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Isolario stability analysis
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README.md

This sankey diagram allows to analyse the stability of the graph partitioning technique used for displaying Isolario data.

Blue bars represent graph partitions and encode the amount of ASes they contain. Bars are placed in rows that represent days. Hence, each row summarizes the status of the ASes in a specific day. Links show the amount of ASes moving from one partition to another in two subsequent days.

The graph partitioning technique seems to be quite stable since:

  • the amount of partitions is almost equal to 6 except for some cases in which it is 7;
  • the overall amount of ASes slightly changes from one day to another;
  • no significant flow emerges from one day to another.

(The data set represented covers a time period of 6 months, from March 1 to September 16)

Raw
data.json
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"internal_links": 2, "id": 5, "links": 28, "as_n": 433}, {"flows": [0, 0, 0, 1, 1, 25, 0], "internal_links": 0, "id": 6, "links": 1, "as_n": 28}, {"flows": [0, 0, 0, 0, 0, 0, 1], "internal_links": 0, "id": 7, "links": 0, "as_n": 1}], "links": 314042, "as_n": 59434}]
Raw
index.coffee
###
LAYOUT SETTING
###
width = document.body.getBoundingClientRect().width
height = document.body.getBoundingClientRect().height
margin = 40
svg = d3.select 'svg'
vis = svg.append 'g'
.attrs
width: width
height: 25000
transform: "translate(10, #{margin}) rotate(-90) translate(0, #{margin}) scale(-1,1)"
# Sankey layout setting
sankey = d3.sankey()
.nodeId (d) -> d.id
.nodePadding 5
.nodeAlign (d) -> d3.sankeyCenter(d)
.size [height-margin*2, width-margin*2]
###
DATA TRANSFORMATION
###
# Data loading
draw = (path) ->
data = await fetch path
.then (response) -> response.json()
# Filter EMPTY data
data = data.filter (d) -> d.partitions?
# Compute nodes
nodes = data
.map (d,i) ->
d.partitions
.map (p,j) -> {
p...
id: "#{i}_#{j}"
row: i
cell: j
}
.reduce (acc, cur) -> acc.concat(cur)
# Compute links
links = data[0...-1]
.map (d,i) ->
d.partitions
.map (p,j) ->
p.flows
.map (f,k) -> {
source: "#{i}_#{j}"
target: "#{i+1}_#{k}"
self: j is k
value: f
}
.filter (f) -> f.value > 0
.reduce (acc, cur) -> acc.concat(cur)
.reduce (acc, cur) -> acc.concat(cur)
# Create graph structure
graph = {nodes: nodes, links: links}
# Compute sankey layout
s = sankey(graph)
# Fix node positions
x_factor = 0
s.nodes.forEach (n,i) ->
if n.cell is 0
return
else if n.cell is 1
x_factor = (s.nodes[i].y0 - 9)
s.nodes[i].y0 -= x_factor
s.nodes[i].y1 -= x_factor
# Update links position
sankey.update(s)
###
VISUALIZATION
###
# links
links = vis.selectAll '.link'
.data graph.links.filter (d) -> not(d.self)
en_links = links.enter().append 'path'
.attrs
class: 'link'
d: d3.sankeyLinkHorizontal()
.styles
'stroke-width': (d) -> Math.max(1, d.width)
.append 'title'
.text (d) -> "group#{+d.source.id[-1..]+1} -> group#{+d.target.id[-1..]+1}: #{d.value}"
# nodes
nodes = vis.selectAll '.node'
.data graph.nodes
en_nodes = nodes.enter().append 'rect'
.attrs
class: 'node'
x: (d) -> d.x0
y: (d) -> d.y0
height: (d) -> d.y1 - d.y0
width: (d) -> d.x1 - d.x0
.append 'title'
.text (d) -> "group#{+d.id[-1..]+1}\n#{d.as_n} ASes"
# Date labels
label_coords = graph.nodes.filter (d) -> d.cell is 0
labels = svg.selectAll '.label'
.data data.map (d) ->
date = new Date d.date.replace(/_/g, ' ')
return date.toLocaleDateString('en-en', {month: "short"}) + date.getDate()
labels.enter().append 'text'
.attrs
class: 'label'
x: 4
y: (d,i) ->
if i < label_coords.length
label_coords[i].x0 + 52
dy: '0.35em'
.text (d) -> d.toUpperCase()
draw './data.json'
d3.select(self.frameElement).transition().duration(500).style('height', "25000px");
Raw
index.css
body, html {
padding: 0;
margin: 0;
font-family: sans-serif;
}
svg {
width: 100%;
height: 25000px;
}
.node {
fill: steelblue;
}
.link {
fill: none;
