def avgRmsd(self, cluster, aMask=None, threshold=0.):
"""
Claculate the average pairwise rmsd (in Angstrom) for members
of a cluter.
@param cluster: cluster number
@type cluster: int
@param aMask: atom mask applied before calculation
@type aMask: [1|0]
@param threshold: float 0-1, minimal cluster membership,
see L{memberTraj()}
@type threshold: float
@return: average rmsd and the standard deviation
@rtype: float, float
"""
try:
rms = self.memberTraj(cluster, threshold).pairwiseRmsd(aMask)
rms = aboveDiagonal(rms)
except:
rms = []
if len(N0.ravel(rms)) == 1:
## was: return N0.average(rms)[0], 0.0
return N0.average(rms), 0.0
if len(N0.ravel(rms)) == 0:
return 0.0, 0.0
return N0.average(rms), SD(rms)
def calcReducedContacts( self, soln, c ):
"""
Get contact matrices and/or fnarc from reduced-atom models.
@param soln: solution number
@type soln: int
@param c: Complex
@type c: Complex
"""
if not (self.reduced_recs and self.reduced_ligs):
return
if not self.requested(c,'c_ratom_10','fnarc_10'):
return
try:
## create Complex with same orientation but reduced coordinates
red_rec = self.reduced_recs[ c.rec_model.source ]
red_lig = self.reduced_ligs[ c.lig_model.source ]
red_com = Complex( red_rec, red_lig, c.ligandMatrix )
contacts = red_com.atomContacts( 10.0, cache=1 )
if self.requested(c, 'c_ratom_10'):
c['c_ratom_10'] = MU.packBinaryMatrix(contacts)
if self.c_ref_ratom_10 is not None:
ref = N0.ravel( self.c_ref_ratom_10 )
c['fnarc_10'] = N0.sum( N0.ravel(contacts) * ref )\
/ float( N0.sum(ref))
except:
self.reportError('reduced contacts error', soln)
def __unmaskedMatrix(self, contacts, rec_mask, lig_mask):
"""
Map contacts between selected rec and lig atoms back to all atoms
matrix.
@param contacts: contact matrix, array sum_rec_mask x sum_lig_mask
@type contacts: array
@param rec_mask: atom mask
@type rec_mask: [1|0]
@param lig_mask: atom mask
@type lig_mask: [1|0]
@return: atom contact matrix, array N_atoms_rec x N_atoms_lig
@rtype: array
"""
l_rec = len(self.rec_model)
l_lig = len(self.lig_model)
## map contacts back to all atoms matrix
r = N0.zeros(l_rec * l_lig)
rMask = N0.ravel(N0.outerproduct(rec_mask, lig_mask))
## (Optimization: nonzero is time consuming step)
N0.put(r, N0.nonzero(rMask), N0.ravel(contacts))
return N0.resize(r, (l_rec, l_lig))
def calcReducedContacts(self, soln, c):
"""
Get contact matrices and/or fnarc from reduced-atom models.
@param soln: solution number
@type soln: int
@param c: Complex
@type c: Complex
"""
if not (self.reduced_recs and self.reduced_ligs):
return
if not self.requested(c, 'c_ratom_10', 'fnarc_10'):
return
try:
## create Complex with same orientation but reduced coordinates
red_rec = self.reduced_recs[c.rec_model.source]
red_lig = self.reduced_ligs[c.lig_model.source]
red_com = Complex(red_rec, red_lig, c.ligandMatrix)
contacts = red_com.atomContacts(10.0, cache=1)
if self.requested(c, 'c_ratom_10'):
c['c_ratom_10'] = MU.packBinaryMatrix(contacts)
if self.c_ref_ratom_10 is not None:
ref = N0.ravel(self.c_ref_ratom_10)
c['fnarc_10'] = N0.sum( N0.ravel(contacts) * ref )\
/ float( N0.sum(ref))
except:
self.reportError('reduced contacts error', soln)
def takeMembers(self, mIndices):
"""
Take all frames belonging to the members in mIndices::
takeMembers( mIndices ) -> EnsembleTraj with frames of given members
@param mIndices: list of member indices
@type mIndices: [int] OR array('i')
@return: EnsembleTraj with specified members
@rtype: EnsembleTraj
@todo: return self.__class__ instead of EnsembleTraj
"""
try:
## assumes that each member traj has same number of frames
fi = N0.array([self.memberIndices(i) for i in mIndices])
fi = N0.ravel(N0.transpose(fi))
n_members = len(mIndices)
## has wrong n_members and member order
t = self.takeFrames(fi)
result = EnsembleTraj(n_members=n_members)
result.__dict__.update(t.__dict__)
result.n_members = n_members
result.resetFrameNames()
return result
except TypeError:
raise EnsembleTrajError, 'takeMembers TypeError '+\
str(mIndices)+\
"\nlenFrames: %i; n_members: %i" %(len(self), self.n_members)
def test_rmsFit(self):
"""rmsFit test"""
import Biskit.tools as T
self.traj = T.load(T.testRoot() + '/lig_pcr_00/traj.dat')
rt, rmsdLst = match(self.traj.ref.xyz, self.traj[-1].xyz)
if self.local:
print 'RMSD: %.2f' % rmsdLst[0][1]
# return rotation matrix
r = abs(N0.sum(N0.ravel(rt[0])))
e = abs(N0.sum(N0.ravel(self.EXPECT)))
self.assertAlmostEqual(r, e, 6)
def test_molTools(self):
"""molTools test"""
