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nm_analyzer.py
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nm_analyzer.py
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import os, sys, shutil
import numpy as np
import math
import ctypes
import ROOT
from ROOT import TFile, TDirectory, THashList, TF1, TH1F
from histo_manager import slice_histogram, rebin_histogram, get_bkg_subtracted, get_ratio
from nm_fitter import NMFitter
class NMAnalyzer:
def __init__(self):
print("default constructor is called");
def __init__(self, h1centrality, h2same, h2mix, particle, ismc):
self.particle = particle;
self.h1nev = h1centrality.Clone("h1nev");
self.h2same = h2same.Clone("h2same");
self.h2mix = h2mix.Clone("h2mix");
self.h2same.Sumw2();
self.h2mix .Sumw2();
self.h2same.SetDirectory(0);
self.h2mix .SetDirectory(0);
self.f1sig = TF1("f1sig","crystalball(0)", 0, 1);
self.f1bkg = TF1("f1bkg","pol1(0)",0,1);
self.f1total = TF1("f1total","f1sig + f1bkg", 0, 1);
self.f1total.SetNpx(1000);
self.fit_min = 0.04;
self.fit_max = 0.24;
self.integral_min_sigma = -3.0;
self.integral_max_sigma = +3.0;
self.xtitle = "#it{m}_{#gamma#gamma} (GeV/#it{c}^{2})";
self.ytitle = "#it{p}_{T,#gamma#gamma} (GeV/#it{c}^{2})";
def __del__(self):
if self.rootfile.IsOpen():
print("close input root file.");
self.rootfile.Close();
def set_arr_pt(self, arr_pt):
self.arr_pt = arr_pt;
def set_fit_range(self, fit_min, fit_max):
self.fit_min = fit_min;
self.fit_max = fit_max;
def set_integral_range(self, integral_min, integral_max):
self.integral_min_sigma = integral_min;
self.integral_max_sigma = integral_max;
def set_fit_function(self, sig, bkg):
if sig == "cb":
self.f1sig = TF1("f1sig","crystalball(0)", 0,1);
if bkg == "pol1":
self.f1bkg = TF1("f1bkg","pol1(0)", 0,1);
self.f1total = TF1("f1total","crystalball(0) + pol1(5)", 0,1);
elif bkg == "pol2":
self.f1bkg = TF1("f1bkg","pol2(0)", 0,1);
self.f1total = TF1("f1total","crystalball(0) + pol2(5)", 0,1);
self.f1total.SetParameter(3,0.5);
self.f1total.SetParameter(4,10.0);
self.f1sig.SetParameter(3,0.5);
self.f1sig.SetParameter(4,10.0);
self.f1total.SetParLimits(3,0, 100);
self.f1total.SetParLimits(4,0, 100);
self.f1sig.SetParLimits(3,0, 100);
self.f1sig.SetParLimits(4,0, 100);
self.f1sig.SetNpx(1000);
self.f1bkg.SetNpx(1000);
self.f1total.SetNpx(1000);
print("initially, ", self.f1total.GetExpFormula(""));
def fix_cb_n(self, n):
self.f1total.FixParameter(3, n);
self.f1sig.FixParameter(3, n);
def fix_cb_alpha(self, alpha):
self.f1total.FixParameter(4, alpha);
self.f1sig.FixParameter(4, alpha);
def set_xtitle(self, title):
self.xtitle = title;
def set_ytitle(self, title):
self.ytitle = title;
def analyze(self): #this is main function
print(sys._getframe().f_code.co_name);
outlist = THashList();
#outlist.SetOwner(True);
outlist.SetName("outlist");
if self.particle == "pi0":
self.h2same.RebinX(2);
self.h2mix .RebinX(2);
elif self.particle == "eta":
self.h2same.RebinX(2);
self.h2mix .RebinX(2);
nev = self.h1ev.GetEntries();
print("nev = {0:e}".format(nev));
outlist.Add(self.h1ev);
outlist.Add(self.h2same);
outlist.Add(self.h2mix);
npt = len(self.arr_pt);
h1yield = TH1F("h1yield","raw yield" ,npt-1, self.arr_pt);
h1mean = TH1F("h1mean" ,"peak mean" ,npt-1, self.arr_pt);
