def GenerateContactMap(TimeStep,protocol):
"""Read a frame and compute the contactMap between two groups of atom given a ContactMapProtocol
NOTE: if protocol.byres=True, then we report the number of atomic contacts for a given
residue pair in contact
Numbering of atoms and residues is the one given by the PSF file"""
rowNS = AtomNeighborSearch(protocol.rowGroup) #KDE-tree object for rowGroup
colNS = AtomNeighborSearch(protocol.colGroup) #KDE-tree object for colGroup
rowClose = rowNS.search_list(protocol.colGroup,protocol.cutOff) #atoms of rowGroup in contact with colGroup
if not rowClose: #no contacts
shape=(TimeStep.numatoms,TimeStep.numatoms) #all atoms in the system
if protocol.byres: shape=(protocol.numberOfResidues,protocol.numberOfResidues)
csr=csr_matrix( ([],([],[])), shape, dtype='int32') #empty map
cma=CMA.csr_ContactMap(csr)
cma.setDistanceCutOff(protocol.cutOff)
return cma
colClose = colNS.search_list(rowClose,protocol.cutOff) #atoms of colGroup in contact with rowClose/rowGroup
dd=distance_array(rowClose.coordinates(),colClose.coordinates(),TimeStep.dimensions[0:3])
(rowIndices,colIndices) = numpy.where(dd<protocol.cutOff)
rowIndices=rowClose.indices()[rowIndices]
colIndices=colClose.indices()[colIndices]
if protocol.byres:
#switch from atomic indices to residue numbers
rowIndices=protocol.atom2res[rowIndices]
colIndices=protocol.atom2res[colIndices]
shape=(protocol.numberOfResidues,protocol.numberOfResidues)
else:
#Take into account if the first atomic index was zero
rowIndices += protocol.shift
colIndices += protocol.shift
shape=(TimeStep.numatoms,TimeStep.numatoms) #all atoms in the system
#create sparse matrix for the contact map.
data=numpy.ones( len(rowIndices) ) #just signaling a contact map
csr=csr_matrix( (data, (rowIndices,colIndices)), shape, dtype='int32')
if protocol.byres: csr.data[:]=1 #overwrite number of atomic contacts per residue pair with 1 only
#trace()
if protocol.filter: csr=protocol.filter(csr) #Filtering
cma=CMA.csr_ContactMap(csr)
cma.setDistanceCutOff(protocol.cutOff)
return cma
def between(group, A, B, distance):
"""Return sub group of *group* that is within *distance* of both *A* and *B*.
*group*, *A*, and *B* must be
:class:`~MDAnalysis.core.AtomGroup.AtomGroup` instances. Works best
if *group* is bigger than either *A* or *B*. This function is not
aware of periodic boundary conditions.
Can be used to find bridging waters or molecules in an interface.
Similar to "*group* and (AROUND *A* *distance* and AROUND *B* *distance*)".
.. SeeAlso:: Makes use of :mod:`MDAnalysis.KDTree.NeighborSearch`.
.. versionadded: 0.7.5
"""
from MDAnalysis.KDTree.NeighborSearch import AtomNeighborSearch
from MDAnalysis.core.AtomGroup import AtomGroup
ns_group = AtomNeighborSearch(group)
resA = set(ns_group.search_list(A, distance))
resB = set(ns_group.search_list(B, distance))
return AtomGroup(resB.intersection(resA))
def between(group, A, B, distance):
"""Return sub group of *group* that is within *distance* of both *A* and *B*.
*group*, *A*, and *B* must be
:class:`~MDAnalysis.core.AtomGroup.AtomGroup` instances. Works best
if *group* is bigger than either *A* or *B*. This function is not
aware of periodic boundary conditions.
Can be used to find bridging waters or molecules in an interface.
Similar to "*group* and (AROUND *A* *distance* and AROUND *B* *distance*)".
.. SeeAlso:: Makes use of :mod:`MDAnalysis.KDTree.NeighborSearch`.
.. versionadded: 0.7.5
"""
from MDAnalysis.KDTree.NeighborSearch import AtomNeighborSearch
from MDAnalysis.core.AtomGroup import AtomGroup
ns_group = AtomNeighborSearch(group)
resA = set(ns_group.search_list(A, distance))
resB = set(ns_group.search_list(B, distance))
return AtomGroup(resB.intersection(resA))
def number_of_neighbouring_residues(residue_to_find, center, radius):
x = AtomNeighborSearch(residue_to_find)
neighboring = AtomNeighborSearch.search_list(x, center, radius, level='R')
number = len(neighboring)
return number
