def plot_rsp_pt(pairs_tree,
pt_var='pt',
pt_title='p_{T}',
pt_min=0,
pt_max=400,
logZ=True,
normX=True,
cut=None,
cleaning_cut=None,
title=None,
oDir=os.getcwd(), output='pt_ptRef.png'):
"""
Plot response vs pt
"""
cut = cut or '1'
cleaning_cut = cleaning_cut or '1'
total_cut = '(%s) && (%s)' % (cut, cleaning_cut)
title = title or ''
c = generate_canvas()
if logZ:
c.SetLogz()
nbins_pt = 200
nbins_rsp, rsp_min, rsp_max = 100, 0, 5
# With cleaning cut
hname = 'hrsp_pt'
pairs_tree.Draw("rsp:%s>>%s(%d, %f, %f, %d, %f, %f)" % (pt_var, hname, nbins_pt, pt_min, pt_max, nbins_rsp, rsp_min, rsp_max),
total_cut,
"COLZ")
h = ROOT.gROOT.FindObject(hname)
h.SetTitle('%s;%s;response (p_{T}^{L1} / p_{T}^{PF})' % (total_cut, pt_title))
h.SetTitleOffset(1.2, 'XY')
if normX:
hnew = cu.norm_vertical_bins(h)
hnew.Draw("COLZ")
draw_horizontal_rsp(pt_max)
c.SaveAs(os.path.join(oDir, output))
if cleaning_cut != '1':
# Inverse of cleaning cut
inv_cut = '(%s) && !(%s)' % (cut, cleaning_cut)
hname = 'hrsp_pt_diff'
pairs_tree.Draw("rsp:%s>>%s(%d, %f, %f, %d, %f, %f)" % (pt_var, hname, nbins_pt, pt_min, pt_max, nbins_rsp, rsp_min, rsp_max),
inv_cut,
"COLZ")
h = ROOT.gROOT.FindObject(hname)
h.SetTitle('%s;%s;response (p_{T}^{L1} / p_{T}^{PF})' % (total_cut, pt_title))
h.SetTitleOffset(1.2, 'XY')
if normX:
hnew = cu.norm_vertical_bins(h)
hnew.Draw("COLZ")
draw_horizontal_rsp(pt_max)
output_name = os.path.splitext(output)[0] + '_diff' + os.path.splitext(output)[1]
c.SaveAs(os.path.join(oDir, output_name))
def plot_rsp_Vs_ref(check_file, eta_min, eta_max, normX, logZ, oDir, oFormat="pdf"):
"""Plot response (l1/ref) Vs ref pt"""
app = "_normX" if normX else ""
hname = "eta_%g_%g/Histograms/h2d_rsp_gen%s" % (eta_min, eta_max, app)
fwd_bin = abs(eta_min)>2.9
if cu.exists_in_file(check_file, hname):
h2d_rsp_ref_orig = cu.get_from_file(check_file, hname)
else:
h2d_rsp_ref_orig = cu.get_from_file(check_file, "eta_%g_%g/Histograms/h2d_rsp_gen" % (eta_min, eta_max))
if normX:
h2d_rsp_ref_orig = cu.norm_vertical_bins(h2d_rsp_ref_orig, rescale_peaks=True)
h2d_rsp_ref = h2d_rsp_ref_orig.Rebin2D(2, 1, "hnew")
c = generate_canvas()
if logZ:
c.SetLogz()
app += "_log"
h2d_rsp_ref.SetTitle("%s: %g-%g;%s;%s" % (eta_l1_str, eta_min, eta_max, pt_ref_str, rsp_str))
if normX:
h2d_rsp_ref.Draw("COL")
else:
h2d_rsp_ref.Draw("COLZ")
h2d_rsp_ref.SetAxisRange(rsp_min, rsp_max, 'Y')
if fwd_bin:
h2d_rsp_ref.SetAxisRange(0, 254, 'X')
line = ROOT.TLine(0, 1, 1022, 1)
line.SetLineStyle(2)
line.SetLineWidth(2)
line.Draw()
c.SaveAs("%s/h2d_rsp_ref_%g_%g%s.%s" % (oDir, eta_min, eta_max, app, oFormat))
def plot_mult_Vs_var(pairs_tree,
var,
var_min=0,
var_max=10,
var_title=None,
logY=False,
logZ=False,
normX=False,
cut=None,
title=None,
oDir=os.getcwd(),
output='rsp_mult.pdf'):
"""Plot multiplicities vs variable 2D hist, for each mulitplicity, on one big canvas.
