def run(args):
    log = sys.stdout
    if (len(args) == 0): args = ["--help"]
    command_line = (option_parser(usage="%s [options] pdb_file" %
                                  libtbx.env.dispatcher_name).option(
                                      None,
                                      "--buffer_layer",
                                      action="store",
                                      type="float",
                                      default=5)).process(args=args, nargs=1)
    pdb_inp = iotbx.pdb.input(file_name=command_line.args[0])
    model = mmtbx.model.manager(model_input=pdb_inp)
    box = uctbx.non_crystallographic_unit_cell_with_the_sites_in_its_center(
        sites_cart=model.get_sites_cart(),
        buffer_layer=command_line.options.buffer_layer)
    model.set_sites_cart(box.sites_cart)
    # Bad hack, never repeat. In fact, all the boxing functionality should
    # go into mmtbx.model.manager
    model._crystal_symmetry = box.crystal_symmetry()
    print('REMARK %s --buffer-layer=%.6g %s' %
          (libtbx.env.dispatcher_name, command_line.options.buffer_layer,
           show_string(command_line.args[0])),
          file=log)
    print('REMARK %s' % date_and_time(), file=log)
    print(model.model_as_pdb(), file=log)
def run(args):
    log = sys.stdout
    if (len(args) == 0): args = ["--help"]
    command_line = (option_parser(usage="%s [options] pdb_file" %
                                  libtbx.env.dispatcher_name).option(
                                      None,
                                      "--buffer_layer",
                                      action="store",
                                      type="float",
                                      default=5)).process(args=args, nargs=1)
    pdb_inp = iotbx.pdb.input(file_name=command_line.args[0])
    atoms = pdb_inp.atoms()
    box = uctbx.non_crystallographic_unit_cell_with_the_sites_in_its_center(
        sites_cart=atoms.extract_xyz(),
        buffer_layer=command_line.options.buffer_layer)
    atoms.set_xyz(new_xyz=box.sites_cart)
    print >> log, 'REMARK %s --buffer-layer=%.6g %s' % (
        libtbx.env.dispatcher_name, command_line.options.buffer_layer,
        show_string(command_line.args[0]))
    print >> log, 'REMARK %s' % date_and_time()
    iotbx.pdb.write_whole_pdb_file(
        output_file=log,
        pdb_hierarchy=pdb_inp.construct_hierarchy(),
        crystal_symmetry=box.crystal_symmetry(),
        ss_annotation=pdb_inp.extract_secondary_structure(log=null_out()))
def run(args):
  if (len(args) == 0): args = ["--help"]
  from libtbx.option_parser import option_parser
  import libtbx.load_env
  command_line = (option_parser(
    usage="%s [options] pdb_file" % libtbx.env.dispatcher_name)
    .option(None, "--buffer_layer",
      action="store",
      type="float",
      default=5)
  ).process(args=args, nargs=1)
  import iotbx.pdb
  pdb_inp = iotbx.pdb.input(file_name=command_line.args[0])
  atoms = pdb_inp.atoms()
  from cctbx import uctbx
  box = uctbx.non_crystallographic_unit_cell_with_the_sites_in_its_center(
    sites_cart=atoms.extract_xyz(),
    buffer_layer=command_line.options.buffer_layer)
  atoms.set_xyz(new_xyz=box.sites_cart)
  from libtbx.str_utils import show_string
  print 'REMARK %s --buffer-layer=%.6g %s' % (
    libtbx.env.dispatcher_name,
    command_line.options.buffer_layer,
    show_string(command_line.args[0]))
  from libtbx.utils import date_and_time
  print 'REMARK %s' % date_and_time()
  print iotbx.pdb.format_cryst1_record(crystal_symmetry=box.crystal_symmetry())
  print pdb_inp.construct_hierarchy().as_pdb_string(append_end=True),
Exemple #4
0
 def write_geo(label, geo, geo_file_name):
     from libtbx.utils import date_and_time
     header = "# %sgeometry restraints for file:\n" % label
     header += "#   %s\n# %s\n" % (show_string(pdb_file_name),
                                   date_and_time())
     geo.write_geo_file(sites_cart=sites_cart,
                        site_labels=site_labels,
                        file_name=geo_file_name,
                        header=header)
 def write_geo(label, geo, geo_file_name):
   from libtbx.utils import date_and_time
   header = "# %sgeometry restraints for file:\n" % label
   header += "#   %s\n# %s\n" % (show_string(pdb_file_name),
       date_and_time())
   geo.write_geo_file(
       sites_cart=sites_cart,
       site_labels=site_labels,
       file_name=geo_file_name,
       header=header)
Exemple #6
0
 def __init__(self,
              params,
              coeffs,
              atom_selection_manager=None,
              xray_structure=None):
     adopt_init_args(self, locals())
     fft_map = coeffs.fft_map(
         resolution_factor=self.params.grid_resolution_factor)
     if (self.params.scale == "volume"): fft_map.apply_volume_scaling()
     elif (self.params.scale == "sigma"): fft_map.apply_sigma_scaling()
     else: raise RuntimeError
     title_lines = [
         "REMARK file: %s" %
         show_string(os.path.basename(self.params.file_name))
     ]
     title_lines.append("REMARK directory: %s" %
                        show_string(os.path.dirname(self.params.file_name)))
     title_lines.append("REMARK %s" % date_and_time())
     assert self.params.region in ["selection", "cell"]
     if (self.params.region == "selection" and xray_structure is not None):
         map_iselection = None
         if atom_selection_manager is not None:
             map_iselection = self.atom_iselection()
         frac_min, frac_max = self.box_around_selection(
             iselection=map_iselection,
             buffer=self.params.atom_selection_buffer)
         n_real = fft_map.n_real()
         gridding_first = [ifloor(f * n) for f, n in zip(frac_min, n_real)]
         gridding_last = [iceil(f * n) for f, n in zip(frac_max, n_real)]
         title_lines.append('REMARK map around selection')
         title_lines.append('REMARK   atom_selection=%s' %
                            show_string(self.params.atom_selection))
         title_lines.append('REMARK   atom_selection_buffer=%.6g' %
                            self.params.atom_selection_buffer)
         if (map_iselection is None):
             sel_size = self.xray_structure.scatterers().size()
         else:
             sel_size = map_iselection.size()
         title_lines.append('REMARK   number of atoms selected: %d' %
                            sel_size)
     else:
         gridding_first = None
         gridding_last = None
         title_lines.append("REMARK map covering the unit cell")
     if params.format == "xplor":
         fft_map.as_xplor_map(file_name=self.params.file_name,
                              title_lines=title_lines,
                              gridding_first=gridding_first,
                              gridding_last=gridding_last)
     else:
         fft_map.as_ccp4_map(file_name=self.params.file_name,
                             gridding_first=gridding_first,
                             gridding_last=gridding_last,
                             labels=title_lines)
Exemple #7
0
 def __init__(self, params, coeffs, atom_selection_manager=None,
              xray_structure=None):
   adopt_init_args(self, locals())
   fft_map = coeffs.fft_map(resolution_factor =
     self.params.grid_resolution_factor)
   if(self.params.scale == "volume"): fft_map.apply_volume_scaling()
   elif(self.params.scale == "sigma"): fft_map.apply_sigma_scaling()
   else: raise RuntimeError
   title_lines=["REMARK file: %s" %
     show_string(os.path.basename(self.params.file_name))]
   title_lines.append("REMARK directory: %s" %
     show_string(os.path.dirname(self.params.file_name)))
   title_lines.append("REMARK %s" % date_and_time())
   assert self.params.region in ["selection", "cell"]
   if(self.params.region == "selection" and xray_structure is not None) :
     map_iselection = None
     if atom_selection_manager is not None :
       map_iselection = self.atom_iselection()
     frac_min, frac_max = self.box_around_selection(
       iselection = map_iselection,
       buffer     = self.params.atom_selection_buffer)
     n_real = fft_map.n_real()
     gridding_first=[ifloor(f*n) for f,n in zip(frac_min,n_real)]
     gridding_last=[iceil(f*n) for f,n in zip(frac_max,n_real)]
     title_lines.append('REMARK map around selection')
     title_lines.append('REMARK   atom_selection=%s' %
       show_string(self.params.atom_selection))
     title_lines.append('REMARK   atom_selection_buffer=%.6g' %
       self.params.atom_selection_buffer)
     if(map_iselection is None):
       sel_size = self.xray_structure.scatterers().size()
     else:
       sel_size = map_iselection.size()
     title_lines.append('REMARK   number of atoms selected: %d' % sel_size)
   else:
     gridding_first = None
     gridding_last = None
     title_lines.append("REMARK map covering the unit cell")
   if params.format == "xplor" :
     fft_map.as_xplor_map(
       file_name      = self.params.file_name,
       title_lines    = title_lines,
       gridding_first = gridding_first,
       gridding_last  = gridding_last)
   else :
     fft_map.as_ccp4_map(
       file_name      = self.params.file_name,
       gridding_first = gridding_first,
       gridding_last  = gridding_last,
       labels=title_lines)
Exemple #8
0
 def write_mtz_file(self, file_name, mtz_history_buffer = None,
     r_free_flags=None):
   from cctbx.array_family import flex
   if(self.mtz_dataset is not None):
     if (r_free_flags is not None) :
       self.mtz_dataset.add_miller_array(r_free_flags,
         column_root_label="FreeR_flag")
     if(mtz_history_buffer is None):
       mtz_history_buffer = flex.std_string()
     mtz_history_buffer.append(date_and_time())
     mtz_history_buffer.append("> file name: %s" % os.path.basename(file_name))
     mtz_object = self.mtz_dataset.mtz_object()
     mtz_object.add_history(mtz_history_buffer)
     mtz_object.write(file_name = file_name)
     return True
   return False
def run(
      args,
      command_name="phenix.reflection_file_converter",
      simply_return_all_miller_arrays=False):
  command_line = (option_parser(
    usage="%s [options] reflection_file ..." % command_name,
    description="Example: %s w1.sca --mtz ." % command_name)
    .enable_symmetry_comprehensive()
    .option(None, "--weak_symmetry",
      action="store_true",
      default=False,
      help="symmetry on command line is weaker than symmetry found in files")
    .enable_resolutions()
    .option(None, "--label",
      action="store",
      type="string",
      help="Substring of reflection data label or number",
      metavar="STRING")
    .option(None, "--non_anomalous",
      action="store_true",
      default=False,
      help="Averages Bijvoet mates to obtain a non-anomalous array")
    .option(None, "--r_free_label",
      action="store",
      type="string",
      help="Substring of reflection data label or number",
      metavar="STRING")
    .option(None, "--r_free_test_flag_value",
      action="store",
      type="int",
      help="Value in R-free array indicating assignment to free set.",
      metavar="FLOAT")
    .option(None, "--generate_r_free_flags",
      action="store_true",
      default=False,
      help="Generates a new array of random R-free flags"
           " (MTZ and CNS output only).")
    .option(None, "--use_lattice_symmetry_in_r_free_flag_generation",
      dest="use_lattice_symmetry_in_r_free_flag_generation",
      action="store_true",
      default=True,
      help="group twin/pseudo symmetry related reflections together"
           " in r-free set (this is the default).")
    .option(None, "--no_lattice_symmetry_in_r_free_flag_generation",
      dest="use_lattice_symmetry_in_r_free_flag_generation",
      action="store_false",
      help="opposite of --use-lattice-symmetry-in-r-free-flag-generation")
    .option(None, "--r_free_flags_fraction",
      action="store",
      default=0.10,
      type="float",
