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seogi_macbook
f944f9b76b
2. Add Analytic tests 3. Fix simple bug in PlotSlice for nodal variable 4. Add more analytic function (sphere)
128 lines
4.2 KiB
Python
128 lines
4.2 KiB
Python
import unittest
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from SimPEG import *
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import SimPEG.EM.Static.DC as DC
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class DCProblemTestsCC(unittest.TestCase):
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def setUp(self):
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aSpacing=2.5
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nElecs=5
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surveySize = nElecs*aSpacing - aSpacing
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cs = surveySize/nElecs/4
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mesh = Mesh.TensorMesh([
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[(cs,10, -1.3),(cs,surveySize/cs),(cs,10, 1.3)],
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[(cs,3, -1.3),(cs,3,1.3)],
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# [(cs,5, -1.3),(cs,10)]
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],'CN')
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srcList = DC.Utils.WennerSrcList(nElecs, aSpacing, in2D=True)
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survey = DC.Survey(srcList)
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problem = DC.Problem3D_CC(mesh, mapping=[('rho', Maps.IdentityMap(mesh))])
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problem.pair(survey)
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mSynth = np.ones(mesh.nC)
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survey.makeSyntheticData(mSynth)
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# Now set up the problem to do some minimization
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dmis = DataMisfit.l2_DataMisfit(survey)
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reg = Regularization.Tikhonov(mesh)
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opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
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invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
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inv = Inversion.BaseInversion(invProb)
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self.inv = inv
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self.reg = reg
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self.p = problem
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self.mesh = mesh
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self.m0 = mSynth
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self.survey = survey
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self.dmis = dmis
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def test_misfit(self):
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derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
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passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
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self.assertTrue(passed)
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def test_adjoint(self):
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# Adjoint Test
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u = np.random.rand(self.mesh.nC*self.survey.nSrc)
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v = np.random.rand(self.mesh.nC)
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w = np.random.rand(self.survey.dobs.shape[0])
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wtJv = w.dot(self.p.Jvec(self.m0, v))
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vtJtw = v.dot(self.p.Jtvec(self.m0, w))
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passed = np.abs(wtJv - vtJtw) < 1e-10
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print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
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self.assertTrue(passed)
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def test_dataObj(self):
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derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
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passed = Tests.checkDerivative(derChk, self.m0, plotIt=False, num=3)
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self.assertTrue(passed)
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class DCProblemTestsN(unittest.TestCase):
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def setUp(self):
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aSpacing=2.5
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nElecs=10
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surveySize = nElecs*aSpacing - aSpacing
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cs = surveySize/nElecs/4
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mesh = Mesh.TensorMesh([
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[(cs,10, -1.3),(cs,surveySize/cs),(cs,10, 1.3)],
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[(cs,3, -1.3),(cs,3,1.3)],
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# [(cs,5, -1.3),(cs,10)]
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],'CN')
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srcList = DC.Utils.WennerSrcList(nElecs, aSpacing, in2D=True)
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survey = DC.Survey(srcList)
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problem = DC.Problem3D_N(mesh, mapping=[('rho', Maps.IdentityMap(mesh))])
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problem.pair(survey)
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mSynth = np.ones(mesh.nC)
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survey.makeSyntheticData(mSynth)
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# Now set up the problem to do some minimization
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dmis = DataMisfit.l2_DataMisfit(survey)
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reg = Regularization.Tikhonov(mesh)
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opt = Optimization.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
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invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta=1e4)
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inv = Inversion.BaseInversion(invProb)
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self.inv = inv
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self.reg = reg
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self.p = problem
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self.mesh = mesh
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self.m0 = mSynth
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self.survey = survey
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self.dmis = dmis
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def test_misfit(self):
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derChk = lambda m: [self.survey.dpred(m), lambda mx: self.p.Jvec(self.m0, mx)]
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passed = Tests.checkDerivative(derChk, self.m0, plotIt=False)
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self.assertTrue(passed)
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def test_adjoint(self):
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# Adjoint Test
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u = np.random.rand(self.mesh.nC*self.survey.nSrc)
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v = np.random.rand(self.mesh.nC)
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w = np.random.rand(self.survey.dobs.shape[0])
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wtJv = w.dot(self.p.Jvec(self.m0, v))
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vtJtw = v.dot(self.p.Jtvec(self.m0, w))
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passed = np.abs(wtJv - vtJtw) < 1e-8
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print 'Adjoint Test', np.abs(wtJv - vtJtw), passed
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self.assertTrue(passed)
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def test_dataObj(self):
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derChk = lambda m: [self.dmis.eval(m), self.dmis.evalDeriv(m)]
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passed = Tests.checkDerivative(derChk, self.m0, plotIt=False)
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self.assertTrue(passed)
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if __name__ == '__main__':
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unittest.main()
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