def draw_toyMC(hist,title,xlabel="",ylabel="",exponent=None, box="tl"):
fit = root.TF1("gauss","gaus")
textbox = r"\begin{align*}\mu&=%s\\\sigma&=%s\end{align*}"
fig, a = utils.get_plotaxes((4,3.2))
hist.Fit(fit,"LQ")
r2mpl.plot(hist,axes=a, errors=True, color="k", zorder=1)
r2mpl.plot(fit,axes=a, color="r", zorder=0)
utils.text_box(a, box, textbox % (
utils.format_error(fit.GetParameter(1), fit.GetParError(1), exponent=exponent),
utils.format_error(fit.GetParameter(2), fit.GetParError(2), exponent=exponent)))
a.set_title(title)
a.set_xlabel(xlabel)
a.set_ylabel(ylabel)
return a, (fit.GetParameter(1), fit.GetParError(1)), (fit.GetParameter(2), fit.GetParError(2))
lin_result.SetBinError(x,fit.GetParError(1))
one_pull.Fit(fit,"LQ")
lin_pull_mean.SetBinContent(x,fit.GetParameter(1))
lin_pull_mean.SetBinError(x,fit.GetParError(1))
lin_pull_sigma.SetBinContent(x,fit.GetParameter(2))
lin_pull_sigma.SetBinError(x,fit.GetParError(2))
fit = root.TF1("line","pol1",-0.8,0.8)
for a,h in (a1,lin_result),(a2,lin_pull_mean),(a3,lin_pull_sigma):
if par is not "yield_signal_br":
h.Fit(fit,"Q")
else:
h.Fit(fit,"Q")
r2mpl.plot(h, axes=a, errors=True, color=colors[par])
r2mpl.plot(fit, axes=a, color=colors[par])
utils.text_box(a, "tl", r"\begin{align*}m&=%s\\t&=%s\end{align*}" % (utils.format_error(fit.GetParameter(1), fit.GetParError(1)), utils.format_error(fit.GetParameter(0), fit.GetParError(0))))
lin_res = lin_result.Clone("tmp")
for i in range(1,lin_res.GetNbinsX()+1):
lin_res.SetBinContent(i,lin_res.GetBinContent(i)-lin_res.GetBinCenter(i))
r2mpl.plot(lin_res, axes=a1, errors=True, color="k")
if par is not "yield_signal_br":
#ymin = result.GetYaxis().GetXmin()
#ymax = result.GetYaxis().GetXmax()
a1.set_ylim(-1.2,1.2)
a2.set_ylim(-1,1)
a3.set_ylim(0,2)
elif isinstance(result,root.TH1D):
toymc.draw_toyMC(result,title)
