python iterative loop gets slower as it continues

I have a for loop like

for tot in range(0,100000): 

at first iterations it is quite fast but as it reaches toward the middle it gets extremely slow. I don't have such code lines that you say sth gets accumulated and gets large so it's computation takes longer.

It stays the same as the first iteration always, but gets processed slower.

Is it because each time tot goes from beginning of "range" to reach to the proper iteration, and as iterative method continues it takes longer to reach to middle of the "range"?

I have no idea why this happens!!!

Inside loop sample code:

for tot in range(0,nt): for k in range(0,nx): if k!=0 and k!=nx-1: for i in range(1,nz-1): phai0[i,k]=(1.0/dz**2)*(w0[i+1,k]-2.0*w0[i,k]+w0[i-1,k])+(1.0/dx**2)*(w0[i,k+1]-2.0*w0[i,k]+w0[i,k-1]) phai1[i,k]=(1.0/dz**2)*(w1[i+1,k]-2.0*w1[i,k]+w1[i-1,k])+(1.0/dx**2)*(w1[i,k+1]-2.0*w1[i,k]+w1[i,k-1]) phai2[i,k]=(2.0-Ncoef**2*dt**2)*phai1[i,k]-phai0[i,k]+1.0*(Ncoef**2)*(dt**2*1.0/dz**2)*(w1[i+1,k]-2*w1[i,k]+w1[i-1,k]) if k==0: for i in range(1,nz-1): phai0[i,k]=(1.0/dz**2)*(w0[i+1,k]-2.0*w0[i,k]+w0[i-1,k])+(1.0/dx**2)*(w0[i,k+1]-2.0*w0[i,k]+w0[i,k-2]) phai1[i,k]=(1.0/dz**2)*(w1[i+1,k]-2.0*w1[i,k]+w1[i-1,k])+(1.0/dx**2)*(w1[i,k+1]-2.0*w1[i,k]+w1[i,k-2]) phai2[i,k]=(2.0-Ncoef**2*dt**2)*phai1[i,k]-phai0[i,k]+1.0*(Ncoef**2)*(dt**2*1.0/dz**2)*(w1[i+1,k]-2*w1[i,k]+w1[i-1,k]) if k==nx-1: for i in range(1,nz-1): phai0[i,k]=(1.0/dz**2)*(w0[i+1,k]-2.0*w0[i,k]+w0[i-1,k])+(1.0/dx**2)*(w0[i,1]-2.0*w0[i,k]+w0[i,k-1]) phai1[i,k]=(1.0/dz**2)*(w1[i+1,k]-2.0*w1[i,k]+w1[i-1,k])+(1.0/dx**2)*(w1[i,1]-2.0*w1[i,k]+w1[i,k-1]) phai2[i,k]=(2.0-Ncoef**2*dt**2)*phai1[i,k]-phai0[i,k]+1.0*(Ncoef**2)*(dt**2*1.0/dz**2)*(w1[i+1,k]-2*w1[i,k]+w1[i-1,k]) for N in range(0,N_inner_iteration): sum_max=0 for k in range(0,nx): if k!=0 and k!=nx-1: for i in range(1,nz): if i!=nz-1: w21[i,k]=0.5*(dz**2)*(w20[i,k+1]+w20[i,k-1])/(dx**2+dz**2)+0.5*(dx**2)*(w20[i+1,k]+w20[i-1,k])/(dx**2+dz**2)-(0.5/(dx**2+dz**2))*(dx**2*dz**2)*phai2[i,k] if i==nz-1: w21[i,k]=1/(1+(p(k*dx,1)/(dx*p(k*dx,2)))+((2/p(k*dx,2)*(p(k*dx,1))**2-p(k*dx,0))/dz)+(p(k*dx,1)/dx/dz))*(((p(k*dx,1)/(dx*p(k*dx,2)))+(p(k*dx,1)/dx/dz))*w0[i,k-1]+(((2/p(k*dx,2)*(p(k*dx,1))**2-p(k*dx,0))/dz)+(p(k*dx,1)/dx/dz))*w0[i-1,k]-((p(k*dx,1)/dx/dz))*w0[i-1,k-1]) sum_max=sum_max+abs(w21[i,k]-w20[i,k]) # w20[i,k]=w21[i,k] if k==0: for i in range(1,nz): if i!