@np.deprecate(message='splmake is deprecated in scipy 0.19.0, use make_interp_spline instead.')
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:
  raise NotImplementedError
 B = _fitpack._bsplmat(order, xk)
 coefs = func(xk, yk, order, conds, B)
 return (xk, coefs, order)

@ np . deprecate ( message = 'splmake is deprecated in scipy 0.19.0, use make_interp_spline instead.' ) 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 : raise NotImplementedError B = _fitpack . _bsplmat ( order , xk ) coefs = func ( xk , yk , order , conds , B ) return ( xk , coefs , order )
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 .