def create_histograms(
self, online_title, offline_title, versus_title, pileup_bins,
res_n_bins, res_low, res_high, vs_n_bins, vs_low, vs_high):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.offline_title = offline_title
self.versus_title = versus_title
self.ymin = res_low
self.ymax = res_high
self.pileup_bins = bn.Sorted(pileup_bins, "pileup",
use_everything_bin=True)
nameTokens = [
"resolution_vs", self.versus_name,
self.online_name, self.offline_name, "pu_{pileup}",
]
name = "__".join(nameTokens)
title = 'Resolution ({online_name} vs. {offline_name}) '
title += 'against {versus_name}'
title = title.format(
online_name=self.online_name,
offline_name=self.offline_name,
versus_name=self.versus_name,
)
title += " in PU bin: {pileup}"
title = ";".join([title, self.offline_title, self.online_title])
self.plots = HistogramCollection(
[self.pileup_bins],
"Hist2D", vs_n_bins, vs_low, vs_high,
res_n_bins, res_low, res_high,
name=name, title=title)
self.filename_format = name
def create_histograms(self,
online_title,
pileup_bins,
n_bins,
low,
high,
legend_title=""):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.pileup_bins = bn.Sorted(pileup_bins,
"pileup",
use_everything_bin=True)
self.legend_title = legend_title
name = ["rate_vs_threshold", self.online_name, "pu_{pileup}"]
name = "__".join(name)
title = " ".join([self.online_name, "vs.", "in PU bin: {pileup}"])
title = ";".join([title, self.online_title])
self.plots = HistogramCollection([self.pileup_bins],
"Hist1D",
n_bins,
low,
high,
name=name,
title=title)
self.filename_format = name
def create_histograms(self,
online_title,
thresholds,
n_bins,
low,
high,
legend_title=""):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.thresholds = thresholds
self.thresholds = bn.GreaterThan(thresholds, "threshold", True)
self.legend_title = legend_title
name = ["rate_vs_pileup", self.online_name]
name += ["thresh_{threshold}"]
name = "__".join(name)
title = " ".join([
self.online_name, " rate vs pileup",
"passing threshold: {threshold}"
])
self.plots = HistogramCollection([self.thresholds],
"Hist1D",
n_bins,
low,
high,
name=name,
title=title)
self.filename_format = name
def create_histograms(
self,
online_title,
offline_title,
pileup_bins,
n_bins,
low,
high=400.,
):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.offline_title = offline_title
self.pileup_bins = bn.Sorted(
pileup_bins,
"pileup",
use_everything_bin=True,
)
nameTokens = [
"onlineVsOffline",
self.online_name,
self.offline_name,
"pu_{pileup}",
]
name = "__".join(nameTokens)
title = " ".join([
self.online_name,
"vs.",
self.offline_name,
"in PU bin: {pileup}",
])
title = ";".join([title, self.offline_title, self.online_title])
if isinstance(low, np.ndarray):
self.plots = HistogramCollection(
[self.pileup_bins],
"Hist2D",
low,
low,
name=name,
title=title,
)
else:
self.plots = HistogramCollection(
[self.pileup_bins],
"Hist2D",
n_bins,
low,
high,
n_bins,
low,
high,
name=name,
title=title,
)
self.filename_format = name
def create_histograms(self,
online_title,
offline_title,
pileup_bins,
thresholds,
n_bins,
low,
high=400,
legend_title=""):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.offline_title = offline_title
self.pileup_bins = bn.Sorted(pileup_bins,
"pileup",
use_everything_bin=True)
self.thresholds = bn.GreaterThan(thresholds, "threshold")
self.legend_title = legend_title
name = ["efficiency", self.online_name, self.offline_name]
name += ["thresh_{threshold}", "pu_{pileup}"]
name = "__".join(name)
title = " ".join([
self.online_name, " in PU bin: {pileup}",
"and passing threshold: {threshold}"
])
self.filename_format = name
def make_efficiency(labels):
this_name = "efficiency" + name.format(**labels)
this_title = title.format(**labels)
'''Checking type of 'low' to see whether it's int (x-range minimum)
or array (bin edges) for constructing TEfficiency'''
if isinstance(low, np.ndarray):
eff = asrootpy(
ROOT.TEfficiency(this_name, this_title, n_bins, low))
self.x_max = 2000
else:
eff = asrootpy(
ROOT.TEfficiency(this_name, this_title, n_bins, low, high))
self.x_max = high
eff.drawstyle = EfficiencyPlot.drawstyle
return eff
self.efficiencies = HistogramCollection(
[self.pileup_bins, self.thresholds], make_efficiency)
def __fit_efficiencies(self):
def make_fit(labels):
pileup_bin = labels["pileup"]
threshold_bin = labels["threshold"]
efficiency = self.efficiencies.get_bin_contents(
[pileup_bin, threshold_bin])
params = fit_efficiency(
efficiency, self.thresholds.get_bin_center(threshold_bin))
return params
# Actually make the efficiencies
self.fits = HistogramCollection([self.pileup_bins, self.thresholds],
make_fit)
class RateVsPileupPlot(BasePlotter):
def __init__(self, online_name):
name = ["rate_vs_pileup", online_name]
super(RateVsPileupPlot, self).__init__("__".join(name))
self.online_name = online_name
def create_histograms(self,
online_title,
thresholds, n_bins, low, high, legend_title=""):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.thresholds = thresholds
self.thresholds = bn.GreaterThan(thresholds, "threshold", True)
self.legend_title = legend_title
name = ["rate_vs_pileup", self.online_name]
name += ["thresh_{threshold}"]
name = "__".join(name)
title = " ".join([self.online_name, " rate vs pileup",
"passing threshold: {threshold}"])
self.plots = HistogramCollection([self.thresholds],
"Hist1D", n_bins, low, high,
name=name, title=title)
self.filename_format = name
def fill(self, pileup, online):
self.plots[online].fill(pileup)
def draw(self, with_fits=False):
for (threshold, ), hist in self.plots.flat_items_all():
hists = []
labels = []
fits = []
thresholds = []
if not isinstance(threshold, int):
continue
label_template = '{online_title} > {threshold} GeV'
label = label_template.format(
online_title=self.online_title,
threshold=self.thresholds.bins[threshold],
)
hist.Divide(self.plots.get_bin_contents([bn.Base.everything]))
hist.drawstyle = "EP"
hist.SetMarkerColor(2)
# if with_fits:
# fit = self.fits.get_bin_contents([threshold])
# fits.append(fit)
hists.append(hist)
labels.append(label)
thresholds.append(threshold)
self.__make_overlay(hists, fits, labels, thresholds)
def overlay(self, other_plotters=None, with_fits=False, comp=False):
hists = []
labels = []
fits = []
thresholds = []
suffix = '__emu_overlay'
titles = ['Hw', 'Emu']
if comp:
suffix = '__comparison'
titles = [other_plotter.comp_title for other_plotter in other_plotters]
titles.insert(0, self.comp_title)
for (threshold, ), hist in self.plots.flat_items_all():
if not isinstance(threshold, int):
continue
label_template = '{online_title} > {threshold} GeV'
label = label_template.format(
online_title='L1 ' + titles[0],
threshold=self.thresholds.bins[threshold],
)
hist.Divide(self.plots.get_bin_contents([bn.Base.everything]))
hist.Scale(2855)
hist.drawstyle = "EP"
hist.SetMarkerColor(1)
# if with_fits:
# fit = self.fits.get_bin_contents([threshold])
# fits.append(fit)
hists.append(hist)
