Version 2.5. All patches have been upstreamed; drop them all.

python-networkx-arg-order.patch

@@ -1,11 +0,0 @@
---- networkx/generators/community.py.orig	2019-10-16 20:03:56.000000000 -0600
-+++ networkx/generators/community.py	2020-03-09 13:58:38.932627094 -0600
-@@ -388,7 +388,7 @@ def gaussian_random_partition_graph(n, s
-             break
-         assigned += size
-         sizes.append(size)
--    return random_partition_graph(sizes, p_in, p_out, directed, seed)
-+    return random_partition_graph(sizes, p_in, p_out, seed, directed)
- 
- 
- def ring_of_cliques(num_cliques, clique_size):

python-networkx-deprecated.patch

@@ -1,242 +0,0 @@
---- networkx/algorithms/centrality/eigenvector.py.orig	2019-10-16 20:03:56.000000000 -0600
-+++ networkx/algorithms/centrality/eigenvector.py	2020-03-09 11:41:34.375972965 -0600
-@@ -224,6 +224,7 @@ def eigenvector_centrality_numpy(G, weig
-        Networks: An Introduction.
-        Oxford University Press, USA, 2010, pp. 169.
-     """
-+    import numpy as np
-     import scipy as sp
-     from scipy.sparse import linalg
-     if len(G) == 0:
-@@ -234,7 +235,7 @@ def eigenvector_centrality_numpy(G, weig
-     eigenvalue, eigenvector = linalg.eigs(M.T, k=1, which='LR',
-                                           maxiter=max_iter, tol=tol)
-     largest = eigenvector.flatten().real
--    norm = sp.sign(largest.sum()) * sp.linalg.norm(largest)
-+    norm = np.sign(largest.sum()) * sp.linalg.norm(largest)
-     return dict(zip(G, largest / norm))
- 
- 
---- networkx/algorithms/centrality/subgraph_alg.py.orig	2019-10-16 20:03:56.000000000 -0600
-+++ networkx/algorithms/centrality/subgraph_alg.py	2020-03-09 11:42:44.854815882 -0600
-@@ -226,6 +226,7 @@ def communicability_betweenness_centrali
-     >>> G = nx.Graph([(0,1),(1,2),(1,5),(5,4),(2,4),(2,3),(4,3),(3,6)])
-     >>> cbc = nx.communicability_betweenness_centrality(G)
-     """
-+    import numpy
-     import scipy
-     import scipy.linalg
-     nodelist = list(G)  # ordering of nodes in matrix
-@@ -247,7 +248,7 @@ def communicability_betweenness_centrali
-         # sum with row/col of node v and diag set to zero
-         B[i, :] = 0
-         B[:, i] = 0
--        B -= scipy.diag(scipy.diag(B))
-+        B -= numpy.diag(numpy.diag(B))
-         cbc[v] = float(B.sum())
-         # put row and col back
-         A[i, :] = row
---- networkx/algorithms/link_analysis/hits_alg.py.orig	2019-10-16 20:03:56.000000000 -0600
-+++ networkx/algorithms/link_analysis/hits_alg.py	2020-03-09 11:43:48.909764257 -0600
-@@ -286,7 +286,7 @@ def hits_scipy(G, max_iter=100, tol=1.0e
-     M = nx.to_scipy_sparse_matrix(G, nodelist=list(G))
-     (n, m) = M.shape  # should be square
-     A = M.T * M  # authority matrix
--    x = scipy.ones((n, 1)) / n  # initial guess
-+    x = np.ones((n, 1)) / n  # initial guess
-     # power iteration on authority matrix
-     i = 0
-     while True:
-@@ -294,7 +294,7 @@ def hits_scipy(G, max_iter=100, tol=1.0e
-         x = A * x
-         x = x / x.max()
-         # check convergence, l1 norm
--        err = scipy.absolute(x - xlast).sum()
-+        err = np.absolute(x - xlast).sum()
-         if err < tol:
-             break
-         if i > max_iter:
---- networkx/algorithms/link_analysis/pagerank_alg.py.orig	2019-10-16 20:03:56.000000000 -0600
-+++ networkx/algorithms/link_analysis/pagerank_alg.py	2020-03-09 11:46:41.977922907 -0600
-@@ -420,6 +420,7 @@ def pagerank_scipy(G, alpha=0.85, person
-        The PageRank citation ranking: Bringing order to the Web. 1999
-        http://dbpubs.stanford.edu:8090/pub/showDoc.Fulltext?lang=en&doc=1999-66&format=pdf
-     """
-+    import numpy
