX=1e-6, tolG=1e-6, maxIterCG=6
)
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
inv = Inversion.BaseInversion(invProb)
self.inv = inv
self.reg = reg
self.p = problem
self.mesh = mesh
self.m0 = mSynth
self.survey = survey
self.dmis = dmis
def setUp(self):
cs = 25.
hx = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
hy = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
hz = [(cs,0, -1.3),(cs,20),(cs,0, 1.3)]
mesh = Mesh.TensorMesh([hx, hy, hz],x0="CCC")
blkind0 = Utils.ModelBuilder.getIndicesSphere(np.r_[-100., -100., -200.], 75., mesh.gridCC)
blkind1 = Utils.ModelBuilder.getIndicesSphere(np.r_[100., 100., -200.], 75., mesh.gridCC)
sigma = np.ones(mesh.nC)*1e-2
airind = mesh.gridCC[:,2]>0.
sigma[airind] = 1e-8
eta = np.zeros(mesh.nC)
tau = np.ones_like(sigma)*1.
eta[blkind0] = 0.1
eta[blkind1] = 0.1
tau[blkind0] = 0.1
tau[blkind1] = 0.01
actmapeta = Maps.InjectActiveCells(mesh, ~airind, 0.)
actmaptau = Maps.InjectActiveCells(mesh, ~airind, 1.)
x = mesh.vectorCCx[(mesh.vectorCCx>-155.)&(mesh.vectorCCx<155.)]
y = mesh.vectorCCx[(mesh.vectorCCy>-155.)&(mesh.vectorCCy<155.)]
Aloc = np.r_[-200., 0., 0.]
Bloc = np.r_[200., 0., 0.]
M = Utils.ndgrid(x-25.,y, np.r_[0.])
N = Utils.ndgrid(x+25.,y, np.r_[0.])
times = np.arange(10)*1e-3 + 1e-3
rx = SIP.Rx.Dipole(M, N, times)
src = SIP.Src.Dipole([rx], Aloc, Bloc)
survey = SIP.Survey([src])
colemap = [("eta", Maps.IdentityMap(mesh)*actmapeta), ("taui", Maps.IdentityMap(mesh)*actmaptau)]
problem = SIP.Problem3D_N(mesh, sigma=sigma, mapping=colemap)
problem.Solver = Solver
problem.pair(survey)
mSynth = np.r_[eta[~airind], 1./tau[~airind]]
survey.makeSyntheticData(mSynth)
# Now set up the problem to do some minimization
dmis = DataMisfit.l2_DataMisfit(survey)
regmap = Maps.IdentityMap(nP=int(mSynth[~airind].size*2))
reg = SIP.MultiRegularization(mesh, mapping=regmap, nModels=2, indActive=~airind)
opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
inv = Inversion.BaseInversion(invProb)
self.inv = inv
self.reg = reg
self.p = problem
self.mesh = mesh
self.m0 = mSynth
self.survey = survey
self.dmis = dmis
def activeCells(self):
if getattr(self, '_activeCells', None) is None:
if self.topofile == 'null':
self._activeCells = np.arange(mesh.nC)
else:
topo = np.genfromtxt(self.basePath + self.topofile, skip_header=1)
# Find the active cells
active = Utils.surface2ind_topo(self.mesh,topo,'N')
inds = np.asarray([inds for inds, elem in enumerate(active, 1) if elem], dtype = int) - 1
self._activeCells = inds
return self._activeCells
def gocad2simpegMeshIndex(gcFile,mesh,extractBoundaryCells=True,extractInside=True):
""""
Function to read gocad polystructure file and output indexes of mesh with in the structure.