      help="Target fraction free/work reflections (default: 0.10).",
      metavar="FLOAT")
    .option(None, "--r_free_flags_max_free",
      action="store",
      default=2000,
      type="int",
      help="Maximum number of free reflections (default: 2000).",
      metavar="INT")
    .option(None, "--r_free_flags_format",
      choices=("cns", "ccp4", "shelx"),
      default="cns",
      help="Convention for generating R-free flags",
      metavar="cns|ccp4")
    .option(None, "--output_r_free_label",
      action="store",
      type="string",
      help="Label for newly generated R-free flags (defaults to R-free-flags)",
      default="R-free-flags",
      metavar="STRING")
    .option(None, "--random_seed",
      action="store",
      type="int",
      help="Seed for random number generator (affects generation of"
           " R-free flags).",
      metavar="INT")
    .option(None, "--change_of_basis",
      action="store",
      type="string",
      help="Change-of-basis operator: h,k,l or x,y,z"
           " or to_reference_setting, to_primitive_setting, to_niggli_cell,"
           " to_inverse_hand",
      metavar="STRING")
    .option(None, "--eliminate_invalid_indices",
      action="store_true",
      default=False,
      help="Remove indices which are invalid given the change of basis desired")
    .option(None, "--expand_to_p1",
      action="store_true",
      default=False,
      help="Generates all symmetrically equivalent reflections."
           " The space group symmetry is reset to P1."
           " May be used in combination with --change_to_space_group to"
           " lower the symmetry.")
    .option(None, "--change_to_space_group",
      action="store",
      type="string",
      help="Changes the space group and merges equivalent reflections"
           " if necessary",
      metavar="SYMBOL|NUMBER")
    .option(None, "--write_mtz_amplitudes",
      action="store_true",
      default=False,
      help="Converts intensities to amplitudes before writing MTZ format;"
           " requires --mtz_root_label")
    .option(None, "--write_mtz_intensities",
      action="store_true",
      default=False,
      help="Converts amplitudes to intensities before writing MTZ format;"
           " requires --mtz_root_label")
    .option(None,"--remove_negatives",
      action="store_true",
      default=False,
      help="Remove negative intensities or amplitudes from the data set" )
    .option(None,"--massage_intensities",
      action="store_true",
      default=False,
      help="'Treat' negative intensities to get a positive amplitude."
           " |Fnew| = sqrt((Io+sqrt(Io**2 +2sigma**2))/2.0). Requires"
           " intensities as input and the flags --mtz,"
           " --write_mtz_amplitudes and --mtz_root_label.")
    .option(None, "--scale_max",
      action="store",
      type="float",
      help="Scales data such that the maximum is equal to the given value",
      metavar="FLOAT")
    .option(None, "--scale_factor",
      action="store",
      type="float",
      help="Multiplies data with the given factor",
      metavar="FLOAT")
    .option(None, "--sca",
      action="store",
      type="string",
      help=
        "write data to Scalepack FILE ('--sca .' copies name of input file)",
      metavar="FILE")
    .option(None, "--mtz",
      action="store",
      type="string",
      help="write data to MTZ FILE ('--mtz .' copies name of input file)",
      metavar="FILE")
    .option(None, "--mtz_root_label",
      action="store",
      type="string",
      help="Root label for MTZ file (e.g. Fobs)",
      metavar="STRING")
    .option(None, "--cns",
      action="store",
      type="string",
      help="write data to CNS FILE ('--cns .' copies name of input file)",
      metavar="FILE")
    .option(None, "--shelx",
      action="store",
      type="string",
      help="write data to SHELX FILE ('--shelx .' copies name of input file)",
      metavar="FILE")
  ).process(args=args)
  co = command_line.options
  if (co.random_seed is not None):
    random.seed(co.random_seed)
    flex.set_random_seed(value=co.random_seed)
  if (    co.write_mtz_amplitudes
      and co.write_mtz_intensities):
    print
    print "--write_mtz_amplitudes and --write_mtz_intensities" \
          " are mutually exclusive."
    print
    return None
  if (   co.write_mtz_amplitudes
      or co.write_mtz_intensities):
    if (co.mtz_root_label is None):
      print
      print "--write_mtz_amplitudes and --write_mtz_intensities" \
            " require --mtz_root_label."
      print
      return None
  if (    co.scale_max is not None
      and co.scale_factor is not None):
    print
    print "--scale_max and --scale_factor are mutually exclusive."
    print
    return None
  if (len(command_line.args) == 0):
    command_line.parser.show_help()
    return None
  all_miller_arrays = reflection_file_reader.collect_arrays(
    file_names=command_line.args,
    crystal_symmetry=None,
    force_symmetry=False,
    merge_equivalents=False,
    discard_arrays=False,
    verbose=1)
  if (simply_return_all_miller_arrays):
    return all_miller_arrays
  if (len(all_miller_arrays) == 0):
    print
    print "No reflection data found in input file%s." % (
      plural_s(len(command_line.args))[1])
    print
    return None
  label_table = reflection_file_utils.label_table(
    miller_arrays=all_miller_arrays)
  selected_array = label_table.select_array(
    label=co.label, command_line_switch="--label")
  if (selected_array is None): return None
  r_free_flags = None
  r_free_info = None
  if (co.r_free_label is not None):
    r_free_flags = label_table.match_data_label(
      label=co.r_free_label,
      command_line_switch="--r_free_label")
    if (r_free_flags is None):
      return None
    r_free_info = str(r_free_flags.info())
    if (not r_free_flags.is_bool_array()):
      test_flag_value = reflection_file_utils.get_r_free_flags_scores(
        miller_arrays=[r_free_flags],
        test_flag_value=co.r_free_test_flag_value).test_flag_values[0]
      if (test_flag_value is None):
        if (co.r_free_test_flag_value is None):
          raise Sorry(
            "Cannot automatically determine r_free_test_flag_value."
            " Please use --r_free_test_flag_value to specify a value.")
        else:
          raise Sorry("Invalid --r_free_test_flag_value.")
      r_free_flags = r_free_flags.customized_copy(
        data=(r_free_flags.data() == test_flag_value))
  print "Selected data:"
  print " ", selected_array.info()
  print "  Observation type:", selected_array.observation_type()
  print
  if (r_free_info is not None):
    print "R-free flags:"
    print " ", r_free_info
    print
  processed_array = selected_array.customized_copy(
    crystal_symmetry=selected_array.join_symmetry(
      other_symmetry=command_line.symmetry,
      force=not co.weak_symmetry)).set_observation_type(
        selected_array.observation_type())
  if (r_free_flags is not None):
    r_free_flags = r_free_flags.customized_copy(
      crystal_symmetry=processed_array)
  print "Input crystal symmetry:"
  crystal.symmetry.show_summary(processed_array, prefix="  ")
  print
  if (processed_array.unit_cell() is None):
    command_line.parser.show_help()
    print "Unit cell parameters unknown. Please use --symmetry or --unit_cell."
    print
    return None
  if (processed_array.space_group_info() is None):
    command_line.parser.show_help()
    print "Space group unknown. Please use --symmetry or --space_group."
    print
    return None
  if (r_free_flags is not None):
    r_free_flags = r_free_flags.customized_copy(
      crystal_symmetry=processed_array)
  if (co.change_of_basis is not None):
    processed_array, cb_op = processed_array.apply_change_of_basis(
      change_of_basis=co.change_of_basis,
      eliminate_invalid_indices=co.eliminate_invalid_indices)
    if (r_free_flags is not None):
      r_free_flags = r_free_flags.change_basis(cb_op=cb_op)
  if (not processed_array.is_unique_set_under_symmetry()):
    print "Merging symmetry-equivalent values:"
    merged = processed_array.merge_equivalents()
    merged.show_summary(prefix="  ")
    print
    processed_array = merged.array()
    del merged
    processed_array.show_comprehensive_summary(prefix="  ")
    print
  if (r_free_flags is not None
      and not r_free_flags.is_unique_set_under_symmetry()):
    print "Merging symmetry-equivalent R-free flags:"
    merged = r_free_flags.merge_equivalents()
    merged.show_summary(prefix="  ")
    print
    r_free_flags = merged.array()
    del merged
    r_free_flags.show_comprehensive_summary(prefix="  ")
    print
  if (co.expand_to_p1):
    print "Expanding symmetry and resetting space group to P1:"
    if (r_free_flags is not None):
      raise Sorry(
        "--expand_to_p1 not supported for arrays of R-free flags.")
    processed_array = processed_array.expand_to_p1()
    processed_array.show_comprehensive_summary(prefix="  ")
    print
  if (co.change_to_space_group is not None):
    if (r_free_flags is not None):
      raise Sorry(
        "--change_to_space_group not supported for arrays of R-free flags.")
    new_space_group_info = sgtbx.space_group_info(
      symbol=co.change_to_space_group)
    print "Change to space group:", new_space_group_info
    new_crystal_symmetry = crystal.symmetry(
      unit_cell=processed_array.unit_cell(),
      space_group_info=new_space_group_info,
      assert_is_compatible_unit_cell=False)
    if (not new_crystal_symmetry.unit_cell()
              .is_similar_to(processed_array.unit_cell())):
      print "  *************"
      print "  W A R N I N G"
      print "  *************"
      print "  Unit cell parameters adapted to new space group symmetry are"
      print "  significantly different from input unit cell parameters:"
      print "      Input unit cell parameters:", \
        processed_array.unit_cell()
      print "    Adapted unit cell parameters:", \
        new_crystal_symmetry.unit_cell()
    processed_array = processed_array.customized_copy(
      crystal_symmetry=new_crystal_symmetry)
    print
    if (not processed_array.is_unique_set_under_symmetry()):
      print "  Merging values symmetry-equivalent under new symmetry:"
      merged = processed_array.merge_equivalents()
      merged.show_summary(prefix="    ")
      print
      processed_array = merged.array()
      del merged
      processed_array.show_comprehensive_summary(prefix="    ")
      print
  if (processed_array.anomalous_flag() and co.non_anomalous):
    print "Converting data array from anomalous to non-anomalous."
    if (not processed_array.is_xray_intensity_array()):
      processed_array = processed_array.average_bijvoet_mates()
    else:
      processed_array = processed_array.f_sq_as_f()
      processed_array = processed_array.average_bijvoet_mates()
      processed_array = processed_array.f_as_f_sq()
      processed_array.set_observation_type_xray_intensity()
  if (r_free_flags is not None
      and r_free_flags.anomalous_flag()
      and co.non_anomalous):
    print "Converting R-free flags from anomalous to non-anomalous."
    r_free_flags = r_free_flags.average_bijvoet_mates()
  d_max = co.low_resolution
  d_min = co.resolution
  if (d_max is not None or d_min is not None):
    if (d_max is not None):
      print "Applying low resolution cutoff: d_max=%.6g" % d_max
    if (d_min is not None):
      print "Applying high resolution cutoff: d_min=%.6g" % d_min
    processed_array = processed_array.resolution_filter(
      d_max=d_max, d_min=d_min)
    print "Number of reflections:", processed_array.indices().size()
    print
  if (co.scale_max is not None):
    print "Scaling data such that the maximum value is: %.6g" % co.scale_max
    processed_array = processed_array.apply_scaling(target_max=co.scale_max)
    print
  if (co.scale_factor is not None):
    print "Multiplying data with the factor: %.6g" % co.scale_factor
    processed_array = processed_array.apply_scaling(factor=co.scale_factor)
    print

