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Mol.py
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Mol.py
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from Util import *
import numpy as np
import random
class Mol:
""" Provides a general purpose molecule"""
def __init__(self, atoms_ = None, coords_ = None, mbe_order_ =5):
if (atoms_!=None):
self.atoms = atoms_
else:
self.atoms = np.zeros(1,dtype=np.uint8)
if (coords_!=None):
self.coords = coords_
else:
self.coords=np.zeros(shape=(1,1),dtype=np.float)
self.properties = {"MW":0}
self.name=None
#things below here are sometimes populated if it is useful.
self.PESSamples = [] # a list of tuples (atom, new coordinates, energy) for storage.
self.ecoords = None # equilibrium coordinates.
self.DistMatrix = None # a list of equilbrium distances, for GO-models.
self.mbe_order = mbe_order_
self.mbe_frags=dict() # list of frag of each order N, dic['N'=list of frags]
self.dist_mbe_frags=dict() # list of far away frag of each order N, dic['N'=list of frags], use limiting formula scale into the cutoff and calculate they
self.mbe_frags_deri=dict()
self.mbe_permute_frags=dict() # list of all the permuted frags
self.mbe_frags_energy=dict() # MBE energy of each order N, dic['N'= E_N]
self.energy=None
self.mbe_energy=dict() # sum of MBE energy up to order N, dic['N'=E_sum]
self.mbe_deri =None
self.nn_energy=None
return
def Reset_Frags(self):
self.mbe_frags=dict() # list of frag of each order N, dic['N'=list of frags]
self.mbe_frags_deri=dict()
self.mbe_permute_frags=dict() # list of all the permuted frags
self.mbe_frags_energy=dict() # MBE energy of each order N, dic['N'= E_N]
self.energy=None
self.mbe_energy=dict() # sum of MBE energy up to order N, dic['N'=E_sum]
self.mbe_deri =None
self.nn_energy=None
return
def AtomName(self, i):
return atoi.keys()[atoi.values().index(self.atoms[i])]
def AllAtomNames(self):
names=[]
for i in range (0, self.atoms.shape[0]):
names.append(atoi.keys()[atoi.values().index(self.atoms[i])])
return names
def IsIsomer(self,other):
return np.array_equals(np.sort(self.atoms),np.sort(other.atoms))
def NAtoms(self):
return self.atoms.shape[0]
def AtomsWithin(self,rad, pt):
# Returns indices of atoms within radius of point.
dists = map(lambda x: np.linalg.norm(x-pt),self.coords)
return [i for i in range(self.NAtoms()) if dists[i]<rad]
def NumOfAtomsE(self, at):
return sum( [1 if e==at else 0 for e in self.atoms ] )
def Rotate(self,axis,ang):
rm=RotationMatrix(axis,ang)
crds=np.copy(self.coords)
for i in range(len(self.coords)):
self.coords[i] = np.dot(rm,crds[i])
def MoveToCenter(self):
first_atom = (self.coords[0]).copy()
for i in range (0, self.NAtoms()):
self.coords[i] = self.coords[i] - first_atom
def AtomsWithin(self, SensRadius, coord):
''' Returns atoms within the sensory radius in sorted order. '''
satoms=np.arange(0,self.NAtoms())
diffs= self.coords-coord
dists= np.power(np.sum(diffs*diffs,axis=1),0.5)
idx=np.argsort(dists)
mxidx = len(idx)
for i in range(self.NAtoms()):
if (dists[idx[i]] >= SensRadius):
mxidx=i
break
return idx[:mxidx]
def WriteXYZfile(self, fpath=".", fname="mol"):
if (os.path.isfile(fpath+"/"+fname+".xyz")):
f = open(fpath+"/"+fname+".xyz","a")
else:
f = open(fpath+"/"+fname+".xyz","w")
natom = self.atoms.shape[0]
f.write(str(natom)+"\n\n")
for i in range (0, natom):
atom_name = atoi.keys()[atoi.values().index(self.atoms[i])]
f.write(atom_name+" "+str(self.coords[i][0])+ " "+str(self.coords[i][1])+ " "+str(self.coords[i][2])+"\n")
f.write("\n\n")
f.close()
def Distort(self,seed=0,disp=0.35):
''' Randomly distort my coords, but save eq. coords first '''
self.BuildDistanceMatrix()
random.seed(seed)
for i in range (0, self.atoms.shape[0]):
for j in range (0, 3):
self.coords[i,j] = self.coords[i,j] + disp*random.uniform(-1, 1)
def AtomTypes(self):
return np.unique(self.atoms)
def ReadGDB9(self,path,mbe_order=3):
try:
f=open(path,"r")
lines=f.readlines()
natoms=int(lines[0])
