def triang_grid(nx=None):
if nx is None:
nx = np.array([2, 2])
g = pp.StructuredTriangleGrid(nx)
g.compute_geometry()
return g
def test_create_partition_2d_tri(self):
g = pp.StructuredTriangleGrid([3, 2])
g.compute_geometry()
part = co.create_partition(co.tpfa_matrix(g))
known = np.array([1, 1, 1, 0, 0, 1, 0, 2, 2, 0, 2, 2])
known_map = np.array([4, 3, 7, 5, 11, 8, 1, 2, 10, 6, 12, 9]) - 1
self.assertTrue(np.array_equal(part, known[known_map]))
def main(self, N):
Nx = Ny = N
# g = structured.CartGrid([Nx, Ny], [2, 2])
g = pp.StructuredTriangleGrid([Nx, Ny], [1, 1])
g.compute_geometry()
# co.coarsen(g, 'by_volume')
# Assign parameters
data = self.add_data(g)
# Choose and define the solvers
solver_flow = pp.MVEM("flow")
solver_flow.discretize(g, data)
A_flow, b_flow = solver_flow.assemble_matrix_rhs(g, data)
solver_source = pp.DualScalarSource("flow")
solver_source.discretize(g, data)
A_source, b_source = solver_source.assemble_matrix_rhs(g, data)
up = sps.linalg.spsolve(A_flow + A_source, b_flow + b_source)
u = solver_flow.extract_flux(g, up, data)
p = solver_flow.extract_pressure(g, up, data)
# P0u = solver_flow.project_flux(g, u, data, keyword="flow")
diam = np.amax(g.cell_diameters())
return diam, self.error_p(g, p)
def test_upwind_2d_simplex_surf_darcy_flux_negative(self):
g = pp.StructuredTriangleGrid([2, 1], [1, 1])
R = pp.map_geometry.rotation_matrix(-np.pi / 5.0, [1, 1, -1])
g.nodes = np.dot(R, g.nodes)
g.compute_geometry()
solver = pp.Upwind()
dis = solver.darcy_flux(g, np.dot(R, [-1, 0, 0]))
bf = g.tags["domain_boundary_faces"].nonzero()[0]
bc = pp.BoundaryCondition(g, bf, bf.size * ["neu"])
specified_parameters = {"bc": bc, "darcy_flux": dis}
data = pp.initialize_default_data(g, {}, "transport", specified_parameters)
solver.discretize(g, data)
M = solver.assemble_matrix_rhs(g, data)[0].todense()
deltaT = solver.cfl(g, data)
M_known = np.array([[1, 0, 0, -1], [-1, 0, 0, 0], [0, 0, 1, 0], [0, 0, -1, 1]])
deltaT_known = 1 / 6
rtol = 1e-15
atol = rtol
self.assertTrue(np.allclose(M, M_known, rtol, atol))
self.assertTrue(np.allclose(deltaT, deltaT_known, rtol, atol))
def test_changing_bc(self):
"""
We test that we can change the boundary condition
"""
g = pp.StructuredTriangleGrid([2, 2], physdims=(1, 1))
g.compute_geometry()
bc = pp.BoundaryConditionVectorial(g)
k = pp.FourthOrderTensor(g.dim, np.ones(g.num_cells),
np.ones(g.num_cells))
stress_neu, bound_stress_neu = pp.numerics.fv.mpsa.mpsa(
g, k, bc, inverter="python")
bc.is_dir[:, g.get_all_boundary_faces()] = True
bc.is_neu[bc.is_dir] = False
stress_dir, bound_stress_dir = pp.numerics.fv.mpsa.mpsa(
g, k, bc, inverter="python")
# Partiall should give same result as full
faces = g.get_all_boundary_faces()
stress, bound_stress = pp.numerics.fv.mpsa.mpsa_update_partial(
stress_neu,
bound_stress_neu,
g,
k,
bc,
faces=faces,
inverter="python")
self.assertTrue(np.allclose((stress - stress_dir).data, 0))
self.assertTrue(np.allclose((bound_stress - bound_stress_dir).data, 0))
def test_structured_triang(self):
nx = 1
ny = 1
g = pp.StructuredTriangleGrid([nx, ny], physdims=[1, 1])
