old_contents: from .. import hill5infall
  from ...classes import Spectrum
  from ... import units
  import numpy as np
  from astropy import units as u
  
  def test_hill5():
      x = np.linspace(-5,5,20)*u.km/u.s
      xarr = units.SpectroscopicAxis(x, refX=5*u.GHz, velocity_convention='radio')
      y = hill5infall.hill5_model(xarr, 0.5, 1.0, 2.0, 1.0, 1.0)
  
      sp = Spectrum(xarr=xarr, data=y)
  
      sp.Registry.add_fitter('hill5_fitter', hill5infall.hill5_fitter, 5)
  
      sp.specfit(fittype='hill5_fitter', guesses=[0.4, 0.9, 2.2, 0.9, 1.1])
  
      np.testing.assert_almost_equal(sp.specfit.parinfo[0].value, 0.5)
      np.testing.assert_almost_equal(sp.specfit.parinfo[1].value, 1.0)
      np.testing.assert_almost_equal(sp.specfit.parinfo[2].value, 2.0)
      np.testing.assert_almost_equal(sp.specfit.parinfo[3].value, 1.0)
      np.testing.assert_almost_equal(sp.specfit.parinfo[4].value, 1.0)
  
  def test_hill5_guessing():
  
      rslt = hill5infall.parse_3par_guesses(['amp', 'cen', 'wid'])
  
      assert rslt == [1.0, 'cen', 1.0, 'wid', 'amp']
  
      rslt = hill5infall.parse_3par_guesses(['amp1', 'cen1', 'wid1',
                                             'amp2', 'cen2', 'wid2',
                                            ])
  
      assert rslt == [1.0, 'cen1', 1.0, 'wid1', 'amp1',
                      1.0, 'cen2', 1.0, 'wid2', 'amp2',
                     ]
  
new_contents: from .. import hill5infall
  from ...classes import Spectrum
  from ... import units
  import numpy as np
  from astropy import units as u
  
  def test_hill5():
      x = np.linspace(-5,5,20)*u.km/u.s
      xarr = units.SpectroscopicAxis(x, refX=5*u.GHz, velocity_convention='radio')
      y = hill5infall.hill5_model(xarr, 0.5, 1.0, 2.0, 1.0, 1.0)
  
      sp = Spectrum(xarr=xarr, data=y, header={})
  
      sp.Registry.add_fitter('hill5_fitter', hill5infall.hill5_fitter, 5)
  
      sp.specfit(fittype='hill5_fitter', guesses=[0.4, 0.9, 2.2, 0.9, 1.1])
  
      np.testing.assert_almost_equal(sp.specfit.parinfo[0].value, 0.5)
      np.testing.assert_almost_equal(sp.specfit.parinfo[1].value, 1.0)
      np.testing.assert_almost_equal(sp.specfit.parinfo[2].value, 2.0)
      np.testing.assert_almost_equal(sp.specfit.parinfo[3].value, 1.0)
      np.testing.assert_almost_equal(sp.specfit.parinfo[4].value, 1.0)
  
  def test_hill5_guessing():
  
      rslt = hill5infall.parse_3par_guesses(['amp', 'cen', 'wid'])
  
      assert rslt == [1.0, 'cen', 1.0, 'wid', 'amp']
  
      rslt = hill5infall.parse_3par_guesses(['amp1', 'cen1', 'wid1',
                                             'amp2', 'cen2', 'wid2',
                                            ])
  
      assert rslt == [1.0, 'cen1', 1.0, 'wid1', 'amp1',
                      1.0, 'cen2', 1.0, 'wid2', 'amp2',
                     ]
  
subject: test fixing: I made some 'prints' into 'warnings', so because the tests are set to fail if warnings are raised, we need to avoid them