self.mbe_order=mbe_order
self.atoms.resize((natoms))
self.coords.resize((natoms,3))
for i in range(natoms):
line = lines[i+2].split()
self.atoms[i]=AtomicNumber(line[0])
try:
self.coords[i,0]=float(line[1])
except:
self.coords[i,0]=scitodeci(line[1])
try:
self.coords[i,1]=float(line[2])
except:
self.coords[i,1]=scitodeci(line[2])
try:
self.coords[i,2]=float(line[3])
except:
self.coords[i,2]=scitodeci(line[3])
f.close()
except Exception as Ex:
print "Read Failed.", Ex
raise Ex
return
def FromXYZString(self,string):
lines = string.split("\n")
natoms=int(lines[1])
self.atoms.resize((natoms))
self.coords.resize((natoms,3))
for i in range(natoms):
line = lines[i+3].split()
self.atoms[i]=AtomicNumber(line[0])
try:
self.coords[i,0]=float(line[1])
except:
self.coords[i,0]=scitodeci(line[1])
try:
self.coords[i,1]=float(line[2])
except:
self.coords[i,1]=scitodeci(line[2])
try:
self.coords[i,2]=float(line[3])
except:
self.coords[i,2]=scitodeci(line[3])
return
def NEle(self):
return np.sum(self.atoms)
def XYZtoGridIndex(self, xyz, ngrids = 250,padding = 2.0):
Max = (self.coords).max() + padding
Min = (self.coords).min() - padding
binsize = (Max-Min)/float(ngrids-1)
x_index = math.floor((xyz[0]-Min)/binsize)
y_index = math.floor((xyz[1]-Min)/binsize)
z_index = math.floor((xyz[2]-Min)/binsize)
# index=int(x_index+y_index*ngrids+z_index*ngrids*ngrids)
return x_index, y_index, z_index
def MolDots(self, ngrids = 250 , padding =2.0, width = 2):
grids = self.MolGrids()
for i in range (0, self.atoms.shape[0]):
x_index, y_index, z_index = self.XYZtoGridIndex(self.coords[i])
for m in range (-width, width):
for n in range (-width, width):
for k in range (-width, width):
index = (x_index)+m + (y_index+n)*ngrids + (z_index+k)*ngrids*ngrids
grids[index] = atoc[self.atoms[i]]
return grids
def Center(self):
''' Returns the center of atom'''
return np.average(self.coords,axis=0)
def rms(self, m):
err = 0.0
for i in range (0, (self.coords).shape[0]):
err += (np.sum((m.coords[i] - self.coords[i])**2))**0.5
return err/float((self.coords).shape[0])
def MolGrids(self, ngrids = 250):
grids = np.zeros((ngrids, ngrids, ngrids), dtype=np.uint8)
grids = grids.reshape(ngrids**3) #kind of ugly, but lets keep it for now
return grids
def SpanningGrid(self,num=250,pad=4.):
''' Returns a regular grid the molecule fits into '''
xmin=np.min(self.coords[:,0])-pad
xmax=np.max(self.coords[:,0])+pad
ymin=np.min(self.coords[:,1])-pad
ymax=np.max(self.coords[:,1])+pad
zmin=np.min(self.coords[:,2])-pad
zmax=np.max(self.coords[:,2])+pad
grids = np.mgrid[xmin:xmax:num*1j, ymin:ymax:num*1j, zmin:zmax:num*1j]
grids = grids.transpose()
grids = grids.reshape((grids.shape[0]*grids.shape[1]*grids.shape[2], grids.shape[3]))
return grids, (xmax-xmin)*(ymax-ymin)*(zmax-zmin)
def AddPointstoMolDots(self, grids, points, value, ngrids =250): # points: x,y,z,prob prob is in (0,1)
points = points.reshape((-1,3)) # flat it
value = value.reshape(points.shape[0]) # flat it
value = value/value.max()
for i in range (0, points.shape[0]):
x_index, y_index, z_index = self.XYZtoGridIndex(points[i])
index = x_index + y_index*ngrids + z_index*ngrids*ngrids
if grids[index] < int(value[i]*250):
grids[index] = int(value[i]*250)
return grids
def GridstoRaw(self, grids, ngrids=250, save_name="mol", save_path ="./densities/"):
if (save_name=="mol" and self.name != None):
save_name=self.name
grids = np.array(grids, dtype=np.uint8)
print "Saving density to:",save_path+save_name+".raw"
f = open(save_path+save_name+".raw", "wb")
f.write(bytes(np.array([ngrids,ngrids,ngrids],dtype=np.uint8).tostring())+bytes(grids.tostring()))
f.close()
def Generate_All_MBE_term(self, atom_group=1, cutoff=10, center_atom=0):
for i in range (1, self.mbe_order+1):
self.Generate_MBE_term(i, atom_group, cutoff, center_atom)
return
def Generate_MBE_term(self, order, atom_group=1, cutoff=10, center_atom=0):
if order in self.mbe_frags.keys():
print ("MBE order", order, "already generated..skipping..")
