def _execute(density):
num_process = 10
batch_size = 20
pool = multiprocessing.Pool(processes=num_process)
pool.map(Worker(density, batch_size), range(num_process))
pool.close()
pool.join()
results = {
'ff': [],
'pq': [],
'ek': [],
'df': [],
'cs': [],
'pr': [],
'rf': []
}
for i in range(num_process):
res = json.load(open(util.get_out_file('worker', '%s_%d.txt' % (density, i+1))))
for k, v in res.items():
results[k].extend(v)
with open(util.get_out_file('%s.txt' % density), 'w') as f:
json.dump(results, f)
print '%s DONE' % density.upper()
def draw_bar(means, density):
from matplotlib import rcParams
rcParams.update({'figure.autolayout': True})
ind = np.arange(len(means)) # the x locations for the groups
width = 0.35 # the width of the bars
fig, ax = plt.subplots()
rects = ax.bar(ind, means, width, color='g')
# add some text for labels, title and axes ticks
ax.set_ylabel('Milliseconds')
ax.set_title('Average running time on %s networks' % density)
ax.set_xticks(ind+width)
ax.set_xticklabels(('Ford-Fulkerson', 'Edmonds-Karp', 'Capacity scaling', 'Generic push relabel', 'Relabel to front'),
rotation=40, ha='right', fontsize=10)
def autolabel(rects):
# attach some text labels
for i, rect in enumerate(rects):
height = rect.get_height()
ax.text(rect.get_x()+rect.get_width()/2., height + 0.05, '%d' % means[i],
ha='center', va='bottom')
autolabel(rects)
plt.savefig(util.get_out_file('chart', '%s.png' % density))
def __call__(self, ord):
self._ord = ord + 1
self._start = ord * self._batch_size + 1
results = self._run_batch()
with open(util.get_out_file('worker', 'sparse_%d.txt' % self._ord), 'w') as f:
json.dump(results, f)
print "WORKER %d DONE" % self._ord
def _run_by_density(density, maxflow_func):
results = [_run_maxflow(maxflow_func, '%s_%d.txt' % (density, i+1)) for i in range(200)]
return results
def _run_batch(density):
results = {
'ek': _run_by_density(density, maxflow.edmonds_karp),
'df': _run_by_density(density, maxflow.edmonds_karp_dfs),
'ff': _run_by_density(density, maxflow.ford_fulkerson),
'pq': _run_by_density(density, maxflow.ford_fulkerson_pq),
'cs': _run_by_density(density, maxflow.capacity_scaling),
'pr': _run_by_density(density, maxflow.generic_push_relabel),
'rf': _run_by_density(density, maxflow.relabel_to_front)
}
return results
if __name__ == '__main__':
sparse_results = _run_batch('sparse')
with open(util.get_out_file('sparse.txt'), 'w') as f:
json.dump(sparse_results, f)
medium_results = _run_batch('medium')
with open(util.get_out_file('medium.txt'), 'w') as f:
json.dump(medium_results, f)
dense_results = _run_batch('dense')
with open(util.get_out_file('dense.txt'), 'w') as f:
json.dump(dense_results, f)
