Module Expr Str Import alias identifier Assign NameStore Call AttributeLoad Str attr ListLoad Str Str Assign NameStore ListLoad Str Str Str Str Str Str FunctionDef arguments args NameParam NameParam NameParam defaults NameLoad body Expr Str If Call AttributeLoad NameLoad attr body Raise Call AttributeLoad NameLoad attr Str If Call AttributeLoad NameLoad attr body Assign NameStore NameLoad If NameLoad body Assign NameStore Call AttributeLoad NameLoad attr orelse Assign NameStore Call AttributeLoad NameLoad attr orelse Assign NameStore NameLoad If NameLoad body Assign NameStore Call AttributeLoad NameLoad attr orelse Assign NameStore Call AttributeLoad NameLoad attr Expr Call AttributeLoad AttributeLoad NameLoad attr attr AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr GeneratorExp TupleLoad NameLoad SubscriptLoad AttributeLoad NameLoad attr Index NameLoad comprehension NameStore NameLoad For NameStore NameLoad body Assign NameStore BinOpSub Call NameLoad GeneratorExp NameLoad comprehension NameStore SubscriptLoad NameLoad Index NameLoad comprehension NameStore SubscriptLoad NameLoad Index NameLoad Call NameLoad ListLoad NameLoad If NameLoad body For NameStore NameLoad body If NameLoad body Assign NameStore BinOpBitAnd Call NameLoad SubscriptLoad NameLoad Index NameLoad Call NameLoad SubscriptLoad AttributeLoad NameLoad attr Index NameLoad orelse Assign NameStore BinOpBitAnd Call NameLoad SubscriptLoad NameLoad Index NameLoad Call NameLoad SubscriptLoad NameLoad Index NameLoad For NameStore NameLoad body If UnaryOpNot Call AttributeLoad NameLoad attr NameLoad NameLoad NameLoad body Expr Call AttributeLoad NameLoad attr NameLoad NameLoad keyword NameLoad orelse Expr Call AttributeLoad NameLoad attr GeneratorExp TupleLoad NameLoad NameLoad comprehension NameStore NameLoad Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults NameLoad body Expr Str If Call AttributeLoad NameLoad attr body Raise Call AttributeLoad NameLoad attr Str If Call AttributeLoad NameLoad attr body Assign NameStore AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr orelse Assign NameStore AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr Expr Call AttributeLoad AttributeLoad NameLoad attr attr AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr GeneratorExp TupleLoad NameLoad SubscriptLoad AttributeLoad NameLoad attr Index NameLoad comprehension NameStore NameLoad Assign NameStore Call NameLoad BinOpSub Call NameLoad NameLoad Call NameLoad NameLoad For NameStore NameLoad body Assign NameStore Call NameLoad SubscriptLoad NameLoad Index NameLoad Assign NameStore BinOpSub Call NameLoad GeneratorExp NameLoad comprehension NameStore NameLoad comprehension NameStore SubscriptLoad NameLoad Index NameLoad Call NameLoad ListLoad NameLoad For NameStore NameLoad body Assign NameStore Call NameLoad SubscriptLoad NameLoad Index NameLoad Assign NameStore BinOpBitAnd NameLoad NameLoad If UnaryOpNot NameLoad body Assign NameStore Call NameLoad NameLoad orelse Assign NameStore BinOpDiv Call NameLoad NameLoad NameLoad Expr Call AttributeLoad NameLoad attr NameLoad NameLoad keyword NameLoad Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Expr Str If Call AttributeLoad NameLoad attr body Raise Call AttributeLoad NameLoad attr Str If Call AttributeLoad NameLoad attr body Assign NameStore AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr orelse Assign NameStore AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr Expr Call AttributeLoad AttributeLoad NameLoad attr attr AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr GeneratorExp TupleLoad NameLoad SubscriptLoad AttributeLoad NameLoad attr Index NameLoad comprehension NameStore NameLoad For NameStore NameLoad body Assign NameStore Call NameLoad SubscriptLoad NameLoad Index NameLoad Assign NameStore BinOpSub