VhO{ddlZddlZddlZdZdZdZdZdZdZ dZ d Z d Z d Z d Zd ZdZdZdZdZdZdZdZdZdZdZdZdZdZdZdZdZdZ dZ!d Z"d!Z#y)"Ncdtj}tjtd5tj |ddddtjtd5tj |ddddtjtd5tj |ddddtjtd5tj |ddddy#1swYxYw#1swYxYw#1swY]xYw#1swYyxYw)Nz7The WL algorithm requires that `iterations` be positive)match iterationsr)nx empty_graphpytestraises ValueErrorweisfeiler_lehman_graph_hash!weisfeiler_lehman_subgraph_hashes)G1s \/home/dcms/DCMS/lib/python3.12/site-packages/networkx/algorithms/tests/test_graph_hashing.pytest_positive_itersr s  B G ; ''r: ; G @ ,,RB? @ G : ''q9 : G ? ,,RA> ??;; @@ :: ??s/D+D&D!D&D DD#&D/ctj}tj}tj|}tj|}tj|d}tj|d}tj|dd}tj|d}||k(sJ||k(sJ||k(sJ||k(sJ||k(sJy) zD empty graphs should give hashes regardless of other params edge_attr1 edge_attr node_attr1 node_attrrr rN)rr r )rG2h1h2h3h4h5h6s rtest_empty_graph_hashr"%s  B  B ( ( ,B ( ( ,B ( (| DB ( (| DB ( ( ll B ( ( ;B 8O8 8O8 8O8 8O8 8O8cd}t|D]e}tjd|zd|z}tj|}tj|}tj|}||k7reJy)z A directed graph with no bi-directional edges should yield different a graph hash to the same graph taken as undirected if there are no hash collisions. rdseedN)rangergn_graph to_undirectedr )ri G_directed G_undirected h_directed h_undirecteds r test_directedr1<sr A 1X*[[acAg6 '' 3 44Z@ 66|D \)))*r#c ^tjdtj}tj||j Dcic]}|t |c}d|j }tj|d}tj|d}||k7sJycc}w)z A directed graph with no bi-directional edges should yield different a graph hash to the same graph taken with edge directions reversed if there are no hash collisions. Here we test a cycle graph which is the minimal counterexample  create_usinglabelnamerN)r cycle_graphDiGraphset_node_attributesnodesstrreverser Gn G_reversedh h_reverseds r test_reversedrELs qrzz2A1!'')>rTR&*>>>>&*>>>>&*AAAA   bbhhj"A1b1f9"A B"$"A"A ,# #%"A"A ,# '*AAAA&*AAAA;B&#Bs. E ctj}|jddddifddifgtjt tj |dyzz If the 'edge_attr' argument is supplied but is missing from an edge in the graph, we should raise a KeyError rJrr[rN)rGraphadd_edges_fromr r KeyErrorr r@s rtest_missing_edge_attrrksL  Aq!lC01Aq":>? MM(B;;Q,Wr#c d\}}d|z }td|dzD],}tj|||zd|z}|jD],}|d|j|d<|d|j|d <.tj|d }tj|d }tj|d }||k7sJ||k7sJ||k7sJtj ||jDcic]}|d |z c}} tj| d } tj| d } || k(sJ|| k(r-Jy cc}w) a Isomorphic graphs with differing node attributes should yield different graph hashes if the 'node_attr' argument is supplied and populated in the graph, and there are no hash collisions. The output should still be invariant to node-relabeling rHrIrJr&rWrrX node_attr2rNrL)r(rrMr<r rN) rAr+rOr,rrPg1_hash_with_node_attr1g1_hash_with_node_attr2g1_hash_no_node_attrrg2_hash_with_node_attr1g2_hash_with_node_attr2s rtest_isomorphic_node_attrrts DAq aA 1a!e_B  ! !!QUq 9 1A+,#RBHHQK %+,#RBHHQK % 1#%"A"A ,# #%"A"A ,#  ">>rTR&*>>>>&*>>>>&*AAAA   bbhhj"A1b1f9"A B"$"A"A ,# #%"A"A ,# '*AAAA&*AAAA;B&#Bs7 E ctj}|jdddifdifg|jgdt j t tj|dyzy If the 'node_attr' argument is supplied but is missing from a node in the graph, we should raise a KeyError rJrr[re)rJre)rerf)rfrJ)rJrN)rrgadd_nodes_fromrhr r rir rjs rtest_missing_node_attrrzsW  Aq<-.B8956 MM(B;;Q,Wr#c \d\}}d|z }td|dzD]}tj|||zd|z}|jD],}|d|j|d<|d|j|d <.