3 dP4@sdZddlZddlZddlmZmZmZdddddd d gZdd dZ dd dZ dddZ dddZ dddZ ddd Zddd ZdS)aFunctions to convert NetworkX graphs to and from other formats. The preferred way of converting data to a NetworkX graph is through the graph constructor. 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 N) Collection GeneratorIteratorto_networkx_graphfrom_dict_of_dictsto_dict_of_dictsfrom_dict_of_liststo_dict_of_lists from_edgelist to_edgelistFc |Cst|drybt|j||jd}t|dr8|jj|jt|drjx&|jjD]\}}|j|j|qNW|St k r}zt j d|WYdd}~XnXt|dryt j j ||dSt k r}zt j d |WYdd}~XnXt|trJyt|||dSy t||dSt k rB}ztd |WYdd}~XnXYnXyd dl}t||jr|jd |jd kryt j||dSt k r}zd }t j ||WYdd}~XnXnFyt j|d|dSt k r}zd}t j ||WYdd}~XnXWn&tk r,d}tj|tYnXy`d dl} t|| j| jfryt j||dSt k r}zt j d|WYdd}~XnXWn"tk rtjdtYnXyXd dl} t|dryt j ||dSt k r}zt j d|WYdd}~XnXWn"tk r,tjdtYnXt|t!t"t#fr~y t$||dSt k r|}zt j d|WYdd}~XnXt j ddS)aMake 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 : object to be converted Current known types are: any NetworkX graph dict-of-dicts dict-of-lists container (e.g. set, list, tuple) of edges iterator (e.g. itertools.chain) that produces edges generator of edges Pandas DataFrame (row per edge) numpy matrix numpy ndarray scipy sparse matrix pygraphviz agraph create_using : NetworkX graph constructor, optional (default=nx.Graph) Graph type to create. If graph instance, then cleared before populated. 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. adj) create_usingmultigraph_inputgraphnodesz&Input is not a correct NetworkX graph.NZ is_strict)r z(Input is not a correct pygraphviz graph.zInput is not known type.rz9Input is not a correct Pandas DataFrame adjacency matrix.T)Z edge_attrr z2Input is not a correct Pandas DataFrame edge-list.z+pandas not found, skipping conversion test.z-Input is not a correct numpy matrix or array.z*numpy not found, skipping conversion test.formatz0Input is not a correct scipy sparse matrix type.z*scipy not found, skipping conversion test.zInput is not a valid edge listz.Input is not a known data type for conversion.)%hasattrrr is_multigraphrupdateritems_node ExceptionnxZ NetworkXErrorZ nx_agraphZ from_agraph isinstancedictr TypeErrorZpandasZ DataFrameshapeZfrom_pandas_adjacencyZfrom_pandas_edgelist ImportErrorwarningswarn ImportWarningnumpyZmatrixZndarrayZfrom_numpy_matrixscipyZfrom_scipy_sparse_matrixrrrr ) datar rresultnddepdmsgr"r#r+4/tmp/pip-build-7vycvbft/networkx/networkx/convert.pyr!s)        "  "  cs>dkr |i}x(D] }fdd|j|D||<qW|S)a&Returns adjacency representation of graph as a dictionary of lists. Parameters ---------- G : graph A NetworkX graph nodelist : list Use only nodes specified in nodelist Notes ----- Completely ignores edge data for MultiGraph and MultiDiGraph. Ncsg|]}|kr|qSr+r+).0nbr)nodelistr+r, sz$to_dict_of_lists..)Z neighbors)Gr/dr&r+)r/r,r s   cCstjd|}|j||jrn|j rni}xX|jD]2\}}x |D]}||krD|j||qDWd||<q6Wn|jdd|jD|S)aReturns a graph from a dictionary of lists. Parameters ---------- d : dictionary of lists A dictionary of lists adjacency representation. create_using : NetworkX graph constructor, optional (default=nx.Graph) Graph type to create. If graph instance, then cleared before populated. Examples -------- >>> dol = {0: [1]} # single edge (0,1) >>> G = nx.from_dict_of_lists(dol) or >>> G = nx.Graph(dol) # use Graph constructor rrcss$|]\}}|D]}||fVqqdS)Nr+)r-nodenbrlistr.r+r+r, sz%from_dict_of_lists..)r empty_graphadd_nodes_fromr is_directedradd_edgeadd_edges_from)r2r r1seenr3r4r.r+r+r,rs   csi}dkr`|dkr8xH|jD]\}}|j||<qWqx|jD]\}}|j||||<qBWn|dkrxD]@}i||<x2fdd||jDD]\}}||||<qWqnWnBx@D]8}i||<x*fdd||DD]}||||<qWqW|S)aHReturns adjacency representation of graph as a dictionary of dictionaries. Parameters ---------- G : graph A NetworkX graph nodelist : list Use only nodes specified in nodelist edge_data : list, optional If provided, the value of the dictionary will be set to edge_data for all edges. This is useful to make an adjacency matrix type representation with 1 as the edge data. If edgedata is None, the edgedata in G is used to fill the values. If G is a multigraph, the edgedata is a dict for each pair (u,v). Nc3s"|]\}}|kr||fVqdS)Nr+)r-vr$)r/r+r,r5sz#to_dict_of_dicts..c3s|]}|kr|VqdS)Nr+)r-r<)r/r+r,r5s)Z adjacencycopyfromkeysr)r1r/Z edge_dataZdoduZnbrdictr<r$r+)r/r,rs" $ cstjd|}|j||r@|jr`|jrF|jdd|jDn|jdd|jDn|jrt}x|jD]V\}xL|jD]@\}f|kr|jfdd|jD|jfqWqxWnjt}xb|jD]V\}xL|jD]@\}f|kr|jfdd|jD|jfqWqWn|jr|j rt}x|jD]d\}xX|jD]L\}f|kr|j dd|dj ||jfqxWqfWn|jdd|jD|S) aReturns a graph from a dictionary of dictionaries. Parameters ---------- d : dictionary of dictionaries A dictionary of dictionaries adjacency representation. create_using : NetworkX graph constructor, optional (default=nx.Graph) Graph type to create. If graph instance, then cleared before populated. 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 rcssB|]:\}}|jD](\}}|jD]\}}||||fVq"qqdS)N)r)r-r?nbrsr<datadictkeyr$r+r+r,r5;sz%from_dict_of_dicts..css@|]8\}}|jD]&\}}|jD]\}}|||fVq"qqdS)N)r)r-r?r@r<rArBr$r+r+r,r5Bsc3s|]\}}||fVqdS)Nr+)r-rBr$)r?r<r+r,r5Nsc3s|]\}}|fVqdS)Nr+)r-rBr$)r?r<r+r,r5Ws)rBcss.|]&\}}|jD]\}}|||fVqqdS)N)r)r-r?r@r<r$r+r+r,r5is) rr6r7r8rr:rsetaddr9r)r2r rr1r;r@rAr$r+)r?r<r,rsJ    cCs"|dkr|jddS|j|ddS)zReturns a list of edges in the graph. Parameters ---------- G : graph A NetworkX graph nodelist : list Use only nodes specified in nodelist NT)r$)edges)r1r/r+r+r,r ns  cCstjd|}|j||S)aReturns a graph from a list of edges. Parameters ---------- edgelist : list or iterator Edge tuples create_using : NetworkX graph constructor, optional (default=nx.Graph) Graph type to create. If graph instance, then cleared before populated. Examples -------- >>> edgelist = [(0, 1)] # single edge (0,1) >>> G = nx.from_edgelist(edgelist) or >>> G = nx.Graph(edgelist) # use Graph constructor r)rr6r:)Zedgelistr r1r+r+r,r s  )NF)N)N)NN)NF)N)N)__doc__rZnetworkxrcollections.abcrrr__all__rr rrrr r r+r+r+r,s$   ( ( U