我正在尝试执行VPython附带的名为'gas.py'的示例。我已经从VPython web（Python 2.7）和VPython 6.11完成了新的Python安装。
Vpython附带的每个例子都适用于我，但是'gas.py'。它汇编并执行，并且在第一次运行中，它等待5秒钟并冻结。下一次运行甚至没有显示任何图表。
我无法找到解决方案，因为它是一个正常工作的代码，并且库似乎正常工作，因为所有其他示例（43）都像魅力一样工作。
任何建议都会有所帮助，谢谢。
from visual import *
from visual.graph import *
from random import random
# A model of an ideal gas with hard-sphere collisions
# Program uses numpy arrays for high speed computations
# Bruce Sherwood
win=500
Natoms = 100 # change this to have more or fewer atoms
# Typical values
L = 1. # container is a cube L on a side
gray = (0.7,0.7,0.7) # color of edges of container
Matom = 4E-3/6E23 # helium mass
Ratom = 0.03 # wildly exaggerated size of helium atom
k = 1.4E-23 # Boltzmann constant
T = 300. # around room temperature
dt = 1E-5
scene = display(title="Gas", width=win, height=win, x=0, y=0,
center=(L/2.,L/2.,L/2.))
deltav = 100. # binning for v histogram
vdist = gdisplay(x=0, y=win, ymax = Natoms*deltav/1000.,
width=win, height=0.6*win, xtitle='v', ytitle='dN')
theory = gcurve(color=color.cyan)
dv = 10.
for v in arange(0.,3001.+dv,dv): # theoretical prediction
theory.plot(pos=(v,
(deltav/dv)*Natoms*4.*pi*((Matom/(2.*pi*k*T))**1.5)
*exp((-0.5*Matom*v**2)/(k*T))*v**2*dv))
observation = ghistogram(bins=arange(0.,3000.,deltav),
accumulate=1, average=1, color=color.red)
xaxis = curve(pos=[(0,0,0), (L,0,0)], color=gray)
yaxis = curve(pos=[(0,0,0), (0,L,0)], color=gray)
zaxis = curve(pos=[(0,0,0), (0,0,L)], color=gray)
xaxis2 = curve(pos=[(L,L,L), (0,L,L), (0,0,L), (L,0,L)], color=gray)
yaxis2 = curve(pos=[(L,L,L), (L,0,L), (L,0,0), (L,L,0)], color=gray)
zaxis2 = curve(pos=[(L,L,L), (L,L,0), (0,L,0), (0,L,L)], color=gray)
Atoms = []
##colors = [color.red, color.green, color.blue,
## color.yellow, color.cyan, color.magenta]
poslist = []
plist = []
mlist = []
rlist = []
for i in range(Natoms):
Lmin = 1.1*Ratom
Lmax = L-Lmin
x = Lmin+(Lmax-Lmin)*random()
y = Lmin+(Lmax-Lmin)*random()
z = Lmin+(Lmax-Lmin)*random()
r = Ratom
## Atoms = Atoms+[sphere(pos=(x,y,z), radius=r, color=colors[i % 6])]
if i == 0:
Atoms.append(sphere(pos=(x,y,z), radius=r, color=color.yellow,
make_trail=True, retain=100))
## Atoms[0].trail_object.radius = 1
else:
Atoms.append(sphere(pos=(x,y,z), radius=r, color=color.cyan))
mass = Matom*r**3/Ratom**3
pavg = sqrt(2.*mass*1.5*k*T) # average kinetic energy p**2/(2mass) = (3/2)kT
theta = pi*random()
phi = 2*pi*random()
px = pavg*sin(theta)*cos(phi)
py = pavg*sin(theta)*sin(phi)
pz = pavg*cos(theta)
poslist.append((x,y,z))
plist.append((px,py,pz))
mlist.append(mass)
rlist.append(r)
pos = array(poslist)
p = array(plist)
m = array(mlist)
m.shape = (Natoms,1) # Numeric Python: (1 by Natoms) vs. (Natoms by 1)
radius = array(rlist)
pos = pos+(p/m)*(dt/2.) # initial half-step
while True:
rate(50)
observation.plot(data=mag(p/m))
# Update all positions
pos = pos+(p/m)*dt
r = pos-pos[:,newaxis] # all pairs of atom-to-atom vectors
rmag = sqrt(sum(square(r),-1)) # atom-to-atom scalar distances
hit = less_equal(rmag,radius+radius[:,None])-identity(Natoms)
hitlist = sort(nonzero(hit.flat)[0]).tolist() # i,j encoded as i*Natoms+j
# If any collisions took place:
for ij in hitlist:
i, j = divmod(ij,Natoms) # decode atom pair
hitlist.remove(j*Natoms+i) # remove symmetric j,i pair from list
ptot = p[i]+p[j]
mi = m[i,0]
mj = m[j,0]
vi = p[i]/mi
vj = p[j]/mj
ri = Atoms[i].radius
rj = Atoms[j].radius
a = mag(vj-vi)**2
if a == 0: continue # exactly same velocities
b = 2*dot(pos[i]-pos[j],vj-vi)
c = mag(pos[i]-pos[j])**2-(ri+rj)**2
d = b**2-4.*a*c
if d < 0: continue # something wrong; ignore this rare case
deltat = (-b+sqrt(d))/(2.*a) # t-deltat is when they made contact
pos[i] = pos[i]-(p[i]/mi)*deltat # back up to contact configuration
pos[j] = pos[j]-(p[j]/mj)*deltat
mtot = mi+mj
pcmi = p[i]-ptot*mi/mtot # transform momenta to cm frame
pcmj = p[j]-ptot*mj/mtot
rrel = norm(pos[j]-pos[i])
pcmi = pcmi-2*dot(pcmi,rrel)*rrel # bounce in cm frame
pcmj = pcmj-2*dot(pcmj,rrel)*rrel
p[i] = pcmi+ptot*mi/mtot # transform momenta back to lab frame
p[j] = pcmj+ptot*mj/mtot
pos[i] = pos[i]+(p[i]/mi)*deltat # move forward deltat in time
pos[j] = pos[j]+(p[j]/mj)*deltat
# Bounce off walls
outside = less_equal(pos,Ratom) # walls closest to origin
p1 = p*outside
p = p-p1+abs(p1) # force p component inward
outside = greater_equal(pos,L-Ratom) # walls farther from origin
p1 = p*outside
p = p-p1-abs(p1) # force p component inward
# Update positions of display objects
for i in range(Natoms):
Atoms[i].pos = pos[i]