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* Fixes Pathfinder module AGAIN, General JPS Tweak (#84348) ## About The Pull Request 1. Fixes the modsuit pathfinder module's pathfinding for the second time. This time AI idling broke it, we just make it not idle. 2. Changes the heuristic used by JPS nodes from Chebyshev distance to Euclidean distance. I have no real logical explanation, it just appeared to produce a more optimal path. CC @ LemonInTheDark 3. Renames `get_dist_euclidian()` to `get_dist_euclidean()`. Red line: Euclidean dist JPS path (roughly) Green line: Chebyshev dist JPS path (roughly)  ## Changelog 🆑 fix: MODsuit pathfinder module works. Again. code: AI pathfinding should produce slightly better paths. /🆑 * Fixes Pathfinder module AGAIN, General JPS Tweak * Update goldeneye.dm --------- Co-authored-by: Kapu1178 <75460809+Kapu1178@users.noreply.github.com> Co-authored-by: SpaceLoveSs13 <68121607+SpaceLoveSs13@users.noreply.github.com>
306 lines
13 KiB
Plaintext
306 lines
13 KiB
Plaintext
/**
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* This file contains the stuff you need for using JPS (Jump Point Search) pathing, an alternative to A* that skips
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* over large numbers of uninteresting tiles resulting in much quicker pathfinding solutions. Mind that diagonals
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* cost the same as cardinal moves currently, so paths may look a bit strange, but should still be optimal.
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*/
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/// A helper macro for JPS, for telling when a node has forced neighbors that need expanding
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/// Only usable in the context of the jps datum because of the datum vars it relies on
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#define STEP_NOT_HERE_BUT_THERE(cur_turf, dirA, dirB) ((!CAN_STEP(cur_turf, get_step(cur_turf, dirA), simulated_only, pass_info, avoid) && CAN_STEP(cur_turf, get_step(cur_turf, dirB), simulated_only, pass_info, avoid)))
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/// The JPS Node datum represents a turf that we find interesting enough to add to the open list and possibly search for new tiles from
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/datum/jps_node
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/// The turf associated with this node
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var/turf/tile
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/// The node we just came from
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var/datum/jps_node/previous_node
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/// The A* node weight (f_value = number_of_tiles + heuristic)
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var/f_value
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/// The A* node heuristic (a rough estimate of how far we are from the goal)
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var/heuristic
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/// How many steps it's taken to get here from the start (currently pulling double duty as steps taken & cost to get here, since all moves incl diagonals cost 1 rn)
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var/number_tiles
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/// How many steps it took to get here from the last node
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var/jumps
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/// Nodes store the endgoal so they can process their heuristic without a reference to the pathfind datum
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var/turf/node_goal
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/datum/jps_node/New(turf/our_tile, datum/jps_node/incoming_previous_node, jumps_taken, turf/incoming_goal)
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tile = our_tile
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jumps = jumps_taken
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if(incoming_goal) // if we have the goal argument, this must be the first/starting node
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node_goal = incoming_goal
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else if(incoming_previous_node) // if we have the parent, this is from a direct lateral/diagonal scan, we can fill it all out now
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previous_node = incoming_previous_node
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number_tiles = previous_node.number_tiles + jumps
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node_goal = previous_node.node_goal
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heuristic = get_dist_euclidean(tile, node_goal)
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f_value = number_tiles + heuristic
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// otherwise, no parent node means this is from a subscan lateral scan, so we just need the tile for now until we call [datum/jps/proc/update_parent] on it
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/datum/jps_node/Destroy(force)
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previous_node = null
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return ..()
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/datum/jps_node/proc/update_parent(datum/jps_node/new_parent)
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previous_node = new_parent
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node_goal = previous_node.node_goal
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jumps = get_dist(tile, previous_node.tile)
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number_tiles = previous_node.number_tiles + jumps
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heuristic = get_dist_euclidean(tile, node_goal)
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f_value = number_tiles + heuristic
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/proc/HeapPathWeightCompare(datum/jps_node/a, datum/jps_node/b)
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return b.f_value - a.f_value
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/datum/pathfind/jps
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/// The movable we are pathing
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var/atom/movable/caller
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/// The turf we're trying to path to (note that this won't track a moving target)
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var/turf/end
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/// The open list/stack we pop nodes out from (TODO: make this a normal list and macro-ize the heap operations to reduce proc overhead)
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var/datum/heap/open
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/// The list we compile at the end if successful to pass back
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var/list/path
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///An assoc list that serves as the closed list. Key is the turf, points to true if we've seen it before
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var/list/found_turfs
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/// How far away we have to get to the end target before we can call it quits
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var/mintargetdist = 0
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/// If we should delete the first step in the path or not. Used often because it is just the starting tile
