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Compact adjacency matrix constructor.
To use in Observable,
CompactAdjacencyMatrix = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/utils-compact-adjacency-matrix@umd/browser.js' )To vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:
var CompactAdjacencyMatrix = require( 'path/to/vendor/umd/utils-compact-adjacency-matrix/index.js' )To include the bundle in a webpage,
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/utils-compact-adjacency-matrix@umd/browser.js"></script>If no recognized module system is present, access bundle contents via the global scope:
<script type="text/javascript">
(function () {
window.CompactAdjacencyMatrix;
})();
</script>Returns a compact adjacency matrix instance.
var adj = new CompactAdjacencyMatrix( 4 );
// returns <CompactAdjacencyMatrix>
// ...
adj.addEdge( 0, 1 );
adj.addEdge( 0, 2 );
adj.addEdge( 1, 2 );
adj.addEdge( 2, 3 );<!DOCTYPE html>
<html lang="en">
<body>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/utils-compact-adjacency-matrix@umd/browser.js"></script>
<script type="text/javascript">
(function () {
// Create a new adjacency matrix:
var adj = new CompactAdjacencyMatrix( 4 );
// Add edges:
adj.addEdge( 1, 0 );
adj.addEdge( 1, 2 );
adj.addEdge( 0, 2 );
adj.addEdge( 2, 3 );
// Compute the indegrees and outdegrees for each vertex:
var id;
var od;
var i;
for ( i = 0; i < 4; i++ ) {
id = adj.inDegree( i );
od = adj.outDegree( i );
console.log( 'vertex: %d. indegree: %d. outdegree: %d.', i, id, od );
}
// Print the list of all edges:
console.log( adj.edges );
// => [ [ 0, 2 ], [ 1, 0 ], [ 1, 2 ], [ 2, 3 ] ]
// Convert the adjacency matrix to an adjacency list representation:
console.log( adj.toAdjacencyList() );
// => [ [ 2 ], [ 0, 2 ], [ 3 ], [] ]
// Compute a topological ordering:
console.log( adj.toposort() );
// => [ [ 1, 0, 2, 3 ], null ]
})();
</script>
</body>
</html>This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
See LICENSE.
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