labels.append(label)
thresholds.append(threshold)
for other_plotter in other_plotters:
for (threshold, ), hist in other_plotter.plots.flat_items_all():
if not isinstance(threshold, int):
continue
label_template = '{online_title} > {threshold} GeV'
label = label_template.format(
online_title='L1 ' + titles[other_plotters.index(other_plotter) + 1],
threshold=other_plotter.thresholds.bins[threshold],
)
hist.Divide(other_plotter.plots.get_bin_contents([bn.Base.everything]))
hist.Scale(2855)
hist.drawstyle = "EP"
hist.SetMarkerColor(2)
hist.markerstyle = 21 + other_plotters.index(other_plotter)
# if with_fits:
# fit = self.fits.get_bin_contents([threshold])
# fits.append(fit)
hists.append(hist)
labels.append(label)
thresholds.append(threshold)
self.__make_overlay(hists, fits, labels, thresholds, suffix)
def __make_overlay(self, hists, fits, labels, thresholds, suffix=""):
with preserve_current_style():
# Draw each rate vs pileup (with fit)
xtitle = "< \\mu >"
ytitle = "Rate (kHz)"
canvas = draw(hists, draw_args={"xtitle": xtitle, "ytitle": ytitle, "xlimits": (20, 50), "ylimits": (0, 5)})
if fits:
for fit, hist in zip(fits, hists):
fit["asymmetric"].linecolor = hist.GetLineColor()
fit["asymmetric"].Draw("same")
# Add labels
label_canvas()
# Add a legend
legend = Legend(
len(hists),
header=self.legend_title,
topmargin=0.02,
leftmargin=0.22,
rightmargin=0.78,
textsize=0.025,
entryheight=0.028,
)
for hist, label in zip(hists, labels):
legend.AddEntry(hist, label)
legend.SetBorderSize(0)
legend.Draw()
# Save canvas to file
name = self.filename_format.format(threshold=thresholds[0])
self.save_canvas(canvas, name + suffix)
def _is_consistent(self, new):
"""
Check the two plotters are the consistent, so same binning and same axis names
"""
return all([self.thresholds.bins == new.thresholds.bins,
self.online_name == new.online_name,
])
def _merge(self, other):
"""
Merge another plotter into this one
"""
self.plots += other.plots
return self.plots
def get_stats(self, summary_bins=[], summary_label=''):
summary_columns = list(self._summary_columns(summary_bins, summary_label))
stats = list(self._collect_stats(summary_bins, summary_label))
df = pd.DataFrame(stats)
return df[['identifier', 'total', 'overflow'] + summary_columns]
def _summary_columns(self, summary_bins, summary_label):
for lower, upper in zip(summary_bins[:-1], summary_bins[1:]):
yield '{} {}-{}'.format(summary_label, lower, upper)
def _collect_stats(self, summary_bins, summary_label):
normalisation = self.plots.get_bin_contents([bn.Base.everything]).integral(overflow=True)
for (threshold, ), hist in self.plots.flat_items():
human_readable_threshold = '{0} > {1} GeV'.format(self.online_title, self.thresholds.bins[threshold])
rhist = hist.rebinned(summary_bins)
stats = {}
summary_columns = self._summary_columns(summary_bins, summary_label)
for summary_column, y in zip(summary_columns, rhist.y()):
stats[summary_column] = y * normalisation
total = sum(stats.values())
overflow = rhist.integral(overflow=True) * normalisation - total
header = dict(identifier=human_readable_threshold, total=total, overflow=overflow)
header.update(stats)
yield header
class EfficiencyPlot(BasePlotter):
drawstyle = 'HIST'
drawstyle_data = 'P'
markerstyle_overlay = 23
def __init__(self, online_name, offline_name):
name = ["efficiency", online_name, offline_name]
super(EfficiencyPlot, self).__init__("__".join(name))
self.online_name = online_name
self.offline_name = offline_name
def create_histograms(self,
online_title,
offline_title,
pileup_bins,
thresholds,
n_bins,
low,
high=400,
legend_title=""):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.offline_title = offline_title
self.pileup_bins = bn.Sorted(pileup_bins,
"pileup",
use_everything_bin=True)
self.thresholds = bn.GreaterThan(thresholds, "threshold")
self.legend_title = legend_title
name = ["efficiency", self.online_name, self.offline_name]
name += ["thresh_{threshold}", "pu_{pileup}"]
name = "__".join(name)
title = " ".join([
self.online_name, " in PU bin: {pileup}",
"and passing threshold: {threshold}"
])
self.filename_format = name
def make_efficiency(labels):
this_name = "efficiency" + name.format(**labels)
this_title = title.format(**labels)
'''Checking type of 'low' to see whether it's int (x-range minimum)
or array (bin edges) for constructing TEfficiency'''
if isinstance(low, np.ndarray):
eff = asrootpy(
ROOT.TEfficiency(this_name, this_title, n_bins, low))
self.x_max = 2000
else:
eff = asrootpy(
ROOT.TEfficiency(this_name, this_title, n_bins, low, high))
self.x_max = high
eff.drawstyle = EfficiencyPlot.drawstyle
return eff
self.efficiencies = HistogramCollection(
[self.pileup_bins, self.thresholds], make_efficiency)
def fill(self, pileup, offline, online):
efficiencies = {
(pu, thresh): eff
for (pu, ), thresholds in self.efficiencies[pileup].items()
for thresh, eff in thresholds.items()
}
for (pu_bin, threshold_bin), efficiency in efficiencies.items():
threshold = self.thresholds.get_bin_center(threshold_bin)
passed = False
if isinstance(threshold, str):
continue
elif online > threshold:
passed = True
efficiency.fill(passed, offline)
def draw(self, with_fits=False):
# Fit the efficiencies if requested
if with_fits:
self.__fit_efficiencies()
# Overlay the "all" pile-up bin for each threshold
all_pileup_effs = self.efficiencies.get_bin_contents(
[bn.Base.everything])
hists = []
labels = []
fits = []
label_template = '{online_title} > {threshold} GeV'
for threshold in all_pileup_effs.iter_all():
if not isinstance(threshold, int):
continue
hist = all_pileup_effs.get_bin_contents(threshold)
hist.drawstyle = EfficiencyPlot.drawstyle
hists.append(hist)
label = label_template.format(
online_title=self.online_title,
threshold=self.thresholds.bins[threshold],
)
labels.append(label)
if with_fits:
fits.append(
self.fits.get_bin_contents([bn.Base.everything,
threshold]))
self.__make_overlay(
"all",
"all",
hists,
fits,
labels,
self.online_title,
)
# Overlay individual pile-up bins for each threshold
for threshold in self.thresholds:
hists = []
labels = []
fits = []
for pileup in self.pileup_bins:
if not isinstance(pileup, int):
continue
hist = self.efficiencies.get_bin_contents([pileup, threshold])
hist.drawstyle = EfficiencyPlot.drawstyle_data
hists.append(hist)
if with_fits:
fits.append(self.fits.get_bin_contents([pileup,
threshold]))
labels.append(str(self.pileup_bins.bins[pileup]))
self.__make_overlay(pileup, threshold, hists, fits, labels,
"PU bin")
# Produce the fit summary plot
if with_fits:
self.__summarize_fits()
def overlay_with_emu(self, emu_plotter, with_fits=False):
# Fit the efficiencies if requested
if with_fits:
self.__fit_efficiencies()
# Overlay the "all" pile-up bin for each threshold
all_pileup_effs = self.efficiencies.get_bin_contents(
[bn.Base.everything])
emu_pileup_effs = emu_plotter.efficiencies.get_bin_contents(
[bn.Base.everything])
hists = []
labels = []
fits = []
ROOT.gStyle.SetErrorX(0.)
