def get_plot_attributes(year, dmc, plot):
"""
Get the plot attributes for a given plot
"""
year_colors = {
'2012': 1,
'2016': default_colors()[0],
'2017': default_colors()[1]
}
marker_style = {'2012': 20, '2016': 22, '2017': 23}
marker_style_open = {'2012': 24, '2016': 26, '2017': 32}
fill_style = {'chic1': 3354, 'chic2': 3345, 'chib1': 3354, 'chib2': 3345}
size = 2
linewidth = 2
color = year_colors[year]
if plot == 'ratio' or plot == 'chic2' or plot == 'chib2':
marker = marker_style[year]
else:
marker = marker_style_open[year]
attr = {'color': color, 'marker': marker, 'size': size, 'width': linewidth}
if dmc == 'mc':
attr['size'] = 0 # do not plot markers for mc
attr['width'] = 0
if plot == 'ratio':
attr['fillalpha'] = (color, 0.5)
else:
attr['fillstyle'] = fill_style[plot]
return attr
def make_mass_quantile_plot(hist, quantile_pairs, color, savename):
"""
Quantile plots for one state.
TODO:
"""
y_range = [0, hist.GetMaximum() * 1.05]
set_range_hists([hist], y_range=y_range)
can = mkplot([hist], colors=[color], drawOpt='H')
leg = r.TLegend(0.1, 0.91, 0.9, 0.95)
leg.SetNColumns(len(quantile_pairs))
leg.SetBorderSize(0)
line_styles = [2, 3, 5, 6]
# store all lines in this list so that they live long enough to be plotted
lines = []
for i, pair in enumerate(quantile_pairs):
quantiles = get_quantiles(hist, pair)
qline_1, qline_2 = get_quantile_lines(quantiles, y_range,
default_colors()[0], line_styles[i])
qline_2.Draw()
qline_1.Draw()
leg.AddEntry(qline_1, '[{}, {}]'.format(*pair), 'l')
lines.append(qline_1)
lines.append(qline_2)
leg.Draw()
can.Draw()
can.SaveAs(savename)
def make_mass_quantile_plots(mcfile, quantile_pairs, savename_base):
"""
TODO
"""
chic1_h, chic2_h = get_gen_splitted_hists(mcfile, 'chicMass',
[select_trigger(),
base_selection()])
set_labels(chic1_h, xlabel='M^{#mu#mu#gamma}')
set_labels(chic2_h, xlabel='M^{#mu#mu#gamma}')
chic1_col = default_colors()[1]
chic2_col = default_colors()[2]
make_mass_quantile_plot(chic1_h, quantile_pairs, chic1_col,
savename_base + '_chic1.pdf')
make_mass_quantile_plot(chic2_h, quantile_pairs, chic2_col,
savename_base + '_chic2.pdf')
def get_attributes():
"""attributes for plotting nicely in accordance with order of histograms as
returned by select_histsk"""
defc = default_colors()
# return [
# {'color': defc[0], 'marker': 20, 'size': 1.5}, {'color': defc[0], 'marker': 24, 'size': 1.5},
# {'color': defc[1], 'marker': 21, 'size': 1.5}, {'color': defc[1], 'marker': 25, 'size': 1.5},
# {'color': defc[2], 'marker': 22, 'size': 1.5}, {'color': defc[2], 'marker': 26, 'size': 1.5},
# {'color': defc[3], 'marker': 23, 'size': 1.5}, {'color': defc[3], 'marker': 32, 'size': 1.5}
# ]
return [
{'color': defc[0], 'marker': 20, 'size': 1.5},
{'color': defc[1], 'marker': 21, 'size': 1.5},
{'color': defc[2], 'marker': 22, 'size': 1.5},
{'color': defc[3], 'marker': 23, 'size': 1.5}
]
def make_var_plot(nom_file, var_files, var):
"""
Make a variation plot comparing the nominal PPD to the variations PPDs
"""
nom_ppd = get_scaled_ppd(nom_file, var)
nom_quants = get_quantiles(nom_ppd, QUANTILES)
nom_lo, nom_hi = np.diff(nom_quants)
