def n_neighbor_distance_list(v_pos_mat,inputfile):
distance=[]
for i in range(1,len(v_pos_mat)):
min=10000
for x in range(1,len(v_pos_mat)):
if u.part_distance(v_pos_mat[i],v_pos_mat[x],inputfile)<min and i!=x:
min=u.part_distance(v_pos_mat[i],v_pos_mat[x],inputfile)
distance.append(min)
return distance
def n_neighbor_vector_list(v_pos_mat,inputfile):
distance=[[0.0,0.0,0.0]]
for i in range(1,len(v_pos_mat)):
min=10000
minvec=[0.0,0.0,0.0]
for x in range(1,len(v_pos_mat)):
if u.part_distance(v_pos_mat[i],v_pos_mat[x],inputfile)<min and i!=x:
minvec=np.subtract(v_pos_mat[x],v_pos_mat[i])
min=u.part_distance(v_pos_mat[i],v_pos_mat[x],inputfile)
distance=np.append(distance,[minvec],axis=0)
return distance
def dist_v_timestep_lat_matrix(nfiles, file1, file2, length, totalnp,
nptocount):
typs = ['S', 'O', 'OH']
file1 = file1[11:-4]
file2 = file2[11:-4]
out = np.zeros((nfiles, nptocount * (length - 1) * 80))
for c in range(0, nfiles):
file0 = (int(file1) + (int(file2) - int(file1)) * c)
toopen = 'atoms.'
for v in range(0, 10 - len(str(file0))):
toopen = toopen + '0'
toopen = toopen + str(file0) + '.xml'
print('Calculating Carbon Distance for ' + str(file0) + ' (' +
str(c + 1) + '/' + str(nfiles) + ')')
ch = chain_pos_lat_matrix(toopen, typs, totalnp, nptocount)
#print ch
spos = [0, 0, 0]
cpos = [0, 0, 0]
count = 0
for i in range(1, len(ch)):
if (ch[i][0] == typs[0]):
spos = [float(ch[i][1]), float(ch[i][2]), float(ch[i][3])]
else:
cpos = [float(ch[i][1]), float(ch[i][2]), float(ch[i][3])]
out[c][count] = u.part_distance(spos, cpos, toopen)
count += 1
return out
def distance_array_V(inputfile):
x = vd.v_pos_matrix(inputfile)
d = [0.0, 0.0, 0.0]
v = 0
for i in range(1, len(x)):
min = 100
temp = u.part_distance(d, x[i], inputfile)
if (temp < min):
v = i
min = temp
distance_array = np.array([0.0])
for b in range(1, len(x)):
if b != i:
c = u.part_distance(x[b], x[v], inputfile)
distance_array = np.append(distance_array, [c], axis=0)
distance_array = np.sort(distance_array)
return distance_array
def new_distance_to_nth_carbon_list(inputfile, nth):
typs = ['S', 'O', 'OH']
list = []
x = nth_carbon_pos_matrix(inputfile, nth, typs)
y = nth_carbon_pos_matrix(inputfile, 0, typs)
for i in range(1, len(x)):
xn = np.array([float(x[i][0]), float(x[i][1]), float(x[i][2])])
yn = np.array([float(y[i][0]), float(y[i][1]), float(y[i][2])])
list.append(u.part_distance(xn, yn, inputfile))
return list
def new_distance_to_nth_carbon(inputfile, nth):
typs = ['S', 'O', 'OH']
x = nth_carbon_pos_matrix(inputfile, nth, typs)
y = nth_carbon_pos_matrix(inputfile, 0, typs)
total = 0
for i in range(1, len(y)):
xn = np.array([float(x[i][0]), float(x[i][1]), float(x[i][2])])
yn = np.array([float(y[i][0]), float(y[i][1]), float(y[i][2])])
total += u.part_distance(xn, yn, inputfile)
return float(total) / float(len(y) - 1)
def max_radius(inputfile, n):
typs = ['S', 'O', 'OH']
x = nth_carbon_pos_matrix(inputfile, n, typs)
y = v.v_pos_matrix(inputfile)
max = 0
for i in range(0, len(x)):
d = u.part_distance(y[1], x[i], inputfile)
if (d > max):
max = d
return max
def distance_carbon_to_carbon(inputfile,first,last):
typs=['S','CH2','CH3']
x=nth_carbon_pos_matrix(inputfile,last,typs)
y=nth_carbon_pos_matrix(inputfile,first,typs)
total=0
for i in range(1,len(y)):
xn=np.array([float(x[i][0]),float(x[i][1]),float(x[i][2])])
yn=np.array([float(y[i][0]),float(y[i][1]),float(y[i][2])])
total+=u.part_distance(xn,yn,inputfile)
return float(total)/float(len(y)-1)
def closest_matrix(ppos_mat,Aupos_mat,inputfile):
close_array=np.array([1000])
for i in range(1,len(ppos_mat)):
a=np.array([float(ppos_mat[i][1]),float(ppos_mat[i][2]),float(ppos_mat[i][3])])
closest_distance=100000
for x in range(1,len(Aupos_mat)):
c=np.array([float(Aupos_mat[x][0]),float(Aupos_mat[x][1]),float(Aupos_mat[x][2])])
distance=u.part_distance(a,c,inputfile)
if(distance<closest_distance):
closest_distance=distance
close_array=np.append(close_array,[closest_distance],axis=0)
return close_array
def min_distance_between_nth_carbon(inputfile, n):
typs = ['S', 'O', 'OH']
chain = nth_carbon_pos_matrix(inputfile, n, typs)
#print 'matrix'
min = 10000
for i in range(1, len(chain)):
#print i
for x in range(i + 1, len(chain)):
d = u.part_distance(chain[i], chain[x], inputfile)
if (d < min):
min = d
return min
def np_volume(inputfile):
au = vd.type_pos_matrix(inputfile, 'Au')
v = vd.type_pos_matrix(inputfile, 'V')
numau = (len(au) - 1) / (len(v) - 1)
volume = 0
for x in range(1, len(v)):
for i in range(1 + (numau * x - 1), 1 + numau * x):
r = u.part_distance(au[i], v[x], inputfile)
if (r - float(int(r)) == 0.0):
volume += 0.5 * r**3
i = -1
print i
return volume
def dist_v_timestep(nfiles,file1,file2):
file1=file1[6:-4]
file2=file2[6:-4]
out=np.array([[0.0,0.0]])
for c in range(0,nfiles):
file0=(int(file1)+(int(file2)-int(file1))*c)
toopen='atoms.'
for v in range(0,10-len(str(file0))):
toopen=toopen + '0'
toopen=toopen + str(file0) + '.xml'
x=v_pos_matrix(toopen)
out=np.append(out,[[file0,u.part_distance(x[1],x[2],toopen)]],axis=0)
return out
