def setUp(self):

        cs = 25.
        hx = [(cs, 0, -1.3), (cs, 21), (cs, 0, 1.3)]
        hz = [(cs, 0, -1.3), (cs, 20)]
        mesh = Mesh.TensorMesh([hx, hz], x0="CN")
        blkind0 = Utils.ModelBuilder.getIndicesSphere(np.r_[-100., -200.], 75.,
                                                      mesh.gridCC)
        blkind1 = Utils.ModelBuilder.getIndicesSphere(np.r_[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] = 0.1

        x = mesh.vectorCCx[(mesh.vectorCCx > -155.) & (mesh.vectorCCx < 155.)]

        Aloc = np.r_[-200., 0.]
        Bloc = np.r_[200., 0.]
        M = Utils.ndgrid(x - 25., np.r_[0.])
        N = Utils.ndgrid(x + 25., 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.Problem2D_CC(mesh,
                                   rho=1. / sigma,
                                   etaMap=wires.eta,
                                   tauiMap=wires.taui,
                                   verbose=False)
        problem.Solver = Solver
        problem.pair(survey)
        mSynth = np.r_[eta, 1. / tau]
        problem.model = mSynth
        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 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.
        c = np.ones_like(sigma) * 0.5

        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.)
        actmapc = Maps.InjectActiveCells(mesh, ~airind, 1.)

        x = mesh.vectorCCx[(mesh.vectorCCx > -155.) & (mesh.vectorCCx < 155.)]
        y = mesh.vectorCCy[(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', actmapeta.nP), ('taui', actmaptau.nP), ('c', actmapc.nP))
        problem = SIP.Problem3D_N(
            mesh,
            sigma=sigma,
            etaMap=actmapeta*wires.eta,
            tauiMap=actmaptau*wires.taui,
            cMap=actmapc*wires.c,
            actinds=~airind,
            storeJ = True,
            verbose=False
        )

        problem.Solver = Solver
        problem.pair(survey)
        mSynth = np.r_[eta[~airind], 1./tau[~airind], c[~airind]]
        survey.makeSyntheticData(mSynth)
        # Now set up the problem to do some minimization
        dmis = DataMisfit.l2_DataMisfit(survey)
        dmis = DataMisfit.l2_DataMisfit(survey)
        reg_eta = Regularization.Simple(mesh, mapping=wires.eta, indActive=~airind)
        reg_taui = Regularization.Simple(mesh, mapping=wires.taui, indActive=~airind)
        reg_c = Regularization.Simple(mesh, mapping=wires.c, indActive=~airind)
        reg = reg_eta + reg_taui + reg_c
        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