The sample script which demonstrates the optimisation of all model-free models from m0 to m9 of individual spins is model_free/mf_multimodel.py. The important parts of the script are:
# Set the data pipe names (also the names of preset model-free models).
pipes = ['m0', 'm1', 'm2', 'm3', 'm4', 'm5', 'm6', 'm7', 'm8', 'm9']
# Loop over the pipes.
for name in pipes:
# Create the data pipe.
pipe.create(name, 'mf')
# Set up the 15N spins.
sequence.read('noe.500.out', res_num_col=1)
spin.name('N')
spin.element(element='N', spin_id='@N')
spin.isotope('15N', spin_id='@N')
# Load a PDB file.
structure.read_pdb('example.pdb')
# Load the relaxation data.
relax_data.read(ri_id='R1_600', ri_type='R1', frq=600.0*1e6, file='r1.600.out', res_num_col=1, data_col=3, error_col=4)
relax_data.read(ri_id='R2_600', ri_type='R2', frq=600.0*1e6, file='r2.600.out', res_num_col=1, data_col=3, error_col=4)
relax_data.read(ri_id='NOE_600', ri_type='NOE', frq=600.0*1e6, file='noe.600.out', res_num_col=1, data_col=3, error_col=4)
relax_data.read(ri_id='R1_500', ri_type='R1', frq=500.0*1e6, file='r1.500.out', res_num_col=1, data_col=3, error_col=4)
relax_data.read(ri_id='R2_500', ri_type='R2', frq=500.0*1e6, file='r2.500.out', res_num_col=1, data_col=3, error_col=4)
relax_data.read(ri_id='NOE_500', ri_type='NOE', frq=500.0*1e6, file='noe.500.out', res_num_col=1, data_col=3, error_col=4)
# Set up the diffusion tensor.
diffusion_tensor.init(1e-8, fixed=True)
# Generate the 1H spins for the magnetic dipole-dipole relaxation interaction.
sequence.attach_protons()
# Define the magnetic dipole-dipole relaxation interaction.
interatom.define(spin_id1='@N', spin_id2='@H', direct_bond=True)
interatom.set_dist(spin_id1='@N', spin_id2='@H', ave_dist=1.02 * 1e-10)
structure.get_pos('@N')
structure.get_pos('@H')
interatom.unit_vectors()
# Define the chemical shift relaxation interaction.
value.set(-172 * 1e-6, 'csa', spin_id='@N')
# Select the model-free model.
model_free.select_model(model=name)
# Minimise.
minimise.grid_search(inc=11)
minimise.execute('newton')
# Write the results.
results.write(file='results', force=True)
# Save the program state.
state.save('save', force=True)