label_template = '{online_title} > {threshold} GeV'
for threshold in all_pileup_effs.iter_all():
if not isinstance(threshold, int):
continue
hist = all_pileup_effs.get_bin_contents(threshold)
hist.drawstyle = EfficiencyPlot.drawstyle_data
hists.append(hist)
label = label_template.format(
online_title=self.online_title,
threshold=self.thresholds.bins[threshold],
)
labels.append(label)
if with_fits:
fits.append(
self.fits.get_bin_contents([bn.Base.everything,
threshold]))
for threshold in emu_pileup_effs.iter_all():
if not isinstance(threshold, int):
continue
hist = emu_pileup_effs.get_bin_contents(threshold)
hist.drawstyle = EfficiencyPlot.drawstyle_data
hist.markerstyle = EfficiencyPlot.markerstyle_overlay
hists.append(hist)
label = label_template.format(
online_title=emu_plotter.online_title + ' Emu',
threshold=emu_plotter.thresholds.bins[threshold],
)
labels.append(label)
if with_fits:
fits.append(
emu_plotter.fits.get_bin_contents(
[bn.Base.everything, threshold]))
self.__make_overlay(
"all",
"all_overlay_with_Emu",
hists,
fits,
labels,
self.online_title,
)
'''
# Overlay individual pile-up bins for each threshold
for threshold in self.thresholds:
hists = []
labels = []
fits = []
for pileup in self.pileup_bins:
if not isinstance(pileup, int):
continue
hist = self.efficiencies.get_bin_contents([pileup, threshold])
hist.drawstyle = "EP"
hists.append(hist)
if with_fits:
fits.append(self.fits.get_bin_contents(
[pileup, threshold]))
labels.append(str(self.pileup_bins.bins[pileup]))
self.__make_overlay(pileup, threshold, hists,
fits, labels, "PU bin")
'''
# Produce the fit summary plot
if with_fits:
self.__summarize_fits()
def __fit_efficiencies(self):
def make_fit(labels):
pileup_bin = labels["pileup"]
threshold_bin = labels["threshold"]
efficiency = self.efficiencies.get_bin_contents(
[pileup_bin, threshold_bin])
params = fit_efficiency(
efficiency, self.thresholds.get_bin_center(threshold_bin))
return params
# Actually make the efficiencies
self.fits = HistogramCollection([self.pileup_bins, self.thresholds],
make_fit)
def __make_overlay(self, pileup, threshold, hists, fits, labels, header):
with preserve_current_style():
name = self.filename_format.format(pileup=pileup,
threshold=threshold)
# Draw each efficiency (with fit)
draw_args = {"xtitle": self.offline_title, "ytitle": "Efficiency"}
# TODO: special case should not be implemented here!
if 'Jet' in name and 'HiRange' in name:
draw_args['xlimits'] = [20, 2000]
canvas = draw(hists, draw_args=draw_args)
if len(fits) > 0:
for fit, hist in zip(fits, hists):
fit["asymmetric"].linecolor = hist.GetLineColor()
fit["asymmetric"].Draw("same")
# Add labels
label_canvas()
# Add a legend
legend = Legend(
len(hists),
header=self.legend_title,
topmargin=0.35,
rightmargin=0.3,
leftmargin=0.7,
textsize=0.025,
entryheight=0.028,
)
for hist, label in zip(hists, labels):
legend.AddEntry(hist, label)
legend.SetBorderSize(0)
legend.Draw()
xmin = 0
xmax = self.x_max
# TODO: also specialisation, needs removal
if ("HT" in name):
xmax = 800
xmin = 30
if ("MET" in name):
xmin = 0
xmax = 400
if ("Jet" in name):
xmin = 20
xmax = 400
if ("HiRange" in name):
xmax = 2000
for val in [0.25, 0.5, 0.75, 0.95, 1.]:
line = ROOT.TLine(xmin, val, xmax, val)
line.SetLineStyle("dashed")
line.SetLineColor(15)
line.Draw()
for val in range(100, xmax, 100):
line = ROOT.TLine(val, 0., val, 1.)