  if (([co.remove_negatives, co.massage_intensities]).count(True) == 2):
    raise Sorry(
      "It is not possible to use --remove_negatives and"
      " --massage_intensities at the same time.")

  if (co.remove_negatives):
    if processed_array.is_real_array():
      print "Removing negatives items"
      processed_array = processed_array.select(
        processed_array.data() > 0)
      if processed_array.sigmas() is not None:
        processed_array = processed_array.select(
          processed_array.sigmas() > 0)
    else:
      raise Sorry("--remove_negatives not applicable to complex data arrays.")

  if (co.massage_intensities):
    if processed_array.is_real_array():
      if processed_array.is_xray_intensity_array():
        if (co.mtz is not None):
          if (co.write_mtz_amplitudes):
            print "The supplied intensities will be used to estimate"
            print " amplitudes in the following way:  "
            print " Fobs = Sqrt[ (Iobs + Sqrt(Iobs**2 + 2sigmaIobs**2))/2 ]"
            print " Sigmas are estimated in a similar manner."
            print
            processed_array = processed_array.enforce_positive_amplitudes()
          else:
            raise Sorry(
              "--write_mtz_amplitudes has to be specified when using"
              " --massage_intensities")
        else:
          raise Sorry("--mtz has to be used when using --massage_intensities")
      else:
        raise Sorry(
          "Intensities must be supplied when using the option"
          " --massage_intensities")
    else:
      raise Sorry(
        "--massage_intensities not applicable to complex data arrays.")

  if (not co.generate_r_free_flags):
    if (r_free_flags is None):
      r_free_info = []
    else:
      if (r_free_flags.anomalous_flag() != processed_array.anomalous_flag()):
        if (processed_array.anomalous_flag()): is_not = ("", " not")
        else:                                  is_not = (" not", "")
        raise Sorry(
          "The data array is%s anomalous but the R-free array is%s.\n"
            % is_not
          + "  Please try --non_anomalous.")
      r_free_info = ["R-free flags source: " + r_free_info]
      if (not r_free_flags.indices().all_eq(processed_array.indices())):
        processed_array = processed_array.map_to_asu()
        r_free_flags = r_free_flags.map_to_asu().common_set(processed_array)
        n_missing_r_free_flags = processed_array.indices().size() \
                               - r_free_flags.indices().size()
        if (n_missing_r_free_flags != 0):
          raise Sorry("R-free flags not compatible with data array:"
           " missing flag for %d reflections selected for output." %
             n_missing_r_free_flags)
  else:
    if (r_free_flags is not None):
      raise Sorry(
        "--r_free_label and --generate_r_free_flags are mutually exclusive.")
    print "Generating a new array of R-free flags:"
    r_free_flags = processed_array.generate_r_free_flags(
      fraction=co.r_free_flags_fraction,
      max_free=co.r_free_flags_max_free,
      use_lattice_symmetry=co.use_lattice_symmetry_in_r_free_flag_generation,
      format=co.r_free_flags_format)
    test_flag_value = True
    if (co.r_free_flags_format == "ccp4") :
      test_flag_value = 0
    elif (co.r_free_flags_format == "shelx") :
      test_flag_value = -1
    r_free_as_bool = r_free_flags.customized_copy(
      data=r_free_flags.data()==test_flag_value)
    r_free_info = [
      "R-free flags generated by %s:" % command_name]
    r_free_info.append("  "+date_and_time())
    r_free_info.append("  fraction: %.6g" % co.r_free_flags_fraction)
    r_free_info.append("  max_free: %s" % str(co.r_free_flags_max_free))
    r_free_info.append("  size of work set: %d" %
      r_free_as_bool.data().count(False))
    r_free_info.append("  size of free set: %d" %
      r_free_as_bool.data().count(True))
    r_free_info_str = StringIO()
    r_free_as_bool.show_r_free_flags_info(prefix="  ", out=r_free_info_str)
    if (co.r_free_flags_format == "ccp4") :
      r_free_info.append("  convention: CCP4 (test=0, work=1-%d)" %
        flex.max(r_free_flags.data()))
    elif (co.r_free_flags_format == "shelx") :
      r_free_info.append("  convention: SHELXL (test=-1, work=1)")
    else :
      r_free_info.append("  convention: CNS/X-PLOR (test=1, work=0)")
    print "\n".join(r_free_info[2:4])
    print r_free_info[-1]
    print r_free_info_str.getvalue()
    print

  n_output_files = 0
  if (co.sca is not None):
    if (co.generate_r_free_flags):
      raise Sorry("Cannot write R-free flags to Scalepack file.")
    file_name = reflection_file_utils.construct_output_file_name(
      input_file_names=[selected_array.info().source],
      user_file_name=co.sca,
      file_type_label="Scalepack",
      file_extension="sca")
    print "Writing Scalepack file:", file_name
    iotbx.scalepack.merge.write(
      file_name=file_name,
      miller_array=processed_array)
    n_output_files += 1
    print
  if (co.mtz is not None):
    file_name = reflection_file_utils.construct_output_file_name(
      input_file_names=[selected_array.info().source],
      user_file_name=co.mtz,
      file_type_label="MTZ",
      file_extension="mtz")
    print "Writing MTZ file:", file_name
    mtz_history_buffer = flex.std_string()
    mtz_history_buffer.append(date_and_time())
    mtz_history_buffer.append("> program: %s" % command_name)
    mtz_history_buffer.append("> input file name: %s" %
      os.path.basename(selected_array.info().source))
    mtz_history_buffer.append("> input directory: %s" %
      os.path.dirname(os.path.abspath(selected_array.info().source)))
    mtz_history_buffer.append("> input labels: %s" %
      selected_array.info().label_string())
    mtz_output_array = processed_array
    if (co.write_mtz_amplitudes):
      if (not mtz_output_array.is_xray_amplitude_array()):
        print "  Converting intensities to amplitudes."
        mtz_output_array = mtz_output_array.f_sq_as_f()
        mtz_history_buffer.append("> Intensities converted to amplitudes.")
    elif (co.write_mtz_intensities):
      if (not mtz_output_array.is_xray_intensity_array()):
        print "  Converting amplitudes to intensities."
        mtz_output_array = mtz_output_array.f_as_f_sq()
        mtz_history_buffer.append("> Amplitudes converted to intensities.")
    column_root_label = co.mtz_root_label
    if (column_root_label is None):
      # XXX 2013-03-29: preserve original root label by default
      # XXX 2014-12-16: skip trailing "(+)" in root_label if anomalous
      column_root_label = selected_array.info().labels[0]
    column_root_label=remove_anomalous_suffix_if_necessary(
      miller_array=selected_array,
      column_root_label=column_root_label)
    mtz_dataset = mtz_output_array.as_mtz_dataset(
      column_root_label=column_root_label)
    del mtz_output_array
    if (r_free_flags is not None):
      mtz_dataset.add_miller_array(
        miller_array=r_free_flags,
        column_root_label=co.output_r_free_label)
      for line in r_free_info:
        mtz_history_buffer.append("> " + line)
    mtz_history_buffer.append("> output file name: %s" %
      os.path.basename(file_name))
    mtz_history_buffer.append("> output directory: %s" %
      os.path.dirname(os.path.abspath(file_name)))
    mtz_object = mtz_dataset.mtz_object()
    mtz_object.add_history(mtz_history_buffer)
    mtz_object.write(file_name=file_name)
    n_output_files += 1
    print
  if (co.cns is not None):
    file_name = reflection_file_utils.construct_output_file_name(
      input_file_names=[selected_array.info().source],
      user_file_name=co.cns,
      file_type_label="CNS",
      file_extension="cns")
    print "Writing CNS file:", file_name
    processed_array.export_as_cns_hkl(
      file_object=open(file_name, "w"),
      file_name=file_name,
      info=["source of data: "+str(selected_array.info())] + r_free_info,
      r_free_flags=r_free_flags)
    n_output_files += 1
    print
  if (co.shelx is not None):
    if (co.generate_r_free_flags):
      raise Sorry("Cannot write R-free flags to SHELX file.")
    file_name = reflection_file_utils.construct_output_file_name(
      input_file_names=[selected_array.info().source],
      user_file_name=co.shelx,
      file_type_label="SHELX",
      file_extension="shelx")
    print "Writing SHELX file:", file_name
    processed_array.as_amplitude_array().export_as_shelx_hklf(
      open(file_name, "w"))
    n_output_files += 1
    print
  if (n_output_files == 0):
    command_line.parser.show_help()
    print "Please specify at least one output file format,",
    print "e.g. --mtz, --sca, etc."
    print
    return None
  return processed_array
Exemple #10
0
def run(args):
    from iotbx.option_parser import option_parser as iotbx_option_parser
    import libtbx.utils
    show_times = libtbx.utils.show_times(time_start="now")
    command_call = ["iotbx.python", __file__]
    command_line = (iotbx_option_parser(
        usage=" ".join(command_call) +
        " [options] directory|file...").enable_chunk(
            easy_all=True).enable_multiprocessing()).process(args=args,
                                                             min_nargs=1)
    if (command_line.run_multiprocessing_chunks_if_applicable(
            command_call=command_call)):
        show_times()
        return
    co = command_line.options
    #
    print "TIME BEGIN cod_refine:", date_and_time()
    print
    #
    master_phil = get_master_phil()
    argument_interpreter = master_phil.command_line_argument_interpreter()
    phil_objects = []
    remaining_args = []
    for arg in command_line.args:
        if (arg.find("=") >= 0):
            phil_objects.append(argument_interpreter.process(arg=arg))
        else:
            remaining_args.append(arg)
    work_phil = master_phil.fetch(sources=phil_objects)
    work_phil.show()
    print
    params = work_phil.extract()
    #
    qi_dict = {}
    all_pickles = []
    for arg in remaining_args:
        if (op.isdir(arg)):
            for node in sorted(os.listdir(arg)):
                if (node.endswith(".pickle")):
                    all_pickles.append(op.join(arg, node))
                elif (node.startswith("qi_") and len(node) == 10):
                    qi = open(op.join(arg, node)).read().splitlines()
                    if (len(qi) == 1):
                        cod_id = node[3:]
                        quick_info = eval(qi[0])
                        assert cod_id not in qi_dict
                        qi_dict[cod_id] = quick_info
        elif (op.isfile(arg)):
            all_pickles.append(arg)
        else:
            raise RuntimeError("Not a file or directory: %s" % arg)
    print "Number of pickle files:", len(all_pickles)
    print "Number of quick_infos:", len(qi_dict)
    sort_choice = params.sorting_of_pickle_files
    if (len(qi_dict) != 0 and sort_choice is not None):
        print "Sorting pickle files by n_atoms * n_refl:", sort_choice
        assert sort_choice in ["down", "up"]

        def sort_pickle_files():
            if (sort_choice == "down"): i_sign = -1
            else: i_sign = 1
            buffer = []
            for i, path in enumerate(all_pickles):
                cod_id = op.basename(path).split(".", 1)[0]
                qi = qi_dict.get(cod_id)
                if (qi is None): nn = 2**31
                else: nn = qi[0] * qi[1] * qi[2]
                buffer.append((nn, i_sign * i, path))
            buffer.sort()
            if (i_sign < 0):
                buffer.reverse()
            result = []
            for elem in buffer:
                result.append(elem[-1])
            return result

