import IMP import IMP.restrainer import IMP.atom import sys output = (sys.argv[1]) IMP.set_log_level(IMP.VERBOSE) # Create restrainer object restrainer = IMP.restrainer.Main() # Add representation, restraint, optimization and display to restrainer rep = restrainer.add_representation('input/repr_cog_Tags_rdm_' + output + '.xml') rsr = restrainer.add_restraint('input/restraint_cog_Tags.xml') opt = restrainer.add_optimization('input/optimization.xml') disp = restrainer.add_display('input/displ_cog_Tags.xml') ###=======================================================================### # At this point all data from XML files have been placed into the model. # Now it is possible to perform various operations on the IMP model. ###=======================================================================### # Save the initial state in Chimera format restrainer.log.write(output + '/initial.py') # Perform optimization restrainer.optimize() # Save the optimized state in Chimera format restrainer.log.write(output + '/optimized.py') score = restrainer.get_model().evaluate(False) print "Final score: " + str(score)
#-- File: nup84_complex_in_bead_representation.py --# import IMP import IMP.restrainer import IMP.atom IMP.set_log_level(IMP.VERBOSE) # Create restrainer object restrainer = IMP.restrainer.Main() # Add representation, restraint, optimization and display to restrainer rep = restrainer.add_representation('input/repr_exocyst_rdm.xml') rsr = restrainer.add_restraint('input/restraint_exocyst.xml') opt = restrainer.add_optimization('input/optimization.xml') disp = restrainer.add_display('input/displ_exocyst.xml') ###=======================================================================### # At this point all data from XML files have been placed into the model. # Now it is possible to perform various operations on the IMP model. ###=======================================================================### # Save the initial state in Chimera format restrainer.log.write('output/initial.py') # Perform optimization restrainer.optimize() # Save the optimized state in Chimera format restrainer.log.write('output/optimized.py') score = restrainer.get_model().evaluate(False) print "Final score: "+str(score)
#-- File: nup84_complex_in_bead_representation.py --# import IMP import IMP.restrainer IMP.base.set_log_level(IMP.base.VERBOSE) # Create restrainer object restrainer = IMP.restrainer.Main() # Add representation, restraint, optimization and display to restrainer rep = restrainer.add_representation(IMP.restrainer.get_example_path('input/nup84_representation.xml')) rsr = restrainer.add_restraint(IMP.restrainer.get_example_path('input/nup84_restraint.xml')) opt = restrainer.add_optimization(IMP.restrainer.get_example_path('input/nup84_optimization.xml')) disp = restrainer.add_display(IMP.restrainer.get_example_path('input/nup84_display.xml')) ###=======================================================================### # At this point all data from XML files have been placed into the model. # Now it is possible to perform various operations on the IMP model. ###=======================================================================### # Save the initial state in Chimera format restrainer.log.write('initial.py') # Perform optimization restrainer.optimize() # Save the optimized state in Chimera format restrainer.log.write('optimized.py')
rmf.set_description("Simulate nup84.\n") model = restrainer.get_model() root_hierarchy = rep.get_root_imp_hierarchy() IMP.rmf.add_hierarchy(rmf, root_hierarchy) IMP.rmf.add_restraints(rmf, model.get_restraints()) IMP.rmf.save_frame(rmf, 0) os= IMP.rmf.SaveOptimizerState(rmf) os.update_always("initial conformation") restrainer.log = os #END ADDED PART opt = restrainer.add_optimization(IMP.restrainer.get_example_path('input/nup84_optimization.xml')) disp = restrainer.add_display(IMP.restrainer.get_example_path('input/nup84_display.xml'), 'some_log_name') ###=======================================================================### # At this point all data from XML files have been placed into the model. # Now it is possible to perform various operations on the IMP model. ###=======================================================================### # Save the initial state in Chimera format # restrainer.log.write('initial.py') # Perform optimization restrainer.optimize() # Save the optimized state in Chimera format # restrainer.log.write('optimized.py')