preparing for next release

Author: jdfekete

README.md

@@ -1,6 +1,8 @@
 # Reorder.js
 
-[Reorder.js](http://www.reorderjs.org/) is a JavaScript library for reordering matrices.
+[Reorder.js](https://github.com/jdfekete/reorder.js/) is a JavaScript library for reordering matrices.
+
+Want to learn more? [See the wiki.](https://github.com/jdfekete/reorder.js/wiki)
 
 ## Development
 

src/graph2distmat.js

@@ -0,0 +1,37 @@
+// Converts a graph with weighted edges (weight in l.value)
+// into a distance matrix suitable for reordering with e.g.
+// Optimal Leaf Ordering.
+
+function distmat2valuemat(distmat) {
+    var n = distmat.length,
+	valuemat = reorder.zeroes(n, n),
+	max_dist = reorder.distmax(distmat),
+	i, j;
+
+    for (i = 0; i < n; i++) {
+	for (j = i; j < n; j++) {	    
+	    valuemat[j][i] = valuemat[i][j] = 1+max_dist - distmat[i][j];
+	}
+    }
+    return valuemat;
+}
+reorder.distmat2valuemat = distmat2valuemat;
+
+reorder.graph2valuemats = function(graph, comps) {
+    if (! comps)
+	comps = graph.components();
+
+    var	dists = reorder.all_pairs_distance(graph, comps);
+    return dists.map(distmat2valuemat);
+};
+
+reorder.valuemats_reorder = function(valuemats, leaforder, comps) {
+    var orders = valuemats.map(leaforder);
+
+    if (comps) {
+	orders = orders.map(function(d, i) {
+	    return reorder.permute(comps[i], d);
+	});
+    }
+    return orders.reduce(reorder.flatten);
+};

test/graph2distmat-test.js

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+require("science");
+require("../reorder.v1");
+require("../reorder.v1");
+
+var vows = require("vows"),
+    assert = require("assert");
+var seedrandom = require('seedrandom');
+Math.seedrandom('reorder');
+
+var suite = vows.describe("reorder.graph2distmat");
+
+suite.addBatch({
+    "graph2distmat": {
+	"simple": function() {
+	    var mat = [
+		[0, 1, 0],
+		[1, 0, 1],
+		[0, 1, 0]
+	    ],
+		dist = [
+		    [0, 1, 2],
+		    [1, 0, 1],
+		    [2, 1, 0]
+		];
+	    var graph = reorder.mat2graph(mat);
+	    assert.equal(graph.nodes().length, 3);
+	    assert.equal(graph.links().length, 2);
+	    var dists = reorder.all_pairs_distance(graph);
+	    assert.deepEqual(dists[0], dist);
+	    var valuemat = reorder.distmat2valuemat(dist);
+	    assert.deepEqual(valuemat,
+			     [[3, 2, 1],
+			      [2, 3, 2],
+			      [1, 2, 3]]);
+	    // var max_link = graph.links().reduce(
+	    // 	function(a, b) {
+	    // 	    return a.value > b.value ? a : b;
+	    // 	}),
+	    // 	max_value = max_link ? max_link.value : 0;
+	    // var links = graph.links()
+	    // 	    .map(function(l) {
+	    // 		return {
+	    // 		    value: (max_value - l.value)/max_value,
+	    // 		    source: l.source.index,
+	    // 		    target: l.target.index
+	    // 		};
+	    // 	    });
+	    // console.log(links);
+	}
+    }
+});
+
+suite.export(module);