from Biskit import PDBModel
## Loading PDB...
self.m = PDBModel( T.testRoot() + '/lig/1A19.pdb' )
self.m = self.m.compress( self.m.maskProtein() )
hb = hbonds( self.m )
xyz = xyzOfNearestCovalentNeighbour( 40, self.m )
if self.local:
print '\nThe nearest covalently attached atom to the'
print ' atom with index 40 has the coordinates:'
print xyz
print 'Potential h-bonds in model:'
print '(donor index, acceptor index, distance and angle)'
for h in hb:
print h
globals().update( locals() )
self.r = N0.sum(N0.ravel(hb[3:5])) + N0.sum(xyz)
self.assertAlmostEqual( self.r, self.EXPECT, 3 )
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((range(1093, 1191), range(0,
1093), 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_molTools(self):
"""molTools test"""
from Biskit import PDBModel
## Loading PDB...
self.m = PDBModel(T.testRoot() + '/lig/1A19.pdb')
self.m = self.m.compress(self.m.maskProtein())
hb = hbonds(self.m)
xyz = xyzOfNearestCovalentNeighbour(40, self.m)
if self.local:
print '\nThe nearest covalently attached atom to the'
print ' atom with index 40 has the coordinates:'
print xyz
print 'Potential h-bonds in model:'
print '(donor index, acceptor index, distance and angle)'
for h in hb:
print h
globals().update(locals())
self.r = N0.sum(N0.ravel(hb[3:5])) + N0.sum(xyz)
self.assertAlmostEqual(self.r, self.EXPECT, 3)
def random_contacts( self, contMat, n, maskRec=None, maskLig=None ):
"""
Create randomized surface contact matrix with same number of
contacts and same shape as given contact matrix.
@param contMat: template contact matrix
@type contMat: matrix
@param n: number of matrices to generate
@type n: int
@param maskRec: surface masks (or something similar)
@type maskRec: [1|0]
@param maskLig: surface masks (or something similar)
@type maskLig: [1|0]
@return: list of [n] random contact matricies
@rtype: [matrix]
"""
a,b = N0.shape( contMat )
nContacts = N0.sum( N0.sum( contMat ))
if not maskLig:
r_size, l_size = N0.shape( contMat )
maskLig = N0.ones( l_size )
maskRec = N0.ones( r_size )
c_mask = N0.ravel( N0.outerproduct( maskRec, maskLig ) )
c_pos = N0.nonzero( c_mask )
# get array with surface positions from complex
cont = N0.take( N0.ravel(contMat), c_pos )
length = len( cont )
result = []
for i in range( n ):
# create random array
ranCont = mathUtils.randomMask( nContacts,length )
# blow up to size of original matrix
r = N0.zeros(a*b)
N0.put( r, c_pos, ranCont)
result += [ N0.reshape( r, (a,b) ) ]
return result
def plotContactDensity(self, step=1, cutoff=4.5):
"""
Example. plot histogramm of contact density. Somehing wrong??
@raise ComplexTrajError: if gnuplot program is not installed
"""
if not gnuplot.installed:
raise ComplexTrajError, 'gnuplot program is not installed'
r = self.averageContacts(step, cutoff)
r = N0.ravel(r)
r = N0.compress(r, r)
gnuplot.plot(hist.density(r, 10))
def calcContacts( self, soln, c ):
"""
Calculate contact matrices and fraction of native contacts, residue-
and atom-based, with different distance cutoffs.
