Archivo:Hamiltonian flow classical.gif

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Hamiltonian_flow_classical.gif(195 × 390 píxeles; tamaño de archivo: 172 kB; tipo MIME: image/gif, bucleado, 86 frames, 26s)

Resumen

Descripción
English: Flow of a statistical ensemble in the potential x**6 + 4*x**3 - 5*x**2 - 4*x. Over long times it becomes swirled up, and appears to become a smooth and stable distribution. However, this stability is an artifact of the pixelization (the actual structure is too fine to perceive).
This animation is inspired by a discussion of Gibbs in his 1902 wikisource:Elementary Principles in Statistical Mechanics, Chapter XII, p. 143: "Tendency in an ensemble of isolated systems toward a state of statistical equilibrium". A quantum version of this can be found at File:Hamiltonian flow quantum.webm
Fecha
Fuente Trabajo propio
Autor Nanite

Source

Created with Matplotlib-logo 
Este GIF gráfico fue creado con Matplotlib.
ImageMagick logo 
Esta imagen fue creada con ImageMagick.

Python source code. Requires matplotlib ImageMagick. Possibly does not run in Windows.

from pylab import *
import subprocess
import sys
import os

figformat = '.png'
seterr(divide='ignore')
rcParams['font.size'] = 9

#define color map that is transparent for low values, and dark blue for high values.
# weighted to show low probabilities well
cdic = {'red':   [(0,0,0),(1,0,0)],
        'green': [(0,0,0),(1,0,0)],
        'blue':  [(0,0.7,0.7),(1,0.7,0.7)],
        'alpha': [(0,0,0),
                  (0.1,0.4,0.4),
                  (0.2,0.6,0.6),
                  (0.4,0.8,0.8),
                  (0.6,0.9,0.9),
                  (1,1,1)]}
cm_prob = matplotlib.colors.LinearSegmentedColormap('prob',cdic,N=640)

### System dynamics ###

# potential is a polynomial
potential_coefs = array([1,0,0,4,-5,-4,0],'d')
def potential(x,t):
    return polyval(potential_coefs,x)

# force function is its derivative.
force_coefs = (potential_coefs*arange(len(potential_coefs)-1,-1,-1))[:-1]
def force(x,t):
    """ derivative of potential(x) """
    return polyval(force_coefs,x)
invmass = 1.0
dt = 0.03

def motion(t,x,p):
    """ returns dx/dt, dp/dt """
    return p*invmass, -force(x,t)

cur_x = -0.1
cur_p = 0

def rkky_step(t, x_i, p_i, dt):
    kx1,kp1 = motion(t, x_i, p_i)
    dt2 = 0.5*dt
    kx2,kp2 = motion(t+dt2, x_i+dt2*kx1, p_i+dt2*kp1)
    kx3,kp3 = motion(t+dt2, x_i+dt2*kx2, p_i+dt2*kp2)
    kx4,kp4 = motion(t+dt, x_i+dt*kx3, p_i+dt*kp3)
    newx = x_i + (dt/6.0)*(kx1 + 2.0*kx2 + 2.0*kx3 + kx4)
    newp = p_i + (dt/6.0)*(kp1 + 2.0*kp2 + 2.0*kp3 + kp4)
    return newx, newp

### Setup ensemble points ###

# most are randomly chosen
x = 0 + 0.5*rand(20000)
p = -1.0 + 2.0*rand(20000)

# the pilot points are set manually
x[0] = 0;    p[0] = 0
x[1] = 0.4;  p[1] = 0.0
pilots = [0,1]
pilot_colors = {
       0: (0,0.7,0),
       1: (0.7,0,0)}
E = potential(x,0) + 0.5*invmass*p**2

### set up plot limits and histogram bins ###
xedges = linspace(-2.1,1.7,151)
pedges = linspace(-7.5,7.5,151)
Eedges = linspace(-9,9,151)
pix = 150
extent = [xedges[0], xedges[-1], pedges[-1], pedges[0]]
H = histogram2d(x,p,bins=[xedges,pedges])[0].transpose()
cmax = amax(H)*0.8

extenten = [xedges[0], xedges[-1], Eedges[-1], Eedges[0]]
Hen = histogram2d(x,E,bins=[xedges,Eedges])[0].transpose()
cmaxen = amax(Hen)*0.3

fig = figure(1)
ysize = 2.6
xsize = 1.3
fig.set_size_inches(xsize,ysize)

