Testing boundary conditoins

- I am not sure what happend... but this is what I did for last push
This commit is contained in:
seogi
2014-02-19 15:24:37 -08:00
parent 9c8b64b9f1
commit 72fe771071
+326
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@@ -169,7 +169,333 @@ class Test2D_InhomogeneousDirichlet(OrderTest):
self.myTest = 'xcJ'
self.orderTest()
class Test1D_InhomogeneousNeumann(OrderTest):
name = "1D - Neumann"
meshTypes = MESHTYPES
meshDimension = 1
expectedOrders = 2
meshSizes = [4, 8, 16, 32, 64, 128]
def getError(self):
#Test function
phi = lambda x: np.sin(np.pi*x)
j_fun = lambda x: np.pi*np.cos(np.pi*x)
q_fun = lambda x: -(np.pi**2)*np.sin(np.pi*x)
xc_anal = phi(self.M.gridCC)
q_anal = q_fun(self.M.gridCC)
j_anal = j_fun(self.M.gridFx)
#TODO: Check where our boundary conditions are CCx or Nx
vecN = self.M.vectorNx
vecC = self.M.vectorCCx
phi_bc = phi(vecC[[0,-1]])
j_bc = j_fun(vecN[[0,-1]])
P, Pin, Pout = self.M.getBCProjWF([['neumann', 'neumann']])
Mc = self.M.getFaceInnerProduct()
McI = Utils.sdInv(self.M.getFaceInnerProduct())
V = Utils.sdiag(self.M.vol)
G = -Pin.T*Pin*self.M.faceDiv.T * V
D = self.M.faceDiv
j = McI*(G*xc_anal + P*phi_bc)
q = V*D*Pin.T*Pin*j + V*D*Pout.T*j_bc
# Rearrange if we know q to solve for x
A = V*D*Pin.T*Pin*McI*G
rhs = V*q_anal - V*D*Pin.T*Pin*McI*P*phi_bc - V*D*Pout.T*j_bc
# A = D*McI*G
# rhs = q_anal - D*McI*P*phi_bc
if self.myTest == 'j':
err = np.linalg.norm((Pin*j-Pin*j_anal), np.inf)
elif self.myTest == 'q':
err = np.linalg.norm((q-V*q_anal), np.inf)
elif self.myTest == 'xc':
#TODO: fix the null space
xc, info = sp.linalg.minres(A, rhs, tol = 1e-6)
err = np.linalg.norm((xc-xc_anal), np.inf)
if info > 0:
print 'Solve does not work well'
print 'ACCURACY', np.linalg.norm(Utils.mkvc(A*xc) - rhs)
elif self.myTest == 'xcJ':
#TODO: fix the null space
xc, info = sp.linalg.minres(A, rhs, tol = 1e-6)
j = McI*(G*xc + P*phi_bc)
err = np.linalg.norm((Pin*j-Pin*j_anal), np.inf)
if info > 0:
print 'Solve does not work well'
print 'ACCURACY', np.linalg.norm(Utils.mkvc(A*xc) - rhs)
return err
def test_orderJ(self):
self.name = "1D - InhomogeneousNeumann_Forward j"
self.myTest = 'j'
self.orderTest()
def test_orderQ(self):
self.name = "1D - InhomogeneousNeumann_Forward q"
self.myTest = 'q'
self.orderTest()
def test_orderXJ(self):
self.name = "1D - InhomogeneousNeumann_Inverse J"
self.myTest = 'xcJ'
self.orderTest()
class Test2D_InhomogeneousNeumann(OrderTest):
name = "2D - Neumann"
meshTypes = MESHTYPES
meshDimension = 2
expectedOrders = 2
meshSizes = [4, 8, 16, 32]
# meshSizes = [4]
def getError(self):
#Test function
phi = lambda x: np.sin(np.pi*x[:,0])*np.sin(np.pi*x[:,1])
j_funX = lambda x: np.pi*np.cos(np.pi*x[:,0])*np.sin(np.pi*x[:,1])
j_funY = lambda x: np.pi*np.sin(np.pi*x[:,0])*np.cos(np.pi*x[:,1])
q_fun = lambda x: -2*(np.pi**2)*phi(x)
xc_anal = phi(self.M.gridCC)
q_anal = q_fun(self.M.gridCC)
jX_anal = j_funX(self.M.gridFx)
jY_anal = j_funY(self.M.gridFy)
j_anal = np.r_[jX_anal,jY_anal]
#TODO: Check where our boundary conditions are CCx or Nx
cxm,cxp,cym,cyp = self.M.cellBoundaryInd
fxm,fxp,fym,fyp = self.M.faceBoundaryInd
