fiOdZddlZddlZddlmZddlZddlmZm Z gdZ ej ddeddgdd Z e d ej d dd dd Z ej ddd ddZej ddddZej ddddZe d ej ddddZe d ej ddddZe d ej ddddZdZdS)z0 Generators and functions for bipartite graphs. N)reduce)nodes_or_numberpy_random_state)configuration_modelhavel_hakimi_graphreverse_havel_hakimi_graphalternating_havel_hakimi_graphpreferential_attachment_graph random_graphgnmk_random_graphcomplete_bipartite_graphT)graphs returns_graphctjd|}|rtjd\}|\}t t jr(t |t jrfdD||d|dt|t|tzkrtjd| fd|Ddt|d td |j d <|S) aReturns the complete bipartite graph `K_{n_1,n_2}`. The graph is composed of two partitions with nodes 0 to (n1 - 1) in the first and nodes n1 to (n1 + n2 - 1) in the second. Each node in the first is connected to each node in the second. Parameters ---------- n1, n2 : integer or iterable container of nodes If integers, nodes are from `range(n1)` and `range(n1, n1 + n2)`. If a container, the elements are the nodes. create_using : NetworkX graph instance, (default: nx.Graph) Return graph of this type. Notes ----- Nodes are the integers 0 to `n1 + n2 - 1` unless either n1 or n2 are containers of nodes. If only one of n1 or n2 are integers, that integer is replaced by `range` of that integer. The nodes are assigned the attribute 'bipartite' with the value 0 or 1 to indicate which bipartite set the node belongs to. This function is not imported in the main namespace. To use it use nx.bipartite.complete_bipartite_graph rDirected Graph not supportedcg|]}|zSr).0in1s /var/www/development/aibuddy-work/election-extract/venv/lib/python3.11/site-packages/networkx/algorithms/bipartite/generators.py z,complete_bipartite_graph..<s)))Q"q&))) bipartiterz,Inputs n1 and n2 must contain distinct nodesc3*K|] }D]}||fV dSNr)ruvbottoms r z+complete_bipartite_graph..As499&99QaV9999999rzcomplete_bipartite_graph(z, )name) nx empty_graph is_directed NetworkXError isinstancenumbersIntegraladd_nodes_fromlenadd_edges_fromgraph)rn2 create_usingGtopr!s` @rr r sK: q,''A}}?=>>>GBJB"g&''*Jr7;K,L,L*))))&)))SA&&&Vq))) 1vvSCKK'''MNNN9999S999999L#c((LLc&kkLLLAGFO Hrbipartite_configuration_model)r$rrc2 tjd|tj}|rtjdt  t }t }t }||kstjd|d|t| |}t dkstdkr|Sfdt D}d|D  fdt |zD}d |D | | | fd t|Dd |_ |S) aReturns a random bipartite graph from two given degree sequences. Parameters ---------- aseq : list Degree sequence for node set A. bseq : list Degree sequence for node set B. create_using : NetworkX graph instance, optional Return graph of this type. seed : integer, random_state, or None (default) Indicator of random number generation state. See :ref:`Randomness`. The graph is composed of two partitions. Set A has nodes 0 to (len(aseq) - 1) and set B has nodes len(aseq) to (len(bseq) - 1). Nodes from set A are connected to nodes in set B by choosing randomly from the possible free stubs, one in A and one in B. Notes ----- The sum of the two sequences must be equal: sum(aseq)=sum(bseq) If no graph type is specified use MultiGraph with parallel edges. If you want a graph with no parallel edges use create_using=Graph() but then the resulting degree sequences might not be exact. The nodes are assigned the attribute 'bipartite' with the value 0 or 1 to indicate which bipartite set the node belongs to. This function is not imported in the main namespace. To use it use nx.bipartite.configuration_model rdefaultr/invalid degree sequences, sum(aseq)!=sum(bseq),,c(g|]}|g|zSrrrr aseqs rrz'configuration_model..~s# 0 0 0qaS47] 0 0 0rcg|] }|D]}| Srrrsubseqxs rrz'configuration_model..