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@@ -3,37 +3,8 @@ import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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from filval.result_set import ResultSet
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from filval.result_set import ResultSet
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-from filval.histogram_utils import hist, hist_add
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-from filval.plotter import (decl_plot, render_plots, hist_plot, hist_plot_stack, Plot)
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-
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-
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-def generate_dashboard(plots, output='dashboard.htm'):
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- from jinja2 import Environment, PackageLoader, select_autoescape
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- from os.path import join
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- from urllib.parse import quote
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-
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- env = Environment(
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- loader=PackageLoader('plots', 'templates'),
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- autoescape=select_autoescape(['htm', 'html', 'xml']),
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- )
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- env.globals.update({'quote': quote,
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- 'enumerate': enumerate,
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- 'zip': zip,
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- })
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-
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- def render_to_file(template_name, **kwargs):
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- with open(join('output', output), 'w') as tempout:
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- template = env.get_template(template_name)
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- tempout.write(template.render(**kwargs))
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-
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- def get_by_n(objs, n=2):
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- objs = list(objs)
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- while objs:
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- yield objs[:n]
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- objs = objs[n:]
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-
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- render_to_file('dashboard.htm', plots=get_by_n(plots, 3),
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- outdir="figures/")
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+from filval.histogram_utils import hist, hist_add, hist_normalize
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+from filval.plotter import (decl_plot, render_plots, hist_plot, hist_plot_stack, Plot, generate_dashboard)
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@decl_plot
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@decl_plot
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@@ -46,18 +17,36 @@ def plot_yield_grid(rss):
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"""
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"""
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_, ((ax_tttt, ax_ttw), (ax_ttz, ax_tth)) = plt.subplots(2, 2)
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_, ((ax_tttt, ax_ttw), (ax_ttz, ax_tth)) = plt.subplots(2, 2)
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ft, ttw, ttz, tth = map(lambda rs: hist(rs.SRs), rss)
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ft, ttw, ttz, tth = map(lambda rs: hist(rs.SRs), rss)
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+ # ft, ttw = map(lambda rs: hist(rs.SRs), rss[:2])
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plt.sca(ax_tttt)
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plt.sca(ax_tttt)
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- hist_plot(ft, title='TTTT', stats=False)
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+ an = ((0.47, 0.33, 0.18, 0.78, 0.49, 0.52, 0.33, 0.49),
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+ (0, 0, 0, 0, 0, 0, 0, 0), [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5])
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+ hist_plot(ft, title='TTTT', stats=False, label='Mock')
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+ hist_plot(an, title='TTTT', stats=False, label='AN')
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+
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plt.sca(ax_ttw)
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plt.sca(ax_ttw)
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- hist_plot(ttw, title='TTW', stats=False)
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+ an = ([2.29663, 0.508494, 0.161166, 1.03811, 0.256401, 0.127582, 0.181522, 0.141659],
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+ [0, 0, 0, 0, 0, 0, 0, 0], [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5])
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+ hist_plot(ttw, title='TTW', stats=False, label='Mock')
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+ hist_plot(an, title='TTW', stats=False, label='AN')
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+ plt.legend()
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+
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plt.sca(ax_ttz)
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plt.sca(ax_ttz)
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- hist_plot(ttz, title='TTZ', stats=False)
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- plt.sca(ax_tth)
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- hist_plot(tth, title='TTH', stats=False)
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+ an = ([0.974751, 0.269195, 1e-06, 0.395831, 0.0264703, 0.06816, 0.8804, 0.274265],
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+ [0, 0, 0, 0, 0, 0, 0, 0], [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5])
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+ hist_plot(ttz, title='TTZ', stats=False, label='Mock')
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+ hist_plot(an, title='TTZ', stats=False, label='AN')
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+ plt.xlabel('Signal Region')
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+ plt.sca(ax_tth)
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+ an = ([1.13826, 0.361824, 0.162123, 0.683917, 0.137608, 0.0632719, 0.554491, 0.197864],
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+ [0, 0, 0, 0, 0, 0, 0, 0], [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5])
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+ hist_plot(tth, title='TTH', stats=False, label='Mock')
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+ hist_plot(an, title='TTH', stats=False, label='AN')
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plt.xlabel('Signal Region')
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plt.xlabel('Signal Region')
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+
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@decl_plot
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@decl_plot
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def plot_yield_stack(rss):
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def plot_yield_stack(rss):
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r"""## Event Yield - Stacked
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r"""## Event Yield - Stacked
