mirror of
https://github.com/wassname/simpeg.git
synced 2026-06-27 19:48:52 +08:00
switch coverage and delete old tests.
This commit is contained in:
Rowan Cockett
+1
-1
@@ -18,7 +18,7 @@ env:
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- TEST_DIR="tests/mesh tests/base tests/utils"
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- TEST_DIR=tests/em/fdem/inverse/derivs
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- TEST_DIR=tests/em/tdem
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- TEST_DIR=tests/dcip
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- TEST_DIR=tests/em/static
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- TEST_DIR=tests/flow
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- TEST_DIR=tests/mt
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- TEST_DIR=tests/examples
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@@ -1,12 +0,0 @@
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import os
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import glob
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import unittest
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if __name__ == '__main__':
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test_file_strings = glob.glob('test_*.py')
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module_strings = [str[0:len(str)-3] for str in test_file_strings]
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suites = [unittest.defaultTestLoader.loadTestsFromName(str) for str
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in module_strings]
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testSuite = unittest.TestSuite(suites)
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unittest.TextTestRunner(verbosity=2).run(testSuite)
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@@ -1,77 +0,0 @@
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import unittest
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from SimPEG import *
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import SimPEG.DCIP as DC
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class DCProblemTests(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.SurveyDC(srcList)
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problem = DC.ProblemDC_CC(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-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)
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self.assertTrue(passed)
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def test_massMatrices(self):
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Gu = np.random.rand(self.mesh.nF)
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def derChk(m):
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self.p.curModel = m
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return [self.p.Msig * Gu, self.p.dMdsig(Gu)]
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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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@@ -1,65 +0,0 @@
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import unittest
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import SimPEG.DCIP as DC
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from SimPEG import *
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class IPforwardTests(unittest.TestCase):
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def test_IPforward(self):
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cs = 12.5
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nc = 200/cs+1
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hx = [(cs,7, -1.3),(cs,nc),(cs,7, 1.3)]
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hy = [(cs,7, -1.3),(cs,int(nc/2+1)),(cs,7, 1.3)]
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hz = [(cs,7, -1.3),(cs,int(nc/2+1))]
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mesh = Mesh.TensorMesh([hx, hy, hz], 'CCN')
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sighalf = 1e-2
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sigma = np.ones(mesh.nC)*sighalf
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p0 = np.r_[-50., 50., -50.]
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p1 = np.r_[ 50.,-50., -150.]
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blk_ind = Utils.ModelBuilder.getIndicesBlock(p0, p1, mesh.gridCC)
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sigma[blk_ind] = 1e-3
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eta = np.zeros_like(sigma)
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eta[blk_ind] = 0.1
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sigmaInf = sigma.copy()
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sigma0 = sigma*(1-eta)
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nElecs = 11
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x_temp = np.linspace(-100, 100, nElecs)
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aSpacing = x_temp[1]-x_temp[0]
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y_temp = 0.
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xyz = Utils.ndgrid(x_temp, np.r_[y_temp], np.r_[0.])
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srcList = DC.Utils.WennerSrcList(nElecs,aSpacing)
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survey = DC.SurveyDC(srcList)
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imap = Maps.IdentityMap(mesh)
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problem = DC.ProblemDC_CC(mesh, mapping=imap)
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try:
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from pymatsolver import MumpsSolver
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solver = MumpsSolver
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except ImportError, e:
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solver = SolverLU
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problem.Solver = solver
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problem.pair(survey)
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phi0 = survey.dpred(sigma0)
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phiInf = survey.dpred(sigmaInf)
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phiIP_true = phi0-phiInf
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surveyIP = DC.SurveyIP(srcList)
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problemIP = DC.ProblemIP(mesh, sigma=sigma)
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problemIP.pair(surveyIP)
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problemIP.Solver = solver
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phiIP_approx = surveyIP.dpred(eta)
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err = np.linalg.norm(phiIP_true-phiIP_approx) / np.linalg.norm(phiIP_true)
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self.assertTrue(err < 0.02)
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if __name__ == '__main__':
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unittest.main()
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@@ -1,82 +0,0 @@
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import unittest
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from SimPEG import *
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import SimPEG.DCIP as DC
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class IPProblemTests(unittest.TestCase):
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def setUp(self):
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cs = 12.5
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nc = 500/cs+1
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hx = [(cs,0, -1.3),(cs,nc),(cs,0, 1.3)]
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hy = [(cs,0, -1.3),(cs,int(nc/2+1)),(cs,0, 1.3)]
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hz = [(cs,0, -1.3),(cs,int(nc/2+1))]
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mesh = Mesh.TensorMesh([hx, hy, hz], 'CCN')
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sighalf = 1e-2
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sigma = np.ones(mesh.nC)*sighalf
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p0 = np.r_[-50., 50., -50.]
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p1 = np.r_[ 50.,-50., -150.]
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blk_ind = Utils.ModelBuilder.getIndicesBlock(p0, p1, mesh.gridCC)
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sigma[blk_ind] = 1e-3
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eta = np.zeros_like(sigma)
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eta[blk_ind] = 0.1
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nElecs = 5
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x_temp = np.linspace(-250, 250, nElecs)
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aSpacing = x_temp[1]-x_temp[0]
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y_temp = 0.
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xyz = Utils.ndgrid(x_temp, np.r_[y_temp], np.r_[0.])
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srcList = DC.Utils.WennerSrcList(nElecs,aSpacing)
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survey = DC.SurveyIP(srcList)
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imap = Maps.IdentityMap(mesh)
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problem = DC.ProblemIP(mesh, sigma=sigma, mapping= imap)
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problem.pair(survey)
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try:
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from pymatsolver import MumpsSolver
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problem.Solver = MumpsSolver
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except ImportError, e:
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problem.Solver = SolverLU
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mSynth = eta
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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*0, 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-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)
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self.assertTrue(passed)
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if __name__ == '__main__':
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unittest.main()
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