        all_pickles = sort_pickle_files()
    print
    #
    rss = params.random_subset.size
    if (rss is not None and rss > 0):
        seed = params.random_subset.seed
        print "Selecting subset of %d pickle files using random seed %d" % (
            rss, seed)
        mt = flex.mersenne_twister(seed=seed)
        perm = mt.random_permutation(size=len(all_pickles))[:rss]
        flags = flex.bool(len(all_pickles), False).set_selected(perm, True)
        all_pickles = flex.select(all_pickles, permutation=flags.iselection())
        print
    #
    from libtbx.path import makedirs_race
    if (params.wdir_root is not None):
        makedirs_race(path=params.wdir_root)
    if (params.pickle_refined_dir is not None):
        makedirs_race(path=params.pickle_refined_dir)
    #
    n_caught = 0
    for i_pickle, pickle_file_name in enumerate(all_pickles):
        if (i_pickle % command_line.chunk.n != command_line.chunk.i): continue
        tm = user_plus_sys_time()
        try:
            process(params, pickle_file_name)
        except KeyboardInterrupt:
            print >> sys.stderr, "CAUGHT EXCEPTION: KeyboardInterrupt"
            traceback.print_exc()
            print >> sys.stderr
            sys.stderr.flush()
            return
        except Exception:
            sys.stdout.flush()
            print >> sys.stderr, "CAUGHT EXCEPTION: %s" % pickle_file_name
            traceback.print_exc()
            print >> sys.stderr
            sys.stderr.flush()
            n_caught += 1
        else:
            print "done_with: %s (%.2f seconds)" % (pickle_file_name,
                                                    tm.elapsed())
            print
            sys.stdout.flush()
    print
    print "Number of exceptions caught:", n_caught
    #
    show_times()
    print
    print "TIME END cod_refine:", date_and_time()
Exemple #11
0
def run(args):
  from iotbx.option_parser import option_parser as iotbx_option_parser
  import libtbx.utils
  show_times = libtbx.utils.show_times(time_start="now")
  command_call = ["iotbx.python", __file__]
  command_line = (iotbx_option_parser(
    usage=" ".join(command_call) + " [options] directory|file...")
    .enable_chunk(easy_all=True)
    .enable_multiprocessing()
  ).process(args=args, min_nargs=1)
  if (command_line.run_multiprocessing_chunks_if_applicable(
        command_call=command_call)):
    show_times()
    return
  co = command_line.options
  #
  print "TIME BEGIN pdb_dev:", date_and_time()
  print
  libtbx.utils.host_and_user().show()
  print
  sys.stdout.flush()
  #
  from cctbx.omz import cod_refine
  master_phil = cod_refine.get_master_phil(
    max_atoms=None,
    f_calc_options_algorithm="direct *fft",
    bulk_solvent_correction=True)
  argument_interpreter = master_phil.command_line_argument_interpreter()
  phil_objects = []
  remaining_args = []
  for arg in command_line.args:
    if (arg.find("=") >= 0):
      phil_objects.append(argument_interpreter.process(arg=arg))
    else:
      remaining_args.append(arg)
  work_phil = master_phil.fetch(sources=phil_objects)
  work_phil.show()
  print
  params = work_phil.extract()
  #
  mtz_pdb_pairs = []
  arg_iter = iter(remaining_args)
  pdb_v3_mirror_dir = os.environ.get("PDB_MIRROR_PDB")
  assert pdb_v3_mirror_dir is None or op.isdir(pdb_v3_mirror_dir)
  cci_pdbmtz_path = os.environ.get("CCI_PDBMTZ")
  assert cci_pdbmtz_path is None or op.isdir(cci_pdbmtz_path)
  for arg in arg_iter:
    def get_next(expected_exts):
      def raise_bad_file(what, fn=None):
        msg = "%s file name (%s expected)" % (what, " or ".join(expected_exts))
        if (fn is None):
          msg += "."
        else:
          msg += ": " + show_string(fn)
        raise RuntimeError(msg)
      try:
        arg = arg_iter.next()
      except StopIteration:
        raise_bad_file("Missing")
      if (not arg.endswith(tuple(expected_exts))):
        raise_bad_file("Unexpected", arg)
      return arg
    if (op.isfile(arg) and arg.endswith((".mtz", ".pdb", ".ent"))):
      if (arg.endswith(".mtz")):
        fn_mtz = arg
        fn_pdb = get_next([".pdb", ".ent"])
      else:
        fn_pdb = arg
        fn_mtz = get_next([".mtz"])
    else:
      fn_mtz = arg+".mtz"
      def raise_mtz_but_no_pdb():
        raise RuntimeError(
          "MTZ file found but no PDB file: %s" % show_string(fn_mtz))
      if (op.isfile(fn_mtz)):
        for ext in [".pdb", ".ent"]:
          fn_pdb = arg+ext
          if (op.isfile(fn_pdb)):
            break
        else:
          raise_mtz_but_no_pdb()
      else:
        fn_mtz = op.join(cci_pdbmtz_path, arg+".mtz")
        if (not op.isfile(fn_mtz)):
          raise RuntimeError(
            "MTZ file not found: %s" % show_string(fn_mtz))
        fn_pdb = op.join(pdb_v3_mirror_dir, arg[1:3], "pdb"+arg+".ent.gz")
        if (not op.isfile(fn_pdb)):
          raise_mtz_but_no_pdb()
    mtz_pdb_pairs.append((fn_mtz, fn_pdb))
  #
  n_caught = 0
  for i_pair,mtz_pdb_pair in enumerate(mtz_pdb_pairs):
    if (i_pair % command_line.chunk.n != command_line.chunk.i): continue
    tm = user_plus_sys_time()
    try:
      process(params, mtz_pdb_pair)
    except KeyboardInterrupt:
      print >> sys.stderr, "CAUGHT EXCEPTION: KeyboardInterrupt"
      traceback.print_exc()
      print >> sys.stderr
      sys.stderr.flush()
      return
    except Exception:
      sys.stdout.flush()
      print >> sys.stderr, "CAUGHT EXCEPTION: %s" % ", ".join(mtz_pdb_pair)
      traceback.print_exc()
      print >> sys.stderr
      sys.stderr.flush()
      n_caught += 1
    else:
      print "done_with: %s, %s (%.2f seconds)" % (
        mtz_pdb_pair + (tm.elapsed(),))
      print
      sys.stdout.flush()
  print
  print "Number of exceptions caught:", n_caught
  #
  show_times()
  print
  print "TIME END pdb_dev:", date_and_time()
  sys.stdout.flush()
Exemple #12
0
def run(args):

  if len(args)==0:
    master_params.show(expert_level=100)
  elif ( "--help" in args ):
    print "no help available"
  elif ( "--h" in args ):
    print "no help available"
  elif ( "--show_defaults" in args ):
    master_params.show(expert_level=0)
  elif ( "--show_defaults_all" in args ):
    master_params.show(expert_level=10)

  else:
    log = multi_out()
    if (not "--quiet" in args):
      log.register(label="stdout", file_object=sys.stdout)
    string_buffer = StringIO()
    string_buffer_plots = StringIO()
    log.register(label="log_buffer", file_object=string_buffer)

    log_plots = StringIO()
    print >> log,"#phil __OFF__"
    print >> log
    print >> log, date_and_time()
    print >> log
    print >> log

    phil_objects = []
    argument_interpreter = master_params.command_line_argument_interpreter(
      home_scope="scaling")

    reflection_file = None

    for arg in args:
      command_line_params = None
      arg_is_processed = False
      if arg == '--quiet':
        arg_is_processed = True
        ## The associated action with this keyword is implemented above
      if (os.path.isfile(arg)): ## is this a file name?
        ## Check if this is a phil file
        try:
          command_line_params = iotbx.phil.parse(file_name=arg)
        except KeyboardInterrupt: raise
        except Exception : pass
        if command_line_params is not None:
            phil_objects.append(command_line_params)
            arg_is_processed = True
        ## Check if this file is a reflection file
        if command_line_params is None:
          reflection_file = reflection_file_reader.any_reflection_file(
            file_name=arg, ensure_read_access=False)
        if (reflection_file is not None):
          reflection_file = arg
          arg_is_processed = True
      ## If it is not a file, it must be a phil command
      else:
        try:
          command_line_params = argument_interpreter.process(arg=arg)
          if command_line_params is not None:
            phil_objects.append(command_line_params)
            arg_is_processed = True
        except KeyboardInterrupt: raise
        except Exception : pass

      if not arg_is_processed:
        print >> log, "##----------------------------------------------##"
        print >> log, "## Unknown phil-file or phil-command:", arg
        print >> log, "##----------------------------------------------##"
        print >> log
        raise Sorry("Unknown file format or phil command: %s" % arg)


    effective_params = master_params.fetch(sources=phil_objects)
    params = effective_params.extract()


    ## Now please read in the reflections files

    ## get symmetry and cell data first please
    ## By default, the native cell and symmetry are used
    ## as reference
    crystal_symmetry_nat = None
    print params.scaling.input.xray_data.wavelength1.file_name
    crystal_symmetry_nat = crystal_symmetry_from_any.extract_from(
      file_name=params.scaling.input.xray_data.wavelength1.file_name)

    if params.scaling.input.xray_data.space_group is None:
      params.scaling.input.xray_data.space_group =\
        crystal_symmetry_nat.space_group_info()
      print >> log, "Using symmetry of native data"

    if params.scaling.input.xray_data.unit_cell is None:
      params.scaling.input.xray_data.unit_cell =\
        crystal_symmetry_nat.unit_cell()
      print >> log, "Using cell of native data"

    ## Check if a unit cell is defined
    if params.scaling.input.xray_data.space_group is None:
      raise Sorry("No space group defined")
    if params.scaling.input.xray_data.unit_cell is None:
      raise Sorry("No unit cell defined")


    crystal_symmetry = crystal_symmetry = crystal.symmetry(
      unit_cell =  params.scaling.input.xray_data.unit_cell,
      space_group_symbol = str(
        params.scaling.input.xray_data.space_group) )


    effective_params = master_params.fetch(sources=phil_objects)
    new_params = master_params.format(python_object=params)
    print >> log, "Effective parameters"
    print >> log, "#phil __ON__"
    new_params.show(out=log,expert_level=params.scaling.input.expert_level)
    print >> log, "#phil __END__"
    print >> log

    ## define a xray data server
    xray_data_server =  reflection_file_utils.reflection_file_server(
      crystal_symmetry = crystal_symmetry,
      force_symmetry = True,
      reflection_files=[])

    ## Read in native data and make appropriate selections
    miller_array_w1 = None
    miller_array_w1 = xray_data_server.get_xray_data(
      file_name = params.scaling.input.xray_data.wavelength1.file_name,
      labels = params.scaling.input.xray_data.wavelength1.labels,
      ignore_all_zeros = True,
      parameter_scope = 'scaling.input.SIR_scale.xray_data.native'
    )
    info_native = miller_array_w1.info()
    miller_array_w1=miller_array_w1.map_to_asu().select(
      miller_array_w1.indices()!=(0,0,0) )
    miller_array_w1 = miller_array_w1.select(
      miller_array_w1.data() > 0 )
    ## Convert to amplitudes
    if (miller_array_w1.is_xray_intensity_array()):
      miller_array_w1 = miller_array_w1.f_sq_as_f()
    elif (miller_array_w1.is_complex_array()):
      miller_array_w1 = abs(miller_array_w1)
    if not miller_array_w1.is_real_array():
      raise Sorry("miller_array_native is not a real array")
    miller_array_w1.set_info(info = info_native)



    ## Read in derivative data and make appropriate selections
    miller_array_w2 = None
    miller_array_w2 = xray_data_server.get_xray_data(
      file_name = params.scaling.input.xray_data.wavelength2.file_name,
      labels = params.scaling.input.xray_data.wavelength2.labels,
      ignore_all_zeros = True,
      parameter_scope = 'scaling.input.SIR_scale.xray_data.derivative'
    )
    info_w2 = miller_array_w2.info()
    miller_array_w2=miller_array_w2.map_to_asu().select(
      miller_array_w2.indices()!=(0,0,0) )
    miller_array_w2 = miller_array_w2.select(
      miller_array_w2.data() > 0 )
    ## Convert to amplitudes
    if (miller_array_w2.is_xray_intensity_array()):
      miller_array_w2 = miller_array_w2.f_sq_as_f()
    elif (miller_array_w2.is_complex_array()):
      miller_array_w2 = abs(miller_array_w2)
    if not miller_array_w2.is_real_array():
      raise Sorry("miller_array_derivative is not a real array")
    miller_array_w2.set_info(info = info_w2)

    ## Make sure we have anomalous diffs in both files
    assert miller_array_w1.anomalous_flag()
    assert miller_array_w2.anomalous_flag()


