def test_pidon_operator_on_spherical_pde():
set_random_seed(0)
diff_eq = DiffusionEquation(3)
mesh = Mesh(
[(1., 11.), (0., 2 * np.pi), (.25 * np.pi, .75 * np.pi)],
[2., np.pi / 5., np.pi / 4],
CoordinateSystem.SPHERICAL)
bcs = [
(DirichletBoundaryCondition(
lambda x, t: np.ones((len(x), 1)), is_static=True),
DirichletBoundaryCondition(
lambda x, t: np.full((len(x), 1), 1. / 11.), is_static=True)),
(NeumannBoundaryCondition(
lambda x, t: np.zeros((len(x), 1)), is_static=True),
NeumannBoundaryCondition(
lambda x, t: np.zeros((len(x), 1)), is_static=True)),
(NeumannBoundaryCondition(
lambda x, t: np.zeros((len(x), 1)), is_static=True),
NeumannBoundaryCondition(
lambda x, t: np.zeros((len(x), 1)), is_static=True))
]
cp = ConstrainedProblem(diff_eq, mesh, bcs)
ic = ContinuousInitialCondition(cp, lambda x: 1. / x[:, :1])
t_interval = (0., .5)
ivp = InitialValueProblem(cp, t_interval, ic)
sampler = UniformRandomCollocationPointSampler()
pidon = PIDONOperator(sampler, .001, True)
training_loss_history, test_loss_history = pidon.train(
cp,
t_interval,
training_data_args=DataArgs(
y_0_functions=[ic.y_0],
n_domain_points=20,
n_boundary_points=10,
n_batches=1
),
model_args=ModelArgs(
latent_output_size=20,
branch_hidden_layer_sizes=[30, 30],
trunk_hidden_layer_sizes=[30, 30],
),
optimization_args=OptimizationArgs(
optimizer=optimizers.Adam(learning_rate=2e-5),
epochs=3,
verbose=False
)
)
assert len(training_loss_history) == 3
for i in range(2):
assert np.all(
training_loss_history[i + 1].weighted_total_loss.numpy() <
training_loss_history[i].weighted_total_loss.numpy())
solution = pidon.solve(ivp)
assert solution.d_t == .001
assert solution.discrete_y().shape == (500, 6, 11, 3, 1)
def test_discrete_initial_condition_2d_pde():
diff_eq = WaveEquation(2)
mesh = Mesh([(0., 2.), (0., 2.)], [1., 1.])
bcs = [(DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (0., 2.)), is_static=True),
DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (1., 2.)), is_static=True)),
(DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (3., 2.)), is_static=True),
DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (4., 2.)), is_static=True))]
cp = ConstrainedProblem(diff_eq, mesh, bcs)
initial_condition = DiscreteInitialCondition(cp, np.zeros((3, 3, 2)), True)
y = initial_condition.y_0(np.array([1.5, .5]).reshape((1, 2)))
assert np.allclose(y, [1.75, 1.5])
y_0_vertices = initial_condition.discrete_y_0(True)
assert y_0_vertices.shape == (3, 3, 2)
assert np.all(y_0_vertices[0, 1:-1, 0] == 0.)
assert np.all(y_0_vertices[0, 1:-1, 1] == 2.)
assert np.all(y_0_vertices[-1, 1:-1, 0] == 1.)
assert np.all(y_0_vertices[-1, 1:-1, 1] == 2.)
assert np.all(y_0_vertices[:, 0, 0] == 3.)
assert np.all(y_0_vertices[:, 0, 1] == 2.)
assert np.all(y_0_vertices[:, -1, 0] == 4.)
assert np.all(y_0_vertices[:, -1, 1] == 2.)
assert np.all(y_0_vertices[1:-1, 1:-1, :] == 0.)
y_0_cell_centers = initial_condition.discrete_y_0(False)
assert y_0_cell_centers.shape == (2, 2, 2)
def test_fdm_operator_on_2d_pde():
diff_eq = NavierStokesEquation(5000.)
mesh = Mesh([(0., 10.), (0., 10.)], [1., 1.])
