def import_imdb_multi_graph(self, weights):
"""
Make our_imdb multi graph using class
:param weights:
:return:
"""
weights_dict = {'movies_edges': weights[0], 'labels_edges': weights[1]}
dict_paths = {'cast': 'data_set/IMDb title_principals.csv', 'genre': 'data_set/IMDb movies.csv'}
imdb = MoviesGraph(dict_paths, self.args.graph_percentage)
gnx = imdb.create_graph()
labels = imdb.labels2int(gnx)
knowledge_gnx, knowledge_data = imdb.create_knowledge_graph(labels, self.kg_jacard_similarity_threshold)
multi_gnx = imdb.weighted_multi_graph(gnx, knowledge_gnx, labels, weights_dict)
return multi_gnx
def import_imdb_multi_graph(weights):
"""
Make our_imdb multi graph using class
:param weights:
:return:
"""
from IMDb_data_preparation_E2V import MoviesGraph
weights_dict = {'movies_edges': weights[0], 'labels_edges': weights[1]}
dict_paths = {
'cast': 'data_set/IMDb title_principals.csv',
'genre': 'data_set/IMDb movies.csv'
}
imdb = MoviesGraph(dict_paths)
gnx = imdb.create_graph()
labels = imdb.labels2int(gnx)
knowledge_gnx, knowledge_data = imdb.create_knowledge_graph(labels)
multi_gnx = imdb.weighted_multi_graph(gnx, knowledge_gnx, labels,
weights_dict)
return multi_gnx