def draw_conversions(directory):
from minty.utils.brace_expand import get_expand
gStyle.SetOptStat(1110)
#gStyle.SetOptStat(11111111)
variable = "eta"
#variable = "mass_wide"
#variable = "deltar"
hists = get_expand(directory, "conv{1,2,neither,both}/boson/%s" % variable)
hists = map(meaningful_yaxis, hists)
conv1, conv2, convn, convb = hists
titles = ["(only) Leading converted",
"(only) Subleading converted",
"Neither converted",
"Both converted"]
for h, t in zip(hists, titles):
h.SetTitle(t)
#if variable in ["mass_wide", "phi"]:
#print "Scaling", h
#h.Scale(convn.Integral() / h.Integral())
if variable == "mass_wide":
h.Rebin(4000 / 800) # (4000 is original binning, 200 target)
h.GetXaxis().SetRangeUser(50, 300)
#h.GetXaxis().SetRangeUser(80, 100)
if variable == "eta":
h.Rebin(2)
maxv = max(h.GetMaximum() * 1.1 for h in hists)
for h in hists:
h.GetYaxis().SetRangeUser(0, maxv)
canvas = R.TCanvas("mass-conversions", "Mgg conversions")
canvas.Divide(2,2)
#strs = canvas.strs = []
for i, h in enumerate(hists):
canvas.cd(i+1)
h.Draw()
convn.SetLineColor(R.kRed)
convn.Draw("same hist")
#t = R.TText(0.4, 0.5, h.GetTitle())
#t.SetNDC()
#strs.append(t)
#t.Draw()
wait()
if canvas:
canvas.Close()
def multifit(self, params):
import rootils.uncert as U
from minty.utils import wait, canvas
gROOT.SetBatch()
R.gStyle.SetOptStat(1000000) # Integral only
R.gStyle.SetOptFit(11)
f = TFile("all.root")
h = f.Get("corrected/ph/boson/mass_wide")
window_size = 25
bins = array('d', [])
values = array('d', [])
errors = array('d', [])
for i in xrange(80, 600, 5):
h.GetXaxis().SetRangeUser(i - window_size/2, i + window_size/2)
with canvas() as c:
const, slope = U.from_fitresultp(h.Fit("expo", "LLISQ"))
c.SaveAs("plots/massfit-{0}GeV.png".format(i))
integral = h.Integral()
bins.append(i)
values.append(slope.nominal_value)
errors.append(slope.std_dev())
gROOT.SetBatch(0)
with canvas() as c:
g = R.TGraphErrors(len(bins), bins, values, array('d', [0]*len(bins)), errors)
g.Draw("A*P")
c.SaveAs("plots/massfit-pieces.png")
wait()
