Derived from the D3.js example force_cluster.html
network() is the one who takes care of (re)generating the nodes and links from the original data, based on the collapse[] info, i.e. which group(s) should be shown in collapsed form and which shouldn’t.
only group nodes are expected to a .size attribute (read: your own JSON should use that attribute for any node). Same goes for the fields .group_data and .link_count: all of these are expected to be generated by the network() call. (.group_data is a reference to the group (x/y/size/link_count) for a node, group_node.link_count counts the number of links between groups.)
you’ll very probably have to tweak .gravity, .charge, .linkDistance and maybe also .linkStrength to make your own graphs look good. Compare the final layout of this graph with the ones produced by the v2.9.6 force_cluster.html D3 code: note the generally quite different position of the groups which have only a single link to other groups; that and other differences are all due to the 4 aforementioned force parameters.
<!DOCTYPE html>
<html>
<head>
<title>Clustered Network</title>
<script src="//d3js.org/d3.v2.js"></script>
<style type="text/css">
svg {
border: 1px solid #ccc;
}
body {
font: 10px sans-serif;
}
circle.node {
fill: lightsteelblue;
stroke: #555;
stroke-width: 3px;
}
circle.leaf {
stroke: #fff;
stroke-width: 1.5px;
}
path.hull {
fill: lightsteelblue;
fill-opacity: 0.3;
}
line.link {
stroke: #333;
stroke-opacity: 0.5;
pointer-events: none;
}
</style>
</head>
<body>
<script type="text/javascript">
var width = 960, // svg width
height = 600, // svg height
dr = 4, // default point radius
off = 15, // cluster hull offset
collapse = {}, // collapsed clusters
data, net, force, hullg, hull, linkg, link, nodeg, node;
var curve = d3.svg.line()
.interpolate("cardinal-closed")
.tension(.85);
var fill = d3.scale.category20();
function noop() { return false; }
function nodeid(n) {
return n.size ? "_g_"+n.group : n.name;
}
function linkid(l) {
var u = nodeid(l.source),
v = nodeid(l.target);
return u<v ? u+"|"+v : v+"|"+u;
}
function getGroup(n) { return n.group; }
// constructs the network to visualize
function network(data, prev, index, collapse) {
collapse = collapse || {};
var gm = {}, // group map
nm = {}, // node map
lm = {}, // link map
gn = {}, // previous group nodes
gc = {}, // previous group centroids
nodes = [], // output nodes
links = []; // output links
// process previous nodes for reuse or centroid calculation
if (prev) {
prev.nodes.forEach(function(n) {
var i = index(n), o;
if (n.size > 0) {
gn[i] = n;
n.size = 0;
} else {
o = gc[i] || (gc[i] = {x:0,y:0,count:0});
o.x += n.x;
o.y += n.y;
o.count += 1;
}
});
}
// determine nodes
for (var k=0; k<data.nodes.length; ++k) {
var n = data.nodes[k],
i = index(n),
l = gm[i] || (gm[i]=gn[i]) || (gm[i]={group:i, size:0, nodes:[]});
if (collapse[i] !== true) {
// the node should be directly visible
nm[n.name] = nodes.length;
nodes.push(n);
if (gn[i]) {
// place new nodes at cluster location (plus jitter)
n.x = gn[i].x + Math.random();
n.y = gn[i].y + Math.random();
}
} else {
// the node is part of a collapsed cluster
if (l.size == 0) {
// if new cluster, add to set and position at centroid of leaf nodes
nm[i] = nodes.length;
nodes.push(l);
if (gc[i]) {
l.x = gc[i].x / gc[i].count;
l.y = gc[i].y / gc[i].count;
}
}
l.nodes.push(n);
}
// always count group size as we also use it to tweak the force graph strengths/distances
l.size += 1;
n.group_data = l;
}
for (i in gm) { gm[i].link_count = 0; }
// determine links
for (k=0; k<data.links.length; ++k) {
var e = data.links[k],
u = index(e.source),
v = index(e.target);
if (u != v) {
gm[u].link_count++;
gm[v].link_count++;