    ## Print info
    print >> log
    print >> log, "Wavelength 1"
    print >> log, "============"
    miller_array_w1.show_comprehensive_summary(f=log)
    print >> log
    w1_pre_scale = pre_scale.pre_scaler(
      miller_array_w1,
      params.scaling.input.scaling_strategy.pre_scaler_protocol,
      params.scaling.input.basic)
    miller_array_w1 =  w1_pre_scale.x1.deep_copy()
    del w1_pre_scale

    print >> log
    print >> log, "Wavelength 2"
    print >> log, "============"
    miller_array_w2.show_comprehensive_summary(f=log)
    print >> log
    w2_pre_scale = pre_scale.pre_scaler(
      miller_array_w2,
      params.scaling.input.scaling_strategy.pre_scaler_protocol,
      params.scaling.input.basic)
    miller_array_w2 =  w2_pre_scale.x1.deep_copy()
    del w2_pre_scale


    print >> log
    print >> log, "Checking for possible reindexing schemes"
    print >> log, "----------------------------------------"
    print >> log
    print >> log, "Reindexing operator derived as described in:"
    print >> log, "Grosse-Kunstleve, Afonine, Sauter & Adams. (2005)."
    print >> log, "  IUCr Computing Commission Newsletter 5."
    print >> log

    reindex_object = pair_analyses.reindexing(
       set_a=miller_array_w1,
       set_b=miller_array_w2,
       out=log)
    miller_array_w2 = reindex_object.select_and_transform()
    miller_array_w2.map_to_asu()

    print >> log
    print >> log, "Relative scaling of 2-wavelength mad data"
    print >> log, "-----------------------------------------"
    print >> log
    scaler = fa_estimation.combined_scaling(
      miller_array_w1,
      miller_array_w2,
      params.scaling.input.scaling_strategy.iso_protocol)

    miller_array_w1 = scaler.x1.deep_copy()
    miller_array_w2 = scaler.x2.deep_copy()

    del scaler

    print >> log
    print >> log, "Estimating f\" and f' ratios"
    print >> log, "----------------------------"
    print >> log



    # now things are scaled see if we can guestimate the ratio
    fdpratio = pair_analyses.f_double_prime_ratio(
      miller_array_w1,
      miller_array_w2)

    fpfdpratio = pair_analyses.delta_f_prime_f_double_prime_ratio(
      miller_array_w1,
      miller_array_w2)

    k1 = fdpratio.ratio
    k2 = fpfdpratio.ratio

    if k1 is not None:
      print >> log
      print >> log, "  The estimate of f\"(w1)/f\"(w2) is %3.2f"\
            %(fdpratio.ratio)
    if k2 is not None:
      print >> log, "  The estimate of (f'(w1)-f'(w2))/f\"(w2) is %3.2f"\
            %(fpfdpratio.ratio)
      print >> log
      print >> log, "  The quality of these estimates depends to a large extend"
      print >> log, "  on the quality of the data. If user supplied values"
      print >> log, "  of f\" and f' are given, they will be used instead "
      print >> log, "  of the estimates."
      print >> log

    if params.scaling.input.xray_data.wavelength1.f_double_prime is not None:
      if params.scaling.input.xray_data.wavelength2.f_double_prime is not None:
        k1 = (params.scaling.input.xray_data.wavelength1.f_double_prime/
              params.scaling.input.xray_data.wavelength2.f_double_prime)
        print >> log, "    Using user specified f\" values"
        print >> log, "      user specified f\"(w1)/f\"(w2) is %3.2f"\
              %(k1)
        print >> log
    if params.scaling.input.xray_data.wavelength1.f_prime is not None:
      if params.scaling.input.xray_data.wavelength2.f_prime is not None:
        if params.scaling.input.xray_data.wavelength2.f_double_prime is not None:

          k2 = (params.scaling.input.xray_data.wavelength1.f_prime-
                params.scaling.input.xray_data.wavelength2.f_prime)\
                /params.scaling.input.xray_data.wavelength2.f_double_prime
          print >> log, "    Using user specified f\" and f' values"
          print >> log, "     user specified f\"(w1)/f\"(w2) is %3.2f"\
                %(k2)
          print >> log



    fa_gen = fa_estimation.twmad_fa_driver(miller_array_w1,
                                           miller_array_w2,
                                           k1,
                                           k2,
                                           params.scaling.input.fa_estimation)

    print >> log
    print >> log, "writing mtz file"
    print >> log, "----------------"
    print >> log

    ## Please write out the abs_delta_f array

    fa =  fa_gen.fa_values

    mtz_dataset = fa.as_mtz_dataset(
      column_root_label='F'+params.scaling.input.output.outlabel)

    mtz_dataset.mtz_object().write(
      file_name=params.scaling.input.output.hklout)
    def run(self):
        time_total_start = time.time()
        args = sys.argv[1:]

        log = multi_out()
        out = sys.stdout
        log.register("stdout", out)

        log_file_name = "cryo_fit2.log"
        logfile = open(
            log_file_name, "w"
        )  # since it is 'w', an existing file will be overwritten. (if this is "a", new info will be appended to an existing file)
        log.register("logfile", logfile)
        logfile.write(str(date_and_time()))

        print('A user input model name:    %s' %
              self.data_manager.get_default_model_name(),
              file=self.logger)
        model_inp = self.data_manager.get_model()

        print('A user input map file name: %s' %
              self.data_manager.get_default_real_map_name(),
              file=self.logger)
        map_inp = self.data_manager.get_real_map()

        ######### <begin> calculates CC_overall before cryo_fit2
        add_CRYST1_to_pdb_file(self, logfile, map_inp,
                               self.data_manager.get_default_model_name())

        try:
            cc_before_cryo_fit2 = round(
                calculate_overall_cc(map_data=map_inp.map_data(),
                                     model=model_inp,
                                     resolution=self.params.resolution), 4)
            # Pavel thinks that cc_box should be pretty much similar as this cc_before_cryo_fit2
            #Doo Nam confirmed that even without CRYST1 in pdb file, cc value here does not match cc_box (but close)

            write_this = "\n\nCC_overall before cryo_fit2 (both exploration and final MD): " + str(
                cc_before_cryo_fit2) + "\n"
            print('%s' % (write_this))
            logfile.write(str(write_this))
        except:
            write_error_message_for_overall_cc(logfile)

        if (self.params.cc_only == True):
            crystal_symmetry = mmtbx.utils.check_and_set_crystal_symmetry(
                models=[model_inp], map_inps=[map_inp])
            report_map_model_cc(self, map_inp, model_inp, crystal_symmetry,
                                logfile)
            logfile.close()
            exit(1)
        ######### <end> calculates CC_overall before cryo_fit2

        write_this = "\nPreparing cryo_fit2...\n"
        print(write_this)
        logfile.write(write_this)

        old_style_RNA, removed_R_prefix_in_RNA_pdb_file_name = remove_R_prefix_in_RNA(
            self.data_manager.get_default_model_name())
        if (old_style_RNA == True):
            write_this = '''Archaic style of nucleic acids (e.g. RA, RU, RT, RG, RC) were detected in user's pdb file.
phenix can't run with this type of naming.
cryo_fit2 replaced these with A,U,T,G,C and rewrote into ''' + removed_R_prefix_in_RNA_pdb_file_name + '''
Please rerun cryo_fit2 with this re-written pdb file\n'''
            print(write_this)
            logfile.write(write_this)
            logfile.close()
            exit(1)

        cleaned_pdb_file_name, cleaned_unusual_residue = clean_unusual_residue(
            self.data_manager.get_default_model_name())
        if (cleaned_unusual_residue == True):
            write_this = '''
       Unusual residue names like 34G that real_space_refine can't deal were detected in user's pdb file.\nCryo_fit2 removed these and rewrote into ''' + cleaned_pdb_file_name + '''\nPlease rerun cryo_fit2 with this re-written pdb file\n'''
            print(write_this)
            logfile.write(write_this)
            logfile.close()
            exit(1)

        leave_one_conformer(logfile,
                            self.data_manager.get_default_model_name())

        ############# (begin) Assign sigma/slack for H/E
        if ((self.params.HE_sigma != 0.05) or (self.params.HE_slack != 0.0)
                or (self.params.HE_angle_sigma_scale != 1)
                or (self.params.HE_top_out == True)):
            generated_eff_file_name = assign_ss_params_to_H_E(logfile, self.data_manager.get_default_model_name(), \
                                                            self.params.HE_sigma, self.params.HE_slack, self.params.HE_angle_sigma_scale,\
                                                            self.params.HE_top_out)
            if (generated_eff_file_name != False):
                sys.argv.append(generated_eff_file_name)
        ############# (end) Assign sigma/slack for H/E

        ############# (begin) Assign sigmas for nucleic_acids
        if ((self.params.parallelity_sigma != 0.0335)
                or (self.params.planarity_sigma != 0.176)
                or (self.params.stacking_pair_sigma != 0.027)):
            generated_eff_file_name_w_nucleic_acid_sigmas = assign_nucleic_acid_sigmas(logfile, \
                                                        self.data_manager.get_default_model_name(), self.params.parallelity_sigma, self.params.planarity_sigma, self.params.stacking_pair_sigma)
            if (generated_eff_file_name_w_nucleic_acid_sigmas != False):
                sys.argv.append(generated_eff_file_name_w_nucleic_acid_sigmas)
        ############# (end) Assign sigmas for nucleic_acids

        if (self.params.write_custom_geom_only == True):
            generated_eff_file_name = write_custom_geometry(logfile, self.data_manager.get_default_model_name(), \
                                                            self.params.stronger_ss_sigma, self.params.stronger_ss_slack)
            exit(1)
        '''
    # seems wrong to assign sigma and slack ? keep for now
    ############# (begin) deal with Doonam's stronger_ss
    if (self.params.stronger_ss == True):
      
      generated_eff_file_name = write_custom_geometry(logfile, self.data_manager.get_default_model_name(), \
                                                      self.params.stronger_ss_sigma, self.params.stronger_ss_slack)
      
      sys.argv.append(generated_eff_file_name)
    ############# (end) deal with Doonam's stronger_ss
    '''

        logfile.close()
Exemple #14
0
def run(args):

  if len(args)==0:
    master_params.show(expert_level=100)
  elif ( "--help" in args ):
    print("no help available")
  elif ( "--h" in args ):
    print("no help available")
  elif ( "--show_defaults" in args ):
    master_params.show(expert_level=0)
  elif ( "--show_defaults_all" in args ):
    master_params.show(expert_level=10)

  else:
    log = multi_out()
    if (not "--quiet" in args):
      log.register(label="stdout", file_object=sys.stdout)
    string_buffer = StringIO()
    string_buffer_plots = StringIO()
    log.register(label="log_buffer", file_object=string_buffer)

    log_plots = StringIO()
    print("#phil __OFF__", file=log)
    print(file=log)
    print(date_and_time(), file=log)
    print(file=log)
    print(file=log)

    phil_objects = []
    argument_interpreter = master_params.command_line_argument_interpreter(
      home_scope="scaling")

    reflection_file = None

    for arg in args:
      command_line_params = None
      arg_is_processed = False
      if arg == '--quiet':
        arg_is_processed = True
        ## The associated action with this keyword is implemented above
      if (os.path.isfile(arg)): ## is this a file name?
        ## Check if this is a phil file
        try:
          command_line_params = iotbx.phil.parse(file_name=arg)
        except KeyboardInterrupt: raise
        except Exception : pass
        if command_line_params is not None:
            phil_objects.append(command_line_params)
            arg_is_processed = True
        ## Check if this file is a reflection file
        if command_line_params is None:
          reflection_file = reflection_file_reader.any_reflection_file(
            file_name=arg, ensure_read_access=False)
        if (reflection_file is not None):
          reflection_file = arg
          arg_is_processed = True
      ## If it is not a file, it must be a phil command
      else:
        try:
          command_line_params = argument_interpreter.process(arg=arg)
          if command_line_params is not None:
            phil_objects.append(command_line_params)
            arg_is_processed = True
        except KeyboardInterrupt: raise
        except Exception : pass

      if not arg_is_processed:
        print("##----------------------------------------------##", file=log)
        print("## Unknown phil-file or phil-command:", arg, file=log)
        print("##----------------------------------------------##", file=log)
        print(file=log)
        raise Sorry("Unknown file format or phil command: %s" % arg)


    effective_params = master_params.fetch(sources=phil_objects)
    params = effective_params.extract()


