svelte-gallery
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Intelligent masonry style photo gallery that maintains image aspect ratios in perfect rows.
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JavaScript
/******************************************************************************
* Created 2008-08-19.
*
* Dijkstra path-finding functions. Adapted from the Dijkstar Python project.
*
* Copyright (C) 2008
* Wyatt Baldwin <self@wyattbaldwin.com>
* All rights reserved
*
* Licensed under the MIT license.
*
* http://www.opensource.org/licenses/mit-license.php
*
* 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.
*****************************************************************************/
export const dijkstra = {
single_source_shortest_paths: function (graph, s, d) {
// Predecessor map for each node that has been encountered.
// node ID => predecessor node ID
var predecessors = {};
// Costs of shortest paths from s to all nodes encountered.
// node ID => cost
var costs = {};
costs[s] = 0;
// Costs of shortest paths from s to all nodes encountered; differs from
// `costs` in that it provides easy access to the node that currently has
// the known shortest path from s.
// XXX: Do we actually need both `costs` and `open`?
var open = new BinaryHeap(function (x) {
return x.cost;
});
open.push({ value: s, cost: 0 });
var closest,
u,
cost_of_s_to_u,
adjacent_nodes,
cost_of_e,
cost_of_s_to_u_plus_cost_of_e,
cost_of_s_to_v,
first_visit;
while (open.size()) {
// In the nodes remaining in graph that have a known cost from s,
// find the node, u, that currently has the shortest path from s.
closest = open.pop();
u = closest.value;
cost_of_s_to_u = closest.cost;
// Get nodes adjacent to u...
adjacent_nodes = graph(u) || {};
// ...and explore the edges that connect u to those nodes, updating
// the cost of the shortest paths to any or all of those nodes as
// necessary. v is the node across the current edge from u.
for (var v in adjacent_nodes) {
// Get the cost of the edge running from u to v.
cost_of_e = adjacent_nodes[v];
// Cost of s to u plus the cost of u to v across e--this is *a*
// cost from s to v that may or may not be less than the current
// known cost to v.
cost_of_s_to_u_plus_cost_of_e = cost_of_s_to_u + cost_of_e;
// If we haven't visited v yet OR if the current known cost from s to
// v is greater than the new cost we just found (cost of s to u plus
// cost of u to v across e), update v's cost in the cost list and
// update v's predecessor in the predecessor list (it's now u).
cost_of_s_to_v = costs[v];
first_visit = typeof costs[v] === 'undefined';
if (first_visit || cost_of_s_to_v > cost_of_s_to_u_plus_cost_of_e) {
costs[v] = cost_of_s_to_u_plus_cost_of_e;
open.push({ value: v, cost: cost_of_s_to_u_plus_cost_of_e });
predecessors[v] = u;
}
}
}
if (typeof costs[d] === 'undefined') {
var msg = ['Could not find a path from ', s, ' to ', d, '.'].join('');
throw new Error(msg);
}
return predecessors;
},
extract_shortest_path_from_predecessor_list: function (predecessors, d) {
var nodes = [];
var u = d;
var predecessor;
while (u) {
nodes.push(u);
predecessor = predecessors[u];
u = predecessors[u];
}
nodes.reverse();
return nodes;
},
find_path: function (graph, s, d) {
var predecessors = dijkstra.single_source_shortest_paths(graph, s, d);
return dijkstra.extract_shortest_path_from_predecessor_list(
predecessors,
d
);
}
// test: function() {
// // A B C
// // D E F
// // G H I
// graph = function (key) {
// switch (key) {
// case 'a': return {b: 10, d: 1};
// case 'b': return {a: 1, c: 1, e: 1};
// case 'c': return {b: 1, f: 1};
// case 'd': return {a: 1, e: 1, g: 1};
// case 'e': return {b: 1, d: 1, f: 1, h: 1};
// case 'f': return {c: 1, e: 1, i: 1};
// case 'g': return {d: 1, h: 1};
// case 'h': return {e: 1, g: 1, i: 1};
// case 'i': return {f: 1, h: 1};
// }
// };
// var path = dijkstra.find_path(graph, 'a', 'i');
// if (path.join() !== ['a', 'd', 'e', 'f', 'i'].join()) {
// throw new Error('Path finding error!');
// }
// }
};
function BinaryHeap(scoreFunction) {
this.content = [];
this.scoreFunction = scoreFunction;
}
BinaryHeap.prototype = {
push: function (element) {
// Add the new element to the end of the array.
this.content.push(element);
// Allow it to bubble up.
this.bubbleUp(this.content.length - 1);
},
pop: function () {
// Store the first element so we can return it later.
var result = this.content[0];
// Get the element at the end of the array.
var end = this.content.pop();
// If there are any elements left, put the end element at the
// start, and let it sink down.
if (this.content.length > 0) {
this.content[0] = end;
this.sinkDown(0);
}
return result;
},
remove: function (node) {
var len = this.content.length;
// To remove a value, we must search through the array to find
// it.
for (var i = 0; i < len; i++) {
if (this.content[i] === node) {
// When it is found, the process seen in 'pop' is repeated
// to fill up the hole.
var end = this.content.pop();
if (i !== len - 1) {
this.content[i] = end;
if (this.scoreFunction(end) < this.scoreFunction(node))
this.bubbleUp(i);
else this.sinkDown(i);
}
return;
}
}
throw new Error('Node not found.');
},
size: function () {
return this.content.length;
},
bubbleUp: function (n) {
// Fetch the element that has to be moved.
var element = this.content[n];
// When at 0, an element can not go up any further.
while (n > 0) {
// Compute the parent element's index, and fetch it.
var parentN = Math.floor((n + 1) / 2) - 1,
parent = this.content[parentN];
// Swap the elements if the parent is greater.
if (this.scoreFunction(element) < this.scoreFunction(parent)) {
this.content[parentN] = element;
this.content[n] = parent;
// Update 'n' to continue at the new position.
n = parentN;
}
// Found a parent that is less, no need to move it further.
else {
break;
}
}
},
sinkDown: function (n) {
// Look up the target element and its score.
var length = this.content.length,
element = this.content[n],
elemScore = this.scoreFunction(element);
while (true) {
// Compute the indices of the child elements.
var child2N = (n + 1) * 2,
child1N = child2N - 1;
// This is used to store the new position of the element,
// if any.
var swap = null;
// If the first child exists (is inside the array)...
if (child1N < length) {
// Look it up and compute its score.
var child1 = this.content[child1N],
child1Score = this.scoreFunction(child1);
// If the score is less than our element's, we need to swap.
if (child1Score < elemScore) swap = child1N;
}
// Do the same checks for the other child.
if (child2N < length) {
var child2 = this.content[child2N],
child2Score = this.scoreFunction(child2);
if (child2Score < (swap === null ? elemScore : child1Score))
swap = child2N;
}
// If the element needs to be moved, swap it, and continue.
if (swap != null) {
this.content[n] = this.content[swap];
this.content[swap] = element;
n = swap;
}
// Otherwise, we are done.
else {
break;
}
}
}
};