% 4 4 4FV 4 4a 4 4 4 4rc.g|]}|g|z zSrrrr bseqlenas rrz'configuration_model..s( D D DaaS4D> ! D D Drcg|] }|D]}| Srrr?s rrz'configuration_model..rBrc38K|]}||gVdSrr)rrastubsbstubss rr"z&configuration_model..s0AAfQi+AAAAAArr5) r%r& MultiGraphr'r(r-sum_add_nodes_with_bipartite_labelmaxrangeshuffler.r$) r=rEr1seedr2lenbsumasumbstubsrIrJrFs `` @@@rrrFsF q, >>>A}}?=>>> t99D t99D t99D t99D 4<< Kd K KT K K    (466A 4yyA~~Ta 1 0 0 0E$KK 0 0 0E 4 4e 4 4 4F D D D D D5td{+C+C D D DE 4 4e 4 4 4F LLLLAAAAAU4[[AAAAAA ,AF Hrbipartite_havel_hakimi_graphc tjd|tj}|rtjdt  t }t }t }||kstjd|d|t| |}t dkstdkr|Sfdt D} fdt |zD}| |r| \} } | dkrns| || dD]Q} | d } | | | | dxxd zcc<| ddkr| | R|d |_|S) aReturns a bipartite graph from two given degree sequences using a Havel-Hakimi style construction. The graph is composed of two partitions. Set A has nodes 0 to (len(aseq) - 1) and set B has nodes len(aseq) to (len(bseq) - 1). Nodes from the set A are connected to nodes in the set B by connecting the highest degree nodes in set A to the highest degree nodes in set B until all stubs are connected. Parameters ---------- aseq : list Degree sequence for node set A. bseq : list Degree sequence for node set B. create_using : NetworkX graph instance, optional Return graph of this type. Notes ----- The sum of the two sequences must be equal: sum(aseq)=sum(bseq) If no graph type is specified use MultiGraph with parallel edges. If you want a graph with no parallel edges use create_using=Graph() but then the resulting degree sequences might not be exact. The nodes are assigned the attribute 'bipartite' with the value 0 or 1 to indicate which bipartite set the node belongs to. This function is not imported in the main namespace. To use it use nx.bipartite.havel_hakimi_graph rr7rr9r:c$g|] }||g Srrr<s rrz&havel_hakimi_graph..! 1 1 1qtAwl 1 1 1rc*g|]}|z |gSrrrr rEnaseqs rrz&havel_hakimi_graph..& H H HqtAI" H H HrNrrVr%r&rKr'r(r-rLrMrNrOsortpopadd_edgeremover$)r=rEr1r2nbseqrSrTrIrJdegreertargetr r\s`` @rrrsB q, >>>A}}?=>>> IIE IIE t99D t99D 4<< Kd K KT K K    (5%88A 4yyA~~Ta2 1 1 1E%LL 1 1 1F H H H H HE%,G,G H H HF KKMMM  &jjll  Q;;  fWXX& & &Fq A JJq!    1IIINIIIayA~~ f%%%  &,AF Hrc tjd|tj}|rtjdt  t }t }t }||kstjd|d|t| |}t dkstdkr|Sfdt D} fdt |zD}| | |r|| \} } | dkrn^|d| D]Q} | d} | | | | dxxdzcc<| ddkr| | R||d |_|S) aReturns a bipartite graph from two given degree sequences using a Havel-Hakimi style construction. The graph is composed of two partitions. Set A has nodes 0 to (len(aseq) - 1) and set B has nodes len(aseq) to (len(bseq) - 1). Nodes from set A are connected to nodes in the set B by connecting the highest degree nodes in set A to the lowest degree nodes in set B until all stubs are connected. Parameters ---------- aseq : list Degree sequence for node set A. bseq : list Degree sequence for node set B. create_using : NetworkX graph instance, optional Return graph of this type. Notes ----- The sum of the two sequences must be equal: sum(aseq)=sum(bseq) If no graph type is specified use MultiGraph with parallel edges. If you want a graph with no parallel edges use create_using=Graph() but then the resulting degree sequences might not be exact. The nodes are assigned the attribute 'bipartite' with the value 0 or 1 to indicate which bipartite set the node belongs to. This function is not imported in the main namespace. To use it use nx.bipartite.reverse_havel_hakimi_graph rr7rr9r:c$g|] }||g Srrr<s rrz.reverse_havel_hakimi_graph..s! 0 0 0qtAwl 0 0 0rc*g|]}|z |gSrrrDs rrz.reverse_havel_hakimi_graph..s& D D DatAH~q! D D Drr$bipartite_reverse_havel_hakimi_graphr^)r=rEr1r2rRrSrTrIrJrdrrer rFs`` @rrrsB q, >>>A}}?