plt.close()
plt.figure(2)
plt.close()
##Main execution of program
# define model grid
grd = IsingGrid(dim, sizeN)
if gridMode == 1:
grd = PottsGrid(dim, sizeN, 10)
if gridMode == 2:
grd = SpinGlass(dim, sizeN)
# set magnetic field
grd.fieldB = magField
# run....
output = wangLandau(grd)
# write to file!
dataOut = []
for i in range(0, len(output[0])):
dataOut.append([output[2][i], output[0][i]])
plotArrayToFile(dataOut, fileOut)
thermalizationSweeps, measurementSweeps = 10000, 50000
plotRange = [0.0, 2.0, 30]
MetropolisModule.runAlgorithm(grd, plotRange, thermalizationSweeps, measurementSweeps, 5, fileOut + "_Metropolis")
normConstLog = np.log(normConst)
#for i in range(0,len(logG)):
#out[i]*=normConst
#logG[i]+=normConstLog
# pow(out[i],sumLogG)
return [logG, out]
def isFlatAverage(histogram):
avg = np.mean(histogram)
for i in range(0,len(histogram)):
if(histogram[i]<0.8*avg):
return False
return True
def isFlatStd(histogram, tolerance):
avg = np.mean(histogram)
std = np.std(histogram)
return (std < (avg*tolerance))
def closeGraphs():
plt.figure(1)
plt.close()
plt.figure(2)
plt.close()
#main loop of program
grd = IsingGrid(dim,sizeN)
print('grid made')
output = wangLandau(grd)
print('output')
plotArrayToFile(output[0],fileOut)
def closeGraphs():
plt.figure(1)
plt.close()
plt.figure(2)
plt.close()
##Main execution of program
#define model grid
grd = IsingGrid(dim,sizeN)
modeString = 'Ising'
if(gridMode == 1):
grd = PottsGrid(dim,sizeN,10)
modeString = 'Potts'
if(gridMode==2):
grd= SpinGlass(dim,sizeN)
modeString = 'Spin Glass'
#set magnetic field
grd.fieldB = magField
#run....
output = wangLandau(grd)
#write to file!
dataOut =[]
for i in range(0,len(output[0])):
dataOut.append([output[2][i],output[0][i]])
plotArrayToFile(dataOut,fileOut, '#Wang Landau density of states for L=' + str(grd.gridSize) + ' dimension =' + str(grd.dimension) + ' ' + modeString + ' model.\n#Energy/Sites\tlogarithm of density of states\n',False)
normConst = float(dim**grid.gridSize)/sum(out)
normConstLog = np.log(normConst)
#for i in range(0,len(logG)):
#out[i]*=normConst
#logG[i]+=normConstLog
# pow(out[i],sumLogG)
return [logG, out]
def isFlatAverage(histogram):
avg = np.mean(histogram)
for i in range(0,len(histogram)):
if(histogram[i]<0.8*avg):
return False
return True
def isFlatStd(histogram, tolerance):
avg = np.mean(histogram)
std = np.std(histogram)
return (std < (avg*tolerance))
def closeGraphs():
plt.figure(1)
plt.close()
plt.figure(2)
plt.close()
#main loop of program
grd = IsingGrid(dim,sizeN)
output = wangLandau(grd)
plotArrayToFile(output[0],fileOut)
plt.figure(2)
plt.close()
##Main execution of program
#define model grid
grd = IsingGrid(dim, sizeN)
if (gridMode == 1):
grd = PottsGrid(dim, sizeN, 10)
if (gridMode == 2):
grd = SpinGlass(dim, sizeN)
#set magnetic field
grd.fieldB = magField
#run....
output = wangLandau(grd)
#write to file!
dataOut = []
for i in range(0, len(output[0])):
dataOut.append([output[2][i], output[0][i]])
plotArrayToFile(dataOut, fileOut)
thermalizationSweeps, measurementSweeps = 10000, 50000
plotRange = [0.0, 2.0, 30]
MetropolisModule.runAlgorithm(grd, plotRange, thermalizationSweeps,
measurementSweeps, 5, fileOut + "_Metropolis")