Call NameLoad GeneratorExp NameLoad comprehension NameStore NameLoad comprehension NameStore SubscriptLoad NameLoad Index NameLoad Call NameLoad ListLoad NameLoad For NameStore NameLoad body Assign NameStore Call NameLoad SubscriptLoad NameLoad Index NameLoad Assign NameStore BinOpBitAnd NameLoad NameLoad Assign NameStore Call NameLoad ListComp BinOpDiv Num BinOpSub Call NameLoad SubscriptLoad NameLoad Index NameLoad Num comprehension NameStore NameLoad CompareGt Call NameLoad SubscriptLoad NameLoad Index NameLoad Num Expr Call AttributeLoad NameLoad attr NameLoad NameLoad keyword NameLoad Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults NameLoad body Expr Str If Call AttributeLoad NameLoad attr body Raise Call AttributeLoad NameLoad attr Str If Call AttributeLoad NameLoad attr body Assign NameStore AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr orelse Assign NameStore AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr Expr Call AttributeLoad AttributeLoad NameLoad attr attr AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr GeneratorExp TupleLoad NameLoad SubscriptLoad AttributeLoad NameLoad attr Index NameLoad comprehension NameStore NameLoad For NameStore NameLoad body Assign NameStore Call NameLoad SubscriptLoad NameLoad Index NameLoad Assign NameStore BinOpSub Call NameLoad GeneratorExp NameLoad comprehension NameStore NameLoad comprehension NameStore SubscriptLoad NameLoad Index NameLoad Call NameLoad ListLoad NameLoad For NameStore NameLoad body Assign NameStore Call NameLoad SubscriptLoad NameLoad Index NameLoad If NameLoad body Assign NameStore BinOpDiv Call NameLoad Call NameLoad BinOpBitAnd NameLoad NameLoad Call NameLoad BinOpBitOr NameLoad NameLoad orelse Assign NameStore BinOpDiv Call NameLoad Call NameLoad BinOpBitAnd NameLoad NameLoad Call NameLoad Call NameLoad NameLoad Call NameLoad NameLoad Expr Call AttributeLoad NameLoad attr NameLoad NameLoad keyword NameLoad Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults NameLoad body Expr Str If Call AttributeLoad NameLoad attr body Raise Call AttributeLoad NameLoad attr Str If Call AttributeLoad NameLoad attr body Assign NameStore AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr orelse Assign NameStore AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr If CompareIs NameLoad NameLoad body FunctionDef arguments args NameParam NameParam NameParam defaults body Return Call NameLoad BinOpBitAnd Call NameLoad SubscriptLoad NameLoad Index NameLoad Call NameLoad SubscriptLoad NameLoad Index NameLoad decorator_list Expr Call AttributeLoad AttributeLoad NameLoad attr attr AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr GeneratorExp TupleLoad NameLoad SubscriptLoad AttributeLoad NameLoad attr Index NameLoad comprehension NameStore NameLoad For NameStore NameLoad body Assign NameStore BinOpSub Call NameLoad GeneratorExp NameLoad comprehension NameStore Call NameLoad SubscriptLoad NameLoad Index NameLoad comprehension NameStore SubscriptLoad NameLoad Index NameLoad Call NameLoad ListLoad NameLoad For NameStore NameLoad body Assign NameStore Call NameLoad NameLoad NameLoad NameLoad Expr Call AttributeLoad NameLoad attr NameLoad NameLoad keyword NameLoad Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults NameLoad body Return Call NameLoad NameLoad NameLoad decorator_list
N/A N/A One-mode (unipartite) projections of bipartite graphs.
 N/A networkx nx N/A __author__ N/A N/A join N/A Aric Hagberg <aric.hagberg@gmail.com> Jordi Torrents <jtorrents@milnou.net> N/A __all__ N/A project projected_graph weighted_projected_graph collaboration_weighted_projected_graph overlap_weighted_projected_graph generic_weighted_projected_graph projected_graph N/A N/A B nodes multigraph N/A False N/A N/A Returns the projection of B onto one of its node sets.

