def main(job_id, params): # Logging print "Call to main function (#{})".format(job_id) print " Parameters: {}".format(params) # Create temporary patch dictionary jobname = 'patch.{:08d}'.format(job_id) filename = os.path.realpath('patches/{}.json'.format(jobname)) patch = create_patch(params) # Adversarial-specific change lr_ratio = patch['combined']['model'].pop('lr_ratio') if lr_ratio < 0: lr_ratio = np.power(10., lr_ratio) pass patch['combined']['compile']['loss_weights'] = [lr_ratio, 1.0] # -- Fixed settings for field in ['fit', 'model']: if field not in patch['combined']: patch['combined'][field] = dict() pass pass patch['combined']['pretrain'] = 20 patch['combined']['fit']['epochs'] = 200 patch['combined']['fit']['batch_size'] = 8192 patch['combined']['model']['lambda_reg'] = 10. # Save patch to file save_patch(patch, filename) # Set arguments args = parse_args([ '--optimise-adversarial', '--patch', filename, '--jobname', 'combined-' + jobname, '--gpu', '--devices', '7', '--folds', '3', '--tensorboard' ], adversarial=True) # Call main script (in the correct directory) with cd(PROJECTDIR): result = train.main(args) pass # Ensure correct type, otherwise Spearmint does not accept value result = float(result) return result
def main(job_id, params): # Logging print "Call to main function (#{})".format(job_id) print " Parameters: {}".format(params) # Create temporary patch file jobname = 'patch.{:08d}'.format(job_id) filename = os.path.realpath('patches/{}.json'.format(jobname)) patch = create_patch(params) # -- Fixed settings if 'fit' not in patch['classifier']: patch['classifier']['fit'] = dict() pass patch['classifier']['fit']['epochs'] = 50 patch['classifier']['fit']['batch_size'] = 8192 save_patch(patch, filename) # Set arguments args = parse_args([ '--optimise-classifier', '--patch', filename, '--jobname', 'classifier-' + jobname, '--gpu', '--devices', '7', '--folds', '3', '--tensorboard' ], adversarial=True) # Call main script (in the correct directory) with cd(PROJECTDIR): result = train.main(args) pass # Ensure correct type, otherwise Spearmint does not accept value result = float(result) return result
# Decorations c.text(["#sqrt{s} = 13 TeV"], qualifier=QUALIFIER, ATLAS=False) c.legend() c.ylim(binsy[0], binsy[-1]) c.xlabel("Large-#it{R} jet " + latex('rhoDDT', ROOT=True)) if variable == VAR_TAU21: c.ylabel("Large-#it{R} jet " + latex('#tau_{21}', ROOT=True)) #changed these to latex formatting elif variable == VAR_N2: c.ylabel("Large-#it{R} jet " + latex('N_{2}', ROOT=True)) elif variable == VAR_DECDEEP: c.ylabel("Large-#it{R} jet " + latex('dec_deepWvsQCD', ROOT=True)) elif variable == VAR_DEEP: c.ylabel("Large-#it{R} jet " + latex('deepWvsQCD', ROOT=True)) # Save mkdir('figures/ddt') c.save('figures/ddt/ddt_{}_2d.pdf'.format(variable)) pass return # Main function call if __name__ == '__main__': # Parse command-line arguments args = parse_args() # Call main function main(args) pass
c.text(TEXT + [ "Multijets, training dataset", "Cut on {:s} at #varepsilon_{{sig}}^{{rel}} = 50%".format( latex(var, ROOT=True)), "p_{{T}} #in [{:.0f}, {:.0f}] GeV".format(*pt_bin) ], qualifier='Simulation Internal') c.legend(width=0.25) c.xlabel("Large-#it{R} jet mass [GeV]") c.ylabel("Fraction of jets") c.pad(1).ylabel('KL(P #parallel M)') c.pad(2).ylabel('KL(F #parallel M)') c.pad(3).ylabel('JSD(P #parallel F)') # Save c.save('figures/massdecorrelationmetric_{:s}__pT{:.0f}_{:.0f}GeV.pdf'. format(var, *pt_bin)) pass return 0 # Main function call if __name__ == '__main__': # Parse command-line arguments args = parse_args(backend=True, plots=True) # Call main function main(args) pass
c.latex("m < 300 GeV", -2.5, BOUNDS[1].Eval(-2.5) - 30, align=23, angle=-57, textsize=13, textcolor=ROOT.kGray + 3) # Decorations c.text(qualifier=QUALIFIER, ymax=0.92, xmin=0.15) c.text(["#sqrt{s} = 13 TeV", "Multijets"], ATLAS=False, textcolor=ROOT.kWhite) # Save mkdir('figures/knn/') c.save('figures/knn/knn_{}_{:s}_{:.0f}.pdf'.format( 'fit' if fit else 'profile', VAR, EFF)) pass # Main function call if __name__ == '__main__': # Parse command-line arguments args = parse_args() # (adversarial=True) # Call main function main(args) pass