from timeit import Timer
# This is gratefully modeled after the benchmarks found in
# the numpy svn repository. http://svn.scipy.org/svn/numpy/trunk
class Benchmark(object):
"""
Benchmark a method or simple bit of code using different Graph classes.
If the test code is the same for each graph class, then you can set it
during instantiation through the argument test_string.
The argument test_string can also be a tuple of test code and setup code.
The code is entered as a string valid for use with the timeit module.
Example:
>>> b=Benchmark(['Graph','XGraph'])
>>> b['Graph']=('G.add_nodes_from(nlist)','nlist=range(100)')
>>> b.run()
"""
def __init__(self,graph_classes,title='',test_string=None,runs=3,reps=1000):
self.runs = runs
self.reps = reps
self.title = title
self.class_tests = dict((gc,'') for gc in graph_classes)
# set up the test string if it is the same for all classes.
if test_string is not None:
if isinstance(test_string,tuple):
self['all']=test_string
else:
self['all']=(test_string,'')
def __setitem__(self,graph_class,(test_str,setup_str)):
"""
Set a simple bit of code and setup string for the test.
Use this for cases where the code differs from one class to another.
"""
if graph_class == 'all':
graph_class = self.class_tests.keys()
elif not isinstance(graph_class,list):
graph_class = [graph_class]
for GC in graph_class:
setup_string='import networkx as NX\nG=NX.%s.%s()\n'%\
(GC.lower(),GC) + setup_str
self.class_tests[GC] = Timer(test_str, setup_string)
def run(self):
"""Run the benchmark for each class and print results."""
column_len = max(len(G) for G in self.class_tests)
print '='*72
if self.title:
print "%s: %s runs, %s reps"% (self.title,self.runs,self.reps)
print '='*72
times=[]
for GC,timer in self.class_tests.items():
name = GC.ljust(column_len)
try:
t=sum(timer.repeat(self.runs,self.reps))/self.runs
# print "%s: %s" % (name, timer.repeat(self.runs,self.reps))
times.append((t,name))
except Exception, e:
print "%s: Failed to benchmark (%s)." % (name,e)
times.sort()
tmin=times[0][0]
for t,name in times:
print "%s: %5.2f %s" % (name, t/tmin*100.,t)
print '-'*72
print
if __name__ == "__main__":
# set up for all routines:
classes=['Graph','MultiGraph','DiGraph','MultiDiGraph']
all_tests=['add_nodes','add_edges','remove_nodes','remove_edges',\
'neighbors','edges','degree','dijkstra','shortest path',\
'subgraph','edgedata_subgraph','laplacian']
# Choose which tests to run
tests=all_tests
tests=['subgraph','edgedata_subgraph']
#tests=all_tests[-1:]
N=100
if 'add_nodes' in tests:
title='Benchmark: Adding nodes'
test_string=('G.add_nodes_from(nlist)','nlist=range(%i)'%N)
b=Benchmark(classes,title,test_string,runs=3,reps=1000)
b.run()
if 'add_edges' in tests:
title='Benchmark: Adding edges'
setup='elist=[(i,i+3) for i in range(%s-3)]\nG.add_nodes_from(range(%i))'%(N,N)
test_string=('G.add_edges_from(elist)',setup)
b=Benchmark(classes,title,test_string,runs=3,reps=1000)
b.run()
if 'remove_nodes' in tests:
title='Benchmark: Adding and Deleting nodes'
setup='nlist=range(%i)'%N
test_string=('G.add_nodes_from(nlist)\nG.remove_nodes_from(nlist)',setup)
b=Benchmark(classes,title,test_string,runs=3,reps=1000)
b.run()
if 'remove_edges' in tests:
title='Benchmark: Adding and Deleting edges'
setup='elist=[(i,i+3) for i in range(%s-3)]'%N
test_string=('G.add_edges_from(elist)\nG.remove_edges_from(elist)',setup)
b=Benchmark(classes,title,test_string,runs=3,reps=1000)
b.run()
if 'neighbors' in tests:
N=500
p=0.3
title='Benchmark: reporting neighbors'
b=Benchmark(classes,title,runs=3,reps=1)
test_string='for n in G:\n for nbr in G.neighbors(n):\n pass'
all_setup='H=NX.binomial_graph(%s,%s)\nfor (u,v) in H.edges_iter():\n '%(N,p)
setup=all_setup+'G.add_edge(u,v)\n'
if 'Graph' in classes: b['Graph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'DiGraph' in classes: b['DiGraph']=(test_string,setup)
setup=all_setup+'G.add_edge(u,v)'
if 'MultiGraph' in classes: b['MultiGraph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'MultiDiGraph' in classes: b['MultiDiGraph']=(test_string,setup)
b.run()
if 'edges' in tests:
N=500
p=0.3
title='Benchmark: reporting edges'
b=Benchmark(classes,title,runs=3,reps=1)
test_string='for n in G:\n for e in G.edges(n):\n pass'