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var/skip_first = FALSE
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///Defines how we handle diagonal moves. See __DEFINES/path.dm
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var/diagonal_handling = DIAGONAL_REMOVE_CLUNKY
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/datum/pathfind/jps/proc/setup(atom/movable/caller, list/access, max_distance, simulated_only, avoid, list/datum/callback/on_finish, atom/goal, mintargetdist, skip_first, diagonal_handling)
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src.caller = caller
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src.pass_info = new(caller, access)
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src.max_distance = max_distance
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src.simulated_only = simulated_only
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src.avoid = avoid
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src.on_finish = on_finish
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src.mintargetdist = mintargetdist
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src.skip_first = skip_first
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src.diagonal_handling = diagonal_handling
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end = get_turf(goal)
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open = new /datum/heap(/proc/HeapPathWeightCompare)
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found_turfs = list()
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/datum/pathfind/jps/Destroy(force)
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. = ..()
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caller = null
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end = null
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open = null
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/datum/pathfind/jps/start()
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start = start || get_turf(caller)
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. = ..()
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if(!.)
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return .
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if(!get_turf(end))
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stack_trace("Invalid JPS destination")
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return FALSE
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if(start.z != end.z || start == end ) //no pathfinding between z levels
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return FALSE
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if(max_distance && (max_distance < get_dist(start, end))) //if start turf is farther than max_distance from end turf, no need to do anything
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return FALSE
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var/datum/jps_node/current_processed_node = new (start, -1, 0, end)
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open.insert(current_processed_node)
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found_turfs[start] = TRUE // i'm sure this is fine
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return TRUE
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/datum/pathfind/jps/search_step()
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. = ..()
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if(!.)
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return .
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if(QDELETED(caller))
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return FALSE
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while(!open.is_empty() && !path)
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var/datum/jps_node/current_processed_node = open.pop() //get the lower f_value turf in the open list
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if(max_distance && (current_processed_node.number_tiles > max_distance))//if too many steps, don't process that path
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continue
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var/turf/current_turf = current_processed_node.tile
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for(var/scan_direction in list(EAST, WEST, NORTH, SOUTH))
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lateral_scan_spec(current_turf, scan_direction, current_processed_node)
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for(var/scan_direction in list(NORTHEAST, SOUTHEAST, NORTHWEST, SOUTHWEST))
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diag_scan_spec(current_turf, scan_direction, current_processed_node)
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// Stable, we'll just be back later
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if(TICK_CHECK)
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return TRUE
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return TRUE
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/datum/pathfind/jps/finished()
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//we're done! turn our reversed path (end to start) into a path (start to end)
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found_turfs = null
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QDEL_NULL(open)
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var/list/path = src.path || list()
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path = reverseList(path)
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switch(diagonal_handling)
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if(DIAGONAL_REMOVE_CLUNKY)
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path = remove_clunky_diagonals(path, pass_info, simulated_only, avoid)
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if(DIAGONAL_REMOVE_ALL)
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path = remove_diagonals(path, pass_info, simulated_only, avoid)
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if(skip_first && length(path) > 0)
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path.Cut(1,2)
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hand_back(path)
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return ..()
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/// Called when we've hit the goal with the node that represents the last tile, then sets the path var to that path so it can be returned by [datum/pathfind/proc/search]
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/datum/pathfind/jps/proc/unwind_path(datum/jps_node/unwind_node)
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path = new()
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var/turf/iter_turf = unwind_node.tile
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path.Add(iter_turf)
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while(unwind_node.previous_node)
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var/dir_goal = get_dir(iter_turf, unwind_node.previous_node.tile)
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for(var/i in 1 to unwind_node.jumps)
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iter_turf = get_step(iter_turf,dir_goal)
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path.Add(iter_turf)
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unwind_node = unwind_node.previous_node
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/**
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* For performing lateral scans from a given starting turf.
