diff --git a/src/sage/graphs/digraph_generators.py b/src/sage/graphs/digraph_generators.py index 204c013..af4d8ea 100644 --- a/src/sage/graphs/digraph_generators.py +++ b/src/sage/graphs/digraph_generators.py @@ -63,6 +63,7 @@ Functions and methods from __future__ import print_function, division from six.moves import range +import sys from sage.misc.randstate import current_randstate from sage.graphs.digraph import DiGraph @@ -1104,18 +1105,19 @@ class DiGraphGenerators(): INPUT: - - ``n`` - number of vertices. + - ``n`` - number of vertices. - - ``kernel`` - the attachment kernel + - ``kernel`` - the attachment kernel. - - ``seed`` - for the random number generator + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). EXAMPLES:: sage: D = digraphs.RandomDirectedGN(25) sage: D.edges(labels=False) - [(1, 0), (2, 0), (3, 1), (4, 0), (5, 0), (6, 1), (7, 0), (8, 3), (9, 0), (10, 8), (11, 3), (12, 9), (13, 8), (14, 0), (15, 11), (16, 11), (17, 5), (18, 11), (19, 6), (20, 5), (21, 14), (22, 5), (23, 18), (24, 11)] + [(1, 0), (2, 1), (3, 0), (4, 2), (5, 0), (6, 2), (7, 3), (8, 2), (9, 3), (10, 4), (11, 5), (12, 9), (13, 2), (14, 2), (15, 5), (16, 2), (17, 15), (18, 1), (19, 5), (20, 2), (21, 5), (22, 1), (23, 5), (24, 14)] sage: D.show() # long time REFERENCE: @@ -1124,7 +1126,7 @@ class DiGraphGenerators(): Random Networks, Phys. Rev. E vol. 63 (2001), p. 066123. """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx return DiGraph(networkx.gn_graph(n, kernel, seed=seed)) @@ -1142,16 +1144,17 @@ class DiGraphGenerators(): INPUT: - - ``n`` - number of vertices. + - ``n`` - number of vertices. - - ``seed`` - for the random number generator + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). EXAMPLES:: sage: D = digraphs.RandomDirectedGNC(25) sage: D.edges(labels=False) - [(1, 0), (2, 0), (2, 1), (3, 0), (4, 0), (4, 1), (5, 0), (5, 1), (5, 2), (6, 0), (6, 1), (7, 0), (7, 1), (7, 4), (8, 0), (9, 0), (9, 8), (10, 0), (10, 1), (10, 2), (10, 5), (11, 0), (11, 8), (11, 9), (12, 0), (12, 8), (12, 9), (13, 0), (13, 1), (14, 0), (14, 8), (14, 9), (14, 12), (15, 0), (15, 8), (15, 9), (15, 12), (16, 0), (16, 1), (16, 4), (16, 7), (17, 0), (17, 8), (17, 9), (17, 12), (18, 0), (18, 8), (19, 0), (19, 1), (19, 4), (19, 7), (20, 0), (20, 1), (20, 4), (20, 7), (20, 16), (21, 0), (21, 8), (22, 0), (22, 1), (22, 4), (22, 7), (22, 19), (23, 0), (23, 8), (23, 9), (23, 12), (23, 14), (24, 0), (24, 8), (24, 9), (24, 12), (24, 15)] + [(1, 0), (2, 0), (3, 0), (3, 2), (4, 0), (5, 0), (5, 2), (5, 3), (6, 0), (6, 4), (7, 0), (7, 2), (7, 3), (8, 0), (8, 2), (8, 3), (8, 5), (9, 0), (9, 4), (9, 6), (10, 0), (10, 2), (10, 3), (10, 7), (11, 0), (11, 4), (11, 6), (11, 9), (12, 0), (12, 4), (13, 0), (13, 4), (14, 0), (14, 2), (14, 3), (14, 5), (14, 8), (15, 0), (15, 2), (15, 3), (16, 0), (16, 2), (16, 3), (16, 15), (17, 0), (17, 2), (18, 0), (18, 2), (18, 3), (18, 7), (18, 10), (19, 0), (19, 2), (19, 3), (19, 5), (20, 0), (20, 2), (20, 3), (20, 7), (20, 10), (21, 0), (21, 2), (22, 0), (22, 4), (22, 6), (22, 9), (22, 11), (23, 0), (23, 2), (23, 17), (24, 0), (24, 4), (24, 6), (24, 9)] sage: D.show() # long time REFERENCE: @@ -1160,7 +1163,7 @@ class DiGraphGenerators(): Copying, Phys. Rev. E vol. 71 (2005), p. 036118. """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx return DiGraph(networkx.gnc_graph(n, seed=seed)) @@ -1351,18 +1354,19 @@ class DiGraphGenerators(): INPUT: - - ``n`` - number of vertices. + - ``n`` - number of vertices. - - ``p`` - redirection probability + - ``p`` - redirection probability. - - ``seed`` - for the random number generator. + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). EXAMPLES:: sage: D = digraphs.RandomDirectedGNR(25, .2) sage: D.edges(labels=False) - [(1, 0), (2, 0), (2, 1), (3, 0), (4, 0), (4, 1), (5, 0), (5, 1), (5, 2), (6, 0), (6, 1), (7, 0), (7, 1), (7, 4), (8, 0), (9, 0), (9, 8), (10, 0), (10, 1), (10, 2), (10, 5), (11, 0), (11, 8), (11, 9), (12, 0), (12, 8), (12, 9), (13, 0), (13, 1), (14, 0), (14, 8), (14, 9), (14, 12), (15, 0), (15, 8), (15, 9), (15, 12), (16, 0), (16, 1), (16, 4), (16, 7), (17, 0), (17, 8), (17, 9), (17, 12), (18, 0), (18, 8), (19, 0), (19, 1), (19, 4), (19, 7), (20, 0), (20, 1), (20, 4), (20, 7), (20, 16), (21, 0), (21, 8), (22, 0), (22, 1), (22, 4), (22, 7), (22, 19), (23, 0), (23, 8), (23, 9), (23, 12), (23, 14), (24, 0), (24, 8), (24, 9), (24, 12), (24, 15)] + [(1, 0), (2, 0), (3, 0), (3, 2), (4, 0), (5, 0), (5, 2), (5, 3), (6, 0), (6, 4), (7, 0), (7, 2), (7, 3), (8, 0), (8, 2), (8, 3), (8, 5), (9, 0), (9, 4), (9, 6), (10, 0), (10, 2), (10, 3), (10, 7), (11, 0), (11, 4), (11, 6), (11, 9), (12, 0), (12, 4), (13, 0), (13, 4), (14, 0), (14, 2), (14, 3), (14, 5), (14, 8), (15, 0), (15, 2), (15, 3), (16, 0), (16, 2), (16, 3), (16, 15), (17, 0), (17, 2), (18, 0), (18, 2), (18, 3), (18, 7), (18, 10), (19, 0), (19, 2), (19, 3), (19, 5), (20, 0), (20, 2), (20, 3), (20, 7), (20, 10), (21, 0), (21, 2), (22, 0), (22, 4), (22, 6), (22, 9), (22, 11), (23, 0), (23, 2), (23, 17), (24, 0), (24, 4), (24, 6), (24, 9)] sage: D.show() # long time REFERENCE: @@ -1371,7 +1375,7 @@ class DiGraphGenerators(): Random Networks, Phys. Rev. E vol. 63 (2001), p. 066123. """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx return DiGraph(networkx.gnc_graph(n, seed=seed)) diff --git a/src/sage/graphs/generators/degree_sequence.py b/src/sage/graphs/generators/degree_sequence.py index bcea8db..0d85654 100644 --- a/src/sage/graphs/generators/degree_sequence.py +++ b/src/sage/graphs/generators/degree_sequence.py @@ -16,6 +16,8 @@ The methods defined here appear in :mod:`sage.graphs.graph_generators`. # (at your option) any later version. # https://www.gnu.org/licenses/ # **************************************************************************** + +import sys from sage.graphs.graph import Graph from sage.misc.randstate import current_randstate @@ -142,10 +144,11 @@ def DegreeSequenceConfigurationModel(deg_sequence, seed=None): INPUT: - - ``deg_sequence`` - a list of integers with each - entry corresponding to the expected degree of a different vertex. + - ``deg_sequence`` - a list of integers with each entry corresponding to the + expected degree of a different vertex. - - ``seed`` - for the random number generator. + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). EXAMPLES:: @@ -172,7 +175,7 @@ def DegreeSequenceConfigurationModel(deg_sequence, seed=None): networks, SIAM Review vol. 45, no. 2 (2003), pp. 167-256. """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx return Graph(networkx.configuration_model([int(i) for i in deg_sequence], seed=seed), loops=True, multiedges=True, sparse=True) @@ -210,17 +213,18 @@ def DegreeSequenceExpected(deg_sequence, seed=None): INPUT: - - ``deg_sequence`` - a list of integers with each - entry corresponding to the expected degree of a different vertex. + - ``deg_sequence`` - a list of integers with each entry corresponding to the + expected degree of a different vertex. - - ``seed`` - for the random number generator. + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). EXAMPLES:: sage: G = graphs.DegreeSequenceExpected([1,2,3,2,3]) sage: G.edges(labels=False) - [(0, 2), (0, 3), (1, 1), (1, 4), (2, 3), (2, 4), (3, 4), (4, 4)] + [(0, 3), (1, 4), (2, 2), (2, 3), (2, 4), (4, 4)] sage: G.show() # long time REFERENCE: @@ -230,6 +234,6 @@ def DegreeSequenceExpected(deg_sequence, seed=None): Ann. Combinatorics (6), 2002 pp. 125-145. """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx return Graph(networkx.expected_degree_graph([int(i) for i in deg_sequence], seed=seed), loops=True) diff --git a/src/sage/graphs/generators/random.py b/src/sage/graphs/generators/random.py index 06a5203..5cbf5e9 100644 --- a/src/sage/graphs/generators/random.py +++ b/src/sage/graphs/generators/random.py @@ -14,6 +14,7 @@ The methods defined here appear in :mod:`sage.graphs.graph_generators`. # http://www.gnu.org/licenses/ ########################################################################### from six.moves import range +import sys # import from Sage library from sage.graphs.graph import Graph from sage.misc.randstate import current_randstate @@ -30,7 +31,8 @@ def RandomGNP(n, p, seed=None, fast=True, algorithm='Sage'): - ``p`` -- probability of an edge - - ``seed`` -- integer seed for random number generator (default ``None``). + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). - ``fast`` -- boolean set to True (default) to use the algorithm with time complexity in `O(n+m)` proposed in [BatBra2005]_. It is designed @@ -98,7 +100,7 @@ def RandomGNP(n, p, seed=None, fast=True, algorithm='Sage'): sage: graphs.RandomGNP(50,.2, algorithm="Sage").size() 243 sage: graphs.RandomGNP(50,.2, algorithm="networkx").size() - 258 + 245 """ if n < 0: raise ValueError("The number of nodes must be positive or null.") @@ -106,7 +108,7 @@ def RandomGNP(n, p, seed=None, fast=True, algorithm='Sage'): raise ValueError("The probability p must be in [0..1].") if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) if p == 1: from sage.graphs.generators.basic import CompleteGraph return CompleteGraph(n) @@ -140,7 +142,9 @@ def RandomBarabasiAlbert(n, m, seed=None): - ``m`` - number of edges to attach from each new node - - ``seed`` -- integer seed for random number generator (default ``None``). + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). + EXAMPLES: @@ -149,7 +153,7 @@ def RandomBarabasiAlbert(n, m, seed=None): :: sage: graphs.RandomBarabasiAlbert(6,2).edges(labels=False) - [(0, 2), (0, 3), (0, 4), (1, 2), (2, 3), (2, 4), (2, 5), (3, 5)] + [(0, 2), (0, 3), (1, 2), (1, 4), (1, 5), (2, 3), (2, 4), (3, 5)] We plot a random graph on 12 nodes with m = 3. @@ -175,7 +179,7 @@ def RandomBarabasiAlbert(n, m, seed=None): """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx return Graph(networkx.barabasi_albert_graph(n,m,seed=seed)) @@ -625,7 +629,9 @@ def RandomGNM(n, m, dense=False, seed=None): - ``dense`` - whether to use