"""
# Make the polydata
polyData = gocad2vtp(gcFile)
# Make implicit func
ImpDistFunc = vtk.vtkImplicitPolyDataDistance()
ImpDistFunc.SetInput(polyData)
# Convert the mesh
vtkMesh = vtk.vtkRectilinearGrid()
vtkMesh.SetDimensions(mesh.nNx,mesh.nNy,mesh.nNz)
vtkMesh.SetXCoordinates(npsup.numpy_to_vtk(mesh.vectorNx,deep=1))
vtkMesh.SetYCoordinates(npsup.numpy_to_vtk(mesh.vectorNy,deep=1))
vtkMesh.SetZCoordinates(npsup.numpy_to_vtk(mesh.vectorNz,deep=1))
# Add indexes cell data to the object
vtkInd = npsup.numpy_to_vtk(np.arange(mesh.nC),deep=1)
vtkInd.SetName('Index')
vtkMesh.GetCellData().AddArray(vtkInd)
# Define the extractGeometry
extractImpDistRectGridFilt = vtk.vtkExtractGeometry() # Object constructor
extractImpDistRectGridFilt.SetImplicitFunction(ImpDistFunc) #
extractImpDistRectGridFilt.SetInputData(vtkMesh)
# Set extraction type
if extractBoundaryCells is True:
extractImpDistRectGridFilt.ExtractBoundaryCellsOn()
else:
extractImpDistRectGridFilt.ExtractBoundaryCellsOff()
if extractInside is True:
extractImpDistRectGridFilt.ExtractInsideOn()
else:
extractImpDistRectGridFilt.ExtractInsideOff()
print "Extracting indices from grid..."
# Executing the pipe
extractImpDistRectGridFilt.Update()
# Get index inside
insideGrid = extractImpDistRectGridFilt.GetOutput()
insideGrid = npsup.vtk_to_numpy(insideGrid.GetCellData().GetArray('Index'))
# Return the indexes inside
return insideGrid
def setUp(self):
cs = 25.
hx = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
hy = [(cs,0, -1.3),(cs,21),(cs,0, 1.3)]
hz = [(cs,0, -1.3),(cs,20)]
mesh = Mesh.TensorMesh([hx, hy, hz],x0="CCN")
blkind0 = Utils.ModelBuilder.getIndicesSphere(np.r_[-100., -100., -200.], 75., mesh.gridCC)
blkind1 = Utils.ModelBuilder.getIndicesSphere(np.r_[100., 100., -200.], 75., mesh.gridCC)
sigma = np.ones(mesh.nC)*1e-2
eta = np.zeros(mesh.nC)
tau = np.ones_like(sigma)*1.
eta[blkind0] = 0.1
eta[blkind1] = 0.1
tau[blkind0] = 0.1
tau[blkind1] = 0.01
x = mesh.vectorCCx[(mesh.vectorCCx>-155.)&(mesh.vectorCCx<155.)]
y = mesh.vectorCCx[(mesh.vectorCCy>-155.)&(mesh.vectorCCy<155.)]
Aloc = np.r_[-200., 0., 0.]
Bloc = np.r_[200., 0., 0.]
M = Utils.ndgrid(x-25.,y, np.r_[0.])
N = Utils.ndgrid(x+25.,y, np.r_[0.])
times = np.arange(10)*1e-3 + 1e-3
rx = SIP.Rx.Dipole(M, N, times)
src = SIP.Src.Dipole([rx], Aloc, Bloc)
survey = SIP.Survey([src])
colemap = [("eta", Maps.IdentityMap(mesh)), ("taui", Maps.IdentityMap(mesh))]
problem = SIP.Problem3D_CC(mesh, rho=1./sigma, mapping=colemap)
problem.Solver = MumpsSolver
problem.pair(survey)
mSynth = np.r_[eta, 1./tau]
survey.makeSyntheticData(mSynth)
# Now set up the problem to do some minimization
dmis = DataMisfit.l2_DataMisfit(survey)
reg = Regularization.Tikhonov(mesh)
opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
inv = Inversion.BaseInversion(invProb)
self.inv = inv
self.reg = reg
self.p = problem
self.mesh = mesh
self.m0 = mSynth
self.survey = survey
self.dmis = dmis
def setFrequency(self, time=np.logspace(-7, -1, 256)):
self.Nch = self.time.size
