parameters: (self, nu)
return_statement: return p
docstring: Construct a new piecewise polynomial representing the derivative.
  
          Parameters
          ----------
          nu : ndim-tuple of int
              Order of derivatives to evaluate for each dimension.
              If negative, the antiderivative is returned.
  
          Returns
          -------
          pp : NdPPoly
              Piecewise polynomial of orders (k[0] - nu[0], ..., k[n] - nu[n])
              representing the derivative of this polynomial.
  
          Notes
          -----
          Derivatives are evaluated piecewise for each polynomial
          segment, even if the polynomial is not differentiable at the
          breakpoints. The polynomial intervals in each dimension are
          considered half-open, ``[a, b)``, except for the last interval
          which is closed ``[a, b]``.
docstring_summary: Construct a new piecewise polynomial representing the derivative.
docstring_tokens: Construct a new piecewise polynomial representing the derivative .
function: def derivative(self, nu):
          """
          Construct a new piecewise polynomial representing the derivative.
  
          Parameters
          ----------
          nu : ndim-tuple of int
              Order of derivatives to evaluate for each dimension.
              If negative, the antiderivative is returned.
  
          Returns
          -------
          pp : NdPPoly
              Piecewise polynomial of orders (k[0] - nu[0], ..., k[n] - nu[n])
              representing the derivative of this polynomial.
  
          Notes
          -----
          Derivatives are evaluated piecewise for each polynomial
          segment, even if the polynomial is not differentiable at the
          breakpoints. The polynomial intervals in each dimension are
          considered half-open, ``[a, b)``, except for the last interval
          which is closed ``[a, b]``.
  
          """
          p = self.construct_fast(self.c.copy(), self.x, self.extrapolate)
  
          for axis, n in enumerate(nu):
              p._derivative_inplace(n, axis)
  
          p._ensure_c_contiguous()
          return p
function_tokens: def derivative ( self , nu ) : p = self . construct_fast ( self . c . copy ( ) , self . x , self . extrapolate ) for axis , n in enumerate ( nu ) : p . _derivative_inplace ( n , axis ) p . _ensure_c_contiguous ( ) return p