NetworkX's dense_gnm_random_graph or gnm_random_graph - - ``seed`` -- integer seed for random number generator (default ``None``). + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). + EXAMPLES: We show the edge list of a random graph on 5 nodes with 10 edges. @@ -658,7 +664,7 @@ def RandomGNM(n, m, dense=False, seed=None): sage: G.show() # long time """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx if dense: return Graph(networkx.dense_gnm_random_graph(n, m, seed=seed)) @@ -688,13 +694,15 @@ def RandomNewmanWattsStrogatz(n, k, p, seed=None): - ``p`` - the probability of adding a new edge for each edge - - ``seed`` -- integer seed for random number generator (default ``None``). + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). + EXAMPLES: We show the edge list of a random graph on 7 nodes with 2 "nearest neighbors" and probability `p = 0.2`:: sage: graphs.RandomNewmanWattsStrogatz(7, 2, 0.2).edges(labels=False) - [(0, 1), (0, 2), (0, 3), (0, 6), (1, 2), (2, 3), (2, 4), (3, 4), (3, 6), (4, 5), (5, 6)] + [(0, 1), (0, 4), (0, 6), (1, 2), (1, 4), (2, 3), (3, 4), (4, 5), (5, 6)] :: @@ -708,7 +716,7 @@ def RandomNewmanWattsStrogatz(n, k, p, seed=None): 99, 2566-2572. """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx return Graph(networkx.newman_watts_strogatz_graph(n, k, p, seed=seed)) @@ -728,7 +736,9 @@ def RandomHolmeKim(n, m, p, seed=None): - ``p`` - probability of adding a triangle after adding a random edge. - - ``seed`` -- integer seed for random number generator (default ``None``). + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). + From the NetworkX documentation: The average clustering has a hard time getting above a certain cutoff that depends on m. This cutoff @@ -750,8 +760,7 @@ def RandomHolmeKim(n, m, p, seed=None): :: sage: graphs.RandomHolmeKim(8, 2, 0.5).edges(labels=False) - [(0, 2), (0, 5), (1, 2), (1, 3), (2, 3), (2, 4), (2, 6), (2, 7), - (3, 4), (3, 6), (3, 7), (4, 5)] + [(0, 2), (0, 3), (0, 4), (0, 5), (0, 7), (1, 2), (1, 3), (1, 6), (2, 4), (2, 6), (3, 5), (4, 7)] :: @@ -764,7 +773,7 @@ def RandomHolmeKim(n, m, p, seed=None): with tunable clustering, Phys. Rev. E (2002). vol 65, no 2, 026107. """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx return Graph(networkx.powerlaw_cluster_graph(n, m, p, seed=seed)) @@ -838,13 +847,15 @@ def RandomLobster(n, p, q, seed=None): - ``q`` - probability of adding an edge (claw) to the arms - - ``seed`` -- integer seed for random number generator (default ``None``). + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). + EXAMPLES: We show the edge list of a random graph with 3 backbone nodes and probabilities `p = 0.7` and `q = 0.3`:: sage: graphs.RandomLobster(3, 0.7, 0.3).edges(labels=False) - [(0, 1), (1, 2)] + [(0, 1), (0, 5), (1, 2), (1, 6), (2, 3), (2, 7), (3, 4), (3, 8)] :: @@ -852,7 +863,7 @@ def RandomLobster(n, p, q, seed=None): sage: G.show() # long time """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx return Graph(networkx.random_lobster(n, p, q, seed=seed)) @@ -924,7 +935,7 @@ def RandomTree(n): return g -def RandomTreePowerlaw(n, gamma=3, tries=100, seed=None): +def RandomTreePowerlaw(n, gamma=3, tries=1000, seed=None): """ Returns a tree with a power law degree distribution. Returns False on failure. @@ -943,15 +954,17 @@ def