mirror of
https://github.com/cwinfo/yggdrasil-map
synced 2024-09-19 16:09:34 +00:00
106 lines
3.0 KiB
Python
106 lines
3.0 KiB
Python
import pygraphviz as pgv
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import time
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import json
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import networkx as nx
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from networkx.algorithms import centrality
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import urllib
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def position_nodes(nodes, edges):
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G = pgv.AGraph(strict=True, directed=False, size='10!')
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for n in nodes.values():
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G.add_node(n.ip, label=n.label, coords=n.coords)
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for e in edges:
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G.add_edge(e.a.ip, e.b.ip, len=1.0)
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G.layout(prog='neato', args='-Gepsilon=0.0001 -Gmaxiter=100000')
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return G
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def compute_betweenness(G):
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ng = nx.Graph()
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for start in G.iternodes():
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others = G.neighbors(start)
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for other in others:
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ng.add_edge(start, other)
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c = centrality.betweenness_centrality(ng)
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for k, v in c.items():
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c[k] = v
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return c
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def canonalize_ip(ip):
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return ':'.join( i.rjust(4, '0') for i in ip.split(':') )
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def load_db():
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#with open('nodedb/nodes') as f:
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# return dict([ (canonalize_ip(v[0]), v[1]) for v in [ l.split(None)[:2] for l in f.readlines() ] if len(v) > 1 ])
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url = "https://raw.githubusercontent.com/yakamok/yggdrasil-nodelist/master/nodelist"
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f = urllib.urlopen(url)
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return dict([ (canonalize_ip(v[0]), v[1]) for v in [ l.split(None)[:2] for l in f.readlines() ] if len(v) > 1 ])
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def get_graph_json(G):
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max_neighbors = 1
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for n in G.iternodes():
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neighbors = len(G.neighbors(n))
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if neighbors > max_neighbors:
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max_neighbors = neighbors
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print 'Max neighbors: %d' % max_neighbors
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out_data = {
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'created': int(time.time()),
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'nodes': [],
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'edges': []
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}
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centralities = compute_betweenness(G)
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db = load_db()
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for n in G.iternodes():
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neighbor_ratio = len(G.neighbors(n)) / float(max_neighbors)
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pos = n.attr['pos'].split(',', 1)
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centrality = centralities.get(n.name, 0)
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size = 5*(1 + 1*centrality)
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name = db.get(canonalize_ip(n.name))
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# If label isn't the default value, set name to that instead
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if n.attr['label'] != n.name.split(':')[-1]: name = n.attr['label']
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out_data['nodes'].append({
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'id': n.name,
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'label': name if name else n.attr['label'],
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'name': name,
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'coords': n.attr['coords'],
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'x': float(pos[0]),
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'y': float(pos[1]),
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'color': _gradient_color(neighbor_ratio, [(100, 100, 100), (0, 0, 0)]),
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'size': size,
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'centrality': '%.4f' % centrality
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})
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for e in G.iteredges():
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out_data['edges'].append({
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'sourceID': e[0],
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'targetID': e[1]
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})
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return json.dumps(out_data)
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def _gradient_color(ratio, colors):
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jump = 1.0 / (len(colors) - 1)
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gap_num = int(ratio / (jump + 0.0000001))
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a = colors[gap_num]
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b = colors[gap_num + 1]
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ratio = (ratio - gap_num * jump) * (len(colors) - 1)
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r = a[0] + (b[0] - a[0]) * ratio
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g = a[1] + (b[1] - a[1]) * ratio
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b = a[2] + (b[2] - a[2]) * ratio
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return '#%02x%02x%02x' % (r, g, b)
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