function swarmPathfind(grid, start, end, allowDiag, hFn) {
const h = hFn || HEURISTICS.manhattan;
const weight = 2.5;
const rows = grid.length;
const cols = grid[0].length;
const gScore = Matrix(rows, cols, Infinity);
const visited = new Set();
const prev = new Map();
const heap = PriorityQueue("f");
gScore[start[0]][start[1]] = 0;
priorityQueuePush(heap, {
f: weight * h(start[0], start[1], end[0], end[1]),
g: 0,
row: start[0],
col: start[1]
});
while (priorityQueueSize(heap)) {
const __pattern1 = priorityQueuePop(heap);
const cr = __pattern1.row;
const cc = __pattern1.col;
const cg = __pattern1.g;
const currentKey = key(cr, cc);
if (visited.has(currentKey)) continue;
visited.add(currentKey);
visitNode(cr, cc);
if (cr === end[0] && cc === end[1]) {
reconstructPath(prev, start, end);
return;
}
for (const [nr, nc] of getNeighbors(grid, cr, cc, allowDiag)) {
const neighborKey = key(nr, nc);
if (visited.has(neighborKey)) continue;
const ng = cg + stepCost(grid, cr, cc, nr, nc);
if (ng < gScore[nr][nc]) {
gScore[nr][nc] = ng;
prev.set(neighborKey, [cr, cc]);
priorityQueuePush(heap, {
f: ng + weight * h(nr, nc, end[0], end[1]),
g: ng,
row: nr,
col: nc
});
pushFrontier(nr, nc);
}
}
}
reportNoPath();
} def swarmPathfind(grid, start, end, allowDiag, hFn):
h = (hFn or HEURISTICS.manhattan)
weight = 2.5
rows = grid.length
cols = grid[0].length
gScore = Matrix(rows, cols, Infinity)
visited = Set()
prev = Map()
heap = PriorityQueue("f")
gScore[start[0]][start[1]] = 0
priorityQueuePush(heap, {f: (weight * h(start[0], start[1], end[0], end[1])), g: 0, row: start[0], col: start[1]})
while priorityQueueSize(heap):
__pattern1 = priorityQueuePop(heap)
cr = __pattern1.row
cc = __pattern1.col
cg = __pattern1.g
currentKey = key(cr, cc)
if visited.has(currentKey):
continue
visited.add(currentKey)
visitNode(cr, cc)
if ((cr == end[0]) and (cc == end[1])):
reconstructPath(prev, start, end)
return
for nr, nc in getNeighbors(grid, cr, cc, allowDiag):
neighborKey = key(nr, nc)
if visited.has(neighborKey):
continue
ng = (cg + stepCost(grid, cr, cc, nr, nc))
if (ng < gScore[nr][nc]):
gScore[nr][nc] = ng
prev.set(neighborKey, [cr, cc])
priorityQueuePush(heap, {f: (ng + (weight * h(nr, nc, end[0], end[1]))), g: ng, row: nr, col: nc})
pushFrontier(nr, nc)
reportNoPath() #include <vector>
#include <algorithm>
void swarmPathfind(int grid, int start, int end, int allowDiag, int hFn) {
auto h = (hFn || HEURISTICS.manhattan);
auto weight = 2.5;
auto rows = grid.length;
auto cols = grid[0].length;
auto gScore = Matrix(rows, cols, Infinity);
auto visited = Set();
auto prev = Map();
auto heap = PriorityQueue("f");
gScore[start[0]][start[1]] = 0;
priorityQueuePush(heap, {f: (weight * h(start[0], start[1], end[0], end[1])), g: 0, row: start[0], col: start[1]});
while(priorityQueueSize(heap)) {
auto __pattern1 = priorityQueuePop(heap);
auto cr = __pattern1.row;
auto cc = __pattern1.col;
auto cg = __pattern1.g;
auto currentKey = key(cr, cc);
if(visited.has(currentKey)) {
continue;
}
visited.add(currentKey);
visitNode(cr, cc);
if(((cr == end[0]) && (cc == end[1]))) {
