Update style

2 files changed, 65 insertions, 66 deletions

diff --git a/networkx/algorithms/flow/tests/test_gomory_hu.py b/networkx/algorithms/flow/tests/test_gomory_hu.py
index b82a32f7..0d9ded84 100644
--- a/networkx/algorithms/flow/tests/test_gomory_hu.py
+++ b/networkx/algorithms/flow/tests/test_gomory_hu.py
@@ -18,10 +18,9 @@ flow_funcs = [
 
 
 class TestGomoryHuTree:
-
     def minimum_edge_weight(self, T, u, v):
-        path = nx.shortest_path(T, u, v, weight='weight')
-        return min((T[u][v]['weight'], (u, v)) for (u, v) in zip(path, path[1:]))
+        path = nx.shortest_path(T, u, v, weight="weight")
+        return min((T[u][v]["weight"], (u, v)) for (u, v) in zip(path, path[1:]))
 
     def compute_cutset(self, G, T_orig, edge):
         T = T_orig.copy()
@@ -34,61 +33,56 @@ class TestGomoryHuTree:
 
     def test_default_flow_function_karate_club_graph(self):
         G = nx.karate_club_graph()
-        nx.set_edge_attributes(G, 1, 'capacity')
+        nx.set_edge_attributes(G, 1, "capacity")
         T = nx.gomory_hu_tree(G)
         assert nx.is_tree(T)
         for u, v in combinations(G, 2):
             cut_value, edge = self.minimum_edge_weight(T, u, v)
-            assert (nx.minimum_cut_value(G, u, v) ==
-                    cut_value)
+            assert nx.minimum_cut_value(G, u, v) == cut_value
 
     def test_karate_club_graph(self):
         G = nx.karate_club_graph()
-        nx.set_edge_attributes(G, 1, 'capacity')
+        nx.set_edge_attributes(G, 1, "capacity")
         for flow_func in flow_funcs:
             T = nx.gomory_hu_tree(G, flow_func=flow_func)
             assert nx.is_tree(T)
             for u, v in combinations(G, 2):
                 cut_value, edge = self.minimum_edge_weight(T, u, v)
-                assert (nx.minimum_cut_value(G, u, v) ==
-                        cut_value)
+                assert nx.minimum_cut_value(G, u, v) == cut_value
 
     def test_davis_southern_women_graph(self):
         G = nx.davis_southern_women_graph()
-        nx.set_edge_attributes(G, 1, 'capacity')
+        nx.set_edge_attributes(G, 1, "capacity")
         for flow_func in flow_funcs:
             T = nx.gomory_hu_tree(G, flow_func=flow_func)
             assert nx.is_tree(T)
             for u, v in combinations(G, 2):
                 cut_value, edge = self.minimum_edge_weight(T, u, v)
-                assert (nx.minimum_cut_value(G, u, v) ==
-                        cut_value)
+                assert nx.minimum_cut_value(G, u, v) == cut_value
 
     def test_florentine_families_graph(self):
         G = nx.florentine_families_graph()
-        nx.set_edge_attributes(G, 1, 'capacity')
+        nx.set_edge_attributes(G, 1, "capacity")
         for flow_func in flow_funcs:
             T = nx.gomory_hu_tree(G, flow_func=flow_func)
             assert nx.is_tree(T)
             for u, v in combinations(G, 2):
                 cut_value, edge = self.minimum_edge_weight(T, u, v)
-                assert (nx.minimum_cut_value(G, u, v) ==
-                        cut_value)
+                assert nx.minimum_cut_value(G, u, v) == cut_value
 
     def test_les_miserables_graph_cutset(self):
         G = nx.les_miserables_graph()
-        nx.set_edge_attributes(G, 1, 'capacity')
+        nx.set_edge_attributes(G, 1, "capacity")
         for flow_func in flow_funcs:
             T = nx.gomory_hu_tree(G, flow_func=flow_func)
             assert nx.is_tree(T)
             for u, v in combinations(G, 2):
                 cut_value, edge = self.minimum_edge_weight(T, u, v)
-                assert (nx.minimum_cut_value(G, u, v) ==
-                        cut_value)
+                assert nx.minimum_cut_value(G, u, v) == cut_value
 
