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<!DOCTYPE html>
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<h2><span class="algo">Pathfinding</span> visualization</h2>
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Algorithm always finds shortest path.
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Algorithm does not guarantee shortest path.
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<div class="col-11">Please select an algorithm first.</div>
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<hr data-content="Explanation" class="hr-text mb-3 mt-4" />
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<div id="astar-expl" hidden>
<b>
A* is a weighted algorithm which always finds the shortest path.
</b>
<br /><br />
A* uses heuristics to find the destination faster. It starts from
a specific starting node of a graph, and aims to find a path to
the given goal node having the smallest cost. A* does this by
maintaining a tree of paths originating at the start node and
extending those paths one edge at a time until it reached the
destination. At each iteration of its main loop, A* needs to
determine which of its paths to extend. It does so based on the
cost of the path and an estimate of the cost required to extend
the path all the way to the goal, selecting the path which
minimizes the sum of the current cost and the estimated remaining
cost.<br />
A* terminates when the path it chooses to extend is a path from
start to goal or if there are no paths eligible to be extended.
<br /><br />
Dijkstra's algorithm can be viewed as a special case of A* without
a heuristics function.
</div>
<div id="bfs-expl" hidden>
<b>
Breadth-first search is an unweighted algorithm which always
finds the shortest path.
</b>
<br /><br />
Breadth-first search starts at the source node, and explores all
of the neighbor nodes at the present depth prior to moving on to
the nodes at the next depth level. It uses the opposite strategy
as depth-first search.
<br /><br />
It works similar to Dijkstra's algorithm, the main difference
being that it only works with unweighted edges thus not taking
weights added by the user into consideration and treating them as
simple nodes.
<br /><br />
An explanation of the algorithm can be found
<a href="bfs.html">here</a>.
</div>
<div id="dfs-expl" hidden>
<b>
Depth-first search is an unweighted algorithm which does not
always find the shortest path.
</b>
<br /><br />
Depth-first search starts at the source node and explores as far
as possible along each branch before backtracking. It is thus not
the best choice for pathfinding, as it's not guaranteed to find a
shortest path and may take a long time to find the destination
vertex.
<br /><br />
An explanation of the algorithm can be found
<a href="dfs.html">here</a>.
</div>
<div id="dijkstra-expl" hidden>
<b>
Dijkstras algorithm is a weighted algorithm which always finds
the shortest path.
</b>
<br /><br />
The original algorithm Dijkstra created finds the shortest path
from a single starting point to a single target. This is the
variant I implemented here. Other variations of Dijkstra's
algorithm find the shortest path from the source node to every
other node in the graph, thus creating a shortest-path-tree.
<br /><br />
The principle behind Dijkstra's algorithm is best explained with
an example.<br /><br />
Suppose you're a pirate captain in the 1670's having a base on one
of the countless islands in an archipelago somewhere in the
carribean. You and your crew hid a treasure on another island far
away from your base. Of course you have a map of the archipelago
with all the ways to get from one island to another and the length
of these routes.<br />
Being a smart pirate you thought of a way to find the shortest
path between your location and the treasure.<br />
You start by marking the distance from your location to every
other island with infinity, because you don't know yet how far
they are from your base. Next you have a look at the islands you
can directly reach from your base and update their respective
distances. You do this by determining the sum of the distance
between an unvisited island and the value of the current island (0
because you're still in your base) and then relabeling the
unvisited island with the sum if it is less than the unvisited
island's current value, drawing an arrow from the current island
to the other one and erasing every other arrow pointing to that
island. After marking the current island as "done", you repeat
that process for the island closest to yours, once again finding
all islands you can reach from that specific island, updating
their values and drawing/erasing arrows. You sit the whole night
updating the map until you finally mark the treasure island as
done. <br />
Now finding the shortest path is done by simply tracing your way
back by following the arrows in reverse.
