I’m new to this neighborhood; I’ve tried my greatest to respect the coverage of the neighborhood. I’ve written the Monte Carlo metropolis algorithm for the ising mannequin. I need to optimize the code. I’ve tried my greatest. I need to optimize it additional. The next is the code:

(I’ve used methods like discovering exponential solely as soon as, cautious era of random quantity, and so forth.)

import numpy as np
import time
import random

def monteCarlo(N,state,Power,Magazine,Beta,sweeps):
    if sweeps > 10000:
        print("Warning:Variety of sweeps exceeded 10000ntsetting variety of sweeps to 10000")
        sweeps = 10000
    start_time = time.time()
    expBeta = np.exp(-Beta*np.arange(0,9))
    E = np.zeros(sweeps)
    M = np.zeros(sweeps)
    for t in vary(sweeps):
        for tt in vary(N*N):
            a = random.randint(0, N-1)
            b = random.randint(0, N-1)
            s = state[a,b]
            delta_E = 2*s*(state[(a+1)%N,b] + state[a,(b+1)%N] + state[(a-1)%N,b] + state[a,(b-1)%N])
            if delta_E < 0:
                s *= -1
                Power += delta_E
                Magazine += 2*s
            elif random.random() < expBeta[delta_E]:
                s *= -1
                Power += delta_E
                Magazine += 2*s
            state[a, b] = s
        E[t] = Power
        M[t] = Magazine
    print("%d monte carlo sweeps accomplished in %d seconds" %(sweeps,time.time()-start_time))
    return E,M #returning record of Power and Magnetization set

#####lattice config#####
"""N is lattice dimension
nt is variety of Temperature factors
sweeps are variety of mc steps per spin"""
print("Beginning Ising Mannequin Simulation")
N = int(enter("Enter lattice dimension : "))
startTime = time.time()
nt = 10
N2 = N*N
sweeps = 10000 #mc steps per spin
"""we'll plot the next wrt temperature, T"""
T = np.linspace(2, 3, nt) #you may set temperature vary
"""getting ready lattice with all spins up"""
state = np.ones((N,N),dtype="int")
Power = -N2
Magazine = N2
#temperature loop
#for okay in tqdm_gui(vary(nt)):
for okay in vary(nt):
    temp = T[k]
    Beta=1/temp
    print("____________________________________nTemperature is %0.2f, time is %d" %(temp,time.time()-startTime))
    E, M = monteCarlo(N,state,Power,Magazine,Beta,sweeps) #record of Power and Magnetization
    Power = E[-1]
    Magazine = M[-1]

#additional code is discovering magnetization, autocorrelation, particular warmth, autocorrelation, and so forth.```