var: string of varibale name in tree
var_min, var_max: cuts to put on response range
var_title: variable description for axis title
logZ: make Z axis logartithmic
normX: normalise each X bin such that integral of all y values = 1.
cut: cut to apply (no need to include var range)
title: title to put on each plot
oDir: output directory for plot
output: output filename
"""
var_cut = '%s < %d && %s > %d' % (var, var_max, var, var_min)
cut = var_cut if not cut else '%s && %s' % (cut, var_cut)
var_title = var_title or ''
ncol, nrow = 4, 2
c = generate_canvas(width=600 * ncol, height=600 * nrow)
c.Divide(ncol, nrow)
hists = []
for i, mult in enumerate(multiplicities):
c.cd(i + 1)
ROOT.gPad.SetTicks(1, 1)
if logY:
ROOT.gPad.SetLogy()
if logZ:
ROOT.gPad.SetLogz()
hname = 'h2d' + mult
# nbins_var = (var_max - var_min) / 0.05
nbins_var = 100
nbins_mult, mult_min, mult_max = 20, 0, 20
pairs_tree.Draw(
'%s:%s>>%s(%d, %f, %f, %d, %f, %f)' %
(mult, var, hname, nbins_var, var_min, var_max, nbins_mult,
mult_min, mult_max), cut, 'GOFF' if normX else 'COLZ')
h = ROOT.gROOT.FindObject(hname)
h.SetTitle('%s;%s;%s Multiplicity' % (title, var_title, sources[i]))
h.SetTitleOffset(1.2, 'XY')
if normX:
hnew = cu.norm_vertical_bins(h)
hnew.Draw('COLZ')
ROOT.SetOwnership(hnew, False)
# hists.append(hnew)
c.SaveAs(os.path.join(oDir, output))
def plot_energy_Vs_var(pairs_tree, var, var_min=0, var_max=10, var_title=None,
logY=False, logZ=False, normX=False, cut=None, title=None,
oDir=os.getcwd(), output='rsp_energy.pdf'):
"""Plot energy fractions vs variable 2D hist, for each energy source, on one big canvas.
var: string of varibale name in tree
var_min, var_max: cuts to put on response range
var_title: variable description for axis title
logZ: make Z axis logartithmic
normX: normalise each X bin such that integral of all y values = 1.
cut: cut to apply (no need to include var range)
title: title to put on each plot
oDir: output directory for plot
output: output filename
"""
var_cut = '%s < %d && %s > %d' % (var, var_max, var, var_min)
cut = var_cut if not cut else '%s && %s' % (cut, var_cut)
var_title = var_title or ''
ncol, nrow = 4, 2
c = generate_canvas(width=600*ncol, height=600*nrow)
c.Divide(ncol, nrow)
hists = []
for i, fraction in enumerate(fractions):
c.cd(i+1)
ROOT.gPad.SetTicks(1, 1)
if logY:
ROOT.gPad.SetLogy()
if logZ:
ROOT.gPad.SetLogz()
hname = 'h2d' + fraction
# nbins_var = (var_max - var_min) / 0.05
nbins_var = 100
nbins_frac, fmin, fmax = 200, 0, 1.2
pairs_tree.Draw('%s:%s>>%s(%d, %f, %f, %d, %f, %f)' % (fraction, var, hname,
nbins_var, var_min, var_max,
nbins_frac, fmin, fmax),
cut, 'GOFF' if normX else 'COLZ')
h = ROOT.gROOT.FindObject(hname)
h.SetTitle('%s;%s;%s Energy Fraction' % (title, var_title, sources[i]))
h.SetTitleOffset(1.2, 'XY')
if normX:
hnew = cu.norm_vertical_bins(h)
hnew.Draw('COLZ')
ROOT.SetOwnership(hnew, False)
# hists.append(hnew)
c.SaveAs(os.path.join(oDir, output))
def plot_checks(inputfile, outputfile, absetamin, absetamax, max_pt, pu_min, pu_max):
"""
Do all the relevant response 1D and 2D hists, for one eta bin.
