data.py 文件源码

def parse_cora_sparse():
    path = "%s/../data/cora/" % (current_dir,)

    features, labels, id2index = _parse_cora_features_labels()

    n_papers = len(id2index)
    graph = nx.Graph()

    with open(path + 'cora.cites', 'r') as f:
        for line in f.xreadlines():
            items = line.strip().split('\t')

            tail = id2index[items[0]]
            head = id2index[items[1]]

            graph.add_edge(head, tail)

    adj = nx.to_scipy_sparse_matrix(graph, format='csr')

    return adj.astype('float32'), features.astype('float32'), labels.astype('int32')