def plot_on(self,
ax: plt.axis,
ylabel="Events",
draw_legend=True,
legend_inside=True,
hide_labels: bool = False):
bin_edges, bin_mids, bin_width = self._get_bin_edges()
self._bin_edges = bin_edges
self._bin_mids = bin_mids
self._bin_width = bin_width
ax.hist(
x=[comp.data for comp in self._mc_components['stacked']],
bins=bin_edges,
weights=[comp.weights for comp in self._mc_components['stacked']],
stacked=True,
edgecolor="black",
lw=0.3,
color=[comp.color for comp in self._mc_components['stacked']],
label=[comp.label for comp in self._mc_components['stacked']],
histtype='stepfilled')
if not hide_labels:
ax.set_xlabel(self._variable.x_label, plot_style.xlabel_pos)
y_label = self._get_y_label(False, bin_width, ylabel)
ax.set_ylabel(y_label, plot_style.ylabel_pos)
if draw_legend:
if legend_inside:
ax.legend(frameon=False)
ylims = ax.get_ylim()
ax.set_ylim(ylims[0], 1.4 * ylims[1])
else:
ax.legend(frameon=False, bbox_to_anchor=(1, 1))
return ax
def plot_on(
self,
ax1: plt.axis,
ax2,
style="stacked",
ylabel="Events",
sum_color=plot_style.KITColors.kit_purple,
draw_legend: bool = True,
legend_inside: bool = True,
):
bin_edges, bin_mids, bin_width = self._get_bin_edges()
self._bin_edges = bin_edges
self._bin_mids = bin_mids
self._bin_width = bin_width
sum_w = np.sum(np.array([
binned_statistic(comp.data,
comp.weights,
statistic="sum",
bins=bin_edges)[0]
for comp in self._mc_components["MC"]
]),
axis=0)
sum_w2 = np.sum(np.array([
binned_statistic(comp.data,
comp.weights**2,
statistic="sum",
bins=bin_edges)[0]
for comp in self._mc_components["MC"]
]),
axis=0)
hdata, _ = np.histogram(self._data_component.data, bins=bin_edges)
if style.lower() == "stacked":
ax1.hist(
x=[comp.data for comp in self._mc_components['MC']],
bins=bin_edges,
weights=[comp.weights for comp in self._mc_components['MC']],
stacked=True,
edgecolor="black",
lw=0.3,
color=[comp.color for comp in self._mc_components['MC']],
label=[comp.label for comp in self._mc_components['MC']],
histtype='stepfilled')
ax1.bar(x=bin_mids,
height=2 * np.sqrt(sum_w2),
width=self.bin_width,
bottom=sum_w - np.sqrt(sum_w2),
color="black",
hatch="///////",
fill=False,
lw=0,
label="MC stat. unc.")
if style.lower() == "summed":
ax1.bar(x=bin_mids,
height=2 * np.sqrt(sum_w2),
width=self.bin_width,
bottom=sum_w - np.sqrt(sum_w2),
color=sum_color,
lw=0,
label="MC")
ax1.errorbar(x=bin_mids,
y=hdata,
yerr=np.sqrt(hdata),
ls="",
marker=".",
color="black",
label=self._data_component.label)
y_label = self._get_y_label(False, bin_width, evts_or_cand=ylabel)
# ax1.legend(loc=0, bbox_to_anchor=(1,1))
ax1.set_ylabel(y_label, plot_style.ylabel_pos)
if draw_legend:
if legend_inside:
ax1.legend(frameon=False)
ylims = ax1.get_ylim()
ax1.set_ylim(ylims[0], 1.4 * ylims[1])
else:
ax1.legend(frameon=False, bbox_to_anchor=(1, 1))
ax2.set_ylabel(r"$\frac{\mathrm{Data - MC}}{\mathrm{Data}}$")
ax2.set_xlabel(self._variable.x_label, plot_style.xlabel_pos)
ax2.set_ylim((-1, 1))
try:
uhdata = unp.uarray(hdata, np.sqrt(hdata))
uhmc = unp.uarray(sum_w, np.sqrt(sum_w2))
ratio = (uhdata - uhmc) / uhdata
ax2.axhline(y=0, color=plot_style.KITColors.dark_grey, alpha=0.8)
ax2.errorbar(bin_mids,
unp.nominal_values(ratio),
yerr=unp.std_devs(ratio),
ls="",
marker=".",
color=plot_style.KITColors.kit_black)
except ZeroDivisionError:
ax2.axhline(y=0, color=plot_style.KITColors.dark_grey, alpha=0.8)
plt.subplots_adjust(hspace=0.08)
def plot_on(self,
ax: plt.axis,
draw_legend: bool = True,
legend_inside: bool = True,
yaxis_scale=1.3,
normed: bool = False,
ylabel="Events",
hide_labels: bool = False) -> plt.axis:
"""
Plots the component on a given matplotlib.pyplot.axis
:param ax: matplotlib.pyplot.axis where the histograms will be drawn
on.
:param draw_legend: Draw legend on axis if True.
:param normed: If true the histograms are normalized.
:return: matplotlib.pyplot.axis with histogram drawn on it
"""
bin_edges, bin_mids, bin_width = self._get_bin_edges()
self._bin_edges = bin_edges
self._bin_mids = bin_mids
self._bin_width = bin_width
for component in self._mc_components['single']:
if component.histtype == 'stepfilled':
alpha = 0.6
edge_color = 'black'
else:
edge_color = None
alpha = 1.0
ax.hist(x=component.data,
bins=bin_edges,
density=normed,
weights=component.weights,
histtype=component.histtype,
label=component.label,
edgecolor=edge_color
if edge_color is not None else component.color,
alpha=alpha,
lw=1.5,
ls=component.ls,
color=component.color)
if not hide_labels:
ax.set_xlabel(self._variable.x_label, plot_style.xlabel_pos)
y_label = self._get_y_label(normed=normed,
bin_width=bin_width,
evts_or_cand=ylabel)
ax.set_ylabel(y_label, plot_style.ylabel_pos)
if draw_legend:
if legend_inside:
ax.legend(frameon=False)
ylims = ax.get_ylim()
ax.set_ylim(ylims[0], yaxis_scale * ylims[1])
else:
ax.legend(frameon=False, bbox_to_anchor=(1, 1))
return ax