Can optionally impose maximum pt cut on L1 jets (to avoid problems with saturation),
and on number of PU vertices.
"""
print "Doing eta bin: %g - %g, max L1 jet pt: %g" % (absetamin, absetamax, max_pt)
# Input tree
tree_raw = inputfile.Get("valid")
# Output folders
output_f = outputfile.mkdir('eta_%g_%g' % (absetamin, absetamax))
output_f_hists = output_f.mkdir("Histograms")
# Eta cut string
eta_cutStr = " TMath::Abs(eta)<%g && TMath::Abs(eta) > %g " % (absetamax, absetamin)
# Pt cut string
pt_cutStr = "pt < %g" % max_pt
# PU cut string
pu_cutStr = "numPUVertices <= %f && numPUVertices >= %f" % (pu_max, pu_min)
cutStr = " && ".join([eta_cutStr, pt_cutStr, pu_cutStr])
# Draw response (pT^L1/pT^Gen) for all pt bins
tree_raw.Draw("rsp>>hrsp_eta_%g_%g(100,0,5)" % (absetamin, absetamax), cutStr)
hrsp_eta = ROOT.gROOT.FindObject("hrsp_eta_%g_%g" % (absetamin, absetamax))
hrsp_eta.SetTitle(";response (p_{T}^{L1}/p_{T}^{Ref});")
if absetamin < 2.9:
fit_result = hrsp_eta.Fit("gaus", "QER", "",
hrsp_eta.GetMean() - hrsp_eta.GetRMS(),
hrsp_eta.GetMean() + hrsp_eta.GetRMS())
else:
peak = hrsp_eta.GetBinCenter(hrsp_eta.GetMaximumBin())
fit_result = hrsp_eta.Fit("gaus", "QER", "",
peak - (0.5 * hrsp_eta.GetRMS()),
peak + (0.5 * hrsp_eta.GetRMS()))
# mean = hrsp_eta.GetFunction("gaus").GetParameter(1)
# err = hrsp_eta.GetFunction("gaus").GetParError(1)
output_f_hists.WriteTObject(hrsp_eta)
# nb_pt, pt_min, pt_max = 63, 0, 252 # for GCT/Stage 1
nb_pt, pt_min, pt_max = 512, 0, 1024 # for Stage 2
nb_rsp, rsp_min, rsp_max = 100, 0, 5
# Draw rsp (pT^L1/pT^Gen) Vs GenJet pT
tree_raw.Draw("rsp:ptRef>>h2d_rsp_gen(%d,%g,%g,%d,%g,%g)" % (nb_pt, pt_min, pt_max, nb_rsp, rsp_min, rsp_max), cutStr)
h2d_rsp_gen = ROOT.gROOT.FindObject("h2d_rsp_gen")
h2d_rsp_gen.SetTitle(";p_{T}^{Ref} [GeV];response (p_{T}^{L1}/p_{T}^{Ref})")
output_f_hists.WriteTObject(h2d_rsp_gen)
h2d_rsp_gen_norm = cu.norm_vertical_bins(h2d_rsp_gen)
output_f_hists.WriteTObject(h2d_rsp_gen_norm)
# Draw rsp (pT^L1/pT^Gen) Vs L1 pT
tree_raw.Draw("rsp:pt>>h2d_rsp_l1(%d,%g,%g,%d,%g,%g)" % (nb_pt, pt_min, pt_max, nb_rsp, rsp_min, rsp_max), cutStr)
h2d_rsp_l1 = ROOT.gROOT.FindObject("h2d_rsp_l1")
h2d_rsp_l1.SetTitle(";p_{T}^{L1} [GeV];response (p_{T}^{L1}/p_{T}^{Ref})")
output_f_hists.WriteTObject(h2d_rsp_l1)
h2d_rsp_l1_norm = cu.norm_vertical_bins(h2d_rsp_l1)
output_f_hists.WriteTObject(h2d_rsp_l1_norm)
# Draw pT^Gen Vs pT^L1
tree_raw.Draw("pt:ptRef>>h2d_gen_l1(%d,%g,%g,%d,%g,%g)" % (nb_pt, pt_min, pt_max, nb_pt, pt_min, pt_max), cutStr)
h2d_gen_l1 = ROOT.gROOT.FindObject("h2d_gen_l1")
h2d_gen_l1.SetTitle(";p_{T}^{Ref} [GeV];p_{T}^{L1} [GeV]")
output_f_hists.WriteTObject(h2d_gen_l1)
def make_2d_plot(tree,
xvar, xtitle, xbins, xmin, xmax,
yvar, ytitle, ybins, ymin, ymax,
output_filename, cut='', title='',
logz=False, normx=False, rescale_peak=True,
horizontal_line=False, diagonal_line=False):
"""Make a 2D heat map.