    ## Now please read in the reflections files

    ## get symmetry and cell data first please
    ## By default, the native cell and symmetry are used
    ## as reference
    crystal_symmetry_nat = None
    print(params.scaling.input.xray_data.wavelength1.file_name)
    crystal_symmetry_nat = crystal_symmetry_from_any.extract_from(
      file_name=params.scaling.input.xray_data.wavelength1.file_name)

    if params.scaling.input.xray_data.space_group is None:
      params.scaling.input.xray_data.space_group =\
        crystal_symmetry_nat.space_group_info()
      print("Using symmetry of native data", file=log)

    if params.scaling.input.xray_data.unit_cell is None:
      params.scaling.input.xray_data.unit_cell =\
        crystal_symmetry_nat.unit_cell()
      print("Using cell of native data", file=log)

    ## Check if a unit cell is defined
    if params.scaling.input.xray_data.space_group is None:
      raise Sorry("No space group defined")
    if params.scaling.input.xray_data.unit_cell is None:
      raise Sorry("No unit cell defined")


    crystal_symmetry = crystal_symmetry = crystal.symmetry(
      unit_cell =  params.scaling.input.xray_data.unit_cell,
      space_group_symbol = str(
        params.scaling.input.xray_data.space_group) )


    effective_params = master_params.fetch(sources=phil_objects)
    new_params = master_params.format(python_object=params)
    print("Effective parameters", file=log)
    print("#phil __ON__", file=log)
    new_params.show(out=log,expert_level=params.scaling.input.expert_level)
    print("#phil __END__", file=log)
    print(file=log)

    ## define a xray data server
    xray_data_server =  reflection_file_utils.reflection_file_server(
      crystal_symmetry = crystal_symmetry,
      force_symmetry = True,
      reflection_files=[])

    ## Read in native data and make appropriate selections
    miller_array_w1 = None
    miller_array_w1 = xray_data_server.get_xray_data(
      file_name = params.scaling.input.xray_data.wavelength1.file_name,
      labels = params.scaling.input.xray_data.wavelength1.labels,
      ignore_all_zeros = True,
      parameter_scope = 'scaling.input.SIR_scale.xray_data.native'
    )
    info_native = miller_array_w1.info()
    miller_array_w1=miller_array_w1.map_to_asu().select(
      miller_array_w1.indices()!=(0,0,0) )
    miller_array_w1 = miller_array_w1.select(
      miller_array_w1.data() > 0 )
    ## Convert to amplitudes
    if (miller_array_w1.is_xray_intensity_array()):
      miller_array_w1 = miller_array_w1.f_sq_as_f()
    elif (miller_array_w1.is_complex_array()):
      miller_array_w1 = abs(miller_array_w1)
    if not miller_array_w1.is_real_array():
      raise Sorry("miller_array_native is not a real array")
    miller_array_w1.set_info(info = info_native)



    ## Read in derivative data and make appropriate selections
    miller_array_w2 = None
    miller_array_w2 = xray_data_server.get_xray_data(
      file_name = params.scaling.input.xray_data.wavelength2.file_name,
      labels = params.scaling.input.xray_data.wavelength2.labels,
      ignore_all_zeros = True,
      parameter_scope = 'scaling.input.SIR_scale.xray_data.derivative'
    )
    info_w2 = miller_array_w2.info()
    miller_array_w2=miller_array_w2.map_to_asu().select(
      miller_array_w2.indices()!=(0,0,0) )
    miller_array_w2 = miller_array_w2.select(
      miller_array_w2.data() > 0 )
    ## Convert to amplitudes
    if (miller_array_w2.is_xray_intensity_array()):
      miller_array_w2 = miller_array_w2.f_sq_as_f()
    elif (miller_array_w2.is_complex_array()):
      miller_array_w2 = abs(miller_array_w2)
    if not miller_array_w2.is_real_array():
      raise Sorry("miller_array_derivative is not a real array")
    miller_array_w2.set_info(info = info_w2)

    ## Make sure we have anomalous diffs in both files
    assert miller_array_w1.anomalous_flag()
    assert miller_array_w2.anomalous_flag()


    ## Print info
    print(file=log)
    print("Wavelength 1", file=log)
    print("============", file=log)
    miller_array_w1.show_comprehensive_summary(f=log)
    print(file=log)
    w1_pre_scale = pre_scale.pre_scaler(
      miller_array_w1,
      params.scaling.input.scaling_strategy.pre_scaler_protocol,
      params.scaling.input.basic)
    miller_array_w1 =  w1_pre_scale.x1.deep_copy()
    del w1_pre_scale

    print(file=log)
    print("Wavelength 2", file=log)
    print("============", file=log)
    miller_array_w2.show_comprehensive_summary(f=log)
    print(file=log)
    w2_pre_scale = pre_scale.pre_scaler(
      miller_array_w2,
      params.scaling.input.scaling_strategy.pre_scaler_protocol,
      params.scaling.input.basic)
    miller_array_w2 =  w2_pre_scale.x1.deep_copy()
    del w2_pre_scale


    print(file=log)
    print("Checking for possible reindexing schemes", file=log)
    print("----------------------------------------", file=log)
    print(file=log)
    print("Reindexing operator derived as described in:", file=log)
    print("Grosse-Kunstleve, Afonine, Sauter & Adams. (2005).", file=log)
    print("  IUCr Computing Commission Newsletter 5.", file=log)
    print(file=log)

    reindex_object = pair_analyses.reindexing(
       set_a=miller_array_w1,
       set_b=miller_array_w2,
       out=log)
    miller_array_w2 = reindex_object.select_and_transform()
    miller_array_w2.map_to_asu()

    print(file=log)
    print("Relative scaling of 2-wavelength mad data", file=log)
    print("-----------------------------------------", file=log)
    print(file=log)
    scaler = fa_estimation.combined_scaling(
      miller_array_w1,
      miller_array_w2,
      params.scaling.input.scaling_strategy.iso_protocol)

    miller_array_w1 = scaler.x1.deep_copy()
    miller_array_w2 = scaler.x2.deep_copy()

    del scaler

    print(file=log)
    print("Estimating f\" and f' ratios", file=log)
    print("----------------------------", file=log)
    print(file=log)



    # now things are scaled see if we can guestimate the ratio
    fdpratio = pair_analyses.f_double_prime_ratio(
      miller_array_w1,
      miller_array_w2)

    fpfdpratio = pair_analyses.delta_f_prime_f_double_prime_ratio(
      miller_array_w1,
      miller_array_w2)

    k1 = fdpratio.ratio
    k2 = fpfdpratio.ratio

    if k1 is not None:
      print(file=log)
      print("  The estimate of f\"(w1)/f\"(w2) is %3.2f"\
            %(fdpratio.ratio), file=log)
    if k2 is not None:
      print("  The estimate of (f'(w1)-f'(w2))/f\"(w2) is %3.2f"\
            %(fpfdpratio.ratio), file=log)
      print(file=log)
      print("  The quality of these estimates depends to a large extend", file=log)
      print("  on the quality of the data. If user supplied values", file=log)
      print("  of f\" and f' are given, they will be used instead ", file=log)
      print("  of the estimates.", file=log)
      print(file=log)

    if params.scaling.input.xray_data.wavelength1.f_double_prime is not None:
      if params.scaling.input.xray_data.wavelength2.f_double_prime is not None:
        k1 = (params.scaling.input.xray_data.wavelength1.f_double_prime/
              params.scaling.input.xray_data.wavelength2.f_double_prime)
        print("    Using user specified f\" values", file=log)
        print("      user specified f\"(w1)/f\"(w2) is %3.2f"\
              %(k1), file=log)
        print(file=log)
    if params.scaling.input.xray_data.wavelength1.f_prime is not None:
      if params.scaling.input.xray_data.wavelength2.f_prime is not None:
        if params.scaling.input.xray_data.wavelength2.f_double_prime is not None:

          k2 = (params.scaling.input.xray_data.wavelength1.f_prime-
                params.scaling.input.xray_data.wavelength2.f_prime)\
                /params.scaling.input.xray_data.wavelength2.f_double_prime
          print("    Using user specified f\" and f' values", file=log)
          print("     user specified f\"(w1)/f\"(w2) is %3.2f"\
                %(k2), file=log)
          print(file=log)



    fa_gen = fa_estimation.twmad_fa_driver(miller_array_w1,
                                           miller_array_w2,
                                           k1,
                                           k2,
                                           params.scaling.input.fa_estimation)

    print(file=log)
    print("writing mtz file", file=log)
    print("----------------", file=log)
    print(file=log)

    ## Please write out the abs_delta_f array

    fa =  fa_gen.fa_values

    mtz_dataset = fa.as_mtz_dataset(
      column_root_label='F'+params.scaling.input.output.outlabel)

    mtz_dataset.mtz_object().write(
      file_name=params.scaling.input.output.hklout)
Exemple #15
0
def run(args):
  from iotbx.option_parser import option_parser as iotbx_option_parser
  import libtbx.utils
  show_times = libtbx.utils.show_times(time_start="now")
  command_call = ["iotbx.python", __file__]
  command_line = (iotbx_option_parser(
    usage=" ".join(command_call) + " [options] directory|file...")
    .enable_chunk(easy_all=True)
    .enable_multiprocessing()
  ).process(args=args, min_nargs=1)
  if (command_line.run_multiprocessing_chunks_if_applicable(
        command_call=command_call)):
    show_times()
    return
  co = command_line.options
  #
  print "TIME BEGIN cod_refine:", date_and_time()
  print
  #
  master_phil = get_master_phil()
  argument_interpreter = master_phil.command_line_argument_interpreter()
  phil_objects = []
  remaining_args = []
  for arg in command_line.args:
    if (arg.find("=") >= 0):
      phil_objects.append(argument_interpreter.process(arg=arg))
    else:
      remaining_args.append(arg)
  work_phil = master_phil.fetch(sources=phil_objects)
  work_phil.show()
  print
  params = work_phil.extract()
  #
  qi_dict = {}
  all_pickles = []
  for arg in remaining_args:
    if (op.isdir(arg)):
      for node in sorted(os.listdir(arg)):
        if (node.endswith(".pickle")):
          all_pickles.append(op.join(arg, node))
        elif (node.startswith("qi_") and len(node) == 10):
          qi = open(op.join(arg, node)).read().splitlines()
          if (len(qi) == 1):
            cod_id = node[3:]
            quick_info = eval(qi[0])
            assert cod_id not in qi_dict
            qi_dict[cod_id] = quick_info
    elif (op.isfile(arg)):
      all_pickles.append(arg)
    else:
      raise RuntimeError("Not a file or directory: %s" % arg)
  print "Number of pickle files:", len(all_pickles)
  print "Number of quick_infos:", len(qi_dict)
  sort_choice = params.sorting_of_pickle_files
  if (len(qi_dict) != 0 and sort_choice is not None):
    print "Sorting pickle files by n_atoms * n_refl:", sort_choice
    assert sort_choice in ["down", "up"]
    def sort_pickle_files():
      if (sort_choice == "down"): i_sign = -1
      else:                       i_sign = 1
      buffer = []
      for i,path in enumerate(all_pickles):
        cod_id = op.basename(path).split(".",1)[0]
        qi = qi_dict.get(cod_id)
        if (qi is None): nn = 2**31
        else:            nn = qi[0] * qi[1] * qi[2]
        buffer.append((nn, i_sign*i, path))
      buffer.sort()
      if (i_sign < 0):
        buffer.reverse()
      result = []
      for elem in buffer:
        result.append(elem[-1])
      return result
    all_pickles = sort_pickle_files()
  print
  #
  rss = params.random_subset.size
  if (rss is not None and rss > 0):
    seed = params.random_subset.seed
    print "Selecting subset of %d pickle files using random seed %d" % (
      rss, seed)
    mt = flex.mersenne_twister(seed=seed)
    perm = mt.random_permutation(size=len(all_pickles))[:rss]
    flags = flex.bool(len(all_pickles), False).set_selected(perm, True)
    all_pickles = flex.select(all_pickles, permutation=flags.iselection())
    print
  #
  from libtbx.path import makedirs_race
  if (params.wdir_root is not None):
    makedirs_race(path=params.wdir_root)
  if (params.pickle_refined_dir is not None):
    makedirs_race(path=params.pickle_refined_dir)
  #
  n_caught = 0
  for i_pickle,pickle_file_name in enumerate(all_pickles):
    if (i_pickle % command_line.chunk.n != command_line.chunk.i): continue
    tm = user_plus_sys_time()
    try:
      process(params, pickle_file_name)
    except KeyboardInterrupt:
      print >> sys.stderr, "CAUGHT EXCEPTION: KeyboardInterrupt"
      traceback.print_exc()
      print >> sys.stderr
      sys.stderr.flush()
      return
    except Exception:
      sys.stdout.flush()
      print >> sys.stderr, "CAUGHT EXCEPTION: %s" % pickle_file_name
      traceback.print_exc()
      print >> sys.stderr
      sys.stderr.flush()
      n_caught += 1
    else:
      print "done_with: %s (%.2f seconds)" % (pickle_file_name, tm.elapsed())
      print
      sys.stdout.flush()
  print
  print "Number of exceptions caught:", n_caught
  #
  show_times()
  print
  print "TIME END cod_refine:", date_and_time()
Exemple #16
0
def run(args):

