o ]ZhO@s<dZddlZddlZddlmZddlZddlmZm Z gdZ ej dddeddgd d d Z e d ej d ddd d!ddZ ej dddd d ddZej dddd ddZej dddd ddZe d ej dddd!ddZe d ej dddd"ddZe d ej dddd"ddZddZdS)#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_graphcstd|}|rtd\}|\}ttjr,t|tjr,fddD|j|dd|jddt|t|tkrKtd| fdd |Dd t|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 supportedcsg|]}|qSr.0i)n1rW/var/www/auris/lib/python3.10/site-packages/networkx/algorithms/bipartite/generators.py <sz,complete_bipartite_graph.. bipartiterz,Inputs n1 and n2 must contain distinct nodesc3s"|] }D]}||fVqqdSNr)ruv)bottomrr As z+complete_bipartite_graph..zcomplete_bipartite_graph(z, )name) nx empty_graph is_directed NetworkXError isinstancenumbersIntegraladd_nodes_fromlenadd_edges_fromgraph)rZn2 create_usingGtopr)rrrr s    r bipartite_configuration_model)r r rc stjd|tjd}|rtdtt}t}t}||ks1td|d|t||}tdksCtdkrE|Sfddt D}dd|Dfd dt |D}d d|D| | | fd d 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),,cg|] }|g|qSrrrraseqrrr~z'configuration_model..cSg|] }|D]}|qqSrrrZsubseqxrrrrr9csg|] }|g|qSrrr6bseqlenarrrscSr:rrr;rrrrr9c3s |] }||gVqdSrrr)astubsbstubsrrrsz&configuration_model..r0) r!r" MultiGraphr#r$r)sum_add_nodes_with_bipartite_labelmaxrangeshuffler*r ) r8r>r,seedr-lenbsumasumbstubsr)r8r@r>rAr?rrFs.#    rbipartite_havel_hakimi_graphc sDtjd|tjd}|rtdtt}t}t}||ks1td|d|t||}tdksCtdkrE|Sfddt D}fddt |D}| |r| \} } | dkrpn-| || d D]} | d } | | | | dd 8<| ddkr| | q{|sed |_|S) aReturns a bipartite graph from two given degree sequences using a Havel-Hakimi style construction. The graph is composed of two partitions. Set A has nodes 0 to (len(aseq) - 1) and set B has nodes len(aseq) to (len(bseq) - 1). Nodes from the set A are connected to nodes in the set B by connecting the highest degree nodes in set A to the highest degree nodes in set B until all stubs are connected. Parameters ---------- aseq : list Degree sequence for node set A. bseq : list Degree sequence for node set B. create_using : NetworkX graph instance, optional Return graph of this type. Notes ----- The sum of the two sequences must be equal: sum(aseq)=sum(bseq) If no graph type is specified use MultiGraph with parallel edges. If you want a graph with no parallel edges use create_using=Graph() but then the resulting degree sequences might not be exact. The nodes are assigned the attribute 'bipartite' with the value 0 or 1 to indicate which bipartite set the node belongs to. This function is not imported in the main namespace. To use it use nx.bipartite.havel_hakimi_graph rr1rr3r4cg|]}||gqSrrr6r7rrrz&havel_hakimi_graph..cg|] }||gqSrrr6r>naseqrrrNrrMr!r"rBr#r$r)rCrDrErFsortpopadd_edgeremover ) r8r>r,r-nbseqrJrKr@rAdegreertargetrrr8r>rRrrs@!       rc sBtjd|tjd}|rtdtt}t}t}||ks1td|d|t||}tdksCtdkrE|Sfddt D}fddt |D}| | |r| \} } | dkrtn(|d| D]} | d } | | | | dd 8<| ddkr| | qz|sid |_|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 rr1rr3r4crNrrr6r7rrrrOz.reverse_havel_hakimi_graph..crPrrr6r=rrrrSrZ$bipartite_reverse_havel_hakimi_graphrT) r8r>r,r-rIrJrKr@rArZrr[rr)r8r>r?rrs@!       