Add topological sorting.

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Oleksii Trekhleb 2018-05-08 19:27:42 +03:00
parent fc53c7de5d
commit e73dc2dfd7
7 changed files with 225 additions and 1 deletions

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@ -71,7 +71,7 @@
* [Detect Cycle](https://github.com/trekhleb/javascript-algorithms/tree/master/src/algorithms/graph/detect-cycle) - for both directed and undirected graphs (DFS and Disjoint Set based versions)
* [Prims Algorithm](https://github.com/trekhleb/javascript-algorithms/tree/master/src/algorithms/graph/prim) - finding Minimum Spanning Tree (MST) for weighted undirected graph
* [Kruskals Algorithm](https://github.com/trekhleb/javascript-algorithms/tree/master/src/algorithms/graph/kruskal) - finding Minimum Spanning Tree (MST) for weighted undirected graph
* Topological Sorting
* [Topological Sorting](https://github.com/trekhleb/javascript-algorithms/tree/master/src/algorithms/graph/topological-sorting) - DFS method
* Eulerian path, Eulerian circuit
* Strongly Connected Component algorithm
* Shortest Path Faster Algorithm (SPFA)

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# Topological Sorting
In the field of computer science, a topological sort or
topological ordering of a directed graph is a linear ordering
of its vertices such that for every directed edge `uv` from
vertex `u` to vertex `v`, `u` comes before `v` in the ordering.
For instance, the vertices of the graph may represent tasks to
be performed, and the edges may represent constraints that one
task must be performed before another; in this application, a
topological ordering is just a valid sequence for the tasks.
A topological ordering is possible if and only if the graph has
no directed cycles, that is, if it is a [directed acyclic graph](https://en.wikipedia.org/wiki/Directed_acyclic_graph)
(DAG). Any DAG has at least one topological ordering, and algorithms are
known for constructing a topological ordering of any DAG in linear time.
![Directed Acyclic Graph](https://upload.wikimedia.org/wikipedia/commons/c/c6/Topological_Ordering.svg)
A topological ordering of a directed acyclic graph: every edge goes from
earlier in the ordering (upper left) to later in the ordering (lower right).
A directed graph is acyclic if and only if it has a topological ordering.
## Example
![Topologic Sorting](https://upload.wikimedia.org/wikipedia/commons/0/03/Directed_acyclic_graph_2.svg)
The graph shown above has many valid topological sorts, including:
- `5, 7, 3, 11, 8, 2, 9, 10` (visual left-to-right, top-to-bottom)
- `3, 5, 7, 8, 11, 2, 9, 10` (smallest-numbered available vertex first)
- `5, 7, 3, 8, 11, 10, 9, 2` (fewest edges first)
- `7, 5, 11, 3, 10, 8, 9, 2` (largest-numbered available vertex first)
- `5, 7, 11, 2, 3, 8, 9, 10` (attempting top-to-bottom, left-to-right)
- `3, 7, 8, 5, 11, 10, 2, 9` (arbitrary)
## Application
The canonical application of topological sorting is in
**scheduling a sequence of jobs** or tasks based on their dependencies. The jobs
are represented by vertices, and there is an edge from `x` to `y` if
job `x` must be completed before job `y` can be started (for
example, when washing clothes, the washing machine must finish
before we put the clothes in the dryer). Then, a topological sort
gives an order in which to perform the jobs.
Other application is **dependency resolution**. Each vertex is a package
and each edge is a dependency of package `a` on package 'b'. Then topological
sorting will provide a sequence of installing dependencies in a way that every
next dependency has its dependent packages to be installed in prior.
## References
- [Wikipedia](https://en.wikipedia.org/wiki/Topological_sorting)
- [Topological Sorting on YouTube by Tushar Roy](https://www.youtube.com/watch?v=ddTC4Zovtbc)

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import GraphVertex from '../../../../data-structures/graph/GraphVertex';
import GraphEdge from '../../../../data-structures/graph/GraphEdge';
import Graph from '../../../../data-structures/graph/Graph';
import topologicalSort from '../topologicalSort';
describe('topologicalSort', () => {
it('should do topological sorting on graph', () => {
const vertexA = new GraphVertex('A');
const vertexB = new GraphVertex('B');
const vertexC = new GraphVertex('C');
const vertexD = new GraphVertex('D');
const vertexE = new GraphVertex('E');
const vertexF = new GraphVertex('F');
const vertexG = new GraphVertex('G');
const vertexH = new GraphVertex('H');
const edgeAC = new GraphEdge(vertexA, vertexC);
const edgeBC = new GraphEdge(vertexB, vertexC);
const edgeBD = new GraphEdge(vertexB, vertexD);
const edgeCE = new GraphEdge(vertexC, vertexE);
const edgeDF = new GraphEdge(vertexD, vertexF);
const edgeEF = new GraphEdge(vertexE, vertexF);
const edgeEH = new GraphEdge(vertexE, vertexH);
const edgeFG = new GraphEdge(vertexF, vertexG);
const graph = new Graph(true);
graph
.addEdge(edgeAC)
.addEdge(edgeBC)
.addEdge(edgeBD)
.addEdge(edgeCE)
.addEdge(edgeDF)
.addEdge(edgeEF)
.addEdge(edgeEH)
.addEdge(edgeFG);
const sortedVertices = topologicalSort(graph);
expect(sortedVertices).toBeDefined();
expect(sortedVertices.length).toBe(graph.getAllVertices().length);
expect(sortedVertices).toEqual([
vertexB,
vertexD,
vertexA,
vertexC,
vertexE,
vertexH,
vertexF,
vertexG,
]);
});
});

