Update tests with new calls. Note that there seem to be problems with rotateLOM on some operator tests.

This commit is contained in:
Rowan Cockett
2013-08-06 15:09:01 -07:00
parent a510755926
commit 262aacce85
2 changed files with 79 additions and 95 deletions
+22 -46
View File
@@ -64,33 +64,21 @@ class TestInnerProducts(OrderTest):
analytic = 69881./21600 # Found using matlab symbolic toolbox.
if self.location == 'edges':
if self.M._meshType == 'TENSOR':
Ex = call(ex, self.M.gridEx)
Ey = call(ey, self.M.gridEy)
Ez = call(ez, self.M.gridEz)
E = np.matrix(np.r_[Ex, Ey, Ez]).T
elif self.M._meshType == 'LOM':
cart = lambda g: np.c_[call(ex, g), call(ey, g), call(ez, g)]
Ec = np.vstack((cart(self.M.gridEx),
cart(self.M.gridEy),
cart(self.M.gridEz)))
E = np.matrix(self.M.projectEdgeVector(Ec))
cart = lambda g: np.c_[call(ex, g), call(ey, g), call(ez, g)]
Ec = np.vstack((cart(self.M.gridEx),
cart(self.M.gridEy),
cart(self.M.gridEz)))
E = self.M.projectEdgeVector(Ec)
A = self.M.getEdgeInnerProduct(sigma)
numeric = E.T*A*E
numeric = E.T.dot(A.dot(E))
elif self.location == 'faces':
if self.M._meshType == 'TENSOR':
Fx = call(ex, self.M.gridFx)
Fy = call(ey, self.M.gridFy)
Fz = call(ez, self.M.gridFz)
F = np.matrix(np.r_[Fx, Fy, Fz]).T
elif self.M._meshType == 'LOM':
cart = lambda g: np.c_[call(ex, g), call(ey, g), call(ez, g)]
Fc = np.vstack((cart(self.M.gridFx),
cart(self.M.gridFy),
cart(self.M.gridFz)))
F = np.matrix(self.M.projectFaceVector(Fc))
cart = lambda g: np.c_[call(ex, g), call(ey, g), call(ez, g)]
Fc = np.vstack((cart(self.M.gridFx),
cart(self.M.gridFy),
cart(self.M.gridFz)))
F = self.M.projectFaceVector(Fc)
A = self.M.getFaceInnerProduct(sigma)
numeric = F.T*A*F
numeric = F.T.dot(A.dot(F))
err = np.abs(numeric - analytic)
return err
@@ -164,31 +152,19 @@ class TestInnerProducts2D(OrderTest):
analytic = 781427./360 # Found using matlab symbolic toolbox. z=5
if self.location == 'edges':
if self.M._meshType == 'TENSOR':
Ex = call(ex, self.M.gridEx)
Ey = call(ey, self.M.gridEy)
E = np.matrix(np.r_[Ex, Ey]).T
elif self.M._meshType == 'LOM':
cart = lambda g: np.c_[call(ex, g), call(ey, g)]
Ec = np.vstack((cart(self.M.gridEx),
cart(self.M.gridEy)))
E = np.matrix(self.M.projectEdgeVector(Ec))
cart = lambda g: np.c_[call(ex, g), call(ey, g)]
Ec = np.vstack((cart(self.M.gridEx),
cart(self.M.gridEy)))
E = self.M.projectEdgeVector(Ec)
A = self.M.getEdgeInnerProduct(sigma)
numeric = E.T*A*E
numeric = E.T.dot(A.dot(E))
elif self.location == 'faces':
if self.M._meshType == 'TENSOR':
Fx = call(ex, self.M.gridFx)
Fy = call(ey, self.M.gridFy)
F = np.matrix(np.r_[Fx, Fy]).T
elif self.M._meshType == 'LOM':
cart = lambda g: np.c_[call(ex, g), call(ey, g)]
Fc = np.vstack((cart(self.M.gridFx),
cart(self.M.gridFy)))
F = np.matrix(self.M.projectFaceVector(Fc))
cart = lambda g: np.c_[call(ex, g), call(ey, g)]
Fc = np.vstack((cart(self.M.gridFx),
cart(self.M.gridFy)))
F = self.M.projectFaceVector(Fc)
A = self.M.getFaceInnerProduct(sigma)
numeric = F.T*A*F
numeric = F.T.dot(A.dot(F))
err = np.abs(numeric - analytic)
return err