def read_graph_labels():
rtn = {}
glabel_orig_new_map = {}
with open(get_data_path() + '/{}/label/label.txt'.format(conf.infolder)) as f:
for line in f:
ls = line.rstrip().split()
assert (len(ls) == 2)
gid = get_file_base_id(ls[0])
orig_glabel = int(float(ls[1]))
glabel = glabel_orig_new_map.get(orig_glabel)
if glabel is None: # dangerous to test not glabel since glabel could be 0!
glabel = len(glabel_orig_new_map) # 0-based
glabel_orig_new_map[orig_glabel] = glabel
rtn[gid] = glabel
return rtn
def gen_imdb_multi():
dirin = get_data_path() + '/imdb_comedy_romance_scifi/graph'
k = float('inf')
lesseqk = []
for file in glob(dirin + '/*.gexf'):
g = nx.read_gexf(file)
gid = get_file_base_id(file)
print(gid, g.number_of_nodes())
if g.number_of_nodes() <= k:
g.graph['gid'] = gid
for node in g.nodes():
del g.node[node]['node_class']
for edge in g.edges_iter(data=True):
del edge[2]['weight']
lesseqk.append(g)
print(len(lesseqk))
gen_dataset(lesseqk)
def main():
dirin = get_data_path() + '/{}/graph'.format(conf.infolder)
k = float('inf')
lesseqk = []
glabel_map = read_graph_labels()
info_map = {}
disconnected = []
files = glob(dirin + '/*.gexf')
if conf.need_sort_:
files = sorted_nicely(files)
for i, file in enumerate(files):
g = nx.read_gexf(file)
gid = get_file_base_id(file)
print(i, gid, g.number_of_nodes())
if g.number_of_nodes() <= k:
if not nx.is_connected(g):
print(gid, 'is not connected')
gsize = g.number_of_nodes()
g = max(nx.connected_component_subgraphs(g), key=len)
grmd = gsize - g.number_of_nodes()
assert (grmd > 0)
g_info = 'rm_{}_nodes'.format(grmd)
disconnected.append(g)
else:
g_info = ''
lesseqk.append(g)
info_map[gid] = g_info
g.graph['gid'] = gid
g.graph['label'] = glabel_map[gid]
for node, d in g.nodes(data=True):
type = d['node_class']
if conf.has_node_type:
d.pop('node_class')
d['type'] = type
for edge in g.edges_iter(data=True):
del edge[2]['weight']
print(len(lesseqk))
gen_dataset(lesseqk)
gen_dataset(disconnected)
save_glabels_as_txt(get_data_path() + '/{}/glabels'.format(conf.outfolder), glabel_map)
save_glabels_as_txt(get_data_path() + '/{}/info'.format(conf.outfolder), info_map)
def _load_emb(self, train):
fn = get_result_path(
) + '/{}/emb/{}_graph2vec_{}_emb_dim_{}.npy'.format(
self.dataset, self.dataset, 'train' if train else 'test', self.dim)
if isfile(fn):
emb = np.load(fn)
print('Loaded emb {} from {}'.format(emb.shape, fn))
return emb
data = load_data(self.dataset, train=train)
id_map = self._gid_to_matrixid(data)
emb = np.zeros((len(data.graphs), self.dim))
cnt = 0
d = self._load_json_emb()
for f in d:
gid = get_file_base_id(f)
if gid in id_map:
emb[id_map[gid]] = d[f]
cnt += 1
if cnt != len(id_map):
raise RuntimeError('Mismatch: {} != {}').format(cnt, len(id_map))
np.save(fn, emb)
print('Saved emb {} to {}'.format(emb.shape, fn))
return emb
def get_old_aids_id():
files = glob(get_root_path() + '/data/AIDS_old/data/*.gxl')
return [get_file_base_id(file) for file in files]