bcs = [(DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (1., .1, None, None)),
is_static=True),
DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (0., 0., None, None)),
is_static=True)),
(DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (0., 0., None, None)),
is_static=True),
DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (0., 0., None, None)),
is_static=True))]
cp = ConstrainedProblem(diff_eq, mesh, bcs)
ic = ContinuousInitialCondition(cp, lambda x: np.zeros((len(x), 4)))
ivp = InitialValueProblem(cp, (0., 10.), ic)
op = FDMOperator(RK4(), ThreePointCentralDifferenceMethod(), .25)
solution = op.solve(ivp)
assert solution.vertex_oriented
assert solution.d_t == .25
assert solution.discrete_y().shape == (40, 11, 11, 4)
assert solution.discrete_y(False).shape == (40, 10, 10, 4)
def test_gaussian_initial_condition_2d_pde():
diff_eq = WaveEquation(2)
mesh = Mesh([(0., 2.), (0., 2.)], [1., 1.])
bcs = [(DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (0., 2.)), is_static=True),
DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (1., 2.)), is_static=True)),
(DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (3., 2.)), is_static=True),
DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (4., 2.)), is_static=True))]
cp = ConstrainedProblem(diff_eq, mesh, bcs)
initial_condition = GaussianInitialCondition(cp, [
(np.array([1., 1.]), np.array([[1., 0.], [0., 1.]])),
(np.array([1., 1.]), np.array([[.75, .25], [.25, .75]])),
], [1., 2.])
x_coordinates = np.array([[1., 1.], [.5, 1.5]])
expected_y_0 = [[.15915494, .45015816], [.12394999, .27303472]]
actual_y_0 = initial_condition.y_0(x_coordinates)
assert np.allclose(actual_y_0, expected_y_0)
expected_vertex_discrete_y_0 = [[[3., 2.], [0., 2.], [4., 2.]],
[[3., 2.], [.15915494, .45015816],
[4., 2.]], [[3., 2.], [1., 2.], [4., 2.]]]
actual_vertex_discrete_y_0 = initial_condition.discrete_y_0(True)
assert np.allclose(actual_vertex_discrete_y_0,
expected_vertex_discrete_y_0)
expected_cell_discrete_y_0 = [[[.12394999, .35058353],
[.12394999, .27303472]],
[[.12394999, .27303472],
[.12394999, .35058353]]]
actual_cell_discrete_y_0 = initial_condition.discrete_y_0(False)
assert np.allclose(actual_cell_discrete_y_0, expected_cell_discrete_y_0)
def test_continuous_initial_condition_1d_pde():
diff_eq = DiffusionEquation(1)
mesh = Mesh([(0., 20.)], [.1])
bcs = [(DirichletBoundaryCondition(lambda x, t: np.zeros((len(x), 1)),
is_static=True),
DirichletBoundaryCondition(lambda x, t: np.full((len(x), 1), 1.5),
is_static=True))]
cp = ConstrainedProblem(diff_eq, mesh, bcs)
initial_condition = ContinuousInitialCondition(
cp, lambda x: np.exp(-np.square(np.array(x) - 10.) / (2 * 5**2)))
assert np.isclose(initial_condition.y_0(np.full((1, 1), 10.)), 1.)
assert np.isclose(
initial_condition.y_0(np.full((1, 1),
np.sqrt(50) + 10.)), np.e**-1)
assert np.allclose(initial_condition.y_0(np.full((5, 1), 10.)),
np.ones((5, 1)))
y_0_vertices = initial_condition.discrete_y_0(True)
assert y_0_vertices.shape == (201, 1)
assert y_0_vertices[0, 0] == 0.
assert y_0_vertices[-1, 0] == 1.5
assert y_0_vertices[100, 0] == 1.
assert np.all(0. < y_0_vertices[1:100, 0]) \
and np.all(y_0_vertices[1:100, 0] < 1.)
assert np.all(0. < y_0_vertices[101:-1, 0]) \
and np.all(y_0_vertices[101:-1, 0] < 1.)
y_0_cell_centers = initial_condition.discrete_y_0(False)
assert y_0_cell_centers.shape == (200, 1)
assert np.all(0. < y_0_cell_centers) and np.all(y_0_cell_centers < 1.)
def test_pidon_operator_on_pde_system():
set_random_seed(0)
diff_eq = NavierStokesEquation()
mesh = Mesh([(-2.5, 2.5), (0., 4.)], [1., 1.])
ic_function = vectorize_ic_function(lambda x: [
2. * x[0] - 4.,
2. * x[0] ** 2 + 3. * x[1] - x[0] * x[1] ** 2,
4. * x[0] - x[1] ** 2,
2. * x[0] * x[1] - 3.
