output.addParameter('dpp_rms', lambda: get_dpp(bunch, bunchtwissanalysis))
output.addParameter('beta_x', lambda: bunchtwissanalysis.getBeta(0))
output.addParameter('beta_y', lambda: bunchtwissanalysis.getBeta(1))
output.addParameter('alpha_x', lambda: bunchtwissanalysis.getAlpha(0))
output.addParameter('alpha_y', lambda: bunchtwissanalysis.getAlpha(1))
output.addParameter('mean_x', lambda: bunchtwissanalysis.getAverage(0))
output.addParameter('mean_xp', lambda: bunchtwissanalysis.getAverage(1))
output.addParameter('mean_y', lambda: bunchtwissanalysis.getAverage(2))
output.addParameter('mean_yp', lambda: bunchtwissanalysis.getAverage(3))
output.addParameter('mean_z', lambda: bunchtwissanalysis.getAverage(4))
output.addParameter('mean_dE', lambda: bunchtwissanalysis.getAverage(5))
output.addParameter('eff_beta_x', lambda: bunchtwissanalysis.getEffectiveBeta(0))
output.addParameter('eff_beta_y', lambda: bunchtwissanalysis.getEffectiveBeta(1))
output.addParameter('eff_epsn_x', lambda: bunchtwissanalysis.getEffectiveEmittance(0))
output.addParameter('eff_epsn_y', lambda: bunchtwissanalysis.getEffectiveEmittance(1))
output.addParameter('eff_alpha_x', lambda: bunchtwissanalysis.getEffectiveAlpha(0))
output.addParameter('eff_alpha_y', lambda: bunchtwissanalysis.getEffectiveAlpha(1))
output.addParameter('gamma', lambda: bunch.getSyncParticle().gamma())
# Pre Track Bunch Twiss Analysis & Add BunchGather outputs
#-----------------------------------------------------------------------
print '\n\t\tStart tracking on MPI process: ', rank
turn = -1
bunchtwissanalysis.analyzeBunch(bunch)
moments = BunchGather(bunch, turn, p) # Calculate bunch moments and kurtosis
# Add moments and kurtosis
output.addParameter('sig_x', lambda: moments['Sig_x'])
output.addParameter('sig_xp', lambda: moments['Sig_xp'])
output.addParameter('sig_y', lambda: moments['Sig_y'])
output.addParameter('mean_x', lambda: bunchtwissanalysis.getAverage(0))
output.addParameter('mean_xp', lambda: bunchtwissanalysis.getAverage(1))
output.addParameter('mean_y', lambda: bunchtwissanalysis.getAverage(2))
output.addParameter('mean_yp', lambda: bunchtwissanalysis.getAverage(3))
output.addParameter('mean_z', lambda: bunchtwissanalysis.getAverage(4))
output.addParameter('mean_dE', lambda: bunchtwissanalysis.getAverage(5))
output.addParameter('eff_beta_x',
lambda: bunchtwissanalysis.getEffectiveBeta(0))
output.addParameter('eff_beta_y',
lambda: bunchtwissanalysis.getEffectiveBeta(1))
output.addParameter('eff_epsn_x',
lambda: bunchtwissanalysis.getEffectiveEmittance(0))
output.addParameter('eff_epsn_y',
lambda: bunchtwissanalysis.getEffectiveEmittance(1))
output.addParameter('eff_alpha_x',
lambda: bunchtwissanalysis.getEffectiveAlpha(0))
output.addParameter('eff_alpha_y',
lambda: bunchtwissanalysis.getEffectiveAlpha(1))
output.addParameter('gamma', lambda: bunch.getSyncParticle().gamma())
# Pre Track Bunch Twiss Analysis & Add BunchGather outputs
#-----------------------------------------------------------------------
print '\n\t\tStart tracking on MPI process: ', rank
turn = -1
bunchtwissanalysis.analyzeBunch(bunch)
moments = BunchGather(bunch, turn, p) # Calculate bunch moments and kurtosis
# Add moments and kurtosis
output.addParameter('sig_x', lambda: moments['Sig_x'])
output.addParameter('sig_xp', lambda: moments['Sig_xp'])
output.addParameter('sig_y', lambda: moments['Sig_y'])