gBFx = self.M.gridFx[(fxm|fxp),:]
gBFy = self.M.gridFy[(fym|fyp),:]
gBCx = self.M.gridCC[(cxm|cxp),:]
gBCy = self.M.gridCC[(cym|cyp),:]
phi_bc = phi(np.r_[gBFx,gBFy])
j_bc = np.r_[j_funX(gBFx), j_funY(gBFy)]
# P = sp.csr_matrix(([-1,1],([0,self.M.nF-1],[0,1])), shape=(self.M.nF, 2))
P, Pin, Pout = self.M.getBCProjWF('neumann')
Mc = self.M.getFaceInnerProduct()
McI = Utils.sdInv(self.M.getFaceInnerProduct())
V = Utils.sdiag(self.M.vol)
G = -Pin.T*Pin*self.M.faceDiv.T * V
D = self.M.faceDiv
j = McI*(G*xc_anal + P*phi_bc)
q = V*D*Pin.T*Pin*j + V*D*Pout.T*j_bc
# Rearrange if we know q to solve for x
A = V*D*Pin.T*Pin*McI*G
rhs = V*q_anal - V*D*Pin.T*Pin*McI*P*phi_bc - V*D*Pout.T*j_bc
if self.myTest == 'j':
err = np.linalg.norm((Pin*j-Pin*j_anal), np.inf)
elif self.myTest == 'q':
err = np.linalg.norm((q-V*q_anal), np.inf)
elif self.myTest == 'xc':
#TODO: fix the null space
xc, info = sp.linalg.minres(A, rhs, tol = 1e-6)
err = np.linalg.norm((xc-xc_anal), np.inf)
if info > 0:
print 'Solve does not work well'
print 'ACCURACY', np.linalg.norm(Utils.mkvc(A*xc) - rhs)
elif self.myTest == 'xcJ':
#TODO: fix the null space
xc, info = sp.linalg.minres(A, rhs, tol = 1e-6)
j = McI*(G*xc + P*phi_bc)
err = np.linalg.norm((Pin*j-Pin*j_anal), np.inf)
if info > 0:
print 'Solve does not work well'
print 'ACCURACY', np.linalg.norm(Utils.mkvc(A*xc) - rhs)
return err
def test_orderJ(self):
self.name = "2D - InhomogeneousNeumann_Forward j"
self.myTest = 'j'
self.orderTest()
def test_orderQ(self):
self.name = "2D - InhomogeneousNeumann_Forward q"
self.myTest = 'q'
self.orderTest()
def test_orderXJ(self):
self.name = "2D - InhomogeneousNeumann_Inverse J"
self.myTest = 'xcJ'
self.orderTest()
class Test1D_InhomogeneousMixed(OrderTest):
name = "1D - Mixed"
meshTypes = MESHTYPES
meshDimension = 1
expectedOrders = 2
meshSizes = [4, 8, 16, 32, 64, 128]
def getError(self):
#Test function
phi = lambda x: np.cos(0.5*np.pi*x)
j_fun = lambda x: -0.5*np.pi*np.sin(0.5*np.pi*x)
q_fun = lambda x: -0.25*(np.pi**2)*np.cos(0.5*np.pi*x)
xc_anal = phi(self.M.gridCC)
q_anal = q_fun(self.M.gridCC)
j_anal = j_fun(self.M.gridFx)
#TODO: Check where our boundary conditions are CCx or Nx
vecN = self.M.vectorNx
vecC = self.M.vectorCCx
phi_bc = phi(vecC[[0,-1]])
j_bc = j_fun(vecN[[0,-1]])
P, Pin, Pout = self.M.getBCProjWF([['dirichlet', 'neumann']])
Mc = self.M.getFaceInnerProduct()
McI = Utils.sdInv(self.M.getFaceInnerProduct())
V = Utils.sdiag(self.M.vol)
G = -Pin.T*Pin*self.M.faceDiv.T * V
D = self.M.faceDiv
j = McI*(G*xc_anal + P*phi_bc)
q = V*D*Pin.T*Pin*j + V*D*Pout.T*j_bc
# Rearrange if we know q to solve for x
A = V*D*Pin.T*Pin*McI*G
rhs = V*q_anal - V*D*Pin.T*Pin*McI*P*phi_bc - V*D*Pout.T*j_bc
# A = D*McI*G
# rhs = q_anal - D*McI*P*phi_bc
if self.myTest == 'j':
err = np.linalg.norm((Pin*j-Pin*j_anal), np.inf)
elif self.myTest == 'q':
err = np.linalg.norm((q-V*q_anal), np.inf)
elif self.myTest == 'xc':
#TODO: fix the null space
xc, info = sp.linalg.minres(A, rhs, tol = 1e-6)
err = np.linalg.norm((xc-xc_anal), np.inf)
if info > 0:
print 'Solve does not work well'
print 'ACCURACY', np.linalg.norm(Utils.mkvc(A*xc) - rhs)
elif self.myTest == 'xcJ':