    Returns the graph G that is the projection of the bipartite graph B 
    onto the specified nodes. They retain their attributes and are connected
    in G if they have a common neighbor in B.

    Parameters
    ----------
    B : NetworkX graph 
      The input graph should be bipartite. 

    nodes : list or iterable
      Nodes to project onto (the "bottom" nodes).

    multigraph: bool (default=False)
       If True return a multigraph where the multiple edges represent multiple
       shared neighbors.  They edge key in the multigraph is assigned to the
       label of the neighbor.

    Returns
    -------
    Graph : NetworkX graph or multigraph
       A graph that is the projection onto the given nodes.

    Examples
    --------
    >>> from networkx.algorithms import bipartite
    >>> B = nx.path_graph(4)
    >>> G = bipartite.projected_graph(B, [1,3]) 
    >>> print(G.nodes())
    [1, 3]
    >>> print(G.edges())
    [(1, 3)]
    
    If nodes `a`, and `b` are connected through both nodes 1 and 2 then
    building a multigraph results in two edges in the projection onto 
    [`a`,`b`]:

    >>> B = nx.Graph()
    >>> B.add_edges_from([('a', 1), ('b', 1), ('a', 2), ('b', 2)])
    >>> G = bipartite.projected_graph(B, ['a', 'b'], multigraph=True)
    >>> print([sorted((u,v)) for u,v in G.edges()])
    [['a', 'b'], ['a', 'b']]

    Notes
    ------
    No attempt is made to verify that the input graph B is bipartite.
    Returns a simple graph that is the projection of the bipartite graph B
    onto the set of nodes given in list nodes.  If multigraph=True then
    a multigraph is returned with an edge for every shared neighbor.

    Directed graphs are allowed as input.  The output will also then
    be a directed graph with edges if there is a directed path between
    the nodes.

    The graph and node properties are (shallow) copied to the projected graph.

    See Also
    --------
    is_bipartite, 
    is_bipartite_node_set, 
    sets, 
    weighted_projected_graph,
    collaboration_weighted_projected_graph,
    overlap_weighted_projected_graph,
    generic_weighted_projected_graph
     N/A N/A N/A B is_multigraph N/A N/A N/A N/A nx NetworkXError not defined for multigraphs N/A N/A N/A B is_directed N/A N/A directed True N/A multigraph N/A N/A G N/A N/A nx MultiDiGraph N/A N/A G N/A N/A nx DiGraph N/A N/A directed False N/A multigraph N/A N/A G N/A N/A nx MultiGraph N/A N/A G N/A N/A nx Graph N/A N/A N/A N/A G graph update N/A B graph N/A N/A N/A G add_nodes_from N/A N/A n N/A N/A B node N/A n N/A n nodes N/A u nodes N/A N/A nbrs2 N/A N/A set N/A v N/A nbr N/A B N/A u N/A v N/A B N/A nbr N/A set N/A u N/A multigraph N/A N/A n nbrs2 N/A N/A directed N/A N/A links N/A N/A set N/A B N/A u N/A set N/A N/A B pred N/A n N/A N/A links N/A N/A set N/A B N/A u N/A set N/A B N/A n N/A l links N/A N/A N/A N/A N/A G has_edge u n l N/A N/A N/A N/A G add_edge u n key l N/A N/A N/A N/A G add_edges_from N/A N/A u n N/A n nbrs2 N/A G N/A weighted_projected_graph N/A N/A B nodes ratio N/A False N/A N/A Returns a weighted projection of B onto one of its node sets.

    The weighted projected graph is the projection of the bipartite
    network B onto the specified nodes with weights representing the
    number of shared neighbors or the ratio between actual shared
    neighbors and possible shared neighbors if ratio=True [1]_. The
    nodes retain their attributes and are connected in the resulting graph
    if they have an edge to a common node in the original graph.

    Parameters
    ----------
    B : NetworkX graph 
        The input graph should be bipartite. 

    nodes : list or iterable
        Nodes to project onto (the "bottom" nodes).

    ratio: Bool (default=False)
        If True, edge weight is the ratio between actual shared neighbors 
        and possible shared neighbors. If False, edges weight is the number 
        of shared neighbors.

    Returns
    -------
    Graph : NetworkX graph 
       A graph that is the projection onto the given nodes.

    Examples
    --------
    >>> from networkx.algorithms import bipartite
    >>> B = nx.path_graph(4)
    >>> G = bipartite.weighted_projected_graph(B, [1,3])
    >>> print(G.nodes())
    [1, 3]
    >>> print(G.edges(data=True))
    [(1, 3, {'weight': 1})]
    >>> G = bipartite.weighted_projected_graph(B, [1,3], ratio=True)
    >>> print(G.edges(data=True))
    [(1, 3, {'weight': 0.5})]
    
    Notes
    ------
    No attempt is made to verify that the input graph B is bipartite.
    The graph and node properties are (shallow) copied to the projected graph.

