Author: bugman
Date: Thu Jan 15 11:27:25 2009
New Revision: 8457
URL: http://svn.gna.org/viewcvs/relax?rev=8457&view=rev
Log:
Massive redesign of the Scientific Python structural object atom_loop() method.
The new structural data data structure is now handled, and a number of changes
have occurred to the
class methods:
__molecule_loop() has been deleted.
__residue_loop() has been heavily modified.
The method __ave_atom_pos() has been added to allow the ave arg to
atom_loop() to be handled.
The molecule type is stored in the molecule containers by load_pdb().
Modified:
branches/multi_structure/generic_fns/structure/scientific.py
Modified: branches/multi_structure/generic_fns/structure/scientific.py
URL:
http://svn.gna.org/viewcvs/relax/branches/multi_structure/generic_fns/structure/scientific.py?rev=8457&r1=8456&r2=8457&view=diff
==============================================================================
--- branches/multi_structure/generic_fns/structure/scientific.py (original)
+++ branches/multi_structure/generic_fns/structure/scientific.py Thu Jan 15
11:27:25 2009
@@ -165,72 +165,11 @@
return bonded_num, bonded_name, element, pos, attached_name, None
- def __molecule_loop(self, struct, sel_obj=None):
- """Generator function for looping over molecules in the Scientific PDB
data objects.
-
- @param struct: The individual structure object, the highest level
Scientific Python PDB
- object.
- @type struct: Scientific Python PDB object
- @keyword sel_obj: The selection object.
- @type sel_obj: instance of generic_fns.mol_res_spin.Selection
- @return: A tuple of the Scientific Python PDB object
representing a single
- molecule, the molecule name, and molecule type.
- @rtype: (Scientific Python PDB object, str, str)
- """
-
- # Protein.
- if struct.peptide_chains:
- for chain in struct.peptide_chains:
- # The molecule name.
- if hasattr(chain, 'chain_id') and chain.chain_id:
- mol_name = chain.chain_id
- elif hasattr(chain, 'segment_id') and chain.segment_id:
- mol_name = chain.segment_id
- else:
- mol_name = None
-
- # Skip non-matching molecules.
- if sel_obj and not sel_obj.contains_mol(mol_name):
- continue
-
- # Yield the molecule and its name.
- yield chain, mol_name, 'protein'
-
- # RNA/DNA.
- if struct.nucleotide_chains:
- for chain in struct.nucleotide_chains:
- # The molecule name.
- if hasattr(chain, 'chain_id') and chain.chain_id:
- mol_name = chain.chain_id
- elif hasattr(chain, 'segment_id') and chain.segment_id:
- mol_name = chain.segment_id
- else:
- mol_name = None
-
- # Skip non-matching molecules.
- if sel_obj and not sel_obj.contains_mol(mol_name):
- continue
-
- # Yield the molecule and its name.
- yield chain, mol_name, 'nucleic acid'
-
- # Other molecules.
- if struct.molecules:
- for key in struct.molecules:
- # Yield the molecule and its name.
- yield struct.molecules[key], key, 'other'
-
-
- def __residue_loop(self, mol, mol_name, mol_type, sel_obj=None):
+ def __residue_loop(self, mol, sel_obj=None):
"""Generator function for looping over all residues in the Scientific
PDB data objects.
@param mol: The individual molecule Scientific Python PDB data
object.
@type mol: Scientific Python PDB object
- @param mol_name: The name of the molecule.
- @type mol_name: str or None
- @param mol_type: The type of the molecule. This can be one of
'protein', 'nucleic acid',
- or 'other'.
- @type mol_type: str
@keyword sel_obj: The selection object.
@type sel_obj: instance of generic_fns.mol_res_spin.Selection
@return: A tuple of the Scientific Python PDB object
representing a single
@@ -239,32 +178,40 @@
"""
# Proteins, RNA, and DNA.
- if mol_type != 'other':
+ if mol.mol_type != 'other':
# Loop over the residues of the protein in the PDB file.
+ res_index = -1
for res in mol.residues:
# Residue number and name.
- if mol_type == 'nucleic acid':
+ if mol.mol_type == 'nucleic acid':
res_name = res.name[-1]
else:
res_name = res.name
res_num = res.number
+ # Residue index.
+ res_index = res_index + 1
+
# Skip non-matching residues.
- if sel_obj and not sel_obj.contains_res(res_num, res_name,
mol_name):
+ if sel_obj and not sel_obj.contains_res(res_num, res_name,
mol.name):
continue
# Yield the residue info.
- yield res, res_num, res_name
+ yield res, res_num, res_name, res_index
# Other molecules.
else:
+ res_index = -1
for res in mol:
+ # Residue index.
+ res_index = res_index + 1
+
# Skip non-matching residues.
- if sel_obj and not sel_obj.contains_res(res.number, res.name,
mol_name):
+ if sel_obj and not sel_obj.contains_res(res.number, res.name,
mol.name):
continue
# Yield the residue info.
- yield res, res.number, res.name
+ yield res, res.number, res.name, res_index
def atom_loop(self, atom_id=None, str_id=None, model_num_flag=False,
mol_name_flag=False, res_num_flag=False, res_name_flag=False,
atom_num_flag=False, atom_name_flag=False, element_flag=False, pos_flag=False,
ave=False):
@@ -307,25 +254,43 @@
sel_obj = Selection(atom_id)
# Loop over the models.
- for struct in self.structural_data:
- # Loop over each individual molecule.