-     import scipy.sparse
- 
-     N = len(G)
-@@ -429,23 +430,23 @@ def pagerank_scipy(G, alpha=0.85, person
-     nodelist = list(G)
-     M = nx.to_scipy_sparse_matrix(G, nodelist=nodelist, weight=weight,
-                                   dtype=float)
--    S = scipy.array(M.sum(axis=1)).flatten()
-+    S = numpy.array(M.sum(axis=1)).flatten()
-     S[S != 0] = 1.0 / S[S != 0]
-     Q = scipy.sparse.spdiags(S.T, 0, *M.shape, format='csr')
-     M = Q * M
- 
-     # initial vector
-     if nstart is None:
--        x = scipy.repeat(1.0 / N, N)
-+        x = numpy.repeat(1.0 / N, N)
-     else:
--        x = scipy.array([nstart.get(n, 0) for n in nodelist], dtype=float)
-+        x = numpy.array([nstart.get(n, 0) for n in nodelist], dtype=float)
-         x = x / x.sum()
- 
-     # Personalization vector
-     if personalization is None:
--        p = scipy.repeat(1.0 / N, N)
-+        p = numpy.repeat(1.0 / N, N)
-     else:
--        p = scipy.array([personalization.get(n, 0) for n in nodelist], dtype=float)
-+        p = numpy.array([personalization.get(n, 0) for n in nodelist], dtype=float)
-         p = p / p.sum()
- 
-     # Dangling nodes
-@@ -453,10 +454,10 @@ def pagerank_scipy(G, alpha=0.85, person
-         dangling_weights = p
-     else:
-         # Convert the dangling dictionary into an array in nodelist order
--        dangling_weights = scipy.array([dangling.get(n, 0) for n in nodelist],
-+        dangling_weights = numpy.array([dangling.get(n, 0) for n in nodelist],
-                                        dtype=float)
-         dangling_weights /= dangling_weights.sum()
--    is_dangling = scipy.where(S == 0)[0]
-+    is_dangling = numpy.where(S == 0)[0]
- 
-     # power iteration: make up to max_iter iterations
-     for _ in range(max_iter):
-@@ -464,7 +465,7 @@ def pagerank_scipy(G, alpha=0.85, person
-         x = alpha * (x * M + sum(x[is_dangling]) * dangling_weights) + \
-             (1 - alpha) * p
-         # check convergence, l1 norm
--        err = scipy.absolute(x - xlast).sum()
-+        err = numpy.absolute(x - xlast).sum()
-         if err < N * tol:
-             return dict(zip(nodelist, map(float, x)))
-     raise nx.PowerIterationFailedConvergence(max_iter)
---- networkx/drawing/layout.py.orig	2019-10-16 20:03:56.000000000 -0600
-+++ networkx/drawing/layout.py	2020-03-09 10:37:14.554300047 -0600
-@@ -947,7 +947,7 @@ def planar_layout(G, scale=1, center=Non
-             raise nx.NetworkXException("G is not planar.")
-     pos = nx.combinatorial_embedding_to_pos(embedding)
-     node_list = list(embedding)
--    pos = np.row_stack((pos[x] for x in node_list))
-+    pos = np.row_stack(list(pos[x] for x in node_list))
-     pos = pos.astype(np.float64)
-     pos = rescale_layout(pos, scale=scale) + center
-     return dict(zip(node_list, pos))
---- networkx/drawing/tests/test_pylab.py.orig	2019-10-16 20:03:56.000000000 -0600
-+++ networkx/drawing/tests/test_pylab.py	2020-03-09 10:44:23.573357737 -0600
-@@ -4,7 +4,7 @@ import itertools
- import pytest
- 
- mpl = pytest.importorskip('matplotlib')
--mpl.use('PS', warn=False)
-+mpl.use('PS')
- plt = pytest.importorskip('matplotlib.pyplot')
- plt.rcParams['text.usetex'] = False
- 
-@@ -172,7 +172,7 @@ class TestPylab(object):
-         # See Issue #3295
-         G = nx.path_graph(3, create_using=nx.MultiDiGraph)
-         nx.draw_networkx(G, edgelist=[(0, 1, 0)])
--        nx.draw_networkx(G, edgelist=[(0, 1, 0)], node_size=[10, 20])
-+        nx.draw_networkx(G, edgelist=[(0, 1, 0)], node_size=[10, 20, 0])
- 
-     def test_alpha_iter(self):
-         pos = nx.random_layout(self.G)
---- networkx/linalg/laplacianmatrix.py.orig	2019-10-16 20:03:56.000000000 -0600
