Plot Beta

The following example shows how to use pymad to plot the beta functions for the LHC for injection and collision optics:

from matplotlib import pyplot
from cern import pymad

def plot_beta(model, postfix=''):
    # Run twiss on the model, optionally give name of file
    # where tfs table is stored
    result, summary = model.twiss(seqname='lhcb1',
                                  columns=['name', 's', 'betx', 'bety'],
                                  file='lhcb1' + postfix + '.tfs')

    pyplot.figure()
    # do something with the result (note, madx is still waiting!):
    pyplot.xlabel('dist. from IP1')
    pyplot.ylabel(r'$\beta$')
    pyplot.plot(result.s, result.betx, label=r'$\beta_x$')
    pyplot.plot(result.s, result.bety, label=r'$\beta_y$')
    pyplot.savefig('beta' + postfix + '.eps')


# choose the mode
mode = 'jpymad'
#mode = 'cpymad'

mdefname = 'lhc'
opticname = 'injection'

#
# Here it starts
#
# create the PyMad Service
pms = pymad.init(mode)

# print the name of all model definitions
print pms.mdefnames

# alternatively use convenience function
#pymad.ls_mdefs()

# get one model-definition
model = pms.create_model(mdefname)

# alternatively: create the model by name and get the model definition afterwards:
# model = pms.create_model(mdefname)
# mdef = model.mdef

# list the available (running) models
pymad.ls_models()

# print a list of available sequences:
print mdef.seqnames

plot_beta(model, '_inj')

# list the available optics and set a new one
print mdef.opticnames
model.set_optic(opticname)

plot_beta(model, '_coll')

# remove the model from the service:
pms.delete_model(model)

# and do a cleanup
pymad.cleanup()