def hit_en():
#hit energy
infile = "/home/jaroslav/sim/lmon/data/beam-gas/bg3d/rc.root"
emin = -9
emax = 9
ebin = 0.1
inp = TFile.Open(infile)
htree = inp.Get("htree")
#can = ut.box_canvas()
hE = ut.prepare_TH1D("hE", ebin, emin, emax)
htree.Draw("TMath::Log10(en*1e6) >> hE", "zpos<150.")
xp, yp = ut.h1_to_arrays(hE)
infile2 = "/home/jaroslav/sim/lmon/data/beam-gas/bg3e/rc.root"
inp2 = TFile.Open(infile2)
htree2 = inp2.Get("htree")
hE2 = ut.prepare_TH1D("hE2", ebin, emin, emax)
htree2.Draw("TMath::Log10(en*1e6) >> hE2", "zpos<150.")
xp2, yp2 = ut.h1_to_arrays(hE2)
#plot
#plt.style.use("dark_background")
#col = "lime"
col = "black"
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
set_axes_color(ax, col)
set_grid(plt, col)
plt.plot(xp, yp, "-", color="blue", lw=1)
plt.plot(xp2, yp2, "-", color="red", lw=1)
ax.set_xlabel("Incident hit energy (keV)")
ax.set_ylabel("Counts")
leg = legend()
leg.add_entry(leg_lin("red"), "$E_\gamma$ > 10 keV")
leg.add_entry(leg_lin("blue"), "$E_\gamma$ > 100 keV")
leg.draw(plt, col)
ax.set_yscale("log")
plt.xticks(ax.get_xticks()[1:-1], ["$10^{"+"{0:.0f}".format(i)+"}$" for i in ax.get_xticks()[1:-1]])
fig.savefig("01fig.pdf", bbox_inches = "tight")
plt.close()
def make_h1(infile, tnam, val, xbin, xmin, xmax):
inp = TFile.Open(infile)
tree = inp.Get(tnam)
#tree.Print()
hx = ut.prepare_TH1D("hx", xbin, xmin, xmax)
tree.Draw(val + " >> hx")
#ut.norm_to_integral(hx, 1.)
return ut.h1_to_arrays(hx)
def get_en(infile, ebin=0.5):
emax = 100.
inp_lmon = TFile.Open(infile)
tree = inp_lmon.Get("bunch")
hE = ut.prepare_TH1D("hE", ebin, 0, emax)
#tree.Draw("bun_up_en+bun_down_en >> hE", "(bun_up_en>1)&&(bun_down_en>1)", "", 1000)
tree.Draw("bun_up_en+bun_down_en >> hE", "(bun_up_en>1)&&(bun_down_en>1)")
ut.norm_to_integral(hE, 1.)
return ut.h1_to_arrays(hE)
def lq_rec():
#spectrum of reconstructed log_10(Q^2)
#infile = "/home/jaroslav/sim/lmon/data/taggers/tag1a/Q2rec_s1.root"
#infile = "/home/jaroslav/sim/lmon/data/taggers/tag1a/Q2rec_s2.root"
#infile = "/home/jaroslav/sim/lmon/data/taggers/tag1ax1/Q2rec_s1.root"
#infile = "/home/jaroslav/sim/lmon/data/taggers/tag1ax1/Q2rec_s2.root"
#infile = "/home/jaroslav/sim/lmon/data/luminosity/lm2ax2/Q2rec_s1.root"
infile = "/home/jaroslav/sim/lmon/data/luminosity/lm2ax2/Q2rec_s2.root"
#range along x in log_10(Q^2) (GeV^2)
xmin = -10
xmax = -1
xbin = 0.1
inp = TFile.Open(infile)
tree = inp.Get("Q2rec")
hx = ut.prepare_TH1D("hx", xbin, xmin, xmax)
tree.Draw("rec_lq >> hx")
ut.norm_to_integral(hx, 1)
xp, yp = ut.h1_to_arrays(hx)
#plot
plt.style.use("dark_background")
col = "lime"
#col = "black"
fig = plt.figure()
fig.set_size_inches(5, 5)
ax = fig.add_subplot(1, 1, 1)
set_axes_color(ax, col)
set_grid(plt, col)
plt.plot(xp, yp, "-", color="blue", lw=1)
ax.set_xlabel("lQ2 (GeV2)")
ax.set_ylabel("Normalized counts")
ax.set_yscale("log")
#plt.xticks(ax.get_xticks()[1:-1], ["$10^{"+"{0:.0f}".format(i+6)+"}$" for i in ax.get_xticks()[1:-1]])
fig.savefig("01fig.pdf", bbox_inches="tight")
plt.close()
def xres():
#position resolution
