scipy/signal/bsplines.py
def cspline1d(signal, lamb=0.0):
    """
    Compute cubic spline coefficients for rank-1 array.

    Find the cubic 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, 4.0, 1.0]/ 6.0 .

    Parameters
    ----------
    signal : ndarray
        A rank-1 array representing samples of a signal.
    lamb : float, optional
        Smoothing coefficient, default is 0.0.

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

    """
    if lamb != 0.0:
        return _cubic_smooth_coeff(signal, lamb)
    else:
        return _cubic_coeff(signal)

    Compute cubic spline coefficients for rank-1 array.

    Find the cubic 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, 4.0, 1.0]/ 6.0 .

    Parameters
    ----------
    signal : ndarray
        A rank-1 array representing samples of a signal.
    lamb : float, optional
        Smoothing coefficient, default is 0.0.

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

    
Compute cubic spline coefficients for rank-1 array.
Find the cubic 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, 4.0, 1.0]/ 6.0 .

Parameters

signal : ndarray
A rank-1 array representing samples of a signal.
lamb : float, optional
Smoothing coefficient, default is 0.0.

Returns

c : ndarray
Cubic spline coefficients.
Compute cubic spline coefficients for rank - 1 array . Find the cubic 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 4 . 0 1 . 0 ] / 6 . 0 . Parameters signal : ndarray A rank - 1 array representing samples of a signal . lamb : float optional Smoothing coefficient default is 0 . 0 . Returns c : ndarray Cubic spline coefficients .
def cspline1d(signal, lamb=0.0):
    if lamb != 0.0:
        return _cubic_smooth_coeff(signal, lamb)
    else:
        return _cubic_coeff(signal)
def cspline1d ( signal , lamb = 0.0 ) : if lamb != 0.0 : return _cubic_smooth_coeff ( signal , lamb ) else : return _cubic_coeff ( signal )
Compute cubic spline coefficients for rank-1 array.
Compute cubic spline coefficients for rank - 1 array .
"""
    Compute cubic spline coefficients for rank-1 array.

    Find the cubic 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, 4.0, 1.0]/ 6.0 .

    Parameters
    ----------
    signal : ndarray
        A rank-1 array representing samples of a signal.
    lamb : float, optional
        Smoothing coefficient, default is 0.0.

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

    """
signal
lamb