Merge pull request #30 from mohawk2/fixups

Update to networkx 2.0 API.

halp/utilities/directed_graph_transformations.py

@@ -67,13 +67,13 @@ def to_networkx_digraph(H):
     nx_graph = nx.DiGraph()
 
     for node in G.node_iterator():
-        nx_graph.add_node(node, G.get_node_attributes(node))
+        nx_graph.add_node(node, **G.get_node_attributes(node))
 
     for hyperedge_id in G.hyperedge_id_iterator():
         tail_node = G.get_hyperedge_tail(hyperedge_id).pop()
         head_node = G.get_hyperedge_head(hyperedge_id).pop()
         edge_attributes = G.get_hyperedge_attributes(hyperedge_id)
-        nx_graph.add_edge(tail_node, head_node, edge_attributes)
+        nx_graph.add_edge(tail_node, head_node, **edge_attributes)
 
     return nx_graph
 
@@ -97,10 +97,10 @@ def from_networkx_digraph(nx_digraph):
 
     G = DirectedHypergraph()
 
-    for node in nx_digraph.nodes_iter():
-        G.add_node(node, copy.copy(nx_digraph.node[node]))
+    for node in nx_digraph.nodes():
+        G.add_node(node, **copy.copy(nx_digraph.nodes[node]))
 
-    for edge in nx_digraph.edges_iter():
+    for edge in nx_digraph.edges():
         tail_node = edge[0]
         head_node = edge[1]
         G.add_hyperedge(tail_node,

halp/utilities/undirected_graph_transformations.py

@@ -68,12 +68,12 @@ def to_networkx_graph(H):
     nx_graph = nx.Graph()
 
     for node in G.node_iterator():
-        nx_graph.add_node(node, G.get_node_attributes(node))
+        nx_graph.add_node(node, **G.get_node_attributes(node))
 
     for hyperedge_id in G.hyperedge_id_iterator():
         edge_nodes = G.get_hyperedge_nodes(hyperedge_id)
         edge_attributes = G.get_hyperedge_attributes(hyperedge_id)
-        nx_graph.add_edge(edge_nodes[0], edge_nodes[1], edge_attributes)
+        nx_graph.add_edge(edge_nodes[0], edge_nodes[1], **edge_attributes)
 
     return nx_graph
 
@@ -97,10 +97,10 @@ def from_networkx_graph(nx_graph):
 
     G = UndirectedHypergraph()
 
-    for node in nx_graph.nodes_iter():
-        G.add_node(node, copy.copy(nx_graph.node[node]))
+    for node in nx_graph.nodes():
+        G.add_node(node, copy.copy(nx_graph.nodes[node]))
 
-    for edge in nx_graph.edges_iter():
+    for edge in nx_graph.edges():
         G.add_hyperedge([edge[0], edge[1]],
                         copy.copy(nx_graph[edge[0]][edge[1]]))
 

requirements.txt

@@ -0,0 +1,19 @@
+#  - pip install git+http://github.com/numpy/numpy/
+#  - pip install git+http://github.com/scipy/scipy/
+#  - pip install git+http://github.com/scipy/scipy.git@maintenance/0.14.x
+#  - coverage run --source=halp setup.py test
+
+numpy==1.19.5
+scipy==1.6.0
+networkx==2.5
+## The following requirements were added by pip freeze:
+attrs==20.3.0
+coverage==5.3.1
+decorator==4.4.2
+iniconfig==1.1.1
+packaging==20.8
+pluggy==0.13.1
+py==1.10.0
+pyparsing==2.4.7
+pytest==6.2.1
+toml==0.10.2

tests/algorithms/test_k_shortest_hyperpaths.py

@@ -262,7 +262,7 @@ def test_returns_3_shortest_hypergraphs_for_nielsen_example_with_k_equal_3(
             self):
         threeShortest = ksh.k_shortest_hyperpaths(
             self.nielsenGraph, 's', 't', 3)
-        self.assertEquals(len(threeShortest), 3)
+        self.assertEqual(len(threeShortest), 3)
         # shortest path
         hyperpath = threeShortest[0]
         self.assertEqual(hyperpath.get_node_set(), {'s', '1', '2', 't'})

tests/utilities/test_directed_graph_transformations.py

@@ -36,13 +36,13 @@ def test_to_networkx_digraph():
     G = directed_graph_transformations.to_networkx_digraph(H)
 
     H_nodes = H.get_node_set()
-    G_nodes = G.node.keys()
+    G_nodes = G.nodes.keys()
 
     assert H_nodes == set(G_nodes)
 
     H_nodes_attributes = [H.get_node_attributes(node) for node in H_nodes]
     for node in G_nodes:
-        assert G.node[node] in H_nodes_attributes
+        assert G.nodes[node] in H_nodes_attributes
 
     for hyperedge_id in H.hyperedge_id_iterator():
         tail_set = H.get_hyperedge_tail(hyperedge_id)
@@ -69,12 +69,12 @@ def test_from_networkx_digraph():
 
     G = directed_graph_transformations.from_networkx_digraph(nxG)
 
-    nxG_nodes = nxG.node.keys()
+    nxG_nodes = nxG.nodes.keys()
     G_nodes = G.get_node_set()
 
     assert G_nodes == set(nxG_nodes)
 
-    for edge in nxG.edges_iter():
+    for edge in nxG.edges():
         tail_node = edge[0]
         head_node = edge[1]
         assert G.has_hyperedge(tail_node, head_node)

tests/utilities/test_undirected_graph_transformations.py

@@ -33,13 +33,13 @@ def test_to_networkx_graph():
     G = undirected_graph_transformations.to_networkx_graph(H)
 
     H_nodes = H.get_node_set()
-    G_nodes = G.node.keys()
+    G_nodes = G.nodes.keys()
 
     assert H_nodes == set(G_nodes)
 
     H_nodes_attributes = [H.get_node_attributes(node) for node in H_nodes]
     for node in G_nodes:
-        assert G.node[node] in H_nodes_attributes
+        assert G.nodes[node] in H_nodes_attributes
 
     for hyperedge_id in H.hyperedge_id_iterator():
         hyperedge_nodes = H.get_hyperedge_nodes(hyperedge_id)
@@ -69,12 +69,12 @@ def test_from_networkx_graph():
 
     G = undirected_graph_transformations.from_networkx_graph(nxG)
 
-    nxG_nodes = nxG.node.keys()
+    nxG_nodes = nxG.nodes.keys()
     G_nodes = G.get_node_set()
 
     assert G_nodes == set(nxG_nodes)
 
-    for edge in nxG.edges_iter():
+    for edge in nxG.edges():
         assert G.has_hyperedge((edge[0], edge[1]))
 
     # Try transforming an invalid undirected hypergraph