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)
fig = plt.figure(figsize=(5, 25 / 6))
gs = mpl.gridspec.GridSpec(1, 3)
ax1 = plt.subplot(gs[0, 0:2])
ax2 = plt.subplot(gs[0, 2])
abc = {'dspc_20': '(a)', 'dspc_30': '(a)', 'dspc_40': '(a)', 'dspc_50': '(a)'}
chi = np.zeros((7))
for i in range(len(cont)):
choose = global_objective.pgen(ngen=100)
ax1.errorbar(datasets[i].x,
datasets[i].y * (datasets[i].x)**4 * 10**(i - 1),
yerr=datasets[i].y_err * (datasets[i].x)**4 * 10**(i - 1),
linestyle='',
marker='o',
color=sns.color_palette()[i])
for pvec in choose:
global_objective.setp(pvec)
ax1.plot(datasets[i].x,
models[i](datasets[i].x, x_err=datasets[i].x_err) *
(datasets[i].x)**4 * 10**(i - 1),
color=sns.color_palette()[i],
alpha=0.1)
zs, sld = structures[i].sld_profile()
if zs.min() > -20:
x2 = np.linspace(-20, zs.min(), 100)
zs = np.append(x2, zs)
y2 = np.zeros_like(x2)
sld = np.append(y2, sld)
if zs.max() < 80:
x3 = np.linspace(zs.max(), 81, 100)
y3 = np.ones_like(x3) * sld[-1]
zs = np.append(zs, x3)