def test_closed_boundary(advection_scheme):
# FIXME: rk3 scheme does not bounces off the wall properly
xmin, xmax = 0., 1.
ymin, ymax = 0., 1.
mesh = RectangleMesh(Point(xmin, ymin), Point(xmax, ymax), 10, 10)
# Particle
x = np.array([[0.975, 0.475]])
# Given velocity field:
vexpr = Constant((1., 0.))
# Given time do_step:
dt = 0.05
# Then bounced position is
x_bounced = np.array([[0.975, 0.475]])
p = particles(x, [x, x], mesh)
V = VectorFunctionSpace(mesh, "CG", 1)
v = Function(V)
v.assign(vexpr)
# Different boundary parts
bound_left = UnitSquareLeft()
bound_right = UnitSquareRight()
bound_top = UnitSquareTop()
bound_bottom = UnitSquareBottom()
# Mark all facets
facet_marker = MeshFunction('size_t', mesh, mesh.topology().dim() - 1)
facet_marker.set_all(0)
# Mark as closed
bound_right.mark(facet_marker, 1)
# Mark other boundaries as open
bound_left.mark(facet_marker, 2)
bound_top.mark(facet_marker, 2)
bound_bottom.mark(facet_marker, 2)
if advection_scheme == 'euler':
ap = advect_particles(p, V, v, facet_marker)
elif advection_scheme == 'rk2':
ap = advect_rk2(p, V, v, facet_marker)
elif advection_scheme == 'rk3':
ap = advect_rk3(p, V, v, facet_marker)
else:
assert False
# Do one timestep, particle must bounce from wall of
ap.do_step(dt)
xpE = p.positions()
# Check if particle correctly bounced off from closed wall
xpE_root = comm.gather(xpE, root=0)
if comm.rank == 0:
xpE_root = np.float64(np.vstack(xpE_root))
error = np.linalg.norm(x_bounced - xpE_root)
assert(error < 1e-10)
def test_l2projection_bounded_3D(polynomial_order, lb, ub):
xmin, ymin, zmin = 0., 0., 0.
xmax, ymax, zmax = 1., 1., 1.
nx = 10
interpolate_expression = Ball(0.15, [0.5, 0.5, 0.5],
degree=3,
lb=lb,
ub=ub)
property_idx = 1
mesh = BoxMesh(Point(xmin, ymin, zmin), Point(xmax, ymax, zmax), nx, nx,
nx)
V = FunctionSpace(mesh, "DG", polynomial_order)
x = RegularBox(Point(0., 0., 0.), Point(1., 1.,
1.)).generate([100, 100, 100])
s = assign_particle_values(x, interpolate_expression)
# Just make a complicated particle, possibly with scalars and vectors mixed
p = particles(x, [s], mesh)
vh = Function(V)
lstsq_rho = l2projection(p, V, property_idx)
lstsq_rho.project(vh.cpp_object(), lb, ub)
# Assert if it stays within bounds
assert np.any(vh.vector().get_local() < ub + 1e-12)
assert np.any(vh.vector().get_local() > lb - 1e-12)
def test_l2projection_bounded(polynomial_order, lb, ub):
# Test l2 projection if it stays within bounds given by lb and ub
interpolate_expression = SlottedDisk(radius=0.15,
center=[0.5, 0.5],
width=0.05,
depth=0.,
degree=3,
lb=lb,
ub=ub)
xmin, xmax = 0., 1.
ymin, ymax = 0., 1.
property_idx = 5
mesh = RectangleMesh(Point(xmin, ymin), Point(xmax, ymax), 40, 40)
V = FunctionSpace(mesh, "DG", polynomial_order)
x = RandomRectangle(Point(xmin, ymin), Point(xmax,
ymax)).generate([500, 500])
s = assign_particle_values(x, interpolate_expression)
# Just make a complicated particle, possibly with scalars and vectors mixed
p = particles(x, [x, s, x, x, s], mesh)
vh = Function(V)
lstsq_rho = l2projection(p, V, property_idx)
lstsq_rho.project(vh, lb, ub)
# Assert if it stays within bounds
assert np.all(vh.vector().get_local() < ub + 1e-12)
assert np.all(vh.vector().get_local() > lb - 1e-12)
def test_l2projection(polynomial_order, in_expression):
# Test l2 projection for scalar and vector valued expression
interpolate_expression = Expression(in_expression, degree=3)
xmin, xmax = 0., 1.
ymin, ymax = 0., 1.
