def analytic_soln(t, initial_conditions):
c1 = initial_conditions[0]
c2 = initial_conditions[1] - 1
return D.stack([
c2 * D.sin(D.to_float(D.asarray(t))) + c1 * D.cos(D.to_float(D.asarray(t))) + D.asarray(t),
c2 * D.cos(D.to_float(D.asarray(t))) - c1 * D.sin(D.to_float(D.asarray(t))) + 1
])
def test_bisection_search_vec():
l1 = [0.0, 1.0, 2.0, 3.0, 5.0, 10.0]
l2 = [0.2, 1.2, 2.2, 3.2, 5.2, 9.2]
expected_l2 = [0, 1, 2, 3, 4, 4]
l3 = [0.9, 1.9, 2.9, 3.9, 5.9, 9.9]
expected_l3 = [0, 1, 2, 3, 4, 4]
l4 = [0.2, 9.9, 2.3, 5.5]
expected_l4 = [0, 4, 2, 4]
assert (D.all(de.utilities.search_bisection_vec(l1, l2) == D.asarray(expected_l2)))
assert (D.all(de.utilities.search_bisection_vec(l1, l3) == D.asarray(expected_l3)))
assert (D.all(de.utilities.search_bisection_vec(l1, l4) == D.asarray(expected_l4)))
def test_asarray():
a = np.array([1.0, 2.0, 3.0])
a_torch = D.array(a)
assert (D.all(a_torch == D.asarray(a)))