Spatial C++ Library
Generic Multi-Dimensional Containers and Spatial Operations
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[detail level 123]
 ▼User Manual
 Installing the LibraryThe installation details are presented in the INSTALL file that is provided in the top directory of the source packages
 Compiling the Unit Tests and the Examples
 ▼Structure of the Library
 Containers
 Iterators and QueriesIterators are used in Spatial to perform all types of query in the container that can return a range of elements
 Functionals
 ▼Concepts
 Link ModeA Link Mode defines the relationship between a node and the links that bear the node
 Trivial ComparisonThis concept defines the model for a functor class used to perform strict comparison between two values of a spatial container, over a single dimension
 Generalized ComparisonGeneralized comparison concept defines the model for a functor used to perform a strict comparison between two values of a spatial container, over the same or a different dimension
 Region PredicateThis concept defines the requirements for a predicate to be used in region queries
 MetricThis concept defines the requirements for a Metric to be used with spatial::neighbor_iterator
 DifferenceThis concept defines the requirements for objects to be used in nearest neighbor queries with the library's built-in metrics such as spatial::euclidian, spatial::quadrance or spatial::manhattan
 ▼Complexity in the Library
 Constant Time ComplexityFunctions with constant time complexity, noted $O(1)\,$, will run and return their output in very similar amounts of time regardless of any other factors, such as number of elements in a container, size of a range evaluated, etc
 Fractional Time ComplexityFunctions with fractional time complexity in dimension $d$ noted $O(n^{1\,-\,1/d})\,$ will run and return their output in an amount of time that depends primarily on the number of dimensions used in the container
 Quasilinear Time ComplexityFunctions with quasilinear time complexity, noted $O(n (\log n)^{1/k})\,$ will return their output in an amount of time mostly proportional to the number of elements being considered, although their running time will still grow faster than pure linear time complexity, however it is still very close to it
 Linear Time ComplexityFunctions with linear time complexity, noted $O(O(n)\,$, will return their output in an amount of time proportional to the number of element in the tree
 Logarithmic Time ComplexityFunctions with logarithmic time complexity, noted $O(\log n)\,$ will run and return their output in an amount of time that depends only on the number of elements in the tree
 ▼Performance of the library
 Insertion PerformanceTo be completed