property_idx = 5
mesh = RectangleMesh(Point(xmin, ymin), Point(xmax, ymax), 40, 40)
if len(interpolate_expression.ufl_shape) == 0:
V = FunctionSpace(mesh, "DG", polynomial_order)
elif len(interpolate_expression.ufl_shape) == 1:
V = VectorFunctionSpace(mesh, "DG", polynomial_order)
v_exact = Function(V)
v_exact.interpolate(interpolate_expression)
x = RandomRectangle(Point(xmin, ymin), Point(xmax,
ymax)).generate([500, 500])
s = assign_particle_values(x, interpolate_expression)
# Just make a complicated particle, possibly with scalars and vectors mixed
p = particles(x, [x, s, x, x, s], mesh)
vh = Function(V)
lstsq_rho = l2projection(p, V, property_idx)
lstsq_rho.project(vh)
error_sq = abs(assemble(dot(v_exact - vh, v_exact - vh) * dx))
assert error_sq < 1e-15
def test_pde_constrained(polynomial_order, in_expression):
interpolate_expression = Expression(in_expression, degree=3)
xmin, xmax = 0., 1.
ymin, ymax = 0., 1.
property_idx = 1
dt = 1.
k = polynomial_order
# Make mesh
mesh = RectangleMesh(Point(xmin, ymin), Point(xmax, ymax), 40, 40)
# Make function spaces and functions
W_e = FiniteElement("DG", mesh.ufl_cell(), k)
T_e = FiniteElement("DG", mesh.ufl_cell(), 0)
Wbar_e = FiniteElement("DGT", mesh.ufl_cell(), k)
W = FunctionSpace(mesh, W_e)
T = FunctionSpace(mesh, T_e)
Wbar = FunctionSpace(mesh, Wbar_e)
psi_h, psi0_h = Function(W), Function(W)
lambda_h = Function(T)
psibar_h = Function(Wbar)
uadvect = Constant((0, 0))
# Define particles
x = RandomRectangle(Point(xmin, ymin), Point(xmax,
ymax)).generate([500, 500])
s = assign_particle_values(x, interpolate_expression)
psi0_h.assign(interpolate_expression)
# Just make a complicated particle, possibly with scalars and vectors mixed
p = particles(x, [s], mesh)
p.interpolate(psi0_h, 1)
# Initialize forms
FuncSpace_adv = {
'FuncSpace_local': W,
'FuncSpace_lambda': T,
'FuncSpace_bar': Wbar
}
forms_pde = FormsPDEMap(mesh, FuncSpace_adv).forms_theta_linear(
psi0_h, uadvect, dt, Constant(1.0))
pde_projection = PDEStaticCondensation(mesh, p, forms_pde['N_a'],
forms_pde['G_a'], forms_pde['L_a'],
forms_pde['H_a'], forms_pde['B_a'],
forms_pde['Q_a'], forms_pde['R_a'],
forms_pde['S_a'], [], property_idx)
# Assemble and solve
pde_projection.assemble(True, True)
pde_projection.solve_problem(psibar_h, psi_h, lambda_h, 'none', 'default')
error_psih = abs(assemble((psi_h - psi0_h) * (psi_h - psi0_h) * dx))
error_lamb = abs(assemble(lambda_h * lambda_h * dx))
assert error_psih < 1e-15
assert error_lamb < 1e-15
def test_failsafe_sweep():
interpolate_expression = Expression('x[0]', degree=1)
mesh = UnitSquareMesh(5, 5)
V = FunctionSpace(mesh, "DG", 1)
v = Function(V)
v.assign(interpolate_expression)
np_min, np_max = 1, 2
np_failsafe = 4
# Initialize particles
x = RandomRectangle(Point(0.0, 0.0), Point(1., 1.)).generate([100, 100])
s = assign_particle_values(x, interpolate_expression)
# Broadcast to other procs
x = comm.bcast(x, root=0)
s = comm.bcast(s, root=0)
property_idx = 1
p = particles(x, [s], mesh)
AD = AddDelete(p, np_min, np_max, [v])
AD.do_sweep_failsafe(np_failsafe)
# Must recover linear
lstsq_rho = l2projection(p, V, property_idx)
lstsq_rho.project(v.cpp_object())
error = sqrt(
assemble(
(v - interpolate_expression) * (v - interpolate_expression) * dx))
assert len(p.positions() == mesh.num_cells() * np_failsafe)
assert error < 1e-12
def test_advect_periodic(advection_scheme):
# FIXME: this unit test is sensitive to the ordering of the particle
# array, i.e. xp0_root and xpE_root may contain exactly the same entries
# but only in a different order. This will return an error right now
xmin, xmax = 0., 1.
ymin, ymax = 0., 1.
pres = 3
mesh = RectangleMesh(Point(xmin, ymin), Point(xmax, ymax), 10, 10)
lims = np.array([[xmin, xmin, ymin, ymax], [xmax, xmax, ymin, ymax],
[xmin, xmax, ymin, ymin], [xmin, xmax, ymax, ymax]])
vexpr = Constant((1., 1.))