#mm
xmin = -20
xmax = 20
xbin = 2
infile = "bpc.root"
inp = TFile.Open(infile)
tree = inp.Get("bpc")
hx = ut.prepare_TH1D("hx", xbin, xmin, xmax)
tree.Draw("xrec >> hx")
ut.norm_to_integral(hx, 1)
xp, yp = ut.h1_to_arrays(hx)
#Gaussian fit
cen = []
val = []
for i in range(1, hx.GetNbinsX()+1):
cen.append( hx.GetBinCenter(i) )
val.append( hx.GetBinContent(i) )
pars, cov = curve_fit(lambda x, mu, sig : norm.pdf(x, loc=mu, scale=sig), cen, val)
#print(cen, val)
#fit function
x = np.linspace(cen[0], cen[-1], 300)
y = norm.pdf(x, pars[0], pars[1])
#plot
plt.style.use("dark_background")
col = "lime"
#col = "black"
fig = plt.figure()
fig.set_size_inches(5, 5)
ax = fig.add_subplot(1, 1, 1)
set_axes_color(ax, col)
set_grid(plt, col)
plt.plot(xp, yp, "-", color="blue", lw=1)
plt.plot(x, y, "-", color="red", lw=1)
ax.set_xlabel("x (mm)")
ax.set_ylabel("counts")
#ax.set_yscale("log")
leg = legend()
leg.add_entry(leg_lin("red"), "Gaussian fit")
leg.add_entry(leg_txt(), "mean: {0:.3f}".format(pars[0]))
leg.add_entry(leg_txt(), "sigma: {0:.3f}".format(pars[1]))
leg.draw(plt, col)
fig.savefig("01fig.pdf", bbox_inches = "tight")
plt.close()
def lq_compare():
#input, color, rate in MHz by taggers/hit_rate.py
#Tagger 1
inp_s1 = [\
{"in": "/home/jaroslav/sim/lmon/data/luminosity/lm2ax2/Q2rec_s1.root", "col": "red", "rate": 19.1405, "lab": "Bremsstrahlung"}, \
{"in": "/home/jaroslav/sim/lmon/data/taggers/tag1a/Q2rec_s1.root", "col": "blue", "rate": 0.002905, "lab": "Quasi-real"}, \
{"in": "/home/jaroslav/sim/lmon/data/taggers/tag1ax1/Q2rec_s1.root", "col": "orange", "rate": 0.004053, "lab": "Pythia6"} \
]
#Tagger 2
inp_s2 = [\
{"in": "/home/jaroslav/sim/lmon/data/luminosity/lm2ax2/Q2rec_s2.root", "col": "red", "rate": 22.0011, "lab": "Bremsstrahlung"}, \
{"in": "/home/jaroslav/sim/lmon/data/taggers/tag1a/Q2rec_s2.root", "col": "blue", "rate": 0.005642, "lab": "Quasi-real"}, \
{"in": "/home/jaroslav/sim/lmon/data/taggers/tag1ax1/Q2rec_s2.root", "col": "orange", "rate": 0.008656, "lab": "Pythia6"} \
]
#tnam = "Tagger 1"
#inp = inp_s1
tnam = "Tagger 2"
inp = inp_s2
#range along x in log_10(Q^2) (GeV^2)
xmin = -10
xmax = -1
xbin = 0.1
#plot
#plt.style.use("dark_background")
#col = "lime"
col = "black"
fig = plt.figure()
fig.set_size_inches(5, 5)
ax = fig.add_subplot(1, 1, 1)
set_axes_color(ax, col)
set_grid(plt, col)
leg = legend()
leg.add_entry(leg_txt(), tnam)
#inputs loop
for i in inp:
infile = TFile.Open(i["in"])
tree = infile.Get("Q2rec")
hx = ut.prepare_TH1D("hx_" + i["col"], xbin, xmin, xmax)
tree.Draw("rec_lq >> hx_" + i["col"])
ut.norm_to_integral(hx, i["rate"])
xp, yp = ut.h1_to_arrays(hx)
leg.add_entry(leg_lin(i["col"]), i["lab"])
plt.plot(xp, yp, "-", color=i["col"], lw=1)
ax.set_xlabel("Reconstructed log$_{10}(Q^2)$ (GeV$^2$)")
ax.set_ylabel("Counts normalized to event rate in MHz")
ax.set_yscale("log")
#plt.xticks(ax.get_xticks()[1:-1], ["$10^{"+"{0:.0f}".format(i+6)+"}$" for i in ax.get_xticks()[1:-1]])
leg.draw(plt, col)
fig.savefig("01fig.pdf", bbox_inches="tight")
plt.close()