parameters: (xk, yk, order=3, kind='smoothest', conds=None)
return_statement: return xk, coefs, order
docstring: Return a representation of a spline given data-points at internal knots
  
      Parameters
      ----------
      xk : array_like
          The input array of x values of rank 1
      yk : array_like
          The input array of y values of rank N. `yk` can be an N-d array to
          represent more than one curve, through the same `xk` points. The first
          dimension is assumed to be the interpolating dimension and is the same
          length of `xk`.
      order : int, optional
          Order of the spline
      kind : str, optional
          Can be 'smoothest', 'not_a_knot', 'fixed', 'clamped', 'natural',
          'periodic', 'symmetric', 'user', 'mixed' and it is ignored if order < 2
      conds : optional
          Conds
  
      Returns
      -------
      splmake : tuple
          Return a (`xk`, `cvals`, `k`) representation of a spline given
          data-points where the (internal) knots are at the data-points.
docstring_summary: Return a representation of a spline given data-points at internal knots
docstring_tokens: Return a representation of a spline given data - points at internal knots
function: def splmake(xk, yk, order=3, kind='smoothest', conds=None):
      """
      Return a representation of a spline given data-points at internal knots
  
      Parameters
      ----------
      xk : array_like
          The input array of x values of rank 1
      yk : array_like
          The input array of y values of rank N. `yk` can be an N-d array to
          represent more than one curve, through the same `xk` points. The first
          dimension is assumed to be the interpolating dimension and is the same
          length of `xk`.
      order : int, optional
          Order of the spline
      kind : str, optional
          Can be 'smoothest', 'not_a_knot', 'fixed', 'clamped', 'natural',
          'periodic', 'symmetric', 'user', 'mixed' and it is ignored if order < 2
      conds : optional
          Conds
  
      Returns
      -------
      splmake : tuple
          Return a (`xk`, `cvals`, `k`) representation of a spline given
          data-points where the (internal) knots are at the data-points.
  
      """
      yk = np.asanyarray(yk)
  
      order = int(order)
      if order < 0:
          raise ValueError("order must not be negative")
      if order == 0:
          return xk, yk[:-1], order
      elif order == 1:
          return xk, yk, order
  
      try:
          func = eval('_find_%s' % kind)
      except Exception:
          raise NotImplementedError
  
      # the constraint matrix
      B = _fitpack._bsplmat(order, xk)
      coefs = func(xk, yk, order, conds, B)
      return xk, coefs, order
function_tokens: def splmake ( xk , yk , order = 3 , kind = 'smoothest' , conds = None ) : yk = np . asanyarray ( yk ) order = int ( order ) if order < 0 : raise ValueError ( "order must not be negative" ) if order == 0 : return xk , yk [ : - 1 ] , order elif order == 1 : return xk , yk , order try : func = eval ( '_find_%s' % kind ) except Exception : raise NotImplementedError # the constraint matrix B = _fitpack . _bsplmat ( order , xk ) coefs = func ( xk , yk , order , conds , B ) return xk , coefs , order