import numpy as np from scipy.integrate import odeint from math import * from scipy.integrate import quad import pandas as pd import os import warnings warnings.filterwarnings("ignore") #you need add the following 3 lines from multiprocessing import Pool from multiprocessing import Process import multiprocessing print("Model 4, Equation 11") print("") ###################### STEP NUMBER ####################### N = int(input("PLEASE ENTER NUMBER OF STEP WALKS: ")) # Step walk by user dec=int(input("NUMBER OF DECIMAL PLACES OF OUTPUTS (RECOMENDED 10-15)?")) print("") print("PLEASE WAIT, METROPOLIS HASTINGS IS RUNNING ... ") print("") def FIT(): ########################################################## od0o = np.zeros((N,)) od0o[0]=0.72 od0n = np.zeros((N,)) Mo = np.zeros((N,)) Mo[0]= 0 Mn = np.zeros((N,)) co = np.zeros((N,)) co[0]= 0.84 cn = np.zeros((N,)) bo = np.zeros((N,)) bo[0]= 0.02 bn = np.zeros((N,)) H0o = np.zeros((N,)) H0o[0]= 70 H0n = np.zeros((N,)) Orco = np.zeros((N,)) Orco[0]= 0.0003 Orcn = np.zeros((N,)) temp=1e10 # a big number ########################################################## CovCMB=[[3.182,18.253,-1.429], [18.253,11887.879,-193.808], [-1.429,-193.808,4.556]] # CMB DATA ########################################################## def OD_H(U,z,c,b,Orc): od, H = U Omegai = 3 * b * ((1- od - 2*(Orc)**0.5) + (1- od - 2*(Orc)**0.5)**2/(1-2*(Orc)**0.5)) #equation 10 div1=np.divide((c**2-od),(1+z),where=(1+z)!=0) div2=np.divide(H ,(1+z),where=(1+z)!=0) dMdt = (div1)*(6*od+6-9*(od/c**2)+ Omegai)*(1+c**2+od*(1-3/c**2))**(-1) dHdt = (div2)*(6*od+6-9*(od/c**2)+ Omegai)*(1+c**2+od*(1-3/c**2))**(-1) return [dMdt, dHdt] def solution(H0,z1,z,od0,c,b,Orc): U = odeint(OD_H,[od0,H0],[z1,z], args=(c,b,Orc))[-1] od, H = U return H ########################################################## def DMCMB1(H0,z1,z,od0,c,b,Orc): dm = 1090 * 1/solution(H0,z1,z,od0,c,b,Orc) return dm def R1(H0,z1,z,od0,c,b,Orc): #r=sqrt(Om)*(70/299000)*rszstar(z,Om,Od) r = sqrt(1-od0-2*(Orc)**0.5)*DMCMB1(H0,z1,z,od0,c,b,Orc) return r def lA1(H0,z1,z,od0,c,b,Orc): la=((3.14*299000/H0)*DMCMB1(H0,z1,z,od0,c,b,Orc))/(153) return la def CMBMATRIX1(H0,z1,z,od0,c,b,Orc,M): hmCMB1=[lA1(H0,z1,z,od0,c,b,Orc)-301.57, R1(H0,z1,z,od0,c,b,Orc)-1.7382+M, 0.0222-0.02262] vmCMB1=[[lA1(H0,z1,z,od0,c,b,Orc)-301.57], [R1(H0,z1,z,od0,c,b,Orc)-1.7382], [0.0222-0.02262]] fmCMB1=np.dot(hmCMB1,CovCMB) smCMB1=np.dot(fmCMB1,vmCMB1)[0] return smCMB1 ###################################################### def TOTAL(H0, od0, c, b,Orc, M) : total = CMBMATRIX1(H0,0,1090,od0,c,b,Orc,M) return total ###################################################### ################## MCMC - MH ######################### highest=0 pat='C:/Users/21/Desktop/MHT/Models/outputs' file_path = os.path.join(pat,'Model3.txt') file_path2 = os.path.join(pat,'Model3min.txt') with open(file_path, 'w') as f: # DATA WILL BE SAVED IN THIS FILE, PLEASE BECAREFUL TO CHANGE THE NAME IN EACH RUN TO AVOIDE REWRITING. with open(file_path2, 'w') as d: for i in range (1,N): num = 0 R = np.random.uniform(0,1) while True: num += 1 