def test_ComplexTraj(self):
"""Dock.ComplexTraj test"""
import biskit.tools as T
## there is no complex trajectory in the test folder so will have
## to create a fake trajectory with a complex
f = [ T.testRoot()+ '/com/1BGS.pdb' ] * 5
t = Trajectory( f, verbose=self.local )
t = ComplexTraj( t, recChains=[0] )
#if self.local:
#print 'plotting contact density...'
#t.plotContactDensity( step=2 )
## create a fake second chain in the ligand
for i in range( 1093+98, 1968 ):
t.ref.atoms['chain_id'][i] = 'B'
t.ref.chainIndex( force=1, cache=1 )
t.cl = [1,2]
r = N0.concatenate((list(range(1093,1191)), list(range(0,1093)), list(range(1191,1968))))
tt = t.takeAtoms( r )
contactMat = tt.atomContacts( 1 )
if self.local:
print('Receptor chains: %s Ligand chains: %s'%(t.cr, t.cl))
self.assertEqual( N0.sum(N0.ravel(contactMat)), 308 )
def test_ComplexTraj(self):
"""Dock.ComplexTraj test"""
import biskit.tools as T
## there is no complex trajectory in the test folder so will have
## to create a fake trajectory with a complex
f = [T.testRoot() + '/com/1BGS.pdb'] * 5
t = Trajectory(f, verbose=self.local)
t = ComplexTraj(t, recChains=[0])
#if self.local:
#print 'plotting contact density...'
#t.plotContactDensity( step=2 )
## create a fake second chain in the ligand
for i in range(1093 + 98, 1968):
t.ref.atoms['chain_id'][i] = 'B'
t.ref.chainIndex(force=1, cache=1)
t.cl = [1, 2]
r = N0.concatenate(
(list(range(1093,
1191)), list(range(0, 1093)), list(range(1191, 1968))))
tt = t.takeAtoms(r)
contactMat = tt.atomContacts(1)
if self.local:
print('Receptor chains: %s Ligand chains: %s' % (t.cr, t.cl))
self.assertEqual(N0.sum(N0.ravel(contactMat)), 308)
def test_ComplexRandomizer(self):
"""Dock.ComplexRandomizer test"""
from biskit.md import Trajectory
if self.local:
print("\nLoading Rec and Lig files ...", end=' ')
rec_pdb = t.testRoot() + '/rec/1A2P.pdb'
lig_pdb = t.testRoot() + '/lig/1A19.pdb'
rec_psf = t.testRoot() + '/rec/1A2P.psf'
lig_psf = t.testRoot() + '/lig/1A19.psf'
rec = XplorModel( rec_psf, rec_pdb )
lig = XplorModel( lig_psf, lig_pdb )
if self.local:
print("Initializing Randomizer...")
self.cr = ComplexRandomizer( rec, lig, debug=self.DEBUG )
if self.local:
print("Creating 3 random complexes...")
cs = [ self.cr.random_complex() for i in range(3) ]
self.traj = Trajectory( [ c.model() for c in cs ], verbose=self.local )
if self.local:
self.display( self.traj )
globals().update( locals() )
self.assertEqual( len(self.traj), 3 )
def replaceContent( self, traj ):
"""
Replace content of this trajectory by content of given traj.
No deep-copying, only references are taken.
@param traj: Trajectory
@type traj: Trajectory
@raise ComplexTrajError: if given traj is no ComplexTraj.
"""
if not isinstance( traj, ComplexTraj ):
raise ComplexTrajError(
"Cannot replace ComplexTraj by normal Trajectory.")
Trajectory.replaceContent( self, traj )
self.cr = traj.cr
self.cl = traj.cl
def replaceContent(self, traj):
"""
Replace content of this trajectory by content of given traj.
No deep-copying, only references are taken.
@param traj: Trajectory
@type traj: Trajectory
@raise ComplexTrajError: if given traj is no ComplexTraj.