])
bcs = [
(DirichletBoundaryCondition(
lambda x, t: ic_function(x),
is_static=True),
DirichletBoundaryCondition(
lambda x, t: ic_function(x),
is_static=True))
] * 2
cp = ConstrainedProblem(diff_eq, mesh, bcs)
ic = ContinuousInitialCondition(cp, ic_function)
t_interval = (0., .5)
ivp = InitialValueProblem(cp, t_interval, ic)
sampler = UniformRandomCollocationPointSampler()
pidon = PIDONOperator(sampler, .001, True)
training_loss_history, test_loss_history = pidon.train(
cp,
t_interval,
training_data_args=DataArgs(
y_0_functions=[ic.y_0],
n_domain_points=20,
n_boundary_points=10,
n_batches=1
),
model_args=ModelArgs(
latent_output_size=20,
branch_hidden_layer_sizes=[20, 20],
trunk_hidden_layer_sizes=[20, 20],
),
optimization_args=OptimizationArgs(
optimizer=optimizers.Adam(learning_rate=1e-5),
epochs=3,
verbose=False
)
)
assert len(training_loss_history) == 3
for i in range(2):
assert np.all(
training_loss_history[i + 1].weighted_total_loss.numpy() <
training_loss_history[i].weighted_total_loss.numpy())
solution = pidon.solve(ivp)
assert solution.d_t == .001
assert solution.discrete_y().shape == (500, 6, 5, 4)
def test_dirichlet_boundary_condition():
bc = DirichletBoundaryCondition(lambda x, t: t * x)
assert not bc.is_static
assert bc.has_y_condition
assert not bc.has_d_y_condition
assert np.allclose(
bc._y_condition(np.ones((2, 1)), 5.),
np.full((2, 1), 5.))
with pytest.raises(RuntimeError):
bc.d_y_condition(np.ones((2, 1)), 5.)
def test_cp_pde_with_wrong_boundary_constraint_width():
diff_eq = WaveEquation(2)
mesh = Mesh([(0., 5.), (-5., 5.)], [.1, .2])
bcs = [(DirichletBoundaryCondition(lambda x, t: np.zeros((len(x), 1)),
is_static=True), ) * 2] * 2
with pytest.raises(ValueError):
ConstrainedProblem(diff_eq, mesh, bcs)
bcs = [(DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: [0.]), is_static=True), ) * 2] * 2
with pytest.raises(ValueError):
ConstrainedProblem(diff_eq, mesh, bcs)
def test_cp_pde_with_wrong_boundary_constraint_length():
diff_eq = DiffusionEquation(2)
mesh = Mesh([(0., 5.), (-5., 5.)], [.1, .2])
static_bcs = [(DirichletBoundaryCondition(lambda x, t: np.zeros((13, 1)),
is_static=True), ) * 2] * 2
with pytest.raises(ValueError):
ConstrainedProblem(diff_eq, mesh, static_bcs)
dynamic_bcs = [
(DirichletBoundaryCondition(lambda x, t: np.zeros((13, 1))), ) * 2
] * 2
cp = ConstrainedProblem(diff_eq, mesh, dynamic_bcs)
with pytest.raises(ValueError):
cp.create_boundary_constraints(True, 0.)
def test_discrete_initial_condition_pde_with_wrong_shape():
diff_eq = WaveEquation(1)
mesh = Mesh([(0., 10.)], [1.])
bcs = [(DirichletBoundaryCondition(lambda x: np.zeros((len(x), 2))), ) * 2]
cp = ConstrainedProblem(diff_eq, mesh, bcs)
with pytest.raises(ValueError):
DiscreteInitialCondition(cp, np.zeros((10, 2)), vertex_oriented=True)
def test_continuous_initial_condition_pde_with_wrong_shape():
diff_eq = WaveEquation(1)
mesh = Mesh([(0., 10.)], [1.])
bcs = [(DirichletBoundaryCondition(lambda x: np.zeros((len(x), 2))), ) * 2]
cp = ConstrainedProblem(diff_eq, mesh, bcs)
with pytest.raises(ValueError):
ContinuousInitialCondition(cp, lambda x: np.zeros((3, 2)))
def test_gaussian_initial_condition_pde_with_wrong_means_and_cov_length():
diff_eq = WaveEquation(1)
mesh = Mesh([(0., 10.)], [1.])