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*
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* These scans are called from both the main search loop, as well as subscans for diagonal scans, and they treat finding interesting turfs slightly differently.
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* If we're doing a normal lateral scan, we already have a parent node supplied, so we just create the new node and immediately insert it into the heap, ezpz.
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* If we're part of a subscan, we still need for the diagonal scan to generate a parent node, so we return a node datum with just the turf and let the diag scan
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* proc handle transferring the values and inserting them into the heap.
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*
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* Arguments:
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* * original_turf: What turf did we start this scan at?
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* * heading: What direction are we going in? Obviously, should be cardinal
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* * parent_node: Only given for normal lateral scans, if we don't have one, we're a diagonal subscan.
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*/
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/datum/pathfind/jps/proc/lateral_scan_spec(turf/original_turf, heading, datum/jps_node/parent_node)
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var/steps_taken = 0
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var/turf/current_turf = original_turf
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var/turf/lag_turf = original_turf
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var/datum/can_pass_info/pass_info = src.pass_info
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while(TRUE)
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if(path)
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return
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lag_turf = current_turf
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current_turf = get_step(current_turf, heading)
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steps_taken++
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if(!CAN_STEP(lag_turf, current_turf, simulated_only, pass_info, avoid))
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return
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if(current_turf == end || (mintargetdist && (get_dist(current_turf, end) <= mintargetdist)))
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var/datum/jps_node/final_node = new(current_turf, parent_node, steps_taken)
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found_turfs[current_turf] = TRUE
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if(parent_node) // if this is a direct lateral scan we can wrap up, if it's a subscan from a diag, we need to let the diag make their node first, then finish
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unwind_path(final_node)
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return final_node
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else if(found_turfs[current_turf]) // already visited, essentially in the closed list
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return
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else
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found_turfs[current_turf] = TRUE
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if(parent_node && parent_node.number_tiles + steps_taken > max_distance)
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return
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var/interesting = FALSE // have we found a forced neighbor that would make us add this turf to the open list?
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switch(heading)
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if(NORTH)
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if(STEP_NOT_HERE_BUT_THERE(current_turf, WEST, NORTHWEST) || STEP_NOT_HERE_BUT_THERE(current_turf, EAST, NORTHEAST))
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interesting = TRUE
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if(SOUTH)
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if(STEP_NOT_HERE_BUT_THERE(current_turf, WEST, SOUTHWEST) || STEP_NOT_HERE_BUT_THERE(current_turf, EAST, SOUTHEAST))
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interesting = TRUE
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if(EAST)
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if(STEP_NOT_HERE_BUT_THERE(current_turf, NORTH, NORTHEAST) || STEP_NOT_HERE_BUT_THERE(current_turf, SOUTH, SOUTHEAST))
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interesting = TRUE
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if(WEST)
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if(STEP_NOT_HERE_BUT_THERE(current_turf, NORTH, NORTHWEST) || STEP_NOT_HERE_BUT_THERE(current_turf, SOUTH, SOUTHWEST))
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interesting = TRUE
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if(interesting)
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var/datum/jps_node/newnode = new(current_turf, parent_node, steps_taken)
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if(parent_node) // if we're a diagonal subscan, we'll handle adding ourselves to the heap in the diag
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open.insert(newnode)
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return newnode
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/**
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* For performing diagonal scans from a given starting turf.
