def get_thetas(self):
histogram2D = self.to_hist()
xs = []
ys = []
twodeltaNLLs = []
for i_center, x in enumerate(histogram2D.x_bin_centers):
all_deltaNNLs = histogram2D.H2_array[i_center][:]
all_ys = histogram2D.y_bin_centers
min_deltaNLL = 9999.
for y, deltaNLL in zip(all_ys, all_deltaNNLs):
y_on_line = -1. / 12. * x
if y < 0.8 * y_on_line: continue
if deltaNLL < min_deltaNLL:
min_deltaNLL = deltaNLL
min_y = y
ys.append(min_y)
xs.append(x)
twodeltaNLLs.append(min_deltaNLL)
thetas = [math.atan2(y, x) for x, y in zip(xs, ys)]
thetas, twodeltaNLLs = [
list(l) for l in zip(*sorted(zip(thetas, twodeltaNLLs)))
]
graph = plotting.pywrappers.Graph(utils.get_unique_rootname(),
'theta',
thetas,
twodeltaNLLs,
color=self.color)
return graph
def make_spline(self):
x = self.make_var_unique_name(self.x_var, self.x_min, self.x_max)
y = self.make_var_unique_name(self.y_var, self.y_min, self.y_max)
s = ROOT.RooArgList(x, y)
ROOT.SetOwnership(s, False)
spline = ROOT.RooSplineND(
'spline_' + get_unique_rootname(), 'spline2D',
s,
self.tree,
self.z_var,
self.eps,
True, # boolean rescale
'deltaNLL>0 && deltaNLL<{0}'.format(self.deltaNLL_cutoff) + self.cutstring_addition,
)
splinewrapper = Spline2DWrapper(spline, x, y,
x_min = self.x_min,
x_max = self.x_max,
y_min = self.y_min,
y_max = self.y_max,
)
if self.filled_bestfit:
splinewrapper.fill_bestfit(self.x_bestfit, self.y_bestfit)
return splinewrapper
def make_polyfit(self, graph=None):
logging.info('Creating polyfit')
fstring = self.compile_2d_fit_string()
if graph is None:
graph = self.get_graph()
logging.info('fit string is: ' + fstring)
f2D = ROOT.TF2(
'f2D' + get_unique_rootname(), fstring,
self.x_min, self.x_max,
self.y_min, self.y_max
)
logging.info(
'Fitting TGraph2D ({0} x {1} = {2} points) with TF2...'
.format(graph.GetNpx(), graph.GetNpy(), graph.GetN())
)
graph.Fit(f2D.GetName())
polyfit = PolyFit2DWrapper(f2D,
x_min = self.x_min,
x_max = self.x_max,
y_min = self.y_min,
y_max = self.y_max,
)
polyfit.multiply_by_two = True
if self.filled_bestfit:
polyfit.fill_bestfit(self.x_bestfit, self.y_bestfit)
return polyfit
def to_hist_smxs(self):
histogram = plotting.pywrappers.Histogram(
utils.get_unique_rootname(), core.standard_titles['SM_Vittorio'],
self.binning(), self.smxs)
# histogram.set_err_up([ s.unc.right_error * xs for s, xs in zip(self.scans, self.smxs) ])
# histogram.set_err_down([ s.unc.left_error * xs for s, xs in zip(self.scans, self.smxs) ])
self.process_overflow_and_underflow(histogram)
histogram.add_stylesheet(self.style().copy(
color=16, plot_priority=self.style().plot_priority - 5))
return histogram
def to_hist(self):
histogram = plotting.pywrappers.Histogram(
utils.get_unique_rootname(), self.title, self.binning(),
[s.unc.x_min for s in self.scans])
histogram.set_err_up([s.unc.right_error for s in self.scans])
histogram.set_err_down([s.unc.left_error for s in self.scans])
self.process_overflow_and_underflow(histogram)
# if not(self.color is None): histogram.color = self.color
histogram.add_stylesheet(self.style())
return histogram
def to_graph(self):
name = utils.get_unique_rootname()
graph = plotting.pywrappers.Graph(name, self.title, self.x(),
self.two_times_deltaNLL())
if hasattr(self, 'color'):
# graph.color = self.color
graph.style().color = self.color
if hasattr(self, 'draw_style'):
graph.draw_style = self.draw_style
return graph
def to_hist(self):
histogram2D = plotting.pywrappers.Histogram2D(
utils.get_unique_rootname(), getattr(self, 'title', ''),
self.color)
histogram2D.x_title = self.x_title
histogram2D.y_title = self.y_title
histogram2D.z_title = self.z_title
if self._filled_bestfit:
histogram2D.fill_bestfit(self.bestfit().x, self.bestfit().y)
histogram2D.fill_from_entries(self.entries)
if hasattr(self, 'contour_filter_method'):
histogram2D.contour_filter_method = self.contour_filter_method
return histogram2D
def get_1d_y(self, histogram2D):
xs = []
deltaNLLs = []
for i_center, center in enumerate(histogram2D.y_bin_centers):
deltaNLL = min([row[i_center] for row in histogram2D.H2_array])
xs.append(center)
deltaNLLs.append(deltaNLL)
graph = plotting.pywrappers.Graph(utils.get_unique_rootname(),
self.y_variable,
xs,
deltaNLLs,
color=self.color)
return graph
def name(self):
return 'f2D_' + get_unique_rootname()
def name(self):
return get_unique_rootname()