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Getting a very fast and approximate model

To get an approximate model very quickly (to get a rough idea of what it looks like, or to confirm that the alignment is reasonable) call the automodel.very_fast() method before automodel.make(). This uses only a very limited amount of variable target function optimization with conjugate gradients, and thus is roughly 3 times faster than the default procedure.

Note that no randomization of the starting structure is done in this case, so only a single model can be produced.

This example also demonstrates the use of the assess_methods keyword, to request model assessment. In this case the GA341 method is requested. See section 4.1.1.

Example: examples/automodel/model-fast.py

      # Very fast comparative modeling by the automodel class
      from modeller import *
      from modeller.automodel import *    # Load the automodel class
      #from modeller import soap_protein_od

      log.verbose()
      env = environ()
      # directories for input atom files
      env.io.atom_files_directory = ['.', '../atom_files']

      a = automodel(env,
                    alnfile='alignment.ali',      # alignment filename
                    knowns='5fd1',                # codes of the templates
                    sequence='1fdx',              # code of the target
                    assess_methods=assess.GA341)  # request GA341 model assessment
      #             assess_methods=(assess.GA341, assess.DOPE))  # GA341 and DOPE
      #             assess_methods=soap_protein_od.Scorer())  # assess with SOAP

      a.very_fast()                       # prepare for extremely fast optimization

      a.starting_model = 2
      a.ending_model = 2
      a.final_malign3d = True

      a.make()                            # make the comparative model