code: def qspline1d(signal, lamb=0.0):
      """Compute quadratic spline coefficients for rank-1 array.
  
      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
          Quadratic spline coefficients.
  
      See Also
      --------
      qspline1d_eval : Evaluate a quadratic spline at the new set of points.
  
      Notes
      -----
      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 .
  
      Examples
      --------
      We can filter a signal to reduce and smooth out high-frequency noise with
      a quadratic spline:
  
      >>> import matplotlib.pyplot as plt
      >>> from scipy.signal import qspline1d, qspline1d_eval
      >>> rng = np.random.default_rng()
      >>> sig = np.repeat([0., 1., 0.], 100)
      >>> sig += rng.standard_normal(len(sig))*0.05  # add noise
      >>> time = np.linspace(0, len(sig))
      >>> filtered = qspline1d_eval(qspline1d(sig), time)
      >>> plt.plot(sig, label="signal")
      >>> plt.plot(time, filtered, label="filtered")
      >>> plt.legend()
      >>> plt.show()
  
      """
      if lamb != 0.0:
          raise ValueError(
              "Smoothing quadratic splines not supported yet."
          )
      else:
          return _quadratic_coeff(signal)
  
imports: from numpy import logical_and, asarray, pi, zeros_like, piecewise, array, arctan2, tan, zeros, arange, floor
  from numpy.core.umath import sqrt, exp, greater, less, cos, add, sin, less_equal, greater_equal
  from .spline import cspline2d, sepfir2d
  from scipy.special import comb
  from scipy._lib._util import float_factorial
label_desc: Use image node_id 14 for calling a global function with example usage: qspline1d(signal, lamb) and returns: _quadratic_coeff