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autopep8 graphPlotter

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This commit is contained in:
Michał Zieliński 2015-07-27 21:16:01 +02:00
parent 5ae90eeae3
commit b2fbb011e6
1 changed files with 45 additions and 49 deletions
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94
web/graphPlotter.py
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@ -4,71 +4,67 @@ import json
def position_nodes(nodes, edges): def position_nodes(nodes, edges):
G = pgv.AGraph(strict=True, directed=False, size='10!') G = pgv.AGraph(strict=True, directed=False, size='10!')
for n in nodes.values(): for n in nodes.values():
G.add_node(n.ip, label=n.label, version=n.version) G.add_node(n.ip, label=n.label, version=n.version)
for e in edges: for e in edges:
G.add_edge(e.a.ip, e.b.ip, len=1.0) G.add_edge(e.a.ip, e.b.ip, len=1.0)
G.layout(prog='neato', args='-Gepsilon=0.0001 -Gmaxiter=100000') G.layout(prog='neato', args='-Gepsilon=0.0001 -Gmaxiter=100000')
return G
return G
def get_graph_json(G): def get_graph_json(G):
max_neighbors = 1 max_neighbors = 1
for n in G.iternodes(): for n in G.iternodes():
neighbors = len(G.neighbors(n)) neighbors = len(G.neighbors(n))
if neighbors > max_neighbors: if neighbors > max_neighbors:
max_neighbors = neighbors max_neighbors = neighbors
print 'Max neighbors: %d' % max_neighbors print 'Max neighbors: %d' % max_neighbors
out_data = { out_data = {
'created': int(time.time()), 'created': int(time.time()),
'nodes': [], 'nodes': [],
'edges': [] 'edges': []
} }
for n in G.iternodes(): for n in G.iternodes():
neighbor_ratio = len(G.neighbors(n)) / float(max_neighbors) neighbor_ratio = len(G.neighbors(n)) / float(max_neighbors)
pos = n.attr['pos'].split(',', 1) pos = n.attr['pos'].split(',', 1)
out_data['nodes'].append({
'id': n.name,
'label': n.attr['label'],
'version': n.attr['version'],
'x': float(pos[0]),
'y': float(pos[1]),
'color': _gradient_color(neighbor_ratio, [(100, 100, 100), (0, 0, 0)]),
'size': neighbor_ratio
})
for e in G.iteredges():
out_data['edges'].append({
'sourceID': e[0],
'targetID': e[1]
})
return json.dumps(out_data)
out_data['nodes'].append({
'id': n.name,
'label': n.attr['label'],
'version': n.attr['version'],
'x': float(pos[0]),
'y': float(pos[1]),
'color': _gradient_color(neighbor_ratio, [(100, 100, 100), (0, 0, 0)]),
'size': neighbor_ratio
})
for e in G.iteredges():
out_data['edges'].append({
'sourceID': e[0],
'targetID': e[1]
})
return json.dumps(out_data)
def _gradient_color(ratio, colors): def _gradient_color(ratio, colors):
jump = 1.0 / (len(colors) - 1) jump = 1.0 / (len(colors) - 1)
gap_num = int(ratio / (jump + 0.0000001)) gap_num = int(ratio / (jump + 0.0000001))
a = colors[gap_num] a = colors[gap_num]
b = colors[gap_num + 1] b = colors[gap_num + 1]
ratio = (ratio - gap_num * jump) * (len(colors) - 1) ratio = (ratio - gap_num * jump) * (len(colors) - 1)
r = a[0] + (b[0] - a[0]) * ratio r = a[0] + (b[0] - a[0]) * ratio
g = a[1] + (b[1] - a[1]) * ratio g = a[1] + (b[1] - a[1]) * ratio
b = a[2] + (b[2] - a[2]) * ratio b = a[2] + (b[2] - a[2]) * ratio
return '#%02x%02x%02x' % (r, g, b) return '#%02x%02x%02x' % (r, g, b)