if hTrue is None:

divider = hMeas

else:

divider = hTrue

hTrue.SetMarkerColor("red")

hMeas.SetMarkerColor("blue")

hReco.SetMarkerColor(3)

ratioMeas = hMeas.Clone()

ratioMeas.Divide(divider)

ratioReco = hReco.Clone()

ratioReco.Divide(divider)

fig, axs = plt.subplots(2, 1, figsize=(5, 8), sharey=False, sharex=True)

axs = axs.reshape(2)

axs[0].text(

45,

1e-2,

r"pPb $\sqrt{s_{NN}} = 5.02 \mathrm{TeV}$"

"\n Full jets\n"

r"Anti-$k_T$, R=0.4",

fontsize=7,

)

axs[0].set_ylabel(r"$\frac{dN}{dp_{T,jet}}$", fontsize=18)

axs[0].set_xlabel(r"$p_{T,jet}$", fontsize=18)

axs[1].set_xlabel(r"$p_{T,jet}$", fontsize=18)

axs[1].set_ylabel("Ratio", fontsize=18)

ax = axs[0]

ax.set_xscale("log") # Set logarithmic scale

ax.set_yscale("log")

ax.set_xlim([5, 500]) # Set x-axis limits

ax.set_ylim([1, 500]) # Set y-axis limits

rplt.errorbar(

hMeas, xerr=False, emptybins=False, axes=ax, label="Measured", fmt="go"

) # Plot measured pT

rplt.errorbar(

hReco, xerr=False, emptybins=False, axes=ax, label="Unfolded", fmt="go"

) # Plot unfolded pT

if hTrue is not None:

rplt.errorbar(

hTrue, xerr=False, emptybins=False, axes=ax, label="True", fmt="go"

) # Plot True pT

maxContent = hMeas.GetBinContent(hMeas.GetMaximumBin())

ax.set_ylim([3e-10 * maxContent, 10 * maxContent])

ax.legend(loc="lower left")

ax.yaxis.set_ticks_position("both") # Show ticks on left and right side

ax.xaxis.set_ticks_position("both") # Show ticks on bottom and top

ax.tick_params(which="both", direction="in") # Move ticks from outside to inside

# ax.text(0.3,1e2,r'$p_{{T,\mathrm{{jet}}}}$:''\n'r' {:02d}-{:02d} GeV'.format(pT[0],pT[1]))

ax.grid(True) # Draw grid

ax = axs[1]

rplt.errorbar(ratioMeas, xerr=False, emptybins=False, axes=ax, fmt="o")

rplt.errorbar(ratioReco, xerr=False, emptybins=False, axes=ax, fmt="o")

ax.yaxis.set_ticks_position("both") # Show ticks on left and right side

ax.xaxis.set_ticks_position("both") # Show ticks on bottom and top

ax.tick_params(which="both", direction="in") # Move ticks from outside to inside

# ax.text(0.3,1e2,r'$p_{{T,\mathrm{{jet}}}}$:''\n'r' {:02d}-{:02d} GeV'.format(pT[0],pT[1]))

ax.set_xscale("log") # Set logarithmic scale

# ax.set_yscale('log')

ax.set_xlim([5, 500]) # Set x-axis limits

ax.set_ylim([0, 2]) # Set y-axis limits

ax.grid(True) # Draw grid

plt.tight_layout()

plt.subplots_adjust(wspace=0, hspace=0) # Set space between subfigures to 0

plt.savefig(filename, format="pdf") # Save figure

fig, axs = plt.subplots(1, 1, figsize=(10, 10), sharex=True, sharey=True)

# axs = axs.reshape(4)

ax = axs

ax.set_xlabel(r"$j_T$")

ax.set_ylabel(r"$p_{T,jet}$")

ax.set_xscale("log")

# ax.set_yscale('log')

# rplt.hist2d(hist,label="Hist",norm=PowerNorm(0.8),colorbar=True)

rplt.hist2d(hist, label="Hist", norm=LogNorm(), colorbar=True)

ax.set_xlim([0.01, 10])

ax.set_ylim([5, 100])

ax.text(

1,

7,

title,

fontsize=10,

bbox=dict(boxstyle="round", ec=(1.0, 0.5, 0.5), fc=(1.0, 0.8, 0.8), alpha=0.8),

)

fig, axs = plt.subplots(1, 2, figsize=(10, 10))

axs = axs.reshape(2)

for ax, h, title in zip(axs, hists, titles):

ax.set_xlabel(r"$j_T$")

ax.set_ylabel(r"$p_{T,jet}$")

ax.set_xscale("log")