@param soln: solution number
@type soln: int
@param c: Complex
@type c: Complex
"""
try:
if self.requested(c, 'fnac_4.5') and self.c_ref_atom_4_5 is not None:
## cache pairwise atom distances for following calculations
contacts = c.atomContacts( 4.5, self.mask_rec, self.mask_lig,
cache=1, map_back=0 )
ref = N0.ravel( self.c_ref_atom_4_5 )
c['fnac_4.5'] = N0.sum( N0.ravel(contacts) * ref )\
/ float( N0.sum(ref))
if self.requested(c, 'fnac_10') and self.c_ref_atom_10 is not None:
contacts = c.atomContacts( 10., self.mask_rec, self.mask_lig,
cache=1, map_back=0 )
ref = N0.ravel( self.c_ref_atom_10 )
c['fnac_10'] = N0.sum( N0.ravel(contacts) * ref ) \
/ float( N0.sum(ref))
if self.requested(c, 'c_res_4.5') \
or ( self.c_ref_res_4_5 is not None \
and (self.requested(c,'fnrc_4.5','fnSurf_rec'))):
res_cont = c.resContacts( 4.5,
cache=self.requested(c, 'c_res_4.5'))
if self.c_ref_res_4_5 is not None \
and self.requested(c, 'fnrc_4.5' ):
ref = N0.ravel( self.c_ref_res_4_5 )
c['fnrc_4.5'] = N0.sum(N0.ravel(res_cont)*ref) \
/float(N0.sum(ref))
if self.c_ref_res_4_5 is not None \
and self.requested(c, 'fnSurf_rec'):
r, l = c.fractionNativeSurface(res_cont,
self.c_ref_res_4_5 )
c['fnSurf_rec'] = r
c['fnSurf_lig'] = l
except:
m1 = m2 = s = 0
try:
m1, m2, s = c.get('model1',0), c.get('model2',0),\
c.get('soln',0)
except:
pass
self.reportError('contact error (r %i : l %i, #%i)'%\
(m1,m2,s), soln)
def __init__(self, models, name=None, profileName='relAS', verbose=1):
"""
@param models: List of models display a Ramachandran plot for
@type models: [ PDBModel ] OR PDBModel
@param name: model name, will show up in plot
@type name: str
@param profileName: name of profile to use for coloring
(default: 'relAS')
@type profileName: str
@param verbose: verbosity level (default: 1)
@type verbose: 1|0
"""
if not biggles:
raise ImportError, 'biggles module could not be imported.'
if type(models) != type([]):
models = [models]
self.psi = []
self.phi = []
self.gly = []
self.pro = []
self.prof = []
self.profileName = profileName
self.name = name
self.verbose = verbose
# calculate angles, profiles ...
self.calc(models)
self.prof = N0.ravel(self.prof)
self.gly = N0.ravel(self.gly)
self.pro = N0.ravel(self.pro)
def getFirstCrdLine(self):
"""
Return the first line of Amber crd.
@return: first line of Amber crd formatted coordinate block
@rtype: str
"""
if not self.xyz:
self.getXyz()
result = ""
for x in N0.ravel(self.xyz)[:10]:
result += "%8.3f" % x
return result + "\n"
def changeModel(inFile, prefix, sourceModel):
print '\nget ' + os.path.basename(inFile) + '..',
model = PDBModel(inFile)
model.update()
model = model.sort()
eq = model.equals(sourceModel)
if not eq[0] and eq[1]:
raise ConvertError('source and other models are not equal: ' + str(eq))
# model.validSource()
model.setSource(sourceModel.validSource())
#model.atomsChanged = 0
for k in model.atoms:
model.atoms[k, 'changed'] = N0.all(model[k] == sourceModel[k])
model.xyzChanged = (0 != N0.sum(N0.ravel(model.xyz - sourceModel.xyz)))
model.update(updateMissing=1)
if model.xyzChanged:
doper = PDBDope(model)
if 'MS' in sourceModel.atoms.keys():
doper.addSurfaceRacer(probe=1.4)
if 'density' in sourceModel.atoms.keys():
doper.addDensity()
if 'foldX' in sourceModel.info.keys():
doper.addFoldX()
if 'delphi' in sourceModel.info.keys():
doper.addDelphi()
outFile = os.path.dirname( inFile ) + '/' + prefix +\
T.stripFilename( inFile ) + '.model'
T.dump(model, outFile)
print '-> ' + os.path.basename(outFile)
def changeModel( inFile, prefix, sourceModel ):
print '\nget ' + os.path.basename( inFile ) + '..',
model = PDBModel( inFile )
model.update()
model = model.sort()
eq = model.equals( sourceModel )
