pathfinding3d.core.heuristic module

pathfinding3d.core.heuristic.null(dx, dy, dz)

Special heuristic for Dijkstra return 0, so node.h will always be calculated as 0, distance cost (node.f) is calculated only from start to current point (node.g)

Parameters:

• dx (Union[int, float]) – x distance

• dy (Union[int, float]) – y distance

• dz (Union[int, float]) – z distance

Returns:

0.0

Return type:

float

pathfinding3d.core.heuristic.manhattan(dx, dy, dz)

Manhattan heuristics

Parameters:

• dx (Union[int, float]) – x distance

• dy (Union[int, float]) – y distance

• dz (Union[int, float]) – z distance

Returns:

manhattan distance

Return type:

float

pathfinding3d.core.heuristic.euclidean(dx, dy, dz)

Euclidean distance heuristics

Parameters:

• dx (Union[int, float]) – x distance

• dy (Union[int, float]) – y distance

• dz (Union[int, float]) – z distance

Returns:

euclidean distance

Return type:

float

pathfinding3d.core.heuristic.chebyshev(dx, dy, dz)

Chebyshev distance.

Parameters:

• dx (Union[int, float]) – x distance

• dy (Union[int, float]) – y distance

• dz (Union[int, float]) – z distance

Returns:

chebyshev distance

Return type:

float

pathfinding3d.core.heuristic.octile(dx, dy, dz)

Octile distance.

Parameters:

• dx (Union[int, float]) – x distance

• dy (Union[int, float]) – y distance

• dz (Union[int, float]) – z distance

Returns:

octile distance

Return type:

float