parameters: (self, n=1)
return_statement: return UnivariateSpline._from_tck(tck, self.ext)
docstring: Construct a new spline representing the derivative of this spline.
  
          Parameters
          ----------
          n : int, optional
              Order of derivative to evaluate. Default: 1
  
          Returns
          -------
          spline : UnivariateSpline
              Spline of order k2=k-n representing the derivative of this
              spline.
  
          See Also
          --------
          splder, antiderivative
  
          Notes
          -----
  
          .. versionadded:: 0.13.0
  
          Examples
          --------
          This can be used for finding maxima of a curve:
  
          >>> from scipy.interpolate import UnivariateSpline
          >>> x = np.linspace(0, 10, 70)
          >>> y = np.sin(x)
          >>> spl = UnivariateSpline(x, y, k=4, s=0)
  
          Now, differentiate the spline and find the zeros of the
          derivative. (NB: `sproot` only works for order 3 splines, so we
          fit an order 4 spline):
  
          >>> spl.derivative().roots() / np.pi
          array([ 0.50000001,  1.5       ,  2.49999998])
  
          This agrees well with roots :math:`\\pi/2 + n\\pi` of
          :math:`\\cos(x) = \\sin'(x)`.
docstring_summary: Construct a new spline representing the derivative of this spline.
docstring_tokens: Construct a new spline representing the derivative of this spline .
function: def derivative(self, n=1):
          """
          Construct a new spline representing the derivative of this spline.
  
          Parameters
          ----------
          n : int, optional
              Order of derivative to evaluate. Default: 1
  
          Returns
          -------
          spline : UnivariateSpline
              Spline of order k2=k-n representing the derivative of this
              spline.
  
          See Also
          --------
          splder, antiderivative
  
          Notes
          -----
  
          .. versionadded:: 0.13.0
  
          Examples
          --------
          This can be used for finding maxima of a curve:
  
          >>> from scipy.interpolate import UnivariateSpline
          >>> x = np.linspace(0, 10, 70)
          >>> y = np.sin(x)
          >>> spl = UnivariateSpline(x, y, k=4, s=0)
  
          Now, differentiate the spline and find the zeros of the
          derivative. (NB: `sproot` only works for order 3 splines, so we
          fit an order 4 spline):
  
          >>> spl.derivative().roots() / np.pi
          array([ 0.50000001,  1.5       ,  2.49999998])
  
          This agrees well with roots :math:`\\pi/2 + n\\pi` of
          :math:`\\cos(x) = \\sin'(x)`.
  
          """
          tck = fitpack.splder(self._eval_args, n)
          return UnivariateSpline._from_tck(tck, self.ext)
function_tokens: def derivative ( self , n = 1 ) : tck = fitpack . splder ( self . _eval_args , n ) return UnivariateSpline . _from_tck ( tck , self . ext )