class_docstr: Base class for Bivariate spline s(x,y) interpolation on the rectangle
  [xb,xe] x [yb, ye] calculated from a given set of data points
  (x,y,z).
  
  See Also
  --------
  bisplrep :
      a function to find a bivariate B-spline representation of a surface
  bisplev :
      a function to evaluate a bivariate B-spline and its derivatives
  BivariateSpline :
      a base class for bivariate splines.
  SphereBivariateSpline :
      a bivariate spline on a spherical grid
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docstr: Construct a new spline representing a partial derivative of this
  spline.
  
  Parameters
  ----------
  dx, dy : int
      Orders of the derivative in x and y respectively. They must be
      non-negative integers and less than the respective degree of the
      original spline (self) in that direction (``kx``, ``ky``).
  
  Returns
  -------
  spline :
      A new spline of degrees (``kx - dx``, ``ky - dy``) representing the
      derivative of this spline.
  
  Notes
  -----
  
  .. versionadded:: 1.9.0
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code: def partial_derivative(self, dx, dy):
      """Construct a new spline representing a partial derivative of this
      spline.
  
      Parameters
      ----------
      dx, dy : int
          Orders of the derivative in x and y respectively. They must be
          non-negative integers and less than the respective degree of the
          original spline (self) in that direction (``kx``, ``ky``).
  
      Returns
      -------
      spline :
          A new spline of degrees (``kx - dx``, ``ky - dy``) representing the
          derivative of this spline.
  
      Notes
      -----
  
      .. versionadded:: 1.9.0
  
      """
      if dx == 0 and dy == 0:
          return self
      else:
          kx, ky = self.degrees
          if not (dx >= 0 and dy >= 0):
              raise ValueError(
                  "order of derivative must be positive or" " zero"
              )
          if not (dx < kx and dy < ky):
              raise ValueError(
                  "order of derivative must be less than"
                  " degree of spline"
              )
          tx, ty, c = self.tck[:3]
          newc, ier = dfitpack.pardtc(tx, ty, c, kx, ky, dx, dy)
          if ier != 0:
              # This should not happen under normal conditions.
              raise ValueError(
                  "Unexpected error code returned by"
                  " pardtc: %d" % ier
              )
          nx = len(tx)
          ny = len(ty)
          newtx = tx[dx : nx - dx]
          newty = ty[dy : ny - dy]
          newkx, newky = kx - dx, ky - dy
          newclen = (nx - dx - kx - 1) * (ny - dy - ky - 1)
          return _DerivedBivariateSpline._from_tck(
              (newtx, newty, newc[:newclen], newkx, newky)
          )
  
imports: import warnings
  from numpy import zeros, concatenate, ravel, diff, array, ones
  import numpy
  from .None import _fitpack_impl
  from .None import dfitpack
label_desc: Use image node_id 6 for calling the _BivariateSplineBase obj's underlying member method code with example usage: obj.partial_derivative(dx, dy) and returns: self, _DerivedBivariateSpline