def setUp(self):
graph = CallGraph()
graph.add_stack([Node(1), Node(2)], dict(time=1))
graph.add_stack([Node(1), Node(3)], dict(time=3))
graph.add_stack([Node(1), Node(2), Node(3)], dict(time=7))
graph.add_stack([Node(1), Node(4), Node(2), Node(3)], dict(time=2))
self.graph = graph
def profile_to_json(filename):
root = os.path.abspath(options.datadir) + os.path.sep
abspath = os.path.abspath(os.path.join(root, filename))
assert (abspath + os.path.sep).startswith(root)
graph = CallGraph.load(abspath)
total = sum(stack.weights['calls'] for stack in graph.stacks)
top_stacks = graph.stacks
#top_stacks = [stack for stack in graph.stacks if stack.weights['calls'] > total*.005]
filtered_nodes = set()
for stack in top_stacks:
filtered_nodes.update(stack.nodes)
nodes = [
dict(attrs=node.attrs, weights=node.weights, id=node.id)
for node in filtered_nodes
]
nodes = sorted(nodes, key=lambda n: -n['weights']['calls'])
#index = {node['id']: i for i, node in enumerate(nodes)}
index = dict([(node['id'], i) for i, node in enumerate(nodes)])
# High-degree nodes are generally common utility functions, and
# creating edges from all over the graph tends to obscure more than
# it helps.
degrees = Counter()
dropped = set()
for edge in six.itervalues(graph.edges):
degrees[edge.child.id] += 1
degrees[edge.parent.id] += 1
for node, degree in six.iteritems(degrees):
if degree > 6:
dropped.add(node)
edges = [
dict(source=index[edge.parent.id],
target=index[edge.child.id],
weights=edge.weights) for edge in six.itervalues(graph.edges)
if (edge.parent.id in index and edge.child.id in index
and edge.parent.id not in dropped and edge.child.id not in dropped)
]
stacks = [
dict(nodes=[index[n.id] for n in stack.nodes], weights=stack.weights)
for stack in top_stacks
]
return dict(nodes=nodes, edges=edges, stacks=stacks)
def profile_to_json(filename):
root = os.path.abspath(options.datadir) + os.path.sep
abspath = os.path.abspath(os.path.join(root, filename))
assert (abspath + os.path.sep).startswith(root)
graph = CallGraph.load(abspath)
total = sum(stack.weights['calls'] for stack in graph.stacks)
top_stacks = graph.stacks
#top_stacks = [stack for stack in graph.stacks if stack.weights['calls'] > total*.005]
filtered_nodes = set()
for stack in top_stacks:
filtered_nodes.update(stack.nodes)
nodes=[dict(attrs=node.attrs, weights=node.weights, id=node.id)
for node in filtered_nodes]
nodes = sorted(nodes, key=lambda n: -n['weights']['calls'])
#index = {node['id']: i for i, node in enumerate(nodes)}
index = dict([(node['id'], i) for i, node in enumerate(nodes)])
# High-degree nodes are generally common utility functions, and
# creating edges from all over the graph tends to obscure more than
# it helps.
degrees = Counter()
dropped = set()
for edge in graph.edges.itervalues():
degrees[edge.child.id] += 1
degrees[edge.parent.id] += 1
for node, degree in degrees.iteritems():
if degree > 6:
dropped.add(node)
edges = [dict(source=index[edge.parent.id],
target=index[edge.child.id],
weights=edge.weights)
for edge in graph.edges.itervalues()
if (edge.parent.id in index and
edge.child.id in index and
edge.parent.id not in dropped and
edge.child.id not in dropped)]
stacks = [dict(nodes=[index[n.id] for n in stack.nodes],
weights=stack.weights)
for stack in top_stacks]
return dict(nodes=nodes, edges=edges, stacks=stacks)