In this tutorial, a PyGran System class is created from a LIGGGHTS trajectory dump file. This class is then used to plot different spatial/structural variables.
# Import PyGran + matplotlib modules from PyGran import analysis import matplotlib.pylab as plt # Create a granular object from a LIGGGHTS dump file Sys = analysis.System(Particles='traj*.dump')
The code below constructs the RDF for the last frame in the system and then plots its using pylab.
# Go to last frame Sys.goto(-1) # change unit system to micro Sys.units('micro') # Compute the radial distribution function g, r, _ = Sys.Particles.rdf() # Plot rdf vs radial distance plt.plot(r, g, 'o-')
Constructing a cube of length 1579.55825864 and a circumscribed sphere of radius 394.889564659 Resolution chosen is 3.94889564659
The code below constructs a histogram of all the particle-particle overlaps for the last frame in the system.
# Construct a class for nearest neighbor searching Neigh = analysis.equilibrium.Neighbors(Sys.Particles) # Extract coordination number for all particles coon = Neigh.coon() # Construct + plot histogram of coon over 10 bins plt.hist(coon)
# Extract the overlaps for all particles overlaps = Neigh.overlaps[:,0] # Compute mean radius radius = Sys.Particles.radius.mean() # Construct + plot histogram of overlaps over 20 bins plt.hist(overlaps / radius * 100, bins=20)