all_setup='H=NX.binomial_graph(%s,%s)\nfor (u,v) in H.edges_iter():\n '%(N,p)
setup=all_setup+'G.add_edge(u,v)\n'
if 'Graph' in classes: b['Graph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'DiGraph' in classes: b['DiGraph']=(test_string,setup)
setup=all_setup+'G.add_edge(u,v)'
if 'MultiGraph' in classes: b['MultiGraph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'MultiDiGraph' in classes: b['MultiDiGraph']=(test_string,setup)
b.run()
if 'degree' in tests:
N=500
p=0.3
title='Benchmark: reporting degree'
b=Benchmark(classes,title,runs=3,reps=1)
test_string='for d in G.degree():\n pass'
all_setup='H=NX.binomial_graph(%s,%s)\nfor (u,v) in H.edges_iter():\n '%(N,p)
setup=all_setup+'G.add_edge(u,v)\n'
if 'Graph' in classes: b['Graph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'DiGraph' in classes: b['DiGraph']=(test_string,setup)
setup=all_setup+'G.add_edge(u,v)'
if 'MultiGraph' in classes: b['MultiGraph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'MultiDiGraph' in classes: b['MultiDiGraph']=(test_string,setup)
b.run()
if 'dijkstra' in tests:
N=500
p=0.3
title='dijkstra single source shortest path'
b=Benchmark(classes,title,runs=3,reps=1)
test_string='p=NX.single_source_dijkstra(G,i)'
all_setup='i=6\nH=NX.binomial_graph(%s,%s)\nfor (u,v) in H.edges_iter():\n '%(N,p)
setup=all_setup+'G.add_edge(u,v)'
if 'Graph' in classes: b['Graph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'DiGraph' in classes: b['DiGraph']=(test_string,setup)
setup=all_setup+'G.add_edge(u,v)'
if 'MultiGraph' in classes: b['MultiGraph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'MultiDiGraph' in classes: b['MultiDiGraph']=(test_string,setup)
b.run()
if 'shortest path' in tests:
N=500
p=0.3
title='single source shortest path'
b=Benchmark(classes,title,runs=3,reps=1)
test_string='p=NX.single_source_shortest_path(G,i)'
all_setup='i=6\nH=NX.binomial_graph(%s,%s)\nfor (u,v) in H.edges_iter():\n '%(N,p)
setup=all_setup+'G.add_edge(u,v)'
if 'Graph' in classes: b['Graph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'DiGraph' in classes: b['DiGraph']=(test_string,setup)
setup=all_setup+'G.add_edge(u,v)'
if 'MultiGraph' in classes: b['MultiGraph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'MultiDiGraph' in classes: b['MultiDiGraph']=(test_string,setup)
b.run()
if 'subgraph' in tests:
N=500
p=0.3
title='subgraph method'
b=Benchmark(classes,title,runs=3,reps=1)
test_string='G.subgraph(nlist)'
all_setup='nlist=range(100,150)\nH=NX.binomial_graph(%s,%s)\nfor (u,v) in H.edges_iter():\n '%(N,p)
setup=all_setup+'G.add_edge(u,v)'
if 'Graph' in classes: b['Graph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'DiGraph' in classes: b['DiGraph']=(test_string,setup)
setup=all_setup+'G.add_edge(u,v)'
if 'MultiGraph' in classes: b['MultiGraph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'MultiDiGraph' in classes: b['MultiDiGraph']=(test_string,setup)
b.run()
if 'edgedata_subgraph' in tests:
N=500
p=0.3
title='subgraph method with edge data present'
b=Benchmark(classes,title,runs=3,reps=1)
test_string='G.subgraph(nlist)'
all_setup='nlist=range(100,150)\nH=NX.binomial_graph(%s,%s)\nfor (u,v) in H.edges_iter():\n '%(N,p)
setup=all_setup+'G.add_edge(u,v,hi=3)'
if 'Graph' in classes: b['Graph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)],hi=2)'
if 'DiGraph' in classes: b['DiGraph']=(test_string,setup)
setup=all_setup+'G.add_edge(u,v,hi=1)'
if 'MultiGraph' in classes: b['MultiGraph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)],hi=2)'
if 'MultiDiGraph' in classes: b['MultiDiGraph']=(test_string,setup)
b.run()
if 'laplacian' in tests:
N=500
p=0.3
title='creation of laplacian matrix'
b=Benchmark(classes,title,runs=3,reps=1)
test_string='NX.laplacian(G)'
all_setup='H=NX.binomial_graph(%s,%s)\nfor (u,v) in H.edges_iter():\n '%(N,p)
setup=all_setup+'G.add_edge(u,v)'
if 'Graph' in classes: b['Graph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'DiGraph' in classes: b['DiGraph']=(test_string,setup)
setup=all_setup+'G.add_edge(u,v)'
if 'MultiGraph' in classes: b['MultiGraph']=(test_string,setup)
setup=all_setup+'G.add_edges_from([(u,v),(v,u)])'
if 'MultiDiGraph' in classes: b['MultiDiGraph']=(test_string,setup)
b.run()
|