class_docstr: Bivariate spline s(x,y) of degrees 3 on a sphere, calculated from a
  given set of data points (theta,phi,r).
  
  .. versionadded:: 0.11.0
  
  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
  UnivariateSpline :
      a smooth univariate spline to fit a given set of data points.
  SmoothBivariateSpline :
      a smoothing bivariate spline through the given points
  LSQUnivariateSpline :
      a univariate spline using weighted least-squares fitting
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docstr: Evaluate the spline or its derivatives at given positions.
  
  Parameters
  ----------
  theta, phi : array_like
      Input coordinates.
  
      If `grid` is False, evaluate the spline at points
      ``(theta[i], phi[i]), i=0, ..., len(x)-1``.  Standard
      Numpy broadcasting is obeyed.
  
      If `grid` is True: evaluate spline at the grid points
      defined by the coordinate arrays theta, phi. The arrays
      must be sorted to increasing order.
  dtheta : int, optional
      Order of theta-derivative
  
      .. versionadded:: 0.14.0
  dphi : int
      Order of phi-derivative
  
      .. versionadded:: 0.14.0
  grid : bool
      Whether to evaluate the results on a grid spanned by the
      input arrays, or at points specified by the input arrays.
  
      .. versionadded:: 0.14.0
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code: def __call__(self, theta, phi, dtheta=0, dphi=0, grid=True):
      """
      Evaluate the spline or its derivatives at given positions.
  
      Parameters
      ----------
      theta, phi : array_like
          Input coordinates.
  
          If `grid` is False, evaluate the spline at points
          ``(theta[i], phi[i]), i=0, ..., len(x)-1``.  Standard
          Numpy broadcasting is obeyed.
  
          If `grid` is True: evaluate spline at the grid points
          defined by the coordinate arrays theta, phi. The arrays
          must be sorted to increasing order.
      dtheta : int, optional
          Order of theta-derivative
  
          .. versionadded:: 0.14.0
      dphi : int
          Order of phi-derivative
  
          .. versionadded:: 0.14.0
      grid : bool
          Whether to evaluate the results on a grid spanned by the
          input arrays, or at points specified by the input arrays.
  
          .. versionadded:: 0.14.0
  
      """
      theta = np.asarray(theta)
      phi = np.asarray(phi)
  
      if theta.size > 0 and (theta.min() < 0.0 or theta.max() > np.pi):
          raise ValueError("requested theta out of bounds.")
  
      return _BivariateSplineBase.__call__(
          self, theta, phi, dx=dtheta, dy=dphi, grid=grid
      )
  
imports: import warnings
  from numpy import zeros, concatenate, ravel, diff, array, ones
  import numpy
  from .None import fitpack
  from .None import dfitpack
label_desc: Use image node_id 1 for calling the SphereBivariateSpline obj's underlying member method code with example usage: obj.__call__(theta, phi, dtheta, dphi, grid) and returns: _BivariateSplineBase