# ax.set_yscale('log')

# rplt.hist2d(hist,label="Hist",norm=PowerNorm(0.8),colorbar=True)

rplt.hist2d(h, axes=ax, label=title, norm=LogNorm(), colorbar=True)

ax.set_xlim([0.01, 10])

ax.set_ylim([5, 100])

ax.text(

1,

7,

title,

fontsize=10,

bbox=dict(

boxstyle="round", ec=(1.0, 0.5, 0.5), fc=(1.0, 0.8, 0.8), alpha=0.8

),

)

hJtMeas,

hJtTrue,

hJtFake,

hRecoBayes,

hRecoSVD,

hReco2D,

hZ,

hZTrue,

hZMeas,

hZFake,

hMultiMeas,

hMultiTrue,

hJetPt,

hJetPtTrue,

hJetPtMeas,

hJetPtReco,

responseM,

):

fig, axs = plt.subplots(2, 3, figsize=(15, 10))

axs = axs.reshape(6)

axs[2].yaxis.set_ticks_position("right")

axs[2].yaxis.set_ticks_position("right")

axs[5].yaxis.set_label_position("right")

axs[5].yaxis.set_label_position("right")

for ax in axs:

ax.grid(True)

drawJt(axs[0], hJtMeas, hJtTrue, hJtFake, hRecoBayes, hRecoSVD, hReco2D)

hZInput = hZ.Clone()

hZInput.Scale(hZTrue.Integral() / hZ.Integral())

drawJtRatio(axs[3], hJtMeas, hJtTrue, hJtFake, hRecoBayes, hRecoSVD, hReco2D)

drawZ(axs[1], hZMeas, hZTrue, hZInput, hZFake)

drawMulti(axs[2], hMultiMeas, hMultiTrue)

hJetPtInput = hJetPt.Clone()

hJetPtInput.Scale(hJetPtTrue.Integral() / hJetPt.Integral())

drawJetPtQA(axs[4], hJetPtMeas, hJetPtTrue, hJetPtInput, hJetPtReco)

drawResponse(axs[5], responseM)

ax.set_xlabel(r"$j_{T,obs}\left[GeV\right]$") # Add x-axis labels for bottom row

ax.set_ylabel(r"$j_{T,true}\left[GeV\right]$") # Add x-axis labels for bottom row

# rplt.hist2d(hist, label = "Hist",norm=LogNorm(),colorbar=True)

rplt.hist2d(hist, label="Hist")

ax.set_xlim([0.01, 10])

ax.set_ylim([0.01, 10])

# ax.set_xscale('log')

ax.set_xlabel(r"$p_{T,obs}\left[GeV\right]$") # Add x-axis labels for bottom row

ax.set_ylabel(r"$p_{T,true}\left[GeV\right]$") # Add x-axis labels for bottom row

# rplt.hist2d(hist, label = "Hist",norm=LogNorm(),colorbar=True)

rplt.hist2d(hist, label="Hist", norm=LogNorm())

ax.set_xlim([5, 150])

ax.set_ylim([5, 150])

# ax.set_xscale('log')

ax.set_xlabel(r"$j_T$")

ax.set_ylabel("Ratio to Truth", fontsize=12)

ax.set_xscale("log")

hJtMeas.linecolor = "blue"

hJtTrue.linecolor = "red"

hRecoBayes.linecolor = "green"

hRecoSVD.linecolor = "black"

hReco2D.linecolor = "cyan"

hJtFake.linecolor = "yellow"

h1 = hJtMeas.Clone()

h2 = hJtTrue.Clone()

h3 = hRecoBayes.Clone()

h4 = hRecoSVD.Clone()

h5 = hReco2D.Clone()

h6 = hJtFake.Clone()

for h in (h1, h2, h3, h4, h5, h6):

h.Divide(hJtTrue)

rplt.hist(h1, axes=ax, label="Measured")

rplt.hist(h2, axes=ax, label="True") # Plot jT histogram,

rplt.hist(h3, axes=ax, label="Bayes")