V = VectorFunctionSpace(mesh, "CG", 1)
x = RandomRectangle(Point(0.05, 0.05), Point(0.15, 0.15)).generate([pres, pres])
x = comm.bcast(x, root=0)
dt = 0.05
v = Function(V)
v.assign(vexpr)
p = particles(x, [x*0, x**2], mesh)
if advection_scheme == 'euler':
ap = advect_particles(p, V, v, 'periodic', lims.flatten())
elif advection_scheme == 'rk2':
ap = advect_rk2(p, V, v, 'periodic', lims.flatten())
elif advection_scheme == 'rk3':
ap = advect_rk3(p, V, v, 'periodic', lims.flatten())
else:
assert False
xp0 = p.positions()
t = 0.
while t < 1.-1e-12:
ap.do_step(dt)
t += dt
xpE = p.positions()
# Check if position correct
xp0_root = comm.gather(xp0, root=0)
xpE_root = comm.gather(xpE, root=0)
num_particles = p.number_of_particles()
if comm.Get_rank() == 0:
xp0_root = np.float32(np.vstack(xp0_root))
xpE_root = np.float32(np.vstack(xpE_root))
# Sort on x positions
xp0_root = xp0_root[xp0_root[:, 0].argsort(), :]
xpE_root = xpE_root[xpE_root[:, 0].argsort(), :]
error = np.linalg.norm(xp0_root - xpE_root)
assert error < 1e-10
assert num_particles - pres**2 == 0
def test_advect_periodic(advection_scheme):
xmin, ymin, zmin = 0., 0., 0.
xmax, ymax, zmax = 1., 1., 1.
pres = 10
mesh = UnitCubeMesh(10, 10, 10)
lims = np.array([[xmin, xmin, ymin, ymax, zmin, zmax],
[xmax, xmax, ymin, ymax, zmin, zmax],
[xmin, xmax, ymin, ymin, zmin, zmax],
[xmin, xmax, ymax, ymax, zmin, zmax],
[xmin, xmax, ymin, ymax, zmin, zmin],
[xmin, xmax, ymin, ymax, zmax, zmax]])
vexpr = Constant((1., 1., 1.))
V = VectorFunctionSpace(mesh, "CG", 1)
v = Function(V)
v.assign(vexpr)
x = RandomBox(Point(0., 0., 0.), Point(1., 1.,
1.)).generate([pres, pres, pres])
x = comm.bcast(x, root=0)
dt = 0.05
p = particles(x, [x * 0, x**2], mesh)
if advection_scheme == 'euler':
ap = advect_particles(p, V, v, 'periodic', lims.flatten())
elif advection_scheme == 'rk2':
ap = advect_rk2(p, V, v, 'periodic', lims.flatten())
elif advection_scheme == 'rk3':
ap = advect_rk3(p, V, v, 'periodic', lims.flatten())
else:
assert False
xp0 = p.positions()
t = 0.
while t < 1. - 1e-12:
ap.do_step(dt)
t += dt
xpE = p.positions()
xp0_root = comm.gather(xp0, root=0)
xpE_root = comm.gather(xpE, root=0)
assert len(xp0) == len(xpE)
num_particles = p.number_of_particles()
if comm.Get_rank() == 0:
xp0_root = np.float32(np.vstack(xp0_root))
xpE_root = np.float32(np.vstack(xpE_root))
# Sort on x positions
xp0_root = xp0_root[xp0_root[:, 0].argsort(), :]
xpE_root = xpE_root[xpE_root[:, 0].argsort(), :]
error = np.linalg.norm(xp0_root - xpE_root)
assert error < 1e-10
assert num_particles - pres**3 == 0
def test_open_boundary(advection_scheme):
xmin, xmax = 0.0, 1.0
ymin, ymax = 0.0, 1.0
pres = 3
mesh = RectangleMesh(Point(xmin, ymin), Point(xmax, ymax), 10, 10)
# Particle
x = RandomRectangle(Point(0.955, 0.45), Point(1.0,
0.55)).generate([pres, pres])
x = comm.bcast(x, root=0)
# Given velocity field:
vexpr = Constant((1.0, 1.0))
# Given time do_step:
dt = 0.05
p = particles(x, [x, x], mesh)
V = VectorFunctionSpace(mesh, "CG", 1)
v = Function(V)
v.assign(vexpr)
# Different boundary parts
bound_left = UnitSquareLeft()
bound_right = UnitSquareRight()
bound_top = UnitSquareTop()
bound_bottom = UnitSquareBottom()
# Mark all facets
facet_marker = MeshFunction("size_t", mesh, mesh.topology().dim() - 1)
facet_marker.set_all(0)
# Mark as open
bound_right.mark(facet_marker, 2)
# Mark other boundaries as closed
bound_left.mark(facet_marker, 1)
bound_top.mark(facet_marker, 1)
bound_bottom.mark(facet_marker, 1)
if advection_scheme == "euler":
ap = advect_particles(p, V, v, facet_marker)
elif advection_scheme == "rk2":
ap = advect_rk2(p, V, v, facet_marker)
elif advection_scheme == "rk3":
ap = advect_rk3(p, V, v, facet_marker)
else:
assert False
# Do one timestep, particle must bounce from wall of
ap.do_step(dt)
num_particles = p.number_of_particles()
# Check if all particles left domain
if comm.rank == 0:
assert (num_particles == 0)
def test_advect_periodic_facet_marker(advection_scheme):
xmin, xmax = 0.0, 1.0
ymin, ymax = 0.0, 1.0
mesh = RectangleMesh(Point(xmin, ymin), Point(xmax, ymax), 10, 10)
facet_marker = MeshFunction("size_t", mesh, mesh.topology().dim() - 1)
facet_marker.set_all(0)
boundaries = Boundaries()
boundaries.mark(facet_marker, 3)