     def test_karate_club_graph_cutset(self):
         G = nx.karate_club_graph()
-        nx.set_edge_attributes(G, 1, 'capacity')
+        nx.set_edge_attributes(G, 1, "capacity")
         T = nx.gomory_hu_tree(G)
         assert nx.is_tree(T)
         u, v = 0, 33
@@ -99,18 +93,25 @@ class TestGomoryHuTree:
     def test_wikipedia_example(self):
         # Example from https://en.wikipedia.org/wiki/Gomory%E2%80%93Hu_tree
         G = nx.Graph()
-        G.add_weighted_edges_from((
-            (0, 1, 1), (0, 2, 7), (1, 2, 1),
-            (1, 3, 3), (1, 4, 2), (2, 4, 4),
-            (3, 4, 1), (3, 5, 6), (4, 5, 2),
-        ))
+        G.add_weighted_edges_from(
+            (
+                (0, 1, 1),
+                (0, 2, 7),
+                (1, 2, 1),
+                (1, 3, 3),
+                (1, 4, 2),
+                (2, 4, 4),
+                (3, 4, 1),
+                (3, 5, 6),
+                (4, 5, 2),
+            )
+        )
         for flow_func in flow_funcs:
-            T = nx.gomory_hu_tree(G, capacity='weight', flow_func=flow_func)
+            T = nx.gomory_hu_tree(G, capacity="weight", flow_func=flow_func)
             assert nx.is_tree(T)
             for u, v in combinations(G, 2):
                 cut_value, edge = self.minimum_edge_weight(T, u, v)
-                assert (nx.minimum_cut_value(G, u, v, capacity='weight') ==
-                        cut_value)
+                assert nx.minimum_cut_value(G, u, v, capacity="weight") == cut_value
 
     def test_directed_raises(self):
         with pytest.raises(nx.NetworkXNotImplemented):
diff --git a/networkx/algorithms/flow/tests/test_maxflow_large_graph.py b/networkx/algorithms/flow/tests/test_maxflow_large_graph.py
index e152cb50..dceba17b 100644
--- a/networkx/algorithms/flow/tests/test_maxflow_large_graph.py
+++ b/networkx/algorithms/flow/tests/test_maxflow_large_graph.py
@@ -30,29 +30,27 @@ def gen_pyramid(N):
     G = nx.DiGraph()
 
     for i in range(N - 1):
-        cap = 1. / (i + 2)
+        cap = 1.0 / (i + 2)
         for j in range(i + 1):
-            G.add_edge((i, j), (i + 1, j),
-                       capacity=cap)
-            cap = 1. / (i + 1) - cap
-            G.add_edge((i, j), (i + 1, j + 1),
-                       capacity=cap)
-            cap = 1. / (i + 2) - cap
+            G.add_edge((i, j), (i + 1, j), capacity=cap)
+            cap = 1.0 / (i + 1) - cap
+            G.add_edge((i, j), (i + 1, j + 1), capacity=cap)
+            cap = 1.0 / (i + 2) - cap
 
     for j in range(N):
-        G.add_edge((N - 1, j), 't')
+        G.add_edge((N - 1, j), "t")
 
     return G
 
 
 def read_graph(name):
     dirname = os.path.dirname(__file__)
-    path = os.path.join(dirname, name + '.gpickle.bz2')
+    path = os.path.join(dirname, name + ".gpickle.bz2")
     return nx.read_gpickle(path)
 
 
 def validate_flows(G, s, t, soln_value, R, flow_func):
-    flow_value = R.graph['flow_value']
+    flow_value = R.graph["flow_value"]
     flow_dict = build_flow_dict(G, R)
     assert soln_value == flow_value, msg.format(flow_func.__name__)
     assert set(G) == set(flow_dict), msg.format(flow_func.__name__)
@@ -61,7 +59,9 @@ def validate_flows(G, s, t, soln_value, R, flow_func):
     excess = {u: 0 for u in flow_dict}
     for u in flow_dict:
         for v, flow in flow_dict[u].items():
-            assert flow <= G[u][v].get('capacity', float('inf')), msg.format(flow_func.__name__)
+            assert flow <= G[u][v].get("capacity", float("inf")), msg.format(
+                flow_func.__name__
+            )
             assert flow >= 0, msg.format(flow_func.__name__)
             excess[u] -= flow
             excess[v] += flow
@@ -75,16 +75,15 @@ def validate_flows(G, s, t, soln_value, R, flow_func):
 
 
 class TestMaxflowLargeGraph:
-
     def test_complete_graph(self):
         N = 50
         G = nx.complete_graph(N)
-        nx