|jD]'\}}|d |d|||d <|d |d|||d <)tj |d d }tj |d d } tj |d d } tj |} || k7sJ| | k7sJ|| k7sJ| | k7sJ| |k7sJtj ||jDcic]}|d|z c}} tj | d d } tj | d d }|| k(sJ| |k(rJycc}w)a Isomorphic graphs with differing node attributes should yield different graph hashes if the 'node_attr' and 'edge_attr' argument is supplied and populated in the graph, and there are no hash collisions. The output should still be invariant to node-relabeling rHrIrJr&rWrrXrnrVrrYrrLN)r(rrMr<rZr rN)rAr+rOr,rrPr[r\g1_hash_edge1_node1g1_hash_edge2_node2g1_hash_edge1_node2g1_hash_no_attrrg2_hash_edge1_node1g2_hash_edge2_node2s r'test_isomorphic_edge_attr_and_node_attrrs DAq aA 1a!e_&:  ! !!QUq 9 1A+,#RBHHQK %+,#RBHHQK % 1HH 2DAq()s!A3b\BqE!H\ "()s!A3b\BqE!H\ " 2!== ,, !== ,, !== ,, 99"="o555"o555"&9999"&9999"&9999   bbhhj"A1b1f9"A B == ,, !== ,, #&9999"&9999M&:8#Bs F) c"d\}}d|z }td|dzD]s}tj|||zd|z}tj|}tj|d}||k7sJt |dk(sJt |dk(rsJy ) d The hash string lengths should be as expected for a variety of graphs and digest sizes rHrIrJr&  digest_size@N)r(rrMr len)rAr+rOr,r@h16h32s rtest_digest_sizers DAq aA 1a!e_"  AEq 9--a0--aR@czz3x6!!!3x6!!!"r#c tj}tj}|jgd|jgd|jddg|jddgtj|}tj|}||k7sJtj}|jgd|jgd|jddgtj |d d d d d d d d d t j|}tj |dddddd tj |dddddd tj|dd }tj|dd }||k(sJtj|d }tj|d } || k7sJy)zI These were bugs for directed graphs as discussed in issue #7806 rJrerfrxrwrfrerfrx))rrx)rJr3)re)rf))rx)r3r)r )rr)rr)rrsr[r\)rrrrxr3rrweightdc)rrJrerfrJ)rrrN)rr:ryrhr r;copydeepcopy) GaGbGa_hashGb_hashTree1Tree2Tree1_hash_shortTree2_hash_short Tree1_hash Tree2_hashs rtest_directed_bugsrs B Bl#l#vv&'vv&'--b1G--b1G g   JJLE 9: 9: '7+, CCCCCCCH( MM% E5cccc"BHM5cccc"BHM66 !x66 !x / // /00 J00(KJ  ## #r#c:d\}}d|z }td|dzD]~}tj|||zd|z}tj|||zd|z}tj|}tj|}||k(}tj|ddtj|ddtj|d } tj|d } | | k(} tj |d d tj |d d tj|d } tj|d } | | k(}tj|d d }tj|d d }||k(}|| k(sJ| |k(sJ||k(rJy)zP Trivial labelling of the graph should not change isomorphism verdicts. rHrIrJr|r&*rvaluesr8rr[e_weightrrN)r(rrMr r;set_edge_attributes)rAr+rOr,rrG1_hashG2_hashequal G1_hash_node G2_hash_node equal_node G1_hash_edge G2_hash_edge equal_edge G1_hash_both G2_hash_both equal_boths rtest_trivial_labels_isomorphismr?s DAq aA 1a!e_(  ! !!QUq 9  ! !!QUa 811"511"57" r!(; r!(;66rXN 66rXN !\1  r#J? r#J?66rZP 66rZP !\1 66 * 66 * "\1  """Z'''Z''';(r#c.d\}}d|z }td|dzD]}tj|||zdd|z}tj|||zdd|z}tj|}tj|}||k(}tj|dd tj|dd tj|d } tj|d } | | k(} tj |d d tj |d d tj|d } tj|d } | | k(}tj|d d}tj|d d}||k(}|| k(sJ| |k(sJ||k(rJtj }|jgdtj|}|jddg|jddgtj|}tj|}||k7sJtj|dd tj|dd tj|d }tj|d }||k7sJy)z\ Trivial labelling of the graph should not change isomorphism verdicts on digraphs. rHrIrJTr|)directedr'rrrrr[rrrrrwrrN) r(rrMr r;rr:ryrrrh)rAr+rOr,rrrrrrrrrrrrrrrrrrs r(test_trivial_labels_isomorphism_directedresu DAq aA 1a!e_(  ! !!QUTa H  ! !!QUTQ G11"511"57" r!