def add_to_data(name, g, i, t, data):
g = get_topo_graph(name)
print ">>>%s: %s of %s" % (name, i, t)
de = GraphData(name=name,
n=g.number_of_nodes(),
e=g.number_of_edges(),
ad=g.number_of_edges() / float(g.number_of_nodes()),
ic=nx.is_connected(g),
c=nx.number_connected_components(g),
w=total_weight(g) if has_weights(g) else 0)
data.append(de)
print "\t" + str(de)
def add_to_data(name, g, i, t, data):
g = get_topo_graph(name)
print ">>>%s: %s of %s" % (name, i, t)
de = GraphData(name = name,
n = g.number_of_nodes(),
e = g.number_of_edges(),
ad = g.number_of_edges() / float(g.number_of_nodes()),
ic = nx.is_connected(g),
c = nx.number_connected_components(g),
w = total_weight(g) if has_weights(g) else 0)
data.append(de)
print "\t" + str(de)
def print_topo_stats(name, g):
n = g.number_of_nodes()
e = g.number_of_edges()
ad = 2.0 * g.number_of_edges() / float(g.number_of_nodes())
ic = nx.is_connected(g)
c = nx.number_connected_components(g)
w = total_weight(g) if has_weights(g) else 0
if COMPACT:
print "%s: %s %s %.1f %s %s %.1f" % (name, n, e, ad, ic, c, w)
else:
print "***********"
print "topo name: %s" % name
print "number of nodes: %s" % n
print "number of edges: %s" % e
print "average degree: %.1f" % ad
print "is connected: %s" % ic
print "connected components: %s" % c
print "total weight: %.1f" % w
def print_topo_stats(name, g):
n = g.number_of_nodes()
e = g.number_of_edges()
ad = 2.0 * g.number_of_edges() / float(g.number_of_nodes())
ic = nx.is_connected(g)
c = nx.number_connected_components(g)
w = total_weight(g) if has_weights(g) else 0
if COMPACT:
print "%s: %s %s %.1f %s %s %.1f" % (name, n, e, ad, ic, c, w)
else:
print "***********"
print "topo name: %s" % name
print "number of nodes: %s" % n
print "number of edges: %s" % e
print "average degree: %.1f" % ad
print "is connected: %s" % ic
print "connected components: %s" % c
print "total weight: %.1f" % w
# plot_data[ptype][metric] = [dict of topo data, keyed by metric]
# each value includes:
# x: list of sorted controller k's
# lines: dict of y-axis lists, keyed by aspect
plot_data = {}
# CSV format:
csv_fields = ['metric', 'ptype', 'name', 'topo', 'n', 'e', 'w', 'gdf_name', 'x', 'y']
csv_tuples = []
for i, topo in enumerate(topos):
if not options.max == None and i >= options.max:
break
g, usable, note = get_topo_graph(topo)
if usable:
w = total_weight(g)
# Check for --force here?
print "usable topo: %s" % topo
total_usable += 1
controllers = metrics.get_controllers(g, options)
exp_filename = metrics.get_filename(topo, options, controllers)
path_exists = os.path.exists(exp_filename + '.json')
compute_metrics = 'metrics' in options.operations
# Compute data only when the following conditions hold:
# - asked to complete metrics, AND
# - asked to force, or data is missing
if compute_metrics and (options.force or not path_exists):
print "freshly analyzing topo: %s" % topo
