| Enumerant | Definition | Value |
|---|
| SE_INTERPTYP_BICUBIC_SPLINE |
Bicubic spline interpolation uses sixteen known data points
to estimate the unknown value of c at a given a, b
by fitting a bicubic surface to the sixteen closest data points,
then evaluating for c.
|
1 |
| SE_INTERPTYP_DIAGONALIZATION |
Diagonalization; one common use is for grids representing
terrain elevation data.
|
2 |
| SE_INTERPTYP_DISALLOWED |
Interpolation is disallowed by the data provider.
|
3 |
| SE_INTERPTYP_KRIGING |
Kriging is an interpolation method that predicts unknown
values from data observed at known locations. This method
uses variograms to express the spatial variation, and it
minimizes the error of predicted values which are estimated
by spatial distribution of the predicted values. Kriging
interpolation estimates the unknown value using a weighted
linear combination of the available sample. For more
information, refer to [OLIVER].
|
4 |
| SE_INTERPTYP_LAGRANGIAN |
Lagrangian interpolation uses a specified number of existing
points to fit a polynomial of degree one less than the number
of points. For more information, see [BEYER].
|
5 |
| SE_INTERPTYP_LINEAR |
Linear interpolation (the most common default).
|
6 |
| SE_INTERPTYP_METADATA_SPECIFIED |
See the metadata for the <Axis> instance's <Data Table> aggregate
to determine the data provider's preferred interpolation method.
|
7 |
| SE_INTERPTYP_NEAREST_NEIGHBOUR |
Nearest neighbour.
|
8 |
| SE_INTERPTYP_NOT_SUPPLIED |
No preferred interpolation method was supplied.
|
9 |
| SE_INTERPTYP_OAML_DBDB_SPLINE_FIT |
This enumerant represents a spline-fitting technique, specifically
that used to support derived from data from the U. S. Navy's
Oceanographic and Atmospheric Library (OAML). More specifically,
it is used to support DBDB OAML tables.
One common use is within OAML-derived <Data Table> instances
representing bathymetry.
|
10 |
| SE_INTERPTYP_QUADRATIC |
Quadratic interpolation uses three known data points to
estimate the unknown value of y at a given x by fitting
a parabolic arc (quadratic equation) to the three data
points and then evaluating for y.
|
11 |