h%SrSSKJrJr SSKr/SQr\R"SSSS9S Sj5r\R"SSSS9S 5r \R"SSSS9S 5r \R"SSS 9S 5r g)zOperations on many graphs.)chainrepeatN) union_all compose_alldisjoint_union_allintersection_allz[graphs]T)graphspreserve_all_attrs returns_graphcf^Sn[5nSm[U[S55nU4Sj[X55n[ U5GHXupE[UR 5nUS:XaUR 5nOUR5UR5:wa[R"S5eUR5UR5:wa[R"S5eURU5(d[R"S5eX6-nURRUR5 URUR SS 95 URUR5(aUR!SSS 9OUR!SS 95 GM[ Uc [#S 5eU$) aReturns the union of all graphs. The graphs must be disjoint, otherwise an exception is raised. Parameters ---------- graphs : iterable Iterable of NetworkX graphs rename : iterable , optional Node names of graphs can be changed by specifying the tuple rename=('G-','H-') (for example). Node "u" in G is then renamed "G-u" and "v" in H is renamed "H-v". Infinite generators (like itertools.count) are also supported. Returns ------- U : a graph with the same type as the first graph in list Raises ------ ValueError If `graphs` is an empty list. NetworkXError In case of mixed type graphs, like MultiGraph and Graph, or directed and undirected graphs. Notes ----- For operating on mixed type graphs, they should be converted to the same type. >>> G = nx.Graph() >>> H = nx.DiGraph() >>> GH = union_all([nx.DiGraph(G), H]) To force a disjoint union with node relabeling, use disjoint_union_all(G,H) or convert_node_labels_to integers(). Graph, edge, and node attributes are propagated to the union graph. If a graph attribute is present in multiple graphs, then the value from the last graph in the list with that attribute is used. Examples -------- >>> G1 = nx.Graph([(1, 2), (2, 3)]) >>> G2 = nx.Graph([(4, 5), (5, 6)]) >>> result_graph = nx.union_all([G1, G2]) >>> result_graph.nodes() NodeView((1, 2, 3, 4, 5, 6)) >>> result_graph.edges() EdgeView([(1, 2), (2, 3), (4, 5), (5, 6)]) See Also -------- union disjoint_union_all NcF^TcU$U4Sjn[R"X5$)Nc>TU3$N)xprefixs S/var/www/html/env/lib/python3.13/site-packages/networkx/algorithms/operators/all.pylabel,union_all..add_prefix..labelLsXaS> !)nx relabel_nodes)graphrrs ` r add_prefixunion_all..add_prefixHs% >L "--rc38># UHupT"X5v M g7frr).0Gnamers r union_all..Rs E1Dgaj!!1Dsr*All graphs must be directed or undirected.)All graphs must be graphs or multigraphs.zThe node sets of the graphs are not disjoint. Use `rename` to specify prefixes for the graphs or use disjoint_union(G1, G2, ..., GN).Tdatakeysr%z'cannot apply union_all to an empty list)setrrzip enumeratenodes __class__ is_directedr NetworkXError is_multigraph isdisjointrupdateadd_nodes_fromadd_edges_fromedges ValueError)r renameR seen_nodesir G_nodes_setrs @rrr sft AJ.66$< (F EV1D EF&!!''l 6 A ]]_  /""#OP P __ !//"3 3""#NO O&&{33""3  !  qww d+, -.__->->AGGDG )AGGQUGDV '". yBCC Hrc.Sn[U"U55nU$)aReturns 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. c3j# SnUH'n[R"X!S9v U[U5- nM) g7f)Nr) first_label)rconvert_node_labels_to_integerslen)r r=rs ryield_relabeled+disjoint_union_all..yield_relabeleds3 A44QP P 3q6 !Ks13)r)r r@r7s rrrqsV" /&)*A HrclSn[U5GHup#US:XaUR5nOpUR5UR5:wa[R"S5eUR 5UR 5:wa[R"S5eUR RUR 5 URURSS95 URUR 5(aURSSS9OURSS95 GM Uc [S5eU$) aReturns the composition of all graphs. Composition is the simple union of the node sets and edge sets. The node sets of the supplied graphs need not be disjoint. Parameters ---------- graphs : iterable Iterable of NetworkX graphs Returns ------- C : A graph with the same type as the first graph in list Raises ------ ValueError If `graphs` is an empty list. NetworkXError In case of mixed type graphs, like MultiGraph and Graph, or directed and undirected graphs. Examples -------- >>> G1 = nx.Graph([(1, 2), (2, 3)]) >>> G2 = nx.Graph([(3, 4), (5, 6)]) >>> C = nx.compose_all([G1, G2]) >>> list(C.nodes()) [1, 2, 3, 4, 5, 6] >>> list(C.edges()) [(1, 2), (2, 3), (3, 4), (5, 6)] Notes ----- For operating on mixed type graphs, they should be converted to the same type. Graph, edge, and node attributes are propagated to the union graph. If a graph attribute is present in multiple graphs, then the value from the last graph in the list with that attribute is used. Nrr"r#Tr$r&z)cannot apply compose_all to an empty list) r*r,r-rr.r/rr1r2r+r3r4r5)r r7r9rs rrrsT A&! 6 A ]]_  /""#OP P __ !//"3 3""#NO O qww d+, -.__->->AGGDG )AGGQUGDV " yDEE Hr)r r cSn[U5GH3up#[UR5n[UR5nUR 5(dXUR 5(a"UR S[U555 O!UR S[U555 US:XaUR5nUnUnMUR 5UR 5:wa[R"S5eUR 5UR 5:wa[R"S5eWU-nWU-nGM6 Uc [S5eURW5 URW5 U$)apReturns 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)] Nc3.# UH upo2X4v M g7frr)ruvks rr #intersection_all..+s"NrSs # PDQc Rc LDQ2 R2 jDQ> R> B48W 9W r