two version of R2R are here HEAD master

1 files changed, 321 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/networkx/algorithms/operators/all.py b/.venv/lib/python3.12/site-packages/networkx/algorithms/operators/all.py
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+"""Operations on many graphs."""
+
+from itertools import chain, repeat
+
+import networkx as nx
+
+__all__ = ["union_all", "compose_all", "disjoint_union_all", "intersection_all"]
+
+
+@nx._dispatchable(graphs="[graphs]", preserve_all_attrs=True, returns_graph=True)
+def union_all(graphs, rename=()):
+    """Returns the union of all graphs.
+
+    The graphs must be disjoint, otherwise an exception is raised.
+
+    Parameters
+    ----------
+    graphs : iterable
+       Iterable of NetworkX graphs
+
+    rename : iterable , optional
+       Node names of graphs can be changed by specifying the tuple
+       rename=('G-','H-') (for example).  Node "u" in G is then renamed
+       "G-u" and "v" in H is renamed "H-v". Infinite generators (like itertools.count)
+       are also supported.
+
+    Returns
+    -------
+    U : a graph with the same type as the first graph in list
+
+    Raises
+    ------
+    ValueError
+       If `graphs` is an empty list.
+
+    NetworkXError
+        In case of mixed type graphs, like MultiGraph and Graph, or directed and undirected graphs.
+
+    Notes
+    -----
+    For operating on mixed type graphs, they should be converted to the same type.
+    >>> G = nx.Graph()
+    >>> H = nx.DiGraph()
+    >>> GH = union_all([nx.DiGraph(G), H])
+
+    To force a disjoint union with node relabeling, use
+    disjoint_union_all(G,H) or convert_node_labels_to integers().
+
+    Graph, edge, and node attributes are propagated to the union graph.
+    If a graph attribute is present in multiple graphs, then the value
+    from the last graph in the list with that attribute is used.
+
+    Examples
+    --------
+    >>> G1 = nx.Graph([(1, 2), (2, 3)])
+    >>> G2 = nx.Graph([(4, 5), (5, 6)])
+    >>> result_graph = nx.union_all([G1, G2])
+    >>> result_graph.nodes()
+    NodeView((1, 2, 3, 4, 5, 6))
+    >>> result_graph.edges()
+    EdgeView([(1, 2), (2, 3), (4, 5), (5, 6)])
+
+    See Also
+    --------
+    union
+    disjoint_union_all
+    """
+    R = None
+    seen_nodes = set()
+
+    # rename graph to obtain disjoint node labels
+    def add_prefix(graph, prefix):
+        if prefix is None:
+            return graph
+
+        def label(x):
+            return f"{prefix}{x}"
+
+        return nx.relabel_nodes(graph, label)
+
+    rename = chain(rename, repeat(None))
+    graphs = (add_prefix(G, name) for G, name in zip(graphs, rename))
+
+    for i, G in enumerate(graphs):
+        G_nodes_set = set(G.nodes)
+        if i == 0:
+            # Union is the same type as first graph
+            R = G.__class__()
+        elif G.is_directed() != R.is_directed():
+            raise nx.NetworkXError("All graphs must be directed or undirected.")
+        elif G.is_multigraph() != R.is_multigraph():
+            raise nx.NetworkXError("All graphs must be graphs or multigraphs.")
+        elif not seen_nodes.isdisjoint(G_nodes_set):
+            raise nx.NetworkXError(
+                "The node sets of the graphs are not disjoint.\n"
+                "Use `rename` to specify prefixes for the graphs or use\n"
+                "disjoint_union(G1, G2, ..., GN)."
+            )
+
+        seen_nodes |= G_nodes_set
+        R.graph.update(G.graph)
+        R.add_nodes_from(G.nodes(data=True))
+        R.add_edges_from(
+            G.edges(keys=True, data=True) if G.is_multigraph() else G.edges(data=True)
+        )
+
+    if R is None:
+        raise ValueError("cannot apply union_all to an empty list")
+
+    return R
+
+
+@nx._dispatchable(graphs="[graphs]", preserve_all_attrs=True, returns_graph=True)
+def disjoint_union_all(graphs):
+    """Returns the disjoint union of all graphs.
+
+    This operation forces distinct integer node labels starting with 0
+    for the first graph in the list and numbering consecutively.
+
+    Parameters
+    ----------
+    graphs : iterable
+       Iterable of NetworkX graphs
+
+    Returns
+    -------
+    U : A graph with the same type as the first graph in list
+
+    Raises
+    ------
+    ValueError
+       If `graphs` is an empty list.
+
+    NetworkXError
+        In case of mixed type graphs, like MultiGraph and Graph, or directed and undirected graphs.
+
+    Examples
+    --------
+    >>> G1 = nx.Graph([(1, 2), (2, 3)])
+    >>> G2 = nx.Graph([(4, 5), (5, 6)])
+    >>> U = nx.disjoint_union_all([G1, G2])
+    >>> list(U.nodes())
+    [0, 1, 2, 3, 4, 5]
+    >>> list(U.edges())
+    [(0, 1), (1, 2), (3, 4), (4, 5)]
+
+    Notes
+    -----
+    For operating on mixed type graphs, they should be converted to the same type.
+
+    Graph, edge, and node attributes are propagated to the union graph.
+    If a graph attribute is present in multiple graphs, then the value
+    from the last graph in the list with that attribute is used.
