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https://github.com/wassname/simpeg.git
synced 2026-07-09 22:07:38 +08:00
test all new maps unless added to exclude list
This commit is contained in:
Lindsey Heagy
+108
-68
@@ -2,48 +2,68 @@ import numpy as np
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import unittest
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from SimPEG import *
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from scipy.sparse.linalg import dsolve
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import inspect
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TOL = 1e-14
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MAPS_TO_TEST_2D = ["CircleMap", "ComplexMap", "ExpMap", "IdentityMap", "SurjectVertical1D", "Weighting", "SurjectFull","FullMap"]
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MAPS_TO_TEST_3D = [ "ComplexMap", "ExpMap", "IdentityMap", "SurjectVertical1D", "Weighting", "SurjectFull","FullMap"]
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MAPS_TO_EXCLUDE_2D = ["ComboMap", "ActiveCells", "InjectActiveCells"]
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MAPS_TO_EXCLUDE_3D = ["ComboMap", "ActiveCells", "InjectActiveCells", "CircleMap"]
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class MapTests(unittest.TestCase):
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def setUp(self):
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maps2test2D = [M for M in dir(Maps) if M not in MAPS_TO_EXCLUDE_2D]
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maps2test3D = [M for M in dir(Maps) if M not in MAPS_TO_EXCLUDE_3D]
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self.maps2test2D = [getattr(Maps, m) for m in maps2test2D if
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inspect.isclass(getattr(Maps, M)) and
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issubclass(getattr(Maps, M), Maps.IdentityMap)]
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self.maps2test3D = [getattr(Maps, m) for m in maps2test3D if
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inspect.isclass(getattr(Maps, M)) and
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issubclass(getattr(Maps, M), Maps.IdentityMap)]
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a = np.array([1, 1, 1])
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b = np.array([1, 2])
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self.mesh2 = Mesh.TensorMesh([a, b], x0=np.array([3, 5]))
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self.mesh3 = Mesh.TensorMesh([a, b, [3,4]], x0=np.array([3, 5, 2]))
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self.mesh3 = Mesh.TensorMesh([a, b, [3, 4]], x0=np.array([3, 5, 2]))
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self.mesh22 = Mesh.TensorMesh([b, a], x0=np.array([3, 5]))
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def test_transforms2D(self):
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for M in MAPS_TO_TEST_2D:
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maps = getattr(Maps, M)(self.mesh2)
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self.assertTrue(maps.test())
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for M in self.maps2test2D:
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self.assertTrue(M.test())
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def test_transforms2Dvec(self):
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for M in MAPS_TO_TEST_2D:
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maps = getattr(Maps, M)(self.mesh2)
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self.assertTrue(maps.testVec())
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for M in self.maps2test2D:
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self.assertTrue(M.testVec())
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def test_transforms3D(self):
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for M in MAPS_TO_TEST_3D:
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maps = getattr(Maps, M)(self.mesh3)
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self.assertTrue(maps.test())
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for M in self.maps2test3D:
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self.assertTrue(M.test())
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def test_transforms3Dvec(self):
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for M in MAPS_TO_TEST_3D:
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maps = getattr(Maps, M)(self.mesh3)
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self.assertTrue(maps.test())
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for M in self.maps2test3D:
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self.assertTrue(M.test())
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def test_transforms_logMap_reciprocalMap(self):
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# Note that log/reciprocal maps can be kinda finicky, so we are being explicit about the random seed.
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v2 = np.r_[ 0.40077291, 0.14410044, 0.58452314, 0.96323738, 0.01198519, 0.79754415]
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dv2 = np.r_[ 0.80653921, 0.13132446, 0.4901117, 0.03358737, 0.65473762, 0.44252488]
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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]
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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 ]
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# Note that log/reciprocal maps can be kinda finicky, so we are being
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# explicit about the random seed.
