DistanceGrid

DistanceGrid is a data structure used in computational geometry and spatial analysis. It represents a discrete approximation of space where each cell or point within the grid has an associated value representing its distance to a specific object or set of objects. This distance can be Euclidean, Manhattan, or another defined metric.

The primary purpose of a DistanceGrid is to efficiently query the distance from any point in the grid to the nearest feature. This is achieved by pre-calculating these distances during the grid's construction. Creating a DistanceGrid typically involves a process where the distance is initialized to infinity for most cells and zero for cells occupied by the source object(s). Then, algorithms like breadth-first search or Dijkstra's algorithm are employed to propagate these distance values outwards to all other cells.

Applications of DistanceGrids are diverse. They are commonly used in pathfinding algorithms, where the grid can guide agents towards a target by always moving towards cells with smaller distances. In image processing, DistanceGrids can be used for operations like morphological transformations, skeletonization, and shape analysis. They also find use in simulations, for example, to model diffusion processes or to determine proximity effects. The resolution of the grid is a critical factor, as it influences both the accuracy of the distance calculations and the memory and computational resources required.