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@@ -186,13 +186,13 @@ def scale_signal(x, scale, popt_CB=popt_CB):
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return scale * CB(x, *popt_CB)
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return scale * CB(x, *popt_CB)
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-popt, pcov = curve_fit(scale_signal, bin_centers, extracted_signal, sigma=bin_errors, p0=[1.])
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+popt, pcov = curve_fit(scale_signal, bin_centers, extracted_signal, sigma=pldict['Data'][3], p0=[1.])
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NHiggs = int(popt_CB[0] * popt[0])
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NHiggs = int(popt_CB[0] * popt[0])
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plt.figure(figsize=(12, 8))
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plt.figure(figsize=(12, 8))
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plt.title('Fitted signal', fontsize=22)
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plt.title('Fitted signal', fontsize=22)
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plt.plot(xs, scale_signal(xs, popt), color='r', label='Fitted signal')
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plt.plot(xs, scale_signal(xs, popt), color='r', label='Fitted signal')
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-plt.scatter(bin_centers, extracted_signal, color='k', label='Extracted signal')
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+plt.errorbar(bin_centers, extracted_signal, pldict['Data'][3], xerrs, marker='o', markersize=5, color='k', ecolor='k', ls='', label='Extracted signal')
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plt.text(130, -200, r'$\alpha_{{scale}} = {:.3f}$'.format(*popt) + '\n' + r'$N_{{Higgs}} = {:d}$'.format(NHiggs), size=20, bbox=dict(facecolor='w', edgecolor='gray', boxstyle='round,pad=0.5'))
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plt.text(130, -200, r'$\alpha_{{scale}} = {:.3f}$'.format(*popt) + '\n' + r'$N_{{Higgs}} = {:d}$'.format(NHiggs), size=20, bbox=dict(facecolor='w', edgecolor='gray', boxstyle='round,pad=0.5'))
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plt.xlabel(r'$m_{\mu \mu}$', fontsize=20)
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plt.xlabel(r'$m_{\mu \mu}$', fontsize=20)
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plt.ylabel('Number of events', fontsize=20)
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plt.ylabel('Number of events', fontsize=20)
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Blaz Leban