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v2 = np.r_[ 0.40077291, 0.14410044, 0.58452314, 0.96323738, 0.01198519,
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0.79754415]
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dv2 = np.r_[ 0.80653921, 0.13132446, 0.4901117, 0.03358737, 0.65473762,
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0.44252488]
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v3 = np.r_[ 0.96084865, 0.34385186, 0.39430044, 0.81671285, 0.65929109,
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0.2235217, 0.87897526, 0.5784033, 0.96876393, 0.63535864,
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0.84130763, 0.22123854]
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dv3 = np.r_[ 0.96827838, 0.26072111, 0.45090749, 0.10573893,
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0.65276365, 0.15646586, 0.51679682, 0.23071984,
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0.95106218, 0.14201845, 0.25093564, 0.3732866 ]
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maps = Maps.LogMap(self.mesh2)
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self.assertTrue(maps.test(v2, dx=dv2))
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maps = Maps.LogMap(self.mesh3)
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@@ -62,104 +82,124 @@ class MapTests(unittest.TestCase):
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maps = Maps.Mesh2Mesh([self.mesh22, self.mesh2])
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self.assertTrue(maps.testVec())
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def test_mapMultiplication(self):
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M = Mesh.TensorMesh([2,3])
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M = Mesh.TensorMesh([2, 3])
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expMap = Maps.ExpMap(M)
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vertMap = Maps.SurjectVertical1D(M)
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combo = expMap*vertMap
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m = np.arange(3.0)
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t_true = np.exp(np.r_[0,0,1,1,2,2.])
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self.assertLess(np.linalg.norm((combo * m)-t_true,np.inf),TOL)
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self.assertLess(np.linalg.norm((expMap * vertMap * m)-t_true,np.inf),TOL)
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self.assertLess(np.linalg.norm(expMap * (vertMap * m)-t_true,np.inf),TOL)
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self.assertLess(np.linalg.norm((expMap * vertMap) * m-t_true,np.inf),TOL)
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#Try making a model
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t_true = np.exp(np.r_[0, 0, 1, 1, 2, 2.])
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self.assertLess(np.linalg.norm((combo * m) - t_true, np.inf), TOL)
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self.assertLess(np.linalg.norm((expMap * vertMap * m)-t_true, np.inf),
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TOL)
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self.assertLess(np.linalg.norm(expMap * (vertMap * m)-t_true, np.inf),
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TOL)
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self.assertLess(np.linalg.norm((expMap * vertMap) * m-t_true, np.inf),
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TOL)
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# Try making a model
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mod = Models.Model(m, mapping=combo)
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# print mod.transform
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# import matplotlib.pyplot as plt
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# plt.colorbar(M.plotImage(mod.transform)[0])
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# plt.show()
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self.assertLess(np.linalg.norm(mod.transform-t_true,np.inf),TOL)
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self.assertLess(np.linalg.norm(mod.transform - t_true, np.inf), TOL)
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self.assertRaises(Exception,Models.Model,np.r_[1.0],mapping=combo)
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self.assertRaises(Exception, Models.Model, np.r_[1.0], mapping=combo)
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self.assertRaises(ValueError, lambda: combo * (vertMap * expMap))
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self.assertRaises(ValueError, lambda: (combo * vertMap) * expMap)
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self.assertRaises(ValueError, lambda: vertMap * expMap)
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self.assertRaises(ValueError, lambda: expMap * np.ones(100))
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self.assertRaises(ValueError, lambda: expMap * np.ones((100.0,1)))
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self.assertRaises(ValueError, lambda: expMap * np.ones((100.0,5)))
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self.assertRaises(ValueError, lambda: expMap * np.ones((100.0, 1)))
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self.assertRaises(ValueError, lambda: expMap * np.ones((100.0, 5)))
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self.assertRaises(ValueError, lambda: combo * np.ones(100))
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self.assertRaises(ValueError, lambda: combo * np.ones((100.0,1)))
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self.assertRaises(ValueError, lambda: combo * np.ones((100.0,5)))
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self.assertRaises(ValueError, lambda: combo * np.ones((100.0, 1)))
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self.assertRaises(ValueError, lambda: combo * np.ones((100.0, 5)))
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def test_activeCells(self):
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M = Mesh.TensorMesh([2,4],'0C')
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M = Mesh.TensorMesh([2, 4], '0C')
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expMap = Maps.ExpMap(M)
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for actMap in [Maps.InjectActiveCells(M, M.vectorCCy <=0, 10, nC=M.nCy), Maps.ActiveCells(M, M.vectorCCy <=0, 10, nC=M.nCy)]:
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# actMap = Maps.InjectActiveCells(M, M.vectorCCy <=0, 10, nC=M.nCy)
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for actMap in [Maps.InjectActiveCells(M, M.vectorCCy <= 0, 10,
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nC=M.nCy), Maps.ActiveCells(M, M.vectorCCy <= 0, 10, nC=M.nCy)]:
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# actMap = Maps.InjectActiveCells(M, M.vectorCCy <=0, 10, nC=M.nCy)
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vertMap = Maps.SurjectVertical1D(M)
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combo = vertMap * actMap
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m = np.r_[1,2.]
