#load modules
import numpy as np

#Initialisation and constant definition


#define matrix, right-hand-side and target solution

# A x = b = A x_target  with x_target[i]=i
# aim if to recover x_target after inversion

#how much is the condition number for a Hilbert matrix of dimension 100

#define descent iterations with stopping criteria 

k=0
while(res[k]>0.001 and k<niter):  
    k+=1

    #define gradient gk

    #define optimal descent step size 

    #define new iterate xn+1
    
    #store convergenceresults
    
    
#plot convergence histories versus iterations relative to first iterations values
#plot target and calculated solutions