g.compute_geometry()
bot = g.face_centers[1] < 1e-10
top = g.face_centers[1] > 1 - 1e-10
left = g.face_centers[0] < 1e-10
right = g.face_centers[0] > 1 - 1e-10
is_dir = left
is_neu = top
is_rob = right + bot
bnd = pp.BoundaryConditionVectorial(g)
bnd.is_neu[:] = False
bnd.is_dir[:, is_dir] = True
bnd.is_rob[:, is_rob] = True
bnd.is_neu[:, is_neu] = True
sc_top = pp.fvutils.SubcellTopology(g)
bnd = pp.fvutils.boundary_to_sub_boundary(bnd, sc_top)
bnd_excl = pp.fvutils.ExcludeBoundaries(sc_top, bnd, g.dim)
rhs = pp.numerics.fv.mpsa.create_bound_rhs(bnd, bnd_excl, sc_top, g,
True)
hf2f = pp.fvutils.map_hf_2_f(sc_top.fno_unique, sc_top.subfno_unique,
g.dim)
rhs = rhs * hf2f.T
rhs_known = np.array([
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0],
[1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0],
[0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
])
self.assertTrue(np.all(np.abs(rhs_known - rhs) < 1e-12))
def test_neu(self):
g = pp.StructuredTriangleGrid([2, 2])
basis = np.random.rand(g.dim, g.dim, g.num_faces)
bc = pp.BoundaryConditionVectorial(g, g.get_all_boundary_faces(),
"neu")
# Add a Dirichlet condition so the system is well defined
bc.is_dir[:, g.get_boundary_faces()[0]] = True
bc.is_neu[bc.is_dir] = False
self.run_test(g, basis, bc)
def test_default_basis_2d(self):
g = pp.StructuredTriangleGrid([1, 1])
bc = pp.BoundaryConditionVectorial(g)
basis_known = np.array([
[[1.0, 1.0, 1.0, 1.0, 1.0], [0.0, 0.0, 0.0, 0.0, 0.0]],
[[0.0, 0.0, 0.0, 0.0, 0.0], [1.0, 1.0, 1.0, 1.0, 1.0]],
])
self.assertTrue(np.allclose(bc.basis, basis_known))
def test_simplex_2d(self):
g = pp.StructuredTriangleGrid(np.array([3, 2]))
g.compute_geometry()
c = np.array([0, 1, 3])
true_nodes = np.array([0, 1, 4, 5, 6])
true_faces = np.array([0, 1, 2, 4, 5, 10, 13])
h, sub_f, sub_n = pp.partition.extract_subgrid(g, c)
assert np.array_equal(true_nodes, sub_n)
assert np.array_equal(true_faces, sub_f)
self.compare_grid_geometries(g, h, c, true_faces, true_nodes)
def test_structured_triang(self):
nx = 1
ny = 1
g = pp.StructuredTriangleGrid([nx, ny], physdims=[1, 1])
g.compute_geometry()
c = pp.FourthOrderTensor(2, np.ones(g.num_cells), np.ones(g.num_cells))
robin_weight = np.pi
bot = g.face_centers[1] < 1e-10
top = g.face_centers[1] > 1 - 1e-10
left = g.face_centers[0] < 1e-10
right = g.face_centers[0] > 1 - 1e-10
dir_ind = np.ravel(np.argwhere(left))
neu_ind = np.ravel(np.argwhere(()))
rob_ind = np.ravel(np.argwhere(right + top + bot))
names = ["dir"] * len(dir_ind) + ["rob"] * len(rob_ind)
bnd_ind = np.hstack((dir_ind, rob_ind))
bnd = pp.BoundaryCondition(g, bnd_ind, names)
def u_ex(x):
return np.vstack((x[1], x[0]))
def T_ex(faces):
if np.size(faces) == 0:
return np.atleast_2d(np.array([]))
sigma = np.array([[0, 2], [2, 0]])
T_r = [np.dot(sigma, g.face_normals[:2, f]) for f in faces]
return np.vstack(T_r).T
u_bound = np.zeros((2, g.num_faces))
sgn_n = pp.numerics.fracture_deformation.sign_of_faces(g, neu_ind)
sgn_r = pp.numerics.fracture_deformation.sign_of_faces(g, rob_ind)
u_bound[:, dir_ind] = u_ex(g.face_centers[:, dir_ind])