(; r!(;66rXN 66rXN !\1  r#J? r#J?66rZP 66rZP !\1 66 * 66 * "\1  """Z'''Z''';(B Bl# r Bvv&'vv&'--b1G--b1G g  2ah72ah7--bHEG--bHEG g  r#cd\}}d|z }td|dzD]}tj|||zd|z}tj|ddtj|d }tj |dd tj|d }||k(sJtj|d d }||k(rJy )a7 Test that 'empty' labelling of nodes or edges shouldn't have a different impact on the calculated hash. Note that we cannot assume that trivial weights have no impact at all. Without (trivial) weights, a node will start with hashing its degree. This step is omitted when there are weights. rHrIrJr|r&rrrrrrN)r(rrMr;r r)rAr+rOr,rfirstsecondthirds rtest_trivial_labels_hashesrs DAq aA 1a!e_   ! !!QUq 9 r"8<//hG r":>00zJ// *  r#cHtfd|jDS)z returns True if that each hash sequence in 'a' is a prefix for the corresponding sequence indexed by the same node in 'b'. c3LK|]\}}|dt||k(ywNr).0nodehashesr\s r z"is_subiteration..s)NLD&qw}V%/Ns!$)allitems)r[r\s `ris_subiterationrs NAGGIN NNr#c^|dzfdtfd|jDS)a  returns True if all hex digest sizes are the expected length in a node:subgraph-hashes dictionary. Hex digest string length == 2 * bytes digest length since each pair of hex digits encodes 1 byte (https://docs.python.org/3/library/hashlib.html) rec,tfd|DS)Nc3:K|]}t|k(ywrr)rxhexdigest_sizes rrzMhexdigest_sizes_correct..list_digest_sizes_correct..s73q6^+7s)r)lrs rlist_digest_sizes_correctz:hexdigest_sizes_correct..list_digest_sizes_corrects7Q777r#c3.K|] }|ywr)rrrs rrz*hexdigest_sizes_correct..sJV(0Js)rr)r[rrrs @@rhexdigest_sizes_correctrs,!1_N8 JqxxzJ JJr#cTtj}tj|}tj|d}tj|d}tj|d}tj|d}|ik(sJ|ik(sJ|ik(sJ|ik(sJ|ik(sJy) zZ " empty graphs should give empty dict subgraph hashes regardless of other params rrrrerrrN)rr r)r@subgraph_hashes1subgraph_hashes2subgraph_hashes3subgraph_hashes4subgraph_hashes5s rtest_empty_graph_subgraph_hashrs A;;A>;;AU;;AU;;A!L;;A2N r !! ! r !! ! r !! ! r !! ! r !! !r#cd}t|D]e}tjd|zd|z}tj|}tj|}tj|}||k7reJy)z A directed graph with no bi-directional edges should yield different subgraph hashes to the same graph taken as undirected, if all hashes don't collide. rr%r&N)r(rr)r*r)r+r,r-r.directed_subgraph_hashesundirected_subgraph_hashess rtest_directed_subgraph_hashrsw A 1XF[[acAg6 '' 3 #%#G#G #S %'%I%I,%W"'+EEEEFr#c ^tjdtj}tj||j Dcic]}|t |c}d|j }tj|d}tj|d}||k7sJycc}w)z A directed graph with no bi-directional edges should yield different subgraph hashes to the same graph taken with edge directions reversed if there are no hash collisions. Here we test a cycle graph which is the minimal counterexample r3r4r6r7rN)rr9r:r;r<r=r>rr?s rtest_reversed_subgraph_hashrs qrzz2A1!'')>>>&*>>>>&*AAAA   bbhhj"A1b1f9"A B"$"F"F ,# #%"F"F ,# '"9"?"?"A+ !QBFAI+    '"9"?"