o 3ήc2@s&dZddlZddlZejejejejgZej deej ddddZ ej deej dd d gd d Z ej deej ddd dZ ej deddZej deej ddej ddddZej dejejejgej dgdddZGdddZdS)zCUnit tests for the :mod:`networkx.generators.random_graphs` module.N generatordirected)TFcCsB|dd|d}t|dksJ|dksJ||ksJdS)zMIf the edge probability `p` is <=0, the resulting graph should have no edges. 皙rrNlennumber_of_edges is_directedrrGr S/tmp/pip-target-vg8gfxp4/lib/python/networkx/generators/tests/test_random_graphs.py-test_gnp_generators_negative_edge_probabilitysr)rexpected_num_edges)F-)TZcCsB|dd|d}t|dksJ||ksJ||ksJdS)zKIf the edge probability `p` is >=1, the resulting graph should be complete.rg?rNr)rrrr r r r3test_gnp_generators_greater_than_1_edge_probabilitys rcCs2|dd|d}t|dksJ||ksJdS)zIIf the edge probability `p` is >0 and <1, test only the basic properties.r皙?rN)rr r r r rtest_gnp_generators_basic'srcsFd}tfddt|D}t|t|d|ddks!JdS)zUIf the edge probability `p` is close to 1, the resulting graph should have all edges.dc3s"|] }ddddVqdS)rgwJ?TrN)r .0_rr r 4s z7test_gnp_generators_for_p_close_to_1..rg@N)sumrangeabsfloat)rrunsedgesr rr$test_gnp_generators_for_p_close_to_10s  (r"p)g?皙?c sd}dfddtD}t|D]'}|||d}|jD]\}}|||d7<|s9|||d7<qqtD]*}tD]#}||krV|||dksUJqEt|||t||dkshJqEq?d S) zOTest that gnp generators generate edges according to the their probability `p`.icsg|]}dgqS)rr rnr r Asz8test_gnp_generators_edge_probability..rrgQ?N)rr!rr) rr#rr edge_countsir vwr r&r$test_gnp_generators_edge_probability:s$   &r.)seedrr))*Fi)r0Ti ):Fi)r1Ti cCsD|dd||d}t|dksJ||ksJ||ks JdS)z:Test that aliases give the same result with the same seed.r?)r/rNr)rr/rrr r r rtest_gnp_random_graph_aliasesRs r3c@sHeZdZddZdddZdd d Zd d Zd dZddZddZ dS)TestGeneratorsRandomcsd}tdd|tjdd|ddtdd|tddd|tdks)Jdks1Jtjddd d|d tdksCJdksKJtjtj tjddd d d tdd d|tdkshJdkspJt ddd|tdksJdksJt dd d|tdksJdksJt dd|t dd|dksJt dd|t ddksJt ddd d |dksJt ddd d |dksJt ddd d|dksJt dddd |dksJdksJt dddd|dks)Jdks2Jtddd|tddd|dksKJtdd|ttj tjddttj tjddddg}t||dd fd!d"}tdd d|tfd#d$DdksJ|sJttj tjdd d|ttj tjddd|ttj tjddd|tdd d|sJtjddd%dd&}tjddd%dd&dS)'Nr0rTrrr2r)triesr/r)r7gr)i#r%i'c?i,i333333?g?!)rr5r$)r5(r$csJfddD}|D]}fdd|D}t|dks"dSq dS)z A tree is a caterpillar iff all nodes of degree >=3 are surrounded by at most two nodes of degree two or greater. ref: http://mathworld.wolfram.com/CaterpillarGraph.html cg|] }|dkr|qS)r9degreerr'gr rr(zRTestGeneratorsRandom.test_random_graph..is_caterpillar..crAr6rB)rnbhrEr rr(rGr6FT) neighborsr)rF deg_over_3r'nbh_deg_over_2r rEris_caterpillars z>TestGeneratorsRandom.test_random_graph..is_caterpillarcs fddD}|S)z A tree is a lobster if it has the property that the removal of leaf nodes leaves a caterpillar graph (Gallian 2007) ref: http://mathworld.wolfram.com/LobsterGraph.html csg|] }|dkr|qS)r)rBrDrEr rr(rGzNTestGeneratorsRandom.test_random_graph..is_lobster..)subgraph)rF non_leafs)rMrEr is_lobstersz:TestGeneratorsRandom.test_random_graph..is_lobsterc3s|]}|VqdSNrBrD)r r rrsz9TestGeneratorsRandom.test_random_graph..)r/r7)nxgnm_random_graphdense_gnm_random_graphwatts_strogatz_graphrr connected_watts_strogatz_graphpytestraises NetworkXErrornewman_watts_strogatz_graphbarabasi_albert_graphcomplete_graphextended_barabasi_albert_graphpowerlaw_cluster_graphrandom_regular_graphrandom_shell_graphrandom_lobstermaxnodesrandom_powerlaw_tree_sequencerandom_powerlaw_tree)selfr/ constructorrPseqr )r rMrtest_random_graphbsv   $z&TestGeneratorsRandom.test_random_graphr)r8r;c Csgd}td}|D]}td||}td||d|}||ks'Jtd||} td||d|} | | ksAJtd||} td||||} | | ks[Jtd|||||} td|||}td|||} t|| | krt|| ksJJq tj}t tj ||||dt tj ||||dt tj |d||dt tj |d||dtt||d}tj tj |d||||dd S) z Tests that the dual BA random graph generated behaves consistently. Tests the exceptions are raised as expected. The graphs generation are repeated several times to prevent lucky shots r0r1i rrr)rgg?) initial_graphN) rSr]r\dual_barabasi_albert_graphr!sizeminrcrXrYrZ)rgm1m2r#seedsrlr/BA1DBA1BA2DBA2BA3DBA3DBAdbaginitialr r rtest_dual_barabasi_alberts4 z.TestGeneratorsRandom.test_dual_barabasi_albertr6c Csgd}|D]_}td||}|}td|dd|}||ks$Jtd|dd|}||dks7Jtd|dd|}||ksHJtd|dd|}||ks[J||kseJqtj} ttj| ||ddttj| ddddttj| ddddd S) z Tests that the extended BA random graph generated behaves consistently. Tests the exceptions are raised as expected. The graphs generation are repeated several times to prevent lucky-shots rkrrr$r6r<r)r;N)rSr\r r^rnrXrYrZ) rgmrrr/BA_modelBA_model_edgesG1G2G3ebagr r rtest_extended_barabasi_alberts" z2TestGeneratorsRandom.test_extended_barabasi_albertcCs6d}tdd|}t|dksJ|dksJdS)zYTests that a 0-regular graph has the correct number of nodes and edges. r0rrN)rSr`rr )rgr/r r r rtest_random_zero_regular_graphsz3TestGeneratorsRandom.test_random_zero_regular_graphcCstdd}t|dksJ|dksJtjdddd}t|dks&J|dks.Jtdd}t|dks.integralcs ||SrQr )rr-rrr rrootJrz;TestGeneratorsRandom.test_random_kernel_graph..rootr)ir0r)rSrandom_kernel_graphr)rgrrgraphr rrtest_random_kernel_graphFs  z-TestGeneratorsRandom.test_random_kernel_graphN)r)r8r;rH) __name__ __module__ __qualname__rjr|rrrrrr r r rr4as c .&  r4)__doc__rXnetworkxrSgnp_random_graphfast_gnp_random_graphbinomial_grapherdos_renyi_graph_gnp_generatorsmark parametrizerrrr"r.r3r4r r r rsF