u_bound[:, neu_ind] = T_ex(neu_ind) * sgn_n
u_bound[:,
rob_ind] = (T_ex(rob_ind) * sgn_r +
robin_weight * u_ex(g.face_centers[:, rob_ind]) *
g.face_areas[rob_ind])
u, T = self.solve_mpsa(g, c, robin_weight, bnd, u_bound)
self.assertTrue(np.allclose(u, u_ex(g.cell_centers).ravel("F")))
self.assertTrue(np.allclose(T,
T_ex(np.arange(g.num_faces)).ravel("F")))
def test_convergence_rt0_2d_iso_simplex_exact(self):
p_ex = lambda pt: 2 * pt[0, :] - 3 * pt[1, :] - 9
u_ex = np.array([-1, 4, 0])
for i in np.arange(5):
g = pp.StructuredTriangleGrid([3 + i] * 2, [1, 1])
g.compute_geometry()
kxx = np.ones(g.num_cells)
perm = pp.SecondOrderTensor(kxx=kxx, kyy=kxx, kzz=1)
bf = g.get_boundary_faces()
bc = pp.BoundaryCondition(g, bf, bf.size * ["dir"])
bc_val = np.zeros(g.num_faces)
bc_val[bf] = p_ex(g.face_centers[:, bf])
vect = np.vstack((g.cell_volumes, g.cell_volumes,
np.zeros(g.num_cells))).ravel(order="F")
solver = pp.RT0(keyword="flow")
specified_parameters = {
"bc": bc,
"bc_values": bc_val,
"second_order_tensor": perm,
"vector_source": vect,
}
data = pp.initialize_default_data(g, {}, "flow",
specified_parameters)
solver.discretize(g, data)
M, rhs = solver.assemble_matrix_rhs(g, data)
up = sps.linalg.spsolve(M, rhs)
p = solver.extract_pressure(g, up, data)
err = np.sum(np.abs(p - p_ex(g.cell_centers)))
self.assertTrue(np.isclose(err, 0))
_ = data[pp.DISCRETIZATION_MATRICES]["flow"][
solver.vector_proj_key]
u = solver.extract_flux(g, up, data)
P0u = solver.project_flux(g, u, data)
err = np.sum(
np.abs(P0u -
np.tile(u_ex, g.num_cells).reshape((3, -1), order="F")))
self.assertTrue(np.isclose(err, 0))
def test_mvem_2d_simplex(self):
g = pp.StructuredTriangleGrid([1, 1], [1, 1])
g.compute_geometry()
kxx = np.ones(g.num_cells)
perm = pp.SecondOrderTensor(kxx=kxx, kyy=kxx, kzz=1)
bf = g.get_boundary_faces()
bc = pp.BoundaryCondition(g, bf, bf.size * ["dir"])
vect = np.vstack(
(2 * g.cell_volumes, 3 * g.cell_volumes, np.zeros(g.num_cells))
).ravel(order="F")
b = self._matrix(g, perm, bc, vect)
b_known = np.array(
[-1.33333333, -1.16666667, 0.33333333, 1.16666667, 1.33333333, 0.0, 0.0]
)
self.assertTrue(np.allclose(b, b_known))
def test_simplex_2d(self):
nx = 1
ny = 1
g = pp.StructuredTriangleGrid([nx, ny], physdims=[1, 1])
g.compute_geometry()
g = make_true_2d(g)
sc_top = pp.fvutils.SubcellTopology(g)
D_g, CC = pp.numerics.fv.mpfa.reconstruct_presssure(g, sc_top, eta=0)
D_g_known = np.array(
[
[-1 / 6, -1 / 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0],
[0, 0, -1 / 6, -1 / 3, 0, 0, 0, 0, 0, 0, 0, 0.0],
[0, 0, 0, 0, 0, 0, -1 / 3, -1 / 6, 0, 0, 0, 0.0],
[0, 0, 0, 0, 0, 0, 0, 0, -1 / 3, -1 / 6, 0, 0.0],
[-1 / 12, 1 / 12, 0, 0, 0, 0, 1 / 12, -1 / 12, 0, 0, 0, 0],
[0, 0, 0, 0, -1 / 12, 1 / 12, 0, 0, 0, 0, 1 / 12, -1 / 12],
[0, 0, 1 / 3, 1 / 6, 0, 0, 0, 0, 0, 0, 0, 0.0],
[0, 0, 0, 0, 1 / 3, 1 / 6, 0, 0, 0, 0, 0, 0.0],
[0, 0, 0, 0, 0, 0, 0, 0, 1 / 6, 1 / 3, 0, 0.0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1 / 6, 1 / 3],
]
)
CC_known = np.array(
[
[1, 0.0],
[1, 0.0],
[0, 1.0],
[0, 1.0],
[0.5, 0.5],
[0.5, 0.5],
[1, 0.0],
[1, 0.0],
[0, 1.0],
[0, 1.0],
]
)
