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