line.SetLineStyle("dashed")
line.SetLineColor(15)
line.Draw()
# Save canvas to file
self.save_canvas(canvas, name)
def __summarize_fits(self):
""" Implement this to show fit evolution plots """
# TODO: Implement this __summarize_fits methods
pass
def _is_consistent(self, new):
"""
Check the two plotters are the consistent, so same binning and same axis names
"""
return all([
self.pileup_bins.bins == new.pileup_bins.bins,
self.thresholds.bins == new.thresholds.bins,
self.online_name == new.online_name,
self.offline_name == new.offline_name,
])
def _merge(self, other):
"""
Merge another plotter into this one
"""
self.efficiencies += other.efficiencies
return self.efficiencies
class RatesPlot(BasePlotter):
def __init__(self, online_name):
name = ["rates", online_name]
super(RatesPlot, self).__init__("__".join(name))
self.online_name = online_name
def create_histograms(self,
online_title,
pileup_bins,
n_bins,
low,
high,
legend_title=""):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.pileup_bins = bn.Sorted(pileup_bins,
"pileup",
use_everything_bin=True)
self.legend_title = legend_title
name = ["rate_vs_threshold", self.online_name, "pu_{pileup}"]
name = "__".join(name)
title = " ".join([self.online_name, "vs.", "in PU bin: {pileup}"])
title = ";".join([title, self.online_title])
self.plots = HistogramCollection([self.pileup_bins],
"Hist1D",
n_bins,
low,
high,
name=name,
title=title)
self.filename_format = name
def fill(self, pileup, online):
self.plots[pileup].fill(online)
def draw(self, with_fits=False):
hists = []
labels = []
fits = []
for (pile_up, ), hist in self.plots.flat_items_all():
h = cumulative_hist(hist)
h = normalise_to_collision_rate(h)
if pile_up == bn.Base.everything:
h.linestyle = "dashed"
label = "Everything"
elif isinstance(pile_up, int):
h.drawstyle = "EP"
label = "~ {:.0f}".format(
self.pileup_bins.get_bin_center(pile_up))
else:
continue
h.SetMarkerSize(0.5)
hists.append(h)
labels.append(label)
# if with_fits:
# fits.append(self.fits.get_bin_contents([pile_up]))
self.__make_overlay(hists, fits, labels, "Number of events")
normed_hists = list(normalise_to_unit_area(hists))
self.__make_overlay(normed_hists, fits, labels, "Fraction of events",
"__shapes")
def overlay_with_emu(self, emu_plotter, with_fits=False):
hists = []
labels = []
fits = []
hist = self.plots.get_bin_contents([bn.Base.everything])
hist = cumulative_hist(hist)
hist.drawstyle = "EP"
hist.SetMarkerSize(0.5)
hist.SetMarkerColor(1)
# if with_fits:
# fit = self.fits.get_bin_contents([threshold])
# fits.append(fit)
hists.append(hist)
labels.append("HW")
emu_hist = emu_plotter.plots.get_bin_contents([bn.Base.everything])
emu_hist = cumulative_hist(emu_hist)
emu_hist.drawstyle = "EP"
emu_hist.SetMarkerSize(0.5)
emu_hist.SetMarkerColor(2)
# if with_fits:
# emu_fit = self.fits.get_bin_contents([threshold])
# fits.append(emu_fit)
hists.append(emu_hist)
labels.append("Emu")
self.__make_overlay(hists, fits, labels, "# Events", setlogy=True)
def __make_overlay(self,
hists,
fits,
labels,
ytitle,
suffix="",
setlogy=False):
with preserve_current_style():
# Draw each resolution (with fit)
xtitle = self.online_title
canvas = draw(hists,
draw_args={
"xtitle": xtitle,
"ytitle": ytitle,
"logy": setlogy
})
if fits:
for fit, hist in zip(fits, hists):
fit["asymmetric"].linecolor = hist.GetLineColor()
fit["asymmetric"].Draw("same")
# Add labels
label_canvas()
# Add a legend
legend = Legend(len(hists),
header=self.legend_title,
topmargin=0.35,
rightmargin=0.2,
leftmargin=0.8,
entryheight=0.028)
for hist, label in zip(hists, labels):
legend.AddEntry(hist, label)
legend.SetBorderSize(0)
legend.Draw()
# Save canvas to file
name = self.filename_format.format(pileup="all")
self.save_canvas(canvas, name + suffix)
def _is_consistent(self, new):
"""
Check the two plotters are the consistent, so same binning and same axis names
"""
return all([
self.pileup_bins.bins == new.pileup_bins.bins,
self.online_name == new.online_name,
])
def _merge(self, other):
"""
Merge another plotter into this one
"""
self.plots += other.plots
return self.plots
class EfficiencyPlot(BasePlotter):
drawstyle = 'HISTC'
drawstyle_data = 'PC'
def __init__(self, online_name, offline_name):
name = ["efficiency", online_name, offline_name]
super(EfficiencyPlot, self).__init__("__".join(name))
self.online_name = online_name
self.offline_name = offline_name
def create_histograms(self,
online_title,
offline_title,
pileup_bins,
thresholds,
n_bins,
low,
high=400,
legend_title=""):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.offline_title = offline_title
self.pileup_bins = bn.Sorted(pileup_bins,
"pileup",
use_everything_bin=True)
self.thresholds = bn.GreaterThan(thresholds, "threshold")
self.legend_title = legend_title
name = ["efficiency", self.online_name, self.offline_name]
name += ["thresh_{threshold}", "pu_{pileup}"]
name = "__".join(name)
title = " ".join([
self.online_name, " in PU bin: {pileup}",
"and passing threshold: {threshold}"
])
self.filename_format = name
def make_efficiency(labels):
this_name = "efficiency" + name.format(**labels)
this_title = title.format(**labels)
'''Checking type of 'low' to see whether it's int (x-range minimum)
or array (bin edges) for constructing TEfficiency'''
if isinstance(low, np.ndarray):
eff = asrootpy(
ROOT.TEfficiency(this_name, this_title, n_bins, low))
else:
eff = asrootpy(
ROOT.TEfficiency(this_name, this_title, n_bins, low, high))
eff.drawstyle = EfficiencyPlot.drawstyle
return eff
self.efficiencies = HistogramCollection(
[self.pileup_bins, self.thresholds], make_efficiency)
def fill(self, pileup, offline, online):
efficiencies = {
(pu, thresh): eff
for (pu, ), thresholds in self.efficiencies[pileup].items()
for thresh, eff in thresholds.items()
}
for (pu_bin, threshold_bin), efficiency in efficiencies.items():
threshold = self.thresholds.get_bin_center(threshold_bin)
passed = False
if isinstance(threshold, str):
continue
elif online > threshold:
passed = True
efficiency.fill(passed, offline)
def draw(self, with_fits=False):
# Fit the efficiencies if requested
if with_fits:
self.__fit_efficiencies()
# Overlay the "all" pile-up bin for each threshold
all_pileup_effs = self.efficiencies.get_bin_contents(
[bn.Base.everything])
hists = []
labels = []
fits = []
label_template = '{online_title} > {threshold} GeV'
for threshold in all_pileup_effs.iter_all():
if not isinstance(threshold, int):
continue
hist = all_pileup_effs.get_bin_contents(threshold)
hist.drawstyle = EfficiencyPlot.drawstyle_data
self._dynamic_bin(hist)
hists.append(hist)
label = label_template.format(
online_title=self.online_title,
threshold=self.thresholds.bins[threshold],
)
labels.append(label)
if with_fits:
fits.append(
self.fits.get_bin_contents([bn.Base.everything,
threshold]))
self.__make_overlay(
"all",
"all",
hists,
fits,
labels,
self.online_title,
)
if 'HiRange' not in self.filename_format:
# Overlay individual pile-up bins for each threshold
for threshold in self.thresholds:
hists = []
labels = []
fits = []
for pileup in self.pileup_bins:
if not isinstance(pileup, int):
continue
hist = self.efficiencies.get_bin_contents(
[pileup, threshold])
hist.drawstyle = EfficiencyPlot.drawstyle_data
self._dynamic_bin(hist)
hists.append(hist)
if with_fits:
fits.append(
self.fits.get_bin_contents([pileup, threshold]))
labels.append(str(self.pileup_bins.bins[pileup]))
self.__make_overlay(pileup, threshold, hists, fits, labels,
"PU bin")
# Produce the fit summary plot
if with_fits:
self.__summarize_fits()
def overlay(self, other_plotters=None, with_fits=False):
suffix = '__emu_overlay'
titles = ['Hw', 'Emu']
if self.comp_title:
suffix = '__comparison'
titles = [
other_plotter.comp_title for other_plotter in other_plotters
]
titles.insert(0, self.comp_title)
# Fit the efficiencies if requested
if with_fits:
