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ddœd„«       «       Zej                  j                  d«      ej                  j                  d«       ej
                  dddii¬«      ddœd„«       «       «       Zej                  j                  j                  d	«       ej
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ddœd„«       «       Zy)z3Provides explicit constructions of expander graphs.é    N)Úmargulis_gabber_galil_graphÚchordal_cycle_graphÚpaley_graphÚmaybe_regular_expanderÚis_regular_expanderÚrandom_regular_expander_graphT)ÚgraphsÚreturns_graphc                 óâ  — t        j                  d|t         j                  ¬«      }|j                  «       s|j	                  «       sd}t        j
                  |«      ‚t        j                  t        | «      d¬«      D ][  \  }}|d|z  z   | z  |f|d|z  dz   z   | z  |f||d|z  z   | z  f||d|z  dz   z   | z  ffD ]  \  }}|j                  ||f||f«       Œ Œ] d| › d�|j                  d	<   |S )
aÐ  Returns the Margulis-Gabber-Galil undirected MultiGraph on `n^2` nodes.

    The undirected MultiGraph is regular with degree `8`. Nodes are integer
    pairs. The second-largest eigenvalue of the adjacency matrix of the graph
    is at most `5 \sqrt{2}`, regardless of `n`.

    Parameters
    ----------
    n : int
        Determines the number of nodes in the graph: `n^2`.
    create_using : NetworkX graph constructor, optional (default MultiGraph)
       Graph type to create. If graph instance, then cleared before populated.

    Returns
    -------
    G : graph
        The constructed undirected multigraph.

    Raises
    ------
    NetworkXError
        If the graph is directed or not a multigraph.

    r   ©Údefaultú0`create_using` must be an undirected multigraph.é   )Úrepeaté   zmargulis_gabber_galil_graph(ú)Úname)ÚnxÚempty_graphÚ
MultiGraphÚis_directedÚis_multigraphÚNetworkXErrorÚ	itertoolsÚproductÚrangeÚadd_edgeÚgraph)ÚnÚcreate_usingÚGÚmsgÚxÚyÚuÚvs           ú[/var/www/skyplay_api_hub/venv/lib/python3.12/site-packages/networkx/generators/expanders.pyr   r   1   s
  € ô4 	�‰�q˜,´·±Ô>€AØ‡}�}„˜aŸo™oÔ/Ø@ˆÜ×Ñ˜sÓ#Ð#ä×!Ñ!¤%¨£(°1Ô5ò '‰ˆˆ1à�!�a‘%‰i˜1‰_˜aÐ Ø�1�q‘5˜1‘9‰o Ñ" AÐ&Ø��Q˜‘U‘˜a‘Ð Ø��a˜!‘e˜a‘i‘ AÑ%Ð&ð	
ò 	'‰DˆAˆqð �J‰J˜˜1�v  1˜vÕ&ñ	'ð'ð 5°Q°C°qÐ9€A‡G�GˆF�OØ€Hó    c                 óŒ  — t        j                  d|t         j                  ¬«      }|j                  «       s|j	                  «       sd}t        j
                  |«      ‚t        | «      D ]E  }|dz
  | z  }|dz   | z  }|dkD  rt        || dz
  | «      nd}|||fD ]  }|j                  ||«       Œ ŒG d| › d�|j                  d<   |S )	u  Returns the chordal cycle graph on `p` nodes.

    The returned graph is a cycle graph on `p` nodes with chords joining each
    vertex `x` to its inverse modulo `p`. This graph is a (mildly explicit)
    3-regular expander [1]_.

    `p` *must* be a prime number.

    Parameters
    ----------
    p : a prime number

        The number of vertices in the graph. This also indicates where the
        chordal edges in the cycle will be created.

    create_using : NetworkX graph constructor, optional (default=nx.Graph)
       Graph type to create. If graph instance, then cleared before populated.

    Returns
    -------
    G : graph
        The constructed undirected multigraph.

    Raises
    ------
    NetworkXError

        If `create_using` indicates directed or not a multigraph.

