def test_multipledataset_corefinement(self):
# test corefinement of three datasets
data361 = ReflectDataset(os.path.join(self.pth, 'e361r.txt'))
data365 = ReflectDataset(os.path.join(self.pth, 'e365r.txt'))
data366 = ReflectDataset(os.path.join(self.pth, 'e366r.txt'))
si = SLD(2.07, name='Si')
sio2 = SLD(3.47, name='SiO2')
d2o = SLD(6.36, name='d2o')
h2o = SLD(-0.56, name='h2o')
cm3 = SLD(3.47, name='cm3')
polymer = SLD(1, name='polymer')
structure361 = si | sio2(10, 4) | polymer(200, 3) | d2o(0, 3)
structure365 = si | structure361[1] | structure361[2] | cm3(0, 3)
structure366 = si | structure361[1] | structure361[2] | h2o(0, 3)
structure365[-1].rough = structure361[-1].rough
structure366[-1].rough = structure361[-1].rough
structure361[1].thick.setp(vary=True, bounds=(0, 20))
structure361[2].thick.setp(value=200., bounds=(200., 250.), vary=True)
structure361[2].sld.real.setp(vary=True, bounds=(0, 2))
structure361[2].vfsolv.setp(value=5., bounds=(0., 100.), vary=True)
model361 = ReflectModel(structure361, bkg=2e-5)
model365 = ReflectModel(structure365, bkg=2e-5)
model366 = ReflectModel(structure366, bkg=2e-5)
model361.bkg.setp(vary=True, bounds=(1e-6, 5e-5))
model365.bkg.setp(vary=True, bounds=(1e-6, 5e-5))
model366.bkg.setp(vary=True, bounds=(1e-6, 5e-5))
objective361 = Objective(model361, data361)
objective365 = Objective(model365, data365)
objective366 = Objective(model366, data366)
global_objective = GlobalObjective(
[objective361, objective365, objective366])
# are the right numbers of parameters varying?
assert_equal(len(global_objective.varying_parameters()), 7)
# can we set the parameters?
global_objective.setp(np.array([1e-5, 10, 212, 1, 10, 1e-5, 1e-5]))
f = CurveFitter(global_objective)
f.fit()
indiv_chisqr = np.sum(
[objective.chisqr() for objective in global_objective.objectives])
# the overall chi2 should be sum of individual chi2
global_chisqr = global_objective.chisqr()
assert_almost_equal(global_chisqr, indiv_chisqr)
# now check that the parameters were held in common correctly.
slabs361 = structure361.slabs()
slabs365 = structure365.slabs()
slabs366 = structure366.slabs()
assert_equal(slabs365[0:2, 0:5], slabs361[0:2, 0:5])
assert_equal(slabs366[0:2, 0:5], slabs361[0:2, 0:5])
assert_equal(slabs365[-1, 3], slabs361[-1, 3])
assert_equal(slabs366[-1, 3], slabs361[-1, 3])
# check that the residuals are the correct lengths
res361 = objective361.residuals()
res365 = objective365.residuals()
res366 = objective366.residuals()
res_global = global_objective.residuals()
assert_allclose(res_global[0:len(res361)], res361, rtol=1e-5)
assert_allclose(res_global[len(res361):len(res361) + len(res365)],
res365,
rtol=1e-5)
assert_allclose(res_global[len(res361) + len(res365):],
res366,
rtol=1e-5)
repr(global_objective)
class TestGlobalFitting(object):
def setup_method(self):
self.pth = os.path.dirname(os.path.abspath(__file__))
self.si = SLD(2.07, name='Si')
self.sio2 = SLD(3.47, name='SiO2')
self.d2o = SLD(6.36, name='d2o')
self.h2o = SLD(-0.56, name='h2o')
self.cm3 = SLD(3.5, name='cm3')
self.polymer = SLD(2, name='polymer')
self.sio2_l = self.sio2(40, 3)
self.polymer_l = self.polymer(200, 3)
self.structure = (self.si | self.sio2_l | self.polymer_l
| self.d2o(0, 3))
fname = os.path.join(self.pth, 'c_PLP0011859_q.txt')
self.dataset = ReflectDataset(fname)
self.model = ReflectModel(self.structure, bkg=2e-7)
self.objective = Objective(self.model,
self.dataset,
use_weights=False,
transform=Transform('logY'))
self.global_objective = GlobalObjective([self.objective])
def test_residuals_length(self):
# the residuals should be the same length as the data
residuals = self.global_objective.residuals()
assert_equal(residuals.size, len(self.dataset))
def test_globalfitting(self):