  if len(args)==0:
    master_params.show(expert_level=0)
  elif ( "--help" in args ):
    print "no help available"
  elif ( "--h" in args ):
    print "no help available"
  elif ( "--show_defaults" in args ):
    master_params.show(expert_level=0)
  elif ( "--show_defaults_all" in args ):
    master_params.show(expert_level=10)



  else:
    log = multi_out()
    if (not "--quiet" in args):
      log.register(label="stdout", file_object=sys.stdout)
    string_buffer = StringIO()
    string_buffer_plots = StringIO()
    log.register(label="log_buffer", file_object=string_buffer)

    log_plots = StringIO()
    print >> log,"#phil __OFF__"
    print >> log
    print >> log, date_and_time()
    print >> log
    print >> log

    phil_objects = []
    argument_interpreter = master_params.command_line_argument_interpreter(
      home_scope="scaling")

    reflection_file = None

    for arg in args:
      command_line_params = None
      arg_is_processed = False
      if arg == '--quiet':
        arg_is_processed = True
        ## The associated action with this keyword is implemented above
      if (os.path.isfile(arg)): ## is this a file name?
        ## Check if this is a phil file
        try:
          command_line_params = iotbx.phil.parse(file_name=arg)
        except KeyboardInterrupt: raise
        except Exception : pass
        if command_line_params is not None:
            phil_objects.append(command_line_params)
            arg_is_processed = True
        ## Check if this file is a reflection file
        if command_line_params is None:
          reflection_file = reflection_file_reader.any_reflection_file(
            file_name=arg, ensure_read_access=False)
        if (reflection_file is not None):
          reflection_file = arg
          arg_is_processed = True
      ## If it is not a file, it must be a phil command
      else:
        try:
          command_line_params = argument_interpreter.process(arg=arg)
          if command_line_params is not None:
            phil_objects.append(command_line_params)
            arg_is_processed = True
        except KeyboardInterrupt: raise
        except Exception : pass

      if not arg_is_processed:
        print >> log, "##----------------------------------------------##"
        print >> log, "## Unknown phil-file or phil-command:", arg
        print >> log, "##----------------------------------------------##"
        print >> log
        raise Sorry("Unknown file format or phil command: %s" % arg)


    effective_params = master_params.fetch(sources=phil_objects)
    params = effective_params.extract()

    ## Now please read in the reflections files

    ## get symmetry and cell data first please
    ## By default, the native cell and symmetry are used
    ## as reference
    crystal_symmetry_nat = None
    crystal_symmetry_nat = crystal_symmetry_from_any.extract_from(
      file_name=params.scaling.input.xray_data.after_burn.file_name)

    if params.scaling.input.xray_data.space_group is None:
      params.scaling.input.xray_data.space_group =\
        crystal_symmetry_nat.space_group_info()
      print >> log, "Using symmetry of after_burn data"

    if params.scaling.input.xray_data.unit_cell is None:
      params.scaling.input.xray_data.unit_cell =\
        crystal_symmetry_nat.unit_cell()
      print >> log, "Using cell of after_burn data"

    ## Check if a unit cell is defined
    if params.scaling.input.xray_data.space_group is None:
      raise Sorry("No space group defined")
    if params.scaling.input.xray_data.unit_cell is None:
      raise Sorry("No unit cell defined")


    crystal_symmetry = crystal_symmetry = crystal.symmetry(
      unit_cell =  params.scaling.input.xray_data.unit_cell,
      space_group_symbol = str(
        params.scaling.input.xray_data.space_group) )


    effective_params = master_params.fetch(sources=phil_objects)
    new_params = master_params.format(python_object=params)
    print >> log, "Effective parameters"
    print >> log, "#phil __ON__"
    new_params.show(out=log,
                    expert_level=params.scaling.input.expert_level  )
    print >> log, "#phil __END__"
    print >> log

    ## define a xray data server
    xray_data_server =  reflection_file_utils.reflection_file_server(
      crystal_symmetry = crystal_symmetry,
      force_symmetry = True,
      reflection_files=[])

    ## Read in native data and make appropriatre selections
    miller_array_native = None
    miller_array_native = xray_data_server.get_xray_data(
      file_name = params.scaling.input.xray_data.after_burn.file_name,
      labels = params.scaling.input.xray_data.after_burn.labels,
      ignore_all_zeros = True,
      parameter_scope = 'scaling.input.SIR_scale.xray_data.after_burn'
    )
    info_native = miller_array_native.info()
    miller_array_native=miller_array_native.map_to_asu().select(
      miller_array_native.indices()!=(0,0,0) )
    miller_array_native = miller_array_native.select(
      miller_array_native.data() > 0 )
    ## Convert to amplitudes
    if (miller_array_native.is_xray_intensity_array()):
      miller_array_native = miller_array_native.f_sq_as_f()
    elif (miller_array_native.is_complex_array()):
      miller_array_native = abs(miller_array_native)
    if not miller_array_native.is_real_array():
      raise Sorry("miller_array_native is not a real array")
    miller_array_native.set_info(info = info_native)



    ## Read in derivative data and make appropriate selections
    miller_array_derivative = None
    miller_array_derivative = xray_data_server.get_xray_data(
      file_name = params.scaling.input.xray_data.before_burn.file_name,
      labels = params.scaling.input.xray_data.before_burn.labels,
      ignore_all_zeros = True,
      parameter_scope = 'scaling.input.SIR_scale.xray_data.before_burn'
    )
    info_derivative = miller_array_derivative.info()
    miller_array_derivative=miller_array_derivative.map_to_asu().select(
      miller_array_derivative.indices()!=(0,0,0) )
    miller_array_derivative = miller_array_derivative.select(
      miller_array_derivative.data() > 0 )
    ## Convert to amplitudes
    if (miller_array_derivative.is_xray_intensity_array()):
      miller_array_derivative = miller_array_derivative.f_sq_as_f()
    elif (miller_array_derivative.is_complex_array()):
      miller_array_derivative = abs(miller_array_derivative)
    if not miller_array_derivative.is_real_array():
      raise Sorry("miller_array_derivative is not a real array")
    miller_array_derivative.set_info(info = info_derivative)




    ## As this is a SIR case, we will remove any anomalous pairs
    if miller_array_derivative.anomalous_flag():
      miller_array_derivative = miller_array_derivative.average_bijvoet_mates()\
      .set_observation_type( miller_array_derivative )
    if miller_array_native.anomalous_flag():
      miller_array_native = miller_array_native.average_bijvoet_mates()\
      .set_observation_type( miller_array_native )


    ## Print info
    print >> log
    print >> log, "Native data"
    print >> log, "==========="
    miller_array_native.show_comprehensive_summary(f=log)
    print >> log
    native_pre_scale = pre_scale.pre_scaler(
      miller_array_native,
      params.scaling.input.scaling_strategy.pre_scaler_protocol,
      params.scaling.input.basic)
    miller_array_native =  native_pre_scale.x1.deep_copy()
    del native_pre_scale

    print >> log
    print >> log, "Derivative data"
    print >> log, "==============="
    miller_array_derivative.show_comprehensive_summary(f=log)
    print >> log
    derivative_pre_scale = pre_scale.pre_scaler(
      miller_array_derivative,
      params.scaling.input.scaling_strategy.pre_scaler_protocol,
      params.scaling.input.basic)
    miller_array_derivative =  derivative_pre_scale.x1.deep_copy()
    del derivative_pre_scale

    scaler = fa_estimation.combined_scaling(
      miller_array_native,
      miller_array_derivative,
      params.scaling.input.scaling_strategy.iso_protocol)

    miller_array_native = scaler.x1.deep_copy()
    miller_array_derivative = scaler.x2.deep_copy()
    del scaler

    print >> log
    print >> log, "Making delta f's"
    print >> log, "----------------"
    print >> log

    delta_gen = pair_analyses.delta_generator( miller_array_native,
                                               miller_array_derivative,
                                               params.scaling.input.scaling_strategy.iso_protocol.nsr_bias )
    print >> log
    print >> log, "writing mtz file"
    print >> log, "----------------"
    print >> log

    ## some assertions to make sure nothing went weerd
    assert miller_array_native.observation_type() is not None
    assert miller_array_derivative.observation_type() is not None
    assert delta_gen.abs_delta_f.observation_type() is not None

    ## Please write out the abs_delta_f array

    mtz_dataset = delta_gen.abs_delta_f.as_mtz_dataset(
      column_root_label='F'+params.scaling.input.output.outlabel)
    mtz_dataset.mtz_object().write(
      file_name=params.scaling.input.output.hklout)
Exemple #17
0
def run(args):

    if len(args) == 0:
        master_params.show(expert_level=0)
    elif ("--help" in args):
        print("no help available")
    elif ("--h" in args):
        print("no help available")
    elif ("--show_defaults" in args):
        master_params.show(expert_level=0)
    elif ("--show_defaults_all" in args):
        master_params.show(expert_level=10)

    else:
        log = multi_out()
        if (not "--quiet" in args):
            log.register(label="stdout", file_object=sys.stdout)
        string_buffer = StringIO()
        string_buffer_plots = StringIO()
        log.register(label="log_buffer", file_object=string_buffer)

        log_plots = StringIO()
        print("#phil __OFF__", file=log)
        print(file=log)
        print(date_and_time(), file=log)
        print(file=log)
        print(file=log)

        phil_objects = []
        argument_interpreter = master_params.command_line_argument_interpreter(
            home_scope="scaling")

        reflection_file = None

        for arg in args:
            command_line_params = None
            arg_is_processed = False
            if arg == '--quiet':
                arg_is_processed = True
                ## The associated action with this keyword is implemented above
            if (os.path.isfile(arg)):  ## is this a file name?
                ## Check if this is a phil file
                try:
                    command_line_params = iotbx.phil.parse(file_name=arg)
                except KeyboardInterrupt:
                    raise
                except Exception:
                    pass
                if command_line_params is not None:
                    phil_objects.append(command_line_params)
                    arg_is_processed = True
                ## Check if this file is a reflection file
                if command_line_params is None:
                    reflection_file = reflection_file_reader.any_reflection_file(
                        file_name=arg, ensure_read_access=False)
                if (reflection_file is not None):
                    reflection_file = arg
                    arg_is_processed = True
            ## If it is not a file, it must be a phil command
            else:
                try:
                    command_line_params = argument_interpreter.process(arg=arg)
                    if command_line_params is not None:
                        phil_objects.append(command_line_params)
                        arg_is_processed = True
                except KeyboardInterrupt:
                    raise
                except Exception:
                    pass

            if not arg_is_processed:
                print("##----------------------------------------------##",
                      file=log)
                print("## Unknown phil-file or phil-command:", arg, file=log)
                print("##----------------------------------------------##",
                      file=log)
                print(file=log)
                raise Sorry("Unknown file format or phil command: %s" % arg)

        effective_params = master_params.fetch(sources=phil_objects)
        params = effective_params.extract()