wt = np.array([7.214369775966785e-20, 5.997984537445829e-20, 1.383536819510307e-20, 6.127201193993877e-20, 2.735622069700930e-20, 6.567948836420383e-20, 4.144963335850363e-20, 7.316414067200350e-20, 5.682375914662966e-20, 8.391977074915078e-20, 7.418756524583309e-20, 9.829637687190485e-20, 9.430643800653847e-20, 1.168146262188112e-19, 1.180370735968097e-19, 1.401723019040171e-19, 1.463726071463266e-19, 1.692722072070252e-19, 1.804796158499069e-19, 2.052560499147526e-19, 2.217507732438609e-19, 2.495469564846162e-19, 2.718603842873614e-19, 3.039069705922034e-19, 3.328334008394297e-19, 3.705052796297763e-19, 4.071277819975917e-19, 4.520053409594589e-19, 4.977334107366132e-19, 5.516707191291291e-19, 6.082931168675559e-19, 6.734956703766505e-19, 7.432489554623685e-19, 8.223651399147256e-19, 9.080210233648037e-19, 1.004250388267800e-18, 1.109225156214032e-18, 1.226448534750949e-18, 1.354938655056596e-18, 1.497875155579711e-18, 1.655024636692164e-18, 1.829422009902478e-18, 2.021527957180686e-18, 2.234394042862191e-18, 2.469158736824458e-18, 2.729043278909879e-18, 3.015882778812807e-18, 3.333221019045560e-18, 3.683642665131121e-18, 4.071174485366807e-18, 4.499238428427072e-18, 4.972519918024098e-18, 5.495403162992602e-18, 6.073431145514256e-18, 6.712116746365455e-18, 7.418091347704607e-18, 8.198210388921290e-18, 9.060466264497684e-18, 1.001332641867938e-17, 1.106647001686341e-17, 1.223031194783507e-17, 1.351661046246575e-17, 1.493814249254853e-17, 1.650922025025269e-17, 1.824549287949245e-17, 2.016440324953847e-17, 2.228509875325462e-17, 2.462885473506622e-17, 2.721908372832262e-17, 3.008174877960754e-17, 3.324546598231868e-17, 3.674192913569353e-17, 4.060610542324258e-17, 4.487669220181069e-17, 4.959641037849226e-17, 5.481251456381401e-17, 6.057719336989671e-17, 6.694815564512041e-17, 7.398915178848498e-17, 8.177066132132114e-17, 9.037055462918574e-17, 9.987491078055815e-17, 1.103788451159722e-16, 1.219874911140742e-16, 1.348170262066998e-16, 1.489958578076007e-16, 1.646658879212839e-16, 1.819839514458913e-16, 2.011233698894207e-16, 2.222757000537238e-16, 2.456526388749016e-16, 2.714881529754608e-16, 3.000408107960083e-16, 3.315963787425073e-16, 3.664706739627943e-16, 4.050127315080793e-16, 4.476082920363670e-16, 4.946836672898304e-16, 5.467100025245505e-16, 6.042079955957903e-16, 6.677531050397348e-16, 7.379813122861424e-16, 8.155954842977402e-16, 9.013724102689123e-16, 9.961705740887021e-16, 1.100938748010566e-15, 1.216725486808607e-15, 1.344689623369201e-15, 1.486111865526057e-15, 1.642407614840039e-15, 1.815141131499014e-15, 2.006041190779248e-15, 2.217018384471440e-15, 2.450184243392977e-15, 2.707872369692257e-15, 2.992661792874233e-15, 3.307402781094011e-15, 3.655245368051253e-15, 4.039670879180488e-15, 4.464526774284602e-15, 4.934065153895433e-15, 5.452985315986473e-15, 6.026480787914038e-15, 6.660291305149181e-15, 7.360760256360466e-15, 8.134898170257041e-15, 8.990452879276204e-15, 9.935987062502841e-15, 1.098096394385775e-14, 1.213584200318437e-14, 1.341217964828528e-14, 1.482275089528562e-14, 1.638167321535499e-14, 1.810454882702344e-14, 2.000862084851265e-14, 2.211294587257239e-14, 2.443858469135401e-14, 2.700881307980678e-14, 2.984935474755050e-14, 3.298863879030854e-14, 3.645808421795958e-14, 4.029241440643229e-14, 4.453000462105175e-14, 4.921326608894885e-14, 5.438907046503769e-14, 6.010921893911273e-14, 6.643096067976429e-14, 7.341756580308676e-14, 8.113895860149252e-14, 8.967241736929777e-14, 9.910334783010448e-14, 1.095261379057530e-13, 1.210451023825933e-13, 1.337755269287210e-13, 1.478448219118764e-13, 1.633937975650728e-13, 1.805780732628623e-13, 1.995696350122467e-13, 2.205585567465074e-13, 2.437549026489779e-13, 