-+++ networkx/linalg/laplacianmatrix.py	2020-03-09 11:50:44.872221831 -0600
-@@ -116,6 +116,8 @@ def normalized_laplacian_matrix(G, nodel
-        Laplacian, Electronic Journal of Linear Algebra, Volume 16, pp. 90-98,
-        March 2007.
-     """
-+    import numpy
-+    import numpy.lib.scimath
-     import scipy
-     import scipy.sparse
-     if nodelist is None:
-@@ -127,8 +129,8 @@ def normalized_laplacian_matrix(G, nodel
-     D = scipy.sparse.spdiags(diags, [0], m, n, format='csr')
-     L = D - A
-     with scipy.errstate(divide='ignore'):
--        diags_sqrt = 1.0 / scipy.sqrt(diags)
--    diags_sqrt[scipy.isinf(diags_sqrt)] = 0
-+        diags_sqrt = 1.0 / numpy.lib.scimath.sqrt(diags)
-+    diags_sqrt[numpy.isinf(diags_sqrt)] = 0
-     DH = scipy.sparse.spdiags(diags_sqrt, [0], m, n, format='csr')
-     return DH.dot(L.dot(DH))
- 
-@@ -196,6 +198,8 @@ def directed_laplacian_matrix(G, nodelis
-        Laplacians and the Cheeger inequality for directed graphs.
-        Annals of Combinatorics, 9(1), 2005
-     """
-+    import numpy as np
-+    import numpy.lib.scimath
-     import scipy as sp
-     from scipy.sparse import spdiags, linalg
- 
-@@ -207,9 +211,9 @@ def directed_laplacian_matrix(G, nodelis
-     evals, evecs = linalg.eigs(P.T, k=1)
-     v = evecs.flatten().real
-     p = v / v.sum()
--    sqrtp = sp.sqrt(p)
-+    sqrtp = numpy.lib.scimath.sqrt(p)
-     Q = spdiags(sqrtp, [0], n, n) * P * spdiags(1.0 / sqrtp, [0], n, n)
--    I = sp.identity(len(G))
-+    I = np.identity(len(G))
- 
-     return I - (Q + Q.T) / 2.0
- 
-@@ -329,6 +333,7 @@ def _transition_matrix(G, nodelist=None,
-         If walk_type not specified or alpha not in valid range
-     """
- 
-+    import numpy as np
-     import scipy as sp
-     from scipy.sparse import identity, spdiags
-     if walk_type is None:
-@@ -344,7 +349,7 @@ def _transition_matrix(G, nodelist=None,
-                                   dtype=float)
-     n, m = M.shape
-     if walk_type in ["random", "lazy"]:
--        DI = spdiags(1.0 / sp.array(M.sum(axis=1).flat), [0], n, n)
-+        DI = spdiags(1.0 / np.array(M.sum(axis=1).flat), [0], n, n)
-         if walk_type == "random":
-             P = DI * M
-         else:
-@@ -357,7 +362,7 @@ def _transition_matrix(G, nodelist=None,
-         # this is using a dense representation
-         M = M.todense()
-         # add constant to dangling nodes' row
--        dangling = sp.where(M.sum(axis=1) == 0)
-+        dangling = np.where(M.sum(axis=1) == 0)
-         for d in dangling[0]:
-             M[d] = 1.0 / n
-         # normalize
---- networkx/readwrite/tests/test_graphml.py.orig	2019-10-16 20:03:56.000000000 -0600
-+++ networkx/readwrite/tests/test_graphml.py	2020-03-09 11:37:53.114605527 -0600
-@@ -878,7 +878,7 @@ class TestWriteGraphML(BaseGraphML):
- 
-         xml = parse(fh)
-         # Children are the key elements, and the graph element
--        children = xml.getroot().getchildren()
-+        children = list(xml.getroot())
-         assert len(children) == 3
- 
-         keys = [child.items() for child in children[:2]]
---- networkx/tests/test_convert_pandas.py.orig	2019-10-16 20:03:56.000000000 -0600
-+++ networkx/tests/test_convert_pandas.py	2020-03-09 11:51:57.623748599 -0600
-@@ -8,7 +8,8 @@ from networkx.testing import assert_node
- 
- class TestConvertPandas(object):
-     def setup_method(self):
--        self.rng = pd.np.random.RandomState(seed=5)
-+        import numpy
-+        self.rng = numpy.random.RandomState(seed=5)
-         ints = self.rng.randint(1, 11, size=(3, 2))
-         a = ['A', 'B', 'C']
-         b = ['D', 'A', 'E']