nom_graph = get_nom_graph(len(var_files), nom_lo, nom_hi)
# var_graphs = get_var_graphs_wrt_nominal(var_files, nom_quants, var)
var_graphs = get_var_graphs_wrt_nominal(
var_files, [nom_ppd.GetMean(), nom_ppd.GetRMS()], var)
xran = np.max([nom_lo, nom_hi]) * 1.75
yran = [-0.25, len(var_files) - 0.75]
can = mkplot(nom_graph,
attr=[{
'fillalpha': (default_colors()[1], 0.5)
}],
drawOpt='E2',
xLabel=get_label(var),
xRange=[-xran, xran],
yRange=yran)
mkplot(r.TLine(0, yran[0], 0, yran[1]),
can=can,
drawOpt='same',
attr=default_attributes(widht=2)[1:])
mkplot(var_graphs, drawOpt='samePE', can=can, attr=VAR_ATTR)
phist = can.pltables[0]
phist.GetYaxis().SetLabelSize(0)
phist.GetYaxis().SetTickSize(0)
ltx = setup_latex()
put_on_latex(ltx, get_labels(var_files.keys()), ndc=True)
ltx.Draw()
can.Draw()
return can
def make_plot(data_graph, mc_graphs, pdfname, canvas_sett):
"""
Make plot and save
"""
mc_attributes = [{
'color': default_colors()[0],
'marker': 25,
'size': 1.5,
'fillalpha': (default_colors()[0], 0.5)
}, {
'color': default_colors()[1],
'marker': 26,
'size': 1.5,
'fillalpha': (default_colors()[1], 0.5)
}, {
'color': default_colors()[2],
'marker': 27,
'size': 1.5,
'fillalpha': (default_colors()[2], 0.5)
}]
data_attributes = [{'color': 1, 'marker': 20, 'size': 1.5}]
set_TDR_style()
can = r.TCanvas('rcan', 'rcan', 50, 50, 600, 600)
frame = can.DrawFrame(*canvas_sett['range'])
frame.SetXTitle(canvas_sett['xtitle'])
frame.SetYTitle(canvas_sett['ytitle'])
leg = setup_legend()
mc_rescaled = rescale_MC_graphs(data_graph, mc_graphs.values(), SCALE_FUNC)
plot_on_canvas(can,
mc_rescaled,
drawOpt='P2',
leg=leg,
legOpt='PF',
legEntries=mc_graphs.keys(),
attr=mc_attributes)
plot_on_canvas(can, [data_graph],
drawOpt='samePE',
leg=leg,
legEntries=['data'],
attr=data_attributes)
can.SaveAs(pdfname)
import ROOT as r
r.PyConfig.IgnoreCommandLineOptions = True
r.gROOT.SetBatch()
from utils.plot_helpers import (mkplot, setup_legend, default_colors,
setup_latex, put_on_latex)
from utils.plot_decoration import YLABELS
from utils.data_handling import list_obj
from utils.graph_utils import get_errors, scale_graph_x
from utils.setup_plot_style import set_TDR_style, add_auxiliary_info
from utils.misc_helpers import cond_mkdir, fmt_float
from utils.constants import m_psiPDG
PCOLOR = default_colors()[0]
SCOLOR = default_colors()[2]
FCOLOR = default_colors()[1]
ATTR = {
'central': [{
'color': PCOLOR,
'marker': 20,
'size': 1.0,
'width': 2
}],
'1': [{
'fillalpha': (PCOLOR, 0.65),
'size': 0,
'width': 0
}],
Script that plots all data to best fit model comparisons
"""
import numpy as np
import ROOT as r
r.PyConfig.IgnoreCommandLineOptions = True
r.gROOT.SetBatch()
from utils.plot_helpers import (mkplot, setup_legend, default_colors,
_setup_canvas)
from utils.misc_helpers import cond_mkdir
from utils.setup_plot_style import set_basic_style
from utils.data_handling import list_obj
from utils.graph_utils import scale_graph, pull_graph, divide_func, shift_graph
COL = default_colors()
DATA_ATTR = [{
'color': 1,
'marker': 20,
'size': 0.75
}, {
'color': 1,
'marker': 25,
'size': 0.75
}, {
'color': 1,
'marker': 26,
