def species_mixing(V,W,L,n_finish=1,n_start=0,delta=100,rcut=False):
#The total number of frames we are going to look at
if rcut == False:
rcut=min_particle_distance(V[-1:],W[-1:],L)+6
print rcut
#rcut = 19
rcut = 22
n_frames = (n_finish-n_start)/delta
x = np.arange(n_start,n_finish,delta)
s = []
o = []
for k in x:
Same = 0
Other = 0
print k
for i in range(V[k].shape[0]):
Same += len(nearest_neighbors_point(V[k],V[k][i],L,rcut)[0])
Same += len(nearest_neighbors_point(W[k],W[k][i],L,rcut)[0])
Other += len(nearest_neighbors_point(W[k],V[k][i],L,rcut)[0])
Other += len(nearest_neighbors_point(V[k],W[k][i],L,rcut)[0])
s.append(float(Same)/(W[k].shape[0]+V[k].shape[0]))
o.append(float(Other)/(V[k].shape[0]+W[k].shape[0]))
print s
print o
util.pickle_dump([x,s,o],'mix.pkl')
pyplot.plot2(x, s, x, o, label1='Same',
label2='other', save=('mixing_avg_cut%.1f'%rcut), showleg=True)
def int_type(V, W, DV, DW, CV, CW, L):
#find the two nearest points in the system
#and record their type
def find_nearest(point, A, B, L):
smallA = 100
smallB = 100
typeA = 'G'
typeB = 'G'
for i in range(A.shape[0]):
d = points.dist(point,A[i],L)[0]
if d < smallB:
smallA = smallB
typeA =typeB
smallB = d
typeB = 'A'
else:
if smallA < d:
smallA = d
typeA = 'A'
for i in range(B.shape[0]):
d = points.dist(point,B[i],L)[0]
if d < smallB:
smallA = smallB
typeA =typeB
smallB = d
typeB = 'B'
else:
if smallA < d:
smallA = d
typeA = 'B'
return [typeA,typeB]
totaldiff = []
totalsame =[]
for k in range(DV.shape[0]):
print k
types = []
for i in range(DV.shape[1]):
#if it is an interstitial, look for the 2 closests points
if abs(DV[k][i]) == 2:
types.append(find_nearest(CV[i],V[k],W[k],L))
for i in range(DW.shape[1]):
if abs(DW[k][i]) == 2:
types.append(find_nearest(CW[i],V[k],W[k],L))
different = 0
same = 0
for i in types:
if i[0] == i[1]:
different += 1
else:
same += 1
totaldiff.append(different)
totalsame.append(same)
print totaldiff
print totalsame
x = range(V.shape[0])
pyplot.plot2(x,totaldiff,x,totalsame,label1='different',label2='same',showleg=True,xlabel='Time',ylabel='interstistials',save='int_type')
def end_end_connected(M,L): #find the length of the polymer
## \brief end to end distance of hybridized vs nonhybridized polymers
#
# \returns average distance from start to end of polymer
# for hybridizations and free polymer
#
# \param M - ReadCord Class
# \param L
#
# V ----- A C k
# W ----- F G T
import MD.analysis.connections as con
try:
K=util.pickle_load('K.pkl')
T=util.pickle_load('T.pkl')
S=util.pickle_load('S.pkl')
except:
K=M.cord_auto(['K'])
T=M.cord_auto(['T'])
S=M.cord_auto(['M'])
util.pickle_dump(K,'K.pkl')
util.pickle_dump(T,'T.pkl')
util.pickle_dump(S,'S.pkl')
#get connections
con = _connections(M)
h_sum = []
f_sum = []
for k in range(len(con)):
print k
hybrid = []
free = []
#get the points that are not connected
for i in range(K.shape[1]):
if i in con[k][0]:
hybrid.append(points.dist(K[k][i],S[k][i],L[k])[0]+0.5)
else:
free.append(points.dist(K[k][i],S[k][i],L[k])[0]+0.5)
for i in range(T.shape[1]):
if i in con[k][1]:
hybrid.append(points.dist(T[k][i],S[k][i+K.shape[1]],L[k])[0]+0.5)
else:
free.append(points.dist(T[k][i],S[k][i+K.shape[1]],L[k])[0]+0.5)
print hybrid
h_sum.append(sum(hybrid)/len(hybrid))
f_sum.append(sum(free)/len(free))
f_sum[-1]= f_sum[-2]
h_sum[-1]= h_sum[-2]
x = range(S.shape[0])
pyplot.plot2(x,h_sum,x,f_sum,xlabel='timestep',ylabel='sigma',label1='hybridizations',
label2='free',save='free_hybrid_end_end_connections',showleg='true')
def center_end_connected(M,L):
## \brief center to end distance of hybridized vs nonhybridized polymers
#
# \returns average distance from center of particle to end of polymer
# for hybridizations and free polymer
#
# \param M - ReadCord Class
# \param L
#
# V ----- A C k
# W ----- F G T
#find the length of the polymer
import MD.analysis.connections as con
try:
K=util.pickle_load('K.pkl')
T=util.pickle_load('T.pkl')
V=util.pickle_load('V.pkl')
W=util.pickle_load('W.pkl')
except:
V=M.cord_auto(['V'])
W=M.cord_auto(['W'])
K=M.cord_auto(['K'])
T=M.cord_auto(['T'])
util.pickle_dump(K,'K.pkl')
util.pickle_dump(T,'T.pkl')
util.pickle_dump(V,'V.pkl')
util.pickle_dump(W,'W.pkl')
#get connections
con = _connections(M)
h_sum = []
f_sum = []
if len(con) != K.shape[0]:
print len(con)
print K.shape
print 'connections and K have different lenghts'
asdf
for k in range(len(con)):
print k
hybrid = []
free = []
#get the points that are not connected
for i in range(K.shape[1]):
if i in con[k][0]:
hybrid.append(points.dist(K[k][i],V[k][i/(K.shape[1]/V.shape[1])],L[k])[0]+0.5)
else:
free.append(points.dist(K[k][i],V[k][i/(K.shape[1]/V.shape[1])],L[k])[0]+0.5)
for i in range(T.shape[1]):
if i in con[k][1]:
hybrid.append(points.dist(T[k][i],W[k][i/(T.shape[1]/W.shape[1])],L[k])[0]+0.5)
else:
free.append(points.dist(T[k][i],W[k][i/(T.shape[1]/W.shape[1])],L[k])[0]+0.5)
h_sum.append(sum(hybrid)/len(hybrid))
f_sum.append(sum(free)/len(free))
f_sum[-1]= f_sum[-2]
h_sum[-1]= h_sum[-2]
x = range(V.shape[0])
print 'number of DNA per NP'
print K.shape[1]/V.shape[1]
print T.shape[1]/W.shape[1]
pyplot.plot2(x,h_sum,x,f_sum,xlabel='timestep',ylabel='sigma',label1='hybridizations',
label2='free',save='free_hybrid_connections',showleg='true')