h1sigma = TH1F("h1sigma","peak sigma" ,npt-1, self.arr_pt);
h1alpha = TH1F("h1alpha","alpha of CB",npt-1, self.arr_pt);
h1n = TH1F("h1n" ,"n of CB" ,npt-1, self.arr_pt);
h1yield.SetXTitle("#it{p}_{T} (GeV/#it{c})");
h1yield.SetYTitle("#frac{1}{#it{N}_{ev}} #frac{d#it{N}}{d#it{p}_{T}} (GeV/#it{c})^{-1}");
h1mean.SetXTitle("#it{p}_{T} (GeV/#it{c})");
h1mean.SetYTitle("peak mean (GeV/#it{c}^{2})");
h1sigma.SetXTitle("#it{p}_{T} (GeV/#it{c})");
h1sigma.SetYTitle("peak sigma (GeV/#it{c}^{2})");
h1alpha.SetXTitle("#it{p}_{T} (GeV/#it{c})");
h1alpha.SetYTitle("#alpha of CB");
h1n.SetXTitle("#it{p}_{T} (GeV/#it{c})");
h1n.SetYTitle("n of CB");
for i in range(0, npt-1):
pt1 = self.arr_pt[i];
pt2 = self.arr_pt[i+1];
h1same = slice_histogram(self.h2same, pt1, pt2, "X", False);
h1same.SetName("h1mgg_same_pt{0}".format(i));
h1same.SetTitle("m_{{#gamma#gamma}}^{{same}}, {0:2.1f} < #it{{p}}_{{T,#gamma#gamma}} < {1:2.1f} GeV/#it{{c}}".format(pt1, pt2));
bw = h1same.GetBinWidth(1);
h1same.SetXTitle("#it{m}_{#gamma#gamma} (GeV/#it{c}^{2})");
h1same.SetYTitle("counts / {0:d} MeV/#it{{c}}^{{2}}".format(int(bw*1e+3)));
h1mix = slice_histogram(self.h2mix , pt1, pt2, "X", False);
h1mix.SetName("h1mgg_mix_pt{0}".format(i));
h1mix.SetTitle("m_{{#gamma#gamma}}^{{mix}}, {0:2.1f} < #it{{p}}_{{T,#gamma#gamma}} < {1:2.1f} GeV/#it{{c}}".format(pt1, pt2));
h1mix.SetXTitle("#it{m}_{#gamma#gamma} (GeV/#it{c}^{2})");
h1mix.SetYTitle("counts / {0:d} MeV/#it{{c}}^{{2}}".format(int(bw*1e+3)));
h1same.SetDirectory(0);
h1mix .SetDirectory(0);
if (self.ssname == "PHOSPHOS" or self.ssname=="EMCEMC") and pt1 > 1.99 and self.particle == "eta":
h1same.RebinX(2);
h1mix .RebinX(2);
bw = h1same.GetBinWidth(1);
h1same.SetYTitle("counts / {0:d} MeV/#it{{c}}^{{2}}".format(int(bw*1e+3)));
h1mix.SetYTitle("counts / {0:d} MeV/#it{{c}}^{{2}}".format(int(bw*1e+3)));
if pt1 < 0.11:
h1same.RebinX(2);
h1mix .RebinX(2);
bw = h1same.GetBinWidth(1);
h1same.SetYTitle("counts / {0:d} MeV/#it{{c}}^{{2}}".format(int(bw*1e+3)));
h1mix.SetYTitle("counts / {0:d} MeV/#it{{c}}^{{2}}".format(int(bw*1e+3)));
if pt1 > 1.99 and h1same.GetMaximum() < 25.5:
h1same.RebinX(2);
h1mix .RebinX(2);
bw = h1same.GetBinWidth(1);
h1same.SetYTitle("counts / {0:d} MeV/#it{{c}}^{{2}}".format(int(bw*1e+3)));
h1mix.SetYTitle("counts / {0:d} MeV/#it{{c}}^{{2}}".format(int(bw*1e+3)));
npair_same = h1same.GetEntries();
npair_mix = h1mix.GetEntries();
if npair_mix < 1e-6:
continue;
h1mix.Scale(npair_same/npair_mix);
h1ratio = get_ratio(h1same, h1mix);
h1ratio.SetName("h1mgg_ratio_pt{0}".format(i));
h1ratio.SetTitle("m_{{#gamma#gamma}}^{{ratio}}, {0:2.1f} < #it{{p}}_{{T,#gamma#gamma}} < {1:2.1f} GeV/#it{{c}}".format(pt1, pt2));
h1ratio.SetXTitle("#it{m}_{#gamma#gamma} (GeV/#it{c}^{2})");
h1ratio.SetYTitle("counts / {0:d} MeV/#it{{c}}^{{2}}".format(int(bw*1e+3)));
h1ratio .SetDirectory(0);
height = 1.0;
mean_init = 0.130;
sigma_init = 0.008;
if "pi0" in self.particle:
mean_init = 0.130;
sigma = 0.008;
elif "eta" in self.particle:
mean_init = 0.548;
sigma_init = 0.012;
bin_mean = h1ratio.FindBin(mean_init);
height = h1ratio.GetBinContent(bin_mean) - 1.0;
f1total = self.f1total.Clone("f1ratio_pt{0}".format(i));
f1total.SetParameter(0,height);
f1total.SetParameter(1,mean_init);
f1total.SetParameter(2,sigma_init);