    References
    ----------

    .. [1] Theorem 4.4.2 in A. Lubotzky. "Discrete groups, expanding graphs and
           invariant measures", volume 125 of Progress in Mathematics.
           BirkhÃ¤user Verlag, Basel, 1994.

    r   r   r   r   r   zchordal_cycle_graph(r   r   )
r   r   r   r   r   r   r   Úpowr   r   )	Úpr    r!   r"   r#   ÚleftÚrightÚchordr$   s	            r'   r   r   \   sÍ   € ôN 	�‰�q˜,´·±Ô>€AØ‡}�}„˜aŸo™oÔ/Ø@ˆÜ×Ñ˜sÓ#Ð#ä�1‹Xò ˆØ�A‘˜‰{ˆØ�Q‘˜!‘ˆð %&¨¢E”�A�q˜1‘u˜aÔ ¨qˆØ˜˜uÐ%ò 	ˆAØ�J‰J�q˜!Õñ	ðð  -¨Q¨C¨qÐ1€A‡G�GˆF�OØ€Hr(   c                 ó„  — t        j                  d|t         j                  ¬«      }|j                  «       rd}t        j                  |«      ‚t        d| «      D �ch c]  }|dz  | z  dk7  sŒ|dz  | z  ’Œ }}t        | «      D ]!  }|D ]  }|j                  |||z   | z  «       Œ Œ# d| › d�|j                  d<   |S c c}w )	a%  Returns the Paley $\frac{(p-1)}{2}$ -regular graph on $p$ nodes.

    The returned graph is a graph on $\mathbb{Z}/p\mathbb{Z}$ with edges between $x$ and $y$
    if and only if $x-y$ is a nonzero square in $\mathbb{Z}/p\mathbb{Z}$.

    If $p \equiv 1  \pmod 4$, $-1$ is a square in $\mathbb{Z}/p\mathbb{Z}$ and therefore $x-y$ is a square if and
    only if $y-x$ is also a square, i.e the edges in the Paley graph are symmetric.

    If $p \equiv 3 \pmod 4$, $-1$ is not a square in $\mathbb{Z}/p\mathbb{Z}$ and therefore either $x-y$ or $y-x$
    is a square in $\mathbb{Z}/p\mathbb{Z}$ but not both.

    Note that a more general definition of Paley graphs extends this construction
    to graphs over $q=p^n$ vertices, by using the finite field $F_q$ instead of $\mathbb{Z}/p\mathbb{Z}$.
    This construction requires to compute squares in general finite fields and is
    not what is implemented here (i.e `paley_graph(25)` does not return the true
    Paley graph associated with $5^2$).

    Parameters
    ----------
    p : int, an odd prime number.

    create_using : NetworkX graph constructor, optional (default=nx.Graph)
       Graph type to create. If graph instance, then cleared before populated.

    Returns
    -------
    G : graph
        The constructed directed graph.

    Raises
    ------
    NetworkXError
        If the graph is a multigraph.

    References
    ----------
    Chapter 13 in B. Bollobas, Random Graphs. Second edition.
    Cambridge Studies in Advanced Mathematics, 73.
    Cambridge University Press, Cambridge (2001).
    r   r   z&`create_using` cannot be a multigraph.r   r   zpaley(r   r   )r   r   ÚDiGraphr   r   r   r   r   )r+   r    r!   r"   r#   Ú
square_setÚx2s          r'   r   r   œ   sÆ   € ôT 	�‰�q˜,´·
±
Ô;€AØ‡�ÔØ6ˆÜ×Ñ˜sÓ#Ð#ô
 ',¨A¨q£kÖE °a¸±d¸a±ZÀ1³_�1�a‘4˜1“*ÐE€JÐEä�1‹Xò (ˆØò 	(ˆBØ�J‰J�q˜1˜r™6 Q™,Õ'ñ	(ð(ð ˜q˜c �m€A‡G�GˆF�OØ€Hùò Fs   ÁB=Á-
B=Úseedéd   ©r    Ú	max_triesr3   c                óˆ  — ddl }| dk  rt        j                  d«      ‚|dk\  st        j                  d«      ‚|dz  dk(  st        j                  d«      ‚| dz
  |k\  st        j                  d|dz  › d	| › d
�«      ‚t        j                  | |«      }| dk  r|S g }t	        «       }t        |dz  «      D ]ô  }	|}
t        |«      |	dz   | z  k7  sŒ|
dz  }
|j                  | dz
  «      j                  «       }|j                  | dz
  «       t        j                  j                  |d¬«      D ��ch c]  \  }}||f|vr
||f|vr||f’Œ }}}t        |«      | k(  r"|j                  |«       |j                  |«       |
dk(  rt        j                  d«      ‚t        |«      |	dz   | z  k7  rŒÛŒö |j                  |«       |S c c}}w )u­  Utility for creating a random regular expander.

