Separate tests into folders.

Build in a matrix?
2026-08-02 13:00:17 +08:00 · 2015-10-30 13:39:01 -07:00
parent 0885b72577
commit b8fe0cfdbf
28 changed files with 81 additions and 41 deletions
@@ -0,0 +1,128 @@
+import numpy as np
+import unittest
+from SimPEG.Mesh import TensorMesh
+from SimPEG import Solver, Tests
+
+TOL = 1e-10
+
+class BasicTensorMeshTests(unittest.TestCase):
+
+    def setUp(self):
+        a = np.array([1, 1, 1])
+        b = np.array([1, 2])
+        c = np.array([1, 4])
+        self.mesh2 = TensorMesh([a, b], [3, 5])
+        self.mesh3 = TensorMesh([a, b, c])
+
+    def test_vectorN_2D(self):
+        testNx = np.array([3, 4, 5, 6])
+        testNy = np.array([5, 6, 8])
+
+        xtest = np.all(self.mesh2.vectorNx == testNx)
+        ytest = np.all(self.mesh2.vectorNy == testNy)
+        self.assertTrue(xtest and ytest)
+
+    def test_vectorCC_2D(self):
+        testNx = np.array([3.5, 4.5, 5.5])
+        testNy = np.array([5.5, 7])
+
+        xtest = np.all(self.mesh2.vectorCCx == testNx)
+        ytest = np.all(self.mesh2.vectorCCy == testNy)
+        self.assertTrue(xtest and ytest)
+
+    def test_area_3D(self):
+        test_area = np.array([1, 1, 1, 1, 2, 2, 2, 2, 4, 4, 4, 4, 8, 8, 8, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2])
+        t1 = np.all(self.mesh3.area == test_area)
+        self.assertTrue(t1)
+
+    def test_vol_3D(self):
+        test_vol = np.array([1, 1, 1, 2, 2, 2, 4, 4, 4, 8, 8, 8])
+        t1 = np.all(self.mesh3.vol == test_vol)
+        self.assertTrue(t1)
+
+    def test_vol_2D(self):
+        test_vol = np.array([1, 1, 1, 2, 2, 2])
+        t1 = np.all(self.mesh2.vol == test_vol)
+        self.assertTrue(t1)
+
+    def test_edge_3D(self):
+        test_edge = np.array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4])
+        t1 = np.all(self.mesh3.edge == test_edge)
+        self.assertTrue(t1)
+
+    def test_edge_2D(self):
+        test_edge = np.array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2])
+        t1 = np.all(self.mesh2.edge == test_edge)
+        self.assertTrue(t1)
+
+    def test_oneCell(self):
+        hx = np.array([1e-5])
+        M = TensorMesh([hx])
+        self.assertTrue(M.nC == 1)
+
+    def test_printing(self):
+        print TensorMesh([10])
+        print TensorMesh([10,10])
+        print TensorMesh([10,10,10])
+
+    def test_centering(self):
+        M1d = TensorMesh([10], 'C')
+        M2d = TensorMesh([10,10], 'CC')
+        M3d = TensorMesh([10,10,10], 'CCC')
+        self.assertLess(np.abs(M1d.x0 + 0.5).sum(), TOL)
+        self.assertLess(np.abs(M2d.x0 + 0.5).sum(), TOL)
+        self.assertLess(np.abs(M3d.x0 + 0.5).sum(), TOL)
+
+    def test_negative(self):
+        M1d = TensorMesh([10], 'N')
+        self.assertRaises(Exception, TensorMesh, [10], 'F')
+        M2d = TensorMesh([10,10], 'NN')
+        M3d = TensorMesh([10,10,10], 'NNN')
+        self.assertLess(np.abs(M1d.x0 + 1.0).sum(), TOL)
+        self.assertLess(np.abs(M2d.x0 + 1.0).sum(), TOL)
+        self.assertLess(np.abs(M3d.x0 + 1.0).sum(), TOL)
+
+    def test_cent_neg(self):
+        M3d = TensorMesh([10,10,10], 'C0N')
+        self.assertLess(np.abs(M3d.x0 + np.r_[0.5,0,1.0]).sum(), TOL)
+
+    def test_tensor(self):
+        M = TensorMesh([[(10.,2)]])
+        self.assertLess(np.abs(M.hx - np.r_[10.,10.]).sum(), TOL)
+
+class TestPoissonEqn(Tests.OrderTest):
+    name = "Poisson Equation"
+    meshSizes = [10, 16, 20]
+
+    def getError(self):
+        # Create some functions to integrate
+        fun = lambda x: np.sin(2*np.pi*x[:, 0])*np.sin(2*np.pi*x[:, 1])*np.sin(2*np.pi*x[:, 2])
+        sol = lambda x: -3.*((2*np.pi)**2)*fun(x)
+
+        self.M.setCellGradBC('dirichlet')
+
+        D = self.M.faceDiv
+        G = self.M.cellGrad
+        if self.forward:
+            sA = sol(self.M.gridCC)
+            sN = D*G*fun(self.M.gridCC)
+            err = np.linalg.norm((sA - sN), np.inf)
+        else:
+            fA = fun(self.M.gridCC)
+            fN = Solver(D*G) * (sol(self.M.gridCC))
+            err = np.linalg.norm((fA - fN), np.inf)
+        return err
+
+    def test_orderForward(self):
+        self.name = "Poisson Equation - Forward"
+        self.forward = True
+        self.orderTest()
+
+    def test_orderBackward(self):
+        self.name = "Poisson Equation - Backward"
+        self.forward = False
+        self.orderTest()
+
+
+if __name__ == '__main__':
+    unittest.main()