def msd_index(VW,L):
k=100
time = 500
surface = util.pickle_load('surface.pkl')
DV = util.pickle_load('DV_s.pkl')
DW = util.pickle_load('DW_s.pkl')
CV = util.pickle_load('CV.pkl')
CW = util.pickle_load('CW.pkl')
defects = []
print DV.shape
print DW.shape
for i in range(DV[k].shape[0]):
if DV[k][i] == -1:
index, d = close_neighbors_point(VW[k],CV[i],L)
defects.append(index)
for i in range(DW[k].shape[0]):
if DW[k][i] == -1:
index, d = close_neighbors_point(VW[k],CW[i],L)
defects.append(index)
print len(defects)
fid = open('large.xyz','r')
M = readxyz.ReadCord(trajectory = 'large.xyz',frames = 777)
crystal = M.cord_auto(['V','W'])
bcc = np.zeros((777,432,1))
for frame in range(bcc.shape[0]):
for i in range(bcc.shape[1]):
if crystal[frame][i][0] > L[0]:
bcc[frame][i]=0
else:
bcc[frame][i]=1
s = []
for i in range(len(bcc[k])):
if surface[k][i]:
s.append(i)
gel = []
for i in range(len(bcc[k])):
if bcc[k][i] ==0 and surface[k][i] == 0:
gel.append(i)
crystal = []
for i in range(len(bcc[k])):
if bcc[k][i] == 1:
crystal.append(i)
#diffuse.index_msd(VW,s,L,time,save='msd_index_%i_surface_%i'%(k,len(s)))
x,msd=diffuse.index_msd(VW,gel,L,time,save='msd_index_%i_gel_%i'%(k,len(gel)))
x2,msd2=diffuse.index_msd(VW,crystal,L,time,save='msd_index_%i_solid_%i'%(k,len(crystal)))
util.pickle_dump([x,msd,x2,msd2],'msd_index.pkl')
#diffuse.index_msd(VW,defects,L,time,save='msd_index_%i_defects_%i'%(k,len(defects)))
#r = list(set(s)-set(defects))
#diffuse.index_msd(VW,r,L,time,save='msd_index_%i_nodefect%i'%(k,len(r)))
#print len(defects)
#print len(s)
import MD.plot.pyplot_eps as pyplot_eps
pyplot_eps.plot2(x,msd,x2,msd2,xlabel='t',ylabel='msd',label1='gel',label2='solid',save='msdgelsolid')
def projection_jump(VW,surface,proj,L,k,save='proj_hist'):
#skip = VW.shape[0]/len(surface)
skip = 1
jump_d = []
print len(surface)
print VW.shape
print proj.shape
try:
for i in surface:
n, dist = close_neighbors_point(proj,VW[i],L)
jump_d.append(dist)
except:
for i in surface:
n, dist = close_neighbors_point(proj,VW[i-VW.shape[0]],L)
jump_d.append(dist)
print jump_d
hist_s,xs=histogram_reg(jump_d,bins=10)
pyplot.plot(xs,hist_s,xlabel='distance',ylabel='count',save=save)
return jump_d
def jump_lattice(VW,L):
reload(diffuse)
k=100
time = 500
surface = util.pickle_load('surface.pkl')
CV = util.pickle_load('CV.pkl')
CW = util.pickle_load('CW.pkl')
DV = util.pickle_load('DV_s.pkl')
DW = util.pickle_load('DW_s.pkl')
defects = []
for i in range(DV[k].shape[0]):
if DV[k][i] == -1:
index, d = close_neighbors_point(VW[k],CV[i],L)
defects.append(index)
for i in range(DW[k].shape[0]):
if DW[k][i] == -1:
index, d = close_neighbors_point(VW[k],CW[i],L)
defects.append(index)
proj = np.zeros((CV.shape[0]*2,CV.shape[1]))
for i in range(CV.shape[0]):
proj[i] = CV[i]
for i in range(CW.shape[0]):
proj[i+CV.shape[0]] = CW[i]
fid = open('large.xyz','r')
M = readxyz.ReadCord(trajectory = 'large.xyz',frames = 777)
crystal = M.cord_auto(['V','W'])
bcc = np.zeros((777,432,1))
for frame in range(bcc.shape[0]):
for i in range(bcc.shape[1]):
if crystal[frame][i][0] > L[0]:
bcc[frame][i]=0
else:
bcc[frame][i]=1
s = []
for i in range(len(bcc[k])):
if surface[k][i]:
s.append(i)
gel = []
for i in range(len(bcc[k])):
if bcc[k][i] ==0 and surface[k][i] == 0:
gel.append(i)
crystal = []
for i in range(len(bcc[k])):
if bcc[k][i] == 1:
crystal.append(i)
diffuse.projection_jump(VW[k],s,proj,L,time,save='msd_index_%i_surface_%i'%(k,len(s)))
diffuse.projection_jump(VW[k][:216],gel[:216],CW,L,time,save='msd_index_%i_gelV_%i'%(k,len(gel)))