return 0
if (self.coords).shape[0]%atom_group!=0:
raise Exception("check number of group size")
else:
ngroup = (self.coords).shape[0]/atom_group
xyz=((self.coords).reshape((ngroup, atom_group, -1))).copy() # cluster/molecule needs to be arranged with molecule/sub_molecule
ele=((self.atoms).reshape((ngroup, atom_group))).copy()
mbe_terms=[]
mbe_terms_num=0
mbe_dist=[]
atomlist=list(range(0,ngroup))
dist_mbe_terms = []
dist_mbe_terms_num = 0
dist_mbe_dist = []
if order < 1 :
raise Exception("MBE Order Should be Positive")
else:
time_log = time.time()
print ("generating the combinations..")
combinations=list(itertools.combinations(atomlist,order))
print ("finished..takes", time_log-time.time(),"second")
time_now=time.time()
flag = np.zeros(1)
max_case = 5000 # set max cases for debug
dist_max_case = 5000 # set max distance cases for debug
for i in range (0, len(combinations)):
term = list(combinations[i])
pairs=list(itertools.combinations(term, 2))
saveindex=[]
dist = [10000000]*len(pairs)
# flag = 1
# for j in range (0, len(pairs)):
# m=pairs[j][0]
# n=pairs[j][1]
# #dist[j] = np.linalg.norm(xyz[m]-xyz[n])
# dist[j]=((xyz[m][center_atom][0]-xyz[n][center_atom][0])**2+(xyz[m][center_atom][1]-xyz[n][center_atom][1])**2+(xyz[m][center_atom][2]-xyz[n][center_atom][2])**2)**0.5
# if dist[j] > cutoff:
# flag = 0
# break
# if flag == 1:
flag[0]=1
npairs=len(pairs)
code="""
for (int j=0; j<npairs; j++) {
int m = pairs[j][0];
int n = pairs[j][1];
dist[j] = sqrt(pow(xyz[m*atom_group*3+center_atom*3+0]-xyz[n*atom_group*3+center_atom*3+0],2)+pow(xyz[m*atom_group*3+center_atom*3+1]-xyz[n*atom_group*3+center_atom*3+1],2)+pow(xyz[m*atom_group*3+center_atom*3+2]-xyz[n*atom_group*3+center_atom*3+2],2));
if (float(dist[j]) > cutoff) {
flag[0] = 0;
}
}
"""
res = inline(code, ['pairs','npairs','center_atom','dist','xyz','flag','cutoff','atom_group'],headers=['<math.h>','<iostream>'], compiler='gcc')
if flag[0]==1: # end of weave
if mbe_terms_num%100==0:
#print mbe_terms_num, time.time()-time_now
time_now= time.time()
mbe_terms_num += 1
mbe_terms.append(term)
mbe_dist.append(dist)
if mbe_terms_num >= max_case: # just for generating training case
break;
else:
dist_mbe_terms_num += 1
dist_mbe_terms.append(term)
dist_mbe_dist.append(dist)
if dist_mbe_terms_num >= dist_max_case:
break
mbe_frags = []
for i in range (0, mbe_terms_num):
tmp_atom = np.zeros(order*atom_group)
tmp_coord = np.zeros((order*atom_group, 3))
for j in range (0, order):
tmp_atom[atom_group*j:atom_group*(j+1)] = ele[mbe_terms[i][j]]
tmp_coord[atom_group*j:atom_group*(j+1)] = xyz[mbe_terms[i][j]]
tmp_mol = Frag(tmp_atom, tmp_coord, mbe_terms[i], mbe_dist[i], atom_group, cutoff, center_atom)
mbe_frags.append(tmp_mol)
self.mbe_frags[order]=mbe_frags
dist_mbe_frags = []
for i in range (0, dist_mbe_terms_num):
tmp_atom = np.zeros(order*atom_group)
tmp_coord = np.zeros((order*atom_group, 3))
for j in range (0, order):
tmp_atom[atom_group*j:atom_group*(j+1)] = ele[dist_mbe_terms[i][j]]
tmp_coord[atom_group*j:atom_group*(j+1)] = xyz[dist_mbe_terms[i][j]]
tmp_mol = Frag(tmp_atom, tmp_coord, dist_mbe_terms[i], dist_mbe_dist[i], atom_group, cutoff, center_atom, True)
dist_mbe_frags.append(tmp_mol)
self.dist_mbe_frags[order]=dist_mbe_frags
print "generated {:10d} terms for order {:d}".format(len(mbe_frags), order)
return
def Calculate_Frag_Energy(self, order):
if order in self.mbe_frags_energy.keys():
print ("MBE order", order, "already calculated..skipping..")