- for mol, mol_name, mol_type in self.__molecule_loop(struct,
sel_obj):
- # Loop over the residues of the protein in the PDB file.
- for res, res_num, res_name in self.__residue_loop(mol,
mol_name, mol_type, sel_obj):
+ for model_index in range(len(self.structural_data)):
+ model = self.structural_data[model_index]
+
+ # Loop over the molecules.
+ for mol_index in range(len(model.mol)):
+ mol = model.mol[mol_index]
+
+ # Skip non-matching molecules.
+ if sel_obj and not sel_obj.contains_mol(mol.name):
+ continue
+
+ # Loop over the residues.
+ for res, res_num, res_name, res_index in
self.__residue_loop(mol, sel_obj):
# Loop over the atoms of the residue.
+ atom_index = -1
for atom in res:
- # Atom number, name, and position.
+ # Atom number, name, index, and element type.
atom_num = atom.properties['serial_number']
atom_name = atom.name
element = atom.properties['element']
- pos = atom.position.array
+ atom_index = atom_index + 1
# Skip non-matching atoms.
- if sel_obj and not sel_obj.contains_spin(atom_num,
atom_name, res_num, res_name, mol_name):
+ if sel_obj and not sel_obj.contains_spin(atom_num,
atom_name, res_num, res_name, mol.name):
continue
+ # The atom position.
+ if ave:
+ pos = self.__ave_atom_pos(mol_index, res_index,
atom_index)
+ else:
+ pos = atom.position.array
+
+ # The molecule name.
+ mol_name = mol.name
+
# Replace empty variables with None.
- if not mol_name:
+ if not mol.name:
mol_name = None
if not res_num:
res_num = None
@@ -339,7 +304,10 @@
# Build the tuple to be yielded.
atomic_tuple = ()
if model_num_flag:
- atomic_tuple = atomic_tuple + (struct.model,)
+ if ave:
+ atomic_tuple = atomic_tuple + (None,)
+ else:
+ atomic_tuple = atomic_tuple + (model.num,)
if mol_name_flag:
atomic_tuple = atomic_tuple + (mol_name,)
if res_num_flag:
@@ -358,6 +326,10 @@
# Yield the information.
yield atomic_tuple
+ # Break out of the loop if the ave flag is set, as data from only
one model is used.
+ if ave:
+ break
+
def attached_atom(self, atom_id=None, attached_atom=None, model=None):
"""Find the atom corresponding to 'attached_atom' which is bonded to
the atom of 'atom_id'.
@@ -430,6 +402,44 @@
# Return the atom info.
return bonded_num, bonded_name, element, pos_array
+
+
+ def __ave_atom_pos(self, mol_index, res_index, atom_index):
+ """Determine the average atom position across all models.
+
+ @param mol_index: The molecule index.
+ @type mol_index: int
+ @param res_index: The residue index.
+ @type res_index: int
+ @param atom_index: The atom index.
+ @type atom_index: int
+ """
+
+ # Init.
+ pos = zeros(3, float64)
+
+ # Loop over the models.
+ for model in self.structural_data:
+ # The exact molecule.
+ mol = model.mol[mol_index]
+
+ # The residue.
+ if mol.mol_type != 'other':
+ res = mol.residues[res_index]
+ else:
+ res = mol[res_index]
+
+ # The atom.
+ atom = res[atom_index]
+
+ # Sum the position.
+ pos = pos + atom.position.array
+
+ # Average the position array.
+ pos = pos / len(self.structural_data)
+
+ # Return the ave position.
+ return pos
def bond_vectors(self, atom_id=None, attached_atom=None,
struct_index=None, return_name=False, return_warnings=False):
@@ -611,6 +621,7 @@
# First add the peptide chains (generating the molecule names and
incrementing the molecule index).
if hasattr(model, 'peptide_chains'):
for mol in model.peptide_chains:
+ mol.mol_type = 'protein'
mol_conts[-1].append(mol)
self.target_mol_name(set=set_mol_name,
target=new_mol_name, index=mol_index, mol_num=mol_index+1, file=file)
mol_index = mol_index + 1
@@ -618,6 +629,7 @@
# Then the nucleotide chains (generating the molecule names and
incrementing the molecule index).
if hasattr(model, 'nucleotide_chains'):
for mol in model.nucleotide_chains:
+ mol.mol_type = 'nucleic acid'
mol_conts[-1].append(mol)
self.target_mol_name(set=set_mol_name,
target=new_mol_name, index=mol_index, mol_num=mol_index+1, file=file)
mol_index = mol_index + 1
@@ -625,6 +637,7 @@
# Finally all other molecules (generating the molecule names and
incrementing the molecule index).
if hasattr(model, 'molecules'):
for key in model.molecules.keys():
+ mol.mol_type = 'other'
mol_conts[-1].append(model.molecules[key])
self.target_mol_name(set=set_mol_name,
target=new_mol_name, index=mol_index, mol_num=mol_index+1, file=file)
mol_index = mol_index + 1
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