def CalcTangent(i, pivots, Eprev, Ethis, Enext, L):
dispPrev = med.PeriodicDisplacement(pivots[i], pivots[i - 1], L)
dispNext = med.PeriodicDisplacement(pivots[i + 1], pivots[i], L)
dispPrevNorm = np.linalg.norm(dispPrev)
dispNextNorm = np.linalg.norm(dispNext)
if Enext > Ethis != (Eprev > Ethis): #is not an extremum
tangent = dispNext / dispNextNorm if Enext > Eprev else dispPrev / dispPrevNorm
else: #if it is an extremum, apply smoothening
delta = np.abs([Enext - Ethis, Eprev - Ethis])
deltamax = np.max(delta)
deltamin = np.min(delta)
tangent = dispNext * deltamax + dispPrevNorm * deltamin if Enext > Eprev else dispNext * deltamin + dispPrevNorm * deltamax
tangent /= np.linalg.norm(tangent)
return tangent, dispPrevNorm, dispNextNorm
delta = 1. / args.npoints
alphas = np.arange(0, 1 + delta, delta)
energies = []
distances = []
for alpha in alphas:
interpPos = med.PeriodicInterpPoints(pos2, pos1, L, alpha)
snap.particles.position[:] = interpPos
system.restore_snapshot(snap)
hoomd.run(2)
energy = analyzer.query('potential_energy')
print(energy)
energies.append(energy)
distances.append(med.PeriodicDistance(pos1, interpPos, L))
#Vector of all the particle displacements
disp = med.PeriodicDisplacement(pos1, pos2, L)
#
# FIGURES
#
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import seaborn as sns
#Barrier from the linear interpolation
fig, ax1 = plt.subplots()
ax1.set_xlabel('distance')
ax1.set_ylabel('energy')
ax1.plot(distances, energies)
ax1.tick_params(axis='x')
ax2 = ax1.twiny() # instantiate a second axes that shares the same x-axis
msd=np.zeros(trajDuration, dtype=np.float64) Fk=np.zeros(trajDuration,dtype=np.float64) ################################################################ # # SAVE TRAJECTORY AND CALCULATE MEAN SQUARE DISPLACEMENT # ################################################################ for iframe in range(0, trajDuration, 1): ## we only look 1 frame every "every_forMemory" frame, to save memory: trajectory[iframe] = np.array(hoomdTraj[iframe*every_forMemory].particles.position, dtype=np.float64) time=np.int64(hoomdTraj[iframe*every_forMemory].configuration.step)-time0 times[iframe]=time*every_forMemory*dt msd[iframe]=med.PeriodicSquareDistance(trajectory[iframe], initialPositions, L)/Natoms all_displacements=med.PeriodicDisplacement(trajectory[iframe], initialPositions, L) Fk[iframe]=med.ComputeFkt(n1, n2, n3, L, all_displacements) HoomdFlow.close() ################################################################ # # SAVE MSD and FkT # ################################################################ # # MSD and Fk(t) # #Remove preexisting output files to avoid conflicts namemsd_txt='msd'+label+'.txt'
print('From the energy barrier height I expect it to be: ',
(energies[imax] - energies[-1]) / ek)
print('------')
else:
print('temperature = ', args.temperature)
# Save the path
np.save('./test-output/pivots.npy', pivots)
#
# Now some measurements on the path
#
# Histogram of the motion with the transition state, and participation ratios
import seaborn as sns
disp_inimax = np.linalg.norm(med.PeriodicDisplacement(pivots[0], pivots[imax],
L),
axis=1)
disp_maxfin = np.linalg.norm(med.PeriodicDisplacement(pivots[imax], pivots[-1],
L),
axis=1)
disp_inifin = np.linalg.norm(med.PeriodicDisplacement(pivots[0], pivots[-1],
L),
axis=1)
ipr_inimax = med.InvPRdist(disp_inimax)
ipr_maxfin = med.InvPRdist(disp_maxfin)
ipr_inifin = med.InvPRdist(disp_inifin)
nmovedIPR = int(round(2.0 / (ipr_inimax + ipr_maxfin)))
disps_pivots = np.ndarray((len(pivots) - 1, Natoms))
ipr_pivots = np.ndarray((len(pivots) - 1))
for i in range(len(pivots) - 1):