bcs = [(DirichletBoundaryCondition(lambda x: np.zeros((len(x), 2))), ) * 2]
cp = ConstrainedProblem(diff_eq, mesh, bcs)
with pytest.raises(ValueError):
GaussianInitialCondition(cp, [(np.array([1.]), np.array([[1.]]))] * 1)
def test_auto_regression_operator_on_pde():
set_random_seed(0)
diff_eq = WaveEquation(2)
mesh = Mesh([(-5., 5.), (-5., 5.)], [1., 1.])
bcs = [(DirichletBoundaryCondition(lambda x, t: np.zeros((len(x), 2)),
is_static=True),
DirichletBoundaryCondition(lambda x, t: np.zeros((len(x), 2)),
is_static=True))] * 2
cp = ConstrainedProblem(diff_eq, mesh, bcs)
ic = GaussianInitialCondition(
cp, [(np.array([0., 2.5]), np.array([[.1, 0.], [0., .1]]))] * 2,
[3., .0])
ivp = InitialValueProblem(cp, (0., 10.), ic)
oracle = FDMOperator(RK4(), ThreePointCentralDifferenceMethod(), .1)
ref_solution = oracle.solve(ivp)
ml_op = AutoRegressionOperator(2.5, True)
ml_op.train(
ivp, oracle,
SKLearnKerasRegressor(
DeepONet([
np.prod(cp.y_shape(True)).item(), 100, 50,
diff_eq.y_dimension * 10
], [1 + diff_eq.x_dimension, 50, 50, diff_eq.y_dimension * 10],
diff_eq.y_dimension),
optimizer=optimizers.Adam(
learning_rate=optimizers.schedules.ExponentialDecay(
1e-2, decay_steps=500, decay_rate=.95)),
batch_size=968,
epochs=500,
), 20, lambda t, y: y + np.random.normal(0., t / 75., size=y.shape))
ml_solution = ml_op.solve(ivp)
assert ml_solution.vertex_oriented
assert ml_solution.d_t == 2.5
assert ml_solution.discrete_y().shape == (4, 11, 11, 2)
diff = ref_solution.diff([ml_solution])
assert np.all(diff.matching_time_points == np.linspace(2.5, 10., 4))
assert np.max(np.abs(diff.differences[0])) < .5
def test_ode_operator_on_pde():
diff_eq = DiffusionEquation(1, 1.5)
mesh = Mesh([(0., 10.)], [.1])
bcs = [
(NeumannBoundaryCondition(lambda x, t: np.zeros((len(x), 1))),
DirichletBoundaryCondition(lambda x, t: np.zeros((len(x), 1)))),
]
cp = ConstrainedProblem(diff_eq, mesh, bcs)
ic = GaussianInitialCondition(cp, [(np.array([5.]), np.array([[2.5]]))],
[20.])
ivp = InitialValueProblem(cp, (0., 10.), ic)
op = ODEOperator('RK23', 2.5e-3)
with pytest.raises(ValueError):
op.solve(ivp)
def test_fdm_operator_on_pde_with_dynamic_boundary_conditions():
diff_eq = DiffusionEquation(1, 1.5)
mesh = Mesh([(0., 10.)], [1.])
bcs = [
(NeumannBoundaryCondition(lambda x, t: np.zeros((len(x), 1))),
DirichletBoundaryCondition(lambda x, t: np.full((len(x), 1), t / 5.))
),
]
cp = ConstrainedProblem(diff_eq, mesh, bcs)
ic = GaussianInitialCondition(cp, [(np.array([5.]), np.array([[2.5]]))],
[20.])
ivp = InitialValueProblem(cp, (0., 10.), ic)
op = FDMOperator(RK4(), ThreePointCentralDifferenceMethod(), .5)
solution = op.solve(ivp)
y = solution.discrete_y()
assert solution.vertex_oriented
assert solution.d_t == .5
assert y.shape == (20, 11, 1)
assert solution.discrete_y(False).shape == (20, 10, 1)
assert np.isclose(y[0, -1, 0], .1)
assert np.isclose(y[-1, -1, 0], 2.)