self.assertTrue(np.all(np.abs(D_g - D_g_known).A < 1e-12))
self.assertTrue(np.all(np.abs(CC - CC_known) < 1e-12))
def test_mvem_2d_simplex_surf(self):
g = pp.StructuredTriangleGrid([1, 1], [1, 1])
R = pp.map_geometry.rotation_matrix(-np.pi / 4.0, [1, 1, -1])
g.nodes = np.dot(R, g.nodes)
g.compute_geometry()
kxx = np.ones(g.num_cells)
perm = pp.SecondOrderTensor(kxx=kxx, kyy=kxx, kzz=1)
perm.rotate(R)
bf = g.get_boundary_faces()
bc = pp.BoundaryCondition(g, bf, bf.size * ["dir"])
vect = np.vstack(
(g.cell_volumes, 2 * g.cell_volumes, 0 * g.cell_volumes)
).ravel(order="F")
b = self._matrix(g, perm, bc, vect)
b_known = np.array(
[-0.73570226, -0.82197528, -0.17254603, 0.82197528, 0.73570226, 0.0, 0.0]
)
self.assertTrue(np.allclose(b, b_known))
def test_mixed_bc(self):
"""
We test that we can change the boundary condition in given direction
"""
g = pp.StructuredTriangleGrid([2, 2], physdims=(1, 1))
g.compute_geometry()
bc = pp.BoundaryConditionVectorial(g)
k = pp.FourthOrderTensor(g.dim, np.ones(g.num_cells),
np.ones(g.num_cells))
stress_neu, bound_stress_neu, hf_cell_neu, hf_bound_neu = pp.numerics.fv.mpsa.mpsa(
g, k, bc, hf_disp=True, inverter="python")
faces = g.face_centers[0] > 1 - 1e-10
bc.is_rob[1, faces] = True
bc.is_neu[bc.is_rob] = False
# Full discretization
stress_rob, bound_stress_rob, hf_cell_rob, hf_bound_rob = pp.numerics.fv.mpsa.mpsa(
g, k, bc, hf_disp=True, inverter="python")
# Partiall should give same ressult as full
stress, bound_stress, hf_cell, hf_bound = pp.numerics.fv.mpsa.mpsa_update_partial(
stress_neu,
bound_stress_neu,
g,
k,
bc,
faces=faces,
hf_cell=hf_cell_neu,
hf_bound=hf_bound_neu,
inverter="python",
)
self.assertTrue(np.allclose((stress - stress_rob).data, 0))
self.assertTrue(np.allclose((bound_stress - bound_stress_rob).data, 0))
self.assertTrue(np.allclose((hf_cell - hf_cell_rob).data, 0))
self.assertTrue(np.allclose((hf_bound - hf_bound_rob).data, 0))
def simplex_grid(self, nx=[2, 2]):
g = pp.StructuredTriangleGrid(nx)
g.compute_geometry()
return g
def test_rob(self):
g = pp.StructuredTriangleGrid([2, 2])
basis = np.random.rand(g.dim, g.dim, g.num_faces)
bc = pp.BoundaryConditionVectorial(g, g.get_all_boundary_faces(),
"rob")
self.run_test(g, basis, bc)
def test_neu(self):
g = pp.StructuredTriangleGrid([1, 1])
basis = np.random.rand(g.dim, g.dim, g.num_faces)
bc = pp.BoundaryConditionVectorial(g)
self.run_test(g, basis, bc)
def make_grid(grid, grid_dims, domain, dim):
if grid.lower() == "cart" or grid.lower() == "cartesian":
return pp.CartGrid(grid_dims, domain)
elif (grid.lower() == "simplex"
and dim == 2) or grid.lower() == "triangular":
return pp.StructuredTriangleGrid(grid_dims, domain)
def test_tag_2d_simplex(self):
g = pp.StructuredTriangleGrid([3] * 2, [1] * 2)
self.assertTrue(
np.array_equal(g.tags["fracture_faces"], [False] * g.num_faces))
self.assertTrue(
np.array_equal(g.tags["fracture_nodes"], [False] * g.num_nodes))
self.assertTrue(
np.array_equal(g.tags["tip_faces"], [False] * g.num_faces))
self.assertTrue(
np.array_equal(g.tags["tip_nodes"], [False] * g.num_nodes))
known = np.array(
[
True,