if not eq[0] and eq[1]:
raise ConvertError('source and other models are not equal: ' + str(eq))
# model.validSource()
model.setSource( sourceModel.validSource() )
#model.atomsChanged = 0
for k in model.atoms:
model.atoms[k,'changed'] = N0.all( model[k] == sourceModel[k] )
model.xyzChanged = ( 0 != N0.sum( N0.ravel( model.xyz - sourceModel.xyz)) )
model.update( updateMissing=1 )
if model.xyzChanged:
doper = PDBDope( model )
if 'MS' in sourceModel.atoms.keys():
doper.addSurfaceRacer( probe=1.4 )
if 'density' in sourceModel.atoms.keys():
doper.addDensity()
## if 'foldX' in sourceModel.info.keys():
## doper.addFoldX()
if 'delphi' in sourceModel.info.keys():
doper.addDelphi()
outFile = os.path.dirname( inFile ) + '/' + prefix +\
T.stripFilename( inFile ) + '.model'
T.dump( model, outFile )
print '-> ' + os.path.basename( outFile )
def writeCrd(self, fcrd, append=1, lastAtom=None):
"""
Write/Append Amber-formatted block of coordinates to a file.
If a file handle is given, the file will not be closed.
@param fcrd: file to write to
@type fcrd: str or file object
@param append: append to existing file (default: 1)
@type append: 0|1
@param lastAtom: skip all atoms beyond this one (default: None)
@type lastAtom: int
"""
if not self.xyz:
self.getXyz()
if type(fcrd) == file:
## take file handle
f = fcrd
else:
## create new file handle
mode = 'w'
if append:
mode = 'a'
f = open(T.absfile(fcrd), mode)
newf = (mode == 'w' or not os.path.exists(T.absfile(fcrd)))
if newf:
f.write("\n")
i = 0
for x in N0.ravel(self.xyz):
i = i + 1
f.write("%8.3f" % x)
if (i % 10) == 0:
f.write("\n")
if lastAtom and i / 3.0 == lastAtom:
break
if ((i % 10) != 0):
f.write("\n")
if type(fcrd) != file:
## don't close file that was already given
f.close()
def color_array( self, a, resetLimits=1 ):
"""
@param a: array of float
@type a: array of float
@param resetLimits: re-define color range on max and min of values
(default: 1)
@type resetLimits: 1|0
@return: matrix of color codes with same dimensions as a
@rtype: array of float
"""
s = N0.shape( a )
v = N0.ravel( a )
r = self.colors( v, resetLimits=resetLimits )
r = N0.reshape( r, s )
return r
def slim(self):
"""
Remove coordinates and atoms of ligand and receptor from memory,
if they can be restored from file, compress contact matrix.
@note: CALLED BEFORE PICKLING
"""
self.lig_transformed = None
self.pw_dist = None
## self.ligandMatrix = self.ligandMatrix.tolist()
if 'matrix' in self.info:
del self.info['matrix']
## compress contact matrix array
if self.contacts is not None and \
len(N0.shape( self.contacts['result'] ) )==2:
m = self.contacts['result']
self.contacts['shape'] = N0.shape(m)
self.contacts['result'] = N0.nonzero(N0.ravel(m)).astype(N0.Int32)
def calcRmsd(self, window, f1, f2):
"""
Calulate the rmsd between two frame chunks.
@param window: start and end of two frame chunks within the
whole trajectory
@type window: ((int, int),(int,int))
@param f1: frame chunk
@type f1: array
@param f2: frame chunk
@type f2: array
@return: the rms between the frames
@rtype: [float]
"""
try:
i_start, i_stop = window[0]
j_start, j_stop = window[1]
a = N0.zeros((i_stop - i_start, j_stop - j_start), N0.Float)
i = j = -1
## block on the diagonal, only calculate one half of it
S = (self.only_off_diagonal and window[0] == window[1])
for i in range(i_start, i_stop):
for j in range(S * i - S * j_start + j_start, j_stop):
if self.requested(i, j):
rt, rmsdLst = rmsFit.match(f1[i - i_start],
f2[j - j_start], 1)
a[i - i_start, j - j_start] = rmsdLst[0][1]
return N0.ravel(a).tolist()
except Exception, why:
self.reportError('ERROR ' + str(why), (i, j))
return
def calcRmsd( self, window, f1, f2 ):
"""
Calulate the rmsd between two frame chunks.