lims = np.array([
[xmin, xmin, ymin, ymax],
[xmax, xmax, ymin, ymax],
[xmin, xmax, ymin, ymin],
[xmin, xmax, ymax, ymax],
])
vexpr = Constant((1.0, 1.0))
V = VectorFunctionSpace(mesh, "CG", 1)
x = RandomRectangle(Point(0.05, 0.05), Point(0.15, 0.15)).generate([3, 3])
x = comm.bcast(x, root=0)
dt = 0.05
v = Function(V)
v.assign(vexpr)
p = particles(x, [x * 0, x**2], mesh)
if advection_scheme == "euler":
ap = advect_particles(p, V, v, facet_marker, lims.flatten())
elif advection_scheme == "rk2":
ap = advect_rk2(p, V, v, facet_marker, lims.flatten())
elif advection_scheme == "rk3":
ap = advect_rk3(p, V, v, facet_marker, lims.flatten())
else:
assert False
xp0 = p.positions()
t = 0.0
while t < 1.0 - 1e-12:
ap.do_step(dt)
t += dt
xpE = p.positions()
# Check if position correct
xp0_root = comm.gather(xp0, root=0)
xpE_root = comm.gather(xpE, root=0)
if comm.Get_rank() == 0:
xp0_root = np.float32(np.vstack(xp0_root))
xpE_root = np.float32(np.vstack(xpE_root))
error = np.linalg.norm(xp0_root - xpE_root)
assert error < 1e-10
def test_bounded_domain_boundary(xlims, ylims, advection_scheme):
xmin, xmax = xlims
ymin, ymax = ylims
pres = 1
mesh = RectangleMesh(Point(xmin, ymin), Point(xmax, ymax), 10, 10)
ymin += 0.0025
lims = np.array([xmin, xmax, ymin, ymax])
v_arr = np.array([-1.0, -1.0])
vexpr = Constant(v_arr)
V = VectorFunctionSpace(mesh, "CG", 1)
x = RandomRectangle(Point(0.05, 0.05), Point(0.15,
0.15)).generate([pres, pres])
dt = 0.005
v = Function(V)
v.assign(vexpr)
p = particles(x, [x], mesh)
if advection_scheme == 'euler':
ap = advect_particles(p, V, v, 'bounded', lims.flatten())
elif advection_scheme == 'rk2':
ap = advect_rk2(p, V, v, 'bounded', lims.flatten())
elif advection_scheme == 'rk3':
ap = advect_rk3(p, V, v, 'bounded', lims.flatten())
else:
assert False
original_num_particles = p.number_of_particles()
t = 0.
while t < 3.0 - 1e-12:
ap.do_step(dt)
t += dt
assert p.number_of_particles() == original_num_particles
xpn = np.array(p.get_property(0)).reshape((-1, 2))
x0 = np.array(p.get_property(1)).reshape((-1, 2))
analytical_position = x0 + t * v_arr
analytical_position[:, 0] = np.maximum(
np.minimum(xmax, analytical_position[:, 0]), xmin)
analytical_position[:, 1] = np.maximum(
np.minimum(ymax, analytical_position[:, 1]), ymin)
error = np.abs(xpn - analytical_position)
assert np.all(np.abs(error) < 1e-12)
def test_advect_open(advection_scheme):
pres = 3
mesh = UnitCubeMesh(10, 10, 10)
# Particle
x = RandomBox(Point(0.955, 0.45, 0.5),
Point(0.99, 0.55, 0.6)).generate([pres, pres, pres])
x = comm.bcast(x, root=0)
# Given velocity field:
vexpr = Constant((1.0, 1.0, 1.0))
# Given time do_step:
dt = 0.05
p = particles(x, [x, x], mesh)
V = VectorFunctionSpace(mesh, "CG", 1)
v = Function(V)
v.assign(vexpr)
# Different boundary parts
bounds = Boundaries()
bound_right = UnitCubeRight()
# Mark all facets
facet_marker = MeshFunction("size_t", mesh, mesh.topology().dim() - 1)
facet_marker.set_all(0)
bounds.mark(facet_marker, 1)
bound_right.mark(facet_marker, 2)
# Mark as open
bound_right.mark(facet_marker, 2)
if advection_scheme == "euler":
ap = advect_particles(p, V, v, facet_marker)
elif advection_scheme == "rk2":
ap = advect_rk2(p, V, v, facet_marker)
elif advection_scheme == "rk3":
ap = advect_rk3(p, V, v, facet_marker)
else:
assert False
# Do one timestep, particle must bounce from wall of
ap.do_step(dt)
num_particles = p.number_of_particles()
# Check if all particles left domain
if comm.rank == 0:
assert num_particles == 0
def test_advect_particle(advection_scheme):
if comm.rank == 0:
print('Run advect_particle')
# Rotate one particle, and compute the error
mesh = UnitSquareMesh(10, 10)
# Particle
x = np.array([[0.25, 0.25]])
dt_list = [0.08, 0.04, 0.02, 0.01, 0.005]
# Velocity field
vexpr = Expression(('-pi*(x[1] - 0.5)', 'pi*(x[0]-0.5)'), degree=3)
V = VectorFunctionSpace(mesh, "CG", 1)
v = Function(V)
v.assign(vexpr)
error_list = []
for dt in dt_list:
p = particles(x, [x, x], mesh)
if advection_scheme == 'euler':
ap = advect_particles(p, V, v, 'closed')
elif advection_scheme == 'rk2':
ap = advect_rk2(p, V, v, 'closed')
elif advection_scheme == 'rk3':
ap = advect_rk3(p, V, v, 'closed')
else:
assert False
xp_0 = p.positions()
t = 0.