2.693908295460095e-13, 2.977229104105259e-13, 3.290347022305518e-13, 3.636395839428896e-13, 4.018838928348062e-13, 4.441503908040617e-13, 4.908620951685787e-13, 5.424865123659980e-13, 5.995403169151822e-13, 6.625945224685207e-13, 7.322801967084261e-13, 8.092947772848716e-13, 8.944090520057436e-13, 9.884748731403624e-13, 1.092433683043238e-12, 1.207325936425662e-12, 1.334301513576084e-12, 1.474631228748613e-12, 1.629719548899119e-12, 1.801118650062676e-12, 1.990543952052933e-12, 2.199891286960273e-12, 2.431255873276498e-12, 2.686953285545802e-12, 2.969542629413028e-12, 3.281852154013172e-12, 3.627007558039277e-12, 4.008463272785582e-12, 4.430037035256956e-12, 4.895948097364050e-12, 5.410859453614547e-12, 5.979924509929487e-12, 6.608838660661838e-12, 7.303896290017477e-12, 8.072053768367932e-12, 8.920999073943177e-12, 9.859228736701785e-12, 1.089613287445852e-11, 1.204208917233957e-11, 1.330856674614333e-11, 1.470824092910627e-11, 1.625512013089818e-11, 1.796468603849469e-11, 1.985404856210394e-11, 2.194211707689892e-11, 2.424978967439970e-11, 2.680016231759770e-11, 2.961875999311579e-11, 3.273379217385409e-11, 3.617643514887572e-11, 3.998114404618718e-11, 4.418599767123930e-11, 4.883307961241208e-11, 5.396889942771051e-11, 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ab = 0.7866057737580476e0
#------- Compute Frequency components reqired for transform -------#
# This is for Digital filtering and here we evalute frequency domain responses
# ritght at this bases.
# a. Generate time base
n = np.ceil(-10*np.log(time.min()/time.max()))
tbase = time.max()*np.exp(-0.1*np.arange(0, n+1))
self.wt = wt
self.ab = ab
self.n = n
self.tbase = tbase
# b. Determine required frequencies
omega_int = (ab/tbase[0])*np.exp(0.1*(np.r_[1:786+tbase.size:(786+tbase.size)*1j]-425))
# Case1: Compute frequency domain reponses right at filter coefficient values
if self.switchInterp == False:
self.frequency = omega_int/(2*np.pi)
self.Nfreq = self.frequency.size
# Case2: Compute frequency domain reponses in logarithmic then intepolate
elif self.switchInterp == True:
# This is tested decision: works well 1e-4-1e0 S/m
self.frequency = np.logspace(-3, 8, 81)
self.omega_int = omega_int
self.Nfreq = self.frequency.size
else:
raise Exception('Not implemented!!')
if self.offset is not None and np.isscalar(self.offset):
self.offset = self.offset*np.ones(self.Nfreq)
elif self.offset is not None and not np.isscalar(self.offset):
self.offset = self.offset[0]*np.ones(self.Nfreq)
def dynamicCells(self):
if getattr(self, '_dynamicCells', None) is None:
if getattr(self, '_staticInput', None) is None:
# All cells are dynamic: 1's
self._dynamicCells = np.arange(len(self.m0))
# Cells with specific value are static: 0's
else:
if isinstance(self._staticInput, float):
dynamicCells = self.m0 != self._staticInput
else:
# Read from file active cells with 0:air, 1:dynamic, -1 static
dynamicCells = Mesh.TensorMesh.readModelUBC(self.mesh, self.basePath + self._staticInput)
dynamicCells = dynamicCells[self.activeCells] == 1
inds = np.asarray([inds for inds, elem in enumerate(dynamicCells, 1) if elem], dtype = int) - 1
self._dynamicCells = inds
return self._dynamicCells
def gocad2vtk(gcFile,mesh,bcflag,inflag):
""""
Function to read gocad polystructure file and output indexes of mesh with in the structure.
"""
print "Reading GOCAD ts file..."