python-networkx-doc.patch

@@ -1,12 +0,0 @@
---- doc/conf.py.orig	2019-04-11 14:52:34.000000000 -0600
-+++ doc/conf.py	2019-09-11 12:27:51.389122126 -0600
-@@ -72,7 +72,8 @@ sphinx_gallery_conf = {
-     # path where to save gallery generated examples
-     'gallery_dirs': 'auto_examples',
-     'backreferences_dir': 'modules/generated',
--    'expected_failing_examples': ['../examples/advanced/plot_parallel_betweenness.py']
-+    'filename_pattern': '/plot_(?!parallel_betweenness)',
-+    'expected_failing_examples': ['../examples/graph/plot_football.py']
- }
- 
- # generate autosummary pages

python-networkx-test.patch

@@ -1,42 +0,0 @@
---- networkx/readwrite/tests/test_gexf.py.orig	2019-10-16 20:03:56.000000000 -0600
-+++ networkx/readwrite/tests/test_gexf.py	2019-10-30 11:31:05.799922383 -0600
-@@ -409,17 +409,17 @@ gexf.net/1.2draft http://www.gexf.net/1.
-         nx.set_node_attributes(G, {n: n for n in numpy.arange(4)}, 'number')
-         G[0][1]['edge-number'] = numpy.float64(1.1)
- 
--        expected = """<gexf version="1.2" xmlns="http://www.gexf.net/1.2draft"\
-- xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation\
--="http://www.gexf.net/1.2draft http://www.gexf.net/1.2draft/gexf.xsd">
-+        expected = """<gexf xmlns="http://www.gexf.net/1.2draft" xmlns:xsi="\
-+http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="\
-+http://www.gexf.net/1.2draft http://www.gexf.net/1.2draft/gexf.xsd" version="1.2">
-   <meta lastmodifieddate="{}">
-     <creator>NetworkX {}</creator>
-   </meta>
-   <graph defaultedgetype="undirected" mode="static" name="">
--    <attributes class="edge" mode="static">
-+    <attributes mode="static" class="edge">
-       <attribute id="1" title="edge-number" type="float" />
-     </attributes>
--    <attributes class="node" mode="static">
-+    <attributes mode="static" class="node">
-       <attribute id="0" title="number" type="int" />
-     </attributes>
-     <nodes>
-@@ -445,13 +445,13 @@ gexf.net/1.2draft http://www.gexf.net/1.
-       </node>
-     </nodes>
-     <edges>
--      <edge id="0" source="0" target="1">
-+      <edge source="0" target="1" id="0">
-         <attvalues>
-           <attvalue for="1" value="1.1" />
-         </attvalues>
-       </edge>
--      <edge id="1" source="1" target="2" />
--      <edge id="2" source="2" target="3" />
-+      <edge source="1" target="2" id="1" />
-+      <edge source="2" target="3" id="2" />
-     </edges>
-   </graph>
- </gexf>""".format(time.strftime('%Y-%m-%d'), nx.__version__)