}
u = !collapse[u] ? nm[e.source.name] : nm[u];
v = !collapse[v] ? nm[e.target.name] : nm[v];
var i = (u<v ? u+"|"+v : v+"|"+u),
l = lm[i] || (lm[i] = {source:u, target:v, size:0});
l.size += 1;
}
for (i in lm) { links.push(lm[i]); }
return {nodes: nodes, links: links};
}
function convexHulls(nodes, index, offset) {
var hulls = {};
// create point sets
for (var k=0; k<nodes.length; ++k) {
var n = nodes[k];
if (n.size) continue;
var i = index(n),
l = hulls[i] || (hulls[i] = []);
l.push([n.x-offset, n.y-offset]);
l.push([n.x-offset, n.y+offset]);
l.push([n.x+offset, n.y-offset]);
l.push([n.x+offset, n.y+offset]);
}
// create convex hulls
var hullset = [];
for (i in hulls) {
hullset.push({group: i, path: d3.geom.hull(hulls[i])});
}
return hullset;
}
function drawCluster(d) {
return curve(d.path); // 0.8
}
// --------------------------------------------------------
var body = d3.select("body");
var vis = body.append("svg")
.attr("width", width)
.attr("height", height);
d3.json("miserables.json", function(json) {
data = json;
for (var i=0; i<data.links.length; ++i) {
o = data.links[i];
o.source = data.nodes[o.source];
o.target = data.nodes[o.target];
}
hullg = vis.append("g");
linkg = vis.append("g");
nodeg = vis.append("g");
init();
vis.attr("opacity", 1e-6)
.transition()
.duration(1000)
.attr("opacity", 1);
});
function init() {
if (force) force.stop();
net = network(data, net, getGroup, collapse);
force = d3.layout.force()
.nodes(net.nodes)
.links(net.links)
.size([width, height])
.linkDistance(function(l, i) {
var n1 = l.source, n2 = l.target;
// larger distance for bigger groups:
// both between single nodes and _other_ groups (where size of own node group still counts),
// and between two group nodes.
//
// reduce distance for groups with very few outer links,
// again both in expanded and grouped form, i.e. between individual nodes of a group and
// nodes of another group or other group node or between two group nodes.
//
// The latter was done to keep the single-link groups ('blue', rose, ...) close.
return 30 +
Math.min(20 * Math.min((n1.size || (n1.group != n2.group ? n1.group_data.size : 0)),
(n2.size || (n1.group != n2.group ? n2.group_data.size : 0))),
-30 +
30 * Math.min((n1.link_count || (n1.group != n2.group ? n1.group_data.link_count : 0)),
(n2.link_count || (n1.group != n2.group ? n2.group_data.link_count : 0))),
100);
//return 150;
})
.linkStrength(function(l, i) {
return 1;
})
.gravity(0.05) // gravity+charge tweaked to ensure good 'grouped' view (e.g. green group not smack between blue&orange, ...
.charge(-600) // ... charge is important to turn single-linked groups to the outside
.friction(0.5) // friction adjusted to get dampened display: less bouncy bouncy ball [Swedish Chef, anyone?]
.start();
hullg.selectAll("path.hull").remove();
hull = hullg.selectAll("path.hull")
.data(convexHulls(net.nodes, getGroup, off))
.enter().append("path")
.attr("class", "hull")
.attr("d", drawCluster)
.style("fill", function(d) { return fill(d.group); })
.on("click", function(d) {
console.log("hull click", d, arguments, this, collapse[d.group]);
collapse[d.group] = true; init();
});
link = linkg.selectAll("line.link").data(net.links, linkid);
link.exit().remove();
link.enter().append("line")
.attr("class", "link")
.attr("x1", function(d) { return d.source.x; })
.attr("y1", function(d) { return d.source.y; })
.attr("x2", function(d) { return d.target.x; })
.attr("y2", function(d) { return d.target.y; })
.style("stroke-width", function(d) { return d.size || 1; });
node = nodeg.selectAll("circle.node").data(net.nodes, nodeid);
node.exit().remove();
node.enter().append("circle")
// if (d.size) -- d.size > 0 when d is a group node.
