#print('Base weights:')
#for xp in x:
# print(str(xp))
#resp2=det(modelForGuess.getERange(), model.getFluence(x))#TODO guess-> x
#print('Expected detector responses with calculated spectrum:')
#for i in range(len(resp2[0])):
# print((['No sphere']+milanoReference.names)[i]+' & %.1f'%resp[0][i]+' & %.1f'%resp2[0][i]+' \\\\')
pl.subplot(111, xscale="log", yscale="log")
pn=1e3
E=np.exp(np.linspace(np.log(1e-14), np.log(1e3), pn))
pl.plot(E,[spectrum[1](e) for e in E])
#pl.plot(E,[max(CMSNeutrons.fluence(e),1e-10) for e in E])
E=np.exp(np.linspace(np.log(model.getERange()[0]), np.log(model.getERange()[1]), pn))
#pl.plot(E,[modelForGuess(guess,e) for e in E])
#modelForGuess.plot(guess,errors=guessErrors)
model.plot(x,errors=errors)
#E=np.exp(np.linspace(np.log(1e-13), np.log(2e-10), pn))
#pl.plot(E,[maxwellDistribution(e)/2e10*1.4e4 for e in E])
pl.xlim([1e-13,1e1])
pl.ylim([1e0,1e20])
pl.grid()
pl.xlabel('$E$ [GeV]')
pl.ylabel('$\phi(E)$ [$(\mathrm{fb}^{-1}\ \mathrm{cm}^{2}\mathrm{GeV})^{-1}$]')
pl.show()
for xp in x:
print(str(xp))
resp2=det(model.getERange(), model.getFluence(x))
print('Expected detector responses with calculated spectrum:')
for r in resp2[0]:
print(str(r))
import pylab as pl
pl.subplot(111, xscale="log", yscale="log")
pn=1e3
#E=np.exp(np.linspace(np.log(1e-14), np.log(1e3), pn))
#pl.plot(E,[spectrum[1](e) for e in E])
#pl.plot(E,[CMSNeutrons.fluence(e) for e in E])
#E=np.exp(np.linspace(np.log(model.getERange()[0]), np.log(model.getERange()[1]), pn))
#pl.plot(E,[model(x,e) for e in E])
modelForGuess.plot(guess,errors=guessErrors)
#model.plot(x,errors=errors)
#E=np.exp(np.linspace(np.log(1e-13), np.log(2e-10), pn))
#pl.plot(E,[maxwellDistribution(e)/2e10*1.4e4 for e in E])
pl.ylabel('$\phi(E)$ [$\mathrm{mb}\ \mathrm{cm}^{-2}\mathrm{GeV}^{-1}$]')
pl.xlabel('$E$ [GeV]')
pl.xlim([1e-13,1e1])
pl.ylim([1e-10,1e6])
pl.grid()
pl.show()
print('\\hline')
for i in range(len(x)):
print(str(i+1)+' & $%.3g'%(simx[i])+'\\pm%.3g$'%(simerrors[i])+' &$ %.3g'%(x[i])+'\\pm %.3g$'%(errors[i])+' \\\\')
#plot stuff!!!
import pylab as pl
pl.subplot(111, xscale="log", yscale="log")
pn=1e3
E=np.exp(np.linspace(np.log(1e-14), np.log(1e3), pn))
pl.plot(E,[spectrum[1](e) for e in E],label='Simulated spectrum')
#pl.plot(E,[max(CMSNeutrons.fluence(e),1e-10) for e in E])
#E=np.exp(np.linspace(np.log(model.getERange()[0]), np.log(model.getERange()[1]), pn))
#pl.plot(E,[model(x,e) for e in E])
#modelForGuess.plot(guess,errors=guessErrors)
model.plot(x,errors=errors,label='Using measured responses')
model.plot(simx,errors=simerrors,label='Using simulated responses')
#E=np.exp(np.linspace(np.log(1e-13), np.log(2e-10), pn))
#pl.plot(E,[maxwellDistribution(e)/2e10*1.4e4 for e in E])
pl.legend()
pl.xlim([1e-13,1e1])
pl.ylim([1e5,1e20])
pl.grid()
pl.xlabel('$E$ [GeV]')
pl.ylabel('$\phi(E)$ [$(\mathrm{fb}^{-1}\ \mathrm{cm}^{2}\mathrm{GeV})^{-1}$]')
pl.savefig('unfoldCMS1.pdf',bbox_inches=0)
pl.show()