"""
if not isinstance(traj, ComplexTraj):
raise ComplexTrajError(
"Cannot replace ComplexTraj by normal Trajectory.")
Trajectory.replaceContent(self, traj)
self.cr = traj.cr
self.cl = traj.cl
def takeAtoms( self, indices, returnClass=None ):
"""
takeAtoms( indices, [returnClass] ) -> ComplexTraj
@param indices: atoms to extract
@type indices: [int]
@param returnClass: return type (default: current class)
@type returnClass: class
@return: ComplexTraj
@rtype: ComplexTraj
@raise ComplexTrajError: if (parts of) chains are inserted into
each other
"""
r = Trajectory.takeAtoms( self, indices, returnClass )
oldToNew = self.__translateChainIndices( indices, r.ref.chainMap() )
r.cr = [ oldToNew[ c ] for c in self.cr if c in oldToNew ]
r.cl = [ oldToNew[ c ] for c in self.cl if c in oldToNew ]
return r
def takeAtoms(self, indices, returnClass=None):
"""
takeAtoms( indices, [returnClass] ) -> ComplexTraj
@param indices: atoms to extract
@type indices: [int]
@param returnClass: return type (default: current class)
@type returnClass: class
@return: ComplexTraj
@rtype: ComplexTraj
@raise ComplexTrajError: if (parts of) chains are inserted into
each other
"""
r = Trajectory.takeAtoms(self, indices, returnClass)
oldToNew = self.__translateChainIndices(indices, r.ref.chainMap())
r.cr = [oldToNew[c] for c in self.cr if c in oldToNew]
r.cl = [oldToNew[c] for c in self.cl if c in oldToNew]
return r
#!/usr/bin/env python
## re-generate binary test data in this folder
import biskit as B
import biskit.tools as T
from biskit.md import Trajectory, EnsembleTraj, traj2ensemble
## create standard trajectory object
t = Trajectory('raw/traj.crd', 'raw/traj_ref.pdb' )
t.frameNames = T.load('raw/traj_framenames.list')
te = traj2ensemble(t, members=10)
te.fit(fit=0) ## re-calculate profile 'rms' (all-atom fit to average structure)
T.dump(te, 'traj.dat')
if len( sys.argv ) < 2:
_use()
o = cmdDict( {'o':'traj.dat', 'i':'sim.crd'} )
fcrd = o['i']
fpdb = o['r']
fout = o['o']
box = 'b' in o
wat = 'wat' in o
hyd = 'hyd' in o
rnres = 'rnres' in o
code = o.get('code', None)
step = int(o.get('step', 1))
t = Trajectory( fcrd, fpdb, hasbox=box, rmwat=wat, verbose=True)
if code:
t.ref.pdbCode = code
if hyd:
t.ref.addChainId( keep_old=1 ) ## preserve chain-delimiters
t.removeAtoms( lambda a: a['element'] == 'H' )
if step != 1:
t = t.takeFrames( N.arange(0,len(t),step) )
print("Dumping result to ", fout)
dump( t, absfile(fout) )
print("Done")
import numpy as N
import biskit.tools as T
import biskit as B
from biskit.md import Trajectory, EnsembleTraj, traj2ensemble
com = Trajectory('rpa_com.crd', '0_com.pdb', hasbox=1 )
##com = T.load( 'com.traj' )
# re-order frames into 4 parallel trajectories
frames = N.zeros( len(com), int )
for i in range( 11 ):
N.put( frames, range(i*4,i*4+4), N.arange(i,44,11) )
etraj = EnsembleTraj( n_members=4 )
etraj.frames = com.takeFrames( frames ).frames
etraj.ref = com.ref
etraj.resetFrameNames()
etraj.ref.disconnect()
# separate protein and DNA into two chains
etraj.ref.chainIndex(breaks=True, force=True, cache=True)
etraj.ref.addChainId()
## extract only some residues for speed
t1 = etraj.takeAtoms( etraj.ref.res2atomIndices(range(10)) )
t2 = etraj.takeChains( [1] )