def test_method_from_string(self):
"""Test method_from_string"""
method = method_from_string('scipy-RK45')
self.assertTrue(method == ScipyODE)
method = method_from_string('zvode-adams')
self.assertTrue(method == QiskitZVODE)
def test_RK4(self):
"""Run tests on RK4 fixed-step solver."""
ode_method = method_from_string('RK4')
options = DE_Options(max_dt=10**-3)
# run on matrix problem
solver = ode_method(t0=self.t0,
y0=self.y0,
rhs=self.rhs,
options=options)
solver.integrate(1.)
expected = expm(-1j * np.pi * self.X)
# set the comparison tolerance to be somewhat lenient
self.assertAlmostEqual(solver.y, expected, tol=10**-8)
# test with an arbitrary problem
def rhs(t, y):
return np.array([t**2])
solver = ode_method(t0=0.,
y0=np.array(0.),
rhs={'rhs': rhs},
options=options)
solver.integrate(1.)
expected = 1. / 3
self.assertAlmostEqual(solver.y, expected, tol=10**-8)
def _test_variable_step_method(self, method_str):
"""Some tests for a variable step method."""
# get method and set general options
ode_method = method_from_string(method_str)
options = DE_Options(method=method_str, atol=10**-10, rtol=10**-10)
# run on matrix problem
solver = ode_method(t0=self.t0,
y0=self.y0,
rhs=self.rhs,
options=options)
solver.integrate(1.)
expected = expm(-1j * np.pi * self.X)
# set the comparison tolerance to be somewhat lenient
self.assertAlmostEqual(solver.y, expected, tol=10**-8)
# test with an arbitrary problem
def rhs(t, y):
return np.array([t**2])
solver = ode_method(t0=0.,
y0=np.array(0.),
rhs={'rhs': rhs},
options=options)
solver.integrate(1.)
expected = 1. / 3
self.assertAlmostEqual(solver.y, expected, tol=10**-9)