    See Also
    --------
    is_bipartite, 
    is_bipartite_node_set, 
    sets, 
    collaboration_weighted_projected_graph,
    overlap_weighted_projected_graph,
    generic_weighted_projected_graph
    projected_graph 

    References
    ----------
    .. [1] Borgatti, S.P. and Halgin, D. In press. "Analyzing Affiliation 
        Networks". In Carrington, P. and Scott, J. (eds) The Sage Handbook 
        of Social Network Analysis. Sage Publications.
     N/A N/A N/A B is_multigraph N/A N/A N/A N/A nx NetworkXError not defined for multigraphs N/A N/A N/A B is_directed N/A N/A pred N/A B pred N/A G N/A N/A nx DiGraph N/A N/A pred N/A B adj N/A G N/A N/A nx Graph N/A N/A N/A N/A G graph update N/A B graph N/A N/A N/A G add_nodes_from N/A N/A n N/A N/A B node N/A n N/A n nodes N/A n_top N/A float N/A N/A len B N/A len nodes N/A u nodes N/A N/A unbrs N/A set N/A B N/A u N/A nbrs2 N/A N/A set N/A n N/A nbr unbrs N/A n N/A B N/A nbr N/A set N/A u N/A v nbrs2 N/A N/A vnbrs N/A set N/A pred N/A v N/A common N/A unbrs vnbrs N/A N/A ratio N/A N/A weight N/A len common N/A N/A weight N/A N/A len common n_top N/A N/A N/A G add_edge u v weight weight N/A G N/A collaboration_weighted_projected_graph N/A N/A B nodes N/A N/A N/A Newman's weighted projection of B onto one of its node sets.

    The collaboration weighted projection is the projection of the
    bipartite network B onto the specified nodes with weights assigned
    using Newman's collaboration model [1]_:

    .. math::
        
        w_{v,u} = \sum_k \frac{\delta_{v}^{w} \delta_{w}^{k}}{k_w - 1}

    where `v` and `u` are nodes from the same bipartite node set,
    and `w` is a node of the opposite node set. 
    The value `k_w` is the degree of node `w` in the bipartite
    network and `\delta_{v}^{w}` is 1 if node `v` is
    linked to node `w` in the original bipartite graph or 0 otherwise.
 
    The nodes retain their attributes and are connected in the resulting
    graph if have an edge to a common node in the original bipartite
    graph.

    Parameters
    ----------
    B : NetworkX graph 
      The input graph should be bipartite. 

    nodes : list or iterable
      Nodes to project onto (the "bottom" nodes).

    Returns
    -------
    Graph : NetworkX graph 
       A graph that is the projection onto the given nodes.

    Examples
    --------
    >>> from networkx.algorithms import bipartite
    >>> B = nx.path_graph(5)
    >>> B.add_edge(1,5)
    >>> G = bipartite.collaboration_weighted_projected_graph(B, [0, 2, 4, 5])
    >>> print(G.nodes())
    [0, 2, 4, 5]
    >>> for edge in G.edges(data=True): print(edge)
    ... 
    (0, 2, {'weight': 0.5})
    (0, 5, {'weight': 0.5})
    (2, 4, {'weight': 1.0})
    (2, 5, {'weight': 0.5})
    
    Notes
    ------
    No attempt is made to verify that the input graph B is bipartite.
    The graph and node properties are (shallow) copied to the projected graph.

    See Also
    --------
    is_bipartite, 
    is_bipartite_node_set, 
    sets, 
    weighted_projected_graph,
    overlap_weighted_projected_graph,
    generic_weighted_projected_graph,
    projected_graph 

