def compareTransformed(coords1, coords2, x1, x2, M):
# the lattice matrix
ml1 = lattice.lowerTriangular(coords1.lattice)
ml2 = lattice.lowerTriangular(coords2.lattice)
# the inerse lattice matrix
iml2 = vec3.invert3x3(ml2)
for i in xrange(coords1.nrigid):
ptest = coords1.rotRigid[i]
ptrans = rotations.mx2aa(rotations.np.dot(M, rotations.aa2mx(ptest)))
for d in [np.zeros(3),[0.,1.,0.],[0.,1.,0.],[0.,0.,1.]]:
xtest = coords1.posRigid[i] + np.array(d) - x1
xtrans = np.dot(iml2, np.dot(M, np.dot(ml1, xtest)))
match = False
for j in xrange(coords1.nrigid):
dx = coords2.posRigid[j] - xtrans - x2
dx = dx - np.floor(dx)
dx[dx>0.8]-=1.0
dp = rotations.mx2aa(np.dot(vec3.invert3x3(rotations.aa2mx(ptrans)),rotations.aa2mx(coords2.rotRigid[j])))
match = np.linalg.norm(np.dot(ml2, dx)) < tol_shift \
and np.linalg.norm(dp) < tol_rot
if(match):
break
if(not match):
return False
return True
def has_overlap(coords, cutoff=1.0):
ml = lattice.lowerTriangular(coords[-6:])
natoms = coords.size/3-2
atoms = coords.reshape(coords.size/3,3)[:-2]
# mi = vec3.invert3x3(ml)
mindist = 1000.
a = ml[:,0]
b = ml[:,1]
c = ml[:,2]
for i in xrange(natoms):
for j in xrange(i+1,natoms):
#d = np.dot(mi, atoms[i] - atoms[j])
#d -= np.floor(d)
#d[d>0.5] -= 1.
#r_ij = np.linalg.norm(np.dot(ml, d))
r_i = atoms[i]
r_j = atoms[j]
r_tp = r_j - r_i;
r_dp = r_tp - c*int(r_tp[2]/c[2])
r_sp = r_dp - b*int(r_dp[1]/b[1])
r_ij = r_sp - a*int(r_sp[0]/a[0])
r = np.linalg.norm(r_ij)
if(r < cutoff):
# print "overlapping distance is", r
return True
mindist = min(mindist, r)
#print "the minimum distance ist", mindist
return False
