make fragment sampling available in default modelling pipeline

actions/pm-build-model

@@ -40,6 +40,7 @@ parser = pm3argparse.PM3ArgumentParser(__doc__, action=True)
 parser.AddAlignment()
 parser.AddStructure(attach_views=True)
 parser.AddProfile()
+parser.AddFragments()
 parser.AssembleParser()
 parser.add_argument('-o', '--model-file', metavar='<FILENAME>', type=str,
                     default='model.pdb', help='File to store model coordinates'+
@@ -70,6 +71,12 @@ try:
     # pssm files would not be sufficient and we would be restricted to hhm.
     if len(opts.profiles) > 0:
         modelling.SetSequenceProfiles(mhandle, opts.profiles)
+    # add fragment support for Monte Carlo sampling. The fragment search
+    # is setup in the argument parser. If activated you get fragment support
+    # in any case but for optimal performance you should provide profiles
+    # in hhm format (for profile AND secondary structure information).
+    if len(opts.fragger_handles) > 0:
+        modelling.SetFraggerHandles(mhandle, opts.fragger_handles)
     # build final model
     final_model = modelling.BuildFromRawModel(mhandle)
 except Exception as ex:

modelling/doc/pipeline.rst

@@ -400,6 +400,7 @@ Modelling Steps
            with seqres in **mhandle**
 
 
+.. autofunction:: SetFraggerHandles
 
 .. autofunction:: CloseGaps
 

modelling/pymod/CMakeLists.txt

@@ -23,6 +23,7 @@ set(MODELLING_PYMOD
   _fragger_handle.py
   _reconstruct_sidechains.py
   _monte_carlo.py
+  _mhandle_helper.py
 )
 
 pymod(NAME modelling

modelling/pymod/__init__.py

@@ -24,3 +24,4 @@ from _ring_punches import *
 from _denovo import *
 from _fragger_handle import *
 from _monte_carlo import *
+from _mhandle_helper import *

modelling/pymod/_mhandle_helper.py

+# Copyright (c) 2013-2018, SIB - Swiss Institute of Bioinformatics and 
+#                          Biozentrum - University of Basel
+# 
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+# 
+#   http://www.apache.org/licenses/LICENSE-2.0
+# 
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+def SetFraggerHandles(mhandle, fragger_handles):
+    """ Sets the :attr:`fragger_handles` in **mhandle** while ensuring 
+    consistency with the :attr:`ModellingHandle.seqres`
+
+    :param mhandle:     Will have the fragger handles attached afterwards
+    :param fragger_handles: The fragger handles to attach
+
+    :type mhandle:      :class:`ModellingHandle`
+    :type fragger_handles:  :class:`list` of :class:`FraggerHandle`
+
+    :raises: :class:`ValueError` when the given **fragger_handles** are not 
+             consistent with seqres in **mhandle**
+    """
+    
+    if len(mhandle.seqres) != len(mhandle.fragger_handles):
+        raise RuntimeError("Must have one FraggerHandle per chain!")
+    for a,b in zip(mhandle.seqres, mhandle.fragger_handles):
+        if str(a) != str(b.sequence):
+            raise RuntimeError("Sequence in FraggerHandle must match sequence "+
+                               "in SEQRES!")
+    mhandle.fragger_handles = fragger_handles

modelling/pymod/_pipeline.py

@@ -445,6 +445,13 @@ def BuildFromRawModel(mhandle, use_amber_ff=False, extra_force_fields=list()):
     and adapt the default scoring members. Alternatively, you can setup the
     scoring manually, but you must ensure consistency yourself!
 
+    By default, a simple backbone dihedral sampling is performed when entering 
+    Monte Carlo. If *mhandle* has a list of :class:`FraggerHandle` objects 
+    attached as "fragger_handles" attribute, the sampling will be performed with 
+    structural fragments. To ensure consistency, the fragger handles should be 
+    attached using :meth:`SetFraggerHandles`. 
+    But be aware of increased runtime due to the fragment search step.
+
     If the function fails to close all gaps, it will produce a warning and
     return an incomplete model.
 
@@ -489,10 +496,16 @@ def BuildFromRawModel(mhandle, use_amber_ff=False, extra_force_fields=list()):
     # remove terminal gaps
     RemoveTerminalGaps(mhandle)
 
+    # check whether we have fragger handles
+    fragger_handles = None
+    if hasattr(mhandle, "fragger_handles"):
+        fragger_handles = mhandle.fragger_handles
+        ost.LogInfo("Use fragments for Monte Carlo sampling")
+
     # close gaps
     CloseGaps(mhandle, merge_distance=merge_distance, 
               fragment_db=fragment_db, structure_db=structure_db, 
-              torsion_sampler=torsion_sampler)
+              torsion_sampler=torsion_sampler, fragger_handles=fragger_handles)
 
     # build sidechains
     BuildSidechains(mhandle, merge_distance, fragment_db,