def combineFrames(file, nCombine):
time, atoms = readFrame(file)
l = len(atoms)
combined = np.zeros((l*nCombine,4))
combined[0:l] = atoms
for n in range(nCombine-1):
_, atoms = readFrame(file)
combined[l*(n+1):l*(n+2)] = atoms
return time, combined
def main():
trajFile, outFile, nFrames = getArgs(argv)
atomtype = 1
particles = 3
nSkip = 1 # nFrames / 100
nMon = 5
with open(outFile+'_unwrapped.xyz', 'w') as otp:
otp.write('')
with open(trajFile,'r') as inp:
for n in range(nFrames/nSkip):
### lammmpstrj ###
# # read and filter data
# for s in range(nSkip):
# time, box, frame = readTrj(inp)
# zero = frame[frame[:,1] == particles][:,4].min()
# frame = frame[np.argsort(frame[:,0])]
# frame = frame[frame[:,1] == atomtype][:,2:]
# Lxy = box[:,1] - box[:,0]
# frame = frame * Lxy + box[:,0]
### xyz ###
# read and filter data
for s in range(nSkip):
time, frame = readFrame(inp)
zero = frame[frame[:,0] == particles][:,3].min()
frame = frame[frame[:,0] == atomtype][:,1:]
frame[:,2] -= zero
# build box
box = np.zeros((2,2))
box[:,0] = frame[:,:2].min(0)
box[:,1] = frame[:,:2].max(0)
Lxy = box[:,1] - box[:,0]
frame = unwrap(frame.reshape((-1,nMon,3)), box).reshape((-1,3))
if n == 0:
periods = np.zeros_like(frame[:,:2])
move = np.zeros_like(frame[:,:2])
elif n > 0:
move = frame[:,:2] + periods * Lxy[:2] - oldFrame[:,:2]
periods += (move < box[:2,0])
periods -= (move >= box[:2,1])
frame[:,:2] += periods * Lxy[:2]
# if differences are greater than L/2 in any frame, add 1
oldFrame = np.copy(frame)
with open(outFile+'_unwrapped.xyz', 'a') as otp:
otp.write('%d\n' % len(frame))
otp.write('Atoms. Timestep: %d\n' % time)
np.savetxt(otp,frame,'1 %.5f %.5f %.5f')
print 'Finished analyzing trajectory'
def main():
filename, outFile, nFrames = getArgs(argv)
# Generate multiple MSDs based on the locations of the polymers
# 1. Exclude polymers in the bulk
# 2. Exclude polymers NOT in the bulk
# 3. Look at polymers in the packing exclusively
#
# The point is to find a reasonable time-scale for polymer relaxation
# Polymers in the packing have z coordinate > 0 and those near the surface are less than
# 5 sigma from the surface (most negative polymer value)
MSD = np.zeros((nFrames-1,5))
#MSD[:,0] = np.arange(1,nFrames)
# Calculate atomic and molecular MSD
chainLength = 25
pos = 0
for m in range(nFrames-1):
with open(filename, 'r') as file:
file.seek(pos)
time_m, atoms_m = readFrame(file)
# add a condition to restrict the polymers based on location (make a mask)
# mask = np.logical_and(atoms_m[:,2] < 0, atoms_m[:,2] > 5*(atoms_m[:,2].min()))
atoms_m = atoms_m[:,1:]#[mask]
pos = file.tell()
for n in range(m+1,nFrames):
time_n, atoms_n = readFrame(file)
atoms_n = atoms_n[:,1:]#[mask]
# handle function calls here
MSD[n-m-1,1:] += diffusion(atoms_m, atoms_n, chainLength)
if m == 0:
MSD[n-m-1,0] = time_n - time_m
# average MSD array
MSD[:,1:] /= range(nFrames-1,0,-1)
# write MSD array to file
with open(outFile, 'w') as otp:
otp.write('# lagtime MSD\n')
np.savetxt(otp,MSD,'%0.5f')
def main():
trajFile, outFile, nSteps = getArgs(argv)
nBins = 180
pcf = np.zeros((nBins,2))
with open(trajFile,'r') as inp:
for n in range(nSteps):
for k in range(50):
t, frame = readFrame(inp)
mask = lambda i: (frame[:,0] == i)
poly = frame[mask(1)][:,1:]
surf = frame[mask(2)][:,1:]
# Find the center of mass in the xy direction and center droplet
# poly, center = centerAtoms(poly)
# make box
box = np.ones((3,2))
box[:,0] = frame[:,1:].min(0) #-0.01
box[:,1] = frame[:,1:].max(0) #+0.01
# box[1,:] += [-7,7]
# atoms[:,2] -= box[2,0]
# box[2,:] -= box[2,0]
# find interfacial atoms
# interface = findCylinderInterface(atoms, box)
# calculate volume per horizontal 'slice'
# calculate pair correlation function
pcf += calcPCF(surf, poly, box, nBins)
plt.plot(pcf[:,0], pcf[:,1])
plt.show()
print 'Finished analyzing trajectory'
