Update patches

1 files changed, 0 insertions, 395 deletions

diff --git a/sagemath-networkx-2.2.patch b/sagemath-networkx-2.2.patch
deleted file mode 100644
index 9a1e29b24e71..000000000000
--- a/sagemath-networkx-2.2.patch
+++ /dev/null
@@ -1,395 +0,0 @@
-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))
- 
-