map(h2.Fill, x2) # normalize the histograms h1 /= h1.Integral() h2 /= h2.Integral() # set visual attributes h1.SetFillStyle("solid") h1.SetFillColor("green") h1.SetLineColor("green") h2.SetFillStyle("solid") h2.SetFillColor("red") h2.SetLineColor("red") # plot with ROOT h1.GetXaxis().SetTitle('Smarts') h1.GetYaxis().SetTitle('Probability') h1.SetTitle("Histogram of IQ: #mu=100, #sigma=15") h1.Draw("hist") h2.Draw("same") # plot with matplotlib plt.figure() rplt.hist(h1, alpha=0.75) rplt.hist(h2, alpha=0.75) plt.xlabel('Smarts') plt.ylabel('Probability') plt.title(r'$\mathrm{Histogram\ of\ IQ:}\ \mu=100,\ \sigma=15$') plt.show()
# normalize the histograms h1 /= h1.Integral() h2 /= h2.Integral() # set visual attributes h1.SetFillStyle('solid') h1.SetFillColor('green') h1.SetLineColor('green') h2.SetFillStyle('solid') h2.SetFillColor('red') h2.SetLineColor('red') stack = HistStack() stack.Add(h1) stack.Add(h2) # plot with ROOT h1.SetTitle('Histogram of IQ: #mu=100, #sigma=15') stack.Draw() h1.GetXaxis().SetTitle('Smarts') h1.GetYaxis().SetTitle('Probability') # plot with matplotlib rplt.hist(stack, alpha=0.75) plt.xlabel('Smarts') plt.ylabel('Probability') plt.title(r'$\mathrm{Histogram\ of\ IQ:}\ \mu=100,\ \sigma=15$') plt.show()
map(h.Fill, x) # normalize the histogram h /= h.Integral() # set visual attributes h.SetFillStyle('/') h.SetFillColor('green') h.SetLineColor('green') # plot with ROOT c = Canvas(width=800, height=600) h.GetXaxis().SetTitle('Smarts') h.GetYaxis().SetTitle('Probability') h.SetTitle("Histogram of IQ: #mu=100, #sigma=15") h.Draw("hist") legend = Legend(1) legend.AddEntry(h, 'F') legend.Draw() c.SaveAs('root_hist.png') # plot with matplotlib plt.figure(figsize=(8, 6), dpi=100) rplt.hist(h, label=r'$\mathrm{Histogram\ of\ IQ:}\ \mu=100,\ \sigma=15$', alpha=0.75) plt.xlabel('Smarts') plt.ylabel('Probability') plt.title(r'$\mathrm{Histogram\ of\ IQ:}\ \mu=100,\ \sigma=15$') plt.legend() plt.savefig('matplotlib_hist.png') plt.show()