@param window: start and end of two frame chunks within the
whole trajectory
@type window: ((int, int),(int,int))
@param f1: frame chunk
@type f1: array
@param f2: frame chunk
@type f2: array
@return: the rms between the frames
@rtype: [float]
"""
try:
i_start, i_stop = window[0]
j_start, j_stop = window[1]
a = N0.zeros( (i_stop-i_start, j_stop-j_start), N0.Float )
i = j = -1
## block on the diagonal, only calculate one half of it
S = (self.only_off_diagonal and window[0] == window[1])
for i in range( i_start, i_stop ):
for j in range( S * i - S * j_start + j_start, j_stop ):
if self.requested( i, j ):
rt, rmsdLst = rmsFit.match( f1[i-i_start],
f2[j-j_start], 1 )
a[i-i_start,j-j_start] = rmsdLst[0][1]
return N0.ravel(a).tolist()
except Exception, why:
self.reportError( 'ERROR '+str(why), (i,j) )
return
def writeCrd( self, fname, frames=None ):
"""
Write frames to Amber crd file (w/o box info).
@param fname: output file name
@type fname: str
@param frames: frame indices (default: all)
@type frames: [int]
"""
if frames is None:
frames = range( self.lenFrames() )
template = " %7.3f" * 10 + '\n'
## open new file
out = open( T.absfile(fname), 'w')
__write = out.write ## cache function address for speed
__write('\n')
n_lines = None
for fi in frames:
f = N0.ravel( self.frames[ fi ] )
if n_lines is None:
n_lines = n_lines or len( f ) / 10
overhang= ( 0 != len( f ) % 10 )
i_lines = range( n_lines )
for i in i_lines:
__write( template % tuple( f[10*i:10*i+10] ) )
if overhang:
for x in f[i*10+10:]:
__write(" %7.3f" % x )
__write('\n')
out.close()
def thin(self, step=1):
"""
Keep only each step'th frame from trajectory with 10 ensemble members.
@param step: 1..keep all frames, 2..skip first and every second, ..
(default: 1)
@type step: int
@return: reduced EnsembleTraj
@rtype: EnsembleTraj
"""
T.ensure(step, int, forbidden=[0])
## 10 x lenFrames/10, frame indices of each member
mI = [self.memberIndices(i) for i in range(self.n_members)]
mI = N0.array(mI)
mI = N0.take(mI, range(-1, N0.shape(mI)[1], step)[1:], 1)
mI = N0.transpose(mI)
return self.takeFrames(N0.ravel(mI))
def pcMovie( self, ev, steps, factor=1., ref=0, morph=1 ):
"""
Morph between the two extreme values of a single principal
component.
@param ev: EigenVector to visualize
@type ev: int
@param steps: number of intermediate frames
@type steps: int
@param factor: exageration factor (default: 1 = No exageration)
@type factor: float
@param ref: take other eigenvecors from this frame (default: 1)
@type ref: int
@param morph: morph between min and max (1) or take real values (0)
(default: 1)
@type morph: 1|0
@return: Trajectory with frames visualizing the morphing.
@rtype: Trajectory
"""
fit = 1
if self.pc is not None:
fit = self.pc['fit']
pc = self.getPca( fit=fit )
## eigenvectors (rows)
U = pc['u']
## raveled and centered frames
x_avg = N0.average(self.frames, 0)
X = N0.array( [N0.ravel(x) for x in self.frames - x_avg] )
## ev'th eigenvector of reference frame
alpha_0 = N0.dot( X[ref], U[ev] )
## list of deviations of ev'th eigenvector of each frame from ref
alpha_range = N0.dot(X, U[ev]) - alpha_0
## get some representative alphas...
if morph:
a_min = factor * min(alpha_range)
a_max = factor * max(alpha_range)
delta = (a_max - a_min) / steps
alpha_range = [ a_min + i*(delta) for i in range(0, steps) ]
else:
alpha_range = N0.sort( alpha_range )
delta = len(alpha_range) / (steps * 1.0)
alpha_range = [ alpha_range[ int(round( i*delta )) ]
for i in range(0,steps) ]
## scale ev'th eigenvector of ref with different alphas
Y = N0.array( [ X[ref] + alpha * U[ev] for alpha in alpha_range] )
## back convert to N x 3 coordinates
Y = N0.reshape(Y, (Y.shape[0], -1, 3))
Y = x_avg + Y
result = self.__class__()
result.ref = self.ref
result.frames = Y
return result
def calcContacts(self, soln, c):
"""
Calculate contact matrices and fraction of native contacts, residue-
and atom-based, with different distance cutoffs.