=>>> t99D t99D t99D t99D 4<< Kd K KT K K    (466A 4yyA~~Ta1 0 0 0E$KK 0 0 0F D D D D D5td{+C+C D D DF KKMMM KKMMM  &jjll  Q;; QvX& & &Fq A JJq!    1IIINIIIayA~~ f%%%  &4AF Hrctjd|tj}|rtjdt t }t }t }||kstjd|d|t||}t dkstdkr|SfdtD}fdt|zD}|r,| | \} } | dkrn| |d| dz} || | dzzd } d t| | D} t | t | t | zkr'| | | D]Q}|d }|| ||dxxd zcc<|ddkr||R|,d |_|S) aReturns a bipartite graph from two given degree sequences using an alternating Havel-Hakimi style construction. The graph is composed of two partitions. Set A has nodes 0 to (len(aseq) - 1) and set B has nodes len(aseq) to (len(bseq) - 1). Nodes from the set A are connected to nodes in the set B by connecting the highest degree nodes in set A to alternatively the highest and the lowest degree nodes in set B until all stubs are connected. Parameters ---------- aseq : list Degree sequence for node set A. bseq : list Degree sequence for node set B. create_using : NetworkX graph instance, optional Return graph of this type. Notes ----- The sum of the two sequences must be equal: sum(aseq)=sum(bseq) If no graph type is specified use MultiGraph with parallel edges. If you want a graph with no parallel edges use create_using=Graph() but then the resulting degree sequences might not be exact. The nodes are assigned the attribute 'bipartite' with the value 0 or 1 to indicate which bipartite set the node belongs to. This function is not imported in the main namespace. To use it use nx.bipartite.alternating_havel_hakimi_graph rr7rr9r:c$g|] }||g Srrr<s rrz2alternating_havel_hakimi_graph..YrYrc*g|]}|z |gSrrr[s rrz2alternating_havel_hakimi_graph..Zr]rNcg|] }|D]}| Srr)rzrAs rrz2alternating_havel_hakimi_graph..cs%999qq99!9999rr(bipartite_alternating_havel_hakimi_graph)r%r&rKr'r(r-rLrMrNrOr_r`zipappendrarbr$)r=rEr1r2rcrSrTrIrJrdrsmalllargerUrer r\s`` @rr r #s]D q, >>>A}}?=>>> IIE IIE t99D t99D 4<< Kd K KT K K    (5%88A 4yyA~~Ta 1 1 1 1E%LL 1 1 1F H H H H HE%,G,G H H HF & jjll  Q;;  q6Q;'&A+-00199Cu--999 u::E SZZ/ / / LL % % % & &Fq A JJq!    1IIINIIIayA~~ f%%%! &$8AF Hrc tjd|tj rtjd|dkrtjd|dt }t |d fdt|D}|r=|dr|dd}|d|| |kst |kr=t } |d ||n| fd t|t D}td |} | | } |d |||d||d|=d _ S) a^Create a bipartite graph with a preferential attachment model from a given single degree sequence. The graph is composed of two partitions. Set A has nodes 0 to (len(aseq) - 1) and set B has nodes starting with node len(aseq). The number of nodes in set B is random. Parameters ---------- aseq : list Degree sequence for node set A. p : float Probability that a new bottom node is added. create_using : NetworkX graph instance, optional Return graph of this type. seed : integer, random_state, or None (default) Indicator of random number generation state. See :ref:`Randomness`. References ---------- .. [1] Guillaume, J.L. and Latapy, M., Bipartite graphs as models of complex networks. Physica A: Statistical Mechanics and its Applications, 2006, 371(2), pp.795-813. .. [2] Jean-Loup Guillaume and Matthieu Latapy, Bipartite structure of all complex networks, Inf. Process. Lett. 90, 2004, pg. 215-221 https://doi.org/10.1016/j.ipl.2004.03.007 Notes ----- The nodes are assigned the attribute 'bipartite' with the value 0 or 1 to indicate which bipartite set the node belongs to. This function is not imported in the main namespace. To use it use nx.bipartite.preferential_attachment_graph rr7rrz probability z > 1c(g|]}|g|zSrrr<s rrz1preferential_attachment_graph..s# . . .A1#Q- . . .rrcBg|]}|g|zSr)rd)rbr2s rrz1preferential_attachment_graph..s*FFFAqcAHHQKK'FFFrc ||zSrr)rAys rz/preferential_attachment_graph..s a!er'bipartite_preferential_attachment_model)r%r&rKr'r(r-rMrOrbrandomadd_noderarchoicer$) r=pr1rQr\vvsourcerebbbbstubsr2s ` @rr r qsR q, >>>A}}?