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# scipy.interpolate.LSQSphereBivariateSpline.__call__

`LSQSphereBivariateSpline.``__call__`(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 New in version 0.14.0. dphi : int Order of phi-derivative New in version 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. New in version 0.14.0.