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<!-- Licensing information: https://bootstrapmade.com/license/ -->
<!-- Purchase the pro version with working PHP/AJAX contact form: https://bootstrapmade.com/day-multipurpose-html-template-for-free/ -->
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</div>
</div>
</footer>
<!-- End Footer -->
<!--<a href="#" class="back-to-top"><i class="icofont-simple-up"></i></a>-->
<div id="preloader"></div>
<!-- Vendor JS Files -->
<script src="assets/vendor/jquery/jquery.min.js"></script>
<script src="assets/vendor/bootstrap/js/bootstrap.bundle.min.js"></script>
<script src="assets/vendor/jquery.easing/jquery.easing.min.js"></script>
<script src="assets/vendor/php-email-form/validate.js"></script>
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<script src="https://cdnjs.cloudflare.com/ajax/libs/bootstrap-slider/11.0.2/bootstrap-slider.min.js"></script>
<script src="https://d3js.org/d3.v5.js"></script>
<script src="assets/js/Pathfinding/astar_pf.js"></script>
<script src="assets/js/Pathfinding/bfs_pf.js"></script>
<script src="assets/js/Pathfinding/dfs_pf.js"></script>
<script src="assets/js/Pathfinding/dijkstra_pf.js"></script>
<script src="assets/js/Maze/recursive_dfs.js"></script>
<script src="assets/js/Maze/growing_tree.js"></script>
<script src="assets/js/Maze/binary_tree_generator.js"></script>
<script src="assets/js/Maze/sidewinder.js"></script>
<!-- Template Main JS File -->
<script src="assets/js/main.js"></script>
<script>
var mouseDown = false;
var algo = 0;
var gridArr = [];
var startPos = { x: 0, y: 0 };
var endPos = { x: 0, y: 0 };
$(document)
.mousedown(function (e) {
mouseDown = true;
})
.mouseup(function (e) {
mouseDown = false;
})
.mouseleave(function (e) {
mouseDown = false;
});
function setAlgo(algorithm) {
switch (algorithm) {
case 1:
$("#dropdownAlgo").text("A*");
$("#startPf").text("Visualize A*");
$(".algo").html("A* algorithm");
document.title = "A* - AlgoVis.io";
$("#algowarning").prop("hidden", true);
$(".alert-success").prop("hidden", false);
$(".alert-warning").prop("hidden", true);
$("#astar-expl").prop("hidden", false);
$("#dfs-expl").prop("hidden", true);
$("#bfs-expl").prop("hidden", true);
$("#dijkstra-expl").prop("hidden", true);
algo = new AStar();
break;
case 2:
$("#dropdownAlgo").text("BFS");
$("#startPf").text("Visualize BFS");
$(".algo").html("Breadth-first search");
document.title = "Breadth-first search - AlgoVis.io";
$("#algowarning").prop("hidden", true);
$(".alert-success").prop("hidden", false);
$(".alert-warning").prop("hidden", true);
$("#dfs-expl").prop("hidden", true);
$("#astar-expl").prop("hidden", true);
$("#dijkstra-expl").prop("hidden", true);
$("#bfs-expl").prop("hidden", false);
algo = new BFS();
break;
case 3:
$("#dropdownAlgo").text("DFS");
$("#startPf").text("Visualize DFS");
$(".algo").html("Depth-first search");
document.title = "Depth-first search - AlgoVis.io";
$("#algowarning").prop("hidden", true);
$(".alert-success").prop("hidden", true);
$(".alert-warning").prop("hidden", false);
algo = new DFS();
$("#astar-expl").prop("hidden", true);
$("#bfs-expl").prop("hidden", true);
$("#dijkstra-expl").prop("hidden", true);
$("#dfs-expl").prop("hidden", false);
break;
case 4:
$("#dropdownAlgo").text("Dijkstra's algorithm");
$("#startPf").text("Visualize Dijkstra's");
$(".algo").html("Dijkstra's algorithm");
document.title = "Dijkstra's algorithm - AlgoVis.io";
$("#algowarning").prop("hidden", true);
$(".alert-success").prop("hidden", false);
$(".alert-warning").prop("hidden", true);
algo = new Dijkstras();
$("#astar-expl").prop("hidden", true);
$("#dfs-expl").prop("hidden", true);
$("#bfs-expl").prop("hidden", true);
$("#dijkstra-expl").prop("hidden", false);
break;
default:
$("#dropdownAlgo").text("A*");
$("#startPf").text("Visualize A*");
$(".algo").html("A* algorithm");
