Package: pathfinding3d
Pathfinding3DPathfinding algorithms in 3D for python3 born from the fork ofpython-pathfindingby@brean.Pathfinding3D is a comprehensive library designed for 3D pathfinding applications.Currently there are 7 path-finders bundled in this library, namely:A*: Versatile and most widely used algorithm.Dijkstra: A* without heuristic.Best-FirstBi-directional A*: Efficient for large graphs with a known goal.Breadth First Search (BFS)Iterative Deeping A* (IDA*): Memory efficient algorithm for large graphs.Minimum Spanning Tree (MSP)Theta*: Almost A* with path smoothing.Dijkstra, A* and Bi-directional A* take the weight of the fields on the map into account.
Theta* is a variant of A* but with any angle of movement allowed.InstallationRequirementspython >= 3.8numpyTo install Pathfinding3D, use pip:pipinstallpathfinding3dFor more details, seepathfinding3d on pypiUsage examplesFor a quick start, here's a basic example:importnumpyasnpfrompathfinding3d.core.diagonal_movementimportDiagonalMovementfrompathfinding3d.core.gridimportGridfrompathfinding3d.finder.a_starimportAStarFinder# Create a 3D numpy array with 0s as obstacles and 1s as walkable pathsmatrix=np.ones((10,10,10),dtype=np.int8)# mark the center of the grid as an obstaclematrix[5,5,5]=0# Create a grid object from the numpy arraygrid=Grid(matrix=matrix)# Mark the start and end pointsstart=grid.node(0,0,0)end=grid.node(9,9,9)# Create an instance of the A* finder with diagonal movement allowedfinder=AStarFinder(diagonal_movement=DiagonalMovement.always)path,runs=finder.find_path(start,end,grid)# Path will be a list with all the waypoints as nodes# Convert it to a list of coordinate tuplespath=[p.identifierforpinpath]print("operations:",runs,"path length:",len(path))print("path:",path)For usage examples with detailed descriptions take a look at theexamplesfolder or at thedocumentation.Visualization of the pathYou can visualize the grid along with the path by calling thevisualizemethod of theGridclass. This method can take path as an optional argument and generate a plotly figure. You can install pathfinding3d with theplotlyto use this feature with the following command:pipinstallpathfinding3d[vis]The path produced in the previous example can be visualized by adding the following code to the end of the example:grid.visualize(path=path,# optionally visualize the pathstart=start,end=end,visualize_weight=True,# weights above 1 (default) will be visualizedsave_html=True,# save visualization to html filesave_to="path_visualization.html",# specify the path to save the html filealways_show=True,# always show the visualization in the browser)This will generate a visualization of the grid and the path and save it to the filepath_visualization.htmland also open it in your default browser.Rerun the AlgorithmWhen rerunning the algorithm, remember to clean the grid first usingGrid.cleanup. This will reset the grid to its original state.grid.cleanup()Please note that this operation can be time-consuming but is usally faster than creating a new grid object.Implementation detailsAll pathfinding algorithms in this library inherit from theFinderclass. This class provides common functionality that can be overridden by specific pathfinding algorithm implementations.General Process:You callfind_pathon one of your finder implementations.init_findinstantiates theopen_listand resets all values and counters. Theopen_listis a priority queue that keeps track of nodes to be explored.The main loop starts on theopen_listwhich contains all nodes to be processed next (e.g. all current neighbors that are walkable). You need to implementcheck_neighborsin your finder implementation to fill this list.For example in A* implementation (AStarFinder),check_neighborspops the node with the minimum 'f' value from the open list and marks it as closed. It then either returns the path (if the end node is reached) or continues processing neighbors.If the end node is not reached,check_neighborscallsfind_neighborsto get all adjacent walkable nodes. For most algorithms, this callsgrid.neighbors.If none of the neighbors are walkable, the algorithm terminates. Otherwise,check_neighborscallsprocess_nodeon each neighbor. It calculates the costffor each neighbor node. This involves computingg(the cost from the start node to the current node) andh(the estimated cost from the current node to the end node, calculated byapply_heuristic).Finallyprocess_nodeupdates the open list sofind_pathwith new or updated nodes. This allowsfind_pathto continue the process with the next node in the subsequent iteration.The following diagram illustrates the process:graph TD;
      style find_path stroke:#333,stroke-width:2px
      style init_find stroke:#333,stroke-width:2px
      style while_open_list_not_empty stroke:#333,stroke-width:2px
      style check_neighbors stroke:#333,stroke-width:2px
      style pop_node stroke:#333,stroke-width:2px
      style find_neighbors stroke:#333,stroke-width:2px
      style process_node stroke:#333,stroke-width:2px
      style return_empty_list stroke:#333,stroke-width:2px
      style return_path stroke:#333,stroke-width:2px

      find_path["find_path"] --> init_find["init_find\n(re)set global values\nand open list"];
      init_find --> while_open_list_not_empty["while open_list not empty"];
      while_open_list_not_empty --> check_neighbors["check_neighbors\n(for node with min 'f' value)"];
      check_neighbors --> pop_node["pop_node\n(node with min 'f' value)"];
      pop_node --> find_neighbors["find_neighbors\n(get neighbors)"];
      find_neighbors --> process_node["process_node\n(calculate new cost)"];
      process_node --> while_open_list_not_empty;
      while_open_list_not_empty -- "open list empty" --> return_empty_list["return empty list"];
      while_open_list_not_empty -- "path found" --> return_path["return path"];TestingRun the tests locally using pytest. For detailed instructions, see thetestfolder:pytesttestContributingWe welcome contributions of all sizes and levels! For bug reports and feature requests, please use theissue trackerto submit bug reports and feature requests. Please Follow the guidelines inCONTRIBUTING.mdfor submitting merge requests.LicensePathfinding3D is distributed under theMIT license.Authors / ContributersFind a list of contributorshere.