Parameters
----------
tree : ROOT.TTree
TTree with branches to plots
xvar : str
Variable to plot on x axis
xtitle : str
Title of x axis
xbins : int
Number of bins on x axis
xmin : int
Minimum of x axis range
xmax : int
Maximum of x axis range
yvar : str
Varaible to plot on y axis
ytitle : str
Title of y axis
ybins : int
Number of bins on y axis
ymin : int
Minimum of y axis range
ymax : int
Maximum of y axis range
output_filename : str
Output filename for plot
cut : str, optional
Cut string to apply when doing Draw()
title : str, optional
Title of plot
logz : bool, optional
Make Z axis log
normx : bool, optional
Normalise each x axis bin s.t. integral over y bins = 1
rescale_peak : bool, optional
(Only applies if nromx=True). Rescale peak value in each x bin to be uniform
across all bins, i.e. sets peak color same in all x bins.
horizontal_line : bool, optional
Draw a horizontal line at y = 1
diagonal_line : bool, optional
Draw a diagonal line for y = x
Returns
-------
str
Filename of plot.
"""
canv = generate_canvas()
if logz:
canv.SetLogz()
hname = str(uuid.uuid1())
if normx and not logz:
title += " (NormX)"
if normx and logz:
title += " (NormX, log Z scale)"
h = ROOT.TH2D(hname, ';'.join([title, xtitle, ytitle]),
xbins, xmin, xmax, ybins, ymin, ymax)
tree.Draw("%s:%s>>%s" % (yvar, xvar, hname), cut, 'COLZ')
h.SetTitleOffset(1.15, 'X')
h.SetTitleOffset(1.2, 'Y')
if normx:
h = cu.norm_vertical_bins(h, rescale_peaks=True)
h.Draw("COL")
line = None
if horizontal_line:
line = ROOT.TLine(xmin, 1, xmax, 1)
if diagonal_line:
upper_lim = xmax if ymax > xmax else ymax
line = ROOT.TLine(xmin, ymin, upper_lim, upper_lim)
if line:
line.SetLineWidth(2)
line.SetLineStyle(2)
line.Draw()
out_stem, ext = os.path.splitext(output_filename)
app = ''
if logz:
app += '_log'
if normx:
app += "_normX"
final_filename = out_stem + app + ext
canv.SaveAs(final_filename)
return final_filename
def make_2d_plot(tree,
xvar,
xtitle,
xbins,
xmin,
xmax,
yvar,
ytitle,
ybins,
ymin,
ymax,
output_filename,
cut='',
title='',
logz=False,
normx=False,
rescale_peak=True,
horizontal_line=False,
diagonal_line=False):
"""Make a 2D heat map.
Parameters
----------
tree : ROOT.TTree
TTree with branches to plots
xvar : str
Variable to plot on x axis
xtitle : str
Title of x axis
xbins : int
Number of bins on x axis
xmin : int
Minimum of x axis range
xmax : int
Maximum of x axis range
yvar : str
Varaible to plot on y axis
ytitle : str
Title of y axis
ybins : int
Number of bins on y axis
ymin : int
Minimum of y axis range
ymax : int
Maximum of y axis range
output_filename : str
Output filename for plot
cut : str, optional
Cut string to apply when doing Draw()
title : str, optional
Title of plot
logz : bool, optional
Make Z axis log
normx : bool, optional
Normalise each x axis bin s.t. integral over y bins = 1
rescale_peak : bool, optional
(Only applies if nromx=True). Rescale peak value in each x bin to be uniform
across all bins, i.e. sets peak color same in all x bins.
horizontal_line : bool, optional
Draw a horizontal line at y = 1
diagonal_line : bool, optional
Draw a diagonal line for y = x
Returns
-------
str
Filename of plot.