    References
    ----------
    .. [1] Scientific collaboration networks: II. 
        Shortest paths, weighted networks, and centrality, 
        M. E. J. Newman, Phys. Rev. E 64, 016132 (2001).
     N/A N/A N/A B is_multigraph N/A N/A N/A N/A nx NetworkXError not defined for multigraphs N/A N/A N/A B is_directed N/A N/A pred N/A B pred N/A G N/A N/A nx DiGraph N/A N/A pred N/A B adj N/A G N/A N/A nx Graph N/A N/A N/A N/A G graph update N/A B graph N/A N/A N/A G add_nodes_from N/A N/A n N/A N/A B node N/A n N/A n nodes N/A u nodes N/A N/A unbrs N/A set N/A B N/A u N/A nbrs2 N/A N/A set N/A n N/A nbr unbrs N/A n N/A B N/A nbr N/A set N/A u N/A v nbrs2 N/A N/A vnbrs N/A set N/A pred N/A v N/A common N/A unbrs vnbrs N/A weight N/A sum N/A N/A 1.0 N/A N/A len N/A B N/A n 1 N/A n common N/A N/A len N/A B N/A n 1 N/A N/A N/A G add_edge u v weight weight N/A G N/A overlap_weighted_projected_graph N/A N/A B nodes jaccard N/A True N/A N/A Overlap weighted projection of B onto one of its node sets.

    The overlap weighted projection is the projection of the bipartite 
    network B onto the specified nodes with weights representing 
    the Jaccard index between the neighborhoods of the two nodes in the
    original bipartite network [1]_: 

    .. math::
        
        w_{v,u} = \frac{|N(u) \cap N(v)|}{|N(u) \cup N(v)|}

    or if the parameter 'jaccard' is False, the fraction of common 
    neighbors by minimum of both nodes degree in the original 
    bipartite graph [1]_:
    
    .. math::

        w_{v,u} = \frac{|N(u) \cap N(v)|}{min(|N(u)|,|N(v)|)}
    
    The nodes retain their attributes and are connected in the resulting
    graph if have an edge to a common node in the original bipartite graph.

    Parameters
    ----------
    B : NetworkX graph 
        The input graph should be bipartite. 

    nodes : list or iterable
        Nodes to project onto (the "bottom" nodes).

    jaccard: Bool (default=True)

    Returns
    -------
    Graph : NetworkX graph 
       A graph that is the projection onto the given nodes.

    Examples
    --------
    >>> from networkx.algorithms import bipartite
    >>> B = nx.path_graph(5)
    >>> G = bipartite.overlap_weighted_projected_graph(B, [0, 2, 4])
    >>> print(G.nodes())
    [0, 2, 4]
    >>> print(G.edges(data=True))
    [(0, 2, {'weight': 0.5}), (2, 4, {'weight': 0.5})]
    >>> G = bipartite.overlap_weighted_projected_graph(B, [0, 2, 4], jaccard=False)
    >>> print(G.edges(data=True))
    [(0, 2, {'weight': 1.0}), (2, 4, {'weight': 1.0})]
    
    Notes
    ------
    No attempt is made to verify that the input graph B is bipartite.
    The graph and node properties are (shallow) copied to the projected graph.

    See Also
    --------
    is_bipartite, 
    is_bipartite_node_set, 
    sets, 
    weighted_projected_graph,
    collaboration_weighted_projected_graph,
    generic_weighted_projected_graph,
    projected_graph 

    References
    ----------
    .. [1] Borgatti, S.P. and Halgin, D. In press. Analyzing Affiliation 
        Networks. In Carrington, P. and Scott, J. (eds) The Sage Handbook 
        of Social Network Analysis. Sage Publications.
    
     N/A N/A N/A B is_multigraph N/A N/A N/A N/A nx NetworkXError not defined for multigraphs N/A N/A N/A B is_directed N/A N/A pred N/A B pred N/A G N/A N/A nx DiGraph N/A N/A pred N/A B adj N/A G N/A N/A nx Graph N/A N/A N/A N/A G graph update N/A B graph N/A N/A N/A G add_nodes_from N/A N/A n N/A N/A B node N/A n N/A n nodes N/A u nodes N/A N/A unbrs N/A set N/A B N/A u N/A nbrs2 N/A N/A set N/A n N/A nbr unbrs N/A n N/A B N/A nbr N/A set N/A u N/A v nbrs2 N/A N/A vnbrs N/A set N/A pred N/A v N/A jaccard N/A N/A weight N/A N/A float N/A len N/A unbrs vnbrs N/A len N/A unbrs vnbrs N/A N/A weight N/A N/A float N/A len N/A unbrs vnbrs N/A min N/A len unbrs N/A len vnbrs N/A N/A N/A G add_edge u v weight weight N/A G N/A generic_weighted_projected_graph N/A N/A B nodes weight_function N/A None N/A N/A Weighted projection of B with a user-specified weight function.