python-networkx.spec

@@ -1,23 +1,12 @@
 %global srcname networkx
 
 Name:           python-%{srcname}
-Version:        2.4
+Version:        2.5
-Release:        6%{?dist}
+Release:        1%{?dist}
 Summary:        Creates and Manipulates Graphs and Networks
 License:        BSD
 URL:            http://networkx.github.io/
 Source0:        https://github.com/networkx/networkx/archive/%{srcname}-%{version}.tar.gz
-# The football example requires network access, so expect it to fail.
-# The parallel betweenness example hangs when executed, possibly due to a
-# function that cannot be pickled.  In any case, skip it.
-Patch0:         %{name}-doc.patch
-# Fix a test that fails on python 3.8 due to reordering of XML attributes.
-Patch1:         %{name}-test.patch
-# Update calls to deprecated APIs
-Patch2:         %{name}-deprecated.patch
-# Fix reversed arguments in gaussian-random_partition_graph
-# https://github.com/networkx/networkx/pull/3861
-Patch3:         %{name}-arg-order.patch
 
 BuildArch:      noarch
 
@@ -29,26 +18,26 @@ BuildRequires:  fontconfig
 BuildRequires:  python3-devel
 BuildRequires:  python3-docs
 BuildRequires:  python3-numpy-doc
-BuildRequires:  python3dist(decorator)
+BuildRequires:  %{py3_dist decorator}
-BuildRequires:  python3dist(gdal)
+BuildRequires:  %{py3_dist gdal}
-BuildRequires:  python3dist(lxml)
+BuildRequires:  %{py3_dist lxml}
-BuildRequires:  python3dist(matplotlib)
+BuildRequires:  %{py3_dist matplotlib}
-BuildRequires:  python3dist(nb2plots)
+BuildRequires:  %{py3_dist nb2plots}
-BuildRequires:  python3dist(numpy)
+BuildRequires:  %{py3_dist numpy}
-BuildRequires:  python3dist(numpydoc)
+BuildRequires:  %{py3_dist numpydoc}
-BuildRequires:  python3dist(pandas)
+BuildRequires:  %{py3_dist pandas}
-BuildRequires:  python3dist(pillow)
+BuildRequires:  %{py3_dist pillow}
-BuildRequires:  python3dist(pydot)
+BuildRequires:  %{py3_dist pydot}
-BuildRequires:  python3dist(pygraphviz)
+BuildRequires:  %{py3_dist pygraphviz}
-BuildRequires:  python3dist(pytest)
+BuildRequires:  %{py3_dist pytest}
-BuildRequires:  python3dist(pytest-cov)
+BuildRequires:  %{py3_dist pytest-cov}
-BuildRequires:  python3dist(pyyaml)
+BuildRequires:  %{py3_dist pyyaml}
-BuildRequires:  python3dist(scipy)
+BuildRequires:  %{py3_dist scipy}
-BuildRequires:  python3dist(setuptools)
+BuildRequires:  %{py3_dist setuptools}
-BuildRequires:  python3dist(sphinx)
+BuildRequires:  %{py3_dist sphinx}
-BuildRequires:  python3dist(sphinx-gallery)
+BuildRequires:  %{py3_dist sphinx-gallery}
-BuildRequires:  python3dist(sphinx-rtd-theme)
+BuildRequires:  %{py3_dist sphinx-rtd-theme}
-BuildRequires:  python3dist(texext)
+BuildRequires:  %{py3_dist texext}
 BuildRequires:  xdg-utils
 
