Python networkx.to_pandas_edgelist方法代码示例

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import to_pandas_edgelist [as 别名]
def __load_graph(self):
        """
        Load an undirected and unweighted graph from an edge-list file.
        :param edgelist_filename: string or unicode
            Path to the edge-list file.
            Id of nodes are assumed to be non-negative integers.
        :param delimiter: str, default '\t'
        :param comment: str, default '#'
        :return: Compressed Sparse Row Matrix
            Adjacency matrix of the graph
        """
        edge_df = nx.to_pandas_edgelist(self.g)
        edge_list = edge_df.values
        n_nodes = int(np.max(edge_list) + 1)
        adj_matrix = sparse.coo_matrix((np.ones(edge_list.shape[0]), (edge_list[:, 0], edge_list[:, 1])),
                                       shape=tuple([n_nodes, n_nodes]),
                                       dtype=edge_list.dtype)
        adj_matrix = adj_matrix.tocsr()
        adj_matrix = adj_matrix + adj_matrix.T
        return adj_matrix 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import to_pandas_edgelist [as 别名]
def test_roundtrip(self):
        # edgelist
        Gtrue = nx.Graph([(1, 1), (1, 2)])
        df = nx.to_pandas_edgelist(Gtrue)
        G = nx.from_pandas_edgelist(df)
        assert_graphs_equal(Gtrue, G)
        # adjacency
        Gtrue = nx.Graph(({1: {1: {'weight': 1}, 2: {'weight': 1}}, 2: {1: {'weight': 1}}}))
        df = nx.to_pandas_adjacency(Gtrue, dtype=int)
        G = nx.from_pandas_adjacency(df)
        assert_graphs_equal(Gtrue, G) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import to_pandas_edgelist [as 别名]
def GRAPH_2_EDGELIST_CSV(GRAPH_2):
    edgelist = nx.to_pandas_edgelist(GRAPH_2, source='_node1', target='_node2')
    return create_mock_csv_from_dataframe(edgelist) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import to_pandas_edgelist [as 别名]
def GRAPH_3_EDGELIST_CSV(GRAPH_3):
    edgelist = nx.to_pandas_edgelist(GRAPH_3, source='_node1', target='_node2')
    return create_mock_csv_from_dataframe(edgelist) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import to_pandas_edgelist [as 别名]
def to_pandas_edgelist(G, source='source', target='target', nodelist=None,
                       dtype=None, order=None):
    """Returns the graph edge list as a Pandas DataFrame.

    Parameters
    ----------
    G : graph
        The NetworkX graph used to construct the Pandas DataFrame.

    source : str or int, optional
        A valid column name (string or integer) for the source nodes (for the
        directed case).

    target : str or int, optional
        A valid column name (string or integer) for the target nodes (for the
        directed case).

    nodelist : list, optional
       Use only nodes specified in nodelist

    Returns
    -------
    df : Pandas DataFrame
       Graph edge list

    Examples
    --------
    >>> G = nx.Graph([('A', 'B', {'cost': 1, 'weight': 7}),
    ...               ('C', 'E', {'cost': 9, 'weight': 10})])
    >>> df = nx.to_pandas_edgelist(G, nodelist=['A', 'C'])
    >>> df[['source', 'target', 'cost', 'weight']]
      source target  cost  weight
    0      A      B     1       7
    1      C      E     9      10

    """
    import pandas as pd
    if nodelist is None:
        edgelist = G.edges(data=True)
    else:
        edgelist = G.edges(nodelist, data=True)
    source_nodes = [s for s, t, d in edgelist]
    target_nodes = [t for s, t, d in edgelist]
    all_keys = set().union(*(d.keys() for s, t, d in edgelist))
    edge_attr = {k: [d.get(k, float("nan")) for s, t, d in edgelist]
                 for k in all_keys}
    edgelistdict = {source: source_nodes, target: target_nodes}
    edgelistdict.update(edge_attr)
    return pd.DataFrame(edgelistdict) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import to_pandas_edgelist [as 别名]
def to_pandas_edgelist(G, source='source', target='target', nodelist=None,
                       dtype=None, order=None):
    """Return the graph edge list as a Pandas DataFrame.

    Parameters
    ----------
    G : graph
        The NetworkX graph used to construct the Pandas DataFrame.

    source : str or int, optional
        A valid column name (string or iteger) for the source nodes (for the
        directed case).

    target : str or int, optional
        A valid column name (string or iteger) for the target nodes (for the
        directed case).

    nodelist : list, optional
       Use only nodes specified in nodelist

    Returns
    -------
    df : Pandas DataFrame
       Graph edge list

    Examples
    --------
    >>> G = nx.Graph([('A', 'B', {'cost': 1, 'weight': 7}),
    ...               ('C', 'E', {'cost': 9, 'weight': 10})])
    >>> df = nx.to_pandas_edgelist(G, nodelist=['A', 'C'])
    >>> df
       cost source target  weight
    0     1      A      B       7
    1     9      C      E      10

    """
    import pandas as pd
    if nodelist is None:
        edgelist = G.edges(data=True)
    else:
        edgelist = G.edges(nodelist, data=True)
    source_nodes = [s for s, t, d in edgelist]
    target_nodes = [t for s, t, d in edgelist]
    all_keys = set().union(*(d.keys() for s, t, d in edgelist))
    edge_attr = {k: [d.get(k, float("nan")) for s, t, d in edgelist] for k in all_keys}
    edgelistdict = {source: source_nodes, target: target_nodes}
    edgelistdict.update(edge_attr)
    return pd.DataFrame(edgelistdict)