MC_algo.py

def Sim_Anneal(ps,const):
        T=8.00
        delta = 0.05
        nmoves=10
        while (T > 5e-2):
                accept=0
                reject=0
                Beta=(1.0/T)
                for i in range(0,nmoves):
                        old_ene = Goodness_of_Fit(ps)
                        pick=randint(0,len(ps)-1)
                        old = ps[pick]
                        ps[pick] = old*(1+randrange(-1,2,2)*delta)*const[pick]
                        new_ene = Goodness_of_Fit(ps)
                        boltz = exp(-(new_ene-old_ene) *Beta)
                        charge = np.sum([ps[3*i] for i in range(len(ps)/3)])
#                        if (boltz>uniform(0,1) or new_ene < old_ene):
                #        if ( new_ene < old_ene and abs(charge) < 1e-3):
                        if ( new_ene < old_ene):
                                accept=accept+1
                        else:
                                reject=reject+1
                                ps[pick]=old
                        new_ene = Goodness_of_Fit(ps)
                print("TOTAL= %5d  ACCEPTED= %5d REJECTED= %5d" %(nmoves,accept,reject))
                print("T = %5.5f and Chisq = %5.5f and Charge =%3.3f" %(T,new_ene,charge))
                T=T*0.9
        return new_ene,ps
fene,fpars=Sim_Anneal(INP_pars,DEL_List)
print len(fpars)