    Returns a random $d$-regular graph on $n$ nodes which is an expander
    graph with very good probability.

    Parameters
    ----------
    n : int
      The number of nodes.
    d : int
      The degree of each node.
    create_using : Graph Instance or Constructor
      Indicator of type of graph to return.
      If a Graph-type instance, then clear and use it.
      If a constructor, call it to create an empty graph.
      Use the Graph constructor by default.
    max_tries : int. (default: 100)
      The number of allowed loops when generating each independent cycle
    seed : (default: None)
      Seed used to set random number generation state. See :ref`Randomness<randomness>`.

    Notes
    -----
    The nodes are numbered from $0$ to $n - 1$.

    The graph is generated by taking $d / 2$ random independent cycles.

    Joel Friedman proved that in this model the resulting
    graph is an expander with probability
    $1 - O(n^{-\tau})$ where $\tau = \lceil (\sqrt{d - 1}) / 2 \rceil - 1$. [1]_

    Examples
    --------
    >>> G = nx.maybe_regular_expander(n=200, d=6, seed=8020)

    Returns
    -------
    G : graph
        The constructed undirected graph.

    Raises
    ------
    NetworkXError
        If $d % 2 != 0$ as the degree must be even.
        If $n - 1$ is less than $ 2d $ as the graph is complete at most.
        If max_tries is reached

    See Also
    --------
    is_regular_expander
    random_regular_expander_graph

    References
    ----------
    .. [1] Joel Friedman,
       A Proof of Alonâ€™s Second Eigenvalue Conjecture and Related Problems, 2004
       https://arxiv.org/abs/cs/0405020

    r   Nr   zn must be a positive integerr   z$d must be greater than or equal to 2zd must be evenzNeed n-1>= d to have room for z independent cycles with z nodesT)Úcyclicz-Too many iterations in maybe_regular_expander)Únumpyr   r   r   Úsetr   ÚlenÚpermutationÚtolistÚappendÚutilsÚpairwiseÚupdateÚadd_edges_from)r   Údr    r6   r3   Únpr!   ÚcyclesÚedgesÚiÚ
iterationsÚcycler%   r&   Ú	new_edgess                  r'   r   r   ×   sã  € ó~ àˆ1‚uÜ×ÑÐ=Ó>Ð>à�ŠFÜ×ÑÐEÓFÐFà�‰E�QŠJÜ×ÑÐ/Ó0Ð0à�‰E�QŠJÜ×ÑØ,¨Q°©T¨FÐ2KÈAÈ3ÈfÐUó
ð 	
ô 	�‰�q˜,Ó'€Aàˆ1‚uØˆà€FÜ‹E€Eô �1˜‘6‹]ò XˆØˆ
ä�%‹j˜Q ™U a™KÓ'Ø˜!‰OˆJð ×$Ñ$ Q¨¡UÓ+×2Ñ2Ó4ˆEØ�L‰L˜˜Q™Ôô ŸH™H×-Ñ-¨e¸DÐ-ÓA÷á�A�qØ�q�6 Ñ&¨A¨q¨6¸Ñ+>ð �A’ðˆIñ ô �9‹~ Ò"Ø—‘˜eÔ$Ø—‘˜YÔ'à˜QŠÜ×&Ñ&Ð'VÓWÐWô' �%‹j˜Q ™U a™KÔ'ðXð0 ×Ñ�UÔà€Hùó!s   Ä-F>ÚdirectedÚ
multigraphr!   Úweightr   )Úpreserve_edge_attrs©Úepsilonc                ó�  — ddl }ddlm} |dk  rt        j                  d«      ‚t        j
                  | «      syt        j                  j                  | j                  «      \  }}t        j                  | t        ¬«      } ||ddd¬	«      }t        |«      }t        t        |«      d|j                  |d
z
  «      z  |z   k  «      S )a  Determines whether the graph G is a regular expander. [1]_

    An expander graph is a sparse graph with strong connectivity properties.