def test_cp_2d_pde():
diff_eq = WaveEquation(2)
mesh = Mesh([(2., 6.), (-3., 3.)], [.1, .2])
bcs = ((DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (999., None)), is_static=True),
NeumannBoundaryCondition(
vectorize_bc_function(lambda x, t: (100., -100.)),
is_static=True)),
(NeumannBoundaryCondition(
vectorize_bc_function(lambda x, t: (-x[0], None)),
is_static=True),
DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (x[0], x[1])),
is_static=True)))
cp = ConstrainedProblem(diff_eq, mesh, bcs)
assert cp.are_all_boundary_conditions_static
assert cp.are_there_boundary_conditions_on_y
y_vertices = np.full(cp.y_shape(True), 13.)
apply_constraints_along_last_axis(cp.static_y_vertex_constraints,
y_vertices)
assert np.all(y_vertices[0, :-1, 0] == 999.)
assert np.all(y_vertices[0, :-1, 1] == 13.)
assert np.all(y_vertices[-1, :-1, :] == 13.)
assert np.all(y_vertices[1:, 0, :] == 13.)
assert np.allclose(y_vertices[:, -1, 0],
np.linspace(2., 6., y_vertices.shape[0]))
assert np.all(y_vertices[:, -1, 1] == 3.)
y_vertices = np.zeros(cp.y_shape(True))
diff = ThreePointCentralDifferenceMethod()
d_y_boundary_constraints = cp.static_boundary_vertex_constraints[1]
d_y_0_over_d_x_0 = diff.gradient(y_vertices[..., :1], mesh, 0,
d_y_boundary_constraints[:, :1])
assert np.all(d_y_0_over_d_x_0[-1, :, :] == 100.)
assert np.all(d_y_0_over_d_x_0[:-1, :, :] == 0.)
d_y_0_over_d_x_1 = diff.gradient(y_vertices[..., :1], mesh, 1,
d_y_boundary_constraints[:, :1])
assert np.allclose(d_y_0_over_d_x_1[:, 0, 0],
np.linspace(-2., -6., y_vertices.shape[0]))
assert np.all(d_y_0_over_d_x_1[:, 1:, :] == 0.)
d_y_1_over_d_x_0 = diff.gradient(y_vertices[..., 1:], mesh, 0,
d_y_boundary_constraints[:, 1:])
assert np.all(d_y_1_over_d_x_0[-1, :, :] == -100.)
assert np.all(d_y_1_over_d_x_0[:-1, :, :] == 0.)
d_y_1_over_d_x_1 = diff.gradient(y_vertices[..., 1:], mesh, 1,
d_y_boundary_constraints[:, 1:])
assert np.all(d_y_1_over_d_x_1 == 0.)
y_boundary_cell_constraints = cp.static_boundary_cell_constraints[0]
assert np.all(y_boundary_cell_constraints[0, 0][0].mask == [True] *
cp.y_cells_shape[1])
assert np.all(y_boundary_cell_constraints[0, 0][0].values == 999.)
assert np.all(y_boundary_cell_constraints[0, 1][0].mask == [False] *
cp.y_cells_shape[1])
assert y_boundary_cell_constraints[0, 1][0].values.size == 0
assert np.all(y_boundary_cell_constraints[1, 0][1].mask == [True] *
cp.y_cells_shape[0])
assert np.allclose(y_boundary_cell_constraints[1, 0][1].values,
np.linspace(2.05, 5.95, cp.y_cells_shape[0]))
assert np.all(y_boundary_cell_constraints[1, 1][1].mask == [True] *
cp.y_cells_shape[0])
assert np.all(y_boundary_cell_constraints[1, 1][1].values == 3.)
assert y_boundary_cell_constraints[1, 0][0] is None
def test_cp_3d_pde():
mesh = Mesh([(2., 6.), (-3., 3.), (10., 12.)], [.1, .2, .5])
assert mesh.shape(True) == (41, 31, 5)
assert mesh.shape(False) == (40, 30, 4)
diff_eq = WaveEquation(3)
cp = ConstrainedProblem(
diff_eq, mesh,
((DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (999., None)), is_static=True),
NeumannBoundaryCondition(
vectorize_bc_function(lambda x, t: (None, None)),
is_static=True)),
(DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (0., 0.)), is_static=True),
NeumannBoundaryCondition(lambda x, t: np.full((len(x), 2), t))),
(NeumannBoundaryCondition(lambda x, t: -x[:, :2] * x[:, 1:3],
is_static=True),
DirichletBoundaryCondition(
vectorize_bc_function(lambda x, t: (-999., None))))))
assert cp.y_shape(True) == (41, 31, 5, 2)
assert cp.y_shape(False) == (40, 30, 4, 2)
assert not cp.are_all_boundary_conditions_static
assert cp.are_there_boundary_conditions_on_y
assert cp.static_y_vertex_constraints.shape == (2, )
y = np.full(cp._y_vertices_shape, -1)
cp.static_y_vertex_constraints[0].apply(y[..., :1])
cp.static_y_vertex_constraints[1].apply(y[..., 1:])
assert np.all(y[0, 1:, :, 0] == 999.)
