mirror of
https://github.com/wassname/simpeg.git
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Merge branch 'eldadswork' of https://bitbucket.org/rcockett/simpeg into LOM
Conflicts: SimPEG/utils.py
This commit is contained in:
Rowan Cockett
+28
-12
@@ -20,7 +20,7 @@ class OrderTest(unittest.TestCase):
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Note that you can provide any norm.
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Test is passed when estimated rate order of convergence is at least 90% of the
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Test is passed when estimated rate order of convergence is at least within the specified tolerance of the
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estimated rate supplied by the user.
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Minimal example for a curl operator:
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@@ -63,17 +63,32 @@ class OrderTest(unittest.TestCase):
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name = "Order Test"
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expectedOrder = 2
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tolerance = 0.85
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meshSizes = [4, 8, 16, 32]
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meshType = 'uniformTensorMesh'
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meshDimension = 3
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def setupMesh(self, nc):
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"""
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For a given number of cells nc, generate a TensorMesh with uniform cells with edge length h=1/nc.
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"""
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h1 = np.ones(nc)/nc
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h2 = np.ones(nc)/nc
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h3 = np.ones(nc)/nc
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h = [h1, h2, h3]
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self.M = TensorMesh(h)
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if 'TensorMesh' in self.meshType:
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if 'uniform' in self.meshType:
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h1 = np.ones(nc)/nc
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h2 = np.ones(nc)/nc
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h3 = np.ones(nc)/nc
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h = [h1, h2, h3]
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elif 'random' in self.meshType:
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h1 = np.random.rand(nc)
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h2 = np.random.rand(nc)
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h3 = np.random.rand(nc)
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h = [hi/np.sum(hi) for hi in [h1, h2, h3]] # normalize
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else:
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raise Exception('Unexpected meshType')
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self.M = TensorMesh(h[:self.meshDimension])
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max_h = max([np.max(hi) for hi in self.M.h])
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return max_h
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def getError(self):
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"""For given h, generate A[h], f and A(f) and return norm of error."""
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@@ -89,9 +104,9 @@ class OrderTest(unittest.TestCase):
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"""
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order = []
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err_old = 0.
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nc_old = 0.
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max_h_old = 0.
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for ii, nc in enumerate(self.meshSizes):
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self.setupMesh(nc)
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max_h = self.setupMesh(nc)
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err = self.getError()
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if ii == 0:
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print ''
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@@ -101,13 +116,14 @@ class OrderTest(unittest.TestCase):
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print '~~~~~~|~~~~~~~~~~~~~|~~~~~~~~~~~~~|~~~~~~~~~~'
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print '%4i | %8.2e |' % (nc, err)
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else:
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order.append(np.log(err/err_old)/np.log(float(nc_old)/float(nc)))
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order.append(np.log(err/err_old)/np.log(max_h/max_h_old))
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print '%4i | %8.2e | %6.4f | %6.4f' % (nc, err, err_old/err, order[-1])
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err_old = err
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nc_old = nc
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max_h_old = max_h
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print '---------------------------------------------'
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self.assertTrue(len(np.where(np.array(order) > 0.9*self.expectedOrder)[0]) > np.floor(0.75*len(order)))
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passTest = np.mean(np.array(order)) > self.tolerance*self.expectedOrder
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# passTest = len(np.where(np.array(order) > self.tolerance*self.expectedOrder)[0]) > np.floor(0.75*len(order))
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self.assertTrue(passTest)
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if __name__ == '__main__':
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unittest.main()
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@@ -1,15 +1,36 @@
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import numpy as np
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import unittest
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from OrderTest import OrderTest
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import sys
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sys.path.append('../')
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from getEdgeInnerProducts import *
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class TestEdgeInnerProduct(OrderTest):
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"""Integrate an edge function over a unit cube domain using edgeInnerProducts."""