self.__fit_efficiencies()
# Overlay the "all" pile-up bin for each threshold
all_pileup_effs = self.efficiencies.get_bin_contents(
[bn.Base.everything])
hists = []
labels = []
fits = []
label_template = '{online_title} > {threshold} GeV'
for threshold in all_pileup_effs.iter_all():
if not isinstance(threshold, int):
continue
hist = all_pileup_effs.get_bin_contents(threshold)
hist.drawstyle = EfficiencyPlot.drawstyle_data
self._dynamic_bin(hist)
hists.append(hist)
label = label_template.format(
online_title='L1 ' + titles[0],
threshold=self.thresholds.bins[threshold],
)
labels.append(label)
if with_fits:
fits.append(
self.fits.get_bin_contents([bn.Base.everything,
threshold]))
for other_plotter in other_plotters:
pileup_effs = other_plotter.efficiencies.get_bin_contents(
[bn.Base.everything])
for threshold in pileup_effs.iter_all():
if not isinstance(threshold, int):
continue
hist = pileup_effs.get_bin_contents(threshold)
hist.drawstyle = EfficiencyPlot.drawstyle_data
self._dynamic_bin(hist)
hists.append(hist)
label = label_template.format(
online_title='L1 ' +
titles[other_plotters.index(other_plotter) + 1],
threshold=other_plotter.thresholds.bins[threshold],
)
labels.append(label)
if with_fits:
fits.append(
other_plotter.fits.get_bin_contents(
[bn.Base.everything, threshold]))
self.__make_overlay(
"all",
suffix,
hists,
fits,
labels,
self.online_title,
)
'''
# Overlay individual pile-up bins for each threshold
for threshold in self.thresholds:
hists = []
labels = []
fits = []
for pileup in self.pileup_bins:
if not isinstance(pileup, int):
continue
hist = self.efficiencies.get_bin_contents([pileup, threshold])
hist.drawstyle = "EP"
hists.append(hist)
if with_fits:
fits.append(self.fits.get_bin_contents(
[pileup, threshold]))
labels.append(str(self.pileup_bins.bins[pileup]))
self.__make_overlay(pileup, threshold, hists,
fits, labels, "PU bin")
'''
# Produce the fit summary plot
if with_fits:
self.__summarize_fits()
def __fit_efficiencies(self):
def make_fit(labels):
pileup_bin = labels["pileup"]
threshold_bin = labels["threshold"]
efficiency = self.efficiencies.get_bin_contents(
[pileup_bin, threshold_bin])
params = fit_efficiency(
efficiency, self.thresholds.get_bin_center(threshold_bin))
return params
# Actually make the efficiencies
self.fits = HistogramCollection([self.pileup_bins, self.thresholds],
make_fit)
def __make_overlay(self, pileup, threshold, hists, fits, labels, header):
with preserve_current_style():
name = self.filename_format.format(pileup=pileup,
threshold=threshold)
xmin = int(hists[0].GetTotalHistogram().GetBinLowEdge(1))
xmax = int(hists[0].GetTotalHistogram().GetBinLowEdge(
hists[0].GetTotalHistogram().GetNbinsX() + 1))
xtitle = ""
if 'Jet' in self.online_title:
xtitle = "Jet #it{p}_{T} (GeV)"
if 'HT' in self.online_title:
xtitle = "#it{H}_{T} (GeV)"
if 'MET' in self.online_title:
xtitle = "#it{E}_{T}^{miss} (GeV)"
# Draw each efficiency (with fit)
draw_args = {
"xtitle": xtitle,
"ytitle": "Efficiency",
"xlimits": [xmin, xmax]
}
canvas = draw(hists, draw_args=draw_args)
if len(fits) > 0:
for fit, hist in zip(fits, hists):
fit["asymmetric"].linecolor = hist.GetLineColor()
fit["asymmetric"].Draw("same")
# Add labels
label_canvas()
# Add a legend
legend = Legend(
len(hists),
header=self.legend_title,
topmargin=0.25,
rightmargin=0.25,
leftmargin=0.69,
textsize=0.025,
entryheight=0.028,
)
for hist, label in zip(hists, labels):
legend.AddEntry(hist, label)
legend.SetBorderSize(0)
legend.Draw()
for val in [0.25, 0.5, 0.75, 0.95, 1.]:
line = ROOT.TLine(xmin, val, xmax, val)
line.SetLineStyle("dashed")
line.SetLineColor(15)
line.Draw()
for t in xrange(xmin, xmax, 20):
line = ROOT.TLine(t, 0., t, 1.)
line.SetLineStyle("dashed")
line.SetLineColor(15)
line.Draw()
# Save canvas to file
self.save_canvas(canvas, name)
def __summarize_fits(self):
""" Implement this to show fit evolution plots """
# TODO: Implement this __summarize_fits methods
pass
def _is_consistent(self, new):
"""
Check the two plotters are the consistent, so same binning and same axis names
"""
return all([
self.pileup_bins.bins == new.pileup_bins.bins,
self.thresholds.bins == new.thresholds.bins,
self.online_name == new.online_name,
self.offline_name == new.offline_name,
])
def _merge(self, other):
"""
Merge another plotter into this one
"""
self.efficiencies += other.efficiencies
return self.efficiencies
def _dynamic_bin(self, eff):
"""
Re-build efficiency plots so that there are no bins with < min_ entries
"""
min_ = 16
total = []
passed = []
bins = []
bins.append(eff.GetTotalHistogram().GetBinLowEdge(1))
nbins = eff.GetTotalHistogram().GetNbinsX()
merge_total = 0
merge_passed = 0
for bin in range(1, nbins + 1):
next_bin_total = eff.GetTotalHistogram().GetBinContent(bin + 1)
merge_total += eff.GetTotalHistogram().GetBinContent(bin)
merge_passed += eff.GetPassedHistogram().GetBinContent(bin)
if bin == nbins:
merge_total += eff.GetTotalHistogram().GetBinContent(bin + 1)
merge_passed += eff.GetPassedHistogram().GetBinContent(bin + 1)
if (next_bin_total > min_ and merge_total > min_) or bin == nbins:
bins.append(eff.GetTotalHistogram().GetBinLowEdge(bin + 1))
total.append(merge_total)
passed.append(merge_passed)
merge_total = 0
merge_passed = 0
npbins = np.asarray(bins)
hist_total = asrootpy(
ROOT.TH1I("total", "total",
len(bins) - 1, npbins))
hist_passed = asrootpy(
ROOT.TH1I("passed", "passed",
len(bins) - 1, npbins))
for bin in range(1, len(bins)):
hist_total.SetBinContent(bin, total[bin - 1])
hist_passed.SetBinContent(bin, passed[bin - 1])
hist_total.Sumw2(False)
hist_passed.Sumw2(False)
eff.SetTotalHistogram(hist_total, "f")
eff.SetPassedHistogram(hist_passed, "f")
class ResolutionPlot(BasePlotter):
drawstyle = 'P'
def __init__(self, resolution_type, online_name, offline_name):
name = ["resolution", online_name, offline_name]
super(ResolutionPlot, self).__init__("__".join(name))
self.online_name = online_name
self.offline_name = offline_name
self.resolution_method = get_resolution_function(resolution_type)
def create_histograms(self,
online_title, offline_title,
pileup_bins, n_bins, low, high, legend_title=''):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.offline_title = offline_title
self.legend_title = legend_title
self.pileup_bins = bn.Sorted(pileup_bins, "pileup",
use_everything_bin=True)
name = ["resolution", self.online_name,
self.offline_name, "pu_{pileup}"]
name = "__".join(name)
title = " ".join(
[self.online_name, "vs.", self.offline_name, "in PU bin: {pileup}"])
title = ";".join([title, self.offline_title, self.online_title])
self.plots = HistogramCollection([self.pileup_bins],
"Hist1D", n_bins, low, high,
name=name, title=title)
self.filename_format = name
def fill(self, pileup, offline, online):
difference = self.resolution_method(online, offline)
self.plots[pileup].fill(difference)
def draw(self, with_fits=False):
hists = []
labels = []
fits = []
for (pile_up, ), hist in self.plots.flat_items_all():
if pile_up == bn.Base.everything:
# hist.linestyle = "dashed"
hist.drawstyle = ResolutionPlot.drawstyle
label = "All PU"
elif isinstance(pile_up, int):
hist.drawstyle = ResolutionPlot.drawstyle
if self.pileup_bins.get_bin_upper(pile_up) < 500:
label = "{:.0f} \\leq PU < {:.0f}".format(
self.pileup_bins.get_bin_lower(pile_up),
self.pileup_bins.get_bin_upper(pile_up),
)
else:
label = "{:.0f} < PU".format(
self.pileup_bins.get_bin_lower(pile_up))
else:
continue
hist.SetMarkerSize(0.5)
hist.SetLineWidth(1)
hists.append(hist)
labels.append(label)
# if with_fits:
# fits.append(self.fits.get_bin_contents([pile_up]))
# self.__make_overlay(hists, fits, labels, "Number of events")
normed_hists = list(normalise_to_unit_area(hists))
for hist in normed_hists:
hist.GetYaxis().SetRangeUser(-0.1, 1.1)
self.__make_overlay(normed_hists, fits, labels, "a.u.")
