def test_make_incompressible_gradients_equal_tf_torch(self):
DOMAIN = Domain(x=16, y=16, boundaries=OPEN, bounds=Box[0:100, 0:100]) # TODO CLOSED solve fails because div is not subtracted from dx
velocity0 = DOMAIN.staggered_grid(Noise(vector=2))
grads = []
for backend in [TF_BACKEND, TORCH_BACKEND]:
with backend:
velocity = param = velocity0.with_(values=math.tensor(velocity0.values))
with math.record_gradients(param.values):
solve = math.LinearSolve()
velocity, _, _, _ = fluid.make_incompressible(velocity, DOMAIN, solve_params=solve)
loss = field.l2_loss(velocity)
assert math.isfinite(loss)
grad = math.gradients(loss, param.values)
assert math.all(math.isfinite(grad))
grads.append(grad)
math.assert_close(*grads, abs_tolerance=1e-5)
def lies_inside(self, location):
lower, upper = math.batch_align([self.lower, self.upper], 1, location)
bool_inside = (location >= lower) & (location <= upper)
return math.all(bool_inside, axis=-1, keepdims=True)
def lies_inside(self, location):
bool_inside = (location >= self.lower) & (location <= self.upper)
return math.all(bool_inside, 'vector')
def __eq__(self, other):
return isinstance(other,
Scene) and math.all(other._paths == self._paths)
def value_at(self, global_position):
lower, upper = math.batch_align([self.lower, self.upper], 1,
global_position)
bool_inside = (global_position >= lower) & (global_position <= upper)
bool_inside = math.all(bool_inside, axis=-1, keepdims=True)
return math.to_float(bool_inside)
def make_incompressible(velocity: Grid,
domain: Domain,
obstacles: tuple or list = (),
solve_params: math.LinearSolve = math.LinearSolve(
None, 1e-3),
pressure_guess: CenteredGrid = None):
"""
Projects the given velocity field by solving for the pressure and subtracting its gradient.
This method is similar to :func:`field.divergence_free()` but differs in how the boundary conditions are specified.
Args:
velocity: Vector field sampled on a grid
domain: Used to specify boundary conditions
obstacles: List of Obstacles to specify boundary conditions inside the domain (Default value = ())
pressure_guess: Initial guess for the pressure solve
solve_params: Parameters for the pressure solve
Returns:
velocity: divergence-free velocity of type `type(velocity)`
pressure: solved pressure field, `CenteredGrid`
iterations: Number of iterations required to solve for the pressure
divergence: divergence field of input velocity, `CenteredGrid`
"""
input_velocity = velocity
active = domain.grid(
HardGeometryMask(~union(*[obstacle.geometry
for obstacle in obstacles])),
extrapolation=domain.boundaries['active_extrapolation'])
accessible = domain.grid(
active, extrapolation=domain.boundaries['accessible_extrapolation'])
hard_bcs = field.stagger(accessible,
math.minimum,
domain.boundaries['accessible_extrapolation'],
type=type(velocity))
velocity = layer_obstacle_velocities(velocity * hard_bcs, obstacles).with_(
extrapolation=domain.boundaries['near_vector_extrapolation'])
div = divergence(velocity)
if domain.boundaries[
'near_vector_extrapolation'] == math.extrapolation.BOUNDARY:
div -= field.mean(div)
# Solve pressure
def laplace(p):
grad = gradient(p, type(velocity))
grad *= hard_bcs
grad = grad.with_(
extrapolation=domain.boundaries['near_vector_extrapolation'])
div = divergence(grad)
lap = where(active, div, p)
return lap
pressure_guess = pressure_guess if pressure_guess is not None else domain.scalar_grid(
0)
converged, pressure, iterations = field.solve(laplace,
y=div,
x0=pressure_guess,
solve_params=solve_params,
constants=[active, hard_bcs])
if math.all_available(converged) and not math.all(converged):
raise AssertionError(
f"pressure solve did not converge after {iterations} iterations\nResult: {pressure.values}"
)
# Subtract grad pressure
gradp = field.gradient(pressure, type=type(velocity)) * hard_bcs
velocity = (velocity -
gradp).with_(extrapolation=input_velocity.extrapolation)
return velocity, pressure, iterations, div
def lies_inside(self, location):
bool_inside = (location >= self.lower) & (location <= self.upper)
bool_inside = math.all(bool_inside, 'vector')
bool_inside = math.any(
bool_inside, self.shape.instance) # union for instance dimensions
return bool_inside
def __eq__(self, other):
return isinstance(other, Sphere) \
and self._shape == other.shape \
and math.all(self._radius == other.radius) \
and math.all(self._center == other.center)
def test_all(self):
for backend in BACKENDS:
with backend:
math.assert_close(math.all(math.tensor([[False, True], [True, True]], spatial('y,x')), dim='x'), [False, True])
math.assert_close(math.all(math.tensor([[False, True], [True, True]], spatial('y,x')), dim='x,y'), False)
math.assert_close(math.all(math.tensor([[False, True], [True, True]], spatial('y,x'))), False)