RandomTreePowerlaw(n, gamma=3, tries=100, seed=None): - ``tries`` - number of attempts to adjust sequence to make a tree - - ``seed`` -- integer seed for random number generator (default ``None``). + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). + EXAMPLES: We show the edge list of a random graph with 10 nodes and a power law exponent of 2. :: - sage: graphs.RandomTreePowerlaw(10, 2).edges(labels=False) - [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 7), (6, 8), (6, 9)] + sage: graphs.RandomTreePowerlaw(10, 3).edges(labels=False) + [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (5, 8), (6, 7), (6, 9)] :: @@ -960,7 +973,7 @@ def RandomTreePowerlaw(n, gamma=3, tries=100, seed=None): ....: G.show() # random output, long time """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx try: return Graph(networkx.random_powerlaw_tree(n, gamma, seed=seed, tries=tries)) @@ -981,7 +994,8 @@ def RandomRegular(d, n, seed=None): - ``d`` - degree - - ``seed`` -- integer seed for random number generator (default ``None``). + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). EXAMPLES: We show the edge list of a random graph with 8 nodes each @@ -990,7 +1004,7 @@ def RandomRegular(d, n, seed=None): :: sage: graphs.RandomRegular(3, 8).edges(labels=False) - [(0, 1), (0, 4), (0, 7), (1, 5), (1, 7), (2, 3), (2, 5), (2, 6), (3, 4), (3, 6), (4, 5), (6, 7)] + [(0, 3), (0, 5), (0, 6), (1, 2), (1, 3), (1, 7), (2, 4), (2, 6), (3, 6), (4, 5), (4, 7), (5, 7)] :: @@ -1009,7 +1023,7 @@ def RandomRegular(d, n, seed=None): regular graphs quickly. Prob. and Comp. 8 (1999), pp 377-396. """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx try: N = networkx.random_regular_graph(d, n, seed=seed) @@ -1034,17 +1048,19 @@ def RandomShell(constructor, seed=None): - ``d`` - the ratio of inter (next) shell edges to intra shell edges - - ``seed`` -- integer seed for random number generator (default ``None``). + - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random + number generator (default: ``None``). + EXAMPLES:: sage: G = graphs.RandomShell([(10,20,0.8),(20,40,0.8)]) sage: G.edges(labels=False) - [(0, 3), (0, 7), (0, 8), (1, 2), (1, 5), (1, 8), (1, 9), (3, 6), (3, 11), (4, 6), (4, 7), (4, 8), (4, 21), (5, 8), (5, 9), (6, 9), (6, 10), (7, 8), (7, 9), (8, 18), (10, 11), (10, 13), (10, 19), (10, 22), (10, 26), (11, 18), (11, 26), (11, 28), (12, 13), (12, 14), (12, 28), (12, 29), (13, 16), (13, 21), (13, 29), (14, 18), (16, 20), (17, 18), (17, 26), (17, 28), (18, 19), (18, 22), (18, 27), (18, 28), (19, 23), (19, 25), (19, 28), (20, 22), (24, 26), (24, 27), (25, 27), (25, 29)] + [(0, 7), (0, 8), (0, 9), (1, 3), (1, 4), (1, 5), (1, 7), (1, 9), (1, 27), (2, 5), (2, 9), (2, 15), (2, 21), (3, 6), (3, 8), (3, 9), (4, 6), (4, 7), (6, 7), (8, 21), (10, 26), (12, 17), (12, 18), (12, 20), (12, 25), (12, 26), (13, 14), (13, 19), (14, 16), (14, 18), (14, 19), (14, 22), (14, 24), (15, 21), (16, 17), (16, 25), (16, 26), (16, 28), (17, 19), (17, 29), (18, 24), (18, 26), (19, 28), (20, 27), (20, 29), (22, 24), (22, 27), (22, 29), (23, 24), (23, 26), (24, 27), (26, 29)] sage: G.show() # long time """ if seed is None: - seed = current_randstate().long_seed() + seed = int(current_randstate().long_seed() % sys.maxint) import networkx return Graph(networkx.random_shell_graph(constructor, seed=seed))