@np.deprecate(message='spleval is deprecated in scipy 0.19.0, use BSpline instead.')
def spleval(xck, xnew, deriv=0):
 (xj, cvals, k) = xck
 oldshape = np.shape(xnew)
 xx = np.ravel(xnew)
 sh = cvals.shape[1:]
 res = np.empty((xx.shape + sh), dtype=cvals.dtype)
 for index in np.ndindex(*sh):
  sl = ((slice(None),) + index)
  if issubclass(cvals.dtype.type, np.complexfloating):
   res[sl].real = _fitpack._bspleval(xx, xj, cvals.real[sl], k, deriv)
   res[sl].imag = _fitpack._bspleval(xx, xj, cvals.imag[sl], k, deriv)
  else:
   res[sl] = _fitpack._bspleval(xx, xj, cvals[sl], k, deriv)
 res.shape = (oldshape + sh)
 return res

@ np . deprecate ( message = 'spleval is deprecated in scipy 0.19.0, use BSpline instead.' ) def spleval ( xck , xnew , deriv = 0 ) : ( xj , cvals , k ) = xck oldshape = np . shape ( xnew ) xx = np . ravel ( xnew ) sh = cvals . shape [ 1 : ] res = np . empty ( ( xx . shape + sh ) , dtype = cvals . dtype ) for index in np . ndindex ( * sh ) : sl = ( ( slice ( None ) , ) + index ) if issubclass ( cvals . dtype . type , np . complexfloating ) : res [ sl ] . real = _fitpack . _bspleval ( xx , xj , cvals . real [ sl ] , k , deriv ) res [ sl ] . imag = _fitpack . _bspleval ( xx , xj , cvals . imag [ sl ] , k , deriv ) else : res [ sl ] = _fitpack . _bspleval ( xx , xj , cvals [ sl ] , k , deriv ) res . shape = ( oldshape + sh ) return res
evaluate a fixed spline represented by the given tuple at the new x-values the xj values are the interior knot points .