while t < 2.-1e-12:
ap.do_step(dt)
t += dt
xp_end = p.positions()
error_list.append(np.linalg.norm(xp_0 - xp_end))
if not all(eps == 0 for eps in error_list):
rate = compute_convergence(dt_list, error_list)
if advection_scheme == 'euler':
# First order for euler
assert any(i > 0.9 for i in rate)
elif advection_scheme == 'rk2':
# Second order for rk2
assert any(i > 1.95 for i in rate)
elif advection_scheme == 'rk3':
# Third order for rk3
assert any(i > 2.9 for i in rate)
def test_mesh_generator_2d():
"""Basic functionality test."""
mesh = RectangleMesh(Point(0.0, 0.0), Point(1.0, 1.0), 5, 5)
for x in mesh.coordinates():
x[0] += 0.5 * x[1]
w = RandomCell(mesh)
pts = w.generate(3)
assert len(pts) == mesh.num_cells() * 3
interpolate_expression = Expression("x[0] + x[1]", degree=1)
s = assign_particle_values(pts, interpolate_expression, on_root=False)
p = particles(pts, [s], mesh)
assert np.linalg.norm(np.sum(pts, axis=1) - s) <= 1e-15
assert np.linalg.norm(pts - p.positions()) <= 1e-15
def test_l2_projection_3D(polynomial_order, in_expression):
xmin, ymin, zmin = 0.0, 0.0, 0.0
xmax, ymax, zmax = 1.0, 1.0, 1.0
nx = 25
property_idx = 1
mesh = BoxMesh(Point(xmin, ymin, zmin), Point(xmax, ymax, zmax), nx, nx,
nx)
interpolate_expression = Expression(in_expression, degree=3)
if len(interpolate_expression.ufl_shape) == 0:
V = FunctionSpace(mesh, "DG", polynomial_order)
elif len(interpolate_expression.ufl_shape) == 1:
V = VectorFunctionSpace(mesh, "DG", polynomial_order)
v_exact = Function(V)
v_exact.assign(interpolate_expression)
x = RandomBox(Point(0.0, 0.0, 0.0), Point(1.0, 1.0,
1.0)).generate([4, 4, 4])
s = assign_particle_values(x, interpolate_expression)
# Just make a complicated particle, possibly with scalars and vectors mixed
p = particles(x, [s], mesh)
# Do AddDelete sweep
AD = AddDelete(p, 13, 15, [v_exact])
AD.do_sweep()
vh = Function(V)
lstsq_vh = l2projection(p, V, property_idx)
lstsq_vh.project(vh.cpp_object())
error_sq = abs(assemble(dot(v_exact - vh, v_exact - vh) * dx))
if comm.Get_rank() == 0:
assert error_sq < 1e-13
def test_mesh_generator_3d():
"""Basic functionality test."""
