| x
	  (PLFLT *, input)	    The input x array.
	  y
	  (PLFLT *, input)	    The input y array.
	  z
	  (PLFLT *, input)	    The input z array. Each triple
            x[i], y[i],
            z[i] represents one data sample coordinates.
	  npts
	  (PLINT, input)	    The number of data samples in the x,
            y and z arrays.
	  xg
	  (PLFLT *, input)	    The input array that specifies the grid spacing in the x
	    direction. Usually xg has
            nptsx equaly spaced values from the mininum
            to the maximum values of the x input array.
	  nptsx
	  (PLINT, input)	    The number of points in the xg array.
	  yg
	  (PLFLT *, input)	    The input array that specifies the grid spacing in the y
	    direction. Similar to the xg parameter.
	  nptsy
	  (PLINT, input)	    The number of points in the yg array.
	  sg
	  (PLFLT **, output)	    The output array, where data lies in the regular grid
	    specified by xg and yg.
            the zg array must exists or be allocated by
            the user prior to the calling, and must have dimension
            zg[nptsx][xptsy].
          type
	  (PLINT, input)	    The type of gridding algorithm to use, which can be:
                           GRID_CSA: Bivariate Cubic Spline
                approximation
                              GRID_DTLI: Delaunay Triangulation Linear
                Interpolation
                              GRID_NNI: Natural Neighbors Interpolation
                              GRID_NNIDW: Nearest Neighbors Inverse
                Distance Weighted
                              GRID_NNLI: Nearest Neighbors Linear
                Interpolation
                              GRID_NNAIDW:  Nearest Neighbors Around
                Inverse Distance Weighted
              
             For details on the algorithm read the source file
            plgridd.c.
          data
	  (PLFLT, input)	    Some gridding algorithms require extra data, which can be
	    specified through this argument. Currently, for algoritm:
                           GRID_NNIDW, data
                specifies the number of neighbors to use, the lower the
                value, the noisier (more local) the approximation is.
                              GRID_NNLI, data
                specifies what a thin triangle is, in the range
                [1. .. 2.]. High values enable the usage of very thin
                triangles for interpolation, possibly resulting in error in
                the approximation.
                              GRID_NNI, only weights greater than
                data will be accepted. If 0, all weigths
                will be accepted.
              
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