od0n[i] = od0o[i-1] + 0.001 * np.random.normal() H0n[i] = H0o[i-1] + 0.01 * np.random.normal() bn[i] = bo[i-1] + 0.001 * np.random.normal() cn[i] = co[i-1] + 0.001 * np.random.normal() Mn[i] = Mo[i-1] + 0.01 * np.random.normal() Orcn[i] = Orco[i-1] + 0.00001 * np.random.normal() L = np.exp(-0.5 * (TOTAL(H0n[i], od0n[i], cn[i], bn[i],Orcn[i], Mn[i]) - TOTAL(H0o[i-1], od0o[i-1], co[i-1], bo[i-1],Orco[i-1], Mo[i-1]))) # L = exp(-( x^2 )/2) LL=min(1,max(L,0)) if LL>R: od0o[i]= od0n[i] H0o[i] = H0n[i] bo[i] = bn[i] co[i] = cn[i] Mo[i] = Mn[i] Orco[i] = Orcn[i] chi = TOTAL(H0o[i], od0o[i], co[i], bo[i],Orco[i], Mo[i]) else: od0o[i]= od0o[i-1] H0o[i] = H0o[i-1] bo[i] = bo[i-1] co[i] = co[i-1] Mo[i] = Mo[i-1] Orco[i] = Orco[i-1] chi = TOTAL(H0o[i], od0o[i], co[i], bo[i],Orco[i], Mo[i]) if (Mo[i]>0 and 0<bo[i]<0.09 and Orco[i]>0) or num>100: # constraining the value to stay in positive area highest = max(num, highest) break f.write("{0}\t{1}\t{2}\t{3}\t{4}\t{5}\t{6}\t{7}\t{8}\t{9}\t{10}\t{11}\t{12}\n".format(round(chi,dec),' ',round(H0o[i],dec),' ',round(od0o[i],dec),' ', round(co[i],dec),' ',round(bo[i],dec),' ', round(Orco[i],dec),' ',round(Mo[i],dec))) if chi<temp: temp=chi aa = H0o[i] bb = od0o[i] cc = co[i] dd = bo[i] ee = Mo[i] ff=Orco[i] Om=1-2*sqrt(Orco[i])-od0o[i] # minimum of chi and its parameters d.write("{0}\t{1}\t{2}\t{3}\t{4}\t{5}\t{6}\t{7}\t{8}\t{9}\t{10}\t{11}\t{12},\t{13}\t{14}\n".format(round(temp,dec), "H =", round(aa,dec), "Orc=", round(ff,dec), "OD =",round(bb,dec),"c =", round(cc,dec),"b =", round(dd,dec), "M =",round(ee,dec),"Om =",round(Om,dec))) print(round(temp,dec), "H =", round(aa,dec), "Orc=",round(ff,dec), "OD =",round(bb,dec),"c =", round(cc,dec),"b =", round(dd,dec), "M =",round(ee,dec),"Om =",round(Om,dec)) #print(highest) print("") #test = input("Press the enter to exit...") #print(test) if __name__ == '__main__': p = multiprocessing.Process(target=FIT) p.start() p.join() 

A question. Using multiprocessing is for having a faster code. But after using the following framework, getting the outputs takes the same time or more as it took in normal code.

from multiprocessing import Process import multiprocessing def code() : my code  if __name__ == '__main__' : p = multiprocessing.Process(target = code) p.start() p.join() 

because of being 2 processors laptop, after running this code the program wants me to import data two times. The problem is time which did not make any sense in this way. I run into a long time as long as the normal code without parallelism.

A question. Using multiprocessing is for having a faster code. But after using the following framework, getting the outputs takes the same time or more as it took in normal code.

import multiprocessing def code() : my code if __name__ == '__main__' :  p = multiprocessing.Process(target = code)  p.start()  p.join() 

because of being 2 processors laptop, after running this code the program wants me to import data two times. The problem is time which did not make any sense in this way. I run into a long time as long as the normal code without parallelism.