?"A+ !QBFAI+    ?! &#B+ + s. F F 0F ctj}|jddddifddifgtjt tj |dyrd)rrgrhr r rirrjs r$test_missing_edge_attr_subgraph_hashr?sO  Aq!lC01Aq":>? MM"66\r#c Ld\}}d|z }td|dzD]v}tj|||zd|z}|jD],}|d|j|d<|d|j|d <.tj|d }tj|d }tj|d }||k7sJ||k7sJ||k7sJtj ||jDcic]}|d |z c}} tj| d } tj| d } || j D cic] \} } d | z|  c} } k(sJ|| j D cic] \} } d | z|  c} } k(rwJy cc}wcc} } wcc} } w) a Isomorphic graphs with differing node attributes should yield different subgraph hashes if the 'node_attr' argument is supplied and populated in the graph, and all hashes don't collide. The output should still be invariant to node-relabeling rHrIrJrmr&rWrrXrnrNrL)r(rrMr<rrNr)rAr+rOr,rrProrprqrrrrsrrs r'test_isomorphic_node_attr_subgraph_hashrKs DAq aA 1a!e_!   ! !!QUq 9 1A+,#RBHHQK %+,#RBHHQK % 1#%"F"F ,# #%"F"F ,#  "CCBRVW&*>>>>&*>>>>&*AAAA   bbhhj"A1b1f9"A B"$"F"F ,# #%"F"F ,# '"9"?"?"A+ !QBFAI+    '"9"?"?"A+ !QBFAI+    ?! &#B+ + s7 F F 9F ctj}|jdddifdifg|jgdt j t tj|dyrv)rrgryrhr r rirrjs r$test_missing_node_attr_subgraph_hashrxsZ  Aq<-.B8956 MM"66\r#c d\}}d|z }td|dzD]}tj|||zd|z}|jD],}|d|j|d<|d|j|d <.|jD]'\}}|d |d|||d <|d |d|||d <)tj |d d }tj |d d } tj |d d } tj |} || k7sJ| | k7sJ|| k7sJ| | k7sJ| |k7sJtj ||jDcic]}|d|z c}} tj | d d } tj | d d }|| jDcic] \}}d|z| c}}k(sJ| |jDcic] \}}d|z| c}}k(rJycc}wcc}}wcc}}w)a Isomorphic graphs with differing node attributes should yield different subgraph hashes if the 'node_attr' and 'edge_attr' argument is supplied and populated in the graph, and all hashes don't collide The output should still be invariant to node-relabeling rHrIrJr|r&rWrrXrnrVrrYrrLN)r(rrMr<rZrrNr)rAr+rOr,rrPr[r\r}r~rrrrrrrs r5test_isomorphic_edge_attr_and_node_attr_subgraph_hashrst DAq aA 1a!e_*   ! !!QUq 9 1A+,#RBHHQK %+,#RBHHQK % 1HH 2DAq()s!A3b\BqE!H\ "()s!A3b\BqE!H\ " 2!BB ,, !BB ,, !BB ,, >>rB"o555"o555"&9999"&9999"&9999   bbhhj"A1b1f9"A B BB ,, !BB ,, #"5";";"=' !QBFAI'    #"5";";"=' !QBFAI'    Q* 8#B' ' s G3 +G8 G> c&d\}}d|z }td|dzD]}tj|||zd|z}tj|d}tj|d}tj|d }t d |j DsJt d |j DsJt d |j DsJt ||sJt ||sJt ||rJy )z All nodes should have the correct number of subgraph hashes in the output when using degree as initial node labels. Subsequent iteration depths for the same graph should be additive for each node rHrIrJiXr&rfrrxr3c38K|]}t|dk(ywrfNrrrs rrz'test_iteration_depth..B3v;!#Bc38K|]}t|dk(ywrxNrrs rrz'test_iteration_depth..rrc38K|]}t|dk(ywr3Nrrs rrz'test_iteration_depth..rrN)r(rrMrrrr)rAr+rOr,r@depth3depth4depth5s rtest_iteration_depthrs DAq aA 1a!e_ /  AEa 855aAF55aAF55aAFB&--/BBBBB&--/BBBBB&--/BBBBvv...vv...vv... /r#czd\}}d|z }td|dzD]}tj|||zd|z}|jD]\}}|d|d|||d<tj|dd }tj|dd }tj|dd } t d |j DsJt d|j DsJt d| j DsJt||sJt|| sJt|| rJy)a All nodes should have the correct number of subgraph hashes in the output when setting initial node labels empty and using an edge attribute when aggregating neighborhoods. Subsequent iteration depths for the same graph should be additive for each node rHrIrJir&rVrWrrf)rrrxr3c38K|]}t|dk(ywrrrs rrz1test_iteration_depth_edge_attr..rrc38K|]}t|dk(ywrrrs rrz1test_iteration_depth_edge_attr..rrc38K|]}t|dk(ywrrrs rrz1test_iteration_depth_edge_attr..rrN)r(rrMrZrrrr) rAr+rOr,r@r[r\rrrs rtest_iteration_depth_edge_attrrsK DAq aA 1a!e_/  AEa 8GG 1DAq'(c1#RLAaDGL ! 