### Prepare lower plot ###
axen = axes((0.2/xsize,0.2/ysize,1.0/xsize,1.0/ysize),frameon=True)
axen.xaxis.set_ticks([])
axen.xaxis.labelpad = 2
axen.yaxis.set_ticks([])
axen.yaxis.labelpad = 2
xlim(-2.1,1.7)
ylim(-9,9)
xlabel('position $x$')
ylabel('energy')
potx = linspace(-2.1,1.7,151)

### Prepare upper plot ###
ax = axes((0.2/xsize,1.5/ysize,1.0/xsize,1.0/ysize),frameon=True)
ax.xaxis.set_ticks([])
ax.xaxis.labelpad = 2
ax.yaxis.set_ticks([])
ax.yaxis.labelpad = 2
xlim(-2.1,1.7)
ylim(-7.5,7.5)
xlabel('position $x$')
ylabel('momentum $p$')

### Start running simulation ###
frames = list()
delays = list()
framemod = 5
frame = "frames/background"+figformat
savefig(frame,dpi=pix)
frames.append(frame)
delays.append(16)

print "generating frames...  0%",
sys.stdout.flush()
savesteps = range(0,401,framemod) + [600, 1000, 2000, 6000]
delays += [10]*len(savesteps)
delays[1] = 200
delays[-5:] = [100,200,200,200,400]
totalsteps = max(savesteps)+1
for step in range(totalsteps):
    if step % 20 == 0:
        print "\b\b\b\b\b{0:3}%".format(int(round(step*100.0/totalsteps))),
        sys.stdout.flush()
    if step in savesteps:
        # Every several frames, do a plot
        remlist = list()

        sca(ax)
        H = histogram2d(x,p,bins=[xedges,pedges])[0].transpose()
        remlist.append(imshow(H, extent=extent, cmap=cm_prob, interpolation='none', aspect='auto'))
        remlist[-1].set_clim(0,cmax)
        for i in pilots:
            remlist += plot(x[i], p[i], '.', color=pilot_colors[i], markersize=3)

        E = potential(x,step*dt) + 0.5*invmass*p**2
        sca(axen)
        pot = potential(potx,step*dt)
        remlist += plot(potx,pot,color='r',zorder=0)
        Hen = histogram2d(x,E,bins=[xedges,Eedges])[0].transpose()
        remlist.append(imshow(Hen, extent=extenten, cmap=cm_prob, interpolation='none', aspect='auto',zorder=1))
        remlist[-1].set_clim(0,cmaxen)
        for i in pilots:
            remlist += plot(x[i], E[i], '.', color=pilot_colors[i], markersize=3)

        frame = "frames/frame"+str(step)+figformat
        savefig(frame,dpi=pix)
        frames.append(frame)
        # Clear out updated stuff.
        for r in remlist: r.remove()
    x, p = rkky_step(step*dt, x, p,dt)
print "\b\b\b\b\b      done"

assert(len(delays) == len(frames))

### Assemble animation using ImageMagick ###
calllist = 'convert -dispose Background'.split()
for delay,frame in zip(delays,frames):
    calllist += ['-delay',str(delay)]
    calllist += [frame]
calllist += '-loop 0 -layers Optimize _animation.gif'.split()
f = open('anim_command.txt','w')
f.write(' '.join(calllist)+'\n')
f.close()

print "composing into animated gif...",
sys.stdout.flush()
subprocess.call(calllist)
print "      done"
os.rename('_animation.gif','animation.gif')

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Yo, el titular de los derechos de autor de esta obra, la publico en los términos de la siguiente licencia:
Creative Commons CC-Zero Este archivo está disponible bajo la licencia Creative Commons Dedicación de Dominio Público CC0 1.0 Universal.
La persona que ha asociado una obra a este documento lo dedica al dominio público mediante la cesión mundial de sus derechos bajo la ley de derechos de autor y todos los derechos legales adyacentes propios de dicha, en el ámbito permitido por ley. Puedes copiar, modificar, distribuir y reproducir el trabajo, incluso con objetivos comerciales, sin pedir aprobación del autor.

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Fecha y horaMiniaturaDimensionesUsuarioComentario
actual08:57 27 oct 2013Miniatura de la versión del 08:57 27 oct 2013195 × 390 (172 kB)NaniteAdded potential plot (with bonus ensemble histogram in E,x), as well as a couple of "pilot" systems.
22:39 26 oct 2013Miniatura de la versión del 22:39 26 oct 2013195 × 195 (84 kB)Nanitehigher resolution + a big longer in time to get the smooth look.
22:10 26 oct 2013Miniatura de la versión del 22:10 26 oct 2013195 × 195 (84 kB)NaniteUser created page with UploadWizard

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