rcstjd|tjd}|rtdtt}t}t}||ks1td|d|t||}tdksCtdkrE|Sfddt D}fddt |D}|r| | \} } | dkrpnX| |d| d } || | d d } d dt | | D} t| t| t| kr| | | D]}|d }|| ||dd 8<|ddkr||q|sad |_|S)aReturns a bipartite graph from two given degree sequences using an alternating Havel-Hakimi style construction. The graph is composed of two partitions. Set A has nodes 0 to (len(aseq) - 1) and set B has nodes len(aseq) to (len(bseq) - 1). Nodes from the set A are connected to nodes in the set B by connecting the highest degree nodes in set A to alternatively the highest and the lowest degree nodes in set B until all stubs are connected. Parameters ---------- aseq : list Degree sequence for node set A. bseq : list Degree sequence for node set B. create_using : NetworkX graph instance, optional Return graph of this type. Notes ----- The sum of the two sequences must be equal: sum(aseq)=sum(bseq) If no graph type is specified use MultiGraph with parallel edges. If you want a graph with no parallel edges use create_using=Graph() but then the resulting degree sequences might not be exact. The nodes are assigned the attribute 'bipartite' with the value 0 or 1 to indicate which bipartite set the node belongs to. This function is not imported in the main namespace. To use it use nx.bipartite.alternating_havel_hakimi_graph rr1rr3r4crNrrr6r7rrrYrOz2alternating_havel_hakimi_graph..crPrrr6rQrrrZrSNcSr:rr)rzr<rrrrcr9rZ(bipartite_alternating_havel_hakimi_graph)r!r"rBr#r$r)rCrDrErFrUrVzipappendrWrXr )r8r>r,r-rYrJrKr@rArZrZsmallZlargerLr[rrr\rr#sJ"      rc s<tjd|tjdrtd|dkrtd|dt}t|dfddt|D}|r|dr|dd}|d|| |ksSt|kret}j |dd  ||n'fd dt|tD}t d d |} | | }j |dd  |||ds:||d|s6d _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 rr1rrz probability z > 1cr5rrr6r7rrrr9z1preferential_attachment_graph..rcsg|] }|g|qSr)rZ)rb)r-rrrrScSs||Srr)r<yrrrsz/preferential_attachment_graph..Z'bipartite_preferential_attachment_model)r!r"rBr#r$r)rDrFrXrandomadd_noderWrchoicer ) r8pr,rHrRvvsourcer[ZbbZbbstubsr)r-r8rr qs4)     r Fc Cs~t}t|||}|rt|}d|d|d|d|_|dkr$|S|dkr.t||Std|}d}d}||krxtd|} |dt | |}||krh||krh||}|d}||krh||ksX||krt| |||||ks=|rd}d}||krtd|} |dt | |}||kr||kr||}|d}||kr||ks||kr| |||||ks|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(r4rrrg?) r!GraphrDDiGraphr r mathlogrdintrW) nmrgrHdirectedr-Zlprwlrrrrr sH.     r c Cst}t|||}|rt|}d|d|d|d|_|dks&|dkr(|S||}||kr8tj|||dSdd|jdd D}tt|t|}d } | |krr| |} | |} | || vrdqO| | | | d7} | |ksS|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 -------- from nx.algorithms import bipartite G = 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(r4rr)r,cSs g|] \}}|ddkr|qS)rrr)rrpdrrrrHs z%gnmk_random_graph..T)datar) r!rkrDrlr r nodeslistsetrfrW) rprqkrHrrr-Z max_edgesr.rZ edge_countrrrrrr s,-       r cCs`|t||ttt|dg|}|ttt|||dg|t||d|S)Nrrr)r(rFdictr_updater!Zset_node_attributes)r-r?rIrarrrrDWs $rDr)NN)NF)__doc__rmr& functoolsrZnetworkxr!Znetworkx.utilsrr__all__Z _dispatchabler rrrrr r r rDrrrrs:  ,F  J  I M F U  E