def test_constructor(self):
#
# Define mesh, element, and dofhandler
#
mesh = QuadMesh(box=[0, 20, 0, 20],
resolution=(20, 20),
periodic={0, 1})
dim = mesh.dim()
element = QuadFE(dim, 'Q2')
dofhandler = DofHandler(mesh, element)
dofhandler.distribute_dofs()
basis = Basis(dofhandler, 'u')
alph = 2
kppa = 1
# Symmetric tensor gma T + bta* vv^T
gma = 0.1
bta = 25
p = lambda x: 10/np.pi*(0.75*np.sin(np.pi*x[:,0]/10)+\
0.25*np.sin(np.pi*x[:,1]/10))
f = Nodal(f=p, basis=basis)
fx = f.differentiate((1, 0))
fy = f.differentiate((1, 1))
#plot.contour(f)
x = np.linspace(0, 20, 12)
X, Y = np.meshgrid(x, x)
xy = np.array([X.ravel(), Y.ravel()]).T
U = fx.eval(xy).reshape(X.shape)
V = fy.eval(xy).reshape(X.shape)
v1 = lambda x: -0.25 * np.cos(np.pi * x[:, 1] / 10)
v2 = lambda x: 0.75 * np.cos(np.pi * x[:, 0] / 10)
U = v1(xy).reshape(X.shape)
V = v2(xy).reshape(X.shape)
#plt.quiver(X,Y, U, V)
#plt.show()
h11 = Explicit(lambda x: gma + bta * v1(x) * v1(x), dim=2)
h12 = Explicit(lambda x: bta * v1(x) * v2(x), dim=2)
h22 = Explicit(lambda x: gma + bta * v2(x) * v2(x), dim=2)
tau = (h11, h12, h22)
#tau = (Constant(2), Constant(1), Constant(1))
#
# Define default elliptic field
#
u = EllipticField(dofhandler, kappa=1, tau=tau, gamma=2)
Q = u.precision()
v = Nodal(data=u.sample(mode='precision', decomposition='chol'),
basis=basis)
plot = Plot(20)
plot.contour(v)
def test_same_dofs(self):
#
# Construct nested mesh
#
mesh = QuadMesh()
mesh.record(0)
for dummy in range(2):
mesh.cells.refine()
#
# Define dofhandler
#
element = QuadFE(mesh.dim(), 'Q1')
dofhandler = DofHandler(mesh, element)
dofhandler.distribute_dofs()
#
# Define basis functions
#
phi0 = Basis(dofhandler, 'u', subforest_flag=0)
phi0_x = Basis(dofhandler, 'ux', subforest_flag=0)
phi1 = Basis(dofhandler, 'u')
self.assertTrue(phi0.same_mesh(phi0_x))
self.assertFalse(phi0.same_mesh(phi1))
def test01_solve_2d(self):
"""
Solve a simple 2D problem with no hanging nodes
"""
mesh = QuadMesh(resolution=(5, 5))
# Mark dirichlet boundaries
mesh.mark_region('left',
lambda x, dummy: np.abs(x) < 1e-9,
entity_type='half_edge')
mesh.mark_region('right',
lambda x, dummy: np.abs(x - 1) < 1e-9,
entity_type='half_edge')
Q1 = QuadFE(mesh.dim(), 'Q1')
dQ1 = DofHandler(mesh, Q1)
dQ1.distribute_dofs()
phi = Basis(dQ1, 'u')
phi_x = Basis(dQ1, 'ux')
phi_y = Basis(dQ1, 'uy')
problem = [
Form(1, test=phi_x, trial=phi_x),
Form(1, test=phi_y, trial=phi_y),
Form(0, test=phi)
]
assembler = Assembler(problem, mesh)
assembler.add_dirichlet('left', dir_fn=0)
assembler.add_dirichlet('right', dir_fn=1)
assembler.assemble()
# Get matrix dirichlet correction and right hand side
A = assembler.get_matrix().toarray()
x0 = assembler.assembled_bnd()
b = assembler.get_vector()
ua = np.zeros((phi.n_dofs(), 1))
int_dofs = assembler.get_dofs('interior')
ua[int_dofs, 0] = np.linalg.solve(A, b - x0)
dir_bc = assembler.get_dirichlet()
dir_vals = np.array([dir_bc[dof] for dof in dir_bc])
dir_dofs = [dof for dof in dir_bc]
ua[dir_dofs] = dir_vals
ue_fn = Nodal(f=lambda x: x[:, 0], basis=phi)
ue = ue_fn.data()
self.assertTrue(np.allclose(ue, ua))
self.assertTrue(np.allclose(x0 + A.dot(ua[int_dofs, 0]), b))