@param soln: solution number
@type soln: int
@param c: Complex
@type c: Complex
"""
try:
if self.requested(c,
'fnac_4.5') and self.c_ref_atom_4_5 is not None:
## cache pairwise atom distances for following calculations
contacts = c.atomContacts(4.5,
self.mask_rec,
self.mask_lig,
cache=1,
map_back=0)
ref = N0.ravel(self.c_ref_atom_4_5)
c['fnac_4.5'] = N0.sum( N0.ravel(contacts) * ref )\
/ float( N0.sum(ref))
if self.requested(c, 'fnac_10') and self.c_ref_atom_10 is not None:
contacts = c.atomContacts(10.,
self.mask_rec,
self.mask_lig,
cache=1,
map_back=0)
ref = N0.ravel(self.c_ref_atom_10)
c['fnac_10'] = N0.sum( N0.ravel(contacts) * ref ) \
/ float( N0.sum(ref))
if self.requested(c, 'c_res_4.5') \
or ( self.c_ref_res_4_5 is not None \
and (self.requested(c,'fnrc_4.5','fnSurf_rec'))):
res_cont = c.resContacts(4.5,
cache=self.requested(c, 'c_res_4.5'))
if self.c_ref_res_4_5 is not None \
and self.requested(c, 'fnrc_4.5' ):
ref = N0.ravel(self.c_ref_res_4_5)
c['fnrc_4.5'] = N0.sum(N0.ravel(res_cont)*ref) \
/float(N0.sum(ref))
if self.c_ref_res_4_5 is not None \
and self.requested(c, 'fnSurf_rec'):
r, l = c.fractionNativeSurface(res_cont,
self.c_ref_res_4_5)
c['fnSurf_rec'] = r
c['fnSurf_lig'] = l
except:
m1 = m2 = s = 0
try:
m1, m2, s = c.get('model1',0), c.get('model2',0),\
c.get('soln',0)
except:
pass
self.reportError('contact error (r %i : l %i, #%i)'%\
(m1,m2,s), soln)
def conservationScore(self,
cons_type='cons_ent',
ranNr=150,
log=StdLog(),
verbose=1):
"""
Score of conserved residue pairs in the interaction surface.
Optionally, normalized by radom surface contacts.
@param cons_type: precalculated conservation profile name,
see L{Biskit.PDBDope}.
@type cons_type: str
@param ranNr: number of random matricies to use (default: 150)
@type ranNr: int
@param log: log file [STDOUT]
@type log: Biskit.LogFile
@param verbose: give progress report [1]
@type verbose: bool | int
@return: conservation score
@rtype: float
"""
try:
recCons = self.rec().profile(cons_type, updateMissing=1)
except:
if verbose:
log.add('\n'+'*'*30+'\nNO HHM PROFILE FOR RECEPTOR\n'+\
'*'*30+'\n')
recCons = N0.ones(self.rec().lenResidues())
try:
ligCons = self.lig().profile(cons_type, updateMissing=1)
except:
if verbose:
log.add(\
'\n'+'*'*30+'\nNO HHM PROFILE FOR LIGAND\n'+'*'*30+'\n')
ligCons = N0.ones(self.lig().lenResidues())
if self.rec().profile('surfMask'):
recSurf = self.rec().profile('surfMask')
else:
d = PDBDope(self.rec())
d.addSurfaceMask()
if self.lig().profile('surfMask'):
ligSurf = self.lig().profile('surfMask')
else:
d = PDBDope(self.lig())
d.addSurfaceMask()
surfMask = N0.ravel(N0.outerproduct(recSurf, ligSurf))
missing = N0.outerproduct(N0.equal(recCons, 0), N0.equal(ligCons, 0))
cont = self.resContacts() * N0.logical_not(missing)
consMat = N0.outerproduct(recCons, ligCons)
score = cont * consMat
# get a random score
if ranNr != 0:
if self.verbose:
self.log.write('.')
ranMat = mathUtils.random2DArray(cont, ranNr, mask=surfMask)
random_score = N0.sum(N0.sum(ranMat * consMat)) / (ranNr * 1.0)
return N0.sum(N0.sum(score)) / random_score
else:
return N0.sum(N0.sum(score)) / N0.sum(N0.sum(cont))
