def cluster(clustering_error):
functions = load_functions(PD_FUNCTIONS_PATH, "pandas")
functions.update(load_functions(R_FUNCTIONS_PATH, "R"))
file_name = "clusters"
folder = os.path.join(BASE_CLUSTER_FOLDER, "%0.02f" % clustering_error)
cache.mkdir(folder)
clusters_txt_file = os.path.join(folder, "%s.txt" % file_name)
clusters_pkl_file = os.path.join(folder, "%s.pkl" % file_name)
clusters_report_file = os.path.join(folder, "%s.md" % file_name)
clusterer = RepresentativeClusterer(functions.values(),
distance_function=execution_distance)
clusters = clusterer.cluster(clusters_txt_file,
skip_singles=True,
clustering_error=clustering_error)
cache.save_pickle(clusters_pkl_file, clusters)
n_clusters = len(clusters)
sizes = [
len(cluster_funcs) for label, cluster_funcs in clusters.items()
if label != -1
]
meta_data = "## Cluster sizes\n"
meta_data += "* Number of clusters: %d\n" % n_clusters
meta_data += "* Number of functions clustered: %d\n" % sum(sizes)
meta_data += "* Number of functions not clustered: %d\n\n" % (
len(functions) - sum(sizes))
meta_data += "## REPORT\n"
meta_data += stat.Stat(sizes).report()
cache.write_file(clusters_report_file, meta_data)
def export_runner_ast(xl_path):
cache.mkdir(props.EXPORT_HOME)
writer = pd.ExcelWriter(os.path.join(props.EXPORT_HOME, xl_path),
engine='xlsxwriter')
export_similar_differences(0.9, -9, writer, "HighSim-HighSyn", "d_ast")
export_similar_differences(0.9, 22, writer, "HighSim-LowSyn", "d_ast")
export_similar_differences(-0.1, -9, writer, "LowSim-HighSyn", "d_ast")
export_similar_differences(-0.1, 22, writer, "LowSim-LowSyn", "d_ast")
writer.save()
writer.close()
def remove_overlapping_clusters(dataset, language="java_python"):
# TODO: Think about how to remove syntactic equivalence
store = mongo_store.FunctionStore(dataset)
base_file = os.path.join(properties.META_RESULTS_FOLDER, dataset,
"clusters", "%s.pkl" % language)
clusters = cache.load_pickle(base_file)
non_overlapping_clusters = {}
for label, functions in clusters.items():
if label == -1 or len(functions) == 1: continue
non_overlapping_funcs = []
metas = {}
for func in functions:
meta = store.load_metadata({"name": func.base_name})
metas[func.base_name] = meta
if len(non_overlapping_funcs) == 0:
non_overlapping_funcs.append(func)
continue
is_non_overlapping_funcs_updated = False
for i, existing_func in enumerate(non_overlapping_funcs):
existing_meta = metas[existing_func.base_name]
if overlaps(meta, existing_meta):
is_non_overlapping_funcs_updated = True
if is_more_succinct(meta, existing_meta):
non_overlapping_funcs[i] = func
break
if not is_non_overlapping_funcs_updated:
non_overlapping_funcs.append(func)
if len(non_overlapping_funcs) > 1:
non_overlapping_clusters[label] = non_overlapping_funcs
write_folder = os.path.join(properties.META_RESULTS_FOLDER, dataset,
"clusters", "non_overlapping")
cache.mkdir(write_folder)
clusters_txt_file = os.path.join(write_folder, "%s.txt" % language)
clusters_pkl_file = os.path.join(write_folder, "%s.pkl" % language)
clusters_report_file = os.path.join(write_folder, "%s.md" % language)
cache.save_pickle(clusters_pkl_file, non_overlapping_clusters)
clusterer.save_clusters_to_db(dataset, non_overlapping_clusters,
"non_overlapping")
clusterer.save_clusters_to_txt(non_overlapping_clusters, clusters_txt_file)
sizes = [
len(cluster_funcs)
for label, cluster_funcs in non_overlapping_clusters.items()
if label != -1
]
meta_data = "## Cluster sizes\n"
meta_data += "* Number of clusters: %d\n" % len(non_overlapping_clusters)
meta_data += "* Number of functions clustered: %d\n" % sum(sizes)
meta_data += "## REPORT\n"
meta_data += Stat(sizes).report()
cache.write_file(clusters_report_file, meta_data)
def save_only_target_functions(dataset, mixed_file_base_name, target_language):
"""
Save only java functions from a mixture of java and python clusters
:param dataset: Name of dataset
:param mixed_file_base_name: Type of language eg. java_python
:param target_language: Target Language
:return:
"""
clusters_base_folder = os.path.join(lib.get_clusters_folder(dataset),
"cluster_testing")
for folder in sorted(
cache.list_dir(clusters_base_folder, is_absolute=False)):
LOGGER.info("Processing '%s' ..." % folder)
folder_path = os.path.join(clusters_base_folder, folder)
cache.mkdir(folder_path)
base_clusters_file = os.path.join(folder_path,
"%s.pkl" % mixed_file_base_name)
base_clusters = cache.load_pickle(base_clusters_file)
target_clusters = {}
for label, functions in base_clusters.items():
if label == -1 or len(functions) == 1: continue
contains_target = False
contains_other = False
for func in functions:
if func.source == target_language:
contains_target = True
else:
contains_other = True
if contains_target and not contains_other:
target_clusters[label] = functions
LOGGER.info("For folder = %s, # of '%s' clusters = %d" %
(folder, target_language, len(target_clusters)))
file_path = os.path.join(folder_path, "only_%s.txt" % target_language)
pkl_path = os.path.join(folder_path, "only_%s.pkl" % target_language)
file_contents = []
for label, functions in target_clusters.items():
file_contents.append("\n\n****** Cluster %d ******" % label)
for func in functions:
file_contents.append(func.body)
cache.write_file(file_path, "\n".join(file_contents))
cache.save_pickle(pkl_path, target_clusters)
def save_only_mixed_clusters(dataset, mixed_file_base_name):
"""
Save only mixed functions
:param dataset: Name of dataset
:param mixed_file_base_name: Type of language eg. java_python
:return:
"""
clusters_base_folder = os.path.join(lib.get_clusters_folder(dataset),
"cluster_testing")
for folder in sorted(
cache.list_dir(clusters_base_folder, is_absolute=False)):
LOGGER.info("Processing '%s' ..." % folder)
folder_path = os.path.join(clusters_base_folder, folder)
cache.mkdir(folder_path)
base_clusters_file = os.path.join(folder_path,
"%s.pkl" % mixed_file_base_name)
base_clusters = cache.load_pickle(base_clusters_file)
mixed_clusters = {}
for label, functions in base_clusters.items():
if label == -1 or len(functions) == 1: continue
sources = set()
for func in functions:
sources.add(func.source)
if len(sources) > 1:
mixed_clusters[label] = functions
LOGGER.info("For folder = %s, # of mixed clusters = %d" %
(folder, len(mixed_clusters)))
file_path = os.path.join(folder_path, "only_mixed.txt")
pkl_path = os.path.join(folder_path, "only_mixed.pkl")
file_contents = []
for label, functions in mixed_clusters.items():
file_contents.append("\n\n****** Cluster %d ******" % label)
for func in functions:
file_contents.append(func.body)
cache.write_file(file_path, "\n".join(file_contents))
cache.save_pickle(pkl_path, mixed_clusters)