def test_run_hamiltonian(self):
# Important to restrict the step in order to avoid the
# discontinutiy at x=[0,0] of the hamiltonian
for method in ['central', 'complex']:
step = nd.MaxStepGenerator(base_step=1e-4)
hessian = nd.Hessian(None, step=step, method=method)
h, _error_estimate, true_h = run_hamiltonian(hessian,
verbose=False)
self.assertTrue((np.abs((h - true_h) / true_h) < 1e-4).all())
def test_run_hamiltonian(self):
# Important to restrict the step in order to avoid the
# discontinutiy at x=[0,0] of the hamiltonian
for method in ['central', 'complex']:
step = nd.MaxStepGenerator(base_step=1e-4)
hessian = nd.Hessian(None, step=step, method=method)
h, _error_estimate, true_h = run_hamiltonian(hessian,
verbose=False)
assert (np.abs((h - true_h) / true_h) < 1e-4).all()
def test_run_hamiltonian(self):
h, _error_estimate, true_h = run_hamiltonian(nd.Hessian(None),
verbose=False)
self.assertTrue((np.abs((h - true_h)/true_h) < 1e-4).all())
def test_run_hamiltonian(self):
h, _error_estimate, true_h = run_hamiltonian(nd.Hessian(None),
verbose=False)
self.assertTrue((np.abs((h - true_h) / true_h) < 1e-4).all())