    More precisely, this helper checks whether the graph is a
    regular $(n, d, \lambda)$-expander with $\lambda$ close to
    the Alon-Boppana bound and given by
    $\lambda = 2 \sqrt{d - 1} + \epsilon$. [2]_

    In the case where $\epsilon = 0$ then if the graph successfully passes the test
    it is a Ramanujan graph. [3]_

    A Ramanujan graph has spectral gap almost as large as possible, which makes them
    excellent expanders.

    Parameters
    ----------
    G : NetworkX graph
    epsilon : int, float, default=0

    Returns
    -------
    bool
        Whether the given graph is a regular $(n, d, \lambda)$-expander
        where $\lambda = 2 \sqrt{d - 1} + \epsilon$.

    Examples
    --------
    >>> G = nx.random_regular_expander_graph(20, 4)
    >>> nx.is_regular_expander(G)
    True

    See Also
    --------
    maybe_regular_expander
    random_regular_expander_graph

    References
    ----------
    .. [1] Expander graph, https://en.wikipedia.org/wiki/Expander_graph
    .. [2] Alon-Boppana bound, https://en.wikipedia.org/wiki/Alon%E2%80%93Boppana_bound
    .. [3] Ramanujan graphs, https://en.wikipedia.org/wiki/Ramanujan_graph

    r   N)Úeigshzepsilon must be non negativeF)ÚdtypeÚLMr   )ÚwhichÚkÚreturn_eigenvectorsr   )r9   Úscipy.sparse.linalgrR   r   r   Ú
is_regularr?   Úarbitrary_elementÚdegreeÚadjacency_matrixÚfloatÚminÚboolÚabsÚsqrt)	r!   rP   rD   rR   Ú_rC   ÚAÚlamsÚlambda2s	            r'   r   r   L  s¨   € ób Ý)à�‚{Ü×ÑÐ=Ó>Ð>ä�=‰=˜ÔØä�8‰8×%Ñ% a§h¡hÓ/�D€A€qä
×Ñ˜A¤UÔ+€AÙ�˜$ !¸Ô?€Dô �$‹i€Gô ”�G“˜q B§G¡G¨A°©E£NÑ2°WÑ<Ñ<Ó=Ð=r(   )rP   r    r6   r3   c                ó¾   — t        | ||||¬«      }|}t        ||¬«      s=|dz  }t        | ||||¬«      }|dk(  rt        j                  d«      ‚t        ||¬«      sŒ=|S )a  Returns a random regular expander graph on $n$ nodes with degree $d$.

    An expander graph is a sparse graph with strong connectivity properties. [1]_

    More precisely the returned graph is a $(n, d, \lambda)$-expander with
    $\lambda = 2 \sqrt{d - 1} + \epsilon$, close to the Alon-Boppana bound. [2]_

    In the case where $\epsilon = 0$ it returns a Ramanujan graph.
    A Ramanujan graph has spectral gap almost as large as possible,
    which makes them excellent expanders. [3]_

    Parameters
    ----------
    n : int
      The number of nodes.
    d : int
      The degree of each node.
    epsilon : int, float, default=0
    max_tries : int, (default: 100)
      The number of allowed loops, also used in the maybe_regular_expander utility
    seed : (default: None)
      Seed used to set random number generation state. See :ref`Randomness<randomness>`.

    Raises
    ------
    NetworkXError
        If max_tries is reached

    Examples
    --------
    >>> G = nx.random_regular_expander_graph(20, 4)
    >>> nx.is_regular_expander(G)
    True

    Notes
    -----
    This loops over `maybe_regular_expander` and can be slow when
    $n$ is too big or $\epsilon$ too small.

    See Also
    --------
    maybe_regular_expander
    is_regular_expander

    References
    ----------
    .. [1] Expander graph, https://en.wikipedia.org/wiki/Expander_graph
    .. [2] Alon-Boppana bound, https://en.wikipedia.org/wiki/Alon%E2%80%93Boppana_bound
    .. [3] Ramanujan graphs, https://en.wikipedia.org/wiki/Ramanujan_graph

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