old_contents: # Tests of the diskdf module: distribution functions from Dehnen (1999)
  import numpy
  from galpy.df import dehnendf, shudf
  
  # Tests for cold population, flat rotation curve: <vt> =~ v_c
  def test_dehnendf_cold_flat_vt():
      df= dehnendf(profileParams=(0.3333333333333333,1.0, 0.01),
                   beta=0.,correct=False)
      assert numpy.fabs(df.meanvT(1.)-1.) < 10.**-3., 'mean vT of cold dehnendf in a flat rotation curve is not close to V_c at R=1'
      assert numpy.fabs(df.meanvT(0.5)-1.) < 10.**-3., 'mean vT of cold dehnendf in a flat rotation curve is not close to V_c at R=0.5'
      assert numpy.fabs(df.meanvT(2.)-1.) < 10.**-3., 'mean vT of cold dehnendf in a flat rotation curve is not close to V_c at R=2'
      return None
  
new_contents: # Tests of the diskdf module: distribution functions from Dehnen (1999)
  import numpy
  from galpy.df import dehnendf, shudf
  
  # Tests for cold population, flat rotation curve: <vt> =~ v_c
  def test_dehnendf_cold_flat_vt():
      df= dehnendf(profileParams=(0.3333333333333333,1.0, 0.01),
                   beta=0.,correct=False)
      assert numpy.fabs(df.meanvT(1.)-1.) < 10.**-3., 'mean vT of cold dehnendf in a flat rotation curve is not close to V_c at R=1'
      assert numpy.fabs(df.meanvT(0.5)-1.) < 10.**-3., 'mean vT of cold dehnendf in a flat rotation curve is not close to V_c at R=0.5'
      assert numpy.fabs(df.meanvT(2.)-1.) < 10.**-3., 'mean vT of cold dehnendf in a flat rotation curve is not close to V_c at R=2'
      return None
  
  # Tests for cold population, power-law rotation curve: <vt> =~ v_c
  def test_dehnendf_cold_powerrise_vt():
      # Rising rotation curve
      beta= 0.2
      df= dehnendf(profileParams=(0.3333333333333333,1.0, 0.01),
                   beta=beta,correct=False)
      assert numpy.fabs(df.meanvT(1.)-1.) < 10.**-3., 'mean vT of cold dehnendf in a power-law rotation curve is not close to V_c at R=1'
      assert numpy.fabs(df.meanvT(0.5)-(0.5)**beta) < 10.**-3., 'mean vT of cold dehnendf in a power-law rotation curve is not close to V_c at R=0.5'
      assert numpy.fabs(df.meanvT(2.)-(2.)**beta) < 10.**-3., 'mean vT of cold dehnendf in a power-law rotation curve is not close to V_c at R=2'
  
  def test_dehnendf_cold_powerfall_vt():
      # Falling rotation curve
      beta= -0.2
      df= dehnendf(profileParams=(0.3333333333333333,1.0, 0.01),
                   beta=beta,correct=False)
      assert numpy.fabs(df.meanvT(1.)-1.) < 10.**-3., 'mean vT of cold dehnendf in a power-law rotation curve is not close to V_c at R=1'
      assert numpy.fabs(df.meanvT(0.5)-(0.5)**beta) < 10.**-3., 'mean vT of cold dehnendf in a power-law rotation curve is not close to V_c at R=0.5'
      assert numpy.fabs(df.meanvT(2.)-(2.)**beta) < 10.**-3., 'mean vT of cold dehnendf in a power-law rotation curve is not close to V_c at R=2'
      return None
  
subject: test of meanvT for cold population for power-law rotation curves