mesh.mark_region('bnd', bnd_fn, entity_type='half_edge', on_boundary=True)
# Mark averaging region
dmn_fn = lambda x, y: x >= 0.75 and x <= 1 and y >= 0.75 and y <= 1
mesh.mark_region('dmn',
dmn_fn,
entity_type='cell',
strict_containment=True,
on_boundary=False)
#cells = mesh.get_region(flag='dmn', entity_type='cell', on_boundary=False, subforest_flag=None)
plot.mesh(mesh, regions=[('bnd', 'edge'), ('dmn', 'cell')])
#
# Elements
#
Q0 = QuadFE(mesh.dim(), 'DQ0') # Constants for parameter
Q1 = QuadFE(mesh.dim(), 'Q1') # Linear for output
Q2 = QuadFE(mesh.dim(), 'Q2') # Quadratic for adjoint
#
# DofHandlers
#
dQ0 = DofHandler(mesh, Q0)
dQ1 = DofHandler(mesh, Q1)
dQ2 = DofHandler(mesh, Q2)
# Distribute DOFs
dQ0.distribute_dofs()
dQ1.distribute_dofs()
dQ2.distribute_dofs()
mesh = QuadMesh(resolution=(50, 50))
# Mark Dirichlet boundary regions
out_fn = lambda x, y: abs(x - 1) < 1e-8 and 0.8 <= y and y <= 1
mesh.mark_region('out', out_fn, entity_type='half_edge', on_boundary=True)
in_fn = lambda x, y: abs(x) < 1e-8 and 0 <= y and y <= 0.2
mesh.mark_region('in', in_fn, entity_type='half_edge', on_boundary=True)
x_min, x_max = 0.7, 0.8
y_min, y_max = 0.4, 0.5
reg_fn = lambda x, y: x >= x_min and x <= x_max and y >= y_min and y <= y_max
mesh.mark_region('reg', reg_fn, entity_type='cell')
# Elements
Q1 = QuadFE(mesh.dim(), 'Q1')
dQ1 = DofHandler(mesh, Q1)
dQ1.distribute_dofs()
phi = Basis(dQ1)
phi_x = Basis(dQ1, derivative='vx')
phi_y = Basis(dQ1, derivative='vy')
#
# Diffusion Parameter
#
# Covariance Matrix
K = Covariance(dQ1, name='exponential', parameters={'sgm': 1, 'l': 0.1})
# Gaussian random field θ
def test_eval_phi(self):
"""
Check that the shapes are correct
"""
#
# Mesh
#
mesh = QuadMesh()
dim = mesh.dim()
#
# element information
#
element = QuadFE(dim, 'Q2')
dofhandler = DofHandler(mesh, element)
dofhandler.distribute_dofs()
# Basis
basis = Basis(dofhandler)
# Define phi
n_points = 5
phi = np.random.rand(n_points, 2)
dofs = [0, 1]
#
# Deterministic Data
#
n_dofs = dofhandler.n_dofs()
data = np.random.rand(n_dofs)
# Define deterministic function
f = Nodal(data=data, basis=basis)
# Evaluate and check dimensions
fx = f.eval(phi=phi, dofs=dofs)
self.assertEqual(fx.shape, (n_points, 1))
#
# Sampled Data
#
n_samples = 4
data = np.random.rand(n_dofs, n_samples)
# Define stochastic function
f = Nodal(data=data, basis=basis, dofhandler=dofhandler)
# Evaluate and check dimensions
fx = f.eval(phi=phi, dofs=dofs)
self.assertEqual(fx.shape, (n_points, n_samples))
#
# Bivariate deterministic
#
data = np.random.rand(n_dofs, n_dofs, 1)
# Define deterministic function
f = Nodal(data=data, basis=basis, dofhandler=dofhandler, n_variables=2)
fx = f.eval(phi=(phi, phi), dofs=(dofs, dofs))
self.assertEqual(fx.shape, (n_points, 1))
#
# Bivariate sampled
#
data = np.random.rand(n_dofs, n_dofs, n_samples)
# Define stochastic function
f = Nodal(data=data, basis=basis, dofhandler=dofhandler, n_variables=2)
fx = f.eval(phi=(phi, phi), dofs=(dofs, dofs))
self.assertEqual(fx.shape, (n_points, n_samples))
#
# Trivariate deterministic
#
data = np.random.rand(n_dofs, n_dofs, n_dofs, 1)
f = Nodal(data=data, basis=basis, dofhandler=dofhandler, n_variables=3)
