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RefineTable of content
This refinement offers a highly customizable implementation of Prim’s algorithm to find the minimum spanning tree of individual clusters.
By design, the output is guaranteed to be sanitized (e.g, each cluster will retains its existing connectivity properties).
It relies on user-defined
🝰 Heuristics in order to build the tree, providing very high level of control.
Available Heuristics Modules
🝰 Heuristic Attribute
Attribute-driven heuristics
The Attribute heuristics uses custom point or edge value as raw score.
🝰 Feedback
Favor uncharted points & edges.
The Feedback heuristic add/remove score value to points & edges that are “in use” by other previously computed paths.
🝰 Inertia
Favor active direction preservation.
The Inertia heuristic uses the ongoing traversal data to try and maintain a consistent direction, as if the algorithm had “inertia”.
🝰 Steepness
Favor flat trajectories.
The Steepness heuristic uses the edge angle against an up vector to compute a dot product that is used to determine whether the edge should be considered flat or not.
🝰 Azimuth
Favor edges directed toward the goal.
The Azimuth heuristic attempt to force the path to always aim toward the goal.
🝰 Least Nodes
Favor traversing the least amount of nodes.
The Least Nodes heuristic favor node count traversal over anything else.