document.title = "A* - AlgoVis.io";
$("#algowarning").prop("hidden", true);
$(".alert-success").prop("hidden", false);
$(".alert-warning").prop("hidden", true);
$("#astar-expl").prop("hidden", false);
$("#dfs-expl").prop("hidden", true);
$("#bfs-expl").prop("hidden", true);
$("#dijkstra-expl").prop("hidden", true);
algo = new AStar();
break;
}
}
function gridData() {
var data = new Array();
var xpos = 1; // starting at (1,1) so the stroke gets rendered
var ypos = 1;
var width = 25;
var height = 25;
var click = 0;
var screenWidth = globalThis.screen.availWidth;
var screenHeight = globalThis.screen.availHeight;
var rows = Math.floor(globalThis.screen.availHeight / height) - 6;
var cols = Math.floor(globalThis.screen.availWidth / width) - 1;
for (var row = 0; row < rows; row++) {
data.push(new Array());
gridArr.push(new Array());
for (var column = 0; column < cols; column++) {
data[row].push({
x: xpos,
y: ypos,
width: width,
height: height,
click: click,
row: row,
col: column,
dist: Infinity,
fScore: Infinity,
predecessor: undefined,
type: "floor",
anim: false,
visited: false,
});
gridArr[row].push(1);
xpos += width;
}
xpos = 1;
ypos += height;
}
return data;
}
function getNearestMultiple(input, x) {
var out = Math.round(input / x);
return out == 0 && input > 0 ? (out + 1) * x : out * x;
}
function clamp(number, min, max) {
return Math.max(min, Math.min(number, max));
}
function dragged(d) {
var x = d3.event.x;
var y = d3.event.y;
var gridX = clamp(
getNearestMultiple(x, 25) + 1,
0,
(gridArr[0].length - 1) * 25
);
var gridY = clamp(
getNearestMultiple(y, 25) + 1,
0,
(gridArr.length - 1) * 25
);
if (d == "start") {
var newX = Math.round((gridX - 1) / 25);
var newY = Math.round((gridY - 1) / 25);
if (
(newX != endPos.x || newY != endPos.y) &&
gridData[newY][newX].type != "wall"
) {
startPos.x = newX;
startPos.y = newY;
d3.select(this).attr("x", gridX).attr("y", gridY);
}
} else {
var newX = Math.round((gridX - 1) / 25);
var newY = Math.round((gridY - 1) / 25);
if (
(newX != startPos.x || newY != startPos.y) &&
gridData[newY][newX].type != "wall"
) {
endPos.x = Math.round((gridX - 1) / 25);
endPos.y = Math.round((gridY - 1) / 25);
d3.select(this).attr("x", gridX).attr("y", gridY);
}
}
}
var gridData = gridData();
var drag = d3
.drag()
.subject(function () {
var t = d3.select(this);
return { x: t.attr("x"), y: t.attr("y") };
})
.on("drag", dragged);
var grid = d3
.select("#grid")
.append("svg")
.attr("width", globalThis.screen.availWidth)
.attr("height", globalThis.screen.availHeight - 6 * 25);
var row = grid
.selectAll(".row")
.data(gridData)
.enter()
.append("g")
.attr("id", function (d, i) {
return "row" + i;
});
var column = row
.selectAll(".square")
.data(function (d) {
return d;
})
.enter()
.append("rect")
.attr("class", "square")
.attr("id", function (d, i) {
return "node-" + d.row + "-" + d.col;
})
.attr("x", function (d) {
return d.x;
})
.attr("y", function (d) {
return d.y;
})
.attr("width", function (d) {
return d.width;
})
.attr("height", function (d) {
return d.height;
})
.attr("fill", "#fff")
.attr("stroke", "#222")
.on("mousedown", async function (d) {
var coords = this.id.replace(/^\D+/g, "").split("-");
var col = coords[1];
var row = coords[0];
mouseDown = true;
if (
(col != startPos.x || row != startPos.y) &&
(col != endPos.x || row != endPos.y)
) {
d.click++;
if (d.click % 2 == 0) {
d3.select(this).transition().duration(400).attr("fill", "#fff");
d.type = "floor";
}
if (d.click % 2 == 1) {
d.anim = true;
d3.select(this)
.attr("x", d.x + 12.5)
.attr("y", d.y + 12.5)
.attr("height", 0)
.attr("width", 0)
.attr("fill", "#171717")
.transition()
.duration(150)
.attr("x", d.x)
.attr("y", d.y)
.attr("height", 25)
.attr("width", 25);
await timeout(155);
d.anim = false;
d.type = "wall";
console.log(gridData);
}
}
})
.on("dblclick", function (d) {
var coords = this.id.replace(/^\D+/g, "").split("-");