vrtx, trgl = read_GOCAD_ts(gcFile)
# Adjust the index
trgl = trgl - 1
# Make vtk pts
ptsvtk = vtk.vtkPoints()
ptsvtk.SetData(npsup.numpy_to_vtk(vrtx,deep=1))
# Make the polygon connection
polys = vtk.vtkCellArray()
for face in trgl:
poly = vtk.vtkPolygon()
poly.GetPointIds().SetNumberOfIds(len(face))
for nrv, vert in enumerate(face):
poly.GetPointIds().SetId(nrv,vert)
polys.InsertNextCell(poly)
# Make the polydata, structure of connections and vrtx
polyData = vtk.vtkPolyData()
polyData.SetPoints(ptsvtk)
polyData.SetPolys(polys)
# Make implicit func
ImpDistFunc = vtk.vtkImplicitPolyDataDistance()
ImpDistFunc.SetInput(polyData)
# Convert the mesh
vtkMesh = vtk.vtkRectilinearGrid()
vtkMesh.SetDimensions(mesh.nNx,mesh.nNy,mesh.nNz)
vtkMesh.SetXCoordinates(npsup.numpy_to_vtk(mesh.vectorNx,deep=1))
vtkMesh.SetYCoordinates(npsup.numpy_to_vtk(mesh.vectorNy,deep=1))
vtkMesh.SetZCoordinates(npsup.numpy_to_vtk(mesh.vectorNz,deep=1))
# Add indexes
vtkInd = npsup.numpy_to_vtk(np.arange(mesh.nC),deep=1)
vtkInd.SetName('Index')
vtkMesh.GetCellData().AddArray(vtkInd)
extractImpDistRectGridFilt = vtk.vtkExtractGeometry() # Object constructor
extractImpDistRectGridFilt.SetImplicitFunction(ImpDistFunc) #
extractImpDistRectGridFilt.SetInputData(vtkMesh)
if bcflag is True:
extractImpDistRectGridFilt.ExtractBoundaryCellsOn()
else:
extractImpDistRectGridFilt.ExtractBoundaryCellsOff()
if inflag is True:
extractImpDistRectGridFilt.ExtractInsideOn()
else:
extractImpDistRectGridFilt.ExtractInsideOff()
print "Extracting indices from grid..."
# Executing the pipe
extractImpDistRectGridFilt.Update()
# Get index inside
insideGrid = extractImpDistRectGridFilt.GetOutput()
insideGrid = npsup.vtk_to_numpy(insideGrid.GetCellData().GetArray('Index'))
# Return the indexes inside
return insideGrid
def surface2inds(vrtx, trgl, mesh, boundaries=True, internal=True):
""""
Function to read gocad polystructure file and output indexes of
mesh with in the structure.
"""
# Adjust the index
trgl = trgl - 1
# Make vtk pts
ptsvtk = vtk.vtkPoints()
ptsvtk.SetData(npsup.numpy_to_vtk(vrtx, deep=1))
# Make the polygon connection
polys = vtk.vtkCellArray()
for face in trgl:
poly = vtk.vtkPolygon()
poly.GetPointIds().SetNumberOfIds(len(face))
for nrv, vert in enumerate(face):
poly.GetPointIds().SetId(nrv, vert)
polys.InsertNextCell(poly)
# Make the polydata, structure of connections and vrtx
polyData = vtk.vtkPolyData()
polyData.SetPoints(ptsvtk)
polyData.SetPolys(polys)
# Make implicit func
ImpDistFunc = vtk.vtkImplicitPolyDataDistance()
ImpDistFunc.SetInput(polyData)
# Convert the mesh
vtkMesh = vtk.vtkRectilinearGrid()
vtkMesh.SetDimensions(mesh.nNx, mesh.nNy, mesh.nNz)
vtkMesh.SetXCoordinates(npsup.numpy_to_vtk(mesh.vectorNx, deep=1))
vtkMesh.SetYCoordinates(npsup.numpy_to_vtk(mesh.vectorNy, deep=1))
vtkMesh.SetZCoordinates(npsup.numpy_to_vtk(mesh.vectorNz, deep=1))
# Add indexes
vtkInd = npsup.numpy_to_vtk(np.arange(mesh.nC), deep=1)
vtkInd.SetName('Index')
vtkMesh.GetCellData().AddArray(vtkInd)
extractImpDistRectGridFilt = vtk.vtkExtractGeometry() # Object constructor
extractImpDistRectGridFilt.SetImplicitFunction(ImpDistFunc) #
extractImpDistRectGridFilt.SetInputData(vtkMesh)
if boundaries is True:
extractImpDistRectGridFilt.ExtractBoundaryCellsOn()
else:
extractImpDistRectGridFilt.ExtractBoundaryCellsOff()
if internal is True:
extractImpDistRectGridFilt.ExtractInsideOn()
else:
extractImpDistRectGridFilt.ExtractInsideOff()
print "Extracting indices from grid..."
# Executing the pipe
extractImpDistRectGridFilt.Update()
# Get index inside
insideGrid = extractImpDistRectGridFilt.GetOutput()
insideGrid = npsup.vtk_to_numpy(insideGrid.GetCellData().GetArray('Index'))
# Return the indexes inside
return insideGrid