diffuse.projection_jump(VW[k][216:],gel[216:],CV,L,time,save='msd_index_%i_gelW_%i'%(k,len(gel)))
diffuse.projection_jump(VW[k],crystal,proj,L,time,save='msd_index_%i_solid_%i'%(k,len(crystal)))
diffuse.projection_jump(VW[k][:216],crystal[:216],CW,L,time,save='msd_index_%i_solidW_%i'%(k,len(crystal)))
for i in range(len(crystal)):
crystal[i] = crystal[i] - CV.shape[0]
diffuse.projection_jump(VW[k][216:],crystal[216:],CV,L,time,save='msd_index_%i_solidV_%i'%(k,len(crystal)))
diffuse.projection_jump(VW[k],defects,proj,L,time,save='msd_index_%i_defects_%i'%(k,len(defects)))
r = list(set(s)-set(defects))
diffuse.projection_jump(VW,r,proj,L,time,save='msd_index_%i_nodefect%i'%(k,len(r)))
print len(defects)
print len(s)
def find_defects_mod(CV,CW,VW,V,W,L,n_finish=1,n_start=0,delta=20,filters=0.2):
from MD.analysis.nearest_neighbor import ws_neighbors_point
from MD.analysis.nearest_neighbor import close_neighbors_point
#######
debug = False
x = np.arange(n_start,n_finish,delta)
lattice = []
for i in range(CV.shape[0]):
lattice.append(int(points.dist(CV[0],CV[i],L)[0]))
for i in range(CW.shape[0]):
lattice.append(int(points.dist(CV[0],CW[i],L)[0]))
points.unique(lattice)
lattice.sort()
print lattice
rmin = lattice[1] / 2.0
rmax = lattice[2] / 2.0 +1
#for interstitial
s = min(W.shape[1],V.shape[1])
#for vacancy
#s = max(W.shape[1],V.shape[1])
DW = np.zeros((len(x),CW.shape[0]))
DV = np.zeros((len(x),CV.shape[0]))
vac_count = np.zeros((len(x),1))
int_count = np.zeros((len(x),1))
fid = open('defects.txt','w')
master = [[],[]]
particle_frame = []
for index,k in enumerate(x):
print 'frame',k
# Identify the points on the bcc Lattice which belong to A and B type
#lets look at one point first
# Assign each point to its place on the lattice
#find the closest point
#####################
N = []
N_V = []
N_W = []
Vn = []
Wn = []
for i in V[k]:
if abs(i[0]) < L[0]:
Vn.append(i)
for i in W[k]:
if abs(i[0]) < L[0]:
Wn.append(i)
print 'Wn',len(Wn)
print 'Vn',len(Vn)
particle_frame.append(len(Wn)+len(Vn))
Wn = np.array(Wn)
Vn = np.array(Vn)
for i in range(CV.shape[0]):
N = ws_neighbors_point(Vn,CV[i],L,i,rmin=rmin,rmax=rmax)[0]
N_V.extend(N)
num = len(N)
if num == 0:
N2 = ws_neighbors_point(Wn,CV[i],L,i,rmin=rmin,rmax=rmax)[0]
N_W.extend(N2)
num = -len(N2)
DV[index][i] = num
###########################
for i in range(CW.shape[0]):
N = ws_neighbors_point(Wn,CW[i],L,i+W.shape[1],rmin=rmin,rmax=rmax)[0]
N_W.extend(N)
num = len(N)
if num == 0:
N2 = ws_neighbors_point(Vn,CW[i],L,i+V.shape[1],rmin=rmin,rmax=rmax)[0]
N_V.extend(N2)
num = -len(N2)
DW[index][i] = num
#find the atoms that haven't been placed on the lattice yet
IV = points.difference(range(Vn.shape[0]),N_V)
IW = points.difference(range(Wn.shape[0]),N_W)
##
if debug:
print 'atoms not added listed after first sorting'
print IV, IW
print DW[index]
print DV[index]
for i in IV:
#find closest lattice point
nw, dw = close_neighbors_point(CW,Vn[i],L)
nv, dv = close_neighbors_point(CV,Vn[i],L)
if dw <= dv:
#check to see if there is already an atom at that point
if DW[index][nw] == 1 or DW[index][nw] == -1:
if DV[index][nv] == 0:
DV[index][nv] = 1
N_V.extend([i])
else:
DW[index][nw] = -2
N_V.extend([i])
if DW[index][nw] == 0:
DW[index][nw] = -1
N_V.extend([i])
#check to see if there is already an atom at that point
else:
if DV[index][nv] == 1 or DV[index][nv] == -1:
#if there isn't one at the other point add it
if DW[index][nw] == 0:
DW[index][nw] = -1
N_V.extend([i])
else:
if DV[index][nv] == 1:
DV[index][nv] = 2
if DV[index][nv] == -1:
DV[index][nv] = -2
N_V.extend([i])
if DV[index][nv] == 0:
DV[index][nv] = 1
N_V.extend([i])
for i in IW:
nw, dw = close_neighbors_point(CW,Wn[i],L)
nv, dv = close_neighbors_point(CV,Wn[i],L)
if dv <= dw:
if DV[index][nv] == 1 or DV[index][nv] == -1:
if DW[index][nw] == 0:
DW[index][nw] = 1
N_W.extend([i])
else:
DV[index][nv] = -2
N_W.extend([i])
if DV[index][nv] == 0:
DV[index][nv] = -1
N_W.extend([i])
else:
if DW[index][nw] == 1 or DW[index][nw] == -1:
if DV[index][nv] == 0:
DV[index][nv] = -1
N_W.extend([i])
else:
DW[index][nw] = 2
N_W.extend([i])
if DW[index][nw] == 0:
DW[index][nw] = 1
N_W.extend([i])
#find the atoms that haven't been placed on the lattice yet
IV = points.difference(range(Vn.shape[0]),N_V)
IW = points.difference(range(Wn.shape[0]),N_W)
##
if debug:
print 'atoms not added list for debugging'
print IV, IW
print DW[index]
print DV[index]
print 'Defect list for lattice'
#print out the vacency, substitutions
def out_defect(A, index, fid, def_list, C=0):
for i in range(A.shape[1]):
if A[index][i] == 0:
pr = 'vacecy at '+ str(i+C)+ '\n'
try:
def_list[0].extend(i+C)
except:
def_list[0].append(i+C)
if debug:
print pr
fid.write(pr)
if A[index][i] == -1:
pr = 'substitution ' + str(i+C)+ '\n'
if debug:
print pr
fid.write(pr)
if A[index][i] == -2:
pr = 'interstitial ' + str(i + C)+ '\n'
try:
def_list[1].extend(i+C)
except:
def_list[1].append(i+C)
if debug:
print pr
fid.write(pr)
if A[index][i] == 2:
pr = 'interstitial ' + str(i + C)+ '\n'
try:
def_list[1].extend(i+C)
except:
def_list[1].append(i+C)
if debug:
print pr
fid.write(pr)
frame = 'Frame ' + str(k) + '\n'
fid.write(frame)
def_list = [[],[]]
out_defect(DV, index, fid, def_list)
out_defect(DW, index, fid, def_list, C = DV.shape[1])
if len(points.difference(def_list[0], master[0])) != 0:
vac_count[index] += len(points.difference(def_list[1],master[1]))
master[0] = def_list[0]
if len(points.difference(def_list[1],master[1])) != 0:
int_count[index] += len(points.difference(def_list[1],master[1]))
master[1] = def_list[1]
#find the atoms that haven't been placed on the lattice yet
IV = points.difference(range(V.shape[1]),N_V)
IW = points.difference(range(W.shape[1]),N_W)
# Identify the defects surrounding each point
#The total number of frames we are going to look at
# Find the number of defects in each frame
count = 0
substitutions = []
vacancies = []
intersticial = []
def count_def(A,check):
count = 0
for i in A:
if i == check:
count +=1
return count
def count_ldef(A,check):
count = 0
for i in A:
if i < check:
count +=1
return count
def count_adef(A,check):
count = 0
for i in A:
if abs(i) == check:
count +=1
return count
for k in range(DW.shape[0]):
#find the points that are nearest neighbor that are different
substitutions.append(count_ldef(DW[k],0)+count_ldef(DV[k],0))
vacancies.append(count_def(DW[k],0)+count_def(DV[k],0))
intersticial.append(count_adef(DW[k],2.0)+count_adef(DV[k],2.0))
print 'substitions'
print substitutions
print 'vacancies'
print vacancies
print 'interstitials'
print intersticial
util.pickle_dump(DV,'DV_s.pkl')
util.pickle_dump(DW,'DW_s.pkl')
util.pickle_dump([substitutions, vacancies, intersticial, x],'plot_def_s.pkl')
pyplot.plot3(x, substitutions, x, particle_frame, x, intersticial,
label1='substitutions',label2='number of particles',label3='intersticial',
save='defects_per_frame_surface',showleg=True)
#pyplot.plot(x, vac_count, save='defect_vac_diffusion_count')
#pyplot.plot(x, int_count, save='defect_int_diffusion_count')
return DV, DW, [substitutions, vacancies, intersticial, x]
