anchor.diff:  !  Updated: 2019-09-24
   !  Rayleigh distribution with radial part of Box-Muller.
   ! ================================================================================================ !
  -subroutine rnd_rayleigh(seriesID, rndVec, vLen)
  +subroutine rnd_rayleigh_nocut(seriesID, rndVec, vLen)
   
     use crcoall
     use mathlib_bouncer
  
positive.code:     rnd_seriesData(seriesID)%hasNormR   = .true.
    end if
  
  end subroutine rnd_normal
  
  ! ================================================================================================ !
  !  V.K. Berglyd Olsen, BE-ABP-HSS
  
negative.code:     rndVec(i) = sqrt((-two)*log_mb(rndTmp(i)))
    end do
  
  end subroutine rnd_rayleigh_nocut
  
  ! ================================================================================================ !
  !  V.K. Berglyd Olsen, BE-ABP-HSS
  !  Created: 2019-09-26
  !  Updated: 2019-09-26
  !  Rayleigh distribution with radial part of Box-Muller and a max cut.
  ! ================================================================================================ !
  subroutine rnd_rayleigh_maxcut(seriesID, rndVec, vLen, sMax)
  
    use crcoall
    use mathlib_bouncer
    use numerical_constants, only : one, two
  
    integer,          intent(in)  :: seriesID, vLen
    real(kind=fPrec), intent(out) :: rndVec(vLen), sMax
  
    integer i
    real(kind=fPrec) rndTmp(vLen), cFac
  
    cFac = one - exp_mb(-(sMax**2/two))
    call rnd_uniform(seriesID, rndTmp, vLen)
    do i=1,vLen
      rndVec(i) = sqrt((-two)*log_mb(one - cFac*rndTmp(i)))
    end do
  
  end subroutine rnd_rayleigh_maxcut
  
  ! ================================================================================================ !
  !  V.K. Berglyd Olsen, BE-ABP-HSS
  !  Created: 2019-09-26
  !  Updated: 2019-09-26
  !  Rayleigh distribution with radial part of Box-Muller and a min and max cut.
  ! ================================================================================================ !
  subroutine rnd_rayleigh_maxmincut(seriesID, rndVec, vLen, sMax, sMin)
  
    use crcoall
    use mathlib_bouncer
    use numerical_constants, only : one, two
  
    integer,          intent(in)  :: seriesID, vLen
    real(kind=fPrec), intent(out) :: rndVec(vLen), sMax, sMin
  
    integer i
    real(kind=fPrec) rndTmp(vLen), cFac, sMin2
  
    cFac  = one - exp_mb(-((sMax+sMin)*(sMax-sMin)/two))
    sMin2 = sMin**2
    call rnd_uniform(seriesID, rndTmp, vLen)
    do i=1,vLen
      rndVec(i) = sqrt(sMin2 - two*log_mb(one - cFac*rndTmp(i)))
    end do
  
  end subroutine rnd_rayleigh_maxmincut
  
  ! ================================================================================================ !
  !  V.K. Berglyd Olsen, BE-ABP-HSS
  !  Created: 2019-09-24
  !  Updated: 2019-09-24
  !  Irwin-Hall approximation of a normal distribution of order N = 1:10
  !  The distribution is centred around nOrder/2 and extends from - nOrder/2 to + nOrder/2
  !  1st order is equivalen to uniform, 2nd order is triangular, and 3rd order and up approaches a
  !  Gaussian distribution. First few orders should be faster than Box-Muller.
  ! ================================================================================================ !
  subroutine rnd_irwinHall(seriesID, rndVec, vLen, nOrder)
  