def test_initial_condition_constant():
nb_elements = 6
nb_shoot = 10
init_val = np.random.random(nb_elements, )
init = InitialConditions(init_val,
interpolation=InterpolationType.CONSTANT)
init.check_and_adjust_dimensions(nb_elements, nb_shoot)
expected_val = init_val
for i in range(nb_shoot):
np.testing.assert_almost_equal(init.init.evaluate_at(i), expected_val)
def test_initial_condition_each_frame():
nb_elements = 6
nb_shoot = 10
init_val = np.random.random((nb_elements, nb_shoot + 1))
init = InitialConditions(init_val,
interpolation=InterpolationType.EACH_FRAME)
init.check_and_adjust_dimensions(nb_elements, nb_shoot)
for i in range(nb_shoot + 1):
expected_val = init_val[:, i]
np.testing.assert_almost_equal(init.init.evaluate_at(i), expected_val)
def test_initial_condition_linear():
nb_elements = 6
nb_shoot = 10
init_val = np.random.random((nb_elements, 2))
init = InitialConditions(init_val, interpolation=InterpolationType.LINEAR)
init.check_and_adjust_dimensions(nb_elements, nb_shoot)
for i in range(nb_shoot + 1):
expected_val = init_val[:, 0] + (init_val[:, 1] -
init_val[:, 0]) * i / nb_shoot
np.testing.assert_almost_equal(init.init.evaluate_at(i), expected_val)
def test_initial_condition_constant_with_first_and_last_different():
nb_elements = 6
nb_shoot = 10
init_val = np.random.random((nb_elements, 3))
init = InitialConditions(
init_val,
interpolation=InterpolationType.CONSTANT_WITH_FIRST_AND_LAST_DIFFERENT)
init.check_and_adjust_dimensions(nb_elements, nb_shoot)
for i in range(nb_shoot + 1):
if i == 0:
expected_val = init_val[:, 0]
elif i == nb_shoot:
expected_val = init_val[:, 2]
else:
expected_val = init_val[:, 1]
np.testing.assert_almost_equal(init.init.evaluate_at(i), expected_val)
def test_initial_condition_custom():
nb_elements = 6
nb_shoot = 10
def custom_bound_func(current_shooting, val, total_shooting):
# Linear interpolation created with custom bound function
return val[:, 0] + (val[:, 1] -
val[:, 0]) * current_shooting / total_shooting
init_val = np.random.random((nb_elements, 2))
init = InitialConditions(
custom_bound_func,
interpolation=InterpolationType.CUSTOM,
val=init_val,
total_shooting=nb_shoot,
)
init.check_and_adjust_dimensions(nb_elements, nb_shoot)
for i in range(nb_shoot + 1):
expected_val = init_val[:, 0] + (init_val[:, 1] -
init_val[:, 0]) * i / nb_shoot
np.testing.assert_almost_equal(init.init.evaluate_at(i), expected_val)
def test_initial_condition_spline():
nb_shoot = 10
spline_time = np.hstack((0.0, 1.0, 2.2, 6.0))
init_val = np.array([
[0.5, 0.6, 0.2, 0.8],
[0.4, 0.6, 0.8, 0.2],
[0.0, 0.3, 0.2, 0.5],
[0.5, 0.2, 0.9, 0.4],
[0.5, 0.6, 0.2, 0.8],
[0.5, 0.6, 0.2, 0.8],
])
nb_elements = init_val.shape[0]
# Raise if time is not sent
with pytest.raises(RuntimeError):
InitialConditions(init_val, interpolation=InterpolationType.SPLINE)
init = InitialConditions(init_val,
t=spline_time,
interpolation=InterpolationType.SPLINE)
init.check_and_adjust_dimensions(nb_elements, nb_shoot)
time_to_test = [0, nb_shoot // 3, nb_shoot // 2, nb_shoot]
expected_matrix = np.array([
[0.5, 0.4, 0.0, 0.5, 0.5, 0.5],
[
0.33333333, 0.73333333, 0.23333333, 0.66666667, 0.33333333,
0.33333333
],
[
0.32631579, 0.67368421, 0.26315789, 0.79473684, 0.32631579,
0.32631579
],
[0.8, 0.2, 0.5, 0.4, 0.8, 0.8],
]).T
for i, t in enumerate(time_to_test):
expected_val = expected_matrix[:, i]
np.testing.assert_almost_equal(init.init.evaluate_at(t), expected_val)