assert np.all(y[:, 0, :, 0] == 0.)
assert np.all(y[1:, 1:, :, 0] == -1.)
assert np.all(y[:, 0, :, 1] == 0.)
assert np.all(y[:, 1:, :, 1] == -1.)
vertex_boundary_constraints = cp.static_boundary_vertex_constraints
cell_boundary_constraints = cp.static_boundary_cell_constraints
for y_boundary_constraints in \
[vertex_boundary_constraints[0], cell_boundary_constraints[0]]:
assert y_boundary_constraints.shape == (3, 2)
assert y_boundary_constraints[0, 0][0] is not None
assert y_boundary_constraints[0, 1][0] is not None
assert y_boundary_constraints[0, 0][1] is None
assert y_boundary_constraints[0, 1][1] is None
assert y_boundary_constraints[1, 0][0] is not None
assert y_boundary_constraints[1, 1][0] is not None
assert y_boundary_constraints[1, 0][1] is None
assert y_boundary_constraints[1, 1][1] is None
assert y_boundary_constraints[2, 0][0] is None
assert y_boundary_constraints[2, 1][0] is None
assert y_boundary_constraints[2, 0][1] is None
assert y_boundary_constraints[2, 1][1] is None
for d_y_boundary_constraints in \
[vertex_boundary_constraints[1], cell_boundary_constraints[1]]:
assert d_y_boundary_constraints.shape == (3, 2)
assert d_y_boundary_constraints[0, 0][0] is None
assert d_y_boundary_constraints[0, 1][0] is None
assert d_y_boundary_constraints[0, 0][1] is not None
assert d_y_boundary_constraints[0, 1][1] is not None
assert d_y_boundary_constraints[1, 0][0] is None
assert d_y_boundary_constraints[1, 1][0] is None
assert d_y_boundary_constraints[1, 0][1] is None
assert d_y_boundary_constraints[1, 1][1] is None
assert d_y_boundary_constraints[2, 0][0] is not None
assert d_y_boundary_constraints[2, 1][0] is not None
assert d_y_boundary_constraints[2, 0][1] is None
assert d_y_boundary_constraints[2, 1][1] is None
new_vertex_boundary_constraints = cp.create_boundary_constraints(True, 1.)
new_y_boundary_constraints = new_vertex_boundary_constraints[0]
new_d_y_boundary_constraints = new_vertex_boundary_constraints[1]
assert new_y_boundary_constraints[2, 0][1] is not None
assert new_y_boundary_constraints[2, 1][1] is not None
assert new_d_y_boundary_constraints[1, 0][1] is not None
assert new_d_y_boundary_constraints[1, 1][1] is not None
d_y_boundary = np.full((41, 1, 5, 2), np.nan)
new_d_y_boundary_constraints[1, 0][1].apply(d_y_boundary[..., :1])
new_d_y_boundary_constraints[1, 1][1].apply(d_y_boundary[..., 1:])
assert np.all(d_y_boundary == 1.)
new_y_vertex_constraints = \
cp.create_y_vertex_constraints(new_y_boundary_constraints)
assert new_y_vertex_constraints.shape == (2, )
y = np.full(cp._y_vertices_shape, -1)
new_y_vertex_constraints[0].apply(y[..., :1])
new_y_vertex_constraints[1].apply(y[..., 1:])
assert np.all(y[0, 1:, :-1, 0] == 999.)
assert np.all(y[:, 0, :-1, 0] == 0.)
assert np.all(y[:, :, -1, 0] == -999.)
assert np.all(y[1:, 1:, :-1, 0] == -1.)
assert np.all(y[:, 0, :, 1] == 0.)
assert np.all(y[:, 1:, :, 1] == -1.)