mesh = BoxMesh(Point(0.0, 0.0, 0.0), Point(1.0, 1.0, 1.0), 5, 5, 5)
for x in mesh.coordinates():
x[0] += 0.5 * x[1] + 0.2 * x[2]
w = RandomCell(mesh)
pts = w.generate(3)
assert len(pts) == mesh.num_cells() * 3
interpolate_expression = Expression("x[0] + x[1] + x[2]", degree=1)
s = assign_particle_values(pts, interpolate_expression, on_root=False)
assert np.linalg.norm(np.sum(pts, axis=1) - s) <= 1e-15
p = particles(pts, [s], mesh)
assert pts.shape == p.positions().shape
for i in range(10000):
s, t, u, v = w._random_bary(4)
assert s >= 0 and s <= 1
assert t >= 0 and t <= 1
assert u >= 0 and u <= 1
assert v >= 0 and v <= 1
def read_calving_front_sim(fname_base):
fname_ext = '.npz'
fname = fname_base + fname_ext
print(fname)
# Load particle data
if path.exists(fname):
tracer_data = np.load(fname)
else:
print('Cannot read file')
t = tracer_data['t'].item()
# Load mesh
mesh_file = fname_base + '.xml'
mesh = Mesh(mesh_file)
# Make particle class
n = len(tracer_data['xm'])
xp = np.vstack(
(tracer_data['xm'], tracer_data['zm'])).transpose().reshape(n, 2)
pstrain = tracer_data['strain']
pepsII = tracer_data['epsII']
ptemp = tracer_data['temp']
p = particles(xp, [pstrain, ptemp, pepsII], mesh)
# Interpolate particles to mesh
Vdg = FunctionSpace(mesh, 'DG', 1)
strain = Function(Vdg)
lstsq_strain = l2projection(p, Vdg, 1) # First variable???
lstsq_strain.project_mpm(strain) # Projection is stored in phih0
# Boundary mesh with portion above sea level marked
bmesh = BoundaryMesh(mesh, 'exterior', order=True)
x = bmesh.coordinates()
#ymax = np.max(x[x[:,0]==0,1])
filter = (x[:, 0] > 1e-4) & (x[:, 1] > 0)
xm = np.min(x[filter, 0])
id = np.argwhere(x[:, 0] == xm).item()
# Check if nodes increasing or decreasing
if (x[id - 1, 0] > x[id, 0]):
# Decrease nodes
inc = -1
stop = 0
else:
# Increase nodes
inc = 1
stop = len(x)
iold = id
for i in range(id, stop, inc):
if x[i, 1] > 0.0:
slope = (x[i, 1] - x[iold, 1]) / (x[i, 0] - x[iold, 0])
#print(x[i,0],strain(x[i]),strain(x[i])>0.99,slope,slope<-pi/3)
#print(-slope*180/pi)
if strain(x[i]) > 0.1:
L = x[iold, 0]
break
elif np.abs(slope) > pi / 6:
L = x[iold, 0]
break
iold = i
print('Terminus position', L)
# Extract profile centered on terminus
filter = (x[:, 1] > 0.0) & (x[:, 0] > 10) & (x[:, 0] < L + 5 * 800)
xp = x[filter, 0] - L
zp = x[filter, 1]
idx = np.argsort(xp)
xp = xp[idx]
zp = zp[idx]
zp = gaussian_filter(zp, 1.5)
#fname = fname_base + 'term_pos.npz'
#print(fname)
return xp, zp
def read_files(fname_base):
L = []
t = []
for step in range(0, 1000000, 10):
fname_ext = str(step).zfill(3) + '.npz'
fname = fname_base + fname_ext
print(fname)
# Load particle data
if path.exists(fname):
tracer_data = np.load(fname)
else:
print('Cannot read file')
break
t.append(tracer_data['t'].item())
# Load mesh
mesh_file = fname_base + str(step).zfill(3) + '.xml'
mesh = Mesh(mesh_file)
# Make particle class
n = len(tracer_data['xm'])
xp = np.vstack(
(tracer_data['xm'], tracer_data['zm'])).transpose().reshape(n, 2)
pstrain = tracer_data['strain']
pepsII = tracer_data['epsII']
ptemp = tracer_data['temp']
p = particles(xp, [pstrain, ptemp, pepsII], mesh)
# Interpolate particles to mesh
Vdg = FunctionSpace(mesh, 'DG', 1)
strain = Function(Vdg)
lstsq_strain = l2projection(p, Vdg, 1) # First variable???
