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1.14.0
Core enumeration types defined and used by ndpolator. More...
Enumerations | |
| enum | ndp_status { NDP_SUCCESS = 0 , NDP_INVALID_TYPE } |
| Return codes for ndpolator functions. More... | |
| enum | ndp_extrapolation_method { NDP_METHOD_NONE = 0 , NDP_METHOD_NEAREST , NDP_METHOD_LINEAR } |
| Determines how ndpolator handles out-of-bounds query points. More... | |
| enum | ndp_search_algorithm { NDP_SEARCH_KDTREE = 0 , NDP_SEARCH_LINEAR } |
| Determines which algorithm to use for nearest neighbor searches. More... | |
| enum | ndp_vertex_flag { NDP_ON_GRID = 0 , NDP_ON_VERTEX , NDP_OUT_OF_BOUNDS } |
| Flags each component of a query point relative to axis boundaries. More... | |
Core enumeration types defined and used by ndpolator.
This section defines the core enumeration types used throughout the ndpolator library.
| enum ndp_status |
Return codes for ndpolator functions.
All ndpolator functions that do not allocate memory should return ndp_status. If no exceptions occurred, NDP_SUCCESS should be returned. Otherwise, a suitable error code enumerated by ndp_status should be returned.
Determines how ndpolator handles out-of-bounds query points.
Controls the behavior when query points fall outside the fully defined hypercube boundaries during interpolation operations.
| enum ndp_search_algorithm |
Determines which algorithm to use for nearest neighbor searches.
The default is to use a k-d tree spatial index, but for small datasets a linear search may be faster. K-d tree has O(log N) complexity while linear search has O(N) complexity.
| enum ndp_vertex_flag |
Flags each component of a query point relative to axis boundaries.
Used to classify whether each component of a query point is within the axis span, coincides with a vertex, or lies outside the bounds. This information is crucial for determining interpolation vs extrapolation.
1.14.0