reconstructPath(prev, start, end);
return;
}
for(auto& [nr, nc] : getNeighbors(grid, cr, cc, allowDiag)) {
auto neighborKey = key(nr, nc);
if(visited.has(neighborKey)) {
continue;
}
auto ng = (cg + stepCost(grid, cr, cc, nr, nc));
if((ng < gScore[nr][nc])) {
gScore[nr][nc] = ng;
prev.set(neighborKey, [cr, cc]);
priorityQueuePush(heap, {f: (ng + (weight * h(nr, nc, end[0], end[1]))), g: ng, row: nr, col: nc});
pushFrontier(nr, nc);
}
}
}
reportNoPath();
} public void swarmPathfind(int grid, int start, int end, int allowDiag, int hFn) {
var h = (hFn || HEURISTICS.manhattan);
var weight = 2.5;
var rows = grid.length;
var cols = grid[0].length;
var gScore = Matrix(rows, cols, Infinity);
var visited = Set();
var prev = Map();
var heap = PriorityQueue("f");
gScore[start[0]][start[1]] = 0;
priorityQueuePush(heap, {f: (weight * h(start[0], start[1], end[0], end[1])), g: 0, row: start[0], col: start[1]});
while(priorityQueueSize(heap)) {
var __pattern1 = priorityQueuePop(heap);
var cr = __pattern1.row;
var cc = __pattern1.col;
var cg = __pattern1.g;
var currentKey = key(cr, cc);
if(visited.has(currentKey)) {
continue;
}
visited.add(currentKey);
visitNode(cr, cc);
if(((cr == end[0]) && (cc == end[1]))) {
reconstructPath(prev, start, end);
return;
}
foreach(var (nr, nc) in getNeighbors(grid, cr, cc, allowDiag)) {
var neighborKey = key(nr, nc);
if(visited.has(neighborKey)) {
continue;
}
var ng = (cg + stepCost(grid, cr, cc, nr, nc));
if((ng < gScore[nr][nc])) {
gScore[nr][nc] = ng;
prev.set(neighborKey, [cr, cc]);
priorityQueuePush(heap, {f: (ng + (weight * h(nr, nc, end[0], end[1]))), g: ng, row: nr, col: nc});
pushFrontier(nr, nc);
}
}
}
reportNoPath();
} #include <stdio.h>
void swarmPathfind(int grid, int start, int end, int allowDiag, int hFn) {
var h = (hFn || HEURISTICS.manhattan);
var weight = 2.5;
var rows = grid.length;
var cols = grid[0].length;
var gScore = Matrix(rows, cols, Infinity);
var visited = Set();
var prev = Map();
var heap = PriorityQueue("f");
gScore[start[0]][start[1]] = 0;
priorityQueuePush(heap, {f: (weight * h(start[0], start[1], end[0], end[1])), g: 0, row: start[0], col: start[1]});
while(priorityQueueSize(heap)) {
var __pattern1 = priorityQueuePop(heap);
var cr = __pattern1.row;
var cc = __pattern1.col;
var cg = __pattern1.g;
var currentKey = key(cr, cc);
if(visited.has(currentKey)) {
continue;
}
visited.add(currentKey);
visitNode(cr, cc);
if(((cr == end[0]) && (cc == end[1]))) {
reconstructPath(prev, start, end);
return;
}
for(int _fod_i = 0; _fod_i < getNeighbors(grid, cr, cc, allowDiag)_len; _fod_i++) {
int nr = getNeighbors(grid, cr, cc, allowDiag)[_fod_i][0];
int nc = getNeighbors(grid, cr, cc, allowDiag)[_fod_i][1];
var neighborKey = key(nr, nc);
if(visited.has(neighborKey)) {
continue;
}
var ng = (cg + stepCost(grid, cr, cc, nr, nc));
if((ng < gScore[nr][nc])) {
gScore[nr][nc] = ng;
prev.set(neighborKey, [cr, cc]);
priorityQueuePush(heap, {f: (ng + (weight * h(nr, nc, end[0], end[1]))), g: ng, row: nr, col: nc});
pushFrontier(nr, nc);
}
}
}
reportNoPath();
}