from IsingLattice import *
from matplotlib import pylab as pl
import numpy as np

#First, we use the NumPy loadtxt function to read our previously saved file for the 4x4 lattice
data_4x4_mine= np.loadtxt("4x4_mine.dat")

#Now we use the NumPy loadtxt function to read the corresponding file with the C++ data
data_4x4_provided=np.loadtxt("4x4.dat")


#Calculating Heat Capacity:

#Define number of spins in lattice (so that we can use this to convert values of energy to energy/spin)
spins=16

#Variance of energy/spin is equal to the difference between avg(E^2) and (avgE)^2 where E is energy/spin
var_energies_4x4=np.subtract(data_4x4_mine[:,2],np.multiply(data_4x4_mine[:,1],data_4x4_mine[:,1]))

#Heat Capacity is equal to the Variance / T^2  
Heat_Capacity_4x4 = np.divide(var_energies_4x4, np.multiply(data_4x4_mine[:,0], data_4x4_mine[:,0]))




#Plotting heat capacity/spin vs temperature using BOTH sets of data
pl.plot(data_4x4_mine[:,0],(Heat_Capacity_4x4)/spins,'bo-', markersize = 3, label = 'Using My Data')

pl.plot(data_4x4_provided[:,0],data_4x4_provided[:,5],'ro-', markersize=3, label = 'Using Data Provided') 

pl.title('Plots of Heat Capacity vs Temperature for Lattice Size: 4x4')
pl.ylabel("Heat Capacity (in units of kB)")
pl.xlabel("Temperature")

pl.legend(loc='best')


pl.show()