'size': 0.75
}]
# define which variables to read in
# first the ones that are common to both Toy and real MC, then the ones only
# present in the real MC (into a separate) list, then add the efficiencies to
# the Toy MC
TOY_VARIABLES = [
'Jpsi{Pt,Rap}',
'photon{Pt,Eta}',
'mu{P,N}{Pt,Eta}',
'costh_HX',
]
MC_VARIABLES = TOY_VARIABLES + ['trigger', 'pdgId', 'vtxProb', 'gen_photonEta']
TOY_VARIABLES += ['*eff_sm']
PLOT_ATTRIBUTES = {
'loose': {
'mc': {
'fillalpha': (default_colors()[4], 0.5),
'size': 0,
'marker': 22
},
'toy': {
'color': default_colors()[4],
'size': 1.5,
'marker': 22
}
},
'fiducial': {
'mc': {
'fillalpha': (default_colors()[3], 0.5),
'size': 0,
'marker': 23
},
logging.basicConfig(level=logging.DEBUG,
format='%(levelname)s - %(funcName)s: %(message)s')
from os.path import dirname
from utils.misc_helpers import cond_mkdir, get_storable_name, get_bin_cut_df
from utils.plot_helpers import plot_on_canvas, default_colors
from utils.roofit_utils import get_var_err
from utils.data_handling import get_dataframe
from utils.setup_plot_style import set_TDR_style
from utils.graph_utils import scale_graph, get_y
from common_func import get_bin_sel_info
mc_attributes = [{
'color': default_colors()[0],
'marker': 25,
'size': 1.5,
'fillalpha': (default_colors()[0], 0.5)
}, {
'color': default_colors()[1],
'marker': 26,
'size': 1.5,
'fillalpha': (default_colors()[1], 0.5)
}, {
'color': default_colors()[2],
'marker': 27,
'size': 1.5,
'fillalpha': (default_colors()[2], 0.5)
}]
def make_comp_plot(graph, intgraph, fit=False):
"""
Make one comparison plot and return the TCanvasWrapper
"""
plt_attr = [{
'color': default_colors()[0],
'marker': 20,
'size': 1.5
}, {
'color': default_colors()[1],
'marker': 24,
'size': 0.5,
'fillalpha': (default_colors()[1], 0.5)
}, {
'color': default_colors()[4],
'line': 2,
'width': 2
}]
graph_name = graph.GetName().replace('_v_costh', '')
if graph_name in FIX_RANGES:
yRange = FIX_RANGES[graph_name]
else:
yRange = None
ylabel = YLABELS[graph_name] if graph_name in YLABELS else graph_name
can = mkplot(graph,
xRange=[0, 1],
drawOpt='PE',
attr=plt_attr[0:],
yRange=yRange,
yLabel=ylabel,
xLabel='|cos#vartheta^{HX}|')
# some cosmetics
can.SetTopMargin(0.05)
can.SetRightMargin(0.02)
can.SetLeftMargin(0.15)
can.pltables[0].SetTitleOffset(2.1, 'Y')
if intgraph is not None or fit:
leg = setup_legend(0.65, 0.85, 0.97, 0.94)
if intgraph is not None:
can = mkplot(intgraph,
can=can,
drawOpt='sameP2',
attr=plt_attr[1:],
leg=leg,
legEntries=['cos#vartheta^{HX} int. fit'],
legOpt='PLEF')
can = mkplot(intgraph, can=can, drawOpt='samePE', attr=plt_attr[1:])
if fit:
const = r.TF1('const', '[0]', 0, 1)
const.SetParameter(0, np.array(graph.GetX())[0])
fit_res = graph.Fit(const, 'NSEX0')
can = mkplot(const,
can=can,
drawOpt='sameL',
attr=plt_attr[2:],
leg=leg,
legEntries=['fit to constant'],
legOpt='L')
ltx = setup_latex()
can.add_tobject(ltx)
put_on_latex(ltx,
[(0.595, 0.2, 'c = {:.2e} +/- {:.2e}'.format(
const.GetParameter(0), const.GetParError(0))),
(0.595, 0.25, '#chi^{{2}} / ndf = {:.2f} / {}'.format(
fit_res.Chi2(), fit_res.Ndf()))],
ndc=True)
can.Update()
return can