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mod = Models.Model(m,combo)
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m = np.r_[1., 2.]
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mod = Models.Model(m, combo)
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# import matplotlib.pyplot as plt
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# plt.colorbar(M.plotImage(mod.transform)[0])
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# plt.show()
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self.assertLess(np.linalg.norm(mod.transform - np.r_[1,1,2,2,10,10,10,10.]), TOL)
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self.assertLess((mod.transformDeriv - combo.deriv(m)).toarray().sum(), TOL)
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self.assertLess(np.linalg.norm(mod.transform -
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np.r_[1, 1, 2, 2, 10, 10, 10, 10.]), TOL)
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self.assertLess((mod.transformDeriv -
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combo.deriv(m)).toarray().sum(), TOL)
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def test_tripleMultiply(self):
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M = Mesh.TensorMesh([2,4],'0C')
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M = Mesh.TensorMesh([2, 4], '0C')
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expMap = Maps.ExpMap(M)
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vertMap = Maps.SurjectVertical1D(M)
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actMap = Maps.InjectActiveCells(M, M.vectorCCy <=0, 10, nC=M.nCy)
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m = np.r_[1,2.]
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t_true = np.exp(np.r_[1,1,2,2,10,10,10,10.])
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self.assertLess(np.linalg.norm((expMap * vertMap * actMap * m)-t_true,np.inf),TOL)
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self.assertLess(np.linalg.norm(((expMap * vertMap * actMap) * m)-t_true,np.inf),TOL)
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self.assertLess(np.linalg.norm((expMap * vertMap * (actMap * m))-t_true,np.inf),TOL)
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self.assertLess(np.linalg.norm((expMap * (vertMap * actMap) * m)-t_true,np.inf),TOL)
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self.assertLess(np.linalg.norm(((expMap * vertMap) * actMap * m)-t_true,np.inf),TOL)
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actMap = Maps.InjectActiveCells(M, M.vectorCCy <= 0, 10, nC=M.nCy)
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m = np.r_[1., 2.]
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t_true = np.exp(np.r_[1, 1, 2, 2, 10, 10, 10, 10.])
