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
