ó
    †~iP;  ã                   ó’  • S r SSKrSSKr/ SQr\R
                  " SSS9SS j5       r\R
                  " SSS9SS j5       r\R
                  " SSS9SS j5       r\R                  R                  R                  S	5      \R
                  " SSS9SS
SS.S j5       5       rSS
SS.S jr\R                  R                  S5      \R                  R                  S5      \R
                  " SSS00S9SS.S j5       5       5       r\R                  R                  R                  S	5      \R
                  " SSS9SSS
SS.S j5       5       rg)z3Provides explicit constructions of expander graphs.é    N)Úmargulis_gabber_galil_graphÚchordal_cycle_graphÚpaley_graphÚmaybe_regular_expanderÚmaybe_regular_expander_graphÚis_regular_expanderÚrandom_regular_expander_graphT)ÚgraphsÚreturns_graphc                 óì  • [         R                  " SU[         R                  S9nUR                  5       (       d  UR	                  5       (       d  Sn[         R
                  " U5      e[        R                  " [        U 5      SS9 HX  u  pEUSU-  -   U -  U4USU-  S-   -   U -  U4XESU-  -   U -  4XESU-  S-   -   U -  44 H  u  pgUR                  XE4Xg45        M     MZ     SU  S3UR                  S	'   U$ )
aˆ  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           ÚZ/home/mande/repo/quber/.venv/lib/python3.13/site-packages/networkx/generators/expanders.pyr   r   2   sù   € ô4 	�Š�q˜,´·±Ñ>€AØ‡}�}‡�˜aŸo™o×/Ñ/Ø@ˆÜ×Ò˜sÓ#Ð#ä×!Ò!¤%¨£(°1Ô5‰ˆà�!�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&ó	
‰DˆAð �J‰J˜�v ˜vÖ&ó
ñ 6ð 5°Q°C°qÐ9€A‡G�GˆF�OØ€Hó    c                 ó¢  • [         R                  " SU[         R                  S9nUR                  5       (       d  UR	                  5       (       d  Sn[         R
                  " U5      e[        U 5       HF  nUS-
  U -  nUS-   U -  nUS:”  a  [        X@S-
  U 5      OSnXVU4 H  nUR                  XH5        M     MH     SU  S3UR                  S'   U$ )	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$   ÚleftÚrightÚchordr%   s	            r(   r   r   ]   sÂ   € ôN 	�Š�q˜,´·±Ñ>€AØ‡}�}‡�˜aŸo™o×/Ñ/Ø@ˆÜ×Ò˜sÓ#Ð#ä�1ŽXˆØ�A‘˜‰{ˆØ�Q‘˜!‘ˆð %&¨£E”�A˜1‘u˜aÔ ¨qˆØ˜uÓ%ˆAØ�J‰J�qÖó &ñ ð  -¨Q¨C¨qÐ1€A‡G�GˆF�OØ€Hr)   c                 óš  • [         R                  " SU[         R                  S9nUR                  5       (       a  Sn[         R                  " U5      e[        SU 5       Vs1 s H  oDS-  U -  S:w  d  M  US-  U -  iM     nn[        U 5       H#  nU H  nUR                  XDU-   U -  5        M     M%     SU  S3UR                  S'   U$ s  snf )	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$   Ú
square_setÚx2s          r(   r   r   �   s¾   € ôX 	�Š�q˜,´·
±
Ñ;€AØ‡�×ÑØ6ˆÜ×Ò˜sÓ#Ð#ô
 ',¨A¨q¤kÓE¢k ¸±d¸a±ZÀ1±_“*�1�a‘4˜1”*¡k€JÐEä�1ŽXˆÛˆBØ�J‰J�q˜r™6 Q™,Ö'ó ñ ð ˜q˜c �m€A‡G�GˆF�OØ€Hùò Fs   Á CÁ3CÚseedéd   ©r!   Ú	max_triesr4   c                ó¼  • SSK nU S:  a  [        R                  " S5      eUS:¼  d  [        R                  " S5      eUS-  S:X  d  [        R                  " S5      eU S-
  U:¼  d   [        R                  " SUS-   S	U  S
35      e[        R                  " X5      nU S:  a  U$ / n[	        5       n[        US-  5       GH  n	Un
[        U5      U	S-   U -  :w  d  M  U
S-  n
UR                  U S-
  5      R                  5       nUR                  U S-
  5        [        R                  R                  USS9 VVs1 s H  u  pÍXÍ4U;  d  M  XÜ4U;  d  M  XÍ4iM     nnn[        U5      U :X  a"  UR                  U5        UR                  U5        U
S:X  a  Sn[        R                  " U5      e[        U5      U	S-   U -  :w  a  Mæ  GM     UR                  U5        U$ s  snnf )aõ  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_graph(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 Alon's Second Eigenvalue Conjecture and Related Problems, 2004
   https://arxiv.org/abs/cs/0405020

