ó |£*^c@sÍdZddlZddlZdjdddgƒZddd d d d d gZd„Zde d„Z d„Z d„Z dd„Z dd„Zddd„Zde d„Zdd„Zdd„ZdS(sÝFunctions to convert NetworkX graphs to and from other formats. The preferred way of converting data to a NetworkX graph is through the graph constuctor. The constructor calls the to_networkx_graph() function which attempts to guess the input type and convert it automatically. Examples -------- Create a graph with a single edge from a dictionary of dictionaries >>> d={0: {1: 1}} # dict-of-dicts single edge (0,1) >>> G=nx.Graph(d) See Also -------- nx_agraph, nx_pydot iÿÿÿÿNs s%Aric Hagberg sPieter Swart (swart@lanl.gov)sDan Schult(dschult@colgate.edu)tto_networkx_graphtfrom_dict_of_dictstto_dict_of_dictstfrom_dict_of_liststto_dict_of_listst from_edgelistt to_edgelistcCs>|dkrtjƒSy|jƒWntdƒ‚nX|S(sReturn a graph object ready to be populated. If create_using is None return the default (just networkx.Graph()) If create_using.clear() works, assume it returns a graph object. Otherwise raise an exception because create_using is not a networkx graph. s(Input graph is not a networkx graph typeN(tNonetnxtGraphtcleart TypeError(t create_using((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pyt_prep_create_using"s  cCszt|dƒrÐy¥t|jd|d|jƒƒ}t|dƒrit|jtƒri|jjƒ|_nt|dƒr¯t|jtƒr¯td„|jj ƒDƒƒ|_n|SWqÐt j dƒ‚qÐXnt|dƒryt j j |d|ƒSWqt j d ƒ‚qXnt|tƒruyt|d|d|ƒSWquyt|d|ƒSWqrtd ƒ‚qrXquXnt|tƒs±t|tƒs±t|d ƒs±t|d ƒráyt|d|ƒSWqát j d ƒ‚qáXny[ddl}t||jƒr;yt j|d|ƒSWq;d}t j |ƒ‚q;XnWn'tk red}tj|tƒnXygddl}t||jƒs™t||jƒrÌyt j|d|ƒSWqÌt j dƒ‚qÌXnWn!tk rðtjdtƒnXyRddl}t|dƒrByt j|d|ƒSWqBt j dƒ‚qBXnWn!tk rftjdtƒnXt j dƒ‚dS(s¿Make a NetworkX graph from a known data structure. The preferred way to call this is automatically from the class constructor >>> d={0: {1: {'weight':1}}} # dict-of-dicts single edge (0,1) >>> G=nx.Graph(d) instead of the equivalent >>> G=nx.from_dict_of_dicts(d) Parameters ---------- data : a object to be converted Current known types are: any NetworkX graph dict-of-dicts dist-of-lists list of edges numpy matrix numpy ndarray scipy sparse matrix pygraphviz agraph create_using : NetworkX graph Use specified graph for result. Otherwise a new graph is created. multigraph_input : bool (default False) If True and data is a dict_of_dicts, try to create a multigraph assuming dict_of_dict_of_lists. If data and create_using are both multigraphs then create a multigraph from a multigraph. tadjR tmultigraph_inputtgraphtnodecss'|]\}}||jƒfVqdS(N(tcopy(t.0tntdd((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pys _ss&Input is not a correct NetworkX graph.t is_stricts(Input is not a correct pygraphviz graph.sInput is not known type.tnextt__next__sInput is not a valid edge listiÿÿÿÿNs(Input is not a correct Pandas DataFrame.s+pandas not found, skipping conversion test.s-Input is not a correct numpy matrix or array.s*numpy not found, skipping conversion test.tformats0Input is not a correct scipy sparse matrix type.s*scipy not found, skipping conversion test.s.Input is not a known data type for conversion.( thasattrRRt is_multigrapht isinstanceRtdictRRtitemsRt NetworkXErrort nx_agrapht from_agraphRR tlistttupleRtpandast DataFrametfrom_pandas_dataframet ImportErrortwarningstwarnt ImportWarningtnumpytmatrixtndarraytfrom_numpy_matrixtscipytfrom_scipy_sparse_matrix(tdataR RtresulttpdtmsgR+R/((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pyR2sŽ% !!