.attr("class", function(d) { return "node" + (d.size?"":" leaf"); })
.attr("r", function(d) { return d.size ? d.size + dr : dr+1; })
.attr("cx", function(d) { return d.x; })
.attr("cy", function(d) { return d.y; })
.style("fill", function(d) { return fill(d.group); })
.on("click", function(d) {
console.log("node click", d, arguments, this, collapse[d.group]);
collapse[d.group] = !collapse[d.group];
init();
});
node.call(force.drag);
force.on("tick", function() {
if (!hull.empty()) {
hull.data(convexHulls(net.nodes, getGroup, off))
.attr("d", drawCluster);
}
link.attr("x1", function(d) { return d.source.x; })
.attr("y1", function(d) { return d.source.y; })
.attr("x2", function(d) { return d.target.x; })
.attr("y2", function(d) { return d.target.y; });
node.attr("cx", function(d) { return d.x; })
.attr("cy", function(d) { return d.y; });
});
}
</script>
</body>
</html>
Code derived from the d3.js 'force' example:
The miserables.json file contains the weighted network of coappearances of
characters in Victor Hugo's novel /Les Miserables/. Nodes represent characters
as indicated by the labels, and edges connect any pair of characters that
appear in the same chapter of the book. The values on the edges are the number
of such coappearances. The data on coappearances were taken from D. E. Knuth,
"The Stanford GraphBase: A Platform for Combinatorial Computing",
Addison-Wesley, Reading, MA (1993).
The group labels were transcribed from "Finding and evaluating community
structure in networks" by M. E. J. Newman and M. Girvan.
{"nodes":[{"name":"Myriel","group":1},{"name":"Napoleon","group":1},{"name":"Mlle.Baptistine","group":1},{"name":"Mme.Magloire","group":1},{"name":"CountessdeLo","group":1},{"name":"Geborand","group":1},{"name":"Champtercier","group":1},{"name":"Cravatte","group":1},{"name":"Count","group":1},{"name":"OldMan","group":1},{"name":"Labarre","group":2},{"name":"Valjean","group":2},{"name":"Marguerite","group":3},{"name":"Mme.deR","group":2},{"name":"Isabeau","group":2},{"name":"Gervais","group":2},{"name":"Tholomyes","group":3},{"name":"Listolier","group":3},{"name":"Fameuil","group":3},{"name":"Blacheville","group":3},{"name":"Favourite","group":3},{"name":"Dahlia","group":3},{"name":"Zephine","group":3},{"name":"Fantine","group":3},{"name":"Mme.Thenardier","group":4},{"name":"Thenardier","group":4},{"name":"Cosette","group":5},{"name":"Javert","group":4},{"name":"Fauchelevent","group":0},{"name":"Bamatabois","group":2},{"name":"Perpetue","group":3},{"name":"Simplice","group":2},{"name":"Scaufflaire","group":2},{"name":"Woman1","group":2},{"name":"Judge","group":2},{"name":"Champmathieu","group":2},{"name":"Brevet","group":2},{"name":"Chenildieu","group":2},{"name":"Cochepaille","group":2},{"name":"Pontmercy","group":4},{"name":"Boulatruelle","group":6},{"name":"Eponine","group":4},{"name":"Anzelma","group":4},{"name":"Woman2","group":5},{"name":"MotherInnocent","group":0},{"name":"Gribier","group":0},{"name":"Jondrette","group":7},{"name":"Mme.Burgon","group":7},{"name":"Gavroche","group":8},{"name":"Gillenormand","group":5},{"name":"Magnon","group":5},{"name":"Mlle.Gillenormand","group":5},{"name":"Mme.Pontmercy","group":5},{"name":"Mlle.Vaubois","group":5},{"name":"Lt.Gillenormand","group":5},{"name":"Marius","group":8},{"name