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# MATLAB code:
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name = "Edge Inner Product"
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# syms x y z
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# ex = x.^2+y.*z;
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# ey = (z.^2).*x+y.*z;
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# ez = y.^2+x.*z;
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# e = [ex;ey;ez];
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# sigma1 = x.*y+1;
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# sigma2 = x.*z+2;
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# sigma3 = 3+z.*y;
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# sigma4 = 0.1.*x.*y.*z;
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# sigma5 = 0.2.*x.*y;
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# sigma6 = 0.1.*z;
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# S1 = [sigma1,0,0;0,sigma1,0;0,0,sigma1];
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# S2 = [sigma1,0,0;0,sigma2,0;0,0,sigma3];
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# S3 = [sigma1,sigma4,sigma5;sigma4,sigma2,sigma6;sigma5,sigma6,sigma3];
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# i1 = int(int(int(e.'*S1*e,x,0,1),y,0,1),z,0,1);
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# i2 = int(int(int(e.'*S2*e,x,0,1),y,0,1),z,0,1);
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# i3 = int(int(int(e.'*S3*e,x,0,1),y,0,1),z,0,1);
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class TestInnerProducts(OrderTest):
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"""Integrate an function over a unit cube domain using edgeInnerProducts and faceInnerProducts."""
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def getError(self):
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@@ -26,22 +47,70 @@ class TestEdgeInnerProduct(OrderTest):
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sigma5 = lambda x, y, z: 0.2*x*y
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sigma6 = lambda x, y, z: 0.1*z
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Ex = call(ex, self.M.gridEx)
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Ey = call(ey, self.M.gridEy)
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Ez = call(ez, self.M.gridEz)
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E = np.matrix(np.r_[Ex, Ey, Ez]).T
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Gc = self.M.gridCC
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sigma = np.c_[call(sigma1, Gc), call(sigma2, Gc), call(sigma3, Gc),
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call(sigma4, Gc), call(sigma5, Gc), call(sigma6, Gc)]
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if self.sigmaTest == 1:
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sigma = np.c_[call(sigma1, Gc)]
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analytic = 647./360 # Found using matlab symbolic toolbox.
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elif self.sigmaTest == 3:
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sigma = np.c_[call(sigma1, Gc), call(sigma2, Gc), call(sigma3, Gc)]
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analytic = 37./12 # Found using matlab symbolic toolbox.
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elif self.sigmaTest == 6:
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sigma = np.c_[call(sigma1, Gc), call(sigma2, Gc), call(sigma3, Gc),
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call(sigma4, Gc), call(sigma5, Gc), call(sigma6, Gc)]
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analytic = 69881./21600 # Found using matlab symbolic toolbox.
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if self.location == 'edges':
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Ex = call(ex, self.M.gridEx)
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Ey = call(ey, self.M.gridEy)
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Ez = call(ez, self.M.gridEz)
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E = np.matrix(np.r_[Ex, Ey, Ez]).T
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A = self.M.getEdgeInnerProduct(sigma)
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numeric = E.T*A*E
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elif self.location == 'faces':
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Fx = call(ex, self.M.gridFx)
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Fy = call(ey, self.M.gridFy)
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Fz = call(ez, self.M.gridFz)
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F = np.matrix(np.r_[Fx, Fy, Fz]).T
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A = self.M.getFaceInnerProduct(sigma)
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numeric = F.T*A*F
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A = getEdgeInnerProduct(self.M, sigma)
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numeric = E.T*A*E
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analytic = 69881./21600 # Found using matlab symbolic toolbox.
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err = np.abs(numeric - analytic)
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return err
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def test_order(self):
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def test_order1_edges(self):
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self.name = "Edge Inner Product - Isotropic"
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self.location = 'edges'
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self.sigmaTest = 1
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self.orderTest()
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def test_order3_edges(self):
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self.name = "Edge Inner Product - Anisotropic"
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self.location = 'edges'
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self.sigmaTest = 3
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self.orderTest()
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def test_order6_edges(self):
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self.name = "Edge Inner Product - Full Tensor"
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self.location = 'edges'
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self.sigmaTest = 6
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self.orderTest()
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def test_order1_faces(self):
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self.name = "Face Inner Product - Isotropic"
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self.location = 'faces'
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self.sigmaTest = 1
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self.orderTest()
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def test_order3_faces(self):
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self.name = "Face Inner Product - Anisotropic"
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self.location = 'faces'
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self.sigmaTest = 3
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self.orderTest()
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def test_order6_faces(self):
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self.name = "Face Inner Product - Full Tensor"
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self.location = 'faces'
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self.sigmaTest = 6
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self.orderTest()
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