Bump networkx from 2.5 to 3.0 (#2)

* Bump networkx from 2.5 to 3.0

Bumps [networkx](https://github.com/networkx/networkx) from 2.5 to 3.0.
- [Release notes](https://github.com/networkx/networkx/releases)
- [Commits](networkx/networkx@networkx-2.5...networkx-3.0)

---
updated-dependencies:
- dependency-name: networkx
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <[email protected]>

* Updated code for networkx 3.0

---------

Signed-off-by: dependabot[bot] <[email protected]>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Jan Ernsting <[email protected]>

gem/embedding/hope.py

@@ -25,7 +25,7 @@ def learn_embedding(self, graph=None,
         if not graph:
             raise ValueError('graph needed')
 
-        A = nx.to_numpy_matrix(graph)
+        A = nx.to_numpy_array(graph)
         m_g = np.eye(len(graph.nodes)) - self._beta * A
         m_l = self._beta * A
         S = np.dot(np.linalg.inv(m_g), m_l)

gem/embedding/lle.py

@@ -25,7 +25,7 @@ def learn_embedding(self, graph=None,
         if not graph:
             raise ValueError('graph needed')
         graph = graph.to_undirected()
-        A = nx.to_scipy_sparse_matrix(graph)
+        A = nx.to_scipy_sparse_array(graph)
         normalize(A, norm='l1', axis=1, copy=False)
         i_n = sp.eye(len(graph.nodes))
         i_min_A = i_n - A

gem/embedding/sdne.py

@@ -48,7 +48,7 @@ def learn_embedding(self, graph=None,
                         is_weighted=False, no_python=False):
         if not graph:
             raise ValueError('graph needed')
-        sparse = nx.to_scipy_sparse_matrix(graph)
+        sparse = nx.to_scipy_sparse_array(graph)
         sparse = (sparse + sparse.T) / 2
         self._node_num = len(graph.nodes)
 

requirements.txt

@@ -1,6 +1,6 @@
 numpy==1.24.2
 scipy>=0.19.0
-networkx==2.5
+networkx==3.0
 matplotlib>=2.0.0
 scikit-learn>=0.21.2
 theano>=0.9.0

tests/test_sbm.py

@@ -19,6 +19,7 @@
 
 
 from tests.fit_model import fit_model
+from tests.utils import read_gpickle
 
 
 class SBMTest(unittest.TestCase):
@@ -30,7 +31,7 @@ def setUp(self) -> None:
         file_prefix = os.path.join(self.source_dir, 'data/sbm.gpickle')
 
         # Load graph
-        G = nx.read_gpickle(file_prefix)
+        G = read_gpickle(file_prefix)
         # convert G (networkx 1.x digraph) to networkx 2.x
         H = nx.DiGraph()
         H.add_nodes_from(G.node)

tests/utils.py

@@ -0,0 +1,7 @@
+import pickle
+
+
+def read_gpickle(path: str):
+    with open(path, 'rb') as f:
+        g = pickle.load(f)
+    return g