def overlay_with_emu(self, emu_plotter, with_fits=False):
hists = []
labels = []
fits = []
for (pile_up, ), hist in self.plots.flat_items_all():
if pile_up == bn.Base.everything:
hist.SetLineStyle(1)
hist.drawstyle = ResolutionPlot.drawstyle
label = "HW, all PU"
else:
continue
hist.SetMarkerSize(0.5)
hist.SetLineWidth(1)
hists.append(hist)
labels.append(label)
for (pile_up, ), hist in emu_plotter.plots.flat_items_all():
if pile_up == bn.Base.everything:
hist.SetLineStyle(1)
hist.drawstyle = ResolutionPlot.drawstyle
label = "Emu, all PU"
else:
continue
hist.SetMarkerSize(0.5)
hist.SetLineWidth(1)
hists.append(hist)
labels.append(label)
# self.__make_overlay(hists, fits, labels,
# "Number of events", "__Overlay_Emu")
normed_hists = list(normalise_to_unit_area(hists))
for hist in normed_hists:
hist.GetYaxis().SetRangeUser(-0.1, 1.1)
self.__make_overlay(normed_hists, fits, labels,
"a.u.", "__Overlay_Emu")
def __make_overlay(self, hists, fits, labels, ytitle, suffix=""):
with preserve_current_style():
# Draw each resolution (with fit)
# TODO: this feels like it does not belong here
for hist in hists:
hist.GetYaxis().SetRangeUser(0, 0.1)
hist.GetYaxis().SetTitleOffset(1.4)
xtitle = self.resolution_method.label.format(
on=self.online_title, off=self.offline_title)
canvas = draw(hists, draw_args={
"xtitle": xtitle, "ytitle": ytitle})
if fits:
for fit, hist in zip(fits, hists):
fit["asymmetric"].linecolor = hist.GetLineColor()
fit["asymmetric"].Draw("same")
# Add labels
label_canvas()
# Add a legend
legend = Legend(
len(hists),
header=self.legend_title,
topmargin=0.35,
rightmargin=0.3,
leftmargin=0.7,
textsize=0.03,
entryheight=0.03,
)
for hist, label in zip(hists, labels):
legend.AddEntry(hist, label)
legend.SetBorderSize(0)
legend.Draw()
ymax = 1.2 * max([hist.GetMaximum() for hist in hists])
line = ROOT.TLine(0., 0., 0., ymax)
line.SetLineColor(15)
# Save canvas to file
name = self.filename_format.format(pileup="all")
self.save_canvas(canvas, name + suffix)
def _is_consistent(self, new):
"""
Check the two plotters are the consistent, so same binning and same axis names
"""
return all([self.pileup_bins.bins == new.pileup_bins.bins,
self.resolution_method == new.resolution_method,
self.online_name == new.online_name,
self.offline_name == new.offline_name,
])
def _merge(self, other):
"""
Merge another plotter into this one
"""
self.plots += other.plots
return self.plots
class OnlineVsOffline(BasePlotter):
def __init__(self, online_name, offline_name):
name = ["online_vs_offline", online_name, offline_name]
super(OnlineVsOffline, self).__init__("__".join(name))
self.online_name = online_name
self.offline_name = offline_name
def create_histograms(
self,
online_title,
offline_title,
pileup_bins,
n_bins,
low,
high=400.,
):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.offline_title = offline_title
self.pileup_bins = bn.Sorted(
pileup_bins,
"pileup",
use_everything_bin=True,
)
nameTokens = [
"onlineVsOffline",
self.online_name,
self.offline_name,
"pu_{pileup}",
]
name = "__".join(nameTokens)
title = " ".join([
self.online_name,
"vs.",
self.offline_name,
"in PU bin: {pileup}",
])
title = ";".join([title, self.offline_title, self.online_title])
if isinstance(low, np.ndarray):
self.plots = HistogramCollection(
[self.pileup_bins],
"Hist2D",
low,
low,
name=name,
title=title,
)
else:
self.plots = HistogramCollection(
[self.pileup_bins],
"Hist2D",
n_bins,
low,
high,
n_bins,
low,
high,
name=name,
title=title,
)
self.filename_format = name
def fill(self, pileup, offline, online):
self.plots[pileup].fill(offline, online)
def draw(self, with_fits=True):
for pileup in self.pileup_bins.iter_all():
plot = self.plots.get_bin_contents([pileup])
self.__do_draw(self.pileup_bins.get_bin_center(pileup), plot)
def __do_draw(self, pileup, hist):
with preserve_current_style():
# Draw each efficiency (with fit)
canvas = draw2D(hist,
draw_args={
"xtitle": self.offline_title,
"ytitle": self.online_title
})
canvas.SetLogz(True)
# Add labels
label_canvas()
# Save canvas to file
name = self.filename_format.format(pileup=pileup)
self.save_canvas(canvas, name)
def _is_consistent(self, new):
"""
Check the two plotters are the consistent, so same binning and same axis names
"""
return all([
self.pileup_bins.bins == new.pileup_bins.bins,
self.online_name == new.online_name,
self.offline_name == new.offline_name,
])
def _merge(self, other):
"""
Merge another plotter into this one
"""
self.plots += other.plots
return self.plots
class ResolutionVsXPlot(BasePlotter):
def __init__(self, resolution_type, online_name, offline_name, versus_name):
name = ["resolution_vs_" + versus_name, online_name, offline_name]
super(ResolutionVsXPlot, self).__init__("__".join(name))
self.online_name = online_name
self.offline_name = offline_name
self.versus_name = versus_name
self.resolution_method = get_resolution_function(resolution_type)
def create_histograms(
self, online_title, offline_title, versus_title, pileup_bins,
res_n_bins, res_low, res_high, vs_n_bins, vs_low, vs_high):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.offline_title = offline_title
self.versus_title = versus_title
self.ymin = res_low
self.ymax = res_high
self.pileup_bins = bn.Sorted(pileup_bins, "pileup",
use_everything_bin=True)
nameTokens = [
"resolution_vs", self.versus_name,
self.online_name, self.offline_name, "pu_{pileup}",
]
name = "__".join(nameTokens)
title = 'Resolution ({online_name} vs. {offline_name}) '
title += 'against {versus_name}'
title = title.format(
online_name=self.online_name,
offline_name=self.offline_name,
versus_name=self.versus_name,
)
title += " in PU bin: {pileup}"
title = ";".join([title, self.offline_title, self.online_title])
self.plots = HistogramCollection(
[self.pileup_bins],
"Hist2D", vs_n_bins, vs_low, vs_high,
res_n_bins, res_low, res_high,
name=name, title=title)
self.filename_format = name
def fill(self, pileup, versus, offline, online):
difference = self.resolution_method(online, offline)
self.plots[pileup].fill(versus, difference)
def draw(self, with_fits=True):
for (pileup, ), hist in self.plots.flat_items_all():
self.__do_draw(pileup, hist)
profileX = hist.ProfileX()
projectionX = deepcopy(hist.ProjectionX())
for i in range(hist.GetNbinsX()):
pX_i = profileX.GetBinContent(i)
if pX_i == 0:
projectionX.SetBinContent(i, 0.)
