class Snap_Shot(object):
"""
Class defining a snap shot of the trajectory
instance variables: Time_step, Mol_List, Box_Dim, Rg_Dist, E2E_Dist, RDF_Dist
"""
def __init__(self, Time_Step, Mol_List, Box_Dim, Atom_List, N):
self.Time_Step = Time_Step
self.Mol_List = Mol_List
self.Box_Dim = Box_Dim
self.num_Mols = len(Mol_List)
self.Atom_List = Atom_List
self.DistanceMatrix = DistanceMatrix()
self.DistanceMatrix.setPeriodicBound(Box_Dim)
self.numCarbon = 5680.
boxx, boxy, boxz = Box_Dim
return
def showDistanceDistribution(self):
self.DistanceMatrix.showDistanceDistribution()
def pairCorrelation_Hist(self, numbins=200):
# print "Calculating Snapshot Distance Matrix"
for Mol in self.Mol_List:
self.DistanceMatrix.addPoint(Mol.COM())
# print "Finished placing atoms...Calculating Distance Distribution"
self.DistanceMatrix.calculateDistanceDistribution()
# print "returning pyplot"
n, bins = self.DistanceMatrix.pyplotDistanceDistribution(numbins = 200)
print "n is: "
print n
print bins
return n, bins
def Compute_COM(self):
"""
Compute the centers of mass of all the polymer chains
"""
for Mol in self.Mol_List:
Mass_Weighted_Sum = np.zeros(3,dtype=float)
for Atom in Mol.Atom_List:
Atom.unwrapped_position = Atom.position + np.multiply(self.Box_Dim, Atom.image_flags)
Mass_Weighted_Sum += Polymer.Mass[Atom.Type]*Atom.unwrapped_position
Mol.COM = Mass_Weighted_Sum/Mol.MW
return
def Compute_Tangent_Correlation(self):
TangentCorrelation = []
for Mol in self.Mol_List:
MolTangentCorrelation = []
RelevantAtoms = [Atom for Atom in Mol.Atom_List.tolist() if ((Atom.Mass > 2.) and (Atom.Mass < 196))]
# print "mass of second atom is: " + str(Mol.Atom_List[1].Mass)
initialvector = RelevantAtoms[1].position-RelevantAtoms[0].position
initialvector /= np.linalg.norm(initialvector)
lastpos = RelevantAtoms[0].position
for Atom in RelevantAtoms[1:]:
# print "adding new pos: " + str(Atom.position)
newpos = Atom.position
newvector = newpos-lastpos
newvector /= np.linalg.norm(newvector)
# print "tangent correlation is: " + str(self.Tangent_Correlation(latestpos[0],latestpos[1],newpos))
MolTangentCorrelation.append(np.dot(initialvector,newvector))
lastpos =newpos
# print "Mol Tangent Correlation: " + str(np.asarray(MolTangentCorrelation)) + " with mass"
TangentCorrelation.append(np.asarray(MolTangentCorrelation))
TangentCorrelation = np.asarray(TangentCorrelation)
# print "TangentCorrelation is: " + str(TangentCorrelation)
TangentCorrelation = np.mean(TangentCorrelation, axis = 0)
# print "TangentCorrelation is: " + str(TangentCorrelation)
return TangentCorrelation
def carbonDensity_Hist(self, numbins = 200):
Z_pos = []
Z_max = []
theta = []
N = 0
for Mol in self.Mol_List:
mol_z = []
for Atom in Mol.Atom_List:
if Atom.Mass == 12.011:
# print "found Carbon"
N += 1
Z_pos.append(Atom.position[2])
mol_z.append(Atom.position[2])
try:
Z_max.append(np.asarray(mol_z).max())
except:
continue
# Z_max_av = np.asarray(Z_max).mean()
# Z_max_std = np.asarray(Z_max).std()
n, bins = np.histogram(Z_pos, bins= numbins, range=(0.07,0.3))
return n/self.numCarbon, bins*100-7.6
# return Zn, Zbins, Z_max_av, Z_max_std
def get_net_dipole(self, molclass, molName):
# partial_charges = OPLS.get_partial_charges(molclass, molName)
partial_charges = [(0,.32), (0,-.64)]
print partial_charges
net_dipole = np.zeros(3)
# print pc
# splicing out gold surface
for mol in self.Mol_List:
for atom in mol.Atom_List:
if atom.Element == "Au":
continue
else:
partial_charge = partial_charges[atom.Type-1][1]
# print atom.position
# print partial_charge
dipole_moment = partial_charge*atom.position
# print dipole_moment
net_dipole = net_dipole+dipole_moment
mol.dipoleMoment = mol.dipoleMoment+dipole_moment
print "Net dipole is: ..." + str(net_dipole)
# return net_dipole
# for mol in self.Mol_List[:-1]:
# if (np.dot(mol.dipoleMoment,net_dipole)/(np.linalg.norm(mol.dipoleMoment)*np.linalg.norm(net_dipole)) < -.9):
# print "alert!"
# print mol.dipoleMoment
# for atom in mol.Atom_List:
# print atom.Element, str(atom.position)
# # print net_dipole
# break
plt.hist([np.dot(mol.dipoleMoment,net_dipole)/(np.linalg.norm(mol.dipoleMoment)*np.linalg.norm(net_dipole)) for mol in self.Mol_List[:-1]], bins=100)
print os.getcwd()
plt.savefig(molclass+"_"+molName+"_dipoleDistribution.png")
print "saved!"
plt.clf()
return net_dipole
