def example_data_mc_histogram_plot():
hp = DataMCHistogramPlot(dummy_var)
hp.add_mc_component("Continum",
cont.DummyVariable,
weights=cont.__weight__,
color=TangoColors.slate)
hp.add_mc_component("Background",
bkg.DummyVariable,
weights=bkg.__weight__,
color=TangoColors.sky_blue)
hp.add_mc_component("Signal",
sig.DummyVariable,
weights=sig.__weight__,
color=TangoColors.orange)
hp.add_data_component("Data", data)
fig, ax = create_hist_ratio_figure()
hp.plot_on(ax[0], ax[1], style="stacked", ylabel="Candidates")
add_descriptions_to_plot(
ax[0],
experiment='Belle II',
luminosity=r"$\int \mathcal{L} \,dt=5\,\mathrm{fb}^{-1}$",
additional_info='WG1 Preliminary Plot Style\nDataMCHistogramPlot')
plt.show()
export(fig, 'data-mc', 'examples')
plt.close()
def example_stacked_histogram_plot():
hp = StackedHistogramPlot(dummy_var)
hp.add_component("Continum",
cont.DummyVariable,
weights=cont.__weight__,
color=TangoColors.slate,
comp_type='stacked')
hp.add_component("Background",
bkg.DummyVariable,
weights=bkg.__weight__,
color=TangoColors.sky_blue,
comp_type='stacked')
hp.add_component("Signal",
sig.DummyVariable,
weights=sig.__weight__,
color=TangoColors.orange,
comp_type='stacked')
fig, ax = create_solo_figure()
hp.plot_on(ax, ylabel="Candidates")
add_descriptions_to_plot(
ax,
experiment='Belle II',
luminosity=r"$\int \mathcal{L} \,dt=5\,\mathrm{fb}^{-1}$",
additional_info='WG1 Preliminary Plot Style\nStackedHistogramPlot')
plt.show()
export(fig, 'stacked', 'examples')
plt.close()
def example_simple_histogram_plot():
hp1 = SimpleHistogramPlot(dummy_var)
hp1.add_component("Something",
data.DummyVariable,
color=TangoColors.scarlet_red)
hp2 = SimpleHistogramPlot(dummy_var)
hp2.add_component("Else", bkg.DummyVariable, color=TangoColors.aluminium)
fig, ax = create_solo_figure()
hp1.plot_on(ax, ylabel="Events")
hp2.plot_on(ax)
add_descriptions_to_plot(
ax,
experiment='Belle II',
luminosity=r"$\int \mathcal{L} \,dt=5\,\mathrm{fb}^{-1}$",
additional_info='WG1 Preliminary Plot Style\nSimpleHistogramPlot')
plt.show()
export(fig, 'simple', 'examples')
plt.close()
def example_data_plot():
x = np.linspace(0.5, 10.5, num=10)
y = np.array([np.random.normal(a, 1) for a in x])
x_err = 0.5 * np.ones(10)
y_err = np.ones(10)
variable = DataVariable(r"x-variable", r"x-units", r"y-variable",
"y-units")
measured = DataPoints(
x_values=x,
y_values=y,
x_errors=x_err,
y_errors=y_err,
)
x = np.linspace(0.5, 10.5, num=10)
y = np.array([np.random.normal(a, 1) for a in x])
x_err = 0.5 * np.ones(10)
y_err = np.ones(10) * 0.5
theory = DataPoints(
x_values=x,
y_values=y,
x_errors=x_err,
y_errors=y_err,
)
dp = DataPointsPlot(variable)
dp.add_component("Data Label", measured, style='point')
dp.add_component("Theory Label",
theory,
style='box',
color=TangoColors.scarlet_red)
fig, ax = create_solo_figure(figsize=(5, 5))
dp.plot_on(ax)
add_descriptions_to_plot(ax,
experiment='Can be misused',
luminosity='This too',
additional_info=r'Some process')
plt.show()
export(fig, 'data', 'examples')
plt.close()
def example_combo_plot():
hp1 = StackedHistogramPlot(dummy_var)
hp1.add_component("Continum",
cont.DummyVariable,
weights=cont.__weight__,
color=TangoColors.slate,
comp_type='stacked')
hp1.add_component("Background",
bkg.DummyVariable,
weights=bkg.__weight__,
color=TangoColors.sky_blue,
comp_type='stacked')
hp1.add_component("Signal",
sig.DummyVariable,
weights=sig.__weight__,
color=TangoColors.orange,
comp_type='stacked')
hp2 = SimpleHistogramPlot(dummy_var)
hp2.add_component("Signal Shape x0.5",
sig.DummyVariable,
weights=sig.__weight__ * 0.5,
color=TangoColors.scarlet_red,
ls='-.')
fig, ax = create_solo_figure()
hp1.plot_on(ax, ylabel="Candidates")
hp2.plot_on(ax, hide_labels=True) # Hide labels to prevent overrides)
add_descriptions_to_plot(
ax,
experiment='Belle II',
luminosity=r"$\int \mathcal{L} \,dt=5\,\mathrm{fb}^{-1}$",
additional_info=
'WG1 Preliminary Plot Style\nStackedHistogramPlot\n+SimpleHistogramPlot'
)
plt.show()
export(fig, 'combo', 'examples')
plt.close()
def example3_combo_plot():
hp = DataMCHistogramPlot(dummy_var)
hp.add_mc_component("Continum",
cont.DummyVariable,
weights=cont.__weight__,
color=TangoColors.slate)
hp.add_mc_component("Background",
bkg.DummyVariable,
weights=bkg.__weight__,
color=TangoColors.sky_blue)
hp.add_mc_component("Signal",
sig.DummyVariable,
weights=sig.__weight__,
color=TangoColors.orange)
hp.add_data_component("Data", data)
fig, ax = create_hist_ratio_figure()
hp.plot_on(ax[0], ax[1], style="stacked", ylabel="Candidates")
add_descriptions_to_plot(
ax[0],
experiment='Belle II',
luminosity=r"$\int \mathcal{L} \,dt=5\,\mathrm{fb}^{-1}$",
additional_info=
'WG1 Preliminary Plot Style\nDataMCHistogramPlot\n+SomeFunction')
# Let's add some functions
ax[0].plot(
np.linspace(*dummy_var.scope),
500 * scipy.stats.norm(2).pdf(np.linspace(*dummy_var.scope)),
label="Some function",
color=TangoColors.chameleon,
)
ax[0].legend(frameon=False)
plt.show()
export(fig, 'combo3', 'examples')
plt.close()