def _reflamp(self):
#calc_q = self.probe.calc_Q
#return calc_q,calc_q
key = 'calc_r'
if key not in self._cache:
slabs = self._render_slabs()
w = slabs.w
rho,irho = slabs.rho, slabs.irho
sigma = slabs.sigma
#sigma = slabs.sigma
calc_q = self.probe.calc_Q
#print("calc Q", self.probe.calc_Q)
if slabs.ismagnetic:
rhoM, thetaM = slabs.rhoM, slabs.thetaM
Aguide = self.probe.Aguide
calc_r = reflmag(-calc_q/2, depth=w, rho=rho[0], irho=irho[0],
rhoM=rhoM, thetaM=thetaM, Aguide=Aguide)
else:
calc_r = reflamp(-calc_q/2, depth=w, rho=rho, irho=irho,
sigma=sigma)
if False and numpy.isnan(calc_r).any():
print("w %s",w)
print("rho",rho)
print("irho",irho)
print("sigma",sigma)
print("kz",self.probe.calc_Q/2)
print("R",abs(calc_r**2))
pars = parameter.unique(self.parameters())
fitted = parameter.varying(pars)
print(parameter.summarize(fitted))
print("===")
self._cache[key] = calc_q,calc_r
#if numpy.isnan(calc_q).any(): print("calc_Q contains NaN")
#if numpy.isnan(calc_r).any(): print("calc_r contains NaN")
return self._cache[key]
def _reflamp(self):
#calc_q = self.probe.calc_Q
#return calc_q, calc_q
key = 'calc_r'
if key not in self._cache:
slabs = self._render_slabs()
w = slabs.w
rho, irho = slabs.rho, slabs.irho
sigma = slabs.sigma
#sigma = slabs.sigma
calc_q = self.probe.calc_Q
#print("calc Q", self.probe.calc_Q)
if slabs.ismagnetic:
rhoM, thetaM = slabs.rhoM, slabs.thetaM
Aguide = self.probe.Aguide.value
H = self.probe.H.value
calc_r = reflmag(-calc_q / 2,
depth=w,
rho=rho[0],
irho=irho[0],
rhoM=rhoM,
thetaM=thetaM,
Aguide=Aguide,
H=H,
sigma=sigma)
else:
calc_r = reflamp(-calc_q / 2,
depth=w,
rho=rho,
irho=irho,
sigma=sigma)
if False and np.isnan(calc_r).any():
print("w", w)
print("rho", rho)
print("irho", irho)
if slabs.ismagnetic:
print("rhoM", rhoM)
print("thetaM", thetaM)
print("Aguide", Aguide, "H", H)
print("sigma", sigma)
print("kz", self.probe.calc_Q / 2)
print("R", abs(np.asarray(calc_r)**2))
pars = parameter.unique(self.parameters())
fitted = parameter.varying(pars)
print(parameter.summarize(fitted))
print("===")
self._cache[key] = calc_q, calc_r
#if np.isnan(calc_q).any(): print("calc_Q contains NaN")
#if np.isnan(calc_r).any(): print("calc_r contains NaN")
return self._cache[key]
L.interface.value = min([
L.interface.value, L.thickness.value / 3, L[i].thickness.value / 3,
L[i + 2].thickness.value / 3
])
layers[0].interface.value = min([
layers[0].interface.value, layers[0].thickness.value / 3,
layers[1].thickness.value / 3
])
layers[-1].interface.value = min([
layers[-1].interface.value, layers[-2].thickness.value / 3,
layers[-1].thickness.value / 3
])
sample = silicon(0, 5) | layers | air
T = numpy.linspace(0, 5, 100)
probe = NeutronProbe(T=T, dT=0.01, L=4.75, dL=0.0475)
M = Experiment(probe=probe, sample=sample)
M.simulate_data(1.5)
problem = FitProblem(M)
print("chisq", problem.chisq(), file=out)
print("target", file=out)
print(summarize(problem.parameters), file=out)
problem.randomize()
M.update()
print("start", file=out)
print(summarize(problem.parameters), file=out)
out.close()
elif CONSTRAINTS=="known":
layer.thickness.range(3,2*layer.thickness.value)
layer.interface.range(0,min([2*layer.thickness.value/3.,200.]))
layer.material.rho.range(layer.material.rho.value-1,layer.material.rho.value+1)
return layer
layers = [genlayer("L%d"%i) for i in range(num_layers)]
for i,L in layers[-1:1]:
L.interface.value = min([L.interface.value, L.thickness.value/3, L[i].thickness.value/3, L[i+2].thickness.value/3])
layers[0].interface.value = min([layers[0].interface.value, layers[0].thickness.value/3, layers[1].thickness.value/3])
layers[-1].interface.value = min([layers[-1].interface.value, layers[-2].thickness.value/3, layers[-1].thickness.value/3])
sample = silicon(0,5) | layers | air
T = numpy.linspace(0, 5, 100)
probe = NeutronProbe(T=T, dT=0.01, L=4.75, dL=0.0475)
M = Experiment(probe=probe, sample=sample)
M.simulate_data(1.5)
problem = FitProblem(M)
print("chisq",problem.chisq(), file=out)
print("target", file=out)
print(summarize(problem.parameters), file=out)
problem.randomize()
M.update()
print("start", file=out)
print(summarize(problem.parameters), file=out)
out.close()
