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())