text: #!/usr/bin/env python3
  #
  # Just test that the code runs and produces sensible output!
  #
  import numpy as np                                                      
  import zeftr as Z                                                       
  import matplotlib.pyplot as plt
  # These are taken from the DarkSky simulation, but it could
  # be almost anything for our purposes.
  pk="pk_test.txt"
  ff=0.50765
  b1=1.0
  b2=1.0
  bs=1.0
  Rf=15.00
  # Call the code for pre- and post-reconstruction xi.
  zel=Z.ZeftRecon()                                                       
  raw=zel(pk,ff,b1,b2,bs,-1,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0)
  rec=zel(pk,ff,b1,b2,bs,Rf,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0)
  # and compare them in a figure.
  fig,ax = plt.subplots(1,1)
  ax.plot(raw[1:,0], raw[1:,1],'b:' ,label=r'Raw$(\ell=0)$')
  ax.plot(raw[1:,0],-raw[1:,2],'b--',label=r'Raw$(\ell=2)$')
  ax.plot(rec[1:,0], rec[1:,1],'r:' ,label=r'Rec$(\ell=0)$')
  ax.plot(rec[1:,0],-rec[1:,2],'r--',label=r'Rec$(\ell=2)$')
  ax.set_xlabel(r'$s\quad[h^{-1}{\rm Mpc}]$')
  ax.set_ylabel(r'$i^\ell s^2\xi(s)\quad[h^{-2}{\rm Mpc}^2]$')
  # tidy up and save the figure.
  plt.tight_layout()
  plt.savefig('test.pdf')
  #
  