rplt.hist(h4, axes=ax, label="SVD")

rplt.hist(h5, axes=ax, label="2D Unfolded")

rplt.hist(h6, axes=ax, label="Fake")

ax.set_xlim([0.01, 10])

ax.set_xlim([0.01, 10])

ax.set_ylim([1e-5, 1000])

ax.set_xlabel(r"$j_T$")

ax.set_ylabel(r"$\frac{1}{N_{jets}}\frac{dN}{j_{T}dj_{T}}$", fontsize=18)

ax.set_yscale("log")

ax.set_xscale("log")

hJtMeas.linecolor = "blue"

hJtTrue.linecolor = "red"

hRecoBayes.linecolor = "green"

hRecoSVD.linecolor = "black"

hReco2D.linecolor = "cyan"

hJtFake.linecolor = "yellow"

rplt.hist(hJtMeas, axes=ax, label="Measured")

rplt.hist(hJtTrue, axes=ax, label="True") # Plot jT histogram,

rplt.hist(hRecoBayes, axes=ax, label="Bayes")

rplt.hist(hRecoSVD, axes=ax, label="SVD")

rplt.hist(hReco2D, axes=ax, label="2D")

rplt.hist(hJtFake, axes=ax, label="Fake")

# ax.set_xlim([0,10])

# ax.set_ylim([1e-5,1000])

ax.set_xlabel(r"$Z$")

ax.set_ylabel(r"$\frac{1}{N_{jets}}\frac{dN}{dZ}$", fontsize=18)

ax.set_yscale("log")

# ax.set_xscale('log')

hMeas.linecolor = "blue"

hTrue.linecolor = "red"

hInput.linecolor = "pink"

hFake.linecolor = "yellow"

rplt.hist(hInput, axes=ax, label="Input")

rplt.hist(hMeas, axes=ax, label="Measured")

rplt.hist(hTrue, axes=ax, label="True") # Plot jT histogram,

rplt.hist(hFake, axes=ax, label="Fake")

# ax.set_ylim([1e-5,1000])

ax.set_xlabel(r"$N_{tracks}$")

ax.set_ylabel(r"$\frac{1}{N_{jets}}\frac{dN}{dN_{tracks}}$", fontsize=18)

ax.set_yscale("log")

# ax.set_xscale('log')

hMeas.linecolor = "blue"

hTrue.linecolor = "red"

rplt.hist(hMeas, axes=ax, label="Measured")

rplt.hist(hTrue, axes=ax, label="True") # Plot jT histogram,

# ax.set_ylim([1e-5,1000])

ax.set_xlabel(r"$p_{T}$")

ax.set_ylabel(r"$\frac{dN}{dp_{jet}}$", fontsize=18)

ax.set_yscale("log")

ax.set_xscale("log")

hMeas.linecolor = "blue"

hTrue.linecolor = "red"

hInput.linecolor = "pink"

hReco.linecolor = "green"

rplt.hist(hInput, axes=ax, label="Input")

rplt.hist(hMeas, axes=ax, label="Measured")

rplt.hist(hTrue, axes=ax, label="True")

rplt.hist(hReco, axes=ax, label="Unfolded")

"""Create an 4 by 2 grid of subfigures with shared axes and plots jT with background in jet pT bins

Args:

measJt: List of jT histograms

jetPt: List of jet Pt bins in tuples (low border, high border)

xlog: Whether to use logarithmic scale on X-axis, default is True

ylog: Whether to use logarithmic scale on Y-axis, default is True

name: Name of output file

"""

if option == "grid":

fig, axs = plt.subplots(

2, 4, figsize=(10, 5), sharey=True, sharex=True

) # Create figure with 8 subfigures, axs is a list of subfigures, fig is the whole thing

axs = axs.reshape(

8

) # Because the figures is in a 2x4 layout axs is a 2 dimensional array with 2x4 elements, this makes it a 1 dimensional array with 8 elements

# axs[1].text(0.02,0.005,r'pPb $\sqrt{s_{NN}} = 5.02 \mathrm{TeV}$' '\n Charged jT\n' r'Anti-$k_T$, R=0.4' '\nJet Cone',fontsize=7) #Add text to second subfigure, first parameters are coordinates in the drawn scale/units

for ax in [axs[0], axs[3], axs[4], axs[7]]:

ax.set_ylabel(

"Normalized", fontsize=12

) # Add y-axis labels to left- and righmost subfigures

for ax in axs[4:]:

# ax.set_xlabel(r'$j_{T}\left[GeV\right]$') #Add x-axis labels for bottom row

ax.xaxis.set_ticks((0.5, 1.5, 2.5, 3.5, 4.5, 5.5))

ax.set_xticklabels(

(

"No match",

"One match",

"More than 2 matches",

"No measured jT",

"Two matches",

"Fake tracks",

),

rotation="vertical",

)

for ax in [axs[3], axs[7]]:

ax.yaxis.set_label_position(

"right"

) # Set the y-axis label position to right hand side for the rightmost subfigures

for (h, ax, i, pT) in zip(hists, axs, range(0, 8), jetPt):

h.Scale(1.0 / h.Integral(0, 5))

rplt.hist(h, xerr=False, emptybins=False, axes=ax)

# rplt.errorbar(true,xerr=False,emptybins=False,axes=ax,label='True jT',fmt='go')

# if i == 0: #For the first subfigure add a legend to bottom left corner

# ax.legend(loc ='lower left')

ax.yaxis.set_ticks_position("both") # Show ticks on left and right side

ax.xaxis.set_ticks_position("both") # Show ticks on bottom and top

ax.xaxis.set_major_locator(MaxNLocator(prune="both"))

ax.tick_params(

which="both", direction="in"

) # Move ticks from outside to inside

ax.text(

3,

0.5,

r"$p_{{T,\mathrm{{jet}}}}$:"

"\n"

r" {:02d}-{:02d} GeV".format(pT[0], pT[1]),

)

ax.set_xlim([0, 6]) # Set x-axis limits

ax.set_ylim([0, 1]) # Set y-axis limits

ax.grid(False) # Draw grid

ax.xaxis.set_ticks((0.5, 1.5, 2.5, 3.5, 4.5, 5.5))

plt.tight_layout()

plt.subplots_adjust(wspace=0, hspace=0) # Set space between subfigures to 0

plt.savefig(name, format="pdf") # Save figure

plt.show() # Draw figure on screen

if option == "single":

ax2 = plt.gca()

ax2.set_ylabel("Normalized")

ax2.set_ylim([0, 1])

ax2.set_xlim([0, 5])

ax2.set_xticklabels(

(

"No match",

"One match",

"More than 2 matches",

"No measured jT",

"Two matches",

"Fake tracks",

),

rotation="vertical",

)

ax2.xaxis.set_ticks((0.5, 1.5, 2.5, 3.5, 4.5, 5.5))

ax2.yaxis.set_ticks_position("both")

for h, pT, i, c in zip(

hists,

jetPt,

range(0, 5),

("red", "blue", "green", "yellow", "cyan", "orange", "black", "magenta"),

):

h.color = c

h.fillstyle = "hollow"

h.Scale(1.0 / h.Integral(0, 5))

rplt.hist(

h,

xerr=False,

emptybins=False,

axes=ax2,

histtype="bar",

label=r"$p_{{T,\mathrm{{jet}}}}$:"

"\n"

r" {:02d}-{:02d} GeV".format(pT[0], pT[1]),

)

ax2.legend(loc="upper right")

plt.savefig(name, format="pdf")

measJt,

trueJt,

jetPt,

xlog=True,

ylog=True,

name="newfile.pdf",

proj=None,

unf2d=None,

unf=None,

):

"""Create an 4 by 2 grid of subfigures with shared axes and plots jT with background in jet pT bins

Args:

measJt: List of jT histograms

jetPt: List of jet Pt bins in tuples (low border, high border)

xlog: Whether to use logarithmic scale on X-axis, default is True

ylog: Whether to use logarithmic scale on Y-axis, default is True

name: Name of output file

"""

fig, axs = plt.subplots(

2, 4, figsize=(10, 5), sharey=True, sharex=True

) # Create figure with 8 subfigures, axs is a list of subfigures, fig is the whole thing

axs = axs.reshape(

8

) # Because the figures is in a 2x4 layout axs is a 2 dimensional array with 2x4 elements, this makes it a 1 dimensional array with 8 elements