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@@ -71,11 +60,40 @@ def plot_yield_stack(rss):
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ft = ft[0]*10, ft[1], ft[2]
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ft = ft[0]*10, ft[1], ft[2]
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hist_plot(ft, label='TTTT (x10)', stats=False, color='k')
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hist_plot(ft, label='TTTT (x10)', stats=False, color='k')
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- plt.ylim((0, 160))
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+ plt.ylim((0, 60))
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plt.xlabel('Signal Region')
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plt.xlabel('Signal Region')
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plt.legend()
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plt.legend()
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+@decl_plot
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+def plot_lep_multi(rss, use_mc_reweight, dataset):
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+ _, (ax_els, ax_mus, ax_taus) = plt.subplots(3, 1)
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+ if use_mc_reweight:
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+ els = list(map(lambda rs: hist_normalize(hist(rs.nEls_mc)), rss))
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+ mus = list(map(lambda rs: hist_normalize(hist(rs.nMus_mc)), rss))
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+ taus = list(map(lambda rs: hist_normalize(hist(rs.nTaus_mc)), rss))
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+ else:
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+ els = list(map(lambda rs: hist_normalize(hist(rs.nEls)), rss))
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+ mus = list(map(lambda rs: hist_normalize(hist(rs.nMus)), rss))
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+ taus = list(map(lambda rs: hist_normalize(hist(rs.nTaus)), rss))
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+
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+ def _plot(ax, procs):
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+ plt.sca(ax)
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+ ft, ttw, ttz, tth = procs
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+ h = {'TTTT': ft,
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+ 'TTW': ttw,
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+ 'TTZ': ttz,
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+ 'TTH': tth}[dataset]
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+ hist_plot(h, stats=False, label=dataset)
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+
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+ _plot(ax_els, els)
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+ plt.xlabel('\\# Good Electrons')
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+ plt.legend()
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+ _plot(ax_mus, mus)
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+ plt.xlabel('\\# Good Muons')
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+ _plot(ax_taus, taus)
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+ plt.xlabel('\\# Good Taus')
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+
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@decl_plot
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@decl_plot
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def plot_sig_strength(rss):
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def plot_sig_strength(rss):
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r""" The signal strength of the TTTT signal defined as
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r""" The signal strength of the TTTT signal defined as
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@@ -88,12 +106,55 @@ def plot_sig_strength(rss):
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strength = ft[0] / np.sqrt(ft[0] + bg[0])
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strength = ft[0] / np.sqrt(ft[0] + bg[0])
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hist_plot((strength, ft[1], ft[2]), stats=False)
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hist_plot((strength, ft[1], ft[2]), stats=False)
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+@decl_plot
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+def plot_event_obs(rss, dataset):
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+ r"""
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+
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+ """
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+ _, ((ax_ht, ax_met), (ax_njet, ax_nbjet)) = plt.subplots(2, 2)
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+ # ft, ttw, ttz, tth = map(lambda rs: hist(rs.SRs), rss)
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+ ft, ttw, ttz, tth = rss
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+ rs = {'TTTT': ft,
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+ 'TTW': ttw,
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+ 'TTZ': ttz,
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+ 'TTH': tth}[dataset]
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+
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+ def _plot(ax, obs):
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+ plt.sca(ax)
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+ h = {'MET': rs.met,
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+ 'HT': rs.ht,
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+ 'NJET': rs.njet,
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+ 'NBJET': rs.nbjet}[obs]
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+ hist_plot(hist(h), stats=False, label=dataset, xlabel=obs)
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+
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+ _plot(ax_ht, 'HT')
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+ _plot(ax_met, 'MET')
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+ _plot(ax_njet, 'NJET')
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+ _plot(ax_nbjet, 'NBJET')
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+
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+
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+@decl_plot
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+def plot_fake_taus(rss):
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+ _, ((ax_ft, ax_ttw), (ax_ttz, ax_tth)) = plt.subplots(2, 2)
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+ ft, ttw, ttz, tth = list(map(lambda rs: hist(rs.tau_fakes_v_pt), rss))
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+
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+ def _plot(ax, dataset):
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+ plt.sca(ax)
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+ h = {'TTTT': ft,
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+ 'TTW': ttw,
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+ 'TTZ': ttz,
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+ 'TTH': tth}[dataset]
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+ hist_plot(h, stats=False, label=dataset)
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+
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+ _plot(ax_ft, 'TTTT')
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+ _plot(ax_ttw, 'TTW')
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+ _plot(ax_ttz, 'TTZ')
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+ _plot(ax_tth, 'TTH')
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+
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if __name__ == '__main__':
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if __name__ == '__main__':
