def test_solver_honors_set_time_step(self):
# Given
dt = 0.1
tf = 1.0
pfreq = 1
solver = Solver(integrator=self.integrator,
tf=tf,
dt=dt,
adaptive_timestep=False)
solver.set_print_freq(pfreq)
solver.acceleration_eval = self.a_eval
solver.particles = []
record = []
def _mock_dump_output():
# Record the time at which the solver dumped anything
record.append(solver.t)
solver.dump_output = mock.Mock(side_effect=_mock_dump_output)
# When
solver.set_time_step(0.2)
solver.solve(show_progress=False)
# Then
expected = np.asarray([0.0, 0.2, 0.4, 0.6, 0.8, 1.0])
error_message = "Expected %s, got %s" % (expected, record)
self.assertEqual(len(expected), len(record), error_message)
self.assertTrue(
np.max(np.abs(expected - record)) < 1e-12, error_message)
def test_solver_dumps_output_given_output_at_times(self):
# Given
dt = 0.1
self.integrator.compute_time_step.return_value = dt
tf = 10.05
pfreq = 5
output_at_times = [0.3, 0.35]
solver = Solver(integrator=self.integrator,
tf=tf,
dt=dt,
output_at_times=output_at_times)
solver.set_print_freq(pfreq)
solver.acceleration_eval = self.a_eval
solver.particles = []
# When
record = []
record_dt = []
def _mock_dump_output():
# Record the time at which the solver dumped anything
record.append(solver.t)
# This smells but ...
sd = solver._get_solver_data()
record_dt.append(sd['dt'])
solver.dump_output = mock.Mock(side_effect=_mock_dump_output)
solver.solve(show_progress=False)
# Then
expected = np.asarray([0.0, 0.3, 0.35] +
np.arange(0.45, 10.1, 0.5).tolist() + [10.05])
error_message = "Expected %s, got %s" % (expected, record)
self.assertEqual(len(expected), len(record), error_message)
self.assertTrue(
np.max(np.abs(expected - record)) < 1e-12, error_message)
self.assertEqual(101, solver.count)
# The final timestep should not be a tiny one due to roundoff.
self.assertTrue(solver.dt > 0.1 * 0.25)
npt.assert_array_almost_equal([0.1] * len(record_dt),
record_dt,
decimal=12)
