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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
@@ -64,6 +64,7 @@ Functions and methods
from six.moves import range
from sage.cpython.string import bytes_to_str
+import sys
from sage.misc.randstate import current_randstate
from sage.graphs.digraph import DiGraph
@@ -1101,18 +1102,19 @@ 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:
@@ -1121,7 +1123,7 @@ 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))
@@ -1159,7 +1162,7 @@ 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))
@@ -1372,7 +1376,7 @@ 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.gnr_graph(n, p, 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))
@@ -1239,13 +1248,15 @@ 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)]
::
@@ -1253,7 +1264,7 @@ 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))
@@ -1325,7 +1336,7 @@ 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.
@@ -1344,15 +1355,17 @@ 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)]
::
@@ -1361,7 +1374,7 @@ 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))
@@ -1382,7 +1395,8 @@ 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
@@ -1391,7 +1405,7 @@ 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)]
::
@@ -1410,7 +1424,7 @@ 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)
@@ -1435,17 +1449,19 @@ 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))
|