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)