    The bipartite network B is projected on to the specified nodes
    with weights computed by a user-specified function.  This function
    must accept as a parameter the neighborhood sets of two nodes and
    return an integer or a float.

    The nodes retain their attributes and are connected in the resulting graph 
    if they have an edge to a common node in the original graph.

    Parameters
    ----------
    B : NetworkX graph 
        The input graph should be bipartite. 

    nodes : list or iterable
        Nodes to project onto (the "bottom" nodes).

    weight_function: function
        This function must accept as parameters the same input graph 
        that this function, and two nodes; and return an integer or a float.
        The default function computes the number of shared neighbors.

    Returns
    -------
    Graph : NetworkX graph 
       A graph that is the projection onto the given nodes.

    Examples
    --------
    >>> from networkx.algorithms import bipartite
    >>> # Define some custom weight functions
    >>> def jaccard(G, u, v):
    ...     unbrs = set(G[u])
    ...     vnbrs = set(G[v])
    ...     return float(len(unbrs & vnbrs)) / len(unbrs | vnbrs)
    ... 
    >>> def my_weight(G, u, v, weight='weight'):
    ...     w = 0
    ...     for nbr in set(G[u]) & set(G[v]):
    ...         w += G.edge[u][nbr].get(weight, 1) + G.edge[v][nbr].get(weight, 1)
    ...     return w
    ... 
    >>> # A complete bipartite graph with 4 nodes and 4 edges
    >>> B = nx.complete_bipartite_graph(2,2)
    >>> # Add some arbitrary weight to the edges
    >>> for i,(u,v) in enumerate(B.edges()):
    ...     B.edge[u][v]['weight'] = i + 1
    ... 
    >>> for edge in B.edges(data=True):
    ...     print(edge)
    ... 
    (0, 2, {'weight': 1})
    (0, 3, {'weight': 2})
    (1, 2, {'weight': 3})
    (1, 3, {'weight': 4})
    >>> # Without specifying a function, the weight is equal to # shared partners
    >>> G = bipartite.generic_weighted_projected_graph(B, [0, 1])
    >>> print(G.edges(data=True))
    [(0, 1, {'weight': 2})]
    >>> # To specify a custom weight function use the weight_function parameter
    >>> G = bipartite.generic_weighted_projected_graph(B, [0, 1], weight_function=jaccard)
    >>> print(G.edges(data=True))
    [(0, 1, {'weight': 1.0})]
    >>> G = bipartite.generic_weighted_projected_graph(B, [0, 1], weight_function=my_weight)
    >>> print(G.edges(data=True))
    [(0, 1, {'weight': 10})]
    
    Notes
    ------
    No attempt is made to verify that the input graph B is bipartite.
    The graph and node properties are (shallow) copied to the projected graph.

    See Also
    --------
    is_bipartite, 
    is_bipartite_node_set, 
    sets, 
    weighted_projected_graph,
    collaboration_weighted_projected_graph,
    overlap_weighted_projected_graph,
    projected_graph 

     N/A N/A N/A B is_multigraph N/A N/A N/A N/A nx NetworkXError not defined for multigraphs N/A N/A N/A B is_directed N/A N/A pred N/A B pred N/A G N/A N/A nx DiGraph N/A N/A pred N/A B adj N/A G N/A N/A nx Graph N/A N/A weight_function None N/A weight_function N/A N/A G u v N/A N/A N/A N/A len N/A N/A set N/A G N/A u N/A set N/A pred N/A v N/A N/A N/A N/A N/A G graph update N/A B graph N/A N/A N/A G add_nodes_from N/A N/A n N/A N/A B node N/A n N/A n nodes N/A u nodes N/A N/A nbrs2 N/A N/A set N/A n N/A nbr N/A set N/A B N/A u N/A n N/A B N/A nbr N/A set N/A u N/A v nbrs2 N/A N/A weight N/A weight_function B u v N/A N/A N/A G add_edge u v weight weight N/A G N/A project N/A N/A B nodes create_using N/A None N/A N/A N/A projected_graph B nodes N/A