Python Assignment #2 for LMC

import sys

sys.path.append("K:\\Simulations\\Lmc\\LmcPython")

import Lmc
dir(Lmc)

sim = Lmc.IsingSimulation()
sim.SetHeightWidth(512,512)	# Bigger for better averages

correlationObserver = Lmc.CorrelationObserverFFT()
sim.Attach(correlationObserver)

sim.Sweep()
sim.Notify()

# Make sure your X-windows manager is running.

# JPS home:
sys.path.append("K:\\Simulations\\xmgr") # Your path here
import xmgr
# Early in the semester, we needed this voodoo to get xmgr to work
# File -> Open, K:\Simulations\xmgr\xmgr.py, then close it
graph = xmgr.xmgr()

corr = []
for r in xrange(0,sim.GetWidth()/2):
	corr.append([r,correlationObserver.Correlation(r)])
	
graph.PlotSet(0,corr)

# Measure correlation functions after times 2^n,
# plot them
corrlist = [corr]

def copyCorr():
	corr = []
	for r in xrange(0,sim.GetWidth()/2):
		corr.append([r,correlationObserver.Correlation(r)])
	return corr
	
sim.Sweep()
sim.Notify()

copyCorr()
corrlist.append(copyCorr())	# corrlist[1] is correlation at t=2^1
sim.GetTime()

graph.PlotSet(1,corrlist[1])

n = 2

# LOOP over times 2^n

for i in xrange(0,2**(n-1)):
	sim.Sweep()
sim.Notify()
sim.GetTime()
corrlist.append(copyCorr())
graph.PlotSet(n,corrlist[n])
n = n+1

# Repeat until too time-consuming,
#  or until the correlations extend to the center

# Rescale the correlation functions by t^-alpha
# Remember, t is 2^n
# Try various alpha until you get a good collapse

alpha = -XXX

# Copy rescaledCorr to new list
# There must be a better way!

def CopyList(listOrig,depth):
	if depth == 1:
		return listOrig[:]
	else:
		listNew = []
		for item in listOrig:
			listNew.append(CopyList(item,depth-1))
		return listNew

rescaledCorr = CopyList(corrlist,3)

for i in xrange(0,len(rescaledCorr)):
	for r in xrange(0,len(rescaledCorr[i])):
		rescaledCorr[i][r][0] = rescaledCorr[i][r][0]*2**(alpha*i)	

graph.PlotSets(rescaledCorr[0],rescaledCorr[1],rescaledCorr[2], \
		   rescaledCorr[3],rescaledCorr[4],rescaledCorr[5], \
		   rescaledCorr[6],rescaledCorr[7],rescaledCorr[8], \
		   rescaledCorr[9])
		  
# You'll need to zoom in to see the collapse: use the magnifying-glass button

Statistical Mechanics: Entropy, Order Parameters, and Complexity, now available at Oxford University Press (USA, Europe).