return 0
mbe_frags_energy = 0.0
fragnum=0
time_log=time.time()
max_case = 5000 # set max_case for debug
print "length of order ", order, ":",len(self.mbe_frags[order])
for frag in self.mbe_frags[order][0:max_case]: # just for generating the training set..
fragnum +=1;
print "doing the ",fragnum
frag.PySCF_Frag_MBE_Energy_All()
frag.Set_Frag_MBE_Energy()
mbe_frags_energy += frag.frag_mbe_energy
print "Finished, spent ", time.time()-time_log," seconds"
time_log = time.time()
self.mbe_frags_energy[order] = mbe_frags_energy
return 0
def Calculate_All_Frag_Energy(self): # we ignore the 1st order for He here
for i in range (2, self.mbe_order+1):
print "calculating for MBE order", i
self.Calculate_Frag_Energy(i)
print "mbe_frags_energy", self.mbe_frags_energy
return 0
def Set_MBE_Energy(self):
for i in range (1, self.mbe_order+1):
self.mbe_energy[i] = 0.0
for j in range (1, i+1):
self.mbe_energy[i] += self.mbe_frags_energy[j]
return 0.0
def MBE(self, atom_group=1, cutoff=10, center_atom=0):
self.Generate_All_MBE_term(atom_group, cutoff, center_atom)
self.Calculate_All_Frag_Energy()
self.Set_MBE_Energy()
print self.mbe_frags_energy
return 0
def PySCF_Energy(self):
mol = gto.Mole()
pyscfatomstring=""
for j in range(len(self.atoms)):
s = self.coords[j]
pyscfatomstring=pyscfatomstring+str(self.AtomName(j))+" "+str(s[0])+" "+str(s[1])+" "+str(s[2])+(";" if j!= len(self.atoms)-1 else "")
mol.atom = pyscfatomstring
mol.basis = 'cc-pvqz'
mol.verbose = 0
try:
mol.build()
mf=scf.RHF(mol)
hf_en = mf.kernel()
mp2 = mp.MP2(mf)
mp2_en = mp2.kernel()
en = hf_en + mp2_en[0]
self.energy = en
return en
except Exception as Ex:
print "PYSCF Calculation error... :",Ex
print "Mol.atom:", mol.atom
print "Pyscf string:", pyscfatomstring
return 0.0
#raise Ex
return 0.0
def Get_Permute_Frags(self):
self.mbe_permute_frags=dict()
for order in self.mbe_frags.keys():
self.mbe_permute_frags[order]=list()
for frags in self.mbe_frags[order]:
self.mbe_permute_frags[order] += frags.Permute_Frag()
print "length of permuted frags:", len(self.mbe_permute_frags[order]),"order:", order
return
def Set_Frag_Force_with_Order(self, cm_deri, nn_deri, order):
self.mbe_frags_deri[order]=np.zeros((self.NAtoms(),3))
atom_group = self.mbe_frags[order][0].atom_group # get the number of atoms per group by looking at the frags.