#TODO: fix the null space
xc, info = sp.linalg.minres(A, rhs, tol = 1e-6)
j = McI*(G*xc + P*phi_bc)
err = np.linalg.norm((Pin*j-Pin*j_anal), np.inf)
if info > 0:
print 'Solve does not work well'
print 'ACCURACY', np.linalg.norm(Utils.mkvc(A*xc) - rhs)
return err
def test_orderJ(self):
self.name = "1D - InhomogeneousMixed_Forward j"
self.myTest = 'j'
self.orderTest()
def test_orderQ(self):
self.name = "1D - InhomogeneousMixed_Forward q"
self.myTest = 'q'
self.orderTest()
def test_orderXJ(self):
self.name = "1D - InhomogeneousMixed_Inverse J"
self.myTest = 'xcJ'
self.orderTest()
class Test2D_InhomogeneousMixed(OrderTest):
name = "2D - Mixed"
meshTypes = MESHTYPES
meshDimension = 2
expectedOrders = 2
meshSizes = [2, 4, 8, 16]
# meshSizes = [4]
def getError(self):
#Test function
phi = lambda x: np.cos(0.5*np.pi*x[:,0])*np.cos(0.5*np.pi*x[:,1])
j_funX = lambda x: -0.5*np.pi*np.sin(0.5*np.pi*x[:,0])*np.cos(0.5*np.pi*x[:,1])
j_funY = lambda x: -0.5*np.pi*np.cos(0.5*np.pi*x[:,0])*np.sin(0.5*np.pi*x[:,1])
q_fun = lambda x: -2*((0.5*np.pi)**2)*phi(x)
xc_anal = phi(self.M.gridCC)
q_anal = q_fun(self.M.gridCC)
jX_anal = j_funX(self.M.gridFx)
jY_anal = j_funY(self.M.gridFy)
j_anal = np.r_[jX_anal,jY_anal]
#TODO: Check where our boundary conditions are CCx or Nx
cxm,cxp,cym,cyp = self.M.cellBoundaryInd
fxm,fxp,fym,fyp = self.M.faceBoundaryInd
gBFx = self.M.gridFx[(fxm|fxp),:]
gBFy = self.M.gridFy[(fym|fyp),:]
gBCx = self.M.gridCC[(cxm|cxp),:]
gBCy = self.M.gridCC[(cym|cyp),:]
phi_bc = phi(np.r_[gBCx,gBCy])
j_bc = np.r_[j_funX(gBFx), j_funY(gBFy)]
# P = sp.csr_matrix(([-1,1],([0,self.M.nF-1],[0,1])), shape=(self.M.nF, 2))
P, Pin, Pout = self.M.getBCProjWF([['dirichlet', 'neumann'], ['dirichlet', 'neumann']])
Mc = self.M.getFaceInnerProduct()
McI = Utils.sdInv(self.M.getFaceInnerProduct())
V = Utils.sdiag(self.M.vol)
G = -Pin.T*Pin*self.M.faceDiv.T * V
D = self.M.faceDiv
j = McI*(G*xc_anal + P*phi_bc)
q = V*D*Pin.T*Pin*j + V*D*Pout.T*j_bc
# Rearrange if we know q to solve for x
A = V*D*Pin.T*Pin*McI*G
rhs = V*q_anal - V*D*Pin.T*Pin*McI*P*phi_bc - V*D*Pout.T*j_bc
if self.myTest == 'j':
err = np.linalg.norm((Pin*j-Pin*j_anal), np.inf)
elif self.myTest == 'q':
err = np.linalg.norm((q-V*q_anal), np.inf)
elif self.myTest == 'xc':
#TODO: fix the null space
xc, info = sp.linalg.minres(A, rhs, tol = 1e-6)
err = np.linalg.norm((xc-xc_anal), np.inf)
if info > 0:
print 'Solve does not work well'
print 'ACCURACY', np.linalg.norm(Utils.mkvc(A*xc) - rhs)
elif self.myTest == 'xcJ':
#TODO: fix the null space
xc, info = sp.linalg.minres(A, rhs, tol = 1e-6)
j = McI*(G*xc + P*phi_bc)
err = np.linalg.norm((Pin*j-Pin*j_anal), np.inf)
if info > 0:
print 'Solve does not work well'
print 'ACCURACY', np.linalg.norm(Utils.mkvc(A*xc) - rhs)
return err
def test_orderJ(self):
self.name = "2D - InhomogeneousMixed_Forward j"
self.myTest = 'j'
self.orderTest()
def test_orderQ(self):
self.name = "2D - InhomogeneousMixed_Forward q"
self.myTest = 'q'
self.orderTest()
def test_orderXJ(self):
self.name = "2D - InhomogeneousMixed_Inverse J"
self.myTest = 'xcJ'
self.orderTest()
if __name__ == '__main__':
unittest.main()