 # Documentation
@@ -61,17 +50,17 @@ study of the structure, dynamics, and functions of complex networks.
 
 %package -n python3-%{srcname}
 Summary:        Creates and Manipulates Graphs and Networks
-Recommends:     python3dist(gdal)
+Recommends:     %{py3_dist gdal}
-Recommends:     python3dist(lxml)
+Recommends:     %{py3_dist lxml}
-Recommends:     python3dist(matplotlib)
+Recommends:     %{py3_dist matplotlib}
-Recommends:     python3dist(numpy)
+Recommends:     %{py3_dist numpy}
-Recommends:     python3dist(pandas)
+Recommends:     %{py3_dist pandas}
-Recommends:     python3dist(pillow)
+Recommends:     %{py3_dist pillow}
-Recommends:     python3dist(pydot)
+Recommends:     %{py3_dist pydot}
-Recommends:     python3dist(pygraphviz)
+Recommends:     %{py3_dist pygraphviz}
-Recommends:     python3dist(pyparsing)
+Recommends:     %{py3_dist pyparsing}
-Recommends:     python3dist(pyyaml)
+Recommends:     %{py3_dist pyyaml}
-Recommends:     python3dist(scipy)
+Recommends:     %{py3_dist scipy}
 Recommends:     xdg-utils
 
 # This can be removed when Fedora 30 reaches EOL
@@ -99,7 +88,7 @@ Documentation for networkx
 
 # Do not use env
 for f in $(grep -FRl %{_bindir}/env .); do
-  sed -e 's,%{_bindir}/env python[[:digit:]]*,%{__python3},' \
+  sed -e 's,%{_bindir}/env python[[:digit:]]*,%{python3},' \
       -e 's,%{_bindir}/env ,%{_bindir},' \
       -i.orig $f
   touch -r $f.orig $f
@@ -148,9 +137,6 @@ for fil in $(find doc/build -name \*.zip); do
   rm -fr zip
 done
 
-# The tests have shebangs, so mark them as executable
-grep -rlZ '^#!' %{buildroot}%{python3_sitelib}/networkx | xargs -0 chmod a+x
-
 %check
 pytest
 
@@ -163,6 +149,10 @@ pytest
 %doc doc/build/html/*
 
 %changelog
+* Sat Aug 22 2020 Jerry James <loganjerry@gmail.com> - 2.5-1
+- Version 2.5
+- All patches have been upstreamed; drop them all
+
 * Sat Aug 01 2020 Fedora Release Engineering <releng@fedoraproject.org> - 2.4-6
 - Second attempt - Rebuilt for
   https://fedoraproject.org/wiki/Fedora_33_Mass_Rebuild

sources

@@ -1 +1 @@
-SHA512 (networkx-2.4.tar.gz) = 2fedc556d068d2b0b1d238f5f2715c928c7999df33c318b720650893a3e536459545769c8b86c97c62ef56a62cc808848bd6897df9f37656810b11990f5d6be0
+SHA512 (networkx-2.5.tar.gz) = 8195e56d9b80e03a4d0b4472beb907813d49ca93564a30eeca5516a3fed43273cf753555d50607a08d146504a9c7d0430341c0570cce8dcd226e5bd68321284b