# smoke test for can the global fitting run?
# also tests that global fitting gives same output as
# normal fitting (for a single dataset)
self.model.scale.setp(vary=True, bounds=(0.1, 2))
self.model.bkg.setp(vary=True, bounds=(1e-10, 8e-6))
self.structure[-1].rough.setp(vary=True, bounds=(0.2, 6))
self.sio2_l.thick.setp(vary=True, bounds=(0.2, 80))
self.polymer_l.thick.setp(bounds=(0.01, 400), vary=True)
self.polymer_l.sld.real.setp(vary=True, bounds=(0.01, 4))
self.objective.transform = Transform('logY')
starting = np.array(self.objective.parameters)
with np.errstate(invalid='raise'):
g = CurveFitter(self.global_objective)
res_g = g.fit()
# need the same starting point
self.objective.setp(starting)
f = CurveFitter(self.objective)
res_f = f.fit()
# individual and global should give the same fit.
assert_almost_equal(res_g.x, res_f.x)
def test_multipledataset_corefinement(self):
# test corefinement of three datasets
data361 = ReflectDataset(os.path.join(self.pth, 'e361r.txt'))
data365 = ReflectDataset(os.path.join(self.pth, 'e365r.txt'))
data366 = ReflectDataset(os.path.join(self.pth, 'e366r.txt'))
si = SLD(2.07, name='Si')
sio2 = SLD(3.47, name='SiO2')
d2o = SLD(6.36, name='d2o')
h2o = SLD(-0.56, name='h2o')
cm3 = SLD(3.47, name='cm3')
polymer = SLD(1, name='polymer')
structure361 = si | sio2(10, 4) | polymer(200, 3) | d2o(0, 3)
structure365 = si | structure361[1] | structure361[2] | cm3(0, 3)
structure366 = si | structure361[1] | structure361[2] | h2o(0, 3)
structure365[-1].rough = structure361[-1].rough
structure366[-1].rough = structure361[-1].rough
structure361[1].thick.setp(vary=True, bounds=(0, 20))
structure361[2].thick.setp(value=200., bounds=(200., 250.), vary=True)
structure361[2].sld.real.setp(vary=True, bounds=(0, 2))
structure361[2].vfsolv.setp(value=5., bounds=(0., 100.), vary=True)
model361 = ReflectModel(structure361, bkg=2e-5)
model365 = ReflectModel(structure365, bkg=2e-5)
model366 = ReflectModel(structure366, bkg=2e-5)
model361.bkg.setp(vary=True, bounds=(1e-6, 5e-5))
model365.bkg.setp(vary=True, bounds=(1e-6, 5e-5))
model366.bkg.setp(vary=True, bounds=(1e-6, 5e-5))
objective361 = Objective(model361, data361)
objective365 = Objective(model365, data365)
objective366 = Objective(model366, data366)
global_objective = GlobalObjective(
[objective361, objective365, objective366])
# are the right numbers of parameters varying?
assert_equal(len(global_objective.varying_parameters()), 7)
# can we set the parameters?
global_objective.setp(np.array([1e-5, 10, 212, 1, 10, 1e-5, 1e-5]))
f = CurveFitter(global_objective)
f.fit()
indiv_chisqr = np.sum(
[objective.chisqr() for objective in global_objective.objectives])
# the overall chi2 should be sum of individual chi2
global_chisqr = global_objective.chisqr()
assert_almost_equal(global_chisqr, indiv_chisqr)
# now check that the parameters were held in common correctly.
slabs361 = structure361.slabs()
slabs365 = structure365.slabs()
slabs366 = structure366.slabs()
assert_equal(slabs365[0:2, 0:5], slabs361[0:2, 0:5])
assert_equal(slabs366[0:2, 0:5], slabs361[0:2, 0:5])
assert_equal(slabs365[-1, 3], slabs361[-1, 3])
assert_equal(slabs366[-1, 3], slabs361[-1, 3])
# check that the residuals are the correct lengths
res361 = objective361.residuals()
res365 = objective365.residuals()
res366 = objective366.residuals()
res_global = global_objective.residuals()
assert_allclose(res_global[0:len(res361)], res361, rtol=1e-5)
assert_allclose(res_global[len(res361):len(res361) + len(res365)],
res365,
rtol=1e-5)
assert_allclose(res_global[len(res361) + len(res365):],
res366,
rtol=1e-5)
repr(global_objective)