155 ! 55 ! 55 ! B&--/BBBBB&--/BBBBB&--/BBBBvv...vv...vv...-/r#cd\}}d|z }td|dzD]#}tj|||zd|z}|jD]}|d|j|d<tj|dd }tj|dd }tj|dd }t d |j DsJt d |j DsJt d|j DsJt||sJt||sJt||r$Jy)z All nodes should have the correct number of subgraph hashes in the output when setting initial node labels to an attribute. Subsequent iteration depths for the same graph should be additive for each node rHrIrJi r&rWrrf)rrrxr3c38K|]}t|dk(ywrrrs rrz1test_iteration_depth_node_attr.. rrc38K|]}t|dk(ywrrrs rrz1test_iteration_depth_node_attr..rrc38K|]}t|dk(ywrrrs rrz1test_iteration_depth_node_attr..rrN)r(rrMr<rrrr) rAr+rOr,r@rPrrrs rtest_iteration_depth_node_attrr sC DAq aA 1a!e_/  AEa 8 0A*+BxAGGAJ| $ 055 ! 55 ! 55 ! B&--/BBBBB&--/BBBBB&--/BBBBvv...vv...vv...-/r#cd\}}d|z }td|dzD]K}tj|||zd|z}|jD]}|d|j|d<|jD]\}}|d|d|||d <tj |d dd }tj |d dd } tj |d dd } t d|jDsJt d| jDsJt d| jDsJt|| sJt| | sJt|| rLJy)a! All nodes should have the correct number of subgraph hashes in the output when setting initial node labels to an attribute and also using an edge attribute when aggregating neighborhoods. Subsequent iteration depths for the same graph should be additive for each node rHrIrJir&rWrrVrrf)rrrrxr3c38K|]}t|dk(ywrrrs rrz6test_iteration_depth_node_edge_attr..2rrc38K|]}t|dk(ywrrrs rrz6test_iteration_depth_node_edge_attr..3rrc38K|]}t|dk(ywrrrs rrz6test_iteration_depth_node_edge_attr..4rrN) r(rrMr<rZrrrr) rAr+rOr,r@rPr[r\rrrs r#test_iteration_depth_node_edge_attrrs DAq aA 1a!e_/  AEa 8 0A*+BxAGGAJ| $ 0GG 1DAq'(c1#RLAaDGL ! 155 ! 55 ! 55 ! B&--/BBBBB&--/BBBBB&--/BBBBvv...vv...vv...3/r#cd\}}d|z }td|dzD]o}tj|||zd|z}tj|}tj|d}||k7sJt |dsJt |droJy ) rrHrIrJrr&rrN)r(rrMrr)rAr+rOr,r@digest_size16_hashesdigest_size32_hashess rtest_digest_size_subgraph_hashr;s DAq aA 1a!e_ A  AEq 9!CCAF!CCASUV#';;;;&';R@@@&';R@@@ Ar#c tjd}tj||Dcic]}|td|cxkxrdkncc}dtj|d}t d|j DsJt|j Dchc]}|d c}dk(sJtj|dd }t d |j DsJt|j Dchc]}|d c}d k(sJ|D](}t||d d ||dD] \}}||k(r J*y cc}wcc}wcc}w)zP Including the hashed initial label prepends an extra hash to the lists r3rrxr6rc38K|]}t|dk(ywrrrrs rrz9test_initial_node_labels_subgraph_hash..XsCqs1v{CrrfT)rinclude_initial_labelsc38K|]}t|dk(ywrrrs rrz9test_initial_node_labels_subgraph_hash.._s@qs1v{@rrerJN)strict) r path_graphr;intrrrrzip)r@r,without_initial_labelrwith_initial_labelrPr[r\s r&test_initial_node_labels_subgraph_hashr#Nsa aA1!! CC C== WT @$6$=$=$?@ @@ @ 0779:!: ;q @@ @ q !!" %';s!E # E E)$rr networkxrrr"r1rErSrbrkrtrzrrrrrrrrrrrrrrrrrrrr rrr#rr#rr%s  ?6. * """&BRX&BRX/:d"$#$L#(L5p2O K"& F "X"* Z * Z 3 l/0/D/B"/JA&r#