The fitted function, or fitted surface, methods fit an algebraic surface to the known data and then pick the interpolated values from the fitted surface. The weighted average methods calculate interpolated values as weighted averages of known values.

Among the weighted average methods, the simplest are known as the inverse distance weighted average methods. Dsgrid uses one of these methods.

The capability exists in Dsgrid
to vary the power of the distances used to compute the weights.
For powers of the distances greater than one, the interpolated
surface is flat at the input data; the size of the flat spot increases
with increasing values of the power.
If the power of the distances is one, then
the weights are computed simply as linear inverse distances and the
areas around input data are cone shaped. If the power is less than
one, then the areas around input data form a cusp at the data points.
Example 2 illustrates the effects
of modifying the exponent of the
distances used in computing the weights. For full details on
interpolation methods, consult
Dave Watson's
book *Contouring*.

- Functionally equivalent Fortran and C interfaces are provided in both single and double precision versions.
- Interfaces exist for two-dimensional interpolation as well as 3D.
- Interfaces exist for interpolation at individual points.
- The capability exists to specify that only input data points within a specified distance from an interpolated point be considered in the calculation of weights. In the default case, all input data are used in the calculation of the weights.
- The package has a shadowing option which, when in effect, reduces the effect that a cluster of points might have in skewing interpolated values. This shadowing feature is based on original work of Bob Lackman. Example 4 illustrates the shadowing feature.