bnd_fn = lambda x, y: abs(x) < 1e-6 or abs(1 - x) < 1e-6 or abs(
y) < 1e-6 or abs(1 - y) < 1e-6
mesh.mark_region('bnd', bnd_fn, entity_type='half_edge', on_boundary=True)
# Mark averaging region
dmn_fn = lambda x, y: x >= 0.75 and x <= 1 and y >= 0.75 and y <= 1
mesh.mark_region('dmn',
dmn_fn,
entity_type='cell',
strict_containment=True,
on_boundary=False)
#cells = mesh.get_region(flag='dmn', entity_type='cell', on_boundary=False, subforest_flag=None)
#plot.mesh(mesh, regions=[('bnd','edge'),('dmn','cell')])
# Define Elements
Q0 = QuadFE(mesh.dim(), 'DQ0')
dQ0 = DofHandler(mesh, Q0)
dQ0.distribute_dofs()
phi = Basis(dQ0)
q = Nodal(
f=lambda x: np.sin(2 * np.pi * x[:, 0]) * np.sin(2 * np.pi * x[:, 1]),
dim=2,
basis=phi)
problem = Form(q)
mesh.cells.refine(new_label='fine_mesh')
assembler = Assembler(problem, mesh, subforest_flag='fine_mesh')
assembler.assemble()
def reference_solution():
"""
Use sparse grid method to compute a benchmark solution
"""
mesh = QuadMesh(resolution=(10,10))
mesh.mark_region('boundary', lambda x,y:True,
entity_type='half_edge', on_boundary=True)
element = QuadFE(mesh.dim(), 'Q1')
dofhandler = DofHandler(mesh, element)
dofhandler.distribute_dofs()
n = dofhandler.n_dofs()
phi = Basis(dofhandler, 'u')
phi_x = Basis(dofhandler, 'ux')
phi_y = Basis(dofhandler, 'uy')
yd_fn = Explicit(lambda x: np.sin(2*np.pi*x[:,0])*np.sin(2*np.pi*x[:,1]),dim=2)
g = np.ones((n,1))
#
# Random diffusion coefficient
#
# Sparse grid
tasmanian_library="/home/hans-werner/bin/TASMANIAN-6.0/libtasmaniansparsegrid.so"
grid = TasmanianSG.TasmanianSparseGrid(tasmanian_library=tasmanian_library)
dimensions = 4
outputs = 1
depth = 4
type = 'tensor'
rule = 'gauss-legendre'
grid.makeGlobalGrid(dimensions, outputs, depth, type, rule)
Y = grid.getPoints()
w = grid.getQuadratureWeights()
n_samples = grid.getNumPoints()
x = dofhandler.get_dof_vertices()
a_nodal = 1 + 0.1*(np.outer(np.cos(np.pi*x[:,1]),Y[:,0])+\
np.outer(np.cos(np.pi*x[:,0]),Y[:,1])+\
np.outer(np.sin(2*np.pi*x[:,1]),Y[:,2])+\
np.outer(np.sin(2*np.pi*x[:,0]),Y[:,3]))
a = Nodal(data=a_nodal, dofhandler=dofhandler)
yd_vec = yd_fn.eval(x)
problems = [[Form(a, test=phi_x, trial=phi_x),
Form(a, test=phi_y, trial=phi_y)],
[Form(1, test=phi, trial=phi)]]
assembler = Assembler(problems, mesh)
assembler.assemble()
A = assembler.af[0]['bilinear'].get_matrix()
M = assembler.af[1]['bilinear'].get_matrix()
state = LS(phi)
state.add_dirichlet_constraint('boundary')
adjoint = LS(phi)
adjoint.add_dirichlet_constraint('boundary')
tau = 10
k_max = 20
alpha = 0.1
u = np.zeros((n,1))
norm_dJ_iter = []
J_iter = []
u_iter = []
for k in range(k_max):
print('iteration', k)
#
# Compute average cost and gradient
#
dJ = np.zeros((n,1))
J = 0
print('sampling')
for n in range(n_samples):
print(n)
yn, pn, Jn, dJn = cost_gradient(state,adjoint,A[n],M,
g,u,yd_vec,alpha)
J += w[n]*Jn
dJ += w[n]*dJn
print('')
norm_dJ = np.sqrt(dJ.T.dot(M.dot(dJ)))
#
# Store current iterates
#
norm_dJ_iter.append(norm_dJ)
J_iter.append(J)
u_iter.append(u)
#
# Check for convergence
#
if norm_dJ<1e-8:
break
#
# Update iterate
#
u -= tau*dJ
u_t - div*(D*grad(u)) + div(v*u) + R(u) = 0
subject to the appropriate initial and boundary conditions, using
