#print Twiss parameters of transformed distribution
print("Transformed phase space (x,x\') covariance matrix\n",
bunch.covariance_matrix(['x', 'x\'']))
print('Transformed RMS beta ', bunch.get_beta(['x']), 'mm')
print('Transformed RMS alpha ', bunch.get_alpha(['x']))
print('Transformed RMS gamma ', bunch.get_gamma(['x']), 'mm^{-1}')
print('Transformed RMS emittance', bunch.get_emittance(['x']), 'mm')
#plot x x' and amplitude distribution after - the point being that the x x' distribution is radically different,
#but the amplitude distribution is the same; what one would expect from an ideal transfer line
bunch.root_scatter_graph('x',
'x\'',
'MeV/c',
'MeV/c',
include_weightless=False)
bunch.root_histogram('amplitude x', 'mm')
#translate to z=0
print('Mean z at start', bunch.mean(['z'])['z'])
bunch.translate({'z': -bunch.mean(['z'])['z']})
print('Mean z at end ', bunch.mean(['z'])['z'])
#write out as an ICOOL for003 file
bunch.hit_write_builtin('icool_for003', 'for003_test.dat',
'for003 file generated by XBOA')
print('Press <return> key to finish')
input()
Bunch.clear_global_weights()