%            cCs |jƒS(s6Return a new undirected representation of the graph G.(t to_undirected(tG((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pytconvert_to_undirected¯scCs |jƒS(s4Return a new directed representation of the graph G.(t to_directed(R6((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pytconvert_to_directed´scCsb|dkr|}ni}x@|D]8}g|j|ƒD]}||kr8|^q8||>> dol= {0:[1]} # single edge (0,1) >>> G=nx.from_dict_of_lists(dol) or >>> G=nx.Graph(dol) # use Graph constructor icss.|]$\}}|D]}||fVqqdS(N((RRtnbrlistR=((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pys òs (R tadd_nodes_fromRt is_directedRtadd_edgetadd_edges_from(R<R R6tseenRR>R=((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pyRÑs    cs?i}ˆdkr„|dkrNx`|jƒD]\}}|jƒ||sc3s!|]}|ˆkr|VqdS(N((RRD(R;(sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pys sN(Rtadjacency_iterRtfromkeysR(R6R;t edge_datatdodtutnbrdictRDR1((R;sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pyR÷s"     -  !csit|ƒ}|j|ƒ|r«|jƒrw|jƒrW|jd„|jƒDƒƒq¨|jd„|jƒDƒƒqe|jƒrtƒ}x|jƒD]w\‰}xh|jƒD]Z\‰}ˆˆf|kr²|j‡‡fd†|jƒDƒƒ|jˆˆfƒq²q²Wq™Wqetƒ}xB|jƒD]w\‰}xh|jƒD]Z\‰}ˆˆf|krF|j‡‡fd†|jƒDƒƒ|jˆˆfƒqFqFWq-Wnº|jƒrH|jƒ rHtƒ}x•|jƒD]g\‰}xX|jƒD]J\‰}ˆˆf|kr*|jˆˆd|ƒn|jˆˆfƒqóWqÚWn|jd„|jƒDƒƒ|S(s·Return a graph from a dictionary of dictionaries. Parameters ---------- d : dictionary of dictionaries A dictionary of dictionaries adjacency representation. create_using : NetworkX graph Use specified graph for result. Otherwise a new graph is created. multigraph_input : bool (default False) When True, the values of the inner dict are assumed to be containers of edge data for multiple edges. Otherwise this routine assumes the edge data are singletons. Examples -------- >>> dod= {0: {1:{'weight':1}}} # single edge (0,1) >>> G=nx.from_dict_of_dicts(dod) or >>> G=nx.Graph(dod) # use Graph constructor cssY|]O\}}|jƒD]6\}}|jƒD]\}}||||fVq/qqdS(N(R(RRItnbrsRDtdatadicttkeyR1((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pys >s cssV|]L\}}|jƒD]3\}}|jƒD]\}}|||fVq/qqdS(N(R(RRIRKRDRLRMR1((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pys Ds c3s'|]\}}ˆˆ||fVqdS(N((RRMR1(RIRD(sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pys Osc3s$|]\}}ˆˆ|fVqdS(N((RRMR1(RIRD(sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pys Xst attr_dictcss=|]3\}}|jƒD]\}}|||fVqqdS(N(R(RRIRKRDR1((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pys hs ( R R?R@RRBRtsettaddRA(R<R RR6RCRKRLR1((RIRDsd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pyRsD        ! !  cCs3|dkr|jdtƒS|j|dtƒSdS(s°Return a list of edges in the graph. Parameters ---------- G : graph A NetworkX graph nodelist : list Use only nodes specified in nodelist R1N(RtedgestTrue(R6R;((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pyRms cCst|ƒ}|j|ƒ|S(s“Return a graph from a list of edges. Parameters ---------- edgelist : list or iterator Edge tuples create_using : NetworkX graph Use specified graph for result. Otherwise a new graph is created. Examples -------- >>> edgelist= [(0,1)] # single edge (0,1) >>> G=nx.from_edgelist(edgelist) or >>> G=nx.Graph(edgelist) # use Graph constructor (R RB(tedgelistR R6((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pyR~s  (t__doc__R(tnetworkxRtjoint __author__t__all__R RtFalseRR7R9RRRRRR(((sd/home/gitlab-runner/builds/8480fa44/0/bergerc/fluidmanager-web/art-framework/bin/networkx/convert.pyts&      }    &'O