#f1total.SetParameter(3,0.6);
#f1total.SetParameter(4,0.1);
f1total.SetParameter(5,0.1);
f1total.SetParameter(6,-0.1);
f1total.SetParLimits(0,1e-3,100);
f1total.SetParLimits(1, mean_init - 3 * sigma_init, mean_init + 3 * sigma_init);
f1total.SetParLimits(2, 0.3 * sigma_init, 3 * sigma_init);
#f1total.FixParameter(3,0.5);
#f1total.FixParameter(4,10.0);
#f1total.SetParLimits(3,0, 100);
#f1total.SetParLimits(4,0, 100);
h1ratio.Fit(f1total,"SME","",self.fit_min, self.fit_max);
h1bkg = h1mix.Clone("h1bkg");
f1bkg = self.f1bkg.Clone("f1bkg_pt{0}".format(i));
npar_sig = self.f1sig.GetNpar();
npar_bkg = self.f1bkg.GetNpar();
for ip in range(npar_bkg):
f1bkg.FixParameter(ip, f1total.GetParameter(ip + npar_sig));
h1bkg.Multiply(f1bkg);
h1bkg.SetName("h1mgg_bkg_pt{0}".format(i));
h1bkg.SetTitle("m_{{#gamma#gamma}}^{{bkg}}, {0:2.1f} < #it{{p}}_{{T,#gamma#gamma}} < {1:2.1f} GeV/#it{{c}}".format(pt1, pt2));
h1bkg.SetXTitle("#it{m}_{#gamma#gamma} (GeV/#it{c}^{2})");
h1bkg.SetYTitle("counts / {0:d} MeV/#it{{c}}^{{2}}".format(int(bw*1e+3)));
h1bkg .SetDirectory(0);
h1sig = get_bkg_subtracted(h1same, h1bkg);
h1sig.SetName("h1mgg_sig_pt{0}".format(i));
h1sig.SetTitle("m_{{#gamma#gamma}}^{{sig}}, {0:2.1f} < #it{{p}}_{{T,#gamma#gamma}} < {1:2.1f} GeV/#it{{c}}".format(pt1, pt2));
h1sig.SetXTitle("#it{m}_{#gamma#gamma} (GeV/#it{c}^{2})");
h1sig.SetYTitle("counts / {0:d} MeV/#it{{c}}^{{2}}".format(int(bw*1e+3)));
h1sig .SetDirectory(0);
f1sig = self.f1sig.Clone("f1sig_pt{0}".format(i));
f1sig.SetNpx(1000);
for ip in range(npar_sig):
f1sig.SetParameter(ip, f1total.GetParameter(ip));
height = h1sig.GetBinContent(bin_mean);
f1sig.SetParameter(0,height);
f1sig.SetParameter(1,mean_init);
f1sig.SetParameter(2,sigma_init);
#f1sig.SetParameter(3,0.6);
#f1sig.SetParameter(4,1);
f1sig.SetParLimits(0,1,1e+6);
f1sig.SetParLimits(1, mean_init - 3 * sigma_init, mean_init + 3 * sigma_init);
f1sig.SetParLimits(2, 0.3 * sigma_init, 3 * sigma_init);
#f1sig.FixParameter(3,0.5);
#f1sig.FixParameter(4,10.0);
#f1sig.SetParLimits(3,0, 100);
#f1sig.SetParLimits(4,0, 100);
h1sig.Fit(f1sig,"SME","",self.fit_min, self.fit_max);
mean = f1sig.GetParameter(1);
mean_err = f1sig.GetParError(1);
sigma = f1sig.GetParameter(2);
sigma_err = f1sig.GetParError(2);
alpha = f1sig.GetParameter(3);
alpha_err = f1sig.GetParError(3);
n = f1sig.GetParameter(4);
n_err = f1sig.GetParError(4);
h1mean.SetBinContent(i+1, mean);
h1mean.SetBinError(i+1, mean_err);
h1sigma.SetBinContent(i+1, sigma);
h1sigma.SetBinError(i+1, sigma_err);
h1alpha.SetBinContent(i+1, alpha);
h1alpha.SetBinError(i+1, alpha_err);
h1n.SetBinContent(i+1, n);
h1n.SetBinError(i+1, n_err);
bin1 = h1sig.FindBin(mean + self.integral_min_sigma * sigma);
bin2 = h1sig.FindBin(mean + self.integral_max_sigma * sigma);
ry_err = ctypes.c_double(0);
ry = h1sig.IntegralAndError(bin1,bin2,ry_err,"");
h1yield.SetBinContent(i+1, ry);
h1yield.SetBinError(i+1, ry_err);
outlist.Add(h1same);
outlist.Add(h1mix);
outlist.Add(h1ratio);
outlist.Add(f1total);
outlist.Add(h1bkg);
outlist.Add(h1sig);
outlist.Add(f1sig);
outlist.Add(f1bkg);
h1yield.Scale(1/nev);
h1yield.Scale(1., "width");
outlist.Add(h1yield);
outlist.Add(h1mean );
outlist.Add(h1sigma);
outlist.Add(h1alpha);
outlist.Add(h1n );
return outlist;