":"BaronessT","group":5},{"name":"Mabeuf","group":8},{"name":"Enjolras","group":8},{"name":"Combeferre","group":8},{"name":"Prouvaire","group":8},{"name":"Feuilly","group":8},{"name":"Courfeyrac","group":8},{"name":"Bahorel","group":8},{"name":"Bossuet","group":8},{"name":"Joly","group":8},{"name":"Grantaire","group":8},{"name":"MotherPlutarch","group":9},{"name":"Gueulemer","group":4},{"name":"Babet","group":4},{"name":"Claquesous","group":4},{"name":"Montparnasse","group":4},{"name":"Toussaint","group":5},{"name":"Child1","group":10},{"name":"Child2","group":10},{"name":"Brujon","group":4},{"name":"Mme.Hucheloup","group":8}],"links":[{"source":1,"target":0,"value":1},{"source":2,"target":0,"value":8},{"source":3,"target":0,"value":10},{"source":3,"target":2,"value":6},{"source":4,"target":0,"value":1},{"source":5,"target":0,"value":1},{"source":6,"target":0,"value":1},{"source":7,"target":0,"value":1},{"source":8,"target":0,"value":2},{"source":9,"target":0,"value":1},{"source":11,"target":10,"value":1},{"source":11,"target":3,"value":3},{"source":11,"target":2,"value":3},{"source":11,"target":0,"value":5},{"source":12,"target":11,"value":1},{"source":13,"target":11,"value":1},{"source":14,"target":11,"value":1},{"source":15,"target":11,"value":1},{"source":17,"target":16,"value":4},{"source":18,"target":16,"value":4},{"source":18,"target":17,"value":4},{"source":19,"target":16,"value":4},{"source":19,"target":17,"value":4},{"source":19,"target":18,"value":4},{"source":20,"target":16,"value":3},{"source":20,"target":17,"value":3},{"source":20,"target":18,"value":3},{"source":20,"target":19,"value":4},{"source":21,"target":16,"value":3},{"source":21,"target":17,"value":3},{"source":21,"target":18,"value":3},{"source":21,"target":19,"value":3},{"source":21,"target":20,"value":5},{"source":22,"target":16,"value":3},{"source":22,"target":17,"value":3},{"source":22,"target":18,"value":3},{"source":22,"target":19,"value":3},{"source":22,"target":20,"value":4},{"source":22,"target":21,"value":4},{"source":23,"target":16,"value":3},{"source":23,"target":17,"value":3},{"source":23,"target":18,"value":3},{"source":23,"target":19,"value":3},{"source":23,"target":20,"value":4},{"source":23,"target":21,"value":4},{"source":23,"target":22,"value":4},{"source":23,"target":12,"value":2},{"source":23,"target":11,"value":9},{"source":24,"target":23,"value":2},{"source":24,"target":11,"value":7},{"source":25,"target":24,"value":13},{"source":25,"target":23,"value":1},{"source":25,"target":11,"value":12},{"source":26,"target":24,"value":4},{"source":26,"target":11,"value":31},{"source":26,"target":16,"value":1},{"source":26,"target":25,"value":1},{"source":27,"target":11,"value":17},{"source":27,"target":23,"value":5},{"source":27,"target":25,"value":5},{"source":27,"target":24,"value":1},{"source":27,"target":26,"value":1},{"source":28,"target":11,"value":8},{"source":28,"target":27,"value":1},{"source":29,"target":23,"value":1},{"source":29,"target":27,"value":1},{"source":29,"target":11,"value":2},{"source":30,"target":23,"value":1},{"source":31,"target":30,"value":2},{"source":31,"target":11,"value":3},{"source":31,"target":23,"value":2},{"source":31,"target":27,"value":1},{"source":32,"target":11,"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