# axs[1].text(0.02,0.005,r'pPb $\sqrt{s_{NN}} = 5.02 \mathrm{TeV}$' '\n Charged jT\n' r'Anti-$k_T$, R=0.4' '\nJet Cone',fontsize=7) #Add text to second subfigure, first parameters are coordinates in the drawn scale/units

for ax in [axs[0], axs[3], axs[4], axs[7]]:

ax.set_ylabel(

r"$\frac{1}{N_{jets}}\frac{dN}{j_{T}dj_{T}}$", fontsize=18

) # Add y-axis labels to left- and righmost subfigures

for ax in axs[4:]:

ax.set_xlabel(r"$j_{T}\left[GeV\right]$") # Add x-axis labels for bottom row

for ax in [axs[3], axs[7]]:

ax.yaxis.set_label_position(

"right"

) # Set the y-axis label position to right hand side for the rightmost subfigures

for (jT, true, ax, i, pT) in zip(measJt, trueJt, axs, range(0, 8), jetPt):

if xlog:

ax.set_xscale("log") # Set logarithmic scale

if ylog:

ax.set_yscale("log")

jT.SetMarkerColor("blue")

true.SetMarkerColor("red")

rplt.errorbar(

jT, xerr=False, emptybins=False, axes=ax, label="Measured jT", fmt="+"

)

rplt.errorbar(

true, xerr=False, emptybins=False, axes=ax, label="True jT", fmt="go"

)

for h, color, title in zip(

(proj, unf, unf2d),

(1, 3, 6),

("Projected Meas", "1D unfolded", "2D unfolded"),

):

if h is not None:

h[i].SetMarkerColor(color)

rplt.errorbar(

h[i], xerr=False, emptybins=False, axes=ax, label=title, fmt="go"

)

if i == 0: # For the first subfigure add a legend to bottom left corner

ax.legend(loc="lower left")

ax.yaxis.set_ticks_position("both") # Show ticks on left and right side

ax.xaxis.set_ticks_position("both") # Show ticks on bottom and top

ax.xaxis.set_major_locator(MaxNLocator(prune="both"))

ax.tick_params(

which="both", direction="in"

) # Move ticks from outside to inside

ax.text(

0.3,

1e2,

r"$p_{{T,\mathrm{{jet}}}}$:"

"\n"

r" {:02d}-{:02d} GeV".format(pT[0], pT[1]),

)

ax.set_xlim([0.01, 5]) # Set x-axis limits

ax.set_ylim([5e-4, 2e3]) # Set y-axis limits

ax.grid(True) # Draw grid

plt.tight_layout()

plt.subplots_adjust(wspace=0, hspace=0) # Set space between subfigures to 0

plt.savefig(name, format="pdf") # Save figure

measJt,

trueJt,

jetPt,

xlog=True,

ylog=True,

name="newfile.pdf",

proj=None,

unf2d=None,

unf=None,

fake=None,

unf2dtest=None,

leadingJt=None,

backgroundJt=None,

**kwargs

):

"""Create an 4 by 2 grid of subfigures with shared axes and plots jT with

background in jet pT bins

Args:

measJt: List of jT histograms

jetPt: List of jet Pt bins in tuples (low border, high border)

xlog: Whether to use logarithmic scale on X-axis, default is True

ylog: Whether to use logarithmic scale on Y-axis, default is True

name: Name of output file

"""

if "start" in kwargs:

start = kwargs.get("start")

else:

start = 0

if "stride" in kwargs:

stride = kwargs.get("stride")

else:

stride = 2

# Create figure with 8 subfigures, axs is a list of subfigures,

# fig is the whole thing

fig, axs = plt.subplots(2, 4, figsize=(14, 7), sharey=False, sharex=True)

# Because the figures is in a 2x4 layout axs is a 2 dimensional array

# with 2x4 elements, this makes it a 1 dimensional array with 8 elements

axs = axs.reshape(8)

# axs[1].text(0.02,0.005,r'pPb $\sqrt{s_{NN}} = 5.02 \mathrm{TeV}$' '\n Charged jT\n' r'Anti-$k_T$, R=0.4' '\nJet Cone',fontsize=7) #Add text to second subfigure, first parameters are coordinates in the drawn scale/units

for ax in [axs[0], axs[3]]:

ax.set_ylabel(

r"$\frac{1}{N_{jets}}\frac{dN}{j_{T}dj_{T}}$", fontsize=18

) # Add y-axis labels to left- and righmost subfigures

for ax in [axs[4], axs[7]]:

ax.set_ylabel(

"Ratio to truth", fontsize=12

) # Add y-axis labels to left- and righmost subfigures

for ax in axs[4:]:

# Add x-axis labels for bottom row

ax.set_xlabel(r"$j_{T}\left[GeV\right]$")

for ax in [axs[3], axs[7]]:

# Set the y-axis label position to right hand

# side for the rightmost subfigures

ax.yaxis.set_label_position("right")

if trueJt:

divider = trueJt

else:

divider = measJt

ratios = []

for hists in (measJt, proj, unf2d, unf2dtest, unf, fake, leadingJt, backgroundJt):

if hists is not None:

ratio = []

for h, true in zip(hists, divider):

h2 = h.Clone()

h2.Divide(true)

ratio.append(h2)

else:

ratio = None

ratios.append(ratio)

for (jT, ax, i, pT) in zip(

measJt[start::stride], axs[0:4], range(start, 8, stride), jetPt[start::stride]

):

if xlog:

ax.set_xscale("log") # Set logarithmic scale

if ylog:

ax.set_yscale("log")

jT.SetMarkerColor("blue")

# true.SetMarkerColor('red')

if leadingJt is None:

rplt.errorbar(

jT, xerr=False, emptybins=False, axes=ax, label="Measured jT", fmt="+"

)

# rplt.errorbar(true,xerr=False,emptybins=False,axes=ax,label='True jT',fmt='go')

for h, color, title in zip(

(trueJt, proj, unf2d, unf2dtest, unf, fake, leadingJt, backgroundJt),

("red", 1, 3, 8, 6, 7, 9, 4),

(

"True jT",

"Projected Meas",

"2D unfolded",

"2D unfolded test",

"1D unfolded",

"Fakes",

"Leading ref.",

"Background Jt"

),

):

if h is not None:

h[i].SetMarkerColor(color)

rplt.errorbar(

h[i], xerr=False, emptybins=False, axes=ax, label=title, fmt="go"

)

if i == start: # For the first subfigure add a legend to bottom left corner

ax.legend(loc="lower left")

ax.yaxis.set_ticks_position("both") # Show ticks on left and right side

ax.xaxis.set_ticks_position("both") # Show ticks on bottom and top

ax.xaxis.set_major_locator(MaxNLocator(prune="both"))

ax.tick_params(

which="both", direction="in"

) # Move ticks from outside to inside

ax.text(

0.3,

1e2,

r"$p_{{T,\mathrm{{jet}}}}$:"

"\n"

r" {:02d}-{:02d} GeV".format(pT[0], pT[1]),

)

if leadingJt is None:

ax.set_xlim([0.01, 5]) # Set x-axis limits

else:

ax.set_xlim([0.01, 20]) # Set x-axis limits

maxContent = measJt[start].GetBinContent(measJt[start].GetMaximumBin())

# ax.set_ylim([5e-4,2e4]) #Set y-axis limits

ax.set_ylim([5e-8 * maxContent, 5 * maxContent]) # Set y-axis limits

ax.grid(True) # Draw grid

for ratio, color, title in zip(

ratios,

("blue", 1, 3, 8, 6, 7, 9, 4),

(

"Measured",

"Projected Meas",

"2D unfolded",

"2D unfolded test",

"1D unfolded",

"Fakes",

"Leading ref.",

"Background Jt"

),

):

if ratio is not None:

for r, ax, i in zip(

ratio[start::stride], axs[4:8], range(start, 8, stride),

):

if xlog:

ax.set_xscale("log")

r.SetMarkerColor(color)

if leadingJt is None or title != "Measured":

rplt.errorbar(

r, xerr=False, emptybins=False, axes=ax, label=title, fmt="go"

)

if leadingJt is None:

ax.set_xlim([0.01, 5]) # Set x-axis limits

ax.set_ylim([0, 2]) # Set y-axis limits

else:

ax.set_xlim([0.01, 20]) # Set x-axis limits

ax.set_ylim([0, 2]) # Set y-axis limits

ax.grid(True)

plt.tight_layout()

plt.subplots_adjust(wspace=0, hspace=0) # Set space between subfigures to 0

plt.savefig(name, format="pdf") # Save figure