def test_mixed_reflectivity_model(self):
# test that mixed area model works ok.
# should be same as data generated from Motofit
sio2 = SLD(3.47, name='SiO2')
air = SLD(0, name='air')
si = SLD(2.07, name='Si')
s1 = air | sio2(100, 2) | si(0, 3)
s2 = air | sio2(100, 2) | si(0, 3)
mixed_model = MixedReflectModel([s1, s2], [0.4, 0.3], dq=0)
assert_almost_equal(mixed_model(self.qvals), self.rvals * 0.7)
# now try out the mixed model compared to sum of individual models
# with smearing, but no background.
s1 = air | sio2(100, 2) | si(0, 2)
s2 = air | sio2(50, 3) | si(0, 1)
mixed_model = MixedReflectModel([s1, s2], [0.4, 0.3], dq=5, bkg=0)
indiv1 = ReflectModel(s1, bkg=0)
indiv2 = ReflectModel(s2, bkg=0)
assert_almost_equal(mixed_model(self.qvals),
(0.4 * indiv1(self.qvals) +
0.3 * indiv2(self.qvals)))
# now try out the mixed model compared to sum of individual models
# with smearing, and background.
mixed_model.bkg.value = 1e-7
assert_almost_equal(mixed_model(self.qvals),
(0.4 * indiv1(self.qvals) +
0.3 * indiv2(self.qvals) +
1e-7))
def test_mixed_model(self):
# test for MixedReflectModel
air = SLD(0, name="air")
sio2 = SLD(3.47, name="SiO2")
si = SLD(2.07, name="Si")
structure1 = air | sio2(100, 2) | si(0, 3)
structure2 = air | sio2(50, 3) | si(0, 5)
# this is out theoretical calculation
mixed_model_y = 0.4 * structure1.reflectivity(self.qvals)
mixed_model_y += 0.6 * structure2.reflectivity(self.qvals)
mixed_model = MixedReflectModel([structure1, structure2], [0.4, 0.6],
bkg=0,
dq=0)
assert_equal(mixed_model.scales, np.array([0.4, 0.6]))
assert mixed_model.dq.value == 0
assert_allclose(mixed_model_y, mixed_model(self.qvals), atol=1e-13)
# test repr of MixedReflectModel
q = repr(mixed_model)
r = eval(q)
assert_equal(r.scales, np.array([0.4, 0.6]))
assert r.dq.value == 0
assert_allclose(mixed_model_y, r(self.qvals), atol=1e-13)
def test_mixed_model(self):
# test for MixedReflectModel
air = SLD(0, name='air')
sio2 = SLD(3.47, name='SiO2')
si = SLD(2.07, name='Si')
structure1 = air | sio2(100, 2) | si(0, 3)
structure2 = air | sio2(50, 3) | si(0, 5)
# this is out theoretical calculation
mixed_model_y = 0.4 * structure1.reflectivity(self.qvals)
mixed_model_y += 0.6 * structure2.reflectivity(self.qvals)
mixed_model = MixedReflectModel([structure1, structure2], [0.4, 0.6],
bkg=0, dq=0)
assert_equal(mixed_model.scales, np.array([0.4, 0.6]))
assert_(mixed_model.dq.value == 0)
assert_equal(mixed_model_y, mixed_model(self.qvals))
def insert_structure(self, row, structure):
n = StructureNode(structure, self._model, self)
data_object_node = find_data_object(self.index)
data_object = data_object_node.data_object
orig_model = data_object.model
if len(self.structures) == 1:
self._model.beginInsertRows(self.index, row, row)
new_structures = [self.structures[0], structure]
new_model = MixedReflectModel(new_structures,
bkg=orig_model.bkg,
dq=orig_model.dq)
data_object.model = new_model
data_object_node.set_reflect_model(new_model,
constdq_q=self.constantdq_q)
return
# already a mixed model
# we can't insert at a lower place than the 4rd row
row = max(row, 4)
self._model.beginInsertRows(self.index, row, row)
# insert the structure
orig_model.structures.insert(row - STRUCT_OFFSET, structure)
v = 1 / len(orig_model.structures)
sf = possibly_create_parameter(v, name="scale")
orig_model.scales.insert(row - STRUCT_OFFSET, sf)
self.insertChild(row, n)
self._model.endInsertRows()
# insert a scale factor
self._model.beginInsertRows(
self.child(0).index, row - STRUCT_OFFSET, row - STRUCT_OFFSET)
# add a scale factor
n = ParNode(sf, self._model, self.child(0))
self.child(0).insertChild(row - STRUCT_OFFSET, n)
self._model.endInsertRows()