"""
canv = generate_canvas()
if logz:
canv.SetLogz()
hname = str(uuid.uuid1())
if normx and not logz:
title += " (NormX)"
if normx and logz:
title += " (NormX, log Z scale)"
h = ROOT.TH2D(hname, ';'.join([title, xtitle, ytitle]), xbins, xmin, xmax,
ybins, ymin, ymax)
tree.Draw("%s:%s>>%s" % (yvar, xvar, hname), cut, 'COLZ')
h.SetTitleOffset(1.15, 'X')
h.SetTitleOffset(1.2, 'Y')
if normx:
h = cu.norm_vertical_bins(h, rescale_peaks=True)
h.Draw("COL")
line = None
if horizontal_line:
line = ROOT.TLine(xmin, 1, xmax, 1)
if diagonal_line:
upper_lim = xmax if ymax > xmax else ymax
line = ROOT.TLine(xmin, ymin, upper_lim, upper_lim)
if line:
line.SetLineWidth(2)
line.SetLineStyle(2)
line.Draw()
out_stem, ext = os.path.splitext(output_filename)
app = ''
if logz:
app += '_log'
if normx:
app += "_normX"
final_filename = out_stem + app + ext
canv.SaveAs(final_filename)
return final_filename
def plot_checks(inputfile, outputfile, absetamin, absetamax, max_pt, pu_min,
pu_max):
"""
Do all the relevant response 1D and 2D hists, for one eta bin.
Can optionally impose maximum pt cut on L1 jets (to avoid problems with saturation),
and on number of PU vertices.
"""
print "Doing eta bin: %g - %g, max L1 jet pt: %g" % (absetamin, absetamax,
max_pt)
# Input tree
tree_raw = inputfile.Get("valid")
# Output folders
output_f = outputfile.mkdir('eta_%g_%g' % (absetamin, absetamax))
output_f_hists = output_f.mkdir("Histograms")
# Eta cut string
eta_cutStr = " TMath::Abs(eta)<%g && TMath::Abs(eta) > %g " % (absetamax,
absetamin)
# Pt cut string
pt_cutStr = "pt < %g" % max_pt
# PU cut string
pu_cutStr = "numPUVertices <= %f && numPUVertices >= %f" % (pu_max, pu_min)
# Avoid L1 saturated jets cut (from 2017 any l1 jet with a saturated tower is auto given pt=1024GeV)
avoidSaturation_cut = "pt < 1023.1"
cutStr = " && ".join(
[eta_cutStr, pt_cutStr, pu_cutStr, avoidSaturation_cut])
# Draw response (pT^L1/pT^Gen) for all pt bins
tree_raw.Draw("rsp>>hrsp_eta_%g_%g(100,0,5)" % (absetamin, absetamax),
cutStr)
hrsp_eta = ROOT.gROOT.FindObject("hrsp_eta_%g_%g" % (absetamin, absetamax))
hrsp_eta.SetTitle(";response (p_{T}^{L1}/p_{T}^{Ref});")
if absetamin < 2.9:
fit_result = hrsp_eta.Fit("gaus", "QER", "",
hrsp_eta.GetMean() - hrsp_eta.GetRMS(),
hrsp_eta.GetMean() + hrsp_eta.GetRMS())
else:
peak = hrsp_eta.GetBinCenter(hrsp_eta.GetMaximumBin())
fit_result = hrsp_eta.Fit("gaus", "QER", "",
peak - (0.5 * hrsp_eta.GetRMS()),
peak + (0.5 * hrsp_eta.GetRMS()))
# mean = hrsp_eta.GetFunction("gaus").GetParameter(1)
# err = hrsp_eta.GetFunction("gaus").GetParError(1)
output_f_hists.WriteTObject(hrsp_eta)
# nb_pt, pt_min, pt_max = 63, 0, 252 # for GCT/Stage 1
nb_pt, pt_min, pt_max = 512, 0, 1024 # for Stage 2