continue
pX_i_err = profileX.GetBinError(i)
projX_i = projectionX.GetBinContent(i)
newValue = sqrt(projX_i) * pX_i_err / pX_i
newError = projX_i * pX_i_err
projectionX.SetBinContent(i, newValue)
projectionX.SetBinError(i, 0.)
profileX.SetBinError(i, newError)
if projectionX.GetMaximum() > 3.:
projectionX.GetYaxis().SetRangeUser(0., 2.)
self.__do_draw(pileup, profileX, "_profile2")
self.__do_draw(pileup, projectionX, "_profile")
def __do_draw(self, pileup, hist, suffix=""):
with preserve_current_style():
# Draw each efficiency (with fit)
if suffix == "":
ytitle = "Online Jet Energy / Offline Jet Energy"
elif suffix == "_profile":
ytitle = "RMS/Mean (Online Jet Energy/Offline Jet Energy)"
else:
ytitle = self.resolution_method.label.format(
on=self.online_title,
off=self.offline_title,
)
canvas = draw2D(
hist,
draw_args={"xtitle": self.versus_title, "ytitle": ytitle},
)
# Add labels
label_canvas()
# Save canvas to file
name = self.filename_format.format(pileup=pileup)
self.save_canvas(canvas, name + suffix)
def _is_consistent(self, new):
"""
Check the two plotters are the consistent,
so same binning and same axis names
"""
return all([
self.pileup_bins.bins == new.pileup_bins.bins,
self.resolution_method == new.resolution_method,
self.versus_name == new.versus_name,
self.online_name == new.online_name,
self.offline_name == new.offline_name,
])
def _merge(self, other):
"""
Merge another plotter into this one
"""
self.plots += other.plots
return self.plots
class RatesPlot(BasePlotter):
def __init__(self, online_name):
name = ["rates", online_name]
super(RatesPlot, self).__init__("__".join(name))
self.online_name = online_name
def create_histograms(self,
online_title,
pileup_bins,
n_bins,
low,
high,
legend_title=""):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.pileup_bins = bn.Sorted(pileup_bins,
"pileup",
use_everything_bin=True)
self.legend_title = legend_title
name = ["rate_vs_threshold", self.online_name, "pu_{pileup}"]
name = "__".join(name)
title = " ".join([self.online_name, "vs.", "in PU bin: {pileup}"])
title = ";".join([title, self.online_title])
self.plots = HistogramCollection([self.pileup_bins],
"Hist1D",
n_bins,
low,
high,
name=name,
title=title)
self.filename_format = name
def fill(self, pileup, online):
self.plots[pileup].fill(online)
def draw(self, with_fits=False):
hists = []
labels = []
fits = []
for (pile_up, ), hist in self.plots.flat_items_all():
h = cumulative_hist(hist)
h = normalise_to_collision_rate(h)
if pile_up == bn.Base.everything:
h.linestyle = "dashed"
label = "L1 Rate"
# elif isinstance(pile_up, int):
# h.drawstyle = "HIST"
# label = str(self.pileup_bins.bins[pile_up])
else:
continue
hists.append(h)
labels.append(label)
# if with_fits:
# fits.append(self.fits.get_bin_contents([pile_up]))
self.__make_overlay(hists, fits, labels, "Rate (kHz)", setlogy=True)
normed_hists = list(normalise_to_unit_area(hists))
self.__make_overlay(normed_hists, fits, labels, "Fraction of events",
"__shapes")
def overlay(self, other_plotters=None, with_fits=False, comp=False):
hists = []
labels = []
fits = []
suffix = '__emu_overlay'
titles = ['Hw', 'Emu']
if comp:
suffix = '__comparison'
titles = [
other_plotter.comp_title for other_plotter in other_plotters
]
titles.insert(0, self.comp_title)
hist = self.plots.get_bin_contents([bn.Base.everything])
hist = cumulative_hist(hist)
hist = normalise_to_collision_rate(hist)
hist.drawstyle = "HIST"
hist.SetLineWidth(3)
hist.SetMarkerColor(1)
# if with_fits:
# fit = self.fits.get_bin_contents([threshold])
# fits.append(fit)
hists.append(hist)
labels.append('L1 ' + titles[0])
for other_plotter in other_plotters:
hist = other_plotter.plots.get_bin_contents([bn.Base.everything])
hist = cumulative_hist(hist)
hist = normalise_to_collision_rate(hist)
hist.drawstyle = "HIST"
hist.SetLineWidth(3)
hist.SetMarkerColor(2)
hist.markerstyle = 21 + other_plotters.index(other_plotter)
# if with_fits:
# fit = self.fits.get_bin_contents([threshold])
# fits.append(fit)
hists.append(hist)
labels.append('L1 ' +
titles[other_plotters.index(other_plotter) + 1])
self.__make_overlay(hists,
fits,
labels,
"Rate (kHz)",
suffix,
setlogy=True)
def __make_overlay(self,
hists,
fits,
labels,
ytitle,
suffix="",
setlogy=False):
with preserve_current_style():
# Draw each resolution (with fit)
xtitle = ""
if 'Jet' in self.online_title:
xtitle = "Jet #it{p}_{T} (GeV)"
if 'HT' in self.online_title:
xtitle = "#it{H}_{T} (GeV)"
if 'MET' in self.online_title:
xtitle = "#it{E}_{T}^{miss} (GeV)"
canvas = draw(hists,
draw_args={
"xtitle": xtitle,
"ytitle": ytitle,
"logy": setlogy,
"ylimits": (0.1, 50000)
})
if fits:
for fit, hist in zip(fits, hists):
fit["asymmetric"].linecolor = hist.GetLineColor()
fit["asymmetric"].Draw("same")
# Add labels
label_canvas()
# Add a legend
legend = Legend(len(hists),
header=self.legend_title,
topmargin=0.35,
rightmargin=0.2,
leftmargin=0.8,
entryheight=0.028,
textsize=0.03)
for hist, label in zip(hists, labels):
legend.AddEntry(hist, label)
legend.SetBorderSize(0)
legend.Draw()
# Save canvas to file
name = self.filename_format.format(pileup="all")
self.save_canvas(canvas, name + suffix)
def _is_consistent(self, new):
"""
Check the two plotters are the consistent, so same binning and same axis names
"""
return all([
