def test_addition_centered_grid(self):
"""add one field to another"""
shape = [32, 27]
for boundary in [CLOSED, PERIODIC, OPEN]:
domain = Domain(shape, boundaries=(boundary, boundary))
centered_grid = CenteredGrid.sample(1, domain)
result_array = (centered_grid + centered_grid).data
np.testing.assert_array_equal(result_array, 2)
def test_subtraction_centered_grid(self):
"""subtract one field from another"""
shape = [32, 27]
for boundary in [CLOSED, PERIODIC, OPEN]:
domain = Domain(shape, boundaries=(boundary, boundary))
centered_grid = CenteredGrid.sample(Noise(), domain)
result_array = (centered_grid - centered_grid).data
np.testing.assert_array_equal(result_array, 0)
def test_division_centered_grid(self):
"""divide one field by another"""
shape = [32, 27]
for boundary in [CLOSED, PERIODIC, OPEN]:
domain = Domain(shape, boundaries=(boundary, boundary))
centered_grid = CenteredGrid.sample(2, domain)
result_array = (centered_grid / centered_grid.copied_with(
data=4 * np.ones([1] + shape + [1]))).data
np.testing.assert_array_equal(result_array, 1. / 2)
def test_multiplication_centered_grid(self):
"""multiply one field with another"""
shape = [32, 27]
for boundary in [CLOSED, PERIODIC, OPEN]:
domain = Domain(shape, boundaries=(boundary, boundary))
centered_grid = CenteredGrid.sample(1, domain)
result_array = (centered_grid * centered_grid.copied_with(
data=2 * np.ones([1] + shape + [1]))).data
np.testing.assert_array_equal(result_array, 2)
def test_reconst(self, set_accuracy=1e-5, shape=[40, 40], first_order_tolerance=3, second_order_tolerance=40,
boundary_list=[PERIODIC, OPEN, CLOSED]):
for boundary in boundary_list:
domain = Domain(shape, boundaries=(boundary, boundary))
solver_list = [
('SparseCG', lambda field: poisson_solve(field, domain, SparseCG(accuracy=set_accuracy)), lambda field: field.laplace()),
('GeometricCG', lambda field: poisson_solve(field, domain, GeometricCG(accuracy=set_accuracy)), lambda field: field.laplace()),
#('SparseSciPy', lambda field: poisson_solve(field, domain, SparseSciPy()), lambda field: field.laplace()),
# ('Fourier', lambda field: poisson_solve(field, domain, Fourier()))] # TODO: poisson_solve() causes resolution to be empty
('FFT', math.fourier_poisson, math.fourier_laplace)]
in_data = CenteredGrid.sample(Noise(), domain)
sloped_data = (np.array([np.arange(shape[1]) for _ in range(shape[0])]).reshape([1] + shape + [1]) / 10 + 1)
in_data = in_data.copied_with(data=sloped_data)
for name, solver, laplace in solver_list:
print('Testing {} boundary with {} solver... '.format(boundary, name)),
_test_reconstruction_first_order(in_data, solver, laplace, set_accuracy, name, first_order_tolerance=first_order_tolerance)
_test_reconstruction_second_order(in_data, solver, laplace, set_accuracy, name, second_order_tolerance=second_order_tolerance)
print('Testing {} boundary with {} solver... '.format(boundary, 'higher order FFT')),
_run_higher_order_fft_reconstruction(in_data, set_accuracy, order=2, tolerance=second_order_tolerance)
def _test_random_periodic(solver):
domain = Domain([40, 32], boundaries=PERIODIC)
div = domain.centered_grid(Noise())
div_ = poisson_solve(div, domain, solver)[0].laplace()
np.testing.assert_almost_equal(div.data, div_.data, decimal=3)
domain = Domain([40, 32], boundaries=PERIODIC)
div = domain.centered_grid(Noise())
div_ = poisson_solve(div, domain, solver)[0].laplace()
np.testing.assert_almost_equal(div.data, div_.data, decimal=3)
def _test_all(solver):
for domain in DOMAINS:
_test_solve_no_obstacles(domain, solver)
_test_random_closed(solver)
_test_random_open(solver)
_test_random_periodic(solver)
DOMAINS = [
Domain([4, 5], boundaries=CLOSED),
Domain([4, 5], boundaries=OPEN),
Domain([4, 5], boundaries=PERIODIC),
Domain([4, 5], boundaries=[CLOSED, PERIODIC]),
Domain([4, 5], boundaries=[CLOSED, OPEN]),
Domain([4, 5], boundaries=[PERIODIC, OPEN]),
]
class TestPoissonSolve(TestCase):
def test_equal_results(self):
data_in = _generate_examples()
for domain in DOMAINS:
pressure_fields = [poisson_solve(domain.centered_grid(data_in), domain, solver=solver)[0].data
for solver in [SparseCG(), GeometricCG()]]