def mixing_frame(V,W,L,frame,rcut=False):
#The total number of frames we are going to look at
#rcut = 19
rcut = 22
k = frame
Same = []
Other = []
print k
for k in range(frame,frame+10):
for i in range(V[k].shape[0]):
Same.append(len(nearest_neighbors_point(V[k],V[k][i],L,rcut)[0]))
Same.append(len(nearest_neighbors_point(W[k],W[k][i],L,rcut)[0]))
Other.append(len(nearest_neighbors_point(W[k],V[k][i],L,rcut)[0]))
Other.append(len(nearest_neighbors_point(V[k],W[k][i],L,rcut)[0]))
hist_same, x_s = histogram_reg(Same,8)
hist_other, x_o = histogram_reg(Other,8)
pyplot.plot_bar(x_o, hist_other, label='other', save=('mix_other%i'%k), showleg=True)
pyplot.plot_bar(x_s, hist_same, label='Same',
save=(('mix_same_frame%i_rcut%.1f')%(k,rcut)), showleg=True,color='r')
def end_end(V,W,M,L):
T=M.cord_auto(['T'])
K=M.cord_auto(['K'])
V=M.cord_auto(['V'])
W=M.cord_auto(['W'])
ndna = T.shape[1]/V.shape[1]
#K-V
#W-T
VK=[]
WT=[]
last = V.shape[0]
#find center-ssdna particle distance
for k in range(last-5,last):
for i in range(V.shape[1]):
for j in range(ndna):
VK.append(points.dist(V[k][i],K[k][j+i*ndna],L)[0]-3)
WT.append(points.dist(W[k][i],T[k][j+i*ndna],L)[0]-3)
hist_K,xK,max_k=histogram(VK,10)
hist_T,xT,max_T=histogram(WT,10)
plt.close()
pyplot.plot_bar(xK,hist_K,save='VK_distance')
plt.close()
pyplot.plot_bar(xT,hist_T,save='WT_distance')
plt.close()
#find the length of the polymer
KT=M.cord_auto(['K','T'])
S=M.cord_auto(['M'])
edge=[]
for k in range(last-5,last):
for i in range(S.shape[1]):
edge.append(points.dist(KT[k][i],S[k][i],L)[0])
hist_edge,xedge,max_edge=histogram(edge,50)
pyplot.plot_bar(xedge,hist_edge,save='polymer_length')
plt.close()
def vac_surround(DV,DW,CV,CW,L):
vacancies = np.zeros((DV.shape[0],1))
#find the vacancies in the simulations
for k in range(len(DW)):
#find the points that are nearest neighbor that are different
index = np.where(DW[k] == 0)[0]
if len(index) > 0:
if len(index) > 1:
print index
index = index[0]
vacancies[k] = index
else:
index = np.where(DV[k] == 0)[0]
if len(index) > 1:
index = index[0]
vacancies[k] = index + DW.shape[1]
#now that we have the indexes lets go back through and pick out where they
#came from
def check(vac, DW, DV):
if vac > DW.shape[0]:
return DV[vac-DW.shape[0]]
else:
return DW[vac]
# find lattice point
def find_lattice(vac, CW, CV):
vac = int(vac[0])
if vac > CW.shape[0]:
return CV[vac-CW.shape[0]]
else:
return CW[vac]
#find the index of the neighbors of the vacancey
def find_neighbors(index, CW, CV, L, cut = 17):
point = find_lattice(index,CW,CV)
V_neighbors = []
W_neighbors = []
for i,j in enumerate(CV):
if points.dist(j,point,L)[0] < cut:
if points.dist(j,point,L)[0] > 1:
V_neighbors.append(i)
for i,j in enumerate(CW):
if points.dist(j,point,L)[0] < cut:
if points.dist(j,point,L)[0] > 1:
W_neighbors.append(i)
return V_neighbors, W_neighbors
#Find out if the neighbors are substitutions or correctly placed
def find_subs(V, W, DW, DV):
subs = []
for i in V:
subs.append(DV[i])
for i in W:
subs.append(DW[i])
return subs
#find the number of substitutions at each step surrounding the vacancy
subs = []
for k in range(len(vacancies)):
V_neigh, W_neigh = find_neighbors(vacancies[k], CW, CV, L)
sub = find_subs(V_neigh, W_neigh, DW[k], DV[k])
count = 0
for i in sub:
if i < 0:
count+=1
subs.append(count)
#find the number of substitutions surrounding a point
#find the time that the vacancy remains there
time = 1
vac = []
for k in range(2,vacancies.shape[0]):
if vacancies[k] == vacancies[k-1]:
time += 1
else:
vac.append([subs[k-1],time,k-1])
time = 1
out = open('vacancy_sub_time_frame','w')
out.write('num subs, time, frame\n')
for i in vac:
out.write(('%i %i %i\n')%(i[0],i[1],i[2]))
out.close()
print vac
#lets make the data accessable. How about trying a histogram
#first sort by numer of substittuioins
d0 = []
d1 = []
d2 = []
d3 = []
d4 = []
for i in vac:
if i[1] > 1:
if i[0] == 3:
d3.append(i[1])
if i[0] == 2:
d2.append(i[1])
if i[0] == 1:
d1.append(i[1])
if i[0] == 0:
d0.append(i[1])
if i[0] == 4:
d4.append(i[1])
print d0
print d1
print d2
print d3
print d4
hist0,x0=histogram_reg(d0,20)
hist1,x1=histogram_reg(d1,20)
hist2,x2=histogram_reg(d2,20)
hist3,x3=histogram_reg(d3,20)
s0 = sum(d0)/float(len(d0))
s1 = sum(d1)/float(len(d1))
s2 = sum(d2)/float(len(d2))
s3 = sum(d3)/float(len(d3))
pyplot.plot_bar([0,1,2,3],[s0,s1,s2,s3],save='vaclife')
plt.close()
pyplot.plot_bar(x0,hist0,save='substitutions0')
plt.close()
util.pickle_dump([d0,d1,d2,d3],'subs_lifetime.pkl')
pyplot.plot_bar(x0,hist0,save='substitutions0')
plt.close()
pyplot.plot_bar(x1,hist1,save='substitutions1')
plt.close()
pyplot.plot_bar(x2,hist2,save='substitutions2')
plt.close()
pyplot.plot_bar(x3,hist3,save='substitutions3')
plt.close()