True,
False,
True,
False,
False,
True,
False,
False,
True,
False,
True,
False,
False,
False,
False,
False,
False,
False,
True,
False,
True,
False,
False,
False,
False,
False,
False,
False,
True,
True,
True,
True,
],
dtype=bool,
)
self.assertTrue(np.array_equal(g.tags["domain_boundary_faces"], known))
known = np.array(
[
True,
True,
True,
True,
True,
False,
False,
True,
True,
False,
False,
True,
True,
True,
True,
True,
],
dtype=bool,
)
self.assertTrue(np.array_equal(g.tags["domain_boundary_nodes"], known))
def make_grid(grid, grid_dims, domain):
if grid.lower() == "cart":
return pp.CartGrid(grid_dims, domain)
elif grid.lower() == "triangular":
return pp.StructuredTriangleGrid(grid_dims, domain)
def test_convergence_mvem_2d_ani_simplex(self):
rhs_ex = lambda pt: 14
p_ex = (
lambda pt: 2 * np.power(pt[0, :], 2)
- 6 * np.power(pt[1, :], 2)
+ np.multiply(pt[0, :], pt[1, :])
)
u_ex_0 = lambda pt: -9 * pt[0, :] + 10 * pt[1, :] + 4
u_ex_1 = lambda pt: -6 * pt[0, :] + 23 * pt[1, :] + 5
p_errs_known = np.array(
[
0.2411784823808065,
0.13572349427526526,
0.08688469978140642,
0.060345813825004285,
0.044340156291519606,
]
)
u_errs_known = np.array(
[
1.7264059760345327,
1.3416423116340397,
1.0925566034251672,
0.9198698104736416,
0.7936243780450764,
]
)
for i, p_err_known, u_err_known in zip(
np.arange(5), p_errs_known, u_errs_known
):
g = pp.StructuredTriangleGrid([3 + i] * 2, [1, 1])
g.compute_geometry()
kxx = 2 * np.ones(g.num_cells)
kxy = np.ones(g.num_cells)
perm = pp.SecondOrderTensor(kxx=kxx, kyy=kxx, kxy=kxy, kzz=1)
bf = g.get_boundary_faces()
bc = pp.BoundaryCondition(g, bf, bf.size * ["dir"])
bc_val = np.zeros(g.num_faces)
bc_val[bf] = p_ex(g.face_centers[:, bf])
# Minus sign to move to rhs
source = np.multiply(g.cell_volumes, rhs_ex(g.cell_centers))
vect = np.vstack(
(g.cell_volumes, 2 * g.cell_volumes, np.zeros(g.num_cells))
).ravel(order="F")
solver = pp.MVEM(keyword="flow")
solver_rhs = pp.DualScalarSource(keyword="flow")
specified_parameters = {
"bc": bc,
"bc_values": bc_val,
"second_order_tensor": perm,
"source": source,
"vector_source": vect,
}
data = pp.initialize_default_data(g, {}, "flow", specified_parameters)
solver.discretize(g, data)
solver_rhs.discretize(g, data)
M, rhs_bc = solver.assemble_matrix_rhs(g, data)
_, rhs = solver_rhs.assemble_matrix_rhs(g, data)
up = sps.linalg.spsolve(M, rhs_bc + rhs)
p = solver.extract_pressure(g, up, data)
err = np.sqrt(
np.sum(
np.multiply(g.cell_volumes, np.power(p - p_ex(g.cell_centers), 2))
)
)
self.assertTrue(np.isclose(err, p_err_known))
P = data[pp.DISCRETIZATION_MATRICES]["flow"][solver.vector_proj_key]
u = solver.extract_flux(g, up, data)
P0u = solver.project_flux(g, u, data)
uu_ex_0 = u_ex_0(g.cell_centers)
uu_ex_1 = u_ex_1(g.cell_centers)
uu_ex_2 = np.zeros(g.num_cells)
uu_ex = np.vstack((uu_ex_0, uu_ex_1, uu_ex_2))
err = np.sqrt(
np.sum(
np.multiply(
g.cell_volumes, np.sum(np.power(P0u - uu_ex, 2), axis=0)
)
)
)
self.assertTrue(np.isclose(err, u_err_known))
def test_convergence_mvem_2d_iso_simplex(self):
a = 8 * np.pi ** 2
rhs_ex = lambda pt: np.multiply(
