This tool assigns grid cells in the output image the value of the nearest target cell in the input image, measured by the Euclidean distance (i.e. straight-line distance). Thus, euclidean_allocation essentially creates the Voronoi diagram for a set of target cells. Target cells are all non-zero, non-NoData grid cells in the input image. Distances are calculated using the same efficient algorithm (Shih and Wu, 2003) as the euclidean_distance tool.
Shih FY and Wu Y-T (2004), Fast Euclidean distance transformation in two scans using a 3 x 3 neighborhood, Computer Vision and Image Understanding, 93: 195-205.
euclidean_distance, voronoi_diagram, cost_allocation
def euclidean_allocation(self, input: Raster) -> Raster: ...