Пример #1
0
def sproot(tck,mest=10):
    """
    Find the roots of a cubic B-spline.

    Given the knots (>=8) and coefficients of a cubic B-spline return the
    roots of the spline.

    Parameters
    ----------
    tck : tuple
        A tuple (t,c,k) containing the vector of knots,
        the B-spline coefficients, and the degree of the spline.
        The number of knots must be >= 8.
        The knots must be a montonically increasing sequence.
    mest : int
     An estimate of the number of zeros (Default is 10).

    Returns
    -------
    zeros : ndarray
        An array giving the roots of the spline.

    See also
    --------
    splprep, splrep, splint, spalde, splev
    bisplrep, bisplev
    UnivariateSpline, BivariateSpline


    References
    ----------
    .. [1] C. de Boor, "On calculating with b-splines", J. Approximation
        Theory, 6, p.50-62, 1972.
    .. [2] M.G. Cox, "The numerical evaluation of b-splines", J. Inst. Maths
        Applics, 10, p.134-149, 1972.
    .. [3] P. Dierckx, "Curve and surface fitting with splines", Monographs
        on Numerical Analysis, Oxford University Press, 1993.

    """
    t,c,k=tck
    if k==4: t=t[1:-1]
    if k==5: t=t[2:-2]
    try:
        c[0][0]
        parametric = True
    except:
        parametric = False
    if parametric:
        return _ntlist(map(lambda c,t=t,k=k,mest=mest:sproot([t,c,k],mest),c))
    else:
        if len(t)<8:
            raise TypeError,"The number of knots %d>=8"%(len(t))
        z,ier=_fitpack._sproot(t,c,k,mest)
        if ier==10:
            raise TypeError,"Invalid input data. t1<=..<=t4<t5<..<tn-3<=..<=tn must hold."
        if ier==0: return z
        if ier==1:
            print "Warning: the number of zeros exceeds mest"
            return z
        raise TypeError,"Unknown error"
Пример #2
0
def sproot(tck, mest=10):
    """Find the roots of a cubic B-spline.

    Description:

      Given the knots (>=8) and coefficients of a cubic B-spline return the
      roots of the spline.

    Inputs:

      tck -- A length 3 sequence describing the given spline (See splev).
             The number of knots must be >= 8.  The knots must be a montonically
             increasing sequence.
      mest -- An estimate of the number of zeros (Default is 10).

    Outputs: (zeros, )

      zeros -- An array giving the roots of the spline.

    See also:
      splprep, splrep, splint, spalde, splev - evaluation, roots, integral
      bisplrep, bisplev - bivariate splines
      UnivariateSpline, BivariateSpline - an alternative wrapping
              of the FITPACK functions

    """
    t, c, k = tck
    if k == 4: t = t[1:-1]
    if k == 5: t = t[2:-2]
    try:
        c[0][0]
        parametric = True
    except:
        parametric = False
    if parametric:
        return _ntlist(
            map(lambda c, t=t, k=k, mest=mest: sproot([t, c, k], mest), c))
    else:
        if len(t) < 8:
            raise TypeError, "The number of knots %d>=8" % (len(t))
        z, ier = _fitpack._sproot(t, c, k, mest)
        if ier == 10:
            raise TypeError, "Invalid input data. t1<=..<=t4<t5<..<tn-3<=..<=tn must hold."
        if ier == 0: return z
        if ier == 1:
            print "Warning: the number of zeros exceeds mest"
            return z
        raise TypeError, "Unknown error"
Пример #3
0
def sproot(tck,mest=10):
    """Find the roots of a cubic B-spline.

    Description:

      Given the knots (>=8) and coefficients of a cubic B-spline return the
      roots of the spline.

    Inputs:

      tck -- A length 3 sequence describing the given spline (See splev).
             The number of knots must be >= 8.  The knots must be a montonically
             increasing sequence.
      mest -- An estimate of the number of zeros (Default is 10).

    Outputs: (zeros, )

      zeros -- An array giving the roots of the spline.

    See also:
      splprep, splrep, splint, spalde, splev - evaluation, roots, integral
      bisplrep, bisplev - bivariate splines
      UnivariateSpline, BivariateSpline - an alternative wrapping
              of the FITPACK functions

    """
    t,c,k=tck
    if k==4: t=t[1:-1]
    if k==5: t=t[2:-2]
    try:
        c[0][0]
        parametric = True
    except:
        parametric = False
    if parametric:
        return _ntlist(map(lambda c,t=t,k=k,mest=mest:sproot([t,c,k],mest),c))
    else:
        if len(t)<8:
            raise TypeError,"The number of knots %d>=8"%(len(t))
        z,ier=_fitpack._sproot(t,c,k,mest)
        if ier==10:
            raise TypeError,"Invalid input data. t1<=..<=t4<t5<..<tn-3<=..<=tn must hold."
        if ier==0: return z
        if ier==1:
            print "Warning: the number of zeros exceeds mest"
            return z
        raise TypeError,"Unknown error"
Пример #4
0
def sproot(tck,mest=10):
    """
    Find the roots of a cubic B-spline.

    Given the knots (>=8) and coefficients of a cubic B-spline return the
    roots of the spline.

    Parameters
    ----------

    tck -- A length 3 sequence describing the given spline (See splev).
           The number of knots must be >= 8.  The knots must be a montonically
           increasing sequence.

    mest -- An estimate of the number of zeros (Default is 10)


    Returns
    -------

    zeros -- An array giving the roots of the spline.

    See also
    --------
    splprep, splrep, splint, spalde, splev :
        evaluation, roots, integral
    bisplrep, bisplev :
        bivariate splines
    UnivariateSpline, BivariateSpline :
        An alternative wrapping of the FITPACK functions.

    References
    ----------
    .. [1] C. de Boor, "On calculating with b-splines", J. Approximation
        Theory, 6, p.50-62, 1972.
    .. [2] M.G. Cox, "The numerical evaluation of b-splines", J. Inst. Maths
        Applics, 10, p.134-149, 1972.
    .. [3] P. Dierckx, "Curve and surface fitting with splines", Monographs
        on Numerical Analysis, Oxford University Press, 1993.

    """
    t,c,k=tck
    if k==4: t=t[1:-1]
    if k==5: t=t[2:-2]
    try:
        c[0][0]
        parametric = True
    except:
        parametric = False
    if parametric:
        return _ntlist(map(lambda c,t=t,k=k,mest=mest:sproot([t,c,k],mest),c))
    else:
        if len(t)<8:
            raise TypeError,"The number of knots %d>=8"%(len(t))
        z,ier=_fitpack._sproot(t,c,k,mest)
        if ier==10:
            raise TypeError,"Invalid input data. t1<=..<=t4<t5<..<tn-3<=..<=tn must hold."
        if ier==0: return z
        if ier==1:
            print "Warning: the number of zeros exceeds mest"
            return z
        raise TypeError,"Unknown error"