stroke: #000;
stroke-opacity: 0.3;
}
.label {
font-size: 12px;
}
Raw
index.html
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Isolario stability analysis</title>
<script src="https://d3js.org/d3.v4.min.js"></script>
<script src="https://d3js.org/d3-selection-multi.v0.4.min.js"></script>
<script src="https://unpkg.com/d3-sankey@0"></script>
<link rel="stylesheet" href="index.css">
</head>
<body>
<svg></svg>
<script src="index.js"></script>
</body>
</html>
Raw
index.js
// Generated by CoffeeScript 2.0.0
(function() {
/*
LAYOUT SETTING
*/
var draw, height, margin, sankey, svg, vis, width,
_extends = Object.assign || function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; };
width = document.body.getBoundingClientRect().width;
height = document.body.getBoundingClientRect().height;
margin = 40;
svg = d3.select('svg');
vis = svg.append('g').attrs({
width: width,
height: 25000,
transform: `translate(10, ${margin}) rotate(-90) translate(0, ${margin}) scale(-1,1)`
});
// Sankey layout setting
sankey = d3.sankey().nodeId(function(d) {
return d.id;
}).nodePadding(5).nodeAlign(function(d) {
return d3.sankeyCenter(d);
}).size([height - margin * 2, width - margin * 2]);
/*
DATA TRANSFORMATION
*/
// Data loading
draw = async function(path) {
var data, en_links, en_nodes, graph, label_coords, labels, links, nodes, s, x_factor;
data = (await fetch(path).then(function(response) {
return response.json();
}));
// Filter EMPTY data
data = data.filter(function(d) {
return d.partitions != null;
});
// Compute nodes
nodes = data.map(function(d, i) {
return d.partitions.map(function(p, j) {
return _extends({}, p, {
id: `${i}_${j}`,
row: i,
cell: j
});
});
}).reduce(function(acc, cur) {
return acc.concat(cur);
});
// Compute links
links = data.slice(0, -1).map(function(d, i) {
return d.partitions.map(function(p, j) {
return p.flows.map(function(f, k) {
return {
source: `${i}_${j}`,
target: `${i + 1}_${k}`,
self: j === k,
value: f
};
}).filter(function(f) {
return f.value > 0;
});
}).reduce(function(acc, cur) {
return acc.concat(cur);
});
}).reduce(function(acc, cur) {
return acc.concat(cur);
});
// Create graph structure
graph = {
nodes: nodes,
links: links
};
// Compute sankey layout
s = sankey(graph);
// Fix node positions
x_factor = 0;
s.nodes.forEach(function(n, i) {
if (n.cell === 0) {
return;
} else if (n.cell === 1) {
x_factor = s.nodes[i].y0 - 9;
}
s.nodes[i].y0 -= x_factor;
return s.nodes[i].y1 -= x_factor;
});
// Update links position
sankey.update(s);
/*
VISUALIZATION
*/
// links
links = vis.selectAll('.link').data(graph.links.filter(function(d) {
return !d.self;
}));
en_links = links.enter().append('path').attrs({
class: 'link',
d: d3.sankeyLinkHorizontal()
}).styles({
'stroke-width': function(d) {
return Math.max(1, d.width);
}
}).append('title').text(function(d) {
return `group${+d.source.id.slice(-1) + 1} -> group${+d.target.id.slice(-1) + 1}: ${d.value}`;
});
// nodes
nodes = vis.selectAll('.node').data(graph.nodes);
en_nodes = nodes.enter().append('rect').attrs({
class: 'node',
x: function(d) {
return d.x0;
},
y: function(d) {
return d.y0;
},
height: function(d) {
return d.y1 - d.y0;
},
width: function(d) {
return d.x1 - d.x0;
}
}).append('title').text(function(d) {
return `group${+d.id.slice(-1) + 1}\n${d.as_n} ASes`;
});
// Date labels
label_coords = graph.nodes.filter(function(d) {
return d.cell === 0;
});
labels = svg.selectAll('.label').data(data.map(function(d) {
var date;
date = new Date(d.date.replace(/_/g, ' '));
return date.toLocaleDateString('en-en', {
month: "short"
}) + date.getDate();
}));
return labels.enter().append('text').attrs({
class: 'label',
x: 4,
y: function(d, i) {
if (i < label_coords.length) {
return label_coords[i].x0 + 52;
}
},
dy: '0.35em'
}).text(function(d) {
return d.toUpperCase();
});
};
draw('./data.json');
d3.select(self.frameElement).transition().duration(500).style('height', "25000px");
}).call(this);
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