+    """
+
+    def yield_relabeled(graphs):
+        first_label = 0
+        for G in graphs:
+            yield nx.convert_node_labels_to_integers(G, first_label=first_label)
+            first_label += len(G)
+
+    R = union_all(yield_relabeled(graphs))
+
+    return R
+
+
+@nx._dispatchable(graphs="[graphs]", preserve_all_attrs=True, returns_graph=True)
+def compose_all(graphs):
+    """Returns the composition of all graphs.
+
+    Composition is the simple union of the node sets and edge sets.
+    The node sets of the supplied graphs need not be disjoint.
+
+    Parameters
+    ----------
+    graphs : iterable
+       Iterable of NetworkX graphs
+
+    Returns
+    -------
+    C : A graph with the same type as the first graph in list
+
+    Raises
+    ------
+    ValueError
+       If `graphs` is an empty list.
+
+    NetworkXError
+        In case of mixed type graphs, like MultiGraph and Graph, or directed and undirected graphs.
+
+    Examples
+    --------
+    >>> G1 = nx.Graph([(1, 2), (2, 3)])
+    >>> G2 = nx.Graph([(3, 4), (5, 6)])
+    >>> C = nx.compose_all([G1, G2])
+    >>> list(C.nodes())
+    [1, 2, 3, 4, 5, 6]
+    >>> list(C.edges())
+    [(1, 2), (2, 3), (3, 4), (5, 6)]
+
+    Notes
+    -----
+    For operating on mixed type graphs, they should be converted to the same type.
+
+    Graph, edge, and node attributes are propagated to the union graph.
+    If a graph attribute is present in multiple graphs, then the value
+    from the last graph in the list with that attribute is used.
+    """
+    R = None
+
+    # add graph attributes, H attributes take precedent over G attributes
+    for i, G in enumerate(graphs):
+        if i == 0:
+            # create new graph
+            R = G.__class__()
+        elif G.is_directed() != R.is_directed():
+            raise nx.NetworkXError("All graphs must be directed or undirected.")
+        elif G.is_multigraph() != R.is_multigraph():
+            raise nx.NetworkXError("All graphs must be graphs or multigraphs.")
+
+        R.graph.update(G.graph)
+        R.add_nodes_from(G.nodes(data=True))
+        R.add_edges_from(
+            G.edges(keys=True, data=True) if G.is_multigraph() else G.edges(data=True)
+        )
+
+    if R is None:
+        raise ValueError("cannot apply compose_all to an empty list")
+
+    return R
+
+
+@nx._dispatchable(graphs="[graphs]", returns_graph=True)
+def intersection_all(graphs):
+    """Returns a new graph that contains only the nodes and the edges that exist in
+    all graphs.
+
+    Parameters
+    ----------
+    graphs : iterable
+       Iterable of NetworkX graphs
+
+    Returns
+    -------
+    R : A new graph with the same type as the first graph in list
+
+    Raises
+    ------
+    ValueError
+       If `graphs` is an empty list.
+
+    NetworkXError
+        In case of mixed type graphs, like MultiGraph and Graph, or directed and undirected graphs.
+
+    Notes
+    -----
+    For operating on mixed type graphs, they should be converted to the same type.
+
+    Attributes from the graph, nodes, and edges are not copied to the new
+    graph.
+
+    The resulting graph can be updated with attributes if desired. For example, code which adds the minimum attribute for each node across all graphs could work.
+    >>> g = nx.Graph()
+    >>> g.add_node(0, capacity=4)
+    >>> g.add_node(1, capacity=3)
+    >>> g.add_edge(0, 1)
+
+    >>> h = g.copy()
+    >>> h.nodes[0]["capacity"] = 2
+
+    >>> gh = nx.intersection_all([g, h])
+
+    >>> new_node_attr = {
+    ...     n: min(*(anyG.nodes[n].get("capacity", float("inf")) for anyG in [g, h]))
+    ...     for n in gh
+    ... }
+    >>> nx.set_node_attributes(gh, new_node_attr, "new_capacity")
+    >>> gh.nodes(data=True)
+    NodeDataView({0: {'new_capacity': 2}, 1: {'new_capacity': 3}})
+
+    Examples
+    --------
+    >>> G1 = nx.Graph([(1, 2), (2, 3)])
+    >>> G2 = nx.Graph([(2, 3), (3, 4)])
+    >>> R = nx.intersection_all([G1, G2])
+    >>> list(R.nodes())
+    [2, 3]
+    >>> list(R.edges())
+    [(2, 3)]
+
+    """
+    R = None
+
+    for i, G in enumerate(graphs):
+        G_nodes_set = set(G.nodes)
+        G_edges_set = set(G.edges)
+        if not G.is_directed():
+            if G.is_multigraph():
+                G_edges_set.update((v, u, k) for u, v, k in list(G_edges_set))
+            else:
+                G_edges_set.update((v, u) for u, v in list(G_edges_set))
+        if i == 0:
+            # create new graph
+            R = G.__class__()
+            node_intersection = G_nodes_set
+            edge_intersection = G_edges_set
+        elif G.is_directed() != R.is_directed():
+            raise nx.NetworkXError("All graphs must be directed or undirected.")
+        elif G.is_multigraph() != R.is_multigraph():
+            raise nx.NetworkXError("All graphs must be graphs or multigraphs.")
+        else:
+            node_intersection &= G_nodes_set
+            edge_intersection &= G_edges_set
+
+    if R is None:
+        raise ValueError("cannot apply intersection_all to an empty list")
+
+    R.add_nodes_from(node_intersection)
+    R.add_edges_from(edge_intersection)
+
+    return R