def test_target_function( mock_single_Ih_table, mock_multi_apm_withrestraints, mock_multi_apm_withoutrestraints, ): """Test for the ScalingTarget class.""" # Create a scaling target and check gradients target = ScalingTarget() apm_restr = mock_multi_apm_withrestraints apm_norestr = mock_multi_apm_withoutrestraints # Below methods needed for refinement engine calls r, w = target.compute_residuals(mock_single_Ih_table) assert r.size() == w.size() f, g = target.compute_functional_gradients(mock_single_Ih_table) assert isinstance(f, float) assert g.size( ) == 1 # Number of parameters as determined by deriv matrix cols r, j, w = target.compute_residuals_and_gradients(mock_single_Ih_table) assert r.size() == w.size() assert j.n_cols == 1 # Number of parameters as determined by jacob matrix. assert j.n_rows == r.size() with pytest.raises(AssertionError): _ = target.compute_functional_gradients_and_curvatures( mock_single_Ih_table) restraints = target.compute_restraints_residuals_and_gradients(apm_restr) assert len(restraints) == 3 assert target.param_restraints is True restraints = target.compute_restraints_functional_gradients_and_curvatures( apm_restr) assert len(restraints) == 3 achieved = target.achieved() assert isinstance(achieved, bool) restraints = target.compute_restraints_residuals_and_gradients(apm_norestr) assert restraints is None assert target.param_restraints is False target = ScalingTarget( ) # Need to make new instance or won't calc restr as # param_restraints is set to False assert target.param_restraints is True restraints = target.compute_restraints_functional_gradients_and_curvatures( apm_norestr) assert restraints is None assert target.param_restraints is False
def test_target_function_methods(): """Test for the target methods required for the refinement engine.""" target = ScalingTarget() r, w = target.compute_residuals(mock_single_Ih_table()) assert r.size() == w.size() assert r == pytest.approx([-1.0, 0.0, 1.0]) assert w == pytest.approx([1.0, 1.0, 1.0]) f, g = target.compute_functional_gradients(mock_single_Ih_table()) assert f == pytest.approx(2.0) assert g == pytest.approx([-19.04072398]) r2, j, w2 = target.compute_residuals_and_gradients(mock_single_Ih_table()) assert r == r2 assert w == w2 assert j.n_cols == 1 and j.n_rows == 3
def test_target_gradient_calculation_finite_difference(small_reflection_table, single_exp, physical_param): """Test the calculated gradients against a finite difference calculation.""" model = PhysicalScalingModel.from_data(physical_param, single_exp, small_reflection_table) # need to 'add_data' model.configure_components(small_reflection_table, single_exp, physical_param) model.components["scale"].update_reflection_data() model.components["decay"].update_reflection_data() apm = multi_active_parameter_manager( ScalingTarget(), [model.components], [["scale", "decay"]], scaling_active_parameter_manager, ) model.components["scale"].inverse_scales = flex.double([2.0, 1.0, 2.0]) model.components["decay"].inverse_scales = flex.double([1.0, 1.0, 0.4]) Ih_table = IhTable([small_reflection_table], single_exp.crystal.get_space_group()) with patch.object(SingleScaler, "__init__", lambda x, y, z, k: None): scaler = SingleScaler(None, None, None) scaler._Ih_table = Ih_table # Now do finite difference check. target = ScalingTarget() scaler.update_for_minimisation(apm, 0) grad = target.calculate_gradients(scaler.Ih_table.blocked_data_list[0]) res, _ = target.compute_residuals(scaler.Ih_table.blocked_data_list[0]) assert (res > 1e-8), """residual should not be zero, or the gradient test below will not really be working!""" # Now compare to finite difference f_d_grad = calculate_gradient_fd(target, scaler, apm) print(list(f_d_grad)) print(list(grad)) assert list(grad) == pytest.approx(list(f_d_grad)) sel = f_d_grad > 1e-8 assert sel, """assert sel has some elements, as finite difference grad should