self.pileup_bins.bins == new.pileup_bins.bins,
self.online_name == new.online_name,
])
def _merge(self, other):
"""
Merge another plotter into this one
"""
self.plots += other.plots
return self.plots
def get_stats(self, summary_bins=[], summary_label=''):
summary_columns = list(
self._summary_columns(summary_bins, summary_label))
stats = list(self._collect_stats(summary_bins, summary_label))
df = pd.DataFrame(stats)
return df[['identifier', 'total', 'overflow'] + summary_columns]
def _summary_columns(self, summary_bins, summary_label):
for lower, upper in zip(summary_bins[:-1], summary_bins[1:]):
yield '{} {}-{}'.format(summary_label, lower, upper)
def _collect_stats(self, summary_bins, summary_label):
for (pileup, ), hist in self.plots.flat_items():
human_readable_threshold = '{0}; PU > {1}'.format(
self.online_title, self.pileup_bins.bins[pileup])
rhist = hist.rebinned(summary_bins)
stats = {}
summary_columns = self._summary_columns(summary_bins,
summary_label)
for summary_column, y in zip(summary_columns, rhist.y()):
stats[summary_column] = y
total = sum(stats.values())
overflow = rhist.integral(overflow=True) - total
header = dict(identifier=human_readable_threshold,
total=total,
overflow=overflow)
header.update(stats)
yield header
class RateVsPileupPlot(BasePlotter):
def __init__(self, online_name):
name = ["rate_vs_pileup", online_name]
super(RateVsPileupPlot, self).__init__("__".join(name))
self.online_name = online_name
def create_histograms(self,
online_title,
thresholds, n_bins, low, high, legend_title=""):
""" This is not in an init function so that we can by-pass this in the
case where we reload things from disk """
self.online_title = online_title
self.thresholds = thresholds
self.thresholds = bn.GreaterThan(thresholds, "threshold", True)
self.legend_title = legend_title
name = ["rate_vs_pileup", self.online_name]
name += ["thresh_{threshold}"]
name = "__".join(name)
title = " ".join([self.online_name, " rate vs pileup",
"passing threshold: {threshold}"])
self.plots = HistogramCollection([self.thresholds],
"Hist1D", n_bins, low, high,
name=name, title=title)
self.filename_format = name
def fill(self, pileup, online):
self.plots[online].fill(pileup)
def draw(self, with_fits=False):
for (threshold, ), hist in self.plots.flat_items_all():
hists = []
labels = []
fits = []
thresholds = []
if not isinstance(threshold, int):
continue
label_template = '{online_title} > {threshold} GeV'
label = label_template.format(
online_title=self.online_title,
threshold=self.thresholds.bins[threshold],
)
hist.Divide(self.plots.get_bin_contents([bn.Base.everything]))
hist.drawstyle = "EP"
hist.SetMarkerSize(0.5)
hist.SetMarkerColor(2)
# if with_fits:
# fit = self.fits.get_bin_contents([threshold])
# fits.append(fit)
hists.append(hist)
labels.append(label)
thresholds.append(threshold)
self.__make_overlay(hists, fits, labels, thresholds)
def overlay_with_emu(self, emu_plotter, with_fits=False):
for (threshold, ), hist in self.plots.flat_items_all():
hists = []
labels = []
fits = []
thresholds = []
if not isinstance(threshold, int):
continue
label_template = '{online_title} > {threshold} GeV'
label = label_template.format(
online_title=self.online_title,
threshold=self.thresholds.bins[threshold],
)
hist.Divide(self.plots.get_bin_contents([bn.Base.everything]))
hist.drawstyle = "EP"
hist.SetMarkerSize(0.5)
hist.SetMarkerColor(1)
# if with_fits:
# fit = self.fits.get_bin_contents([threshold])
# fits.append(fit)
hists.append(hist)
labels.append(label)
thresholds.append(threshold)
for (emu_threshold, ), emu_hist in emu_plotter.plots.flat_items_all():
if emu_threshold == threshold:
label_template = '{online_title} > {threshold} GeV'
emu_label = label_template.format(
online_title=emu_plotter.online_title,
threshold=emu_plotter.thresholds.bins[threshold],
)
emu_hist.Divide(emu_plotter.plots.get_bin_contents([bn.Base.everything]))
emu_hist.drawstyle = "EP"
emu_hist.SetMarkerSize(0.5)
emu_hist.SetMarkerColor(2)
# if with_fits:
# emu_fit = self.fits.get_bin_contents([threshold])
# fits.append(emu_fit)
hists.append(emu_hist)
labels.append(emu_label)
thresholds.append(emu_threshold)
self.__make_overlay(hists, fits, labels, thresholds)
def __make_overlay(self, hists, fits, labels, thresholds, suffix=""):
with preserve_current_style():
# Draw each rate vs pileup (with fit)
xtitle = "# reco vertices"
ytitle = "a.u."
canvas = draw(hists, draw_args={"xtitle": xtitle, "ytitle": ytitle})
if fits:
for fit, hist in zip(fits, hists):
fit["asymmetric"].linecolor = hist.GetLineColor()
fit["asymmetric"].Draw("same")
# Add labels
label_canvas()
# Add a legend
legend = Legend(
len(hists),
header=self.legend_title,
topmargin=0.35,
rightmargin=0.7,
leftmargin=0.3,
textsize=0.025,
entryheight=0.028,
)
for hist, label in zip(hists, labels):
legend.AddEntry(hist, label)
legend.SetBorderSize(0)
legend.Draw()
# Save canvas to file
name = self.filename_format.format(threshold=thresholds[0])
self.save_canvas(canvas, name + suffix)
def _is_consistent(self, new):
"""
Check the two plotters are the consistent, so same binning and same axis names
"""
return all([self.thresholds.bins == new.thresholds.bins,
self.online_name == new.online_name,
])
def _merge(self, other):
"""
Merge another plotter into this one
"""
self.plots += other.plots
return self.plots