=nz-1: w21[i,k]=0.5*(dz**2)*(w20[i,1]+w20[i,k-2])/(dx**2+dz**2)+0.5*(dx**2)*(w20[i+1,k]+w20[i-1,k])/(dx**2+dz**2)-(0.5/(dx**2+dz**2))*(dx**2*dz**2)*phai2[i,k] if i==nz-1: k=0.00000001 w21[i,k]=1/(1+(p(k*dx,1)/(dx*p(k*dx,2)))+((2/p(k*dx,2)*(p(k*dx,1))**2-p(k*dx,0))/dz)+(p(k*dx,1)/dx/dz))*(((p(k*dx,1)/(dx*p(k*dx,2)))+(p(k*dx,1)/dx/dz))*w0[i,k-2]+(((2/p(k*dx,2)*(p(k*dx,1))**2-p(k*dx,0))/dz)+(p(k*dx,1)/dx/dz))*w0[i-1,k]-((p(k*dx,1)/dx/dz))*w0[i-1,k-2]) sum_max=sum_max+abs(w21[i,k]-w20[i,k]) if k==nx-1: for i in range(1,nz): # w21[i,k]=w21[i,0] # w20[i,k]=w21[i,k] if i!=nz-1: w21[i,k]=0.5*(dz**2)*(w20[i,1]+w20[i,k-1])/(dx**2+dz**2)+0.5*(dx**2)*(w20[i+1,k]+w20[i-1,k])/(dx**2+dz**2)-(0.5/(dx**2+dz**2))*(dx**2*dz**2)*phai2[i,k] if i==nz-1: w21[i,k]=1/(1+(p(k*dx,1)/(dx*p(k*dx,2)))+((2/p(k*dx,2)*(p(k*dx,1))**2-p(k*dx,0))/dz)+(p(k*dx,1)/dx/dz))*(((p(k*dx,1)/(dx*p(k*dx,2)))+(p(k*dx,1)/dx/dz))*w0[i,k-1]+(((2/p(k*dx,2)*(p(k*dx,1))**2-p(k*dx,0))/dz)+(p(k*dx,1)/dx/dz))*w0[i-1,k]-((p(k*dx,1)/dx/dz))*w0[i-1,k-1]) sum_max=sum_max+abs(w21[i,k]-w20[i,k]) # w20[i,k]=w21[i,k] w20[:]=w21[:] if (1.0/(nx*nz))*sum_max<0.0000001: break print (1.0/(nx*nz))*sum_max, "N=",N w0[:]=w1[:] w1[:]=w20[:] w_final[:,:,tot]=w1[:] for ordstep in range(1,num_of_orders+1): integ_sum2=0 for zstep in range (0,nz): for xstep in range (0,nx): integ_sum2=integ_sum2+w1[zstep,xstep]*np.sin(ordstep*(k_z*1.0/m)*zstep*dz)*np.sin(ordstep*(k_x*1.0/n)*xstep*dx-omega*tot*dt)*dx*dz Amp[ordstep-1,tot]=4.0/(l*h)*integ_sum2/Ampref if tot%1==0: Ampsave=np.reshape(Amp[:,tot],(1,5)) with open('test.csv', 'a') as file: np.savetxt(file,np.array(Ampsave)) # np.save(outfile,Amp) oldcol = wframe wframe = ax.plot_surface(X, Z, w1, rstride=2, cstride=2) if oldcol is not None: ax.collections.remove(oldcol) plt.pause(.001) ax.set_xlabel('(X)') ax.set_ylabel('(Z)') ax.set_zlabel('$ W_{Numerical} $') plt.figure('Amplitude Evolution') plt.axis([0, 40000, -2, 2]) plt.scatter(tot, Amp[0,tot]) plt.scatter(tot, Amp[1,tot]) print Amp[0,tot] plt.draw() plt.legend(bbox_to_anchor=(1, 1), loc=1, borderaxespad=0.) plt.title('Amplitude Evolution') plt.xlabel('Time[s]',fontsize=25) plt.ylabel('Amplitude',fontsize=25) plt.savefig("res.png", transparent = True, pad_inches=0) plt.show() 

I have also changed all range to xrange and avoided using np. inside the loops by predefining them.