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-- ======================================================================
-- Copyright (c) 2012 RapidFire Studio Limited
-- All Rights Reserved.
-- http://www.rapidfirestudio.com
-- Permission is hereby granted, free of charge, to any person obtaining
-- a copy of this software and associated documentation files (the
-- "Software"), to deal in the Software without restriction, including
-- without limitation the rights to use, copy, modify, merge, publish,
-- distribute, sublicense, and/or sell copies of the Software, and to
-- permit persons to whom the Software is furnished to do so, subject to
-- the following conditions:
-- The above copyright notice and this permission notice shall be
-- included in all copies or substantial portions of the Software.
-- THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
-- EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
-- MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
-- IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-- CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
-- TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
-- SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
-- ======================================================================
-- Modifications & updates for ggj20, Alexander Pickering
print("requireing graph...")
mod = ...
----------------------------------------------------------------
-- local variables
----------------------------------------------------------------
local INF = 1/0
local cachedPaths = nil
----------------------------------------------------------------
-- local functions
----------------------------------------------------------------
function dist ( x1, y1, x2, y2 )
return math.sqrt ( ((x2 - x1)^ 2 ) + ((y2 - y1) ^ 2 ) )
end
function dist_between ( nodeA, nodeB )
return dist ( nodeA.x, nodeA.y, nodeB.x, nodeB.y )
end
function heuristic_cost_estimate ( nodeA, nodeB )
return dist ( nodeA.x, nodeA.y, nodeB.x, nodeB.y )
end
function is_valid_node ( node, neighbor )
return true
end
function lowest_f_score ( set, f_score )
local lowest, bestNode = INF, nil
for _, node in ipairs ( set ) do
local score = f_score [ node ]
if score < lowest then
lowest, bestNode = score, node
end
end
return bestNode
end
function neighbor_nodes ( theNode, nodes )
local neighbors = {}
for _, node in ipairs ( nodes ) do
if theNode ~= node and is_valid_node ( theNode, node ) then
table.insert ( neighbors, node )
end
end
return neighbors
end
function not_in ( set, theNode )
for _, node in ipairs ( set ) do
if node == theNode then return false end
end
return true
end
function remove_node ( set, theNode )
for i, node in ipairs ( set ) do
if node == theNode then
set [ i ] = set [ #set ]
set [ #set ] = nil
break
end
end
end
function unwind_path ( flat_path, map, current_node )
if map [ current_node ] then
table.insert ( flat_path, 1, map [ current_node ] )
return unwind_path ( flat_path, map, map [ current_node ] )
else
return flat_path
end
end
------------------------------------------------------------------
---- pathfinding functions
------------------------------------------------------------------
function a_star ( start, goal, nodes, valid_node_func )
local closedset = {}
local openset = { start }
local came_from = {}
if valid_node_func then is_valid_node = valid_node_func end
local g_score, f_score = {}, {}
g_score [ start ] = 0
f_score [ start ] = g_score [ start ] + heuristic_cost_estimate ( start, goal )
while #openset > 0 do
local current = lowest_f_score ( openset, f_score )
if current == goal then
local path = unwind_path ( {}, came_from, goal )
table.insert ( path, goal )
return path
end
remove_node ( openset, current )
table.insert ( closedset, current )
local neighbors = neighbor_nodes ( current, nodes )
for _, neighbor in ipairs ( neighbors ) do
if not_in ( closedset, neighbor ) then
local tentative_g_score = g_score [ current ] + dist_between ( current, neighbor )
if not_in ( openset, neighbor ) or tentative_g_score < g_score [ neighbor ] then
came_from [ neighbor ] = current
g_score [ neighbor ] = tentative_g_score
f_score [ neighbor ] = g_score [ neighbor ] + heuristic_cost_estimate ( neighbor, goal )
if not_in ( openset, neighbor ) then
table.insert ( openset, neighbor )
end
end
end
end
end
return nil -- no valid path
end
----------------------------------------------------------------
-- exposed functions
----------------------------------------------------------------
function clear_cached_paths ()
cachedPaths = nil
end
function distance ( x1, y1, x2, y2 )
return dist ( x1, y1, x2, y2 )
end
function mod.path ( start, goal, nodes, ignore_cache, valid_node_func )
if not cachedPaths then cachedPaths = {} end
if not cachedPaths [ start ] then
cachedPaths [ start ] = {}
elseif cachedPaths [ start ] [ goal ] and not ignore_cache then
return cachedPaths [ start ] [ goal ]
end
local resPath = a_star ( start, goal, nodes, valid_node_func )
if not cachedPaths [ start ] [ goal ] and not ignore_cache then
cachedPaths [ start ] [ goal ] = resPath
end
return resPath
end
return mod
|