np.sin(2 * np.pi * pt[0, :]), np.sin(2 * np.pi * pt[1, :])
)
p_ex = lambda pt: rhs_ex(pt) / a
u_ex_0 = (
lambda pt: np.multiply(
-np.cos(2 * np.pi * pt[0, :]), np.sin(2 * np.pi * pt[1, :])
)
* 2
* np.pi
/ a
+ 1
)
u_ex_1 = (
lambda pt: np.multiply(
-np.sin(2 * np.pi * pt[0, :]), np.cos(2 * np.pi * pt[1, :])
)
* 2
* np.pi
/ a
)
p_errs_known = np.array(
[
0.007347293666843033,
0.004057878042430692,
0.002576479539795832,
0.0017817307824819935,
0.0013057660031758425,
]
)
u_errs_known = np.array(
[
0.024425617686195774,
0.016806807988931565,
0.012859109258624922,
0.010445238111710832,
0.00881184436169123,
]
)
for i, p_err_known, u_err_known in zip(
np.arange(5), p_errs_known, u_errs_known
):
g = pp.StructuredTriangleGrid([3 + i] * 2, [1, 1])
g.compute_geometry()
kxx = np.ones(g.num_cells)
perm = pp.SecondOrderTensor(kxx=kxx, kyy=kxx, kzz=1)
bf = g.get_boundary_faces()
bc = pp.BoundaryCondition(g, bf, bf.size * ["dir"])
bc_val = np.zeros(g.num_faces)
bc_val[bf] = p_ex(g.face_centers[:, bf])
# Minus sign to move to rhs
source = np.multiply(g.cell_volumes, rhs_ex(g.cell_centers))
vect = np.vstack(
(g.cell_volumes, np.zeros(g.num_cells), np.zeros(g.num_cells))
).ravel(order="F")
solver = pp.MVEM(keyword="flow")
solver_rhs = pp.DualScalarSource(keyword="flow")
specified_parameters = {
"bc": bc,
"bc_values": bc_val,
"second_order_tensor": perm,
"source": source,
"vector_source": vect,
}
data = pp.initialize_default_data(g, {}, "flow", specified_parameters)
solver.discretize(g, data)
solver_rhs.discretize(g, data)
M, rhs_bc = solver.assemble_matrix_rhs(g, data)
_, rhs = solver_rhs.assemble_matrix_rhs(g, data)
up = sps.linalg.spsolve(M, rhs_bc + rhs)
p = solver.extract_pressure(g, up, data)
err = np.sqrt(
np.sum(
np.multiply(g.cell_volumes, np.power(p - p_ex(g.cell_centers), 2))
)
)
self.assertTrue(np.isclose(err, p_err_known))
_ = data[pp.DISCRETIZATION_MATRICES]["flow"][solver.vector_proj_key]
u = solver.extract_flux(g, up, data)
P0u = solver.project_flux(g, u, data)
uu_ex_0 = u_ex_0(g.cell_centers)
uu_ex_1 = u_ex_1(g.cell_centers)
uu_ex_2 = np.zeros(g.num_cells)
uu_ex = np.vstack((uu_ex_0, uu_ex_1, uu_ex_2))
err = np.sqrt(
np.sum(
np.multiply(
g.cell_volumes, np.sum(np.power(P0u - uu_ex, 2), axis=0)
)
)
)
self.assertTrue(np.isclose(err, u_err_known))
self.assertTrue(mg.num_cells == 1)
self.assertTrue(mg.num_sides() == 1)
self.assertTrue(np.all(mg.primary_to_mortar_avg().A == [0, 1, 0]))
self.assertTrue(np.all(mg.primary_to_mortar_int().A == [0, 1, 0]))
self.assertTrue(np.all(mg.secondary_to_mortar_avg().A == [0, 1]))
self.assertTrue(np.all(mg.secondary_to_mortar_int().A == [0, 1]))
@pytest.mark.parametrize(
"g",
[
pp.PointGrid([0, 0, 0]),
pp.CartGrid([2]),
pp.CartGrid([2, 2]),
pp.CartGrid([2, 2, 2]),
pp.StructuredTriangleGrid([2, 2]),
pp.StructuredTetrahedralGrid([1, 1, 1]),
],
)
def test_pickle_grid(g):
"""Test that grids can be pickled. Write, read and compare."""
fn = "tmp.grid"
pickle.dump(g, open(fn, "wb"))
g_read = pickle.load(open(fn, "rb"))
test_utils.compare_grids(g, g_read)
test_utils.delete_file(fn)
@pytest.mark.parametrize("g",[ pp.PointGrid([0, 0, 0]),
