parameters: (a, b, tck, full_output=0)
docstring: Evaluate the definite integral of a B-spline.
  
      Given the knots and coefficients of a B-spline, evaluate the definite
      integral of the smoothing polynomial between two given points.
  
      Parameters
      ----------
      a, b : float
          The end-points of the integration interval.
      tck : tuple
          A tuple (t,c,k) containing the vector of knots, the B-spline
          coefficients, and the degree of the spline (see `splev`).
      full_output : int, optional
          Non-zero to return optional output.
  
      Returns
      -------
      integral : float
          The resulting integral.
      wrk : ndarray
          An array containing the integrals of the normalized B-splines
          defined on the set of knots.
  
      Notes
      -----
      splint silently assumes that the spline function is zero outside the data
      interval (a, b).
  
      See Also
      --------
      splprep, splrep, sproot, spalde, splev
      bisplrep, bisplev
      UnivariateSpline, BivariateSpline
  
      References
      ----------
      .. [1] P.W. Gaffney, The calculation of indefinite integrals of b-splines",
          J. Inst. Maths Applics, 17, p.37-41, 1976.
      .. [2] P. Dierckx, "Curve and surface fitting with splines", Monographs
          on Numerical Analysis, Oxford University Press, 1993.
docstring_summary: Evaluate the definite integral of a B-spline.
docstring_tokens: Evaluate the definite integral of a B - spline .
function: def splint(a, b, tck, full_output=0):
      """
      Evaluate the definite integral of a B-spline.
  
      Given the knots and coefficients of a B-spline, evaluate the definite
      integral of the smoothing polynomial between two given points.
  
      Parameters
      ----------
      a, b : float
          The end-points of the integration interval.
      tck : tuple
          A tuple (t,c,k) containing the vector of knots, the B-spline
          coefficients, and the degree of the spline (see `splev`).
      full_output : int, optional
          Non-zero to return optional output.
  
      Returns
      -------
      integral : float
          The resulting integral.
      wrk : ndarray
          An array containing the integrals of the normalized B-splines
          defined on the set of knots.
  
      Notes
      -----
      splint silently assumes that the spline function is zero outside the data
      interval (a, b).
  
      See Also
      --------
      splprep, splrep, sproot, spalde, splev
      bisplrep, bisplev
      UnivariateSpline, BivariateSpline
  
      References
      ----------
      .. [1] P.W. Gaffney, The calculation of indefinite integrals of b-splines",
          J. Inst. Maths Applics, 17, p.37-41, 1976.
      .. [2] P. Dierckx, "Curve and surface fitting with splines", Monographs
          on Numerical Analysis, Oxford University Press, 1993.
  
      """
      t, c, k = tck
      try:
          c[0][0]
          parametric = True
      except Exception:
          parametric = False
      if parametric:
          return list(map(lambda c, a=a, b=b, t=t, k=k:
                          splint(a, b, [t, c, k]), c))
      else:
          aint, wrk = _fitpack._splint(t, c, k, a, b)
          if full_output:
              return aint, wrk
          else:
              return aint
function_tokens: def splint ( a , b , tck , full_output = 0 ) : t , c , k = tck try : c [ 0 ] [ 0 ] parametric = True except Exception : parametric = False if parametric : return list ( map ( lambda c , a = a , b = b , t = t , k = k : splint ( a , b , [ t , c , k ] ) , c ) ) else : aint , wrk = _fitpack . _splint ( t , c , k , a , b ) if full_output : return aint , wrk else : return aint