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  This function estimates the partial derivative of a
  multi-dimensional function, sampled on a regular grid


  data: An n-dimensional datacube, representing a function evenly
        sampled on a grid.
  dimension: The dimension (1-n_dimension(data)) over which to
            calculate the partial derivative (df / d_dim). Defaults
            to 1.

Keyword Parameters

  order: 1-3, indicating how to approximate the derivative. All
        methods implicitly use lagrange interpolation to express
        each data point as a point on a polynomial, and then
        differentiate that polynomial. Order=1,2,3 correspond to a
        (3,5,7) point interpolation scheme. Defaults to 1.


  A grid the same size as data, giving the partial derivative along
  dimension at each data point

Modification History

  August 2010: Written by Chris Beaumont

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