profiles[label.replace(' ', '_')] = { 'x': mean_x, 'y': points_y, 'e': err_x } ax.scatter(mean_x, points_y, s=80, facecolor='w', edgecolor='k', marker='o', linewidth=2) ticks = np.logspace(0, np.log10(np.max(counts)), 10) cbar = fig.colorbar(im, ticks=ticks, format=helpers.label_formatter) helpers.format_cbar(cbar) helpers.add_description( fig, ax, align='br', strings=[helpers.dataSetStr, helpers.seedCutStr]) helpers.add_labels( fig, ax, xlabel=r'$E_T^\mathrm{{{}}}$'.format(label), ylabel='offline jet\'s number of subjets (cut at 6)', title=label) ax.set_xlim((0.0, 100.0)) ax.set_ylim((1.0, 6.0))
profiles = {} profiles_scaled = {} for datapts, label in zip(all_gTower_Et, ['gTower 0', 'gTower 1', 'gTower 2', 'gTower 3']): try: fig, ax = pl.subplots(figsize=helpers.figsize) counts, edges_x, edges_y, im = ax.hist2d(datapts, data['oJet.nsj'][valid_gJets], bins=(np.arange(0., 100., 2.5), np.arange(1, 7, 1)), norm=LogNorm(), alpha=0.75, cmap=helpers.cmap, weights=data['weight'][np.where(tJet_exists)]) points_y, mean_x, err_x = helpers.profile_x(edges_y, data['oJet.nsj'][valid_gJets], datapts) profiles[label.replace(' ', '_')] = {'x': mean_x, 'y': points_y, 'e': err_x} ax.scatter(mean_x, points_y, s=80, facecolor='w', edgecolor='k', marker='o', linewidth=2) ticks = np.logspace(0, np.log10(np.max(counts)), 10) cbar = fig.colorbar(im, ticks=ticks, format=helpers.label_formatter) helpers.format_cbar(cbar) helpers.add_description(fig, ax, align='br', strings=[helpers.dataSetStr, helpers.seedCutStr]) helpers.add_labels(fig, ax, xlabel=r'$E_T^\mathrm{{{}}}$'.format(label), ylabel='offline jet\'s number of subjets (cut at 6)', title=label) ax.set_xlim((0.0, 100.0)) ax.set_ylim((1.0, 6.0)) helpers.add_grid(fig, ax) helpers.to_file(fig, ax, 'plots/gTowers/{}_{}.png'.format(filename_id, label.replace(' ', '_'))) pl.close(fig) fig, ax = pl.subplots(figsize=helpers.figsize) counts, edges_x, edges_y, im = ax.hist2d(datapts/data['tJet.et'][valid_gJets], data['oJet.nsj'][valid_gJets], bins=(np.arange(0., 1., 0.05), np.arange(1, 7, 1)), norm=LogNorm(), alpha=0.75, cmap=helpers.cmap, weights=data['weight'][np.where(tJet_exists)]) points_y, mean_x, err_x = helpers.profile_x(edges_y, data['oJet.nsj'][valid_gJets], datapts/data['tJet.et'][valid_gJets]) profiles_scaled[label.replace(' ', '_')] = {'x': mean_x, 'y': points_y, 'e': err_x} ax.scatter(mean_x, points_y, s=80, facecolor='w', edgecolor='k', marker='o', linewidth=2)