nb_rsp, rsp_min, rsp_max = 100, 0, 5
# Draw rsp (pT^L1/pT^Gen) Vs GenJet pT
tree_raw.Draw(
"rsp:ptRef>>h2d_rsp_gen(%d,%g,%g,%d,%g,%g)" %
(nb_pt, pt_min, pt_max, nb_rsp, rsp_min, rsp_max), cutStr)
h2d_rsp_gen = ROOT.gROOT.FindObject("h2d_rsp_gen")
h2d_rsp_gen.SetTitle(
";p_{T}^{Ref} [GeV];response (p_{T}^{L1}/p_{T}^{Ref})")
output_f_hists.WriteTObject(h2d_rsp_gen)
h2d_rsp_gen_norm = cu.norm_vertical_bins(h2d_rsp_gen)
output_f_hists.WriteTObject(h2d_rsp_gen_norm)
# Draw rsp (pT^L1/pT^Gen) Vs L1 pT
tree_raw.Draw(
"rsp:pt>>h2d_rsp_l1(%d,%g,%g,%d,%g,%g)" %
(nb_pt, pt_min, pt_max, nb_rsp, rsp_min, rsp_max), cutStr)
h2d_rsp_l1 = ROOT.gROOT.FindObject("h2d_rsp_l1")
h2d_rsp_l1.SetTitle(";p_{T}^{L1} [GeV];response (p_{T}^{L1}/p_{T}^{Ref})")
output_f_hists.WriteTObject(h2d_rsp_l1)
h2d_rsp_l1_norm = cu.norm_vertical_bins(h2d_rsp_l1)
output_f_hists.WriteTObject(h2d_rsp_l1_norm)
# Draw pT^Gen Vs pT^L1
tree_raw.Draw(
"pt:ptRef>>h2d_gen_l1(%d,%g,%g,%d,%g,%g)" %
(nb_pt, pt_min, pt_max, nb_pt, pt_min, pt_max), cutStr)
h2d_gen_l1 = ROOT.gROOT.FindObject("h2d_gen_l1")
h2d_gen_l1.SetTitle(";p_{T}^{Ref} [GeV];p_{T}^{L1} [GeV]")
output_f_hists.WriteTObject(h2d_gen_l1)
def plot_rsp_pt(pairs_tree,
pt_var='pt',
pt_title='p_{T}',
pt_min=0,
pt_max=400,
logZ=True,
normX=True,
cut=None,
cleaning_cut=None,
title=None,
oDir=os.getcwd(),
output='pt_ptRef.png'):
"""
Plot response vs pt
"""
cut = cut or '1'
cleaning_cut = cleaning_cut or '1'
total_cut = '(%s) && (%s)' % (cut, cleaning_cut)
title = title or ''
c = generate_canvas()
if logZ:
c.SetLogz()
nbins_pt = 200
nbins_rsp, rsp_min, rsp_max = 100, 0, 5
# With cleaning cut
hname = 'hrsp_pt'
pairs_tree.Draw(
"rsp:%s>>%s(%d, %f, %f, %d, %f, %f)" %
(pt_var, hname, nbins_pt, pt_min, pt_max, nbins_rsp, rsp_min, rsp_max),
total_cut, "COLZ")
h = ROOT.gROOT.FindObject(hname)
h.SetTitle('%s;%s;response (p_{T}^{L1} / p_{T}^{PF})' %
(total_cut, pt_title))
h.SetTitleOffset(1.2, 'XY')
if normX:
hnew = cu.norm_vertical_bins(h)
hnew.Draw("COLZ")
draw_horizontal_rsp(pt_max)
c.SaveAs(os.path.join(oDir, output))
if cleaning_cut != '1':
# Inverse of cleaning cut
inv_cut = '(%s) && !(%s)' % (cut, cleaning_cut)
hname = 'hrsp_pt_diff'
pairs_tree.Draw(
"rsp:%s>>%s(%d, %f, %f, %d, %f, %f)" %
(pt_var, hname, nbins_pt, pt_min, pt_max, nbins_rsp, rsp_min,
rsp_max), inv_cut, "COLZ")
h = ROOT.gROOT.FindObject(hname)
h.SetTitle('%s;%s;response (p_{T}^{L1} / p_{T}^{PF})' %
(total_cut, pt_title))
h.SetTitleOffset(1.2, 'XY')
if normX:
hnew = cu.norm_vertical_bins(h)
hnew.Draw("COLZ")
draw_horizontal_rsp(pt_max)
output_name = os.path.splitext(output)[0] + '_diff' + os.path.splitext(
output)[1]
c.SaveAs(os.path.join(oDir, output_name))