var col = coords[1];
var row = coords[0];
if (
(col != startPos.x || row != startPos.y) &&
(col != endPos.x || row != endPos.y)
) {
d.click = 1;
d3.select(this).transition().duration(400).attr("fill", "#B0B0B0");
d.type = "weight";
}
})
.on("mouseenter", async function (d) {
var coords = this.id.replace(/^\D+/g, "").split("-");
var col = coords[1];
var row = coords[0];
if (
(col != startPos.x || row != startPos.y) &&
(col != endPos.x || row != endPos.y)
) {
if (mouseDown && !d.anim) {
d.click++;
if (d.click % 2 == 0) {
d3.select(this).transition().duration(400).attr("fill", "#fff");
d.type = "floor";
}
if (d.click % 2 == 1) {
d.anim = true;
await colorBlock("#" + this.id, "#171717", 150, "fill");
setTimeout(() => {
d.anim = false;
}, 300);
d.type = "wall";
}
}
}
});
var start = grid
.selectAll(".start")
.data(["start"])
.enter()
.append("image")
.attr("xlink:href", "assets/img/start.svg")
.attr("id", "start")
.attr("x", function () {
var col = Math.round(Math.random() * (gridArr[0].length - 1));
startPos.x = col;
return 25 * col;
})
.attr("y", function () {
var row = Math.round(Math.random() * (gridArr.length - 1));
startPos.y = row;
console.log("startPos: " + startPos.x + ", " + startPos.y);
return 25 * row;
})
.attr("width", 25)
.attr("height", 25)
.call(drag);
var end = grid
.selectAll(".start")
.data(["end"])
.enter()
.append("image")
.attr("id", "end")
.attr("xlink:href", "assets/img/end.svg")
.attr("x", function () {
var col = Math.round(Math.random() * (gridArr[0].length - 1));
endPos.x = col;
return 25 * col;
})
.attr("y", function () {
var row = Math.round(Math.random() * (gridArr.length - 1));
endPos.y = row;
console.log("endPos: " + endPos.x + ", " + endPos.y);
return 25 * row;
})
.attr("width", 25)
.attr("height", 25)
.call(drag);
async function timeout(delay) {
await new Promise((resolve) =>
setTimeout(() => {
resolve();
}, delay)
);
}
async function colorBlock(block, color, delayDraw, delay, mode) {
return new Promise((resolve) => {
if (mode == "fill") {
var coords = block.replace(/^\D+/g, "").split("-");
var col = coords[1];
var row = coords[0];
d3.select(block)
.attr("x", gridData[row][col].x + 12.5)
.attr("y", gridData[row][col].y + 12.5)
.attr("height", 0)
.attr("width", 0)
.attr("fill", color)
.transition()
.duration(delayDraw)
.attr("x", gridData[row][col].x)
.attr("y", gridData[row][col].y)
.attr("height", 25)
.attr("width", 25);
} else {
d3.select(block)
.transition()
.duration(delayDraw)
.attr("fill", color);
}
setTimeout(() => {
resolve();
}, delay);
}, delay);
}
async function runAlgo() {
if (algo != 0) {
$("#algowarning").prop("hidden", true);
$("#startPf").prop("disabled", true);
$("#dropdownAlgo").prop("disabled", true);
$("#dropdownGen").prop("disabled", true);
$("#btnClear").prop("disabled", true);
await algo.run(gridData, startPos, endPos);
$("#startPf").prop("disabled", false);
$("#dropdownAlgo").prop("disabled", false);
$("#dropdownGen").prop("disabled", false);
$("#btnClear").prop("disabled", false);
} else {
$("#algowarning").prop("hidden", false);
}
}
function clearGrid() {
d3.selectAll(".square").transition().duration(500).attr("fill", "#fff");
for (let y = 0; y < gridData.length; y++) {
for (let x = 0; x < gridData[0].length; x++) {
gridData[y][x].type = "floor";
}
}
}
async function generateMaze(type) {
var mazeGen;
var cell = undefined;
switch (type) {
case "recDFS":
mazeGen = new RecursiveDFS();
cell = {
x: Math.round(Math.random() * gridData[0].length),
y: Math.round(Math.random() * gridData.length),
};
break;
case "growing":
mazeGen = new GrowingTree();
cell = {
x: Math.round(Math.random() * (gridData[0].length - 2)) + 1,
y: Math.round(Math.random() * (gridData.length - 2)) + 1,
};
let colEven = gridData[0].length % 2 == 0;
let rowEven = gridData.length % 2 == 0;
if (colEven) {
cell.x = cell.x % 2 == 0 ? cell.x : cell.x + 1;
} else {