def test_scaling_active_parameter_manager():
"""Test the scaling-specific parameter manager."""
components_2 = {"1": mock_scaling_component(2), "2": mock_scaling_component(2)}
scaling_apm = scaling_active_parameter_manager(components_2, ["1"])
assert list(scaling_apm.constant_g_values[0]) == list(
components_2["2"].calculate_scales()
)
assert len(scaling_apm.constant_g_values) == 1
assert scaling_apm.n_obs == [2]
# Test that no constant_g_values if both components selected
scaling_apm = scaling_active_parameter_manager(components_2, ["1", "2"])
assert scaling_apm.constant_g_values is None
# Check that one can't initialise with an unequal number of reflections,
# either within the selection or overall.
with pytest.raises(AssertionError):
components_2 = {"1": mock_scaling_component(2), "2": mock_scaling_component(1)}
scaling_apm = scaling_active_parameter_manager(components_2, ["1", "2"])
with pytest.raises(AssertionError):
components_2 = {"1": mock_scaling_component(2), "2": mock_scaling_component(1)}
scaling_apm = scaling_active_parameter_manager(components_2, ["1"])
data_manager = mock_data_manager(components_2)
pmg = ScalingParameterManagerGenerator([data_manager], mode="concurrent")
assert isinstance(pmg.apm_type, type(scaling_active_parameter_manager))
def test_RefinerCalculator(small_reflection_table):
"""Test for the RefinerCalculator class. This calculates scale factors and
derivatives for reflections based on the model components."""
# To test the basis function, need a scaling active parameter manager - to set
# this up we need a components dictionary with some reflection data.
# Let's use KB model components for simplicity - and have an extra fake 'abs'
# component.
rt = small_reflection_table
components = {
"scale": SingleScaleFactor(flex.double([1.0])),
"decay": SingleBScaleFactor(flex.double([0.0])),
"abs": SingleScaleFactor(flex.double([1.0])),
} # Create empty components.
components["scale"].data = {"id": rt["id"]}
components["decay"].data = {"d": rt["d"]}
components["abs"].data = {"id": rt["id"]}
for component in components.values():
component.update_reflection_data() # Add some data to components.
apm = scaling_active_parameter_manager(components, ["decay", "scale"])
# First test that scale factors can be successfully updated.
# Manually change the parameters in the apm.
decay = components["decay"] # Define alias
_ = components["scale"] # Define alias
# Note, order of params in apm.x depends on order in scaling model components.
new_B = 1.0
new_S = 2.0
apm.set_param_vals(flex.double([new_S, new_B]))
s, d = RefinerCalculator.calculate_scales_and_derivatives(apm, 0)
slist, dlist = RefinerCalculator._calc_component_scales_derivatives(apm, 0)
# Now test that the inverse scale factor is correctly calculated.
calculated_sfs = s
assert list(calculated_sfs) == pytest.approx(
list(new_S * flex.exp(new_B / (2.0 * flex.pow2(decay.d_values[0])))))
# Now check that the derivative matrix is correctly calculated.
calc_derivs = d
assert calc_derivs[0, 0] == dlist[0][0, 0] * slist[1][0]
assert calc_derivs[1, 0] == dlist[0][1, 0] * slist[1][1]
assert calc_derivs[2, 0] == dlist[0][2, 0] * slist[1][2]
assert calc_derivs[0, 1] == dlist[1][0, 0] * slist[0][0]
assert calc_derivs[1, 1] == dlist[1][1, 0] * slist[0][1]
assert calc_derivs[2, 1] == dlist[1][2, 0] * slist[0][2]
# Repeat the test when there is only one active parameter.
# First reset the parameters
components["decay"].parameters = flex.double([0.0])
components["scale"].parameters = flex.double([1.0])
components["abs"].parameters = flex.double([1.0])
components["decay"].calculate_scales_and_derivatives()
components["scale"].calculate_scales_and_derivatives()
components["abs"].calculate_scales_and_derivatives()
# Now generate a parameter manager for a single component.
apm = scaling_active_parameter_manager(components, ["scale"])
new_S = 2.0
apm.set_param_vals(flex.double(components["scale"].n_params, new_S))
s, d = RefinerCalculator.calculate_scales_and_derivatives(apm, 0)
slist, dlist = RefinerCalculator._calc_component_scales_derivatives(apm, 0)
# Test that the scales and derivatives were correctly calculated
assert list(s) == list([new_S] * slist[0].size())
assert d[0, 0] == dlist[0][0, 0]
assert d[1, 0] == dlist[0][1, 0]
assert d[2, 0] == dlist[0][2, 0]
# Test again for two components.
components["decay"].parameters = flex.double([0.0])
components["scale"].parameters = flex.double([1.0])
components["abs"].parameters = flex.double([1.0])
components["decay"].calculate_scales_and_derivatives()
components["scale"].calculate_scales_and_derivatives()
components["abs"].calculate_scales_and_derivatives()
apm = scaling_active_parameter_manager(components, ["scale", "decay"])
_, __ = RefinerCalculator.calculate_scales_and_derivatives(apm, 0)
# Test for no components
apm = scaling_active_parameter_manager(components, [])
_, d = RefinerCalculator.calculate_scales_and_derivatives(apm, 0)
assert d.n_cols == 0 and d.n_rows == 0