Update patches

1 files changed, 269 insertions, 53 deletions

diff --git a/sagemath-networkx-2.2.patch b/sagemath-networkx-2.2.patch
index c9f2e790b51b..2bfe2c699837 100644
--- a/sagemath-networkx-2.2.patch
+++ b/sagemath-networkx-2.2.patch
@@ -1,224 +1,440 @@
 diff --git a/src/sage/graphs/digraph_generators.py b/src/sage/graphs/digraph_generators.py
-index d0023e9..a478727 100644
+index 204c013..af4d8ea 100644
 --- a/src/sage/graphs/digraph_generators.py
 +++ b/src/sage/graphs/digraph_generators.py
-@@ -1108,7 +1108,7 @@ class DiGraphGenerators():
+@@ -63,6 +63,7 @@ Functions and methods
+ from __future__ import print_function, division
+ from six.moves import range
  
-         -  ``kernel`` - the attachment kernel
++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 for the random number generator
++        - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random
++          number generator (default: ``None``).
  
  
          EXAMPLES::
-@@ -1124,7 +1124,7 @@ class DiGraphGenerators():
+ 
+             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 = current_randstate().c_random()
++            seed = int(current_randstate().long_seed() % sys.maxint)
          import networkx
          return DiGraph(networkx.gn_graph(n, kernel, seed=seed))
  
-@@ -1144,7 +1144,7 @@ class DiGraphGenerators():
+@@ -1142,16 +1144,17 @@ class DiGraphGenerators():
+         INPUT:
  
-         -  ``n`` - number of vertices.
+ 
+-        -  ``n`` - number of vertices.
++        - ``n`` - number of vertices.
  
 -        -  ``seed`` - for the random number generator
-+        -  ``seed`` - a ``random.Random`` seed for the random number generator
++        - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random
++          number generator (default: ``None``).
  
  
          EXAMPLES::
-@@ -1160,7 +1160,7 @@ class DiGraphGenerators():
+ 
+             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 = current_randstate().c_random()
++            seed = int(current_randstate().long_seed() % sys.maxint)
          import networkx
          return DiGraph(networkx.gnc_graph(n, seed=seed))
  
-@@ -1355,7 +1355,7 @@ class DiGraphGenerators():
+@@ -1351,18 +1354,19 @@ class DiGraphGenerators():
+         INPUT:
+ 
  
-         -  ``p`` - redirection probability
+-        -  ``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 for the random number generator.
++        - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random
++          number generator (default: ``None``).
  
  
          EXAMPLES::
-@@ -1371,7 +1371,7 @@ class DiGraphGenerators():
+ 
+             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 = current_randstate().c_random()
++            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..5b1e3ce 100644
+index 06a5203..5cbf5e9 100644
 --- a/src/sage/graphs/generators/random.py
 +++ b/src/sage/graphs/generators/random.py
-@@ -30,7 +30,7 @@ def RandomGNP(n, p, seed=None, fast=True, algorithm='Sage'):
+@@ -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 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
-@@ -106,7 +106,7 @@ def RandomGNP(n, p, seed=None, fast=True, algorithm='Sage'):
+@@ -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 = current_randstate().c_random()
++        seed = int(current_randstate().long_seed() % sys.maxint)
      if p == 1:
          from sage.graphs.generators.basic import CompleteGraph
          return CompleteGraph(n)
-@@ -140,7 +140,7 @@ def RandomBarabasiAlbert(n, m, seed=None):
+@@ -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 for random number generator (default ``None``).
++    - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random
++      number generator (default: ``None``).
++
  
      EXAMPLES:
  
-@@ -175,7 +175,7 @@ def RandomBarabasiAlbert(n, m, seed=None):
+@@ -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 = current_randstate().c_random()
++        seed = int(current_randstate().long_seed() % sys.maxint)
      import networkx
      return Graph(networkx.barabasi_albert_graph(n,m,seed=seed))
  
-@@ -625,7 +625,7 @@ def RandomGNM(n, m, dense=False, seed=None):
+@@ -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 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 +658,7 @@ def RandomGNM(n, m, dense=False, seed=None):
+@@ -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 = current_randstate().c_random()
++        seed = int(current_randstate().long_seed() % sys.maxint)
      import networkx
      if dense:
          return Graph(networkx.dense_gnm_random_graph(n, m, seed=seed))
-@@ -688,7 +688,7 @@ def RandomNewmanWattsStrogatz(n, k, p, seed=None):
+@@ -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 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`::
-@@ -708,7 +708,7 @@ def RandomNewmanWattsStrogatz(n, k, p, seed=None):
+ 
+         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 = current_randstate().c_random()
++        seed = int(current_randstate().long_seed() % sys.maxint)
      import networkx
      return Graph(networkx.newman_watts_strogatz_graph(n, k, p, seed=seed))
  
-@@ -728,7 +728,7 @@ def RandomHolmeKim(n, m, p, seed=None):
+@@ -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 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
-@@ -764,7 +764,7 @@ def RandomHolmeKim(n, m, p, seed=None):
+@@ -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 = current_randstate().c_random()
++        seed = int(current_randstate().long_seed() % sys.maxint)
      import networkx
      return Graph(networkx.powerlaw_cluster_graph(n, m, p, seed=seed))
  
-@@ -838,7 +838,7 @@ def RandomLobster(n, p, q, seed=None):
+@@ -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 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`::
-@@ -852,7 +852,7 @@ def RandomLobster(n, p, q, seed=None):
+ 
+         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 = current_randstate().c_random()
++        seed = int(current_randstate().long_seed() % sys.maxint)
      import networkx
      return Graph(networkx.random_lobster(n, p, q, seed=seed))
  
-@@ -943,7 +943,7 @@ def RandomTreePowerlaw(n, gamma=3, tries=100, seed=None):
+@@ -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 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.
-@@ -960,7 +960,7 @@ def RandomTreePowerlaw(n, gamma=3, tries=100, seed=None):
+ 
+     ::
+ 
+-        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 = current_randstate().c_random()
++        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 +981,7 @@ def RandomRegular(d, n, seed=None):
+@@ -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 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
-@@ -1009,7 +1009,7 @@ def RandomRegular(d, n, seed=None):
+@@ -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 = current_randstate().c_random()
++        seed = int(current_randstate().long_seed() % sys.maxint)
      import networkx
      try:
          N = networkx.random_regular_graph(d, n, seed=seed)
-@@ -1034,7 +1034,7 @@ def RandomShell(constructor, seed=None):
+@@ -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 for random number generator (default ``None``).
++    - ``seed`` - a ``random.Random`` seed or a Python ``int`` for the random
++      number generator (default: ``None``).
++
  
      EXAMPLES::
  
-@@ -1044,7 +1044,7 @@ def RandomShell(constructor, seed=None):
+         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 = current_randstate().c_random()
++        seed = int(current_randstate().long_seed() % sys.maxint)
      import networkx
      return Graph(networkx.random_shell_graph(constructor, seed=seed))
  
+