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*
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* Unlike lateral scans, these only are called from the main search loop, so we don't need to worry about returning anything,
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* though we do need to handle the return values of our lateral subscans of course.
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*
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* Arguments:
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* * original_turf: What turf did we start this scan at?
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* * heading: What direction are we going in? Obviously, should be diagonal
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* * parent_node: We should always have a parent node for diagonals
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*/
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/datum/pathfind/jps/proc/diag_scan_spec(turf/original_turf, heading, datum/jps_node/parent_node)
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var/steps_taken = 0
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var/turf/current_turf = original_turf
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var/turf/lag_turf = original_turf
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var/datum/can_pass_info/pass_info = src.pass_info
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while(TRUE)
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if(path)
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return
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lag_turf = current_turf
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current_turf = get_step(current_turf, heading)
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steps_taken++
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if(!CAN_STEP(lag_turf, current_turf, simulated_only, pass_info, avoid))
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return
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if(current_turf == end || (mintargetdist && (get_dist(current_turf, end) <= mintargetdist)))
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var/datum/jps_node/final_node = new(current_turf, parent_node, steps_taken)
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found_turfs[current_turf] = TRUE
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unwind_path(final_node)
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return
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else if(found_turfs[current_turf]) // already visited, essentially in the closed list
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return
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else
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found_turfs[current_turf] = TRUE
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if(parent_node.number_tiles + steps_taken > max_distance)
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return
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var/interesting = FALSE // have we found a forced neighbor that would make us add this turf to the open list?
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var/datum/jps_node/possible_child_node // otherwise, did one of our lateral subscans turn up something?
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switch(heading)
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if(NORTHWEST)
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if(STEP_NOT_HERE_BUT_THERE(current_turf, EAST, NORTHEAST) || STEP_NOT_HERE_BUT_THERE(current_turf, SOUTH, SOUTHWEST))
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interesting = TRUE
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else
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possible_child_node = (lateral_scan_spec(current_turf, WEST) || lateral_scan_spec(current_turf, NORTH))
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if(NORTHEAST)
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if(STEP_NOT_HERE_BUT_THERE(current_turf, WEST, NORTHWEST) || STEP_NOT_HERE_BUT_THERE(current_turf, SOUTH, SOUTHEAST))
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interesting = TRUE
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else
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possible_child_node = (lateral_scan_spec(current_turf, EAST) || lateral_scan_spec(current_turf, NORTH))
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if(SOUTHWEST)
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if(STEP_NOT_HERE_BUT_THERE(current_turf, EAST, SOUTHEAST) || STEP_NOT_HERE_BUT_THERE(current_turf, NORTH, NORTHWEST))
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interesting = TRUE
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else
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possible_child_node = (lateral_scan_spec(current_turf, SOUTH) || lateral_scan_spec(current_turf, WEST))
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if(SOUTHEAST)
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if(STEP_NOT_HERE_BUT_THERE(current_turf, WEST, SOUTHWEST) || STEP_NOT_HERE_BUT_THERE(current_turf, NORTH, NORTHEAST))
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interesting = TRUE
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else
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possible_child_node = (lateral_scan_spec(current_turf, SOUTH) || lateral_scan_spec(current_turf, EAST))
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if(interesting || possible_child_node)
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var/datum/jps_node/newnode = new(current_turf, parent_node, steps_taken)
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open.insert(newnode)
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if(possible_child_node)
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possible_child_node.update_parent(newnode)
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open.insert(possible_child_node)
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if(possible_child_node.tile == end || (mintargetdist && (get_dist(possible_child_node.tile, end) <= mintargetdist)))
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unwind_path(possible_child_node)
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return
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