=>>>1uu5a555666 IIE'5!44A . . . .u . . .B e +U1XF qELL {{}}q  CFFeOOQ 6Q /// 66****FFFFuc!ff1E1EFFF !3!3R88W-- 6Q /// 66***e + "Q%! "7AF HrFc\tj}t|||}|rtj|}d|d|d|d|_|dkr|S|dkrtj||St jd|z }d}d}||krt jd|z } |dzt| |z z}||kr||kr||z }|dz}||kr||k||kr| |||z||k|rd}d}||krt jd|z } |dzt| |z z}||kr||kr||z }|dz}||kr||k||kr| ||z|||k|S)uoReturns a bipartite random graph. This is a bipartite version of the binomial (Erdős-Rényi) graph. The graph is composed of two partitions. Set A has nodes 0 to (n - 1) and set B has nodes n to (n + m - 1). Parameters ---------- n : int The number of nodes in the first bipartite set. m : int The number of nodes in the second bipartite set. p : float Probability for edge creation. seed : integer, random_state, or None (default) Indicator of random number generation state. See :ref:`Randomness`. directed : bool, optional (default=False) If True return a directed graph Notes ----- The bipartite random graph algorithm chooses each of the n*m (undirected) or 2*nm (directed) possible edges with probability p. This algorithm is $O(n+m)$ where $m$ is the expected number of edges. The nodes are assigned the attribute 'bipartite' with the value 0 or 1 to indicate which bipartite set the node belongs to. This function is not imported in the main namespace. To use it use nx.bipartite.random_graph See Also -------- gnp_random_graph, configuration_model References ---------- .. [1] Vladimir Batagelj and Ulrik Brandes, "Efficient generation of large random networks", Phys. Rev. E, 71, 036113, 2005. zfast_gnp_random_graph(r:r#rrg?) r%GraphrMDiGraphr$r mathlogr}intra) nmrrQdirectedr2lpr wlrs rr r s\  A'1a00A JqMM 2a 2 2! 2 2a 2 2 2AFAvvAvv*1a000 #'  B A A a%% XcDKKMM) * * ECRLL 1ffQAAAA1ffQ q55 JJq!a%  a%% %  !ee# -..BABG $Aq&&QUUEEq&&QUU1uu 1q5!$$$!ee HrcPtj}t|||}|rtj|}d|d|d|d|_|dks|dkr|S||z}||krtj|||Sd|dD}tt|t|z }d } | |krV| |} | |} | || vr;| | | | dz } | |kV|S) aReturns a random bipartite graph G_{n,m,k}. Produces a bipartite graph chosen randomly out of the set of all graphs with n top nodes, m bottom nodes, and k edges. The graph is composed of two sets of nodes. Set A has nodes 0 to (n - 1) and set B has nodes n to (n + m - 1). Parameters ---------- n : int The number of nodes in the first bipartite set. m : int The number of nodes in the second bipartite set. k : int The number of edges seed : integer, random_state, or None (default) Indicator of random number generation state. See :ref:`Randomness`. directed : bool, optional (default=False) If True return a directed graph Examples -------- >>> G = nx.bipartite.gnmk_random_graph(10, 20, 50) See Also -------- gnm_random_graph Notes ----- If k > m * n then a complete bipartite graph is returned. This graph is a bipartite version of the `G_{nm}` random graph model. The nodes are assigned the attribute 'bipartite' with the value 0 or 1 to indicate which bipartite set the node belongs to. This function is not imported in the main namespace. To use it use nx.bipartite.gnmk_random_graph zbipartite_gnm_random_graph(r:r#r)r1c0g|]\}}|ddk|S)rrr)rrds rrz%gnmk_random_graph..Gs* C C CAq~/B/B1/B/B/BrT)datar) r%rrMrr$r nodeslistsetrra) rrkrQrr2 max_edgesr3r! edge_countrr s rr r sFX  A'1a00A JqMM 71 7 7q 7 71 7 7 7AFAvvaAII~~*1aa@@@@ C Cd++ C C CC #a&&3s88# $ $FJ q.. KK   KK   !99  JJq!    !OJ q.. Hrc b|t||zttt|dg|z}|ttt|||zdg|zt j||d|S)Nrrr)r,rOdictrqupdater%set_node_attributes)r2rFrRrxs rrMrMVsU4$;''((( StqcDj ) )**AHHT#eD$+..d ;; < <===1a--- Hrr)NN)NF)__doc__rr* functoolsrnetworkxr%networkx.utilsrr__all__ _dispatchabler rrrr r r r rMrrrrs ;;;;;;;;   T222!Q) ) ) 32) X6tSWXXXC C C YXC L5dRVWWWG G G XWG TT222F F F 32F RT222J J J 32J ZT222C C C 32C LT222R R R 32R jT222A A A 32A H     r