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# First create a ResultSet object which loads all of the objects from output.root
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# First create a ResultSet object which loads all of the objects from output.root
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# into memory and makes them available as attributes
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# into memory and makes them available as attributes
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- # if len(sys.argv) != 2:
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- # raise ValueError("please supply root file")
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rss = (ResultSet("ft", 'data/yield_ft.root'),
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rss = (ResultSet("ft", 'data/yield_ft.root'),
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ResultSet("ttw", 'data/yield_ttw.root'),
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ResultSet("ttw", 'data/yield_ttw.root'),
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ResultSet("ttz", 'data/yield_ttz.root'),
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ResultSet("ttz", 'data/yield_ttz.root'),
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@@ -113,25 +174,56 @@ if __name__ == '__main__':
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sig_strength_tau = (plot_sig_strength, (rss,), {})
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sig_strength_tau = (plot_sig_strength, (rss,), {})
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sig_strength_notau = (plot_sig_strength, (rss_notau,), {})
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sig_strength_notau = (plot_sig_strength, (rss_notau,), {})
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+
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+ ft_lep_multi = (plot_lep_multi, (rss, True, 'TTTT'), {})
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+ ttw_lep_multi = (plot_lep_multi, (rss, True, 'TTW'), {})
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+ ttz_lep_multi = (plot_lep_multi, (rss, True, 'TTZ'), {})
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+ tth_lep_multi = (plot_lep_multi, (rss, True, 'TTH'), {})
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+
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+ ft_event_obs = (plot_event_obs, (rss, 'TTTT'), {})
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+ ttw_event_obs = (plot_event_obs, (rss, 'TTW'), {})
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+ ttz_event_obs = (plot_event_obs, (rss, 'TTZ'), {})
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+ tth_event_obs = (plot_event_obs, (rss, 'TTH'), {})
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+
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+ fake_taus = (plot_fake_taus, (rss,), {})
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+
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# Now assemble the plots into figures.
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# Now assemble the plots into figures.
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plots = [
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plots = [
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Plot([[yield_tau]],
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Plot([[yield_tau]],
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'Yield With Tau'),
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'Yield With Tau'),
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Plot([[yield_notau]],
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Plot([[yield_notau]],
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'Yield Without Tau'),
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'Yield Without Tau'),
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- # Plot([[yield_tau_stack]],
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- # 'Yield With Tau Stacked'),
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- # Plot([[yield_notau_stack]],
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- # 'Yield Without Tau Stacked'),
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+ Plot([[yield_tau_stack]],
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+ 'Yield With Tau Stacked'),
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+ Plot([[yield_notau_stack]],
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+ 'Yield Without Tau Stacked'),
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Plot([[yield_tau_stack],
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Plot([[yield_tau_stack],
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[yield_notau_stack]],
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[yield_notau_stack]],
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- 'Event Yield, top: with tau, bottom, no tau'),
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+ 'Event Yield, top: with tau, bottom: no tau'),
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Plot([[sig_strength_tau],
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Plot([[sig_strength_tau],
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[sig_strength_notau]],
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[sig_strength_notau]],
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- 'Signal Strength')
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+ 'Signal Strength'),
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+ Plot([[ft_lep_multi]],
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+ 'Lepton Multiplicity - TTTT'),
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+ Plot([[ttw_lep_multi]],
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+ 'Lepton Multiplicity - TTW'),
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+ Plot([[ttz_lep_multi]],
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+ 'Lepton Multiplicity - TTZ'),
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+ Plot([[tth_lep_multi]],
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+ 'Lepton Multiplicity - TTH'),
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+ Plot([[ft_event_obs]],
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+ 'TTTT - Event Observables'),
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+ Plot([[ttw_event_obs]],
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+ 'TTW - Event Observables'),
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+ Plot([[ttz_event_obs]],
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+ 'TTZ - Event Observables'),
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+ Plot([[tth_event_obs]],
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+ 'TTH - Event Observables'),
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+ Plot([[fake_taus]],
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+ 'Hadronic Tau fake-rate'),
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]
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]
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# Finally, render and save the plots and generate the html+bootstrap
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# Finally, render and save the plots and generate the html+bootstrap
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# dashboard to view them
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# dashboard to view them
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render_plots(plots, to_disk=False)
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render_plots(plots, to_disk=False)
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- generate_dashboard(plots, output='yield.html')
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+ generate_dashboard(plots, 'TTTT Yields', output='yield2.html', source_file=__file__)
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