From 9b2eec0ea34c87ef533bc8c33f06c25382f110ff Mon Sep 17 00:00:00 2001 From: seogi_macbook Date: Sun, 1 May 2016 12:33:39 -0700 Subject: [PATCH] Working 2.5D nodal discretization (Jvec and Jtvec) --- SimPEG/EM/Static/DC/ProblemDC_2D.py | 6 ++--- tests/em/static/test_DC_2D_jvecjtvecadj.py | 30 +++++++++++----------- 2 files changed, 18 insertions(+), 18 deletions(-) diff --git a/SimPEG/EM/Static/DC/ProblemDC_2D.py b/SimPEG/EM/Static/DC/ProblemDC_2D.py index 2b5ed305..86f9dc72 100644 --- a/SimPEG/EM/Static/DC/ProblemDC_2D.py +++ b/SimPEG/EM/Static/DC/ProblemDC_2D.py @@ -148,7 +148,7 @@ class Problem2D_CC(BaseDCProblem_2D): _solutionType = 'phiSolution' _formulation = 'HJ' # CC potentials means J is on faces - fieldsPair = Fields_ky_N + fieldsPair = Fields_ky_CC def __init__(self, mesh, **kwargs): BaseDCProblem_2D.__init__(self, mesh, **kwargs) @@ -326,8 +326,8 @@ class Problem2D_N(BaseDCProblem_2D): vol = self.mesh.vol if adjoint: - return Grad.T*(self.MeSigmaDeriv(Grad*u)*v) + ky**2*self.MnSigmaDeriv(u)*v - return self.MeSigmaDeriv(Grad*u).T * (Grad*v) + ky**2*self.MnSigmaDeriv(u)*v + return self.MeSigmaDeriv(Grad*u).T * (Grad*v) + ky**2*self.MnSigmaDeriv(u).T*v + return Grad.T*(self.MeSigmaDeriv(Grad*u)*v) + ky**2*self.MnSigmaDeriv(u)*v def getRHS(self, ky): """ diff --git a/tests/em/static/test_DC_2D_jvecjtvecadj.py b/tests/em/static/test_DC_2D_jvecjtvecadj.py index 0740adc7..9412614e 100644 --- a/tests/em/static/test_DC_2D_jvecjtvecadj.py +++ b/tests/em/static/test_DC_2D_jvecjtvecadj.py @@ -104,24 +104,24 @@ class DCProblemTestsN(unittest.TestCase): def test_misfit(self): derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)] - passed = Tests.checkDerivative(derChk, self.m0, plotIt=False) + passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3) self.assertTrue(passed) - # def test_adjoint(self): - # # Adjoint Test - # u = np.random.rand(self.mesh.nC*self.survey.nSrc) - # v = np.random.rand(self.mesh.nC) - # w = np.random.rand(self.survey.dobs.shape[0]) - # wtJv = w.dot(self.p.Jvec(self.m0, v)) - # vtJtw = v.dot(self.p.Jtvec(self.m0, w)) - # passed = np.abs(wtJv - vtJtw) < 1e-8 - # print 'Adjoint Test', np.abs(wtJv - vtJtw), passed - # self.assertTrue(passed) + def test_adjoint(self): + # Adjoint Test + u = np.random.rand(self.mesh.nC*self.survey.nSrc) + v = np.random.rand(self.mesh.nC) + w = np.random.rand(self.survey.dobs.shape[0]) + wtJv = w.dot(self.p.Jvec(self.m0, v)) + vtJtw = v.dot(self.p.Jtvec(self.m0, w)) + passed = np.abs(wtJv - vtJtw) < 1e-8 + print 'Adjoint Test', np.abs(wtJv - vtJtw), passed + self.assertTrue(passed) - # def test_dataObj(self): - # derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)] - # passed = Tests.checkDerivative(derChk, self.m0, plotIt=False) - # self.assertTrue(passed) + def test_dataObj(self): + derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)] + passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3) + self.assertTrue(passed) if __name__ == '__main__': unittest.main()