ising.py

#!/usr/bin/env python
#-*- coding:utf-8 -*-
__author__ = "Naich An (An@Naich.org)"
__copyright__ = "Copyright (c) 2012 Naich An" 

import scipy
import random
import math
import sys,os



class Ising (object):

  def __init__(self,SIZE,T,J=1,h=0,ifrandom=0):
		self.SIZE = SIZE
		self.J = J
		self.T = float(T)
		self.h = h
		
		self.m = scipy.ones(SIZE * SIZE,int)
		self.m.shape = (SIZE,SIZE)
		if ifrandom != 0:
			for x in xrange(0,SIZE):
				for y in xrange(0,SIZE):
					if random.random() > 0.5:
						self.m[x][y] = self.m[x][y] * (-1)
			
		
		

		self.e = scipy.exp
		
		self.E = 0.0
		
		self.p = {
			-12 + h: self.e((-1)*(-12+h)/T),
			-8 + h: self.e((-1)*(-8+h)/T),
			-4 + h: self.e((-1)*(-4+h)/T),
			0 + h: self.e((-1)*(0+h)/T),
			4 + h: self.e((-1)*(4+h)/T),
			8 + h: self.e((-1)*(8+h)/T),
			12 + h: self.e((-1)*(12+h)/T),
		}
		
		self.E = self.E0(self.m)

	def E0(self,m):
		e0 = 0.0
		SIZE = self.SIZE
		J = self.J
		h = self.h
		for x in xrange(0,SIZE):
				for y in xrange(0,SIZE):
					factor = y%2 * 2 - 1
					links = m[x][(y + 1)% SIZE ] + m[x][(y - 1)% SIZE ] + m[(x+1)%SIZE][y] + m[(x-1)%SIZE][y] + m[(x-factor)%SIZE][(y-1)%SIZE] + m[(x-factor)%SIZE][(y+1)%SIZE]
					e0 = e0 + (m[x][y] * (links * J + h) ) * (-1)
	
		return e0/2

	def step(self, x, y):
		SIZE = self.SIZE
		J = self.J
		h = self.h
		p = self.p
		
		factor = y%2 * 2 - 1
		links = self.m[x][(y + 1)% SIZE ] + self.m[x][(y - 1)% SIZE ] + self.m[(x+1)%SIZE][y] + self.m[(x-1)%SIZE][y] + self.m[(x-factor)%SIZE][(y-1)%SIZE] + self.m[(x-factor)%SIZE][(y+1)%SIZE]
		deltaH = (self.m[x][y] * 2 * (links * J + h)) 
		#p = e((-1)*deltaH/T) 
		#j = random.random()
		#print deltaH,p[deltaH],j
		#print deltaH
	
		if random.random() < p[deltaH]:
			self.m[x][y] = self.m[x][y] * (-1)
			self.E = self.E + deltaH

	def MCstep(self, N):	
	
		
			
		os.system('rm ./data/%.3f.dat'%self.T)
		f = open('./data/%.3f.dat'%self.T,'w')
		output = ""
	
		for i in xrange(0,N):
	
			if i%1 == 0:
				output += "%f\t%f\n"%(sum(sum(self.m)) / float(self.SIZE * self.SIZE), self.E / float(self.SIZE * self.SIZE))	
			
			for x in xrange(0,self.SIZE):
				for y in xrange(0,self.SIZE):
					self.step(x,y)
		f.write(output)