SUPG and
"""
comment = Verbose()
# Computational mesh
mesh = QuadMesh(box=[0, 10, 0, 10], resolution=(100, 100))
left = mesh.mark_region('left', lambda x, y: abs(x) < 1e-10)
# Finite elements
# Piecewise constants
E0 = QuadFE(mesh.dim(), 'DQ0')
V0 = DofHandler(mesh, E0)
V0.distribute_dofs()
# Piecewise linears
E1 = QuadFE(mesh.dim(), 'Q1')
V1 = DofHandler(mesh, E1)
V1.distribute_dofs()
v = Basis(V1, 'v')
v_x = Basis(V1, 'vx')
v_y = Basis(V1, 'vy')
V1.distribute_dofs()
print(V1.n_dofs())
x_max = 2
y_min = 0
y_max = 1
mesh = QuadMesh(box=[x_min, x_max, y_min, y_max], resolution=(20, 10))
# Mark Dirichlet Edges
mesh.mark_region('left',
lambda x, y: np.abs(x) < 1e-9,
entity_type='half_edge')
mesh.mark_region('right',
lambda x, y: np.abs(x - 2) < 1e-9,
entity_type='half_edge')
# Element
element_Q0 = QuadFE(mesh.dim(), 'DQ0')
element_Q1 = QuadFE(mesh.dim(), 'Q1')
dh_Q0 = DofHandler(mesh, element_Q0)
dh_Q0.distribute_dofs()
n_Q0 = dh_Q0.n_dofs()
dh_Q1 = DofHandler(mesh, element_Q1)
dh_Q1.distribute_dofs()
n_Q1 = dh_Q1.n_dofs()
# Basis functions
phi = Basis(dh_Q1, 'v')
phi_x = Basis(dh_Q1, 'vx')
phi_y = Basis(dh_Q1, 'vy')
def test_integrals_2d(self):
"""
Test Assembly of some 2D systems
"""
mesh = QuadMesh(box=[1, 2, 1, 2], resolution=(2, 2))
mesh.cells.get_leaves()[0].mark(0)
mesh.cells.refine(refinement_flag=0)
# Kernel
kernel = Kernel(Explicit(f=lambda x: x[:, 0] * x[:, 1], dim=2))
problem = Form(kernel)
assembler = Assembler(problem, mesh=mesh)
assembler.assemble()
self.assertAlmostEqual(assembler.get_scalar(), 9 / 4)
#
# Linear forms (x,x) and (x,x') over [1,2]^2 = 7/3, 3/2
#
# Elements
Q1 = QuadFE(mesh.dim(), 'Q1')
Q2 = QuadFE(mesh.dim(), 'Q2')
Q3 = QuadFE(mesh.dim(), 'Q3')
# Dofhandlers
dQ1 = DofHandler(mesh, Q1)
dQ2 = DofHandler(mesh, Q2)
dQ3 = DofHandler(mesh, Q3)
# Distribute dofs
[d.distribute_dofs() for d in [dQ1, dQ2, dQ3]]
for dQ in [dQ1, dQ2, dQ3]:
# Basis
phi = Basis(dQ, 'u')
phi_x = Basis(dQ, 'ux')
# Kernel function
xfn = Nodal(f=lambda x: x[:, 0], basis=phi)
yfn = Nodal(f=lambda x: x[:, 1], basis=phi)
# Kernel
kernel = Kernel(xfn)
# Form
problem = [[Form(kernel, test=phi)], [Form(kernel, test=phi_x)]]
# Assembly
assembler = Assembler(problem, mesh)
assembler.assemble()
# Check b^Tx = (x,y)
b0 = assembler.get_vector(0)
self.assertAlmostEqual(np.sum(b0 * yfn.data()[:, 0]), 9 / 4)
b1 = assembler.get_vector(1)
self.assertAlmostEqual(np.sum(b1 * xfn.data()[:, 0]), 3 / 2)
self.assertAlmostEqual(np.sum(b1 * yfn.data()[:, 0]), 0)
#
# Bilinear forms
#
# Compute (1,x,y) = 9/4, or (xy, 1, 1) = 9/4
for dQ in [dQ1, dQ2, dQ3]:
# Basis
phi = Basis(dQ, 'u')
phi_x = Basis(dQ, 'ux')
phi_y = Basis(dQ, 'uy')
# Kernel function
xyfn = Explicit(f=lambda x: x[:, 0] * x[:, 1], dim=2)
xfn = Nodal(f=lambda x: x[:, 0], basis=phi)
yfn = Nodal(f=lambda x: x[:, 1], basis=phi)
# Form
problems = [[Form(1, test=phi, trial=phi)],
[Form(Kernel(xfn), test=phi, trial=phi_x)],
[Form(Kernel(xyfn), test=phi_y, trial=phi_x)]]
# Assemble
assembler = Assembler(problems, mesh)
assembler.assemble()
x = xfn.data()[:, 0]
y = yfn.data()[:, 0]
for i_problem in range(3):
A = assembler.get_matrix(i_problem)
self.assertAlmostEqual(y.T.dot(A.dot(x)), 9 / 4)