lstsq_strain.project_mpm(strain) # Projection is stored in phih0
# Boundary mesh with portion above sea level marked
bmesh = BoundaryMesh(mesh, 'exterior', order=True)
x = bmesh.coordinates()
#ymax = np.max(x[x[:,0]==0,1])
filter = (x[:, 0] > 1e-4) & (x[:, 1] > 0)
xm = np.min(x[filter, 0])
id = np.argwhere(x[:, 0] == xm).item()
# Check if nodes increasing or decreasing
if (x[id - 1, 0] > x[id, 0]):
# Decrease nodes
inc = -1
stop = 0
else:
# Increase nodes
inc = 1
stop = len(x)
iold = id
for i in range(id, stop, inc):
if x[i, 1] > 0.0:
slope = (x[i, 1] - x[iold, 1]) / (x[i, 0] - x[iold, 0])
#print(x[i,0],strain(x[i]),strain(x[i])>0.99,slope,slope<-pi/3)
#print(-slope*180/pi)
if strain(x[i]) > 0.99:
L.append(x[iold, 0])
break
elif np.abs(slope) > pi / 6:
L.append(x[iold, 0])
break
iold = i
print('Terminus position', L[-1])
if i == stop - inc:
print('No terminus identified')
L.append(np.Nan)
fname = fname_base + 'term_pos.npz'
print(fname)
# Least squares fit to data
#if len(t)>len(L):
# print('Not equal')
# t =t[0:-1]
print(len(t), len(L))
t = np.array(t)
L = np.array(L)
filter = (t > 2 / 12) #
t, L = np.array(t), np.array(L)
dLdt, b, rvalue, pvalue1, err = linregress(t[filter], L[filter])
print('Rate of terminus advance', dLdt, 'Errror', err)
np.savez(fname,
t=t,
L=L,
dLdt=dLdt,
err=err,
pvalue=pvalue1,
rvalue=rvalue)
return None
uh = Function(V)
uh.assign(Expression(("-Uh*x[1]", "Uh*x[0]"), Uh=Uh, degree=3))
psi0_expression = GaussianPulse(center=(xc, yc),
sigma=float(sigma),
U=[Uh, Uh],
time=0.0,
height=1.0,
degree=3)
# Generate particles
x = RandomCircle(Point(x0, y0), r).generate([pres, pres])
s = np.zeros((len(x), 1), dtype=np.float_)
# Initialize particles with position x and scalar property s at the mesh
p = particles(x, [s], mesh)
property_idx = 1 # Scalar quantity is stored at slot 1
# Initialize advection class, use RK3 scheme
ap = advect_rk3(p, V, uh, "open")
# Define the variational (projection problem)
W_e = FiniteElement("DG", mesh.ufl_cell(), k)
T_e = FiniteElement("DG", mesh.ufl_cell(), 0)
Wbar_e = FiniteElement("DGT", mesh.ufl_cell(), k)
W = FunctionSpace(mesh, W_e)
T = FunctionSpace(mesh, T_e)
Wbar = FunctionSpace(mesh, Wbar_e)
psi_h, psi0_h = Function(W), Function(W)
temp_fun = temp_init(Ts, Tb, surf_fun, bed_fun, degree=1)
# Create functions defined on mesh with initial values
strain_mesh.assign(strain_init)
temp_mesh.assign(interpolate(temp_fun, Vdg))
epsII_mesh.assign(strain_init)
# Particle values at nodes
pstrain = assign_particle_values(xp, strain_fun)
pepsII = assign_particle_values(xp, strain_fun)
ptemp = assign_particle_values(xp, temp_fun)
print('Done initializing function spaces')
# Now we initialize the particle class
print('Creating particles')
p = particles(xp, [pstrain, ptemp, pepsII], mesh.mesh)
print('Done particles')
# Make sure we have enough particles per cell
#AD = AddDelete(p, p_min, p_max, [strain_mesh, temp_mesh,epsII_mesh]) # Sweep over mesh to delete/insert particles
#AD.do_sweep()
(xp, pstrain, ptemp,
pepsII) = (p.return_property(mesh, 0), p.return_property(mesh, 1),
p.return_property(mesh, 2), p.return_property(mesh, 3))
#_____________________________________________
# Initialize temperature model
print('Initializing temperature')
Tmodel = tempModel(mesh.mesh, Tb=Tb, Ts=Ts)
x = SpatialCoordinate(mesh.mesh)
zb = bot_fun(x[0])
def test_moving_mesh():
t = 0.
dt = 0.025
num_steps = 20
xmin, ymin = 0., 0.
xmax, ymax = 2., 2.
xc, yc = 1., 1.
nx, ny = 20, 20
pres = 150
k = 1
mesh = RectangleMesh(Point(xmin, ymin), Point(xmax, ymax), nx, ny)
n = FacetNormal(mesh)
# Class for mesh motion
dU = PeriodicVelocity(xmin, xmax, dt, t, degree=1)
Qcg = VectorFunctionSpace(mesh, 'CG', 1)
boundaries = MeshFunction("size_t", mesh, mesh.topology().dim()-1)
boundaries.set_all(0)
leftbound = Left(xmin)
leftbound.mark(boundaries, 99)
ds = Measure('ds', domain=mesh, subdomain_data=boundaries)
# Create function spaces
Q_E_Rho = FiniteElement("DG", mesh.ufl_cell(), k)
T_1 = FunctionSpace(mesh, 'DG', 0)
Qbar_E = FiniteElement("DGT", mesh.ufl_cell(), k)
Q_Rho = FunctionSpace(mesh, Q_E_Rho)
Qbar = FunctionSpace(mesh, Qbar_E)
phih, phih0 = Function(Q_Rho), Function(Q_Rho)
phibar = Function(Qbar)
# Advective velocity
uh = Function(Qcg)
uh.assign(Constant((0., 0.)))