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import Stack from '../../../data-structures/stack/Stack';
import depthFirstSearch from '../depth-first-search/depthFirstSearch';
/**
* @param {Graph} graph
*/
export default function topologicalSort(graph) {
// Create a set of all vertices we want to visit.
const unvisitedSet = {};
graph.getAllVertices().forEach((vertex) => {
unvisitedSet[vertex.getKey()] = vertex;
});
// Create a set for all vertices that we've already visited.
const visitedSet = {};
// Create a stack of already ordered vertices.
const sortedStack = new Stack();
const dfsCallbacks = {
enterVertex: ({ currentVertex }) => {
// Add vertex to visited set in case if all its children has been explored.
visitedSet[currentVertex.getKey()] = currentVertex;
// Remove this vertex from unvisited set.
delete unvisitedSet[currentVertex.getKey()];
},
leaveVertex: ({ currentVertex }) => {
// If the vertex has been totally explored then we may push it to stack.
sortedStack.push(currentVertex);
},
allowTraversal: ({ nextVertex }) => {
return !visitedSet[nextVertex.getKey()];
},
};
// Let's go and do DFS for all unvisited nodes.
while (Object.keys(unvisitedSet).length) {
const currentVertexKey = Object.keys(unvisitedSet)[0];
const currentVertex = unvisitedSet[currentVertexKey];
// Do DFS for current node.
depthFirstSearch(graph, currentVertex, dfsCallbacks);
}
return sortedStack.toArray();
}

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@ -9,6 +9,10 @@ export default class LinkedList {
this.tail = null;
}
/**
* @param {*} value
* @return {LinkedList}
*/
prepend(value) {
// Make new node to be a head.
this.head = new LinkedListNode(value, this.head);
@ -16,6 +20,10 @@ export default class LinkedList {
return this;
}
/**
* @param {*} value
* @return {LinkedList}
*/
append(value) {
const newNode = new LinkedListNode(value);
@ -34,6 +42,10 @@ export default class LinkedList {
return this;
}
/**
* @param {*} value
* @return {LinkedListNode}
*/
delete(value) {
if (!this.head) {
return null;
@ -67,6 +79,12 @@ export default class LinkedList {
return deletedNode;
}
/**
* @param {Object} findParams
* @param {*} findParams.value
* @param {function} [findParams.callback]
* @return {LinkedListNode}
*/
find({ value = undefined, callback = undefined }) {
if (!this.head) {
return null;
@ -91,6 +109,9 @@ export default class LinkedList {
return null;
}
/**
* @return {LinkedListNode}
*/
deleteTail() {
if (this.head === this.tail) {
const deletedTail = this.tail;
@ -116,6 +137,9 @@ export default class LinkedList {
return deletedTail;
}
/**
* @return {LinkedListNode}
*/
deleteHead() {
if (!this.head) {
return null;
@ -133,6 +157,9 @@ export default class LinkedList {
return deletedHead;
}
/**
* @return {LinkedListNode[]}
*/
toArray() {
const nodes = [];
@ -145,6 +172,10 @@ export default class LinkedList {
return nodes;
}
/**
* @param {function} [callback]
* @return {string}
*/
toString(callback) {
return this.toArray().map(node => node.toString(callback)).toString();
}

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@ -5,10 +5,16 @@ export default class Stack {
this.linkedList = new LinkedList();
}
/**
* @return {boolean}
*/
isEmpty() {
return !this.linkedList.tail;
}
/**
* @return {LinkedListNode}
*/
peek() {
if (!this.linkedList.tail) {
return null;
@ -17,15 +23,35 @@ export default class Stack {
return this.linkedList.tail.value;
}
/**
* @param {*} value
*/
push(value) {
this.linkedList.append(value);
}
/**
* @return {LinkedListNode}
*/
pop() {
const removedTail = this.linkedList.deleteTail();
return removedTail ? removedTail.value : null;
}
/**
* @return {*[]}
*/
toArray() {
return this.linkedList
.toArray()
.map(linkedListNode => linkedListNode.value)
.reverse();
}
/**
* @param {function} [callback]
* @return {string}
*/
toString(callback) {
return this.linkedList.toString(callback);
}

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@ -62,4 +62,16 @@ describe('Stack', () => {
expect(stack.pop().value).toBe('test2');
expect(stack.pop().value).toBe('test1');
});
it('should be possible to convert stack to array', () => {
const stack = new Stack();
expect(stack.peek()).toBeNull();
stack.push(1);
stack.push(2);
stack.push(3);
expect(stack.toArray()).toEqual([3, 2, 1]);
});
});