import numpy as np import unittest from SimPEG import * from scipy.sparse.linalg import dsolve TOL = 1e-14 MAPS_TO_TEST_2D = ["CircleMap", "ComplexMap", "ExpMap", "IdentityMap", "SurjectVertical1D", "Weighting", "SurjectFull","FullMap"] MAPS_TO_TEST_3D = [ "ComplexMap", "ExpMap", "IdentityMap", "SurjectVertical1D", "Weighting", "SurjectFull","FullMap"] class MapTests(unittest.TestCase): def setUp(self): a = np.array([1, 1, 1]) b = np.array([1, 2]) self.mesh2 = Mesh.TensorMesh([a, b], x0=np.array([3, 5])) self.mesh3 = Mesh.TensorMesh([a, b, [3,4]], x0=np.array([3, 5, 2])) self.mesh22 = Mesh.TensorMesh([b, a], x0=np.array([3, 5])) def test_transforms2D(self): for M in MAPS_TO_TEST_2D: maps = getattr(Maps, M)(self.mesh2) self.assertTrue(maps.test()) def test_transforms3D(self): for M in MAPS_TO_TEST_3D: maps = getattr(Maps, M)(self.mesh3) self.assertTrue(maps.test()) def test_transforms_logMap_reciprocalMap(self): # Note that log/reciprocal maps can be kinda finicky, so we are being explicit about the random seed. v2 = np.r_[ 0.40077291, 0.14410044, 0.58452314, 0.96323738, 0.01198519, 0.79754415] dv2 = np.r_[ 0.80653921, 0.13132446, 0.4901117, 0.03358737, 0.65473762, 0.44252488] v3 = np.r_[ 0.96084865, 0.34385186, 0.39430044, 0.81671285, 0.65929109, 0.2235217, 0.87897526, 0.5784033, 0.96876393, 0.63535864, 0.84130763, 0.22123854] dv3 = np.r_[ 0.96827838, 0.26072111, 0.45090749, 0.10573893, 0.65276365, 0.15646586, 0.51679682, 0.23071984, 0.95106218, 0.14201845, 0.25093564, 0.3732866 ] maps = Maps.LogMap(self.mesh2) self.assertTrue(maps.test(v2, dx=dv2)) maps = Maps.LogMap(self.mesh3) self.assertTrue(maps.test(v3, dx=dv3)) maps = Maps.ReciprocalMap(self.mesh2) self.assertTrue(maps.test(v2, dx=dv2)) maps = Maps.ReciprocalMap(self.mesh3) self.assertTrue(maps.test(v3, dx=dv3)) def test_Mesh2MeshMap(self): maps = Maps.Mesh2Mesh([self.mesh22, self.mesh2]) self.assertTrue(maps.test()) def test_mapMultiplication(self): M = Mesh.TensorMesh([2,3]) expMap = Maps.ExpMap(M) vertMap = Maps.SurjectVertical1D(M) combo = expMap*vertMap m = np.arange(3.0) t_true = np.exp(np.r_[0,0,1,1,2,2.]) self.assertLess(np.linalg.norm((combo * m)-t_true,np.inf),TOL) self.assertLess(np.linalg.norm((expMap * vertMap * m)-t_true,np.inf),TOL) self.assertLess(np.linalg.norm(expMap * (vertMap * m)-t_true,np.inf),TOL) self.assertLess(np.linalg.norm((expMap * vertMap) * m-t_true,np.inf),TOL) #Try making a model mod = Models.Model(m, mapping=combo) # print mod.transform # import matplotlib.pyplot as plt # plt.colorbar(M.plotImage(mod.transform)[0]) # plt.show() self.assertLess(np.linalg.norm(mod.transform-t_true,np.inf),TOL) self.assertRaises(Exception,Models.Model,np.r_[1.0],mapping=combo) self.assertRaises(ValueError, lambda: combo * (vertMap * expMap)) self.assertRaises(ValueError, lambda: (combo * vertMap) * expMap) self.assertRaises(ValueError, lambda: vertMap * expMap) self.assertRaises(ValueError, lambda: expMap * np.ones(100)) self.assertRaises(ValueError, lambda: expMap * np.ones((100.0,1))) self.assertRaises(ValueError, lambda: expMap * np.ones((100.0,5))) self.assertRaises(ValueError, lambda: combo * np.ones(100)) self.assertRaises(ValueError, lambda: combo * np.ones((100.0,1))) self.assertRaises(ValueError, lambda: combo * np.ones((100.0,5))) def test_activeCells(self): M = Mesh.TensorMesh([2,4],'0C') expMap = Maps.ExpMap(M) for actMap in [Maps.InjectActiveCells(M, M.vectorCCy <=0, 10, nC=M.nCy), Maps.ActiveCells(M, M.vectorCCy <=0, 10, nC=M.nCy)]: # actMap = Maps.InjectActiveCells(M, M.vectorCCy <=0, 10, nC=M.nCy) vertMap = Maps.SurjectVertical1D(M) combo = vertMap * actMap m = np.r_[1,2.] mod = Models.Model(m,combo) # import matplotlib.pyplot as plt # plt.colorbar(M.plotImage(mod.transform)[0]) # plt.show() self.assertLess(np.linalg.norm(mod.transform - np.r_[1,1,2,2,10,10,10,10.]), TOL) self.assertLess((mod.transformDeriv - combo.deriv(m)).toarray().sum(), TOL) def test_tripleMultiply(self): M = Mesh.TensorMesh([2,4],'0C') expMap = Maps.ExpMap(M) vertMap = Maps.SurjectVertical1D(M) actMap = Maps.InjectActiveCells(M, M.vectorCCy <=0, 10, nC=M.nCy) m = np.r_[1,2.] t_true = np.exp(np.r_[1,1,2,2,10,10,10,10.]) self.assertLess(np.linalg.norm((expMap * vertMap * actMap * m)-t_true,np.inf),TOL) self.assertLess(np.linalg.norm(((expMap * vertMap * actMap) * m)-t_true,np.inf),TOL) self.assertLess(np.linalg.norm((expMap * vertMap * (actMap * m))-t_true,np.inf),TOL) self.assertLess(np.linalg.norm((expMap * (vertMap * actMap) * m)-t_true,np.inf),TOL) self.assertLess(np.linalg.norm(((expMap * vertMap) * actMap * m)-t_true,np.inf),TOL) self.assertRaises(ValueError, lambda: expMap * actMap * vertMap ) self.assertRaises(ValueError, lambda: actMap * vertMap * expMap ) def test_map2Dto3D_x(self): M2 = Mesh.TensorMesh([2,4]) M3 = Mesh.TensorMesh([3,2,4]) m = np.random.rand(M2.nC) for m2to3 in [Maps.Surject2Dto3D(M3, normal='X'), Maps.Map2Dto3D(M3, normal='X')]: # m2to3 = Maps.Surject2Dto3D(M3, normal='X') m = np.arange(m2to3.nP) self.assertTrue(m2to3.test()) self.assertTrue(np.all(Utils.mkvc( (m2to3 * m).reshape(M3.vnC,order='F')[0,:,:] ) == m)) def test_map2Dto3D_y(self): M2 = Mesh.TensorMesh([3,4]) M3 = Mesh.TensorMesh([3,2,4]) m = np.random.rand(M2.nC) for m2to3 in [Maps.Surject2Dto3D(M3, normal='Y'),Maps.Map2Dto3D(M3, normal='Y')]: # m2to3 = Maps.Surject2Dto3D(M3, normal='Y') m = np.arange(m2to3.nP) self.assertTrue(m2to3.test()) self.assertTrue(np.all(Utils.mkvc( (m2to3 * m).reshape(M3.vnC,order='F')[:,0,:] ) == m)) def test_map2Dto3D_z(self): M2 = Mesh.TensorMesh([3,2]) M3 = Mesh.TensorMesh([3,2,4]) m = np.random.rand(M2.nC) for m2to3 in [Maps.Surject2Dto3D(M3, normal='Z'),Maps.Map2Dto3D(M3, normal='Z')]: # m2to3 = Maps.Surject2Dto3D(M3, normal='Z') m = np.arange(m2to3.nP) self.assertTrue(m2to3.test()) self.assertTrue(np.all(Utils.mkvc( (m2to3 * m).reshape(M3.vnC,order='F')[:,:,0] ) == m)) if __name__ == '__main__': unittest.main()