# Mesh velocity
umesh = Function(Qcg)
# Total velocity
uadvect = uh-umesh
# Now throw in the particles
x = RandomRectangle(Point(xmin, ymin), Point(xmax, ymax)).generate([pres, pres])
s = assign_particle_values(x, GaussianPulse(center=(xc, yc), sigma=float(0.25),
U=[0, 0], time=0., height=1., degree=3))
x = comm.bcast(x, root=0)
s = comm.bcast(s, root=0)
p = particles(x, [s], mesh)
# Define projections problem
FuncSpace_adv = {'FuncSpace_local': Q_Rho, 'FuncSpace_lambda': T_1, 'FuncSpace_bar': Qbar}
FormsPDE = FormsPDEMap(mesh, FuncSpace_adv, ds=ds)
forms_pde = FormsPDE.forms_theta_linear(phih0, uadvect, dt, Constant(1.0), zeta=Constant(0.))
pde_projection = PDEStaticCondensation(mesh, p,
forms_pde['N_a'], forms_pde['G_a'], forms_pde['L_a'],
forms_pde['H_a'],
forms_pde['B_a'],
forms_pde['Q_a'], forms_pde['R_a'], forms_pde['S_a'],
[], 1)
# Initialize the initial condition at mesh by an l2 projection
lstsq_rho = l2projection(p, Q_Rho, 1)
lstsq_rho.project(phih0.cpp_object())
for step in range(num_steps):
# Compute old area at old configuration
old_area = assemble(phih0*dx)
# Pre-assemble rhs
pde_projection.assemble_state_rhs()
# Move mesh
dU.compute_ubc()
umesh.assign(project(dU, Qcg))
ALE.move(mesh, project(dU * dt, Qcg))
dU.update()
# Relocate particles as a result of mesh motion
# NOTE: if particles were advected themselve,
# we had to run update_facets_info() here as well
p.relocate()
# Assemble left-hand side on new config, but not the right-hand side
pde_projection.assemble(True, False)
pde_projection.solve_problem(phibar.cpp_object(), phih.cpp_object(),
'mumps', 'none')
# Needed to compute conservation, note that there
# is an outgoing flux at left boundary
new_area = assemble(phih*dx)
gamma = conditional(ge(dot(uadvect, n), 0), 0, 1)
bflux = assemble((1-gamma) * dot(uadvect, n) * phih * ds)
# Update solution
assign(phih0, phih)
# Put assertion on (global) mass balance, local mass balance is
# too time consuming but should pass also
assert new_area - old_area + bflux * dt < 1e-12
# Assert that max value of phih stays close to 2 and
# min value close to 0. This typically will fail if
# we do not do a correct relocate of particles
assert np.amin(phih.vector().get_local()) > -0.015
assert np.amax(phih.vector().get_local()) < 1.04
Uhbar0 = Function(mixedG)
# Set initial density field
initial_density = BinaryBlock(geometry, float(rho1), float(rho2), degree=1)
zero_expression = Expression(("0.", "0."), degree=1)
# Initialize particles
x = RandomRectangle(Point(xmin, ymin), Point(xmax, ymax)).generate(
[pres, int(pres * (ymax - ymin) / (xmax - xmin))])
up = assign_particle_values(x, zero_expression)
rhop = assign_particle_values(x, initial_density)
# Increment requires dup to be stored, init zero
dup = up
p = particles(x, [rhop, up, dup], mesh)
# Init rho0 field
lstsq_rho = l2projection(p, Q_Rho, 1)
lstsq_rho.project(rho0, float(rho2), float(rho1))
# Initialize l2 projection for specific momentum
lstsq_u = l2projection(p, W_2, 2)
# Initialize advection class
ap = advect_rk3(p, W_2, Udiv, 'closed')
# Set-up boundary conditions (free slip)
boundaries = MeshFunction("size_t", mesh, mesh.topology().dim() - 1)
boundaries.set_all(0)
all_bounds = Boundaries()
ALE.move(mesh, displacement)
# Entrainment functional measures
de = 1
cf = MeshFunction("size_t", mesh, mesh.topology().dim(), 0)
CompiledSubDomain("x[1] > db - DOLFIN_EPS", db=db).mark(cf, de)
dx = Measure("dx", subdomain_data=cf)
# Setup particles
pres = 25
x = RandomBox(Point(xmin, ymin, zmin), Point(xmax, ymax, zmax)).generate([pres, pres, pres])
s = np.zeros((len(x), 1), dtype=np.float_)
# Interpolate initial function onto particles, index slot 1
property_idx = 1
ptcls = particles(x, [s], mesh)
# Define the variational (projection problem)
k = 1
W_e = FiniteElement("DG", mesh.ufl_cell(), k)
T_e = FiniteElement("DG", mesh.ufl_cell(), 0)
Wbar_e = FiniteElement("DGT", mesh.ufl_cell(), k)
# Composition field space
Wh = FunctionSpace(mesh, W_e)
Th = FunctionSpace(mesh, T_e)
Wbarh = FunctionSpace(mesh, Wbar_e)
phi = interpolate(StepFunction(), Wh)
gamma0 = interpolate(StepFunction(), Wh)
