scipy/signal/bsplines.py
def qspline1d(signal, lamb=0.0):
    """Compute quadratic spline coefficients for rank-1 array.

    Find the quadratic spline coefficients for a 1-D signal assuming
    mirror-symmetric boundary conditions.   To obtain the signal back from the
    spline representation mirror-symmetric-convolve these coefficients with a
    length 3 FIR window [1.0, 6.0, 1.0]/ 8.0 .

    Parameters
    ----------
    signal : ndarray
        A rank-1 array representing samples of a signal.
    lamb : float, optional
        Smoothing coefficient (must be zero for now).

    Returns
    -------
    c : ndarray
        Cubic spline coefficients.

    """
    if lamb != 0.0:
        raise ValueError("Smoothing quadratic splines not supported yet.")
    else:
        return _quadratic_coeff(signal)
Compute quadratic spline coefficients for rank-1 array.

    Find the quadratic spline coefficients for a 1-D signal assuming
    mirror-symmetric boundary conditions.   To obtain the signal back from the
    spline representation mirror-symmetric-convolve these coefficients with a
    length 3 FIR window [1.0, 6.0, 1.0]/ 8.0 .

    Parameters
    ----------
    signal : ndarray
        A rank-1 array representing samples of a signal.
    lamb : float, optional
        Smoothing coefficient (must be zero for now).

    Returns
    -------
    c : ndarray
        Cubic spline coefficients.

    
Compute quadratic spline coefficients for rank-1 array.
Find the quadratic spline coefficients for a 1-D signal assuming
mirror-symmetric boundary conditions.   To obtain the signal back from the
spline representation mirror-symmetric-convolve these coefficients with a
length 3 FIR window [1.0, 6.0, 1.0]/ 8.0 .

Parameters

signal : ndarray
A rank-1 array representing samples of a signal.
lamb : float, optional
Smoothing coefficient (must be zero for now).

Returns

c : ndarray
Cubic spline coefficients.
Compute quadratic spline coefficients for rank - 1 array . Find the quadratic spline coefficients for a 1 - D signal assuming mirror - symmetric boundary conditions . To obtain the signal back from the spline representation mirror - symmetric - convolve these coefficients with a length 3 FIR window [ 1 . 0 6 . 0 1 . 0 ] / 8 . 0 . Parameters signal : ndarray A rank - 1 array representing samples of a signal . lamb : float optional Smoothing coefficient ( must be zero for now ) . Returns c : ndarray Cubic spline coefficients .
def qspline1d(signal, lamb=0.0):
    if lamb != 0.0:
        raise ValueError("Smoothing quadratic splines not supported yet.")
    else:
        return _quadratic_coeff(signal)
def qspline1d ( signal , lamb = 0.0 ) : if lamb != 0.0 : raise ValueError ( "Smoothing quadratic splines not supported yet." ) else : return _quadratic_coeff ( signal )
Compute quadratic spline coefficients for rank-1 array.
Compute quadratic spline coefficients for rank - 1 array .
"""Compute quadratic spline coefficients for rank-1 array.

    Find the quadratic spline coefficients for a 1-D signal assuming
    mirror-symmetric boundary conditions.   To obtain the signal back from the
    spline representation mirror-symmetric-convolve these coefficients with a
    length 3 FIR window [1.0, 6.0, 1.0]/ 8.0 .

    Parameters
    ----------
    signal : ndarray
        A rank-1 array representing samples of a signal.
    lamb : float, optional
        Smoothing coefficient (must be zero for now).

    Returns
    -------
    c : ndarray
        Cubic spline coefficients.

    """
signal
lamb