        ## Now please read in the reflections files

        ## get symmetry and cell data first please
        ## By default, the native cell and symmetry are used
        ## as reference
        crystal_symmetry_nat = None
        crystal_symmetry_nat = crystal_symmetry_from_any.extract_from(
            file_name=params.scaling.input.xray_data.native.file_name)

        if params.scaling.input.xray_data.space_group is None:
            params.scaling.input.xray_data.space_group =\
              crystal_symmetry_nat.space_group_info()
            print("Using symmetry of native data", file=log)

        if params.scaling.input.xray_data.unit_cell is None:
            params.scaling.input.xray_data.unit_cell =\
              crystal_symmetry_nat.unit_cell()
            print("Using cell of native data", file=log)

        ## Check if a unit cell is defined
        if params.scaling.input.xray_data.space_group is None:
            raise Sorry("No space group defined")
        if params.scaling.input.xray_data.unit_cell is None:
            raise Sorry("No unit cell defined")

        crystal_symmetry = crystal_symmetry = crystal.symmetry(
            unit_cell=params.scaling.input.xray_data.unit_cell,
            space_group_symbol=str(params.scaling.input.xray_data.space_group))

        effective_params = master_params.fetch(sources=phil_objects)
        new_params = master_params.format(python_object=params)
        print("Effective parameters", file=log)
        print("#phil __ON__", file=log)
        new_params.show(out=log,
                        expert_level=params.scaling.input.expert_level)
        print("#phil __END__", file=log)
        print(file=log)

        ## define a xray data server
        xray_data_server = reflection_file_utils.reflection_file_server(
            crystal_symmetry=crystal_symmetry,
            force_symmetry=True,
            reflection_files=[])

        ## Read in native data and make appropriatre selections
        miller_array_native = None
        miller_array_native = xray_data_server.get_xray_data(
            file_name=params.scaling.input.xray_data.native.file_name,
            labels=params.scaling.input.xray_data.native.labels,
            ignore_all_zeros=True,
            parameter_scope='scaling.input.SIR_scale.xray_data.native')
        info_native = miller_array_native.info()
        miller_array_native = miller_array_native.map_to_asu().select(
            miller_array_native.indices() != (0, 0, 0))
        miller_array_native = miller_array_native.select(
            miller_array_native.data() > 0)
        ## Convert to amplitudes
        if (miller_array_native.is_xray_intensity_array()):
            miller_array_native = miller_array_native.f_sq_as_f()
        elif (miller_array_native.is_complex_array()):
            miller_array_native = abs(miller_array_native)
        if not miller_array_native.is_real_array():
            raise Sorry("miller_array_native is not a real array")
        miller_array_native.set_info(info=info_native)

        ## Read in derivative data and make appropriate selections
        miller_array_derivative = None
        miller_array_derivative = xray_data_server.get_xray_data(
            file_name=params.scaling.input.xray_data.derivative.file_name,
            labels=params.scaling.input.xray_data.derivative.labels,
            ignore_all_zeros=True,
            parameter_scope='scaling.input.SIR_scale.xray_data.derivative')
        info_derivative = miller_array_derivative.info()
        miller_array_derivative = miller_array_derivative.map_to_asu().select(
            miller_array_derivative.indices() != (0, 0, 0))
        miller_array_derivative = miller_array_derivative.select(
            miller_array_derivative.data() > 0)
        ## Convert to amplitudes
        if (miller_array_derivative.is_xray_intensity_array()):
            miller_array_derivative = miller_array_derivative.f_sq_as_f()
        elif (miller_array_derivative.is_complex_array()):
            miller_array_derivative = abs(miller_array_derivative)
        if not miller_array_derivative.is_real_array():
            raise Sorry("miller_array_derivative is not a real array")
        miller_array_derivative.set_info(info=info_derivative)

        ## As this is a SIR case, we will remove any anomalous pairs
        if miller_array_derivative.anomalous_flag():
            miller_array_derivative = miller_array_derivative.average_bijvoet_mates()\
            .set_observation_type( miller_array_derivative )
        if miller_array_native.anomalous_flag():
            miller_array_native = miller_array_native.average_bijvoet_mates()\
            .set_observation_type( miller_array_native )

        ## Print info
        print(file=log)
        print("Native data", file=log)
        print("===========", file=log)
        miller_array_native.show_comprehensive_summary(f=log)
        print(file=log)
        native_pre_scale = pre_scale.pre_scaler(
            miller_array_native,
            params.scaling.input.scaling_strategy.pre_scaler_protocol,
            params.scaling.input.basic)
        miller_array_native = native_pre_scale.x1.deep_copy()
        del native_pre_scale

        print(file=log)
        print("Derivative data", file=log)
        print("===============", file=log)
        miller_array_derivative.show_comprehensive_summary(f=log)
        print(file=log)
        derivative_pre_scale = pre_scale.pre_scaler(
            miller_array_derivative,
            params.scaling.input.scaling_strategy.pre_scaler_protocol,
            params.scaling.input.basic)
        miller_array_derivative = derivative_pre_scale.x1.deep_copy()
        del derivative_pre_scale

        scaler = fa_estimation.combined_scaling(
            miller_array_native, miller_array_derivative,
            params.scaling.input.scaling_strategy.iso_protocol)

        miller_array_native = scaler.x1.deep_copy()
        miller_array_derivative = scaler.x2.deep_copy()
        del scaler

        print(file=log)
        print("Making delta f's", file=log)
        print("----------------", file=log)
        print(file=log)

        delta_gen = pair_analyses.delta_generator(miller_array_native,
                                                  miller_array_derivative)
        print(file=log)
        print("writing mtz file", file=log)
        print("----------------", file=log)
        print(file=log)

        ## some assertions to make sure nothing went weerd
        assert miller_array_native.observation_type() is not None
        assert miller_array_derivative.observation_type() is not None
        assert delta_gen.abs_delta_f.observation_type() is not None

        ## Please write out the abs_delta_f array

        mtz_dataset = delta_gen.abs_delta_f.as_mtz_dataset(
            column_root_label='F' + params.scaling.input.output.outlabel)
        mtz_dataset.mtz_object().write(
            file_name=params.scaling.input.output.hklout)
Exemple #18
0
def run(args):
    from iotbx.option_parser import option_parser as iotbx_option_parser
    import libtbx.utils
    show_times = libtbx.utils.show_times(time_start="now")
    command_call = ["iotbx.python", __file__]
    command_line = (iotbx_option_parser(
        usage=" ".join(command_call) +
        " [options] directory|file...").enable_chunk(
            easy_all=True).enable_multiprocessing()).process(args=args,
                                                             min_nargs=1)
    if (command_line.run_multiprocessing_chunks_if_applicable(
            command_call=command_call)):
        show_times()
        return
    co = command_line.options
    #
    print("TIME BEGIN pdb_dev:", date_and_time())
    print()
    libtbx.utils.host_and_user().show()
    print()
    sys.stdout.flush()
    #
    from cctbx.omz import cod_refine
    master_phil = cod_refine.get_master_phil(
        max_atoms=None,
        f_calc_options_algorithm="direct *fft",
        bulk_solvent_correction=True)
    argument_interpreter = master_phil.command_line_argument_interpreter()
    phil_objects = []
    remaining_args = []
    for arg in command_line.args:
        if (arg.find("=") >= 0):
            phil_objects.append(argument_interpreter.process(arg=arg))
        else:
            remaining_args.append(arg)
    work_phil = master_phil.fetch(sources=phil_objects)
    work_phil.show()
    print()
    params = work_phil.extract()
    #
    mtz_pdb_pairs = []
    arg_iter = iter(remaining_args)
    pdb_v3_mirror_dir = os.environ.get("PDB_MIRROR_PDB")
    assert pdb_v3_mirror_dir is None or op.isdir(pdb_v3_mirror_dir)
    cci_pdbmtz_path = os.environ.get("CCI_PDBMTZ")
    assert cci_pdbmtz_path is None or op.isdir(cci_pdbmtz_path)
    for arg in arg_iter:

        def get_next(expected_exts):
            def raise_bad_file(what, fn=None):
                msg = "%s file name (%s expected)" % (
                    what, " or ".join(expected_exts))
                if (fn is None):
                    msg += "."
                else:
                    msg += ": " + show_string(fn)
                raise RuntimeError(msg)

            try:
                arg = next(arg_iter)
            except StopIteration:
                raise_bad_file("Missing")
            if (not arg.endswith(tuple(expected_exts))):
                raise_bad_file("Unexpected", arg)
            return arg

        if (op.isfile(arg) and arg.endswith((".mtz", ".pdb", ".ent"))):
            if (arg.endswith(".mtz")):
                fn_mtz = arg
                fn_pdb = get_next([".pdb", ".ent"])
            else:
                fn_pdb = arg
                fn_mtz = get_next([".mtz"])
        else:
            fn_mtz = arg + ".mtz"

            def raise_mtz_but_no_pdb():
                raise RuntimeError("MTZ file found but no PDB file: %s" %
                                   show_string(fn_mtz))

            if (op.isfile(fn_mtz)):
                for ext in [".pdb", ".ent"]:
                    fn_pdb = arg + ext
                    if (op.isfile(fn_pdb)):
                        break
                else:
                    raise_mtz_but_no_pdb()
            else:
                fn_mtz = op.join(cci_pdbmtz_path, arg + ".mtz")
                if (not op.isfile(fn_mtz)):
                    raise RuntimeError("MTZ file not found: %s" %
                                       show_string(fn_mtz))
                fn_pdb = op.join(pdb_v3_mirror_dir, arg[1:3],
                                 "pdb" + arg + ".ent.gz")
                if (not op.isfile(fn_pdb)):
                    raise_mtz_but_no_pdb()
        mtz_pdb_pairs.append((fn_mtz, fn_pdb))
    #
    n_caught = 0
    for i_pair, mtz_pdb_pair in enumerate(mtz_pdb_pairs):
        if (i_pair % command_line.chunk.n != command_line.chunk.i): continue
        tm = user_plus_sys_time()
        try:
            process(params, mtz_pdb_pair)
        except KeyboardInterrupt:
            print("CAUGHT EXCEPTION: KeyboardInterrupt", file=sys.stderr)
            traceback.print_exc()
            print(file=sys.stderr)
            sys.stderr.flush()
            return
        except Exception:
            sys.stdout.flush()
            print("CAUGHT EXCEPTION: %s" % ", ".join(mtz_pdb_pair),
                  file=sys.stderr)
            traceback.print_exc()
            print(file=sys.stderr)
            sys.stderr.flush()
            n_caught += 1
        else:
            print("done_with: %s, %s (%.2f seconds)" % (mtz_pdb_pair +
                                                        (tm.elapsed(), )))
            print()
            sys.stdout.flush()
    print()
    print("Number of exceptions caught:", n_caught)
    #
    show_times()
    print()
    print("TIME END pdb_dev:", date_and_time())
    sys.stdout.flush()