for i in range (0, len(self.mbe_frags[order])):
deri = self.mbe_frags[order][i].Frag_Force(cm_deri[i], nn_deri[i])
index_list = self.mbe_frags[order][i].index
for j in range (0, len(index_list)):
self.mbe_frags_deri[order][index_list[j]*atom_group:(index_list[j]+1)*atom_group] += deri[j]
#print "derviative from order ",order, self.mbe_frags_deri[order]
return
def Set_MBE_Force(self):
self.mbe_deri = np.zeros((self.NAtoms(), 3))
for order in range (2, self.mbe_order+1): # we ignore the 1st order term since we are dealing with helium
if order in self.mbe_frags_deri.keys():
self.mbe_deri += self.mbe_frags_deri[order]
return self.mbe_deri
class Frag(Mol):
""" Provides a MBE frag of general purpose molecule"""
def __init__(self, atoms_ = None, coords_ = None, index_=None, dist_=None, atom_group_=1, cutoff_=10, center_atom_=0, scale_=False):
Mol.__init__(self, atoms_, coords_)
self.center_atom = center_atom_
self.atom_group = atom_group_
self.FragOrder = self.coords.shape[0]/self.atom_group
if (index_!=None):
self.index = index_
else:
self.index = None
if (dist_!=None):
self.dist = dist_
else:
self.dist = None
self.frag_mbe_energies=dict()
self.cutoff = cutoff_
self.scale = scale_
self.scale_factor = 1
if self.scale:
self.Scale_Frag()
self.frag_mbe_energy = None
self.permute_index = range (0, self.FragOrder)
return
def Diople_Diople_Scale(self):
max_dist = max(self.dist)
self.scale_factor = pow(self.cutoff / max_dist,3)
center_of_center = (self.coords[self.center_atom]+self.coords[self.center_atom+self.atom_group])/2
tmp_coords = np.zeros((self.coords.shape[0],3))
for i in range (0, self.FragOrder):
move_vector = center_of_center - self.coords[self.center_atom + self.atom_group*i]
move_vector = (1-self.cutoff / max_dist)*move_vector
for j in range (0, self.atom_group):
tmp_coords[i*self.atom_group + j] = self.coords[i*self.atom_group+j] + move_vector
self.coords = tmp_coords.copy()
return
def Axilrod_Teller_Scale(self):
max_dist = max(self.dist)
self.scale_factor = pow(self.cutoff/max_dist, 9)
center_of_center = (self.coords[self.center_atom]+self.coords[self.center_atom+self.atom_group]+self.coords[self.center_atom+self.atom_group*2])/3
tmp_coords = np.zeros((self.coords.shape[0],3))
for i in range (0, self.FragOrder):
move_vector = center_of_center - self.coords[self.center_atom + self.atom_group*i]
move_vector = (1-self.cutoff / max_dist)*move_vector
for j in range (0, self.atom_group):
tmp_coords[i*self.atom_group + j] = self.coords[i*self.atom_group+j] + move_vector
self.coords = tmp_coords.copy()
return
def Scale_Frag(self): # only included the limiting formula for 2nd order (diople-diople interatcion), and 3rd order (Axilrod-Teller Potential)
if (self.FragOrder == 2): # scale as 1/r^3
self.Diople_Diople_Scale()
elif (self.FragOrder == 3): # scale as 1/(r1r2r3)^3
self.Axilrod_Teller_Scale()
else:
self.scale_factor = 0 # no limiting formula for order larger than 3rd
return
def PySCF_Frag_MBE_Energy(self,order): # calculate the MBE of order N of each frag
inner_index = range(0, self.FragOrder)
real_frag_index=list(itertools.combinations(inner_index,order))
ghost_frag_index=[]
for i in range (0, len(real_frag_index)):
ghost_frag_index.append(list(set(inner_index)-set(real_frag_index[i])))
i =0
while(i< len(real_frag_index)):
# for i in range (0, len(real_frag_index)):
pyscfatomstring=""
mol = gto.Mole()
for j in range (0, order):
for k in range (0, self.atom_group):
s = self.coords[real_frag_index[i][j]*self.atom_group+k]
pyscfatomstring=pyscfatomstring+str(self.AtomName(real_frag_index[i][j]*self.atom_group+k))+" "+str(s[0])+" "+str(s[1])+" "+str(s[2])+";"
for j in range (0, self.FragOrder - order):
for k in range (0, self.atom_group):