r   Nr   zn must be a positive integerr   z$d must be greater than or equal to 2zd must be evenzNeed n-1>= d to have room for z independent cycles with z nodesT)Úcyclicz3Too many iterations in maybe_regular_expander_graph)Únumpyr   r   r   Úsetr   ÚlenÚpermutationÚtolistÚappendÚutilsÚpairwiseÚupdateÚadd_edges_from)r    Údr!   r7   r4   Únpr"   ÚcyclesÚedgesÚiÚ
iterationsÚcycler&   r'   Ú	new_edgesr#   s                   r(   r   r   Ú   så  € ó~ àˆ1ƒuÜ×ÒÐ=Ó>Ð>à�‹FÜ×ÒÐEÓFÐFà�‰E�Q‹JÜ×ÒÐ/Ó0Ð0à�‰E�Q‹JÜ×ÒØ,¨Q°!©V¨HÐ4MÈaÈSÐPVÐWó
ð 	
ô 	�Š�qÓ'€Aàˆ1ƒuØˆà€FÜ‹E€Eô �1˜‘6�]ˆØˆ
ä�%‹j˜Q ™U a™KÕ'Ø˜!‰OˆJð ×$Ñ$ Q¨¡UÓ+×2Ñ2Ó4ˆEØ�L‰L˜˜Q™Ôô ŸH™H×-Ñ-¨e¸DÐ-ÑAôâA‘D�AØ�6 Ñ&ó à,-¨6¸Ñ+>ó �“ÙAð ñ ô �9‹~ Ó"Ø—‘˜eÔ$Ø—‘˜YÔ'à˜Q‹ØK�Ü×&Ò& sÓ+Ð+ô) �%‹j˜Q ™U a™K×'Ð'ñ ð2 ×Ñ�UÔà€Hùó#s   Ä6GÅGÅGc                óJ   • SSK nUR                  S[        SS9  [        XX#US9$ )z�
.. deprecated:: 3.6
   `maybe_regular_expander` is a deprecated alias
   for `maybe_regular_expander_graph`.
   Use `maybe_regular_expander_graph` instead.
r   NzQmaybe_regular_expander is deprecated, use `maybe_regular_expander_graph` instead.r   )ÚcategoryÚ
stacklevelr6   )ÚwarningsÚwarnÚDeprecationWarningr   )r    rD   r!   r7   r4   rO   s         r(   r   r   P  s9   € ó à‡M�Mð	6ä#Øð	 ñ ô (Ø	˜<À4ñð r)   ÚdirectedÚ
multigraphr"   Úweightr   )Úpreserve_edge_attrs©Úepsilonc                óÊ  • SSK nSSKnUS:  a  [        R                  " S5      e[        R                  " U 5      (       d  g[        R
                  R                  U R                  5      u  pE[        R                  " U [        S9nUR                  R                  R                  USSSS9n[        U5      n[        [        U5      SUR!                  US	-
  5      -  U-   :  5      $ )
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_graph
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

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×Ò˜A¤UÑ+€AØ�9‰9×Ñ×!Ñ! !¨4°1È%Ð!ÐP€Dô �$‹i€Gô ”�G“˜q 2§7¡7¨1¨q©5£>Ñ1°GÑ;Ñ;Ó<Ð<r)   )rW   r!   r7   r4   c                ó´   • [        XX4US9nUn[        XbS9(       d<  US-  n[        XX4US9nUS:X  a  [        R                  " S5      e[        XbS9(       d  M<  U$ )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_graph` 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_graph` and can be slow when
$n$ is too big or $\epsilon$ too small.

See Also
--------
maybe_regular_expander_graph
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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