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self.assertRaises(ValueError, lambda: expMap * actMap * vertMap )
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self.assertRaises(ValueError, lambda: actMap * vertMap * expMap )
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self.assertLess(np.linalg.norm((expMap * vertMap * actMap * m) -
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t_true, np.inf), TOL)
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self.assertLess(np.linalg.norm(((expMap * vertMap * actMap) * m) -
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t_true, np.inf), TOL)
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self.assertLess(np.linalg.norm((expMap * vertMap * (actMap * m)) -
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t_true, np.inf), TOL)
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self.assertLess(np.linalg.norm((expMap * (vertMap * actMap) * m) -
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t_true, np.inf), TOL)
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self.assertLess(np.linalg.norm(((expMap * vertMap) * actMap * m) -
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t_true, np.inf), TOL)
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self.assertRaises(ValueError, lambda: expMap * actMap * vertMap)
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self.assertRaises(ValueError, lambda: actMap * vertMap * expMap)
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def test_map2Dto3D_x(self):
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M2 = Mesh.TensorMesh([2,4])
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M3 = Mesh.TensorMesh([3,2,4])
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M2 = Mesh.TensorMesh([2, 4])
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M3 = Mesh.TensorMesh([3, 2, 4])
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m = np.random.rand(M2.nC)
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for m2to3 in [Maps.Surject2Dto3D(M3, normal='X'), Maps.Map2Dto3D(M3, normal='X')]:
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# m2to3 = Maps.Surject2Dto3D(M3, normal='X')
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for m2to3 in [Maps.Surject2Dto3D(M3, normal='X'),
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Maps.Map2Dto3D(M3, normal='X')]:
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# m2to3 = Maps.Surject2Dto3D(M3, normal='X')
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m = np.arange(m2to3.nP)
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self.assertTrue(m2to3.test())
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self.assertTrue(m2to3.testVec())
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self.assertTrue(np.all(Utils.mkvc( (m2to3 * m).reshape(M3.vnC,order='F')[0,:,:] ) == m))
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self.assertTrue(np.all(Utils.mkvc( (m2to3 * m).reshape(M3.vnC ,
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order='F')[0, :, :] ) == m))
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def test_map2Dto3D_y(self):
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M2 = Mesh.TensorMesh([3,4])
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M3 = Mesh.TensorMesh([3,2,4])
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M2 = Mesh.TensorMesh([3, 4])
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M3 = Mesh.TensorMesh([3, 2, 4])
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m = np.random.rand(M2.nC)
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for m2to3 in [Maps.Surject2Dto3D(M3, normal='Y'),Maps.Map2Dto3D(M3, normal='Y')]:
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# m2to3 = Maps.Surject2Dto3D(M3, normal='Y')
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for m2to3 in [Maps.Surject2Dto3D(M3, normal='Y'), Maps.Map2Dto3D(M3,
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normal='Y')]:
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# m2to3 = Maps.Surject2Dto3D(M3, normal='Y')
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m = np.arange(m2to3.nP)
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self.assertTrue(m2to3.test())
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self.assertTrue(m2to3.testVec())
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self.assertTrue(np.all(Utils.mkvc( (m2to3 * m).reshape(M3.vnC,order='F')[:,0,:] ) == m))
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self.assertTrue(np.all(Utils.mkvc( (m2to3 * m).reshape(M3.vnC,
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order='F')[:, 0, :] ) == m))
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def test_map2Dto3D_z(self):
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M2 = Mesh.TensorMesh([3,2])
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M3 = Mesh.TensorMesh([3,2,4])
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M2 = Mesh.TensorMesh([3, 2])
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M3 = Mesh.TensorMesh([3, 2, 4])
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m = np.random.rand(M2.nC)
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for m2to3 in [Maps.Surject2Dto3D(M3, normal='Z'),Maps.Map2Dto3D(M3, normal='Z')]:
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# m2to3 = Maps.Surject2Dto3D(M3, normal='Z')
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for m2to3 in [Maps.Surject2Dto3D(M3, normal='Z'), Maps.Map2Dto3D(M3,
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normal='Z')]:
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# m2to3 = Maps.Surject2Dto3D(M3, normal='Z')
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m = np.arange(m2to3.nP)
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self.assertTrue(m2to3.test())
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self.assertTrue(m2to3.testVec())
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self.assertTrue(np.all(Utils.mkvc( (m2to3 * m).reshape(M3.vnC,order='F')[:,:,0] ) == m))
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self.assertTrue(np.all(Utils.mkvc( (m2to3 * m).reshape(M3.vnC,
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order='F')[:, :, 0] ) == m))
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if __name__ == '__main__':
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Block a user