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IsingLattice_python.py
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IsingLattice_python.py
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from scipy import signal
import sys
import numpy as np
import random
class IsingLattice(object):
def __init__(self, N, flip_prop):
self.J = 1
self.N = N
self.NN = N*N
self.B = 0
self.flip_prop = flip_prop
self.neighbors = None
# self.B = 0
# if self.n_flip != int(self.n_flip):
# self.n_flip = int(self.n_flip) + 1
self.spin = np.random.choice([-1,1],(N,N))
self.conv_mat = np.matrix('0 1 0; 1 0 1; 0 1 0')
# self.matrix_ptr = c_void_p(libc.newMatrix(int(N),int(n_flip)))
self.auto_correlation = []
def free_memory(self):
pass
def step(self, T, B):
#Calculating the total spin of neighbouring cells
self.B = B
# print('B: ',self.B)
self.neighbors = signal.convolve2d(self.spin,self.conv_mat,mode='same',boundary='wrap')
M = float(np.sum(self.spin))/float(self.NN)
E = float(-self.J*(np.sum((self.spin*self.neighbors)))/2.0)/float(self.NN) - float(B)*M
DeltaE = 2.0 * (self.J*(self.spin*self.neighbors) + float(self.B)*self.spin)
#Calculate the transition
p_trans = np.where(DeltaE >= 0.0, np.exp(-1.0*DeltaE/float(T)),1.0)
#Decide which transitions will occur
transitions = [[-1 if (cell>random.random() and self.flip_prop>random.random())
else 1 for cell in row] for row in p_trans]
#Perform the transitions
self.spin *= transitions
return None
def nsteps(self, T, B, n):
for i in range(n):
self.step(T,B)
return None
# return libc.nsteps(self.matrix_ptr,n,T,B)
def get_E(self):
if type(self.neighbors) == type(None):
self.neighbors = signal.convolve2d(self.spin,self.conv_mat,mode='same',boundary='wrap')
return float(-self.J*(np.sum((self.spin*self.neighbors)))/2.0)/float(self.NN) - float(self.B)*self.get_M()
def get_M(self):
return float(np.sum(self.spin))/float(self.NN)
def calc_auto_correlation(self):
# n = len(spin)
corr_array = []
for k in range(1,int(self.N/2)):
col_mean, row_mean = self.spin.mean(axis=0),self.spin.mean(axis=1)
#compute r values for rows and cols
r_col = [np.multiply(self.spin[j,:]-col_mean,self.spin[(j+k)%self.N,:]-col_mean) for j in range(1,self.N)]
r_row = [np.multiply(self.spin[:,j]-row_mean,self.spin[:,(j+k)%self.N]-row_mean) for j in range(1,self.N)]
#normalize r values
r_col = np.divide(r_col,float(self.N))
r_row = np.divide(r_row,float(self.N))
#calculate corr for k and add it to array
corr = (r_col.mean() + r_row.mean())/2.0
corr_array.append([k,corr])
return corr_array
def set_Nflip(self,npick):
self.flip_prop = npick / self.NN
def set_flip_prop(self,flip_prop):
self.flip_prop = flip_prop
def get_Nspin(self):
return np.sum(self.spin)
def get_Nalign(self):
return np.sum(self.neighbors)/2
# return libc.get_Nbond(self.matrix_ptr)
def get_spin(self, i, j):
return self.spin[i,j]
def set_spin(self, i, j, k):
self.spin[i,j] = k
self.neighbors = None
def print_spins(self):
print(self.spin)
def print_aligned(self):
if type(self.neighbors) == type(None):
self.neighbors = signal.convolve2d(self.spin,self.conv_mat,mode='same',boundary='wrap')
print(self.neighbors)
def randomize_spins(self):
self.spin = np.random.choice([-1,1],(self.N,self.N))
def get_numpy_spin_matrix(self):
return self.spin
if __name__ == '__main__':
from sys import argv
n = 10
if len(argv) == 1:
pass
elif argv[1] == "1":
lattice = IsingLattice(n,.1)
lattice.print_spins()
print("----")
for i in range(n):
for j in range(n):
continue
lattice.set_spin(i,j,1)
lattice.print_spins()
print("Nspin : %i"%lattice.get_Nspin())
print(" This is mag: %f"%lattice.get_M())
print("auto_corr:")
x = lattice.calc_auto_correlation()
for val in x:
print(val)
lattice.free_memory()
elif argv[1] == "0":
lattice = IsingLattice(5,.1)
print(argv[0])
lattice.print_spins()
print('---')
lattice.set_spin(0,0,1)
lattice.print_spins()
print('---')
lattice.set_spin(0,0,-1)
lattice.print_spins()
print('---')
flip = True
for i in range(n):
for j in range(n):
flip = not flip
if flip:
lattice.set_spin(i,j,1)
else:
lattice.set_spin(i,j,-1)
lattice.print_spins()
print('---')
lattice.free_memory()
else:
lattice = IsingLattice(10,.01)
lattice.print_spins()
lattice.print_aligned()
lattice.nsteps(4.,2.1,10000)
# lattice.randomize_spins()
print('E: ',lattice.get_E())
print('M: ',lattice.get_M())
print('autocorrelation ', lattice.calc_auto_correlation())
print("set_Nflip: ", lattice.set_Nflip(20))
print("get_Nspin: " , lattice.get_Nspin())
print("get_Nalign: " , lattice.get_Nalign())
# print("step: " , lattice.step(2.9,1.0))
print("get_Nspin: " , lattice.get_Nspin())
print("get_Nalign: " , lattice.get_Nalign())
print('E: ' , lattice.get_E())
print("N " , lattice.N)
print('aligned')
# lattice.print_aligned()
print('spins')
# lattice.print_spins()
lattice.free_memory()
print('exit')
sys.exit()