def similar_graph(conf, result, area, alg, cand=20):
# ed, mcs, edw, mcsw
assert result.area == area
src_dir = conf.get("dag", "output_dir")
l_result = []
for fp in common.rep_dir(src_dir):
r = PCOutput(conf).load(fp)
if r.area == area:
l_result.append(r)
weight = None
if "w" in alg:
weight = EdgeTFIDF(l_result)
data = []
for r in l_result:
if r.filename == result.filename:
continue
if alg.rstrip("w") == "ed":
dist = graph_edit_distance(result, r, True, weight)
elif alg.rstrip("w") == "mcs":
dist = mcs_size_ratio(result, r, True, weight)
else:
raise ValueError()
data.append((dist, r))
#data = sorted(data, key = lambda x: x[0], reverse = False)
data = ex_sorted(data, key=lambda x: x[0], reverse=False)
for d in data[:cand]:
print d[0], d[1].filename
def similar_graph(conf, result, area, alg, cand = 20):
# ed, mcs, edw, mcsw
assert result.area == area
src_dir = conf.get("dag", "output_dir")
l_result = []
for fp in common.rep_dir(src_dir):
r = PCOutput(conf).load(fp)
if r.area == area:
l_result.append(r)
weight = None
if "w" in alg:
weight = EdgeTFIDF(l_result)
data = []
for r in l_result:
if r.filename == result.filename:
continue
if alg.rstrip("w") == "ed":
dist = graph_edit_distance(result, r, True, weight)
elif alg.rstrip("w") == "mcs":
dist = mcs_size_ratio(result, r, True, weight)
else:
raise ValueError()
data.append((dist, r))
#data = sorted(data, key = lambda x: x[0], reverse = False)
data = ex_sorted(data, key = lambda x: x[0], reverse = False)
for d in data[:cand]:
print d[0], d[1].filename
def test_dag_search(conf, method, area = None):
import cg_dag
if method is None:
method = conf.get("search", "method")
src_dir = conf.get("dag", "output_dir")
if area is None:
l_area = pcresult.result_areas(conf)
else:
l_area = [area]
for area in l_area:
l_r = pcresult.results_in_area(conf, src_dir, area)
result = []
for r in l_r:
if method == "log":
result = similar_block_log(conf, r.top_dt, r.end_dt, r.area,
ignore_same = True)
elif method in ("dag_ed", "dag_mcs"):
result = cg_dag.similar_block_dag(conf, r.top_dt, r.end_dt,
r.area, method, ignore_same = True)
else:
raise NotImplementedError
print r.cond_str()
if len(result) > 10:
result = ex_sorted(result,
key = lambda x: x[1], reverse = False)[:10]
for r_found, val in result:
print val, r_found.cond_str()
print