s = self.coords[ghost_frag_index[i][j]*self.atom_group+k]
pyscfatomstring=pyscfatomstring+"GHOST"+str(j*self.atom_group+k)+" "+str(s[0])+" "+str(s[1])+" "+str(s[2])+";"
pyscfatomstring=pyscfatomstring[:-1]+" "
mol.atom =pyscfatomstring
mol.basis ={}
ele_set = list(set(self.AllAtomNames()))
for ele in ele_set:
mol.basis[str(ele)]="cc-pvqz"
for j in range (0, self.FragOrder - order):
for k in range (0, self.atom_group):
atom_type = self.AtomName(ghost_frag_index[i][j]*self.atom_group+k)
mol.basis['GHOST'+str(j*self.atom_group+k)]=gto.basis.load('cc-pvqz',str(atom_type))
mol.verbose=0
try:
print "doing case ", i
time_log = time.time()
mol.build()
mf=scf.RHF(mol)
hf_en = mf.kernel()
mp2 = mp.MP2(mf)
mp2_en = mp2.kernel()
en = hf_en + mp2_en[0]
#print "hf_en", hf_en, "mp2_en", mp2_en[0], " en", en
self.frag_mbe_energies[LtoS(real_frag_index[i])]=en
print ("pyscf time..", time.time()-time_log)
i = i+1
gc.collect()
except Exception as Ex:
print "PYSCF Calculation error... :",Ex
print "Mol.atom:", mol.atom
print "Pyscf string:", pyscfatomstring
return
def PySCF_Frag_MBE_Energy_All(self):
for i in range (0, self.FragOrder):
self.PySCF_Frag_MBE_Energy(i+1)
return
def Set_Frag_MBE_Energy(self):
self.frag_mbe_energy = self.Frag_MBE_Energy()
self.frag_mbe_energy = self.frag_mbe_energy * self.scale_factor
#prod = 1
#for i in self.dist:
# prod = i*prod
#print "self.frag_mbe_energy", self.frag_mbe_energy
return
def Frag_MBE_Energy(self, index=None): # Get MBE energy recursively
if index==None:
index=range(0, self.FragOrder)
order = len(index)
if order==0:
return
energy = self.frag_mbe_energies[LtoS(index)]
for i in range (0, order):
sub_index = list(itertools.combinations(index, i))
for j in range (0, len(sub_index)):
energy=energy-self.Frag_MBE_Energy( sub_index[j])
return energy
def CopyTo(self, target):
target.FragOrder = self.FragOrder
target.frag_mbe_energies=self.frag_mbe_energies
target.frag_mbe_energy = self.frag_mbe_energy
target.permute_index = self.permute_index
def Permute_Frag_by_Index(self, index):
new_frag = Frag( atoms_ = self.atoms, coords_ = self.coords, index_= self.index, dist_=self.dist, atom_group_=self.atom_group)
self.CopyTo(new_frag)
new_frag.permute_index = index
new_frag.coords=new_frag.coords.reshape((new_frag.FragOrder, new_frag.atom_group, -1))
new_frag.coords = new_frag.coords[new_frag.permute_index]
new_frag.coords = new_frag.coords.reshape((new_frag.FragOrder*new_frag.atom_group, -1))
new_frag.atoms = new_frag.atoms.reshape((new_frag.FragOrder, new_frag.atom_group))
new_frag.atoms = new_frag.atoms[new_frag.permute_index]
new_frag.atoms = new_frag.atoms.reshape(new_frag.FragOrder*new_frag.atom_group)
# needs some code that fix the keys in frag_mbe_energies[LtoS(index)] after permutation in futher. KY
return new_frag
def Permute_Frag(self):
permuted_frags=[]
indexs=list(itertools.permutations(range(0, self.FragOrder)))
for index in indexs:
permuted_frags.append(self.Permute_Frag_by_Index(list(index)))
return permuted_frags
def Frag_Force(self, cm_deri, nn_deri):
return self.Combine_CM_NN_Deri(cm_deri, nn_deri)
def Combine_CM_NN_Deri(self, cm_deri, nn_deri):
natom = self.NAtoms()
frag_deri = np.zeros((natom, 3))
for i in range (0, natom):
for j in range (0, natom):
if j >= i:
cm_dx = cm_deri[i][j][0]
cm_dy = cm_deri[i][j][1]
cm_dz = cm_deri[i][j][2]
nn_deri_index = i*(natom+natom-i+1)/2 + (j-i)
nn_dcm = nn_deri[nn_deri_index]
else:
cm_dx = cm_deri[j][i][3]
cm_dy = cm_deri[j][i][4]
cm_dz = cm_deri[j][i][5]
nn_deri_index = j*(natom+natom-j+1)/2 + (i-j)
nn_dcm = nn_deri[nn_deri_index]
frag_deri[i][0] += nn_dcm * cm_dx
frag_deri[i][1] += nn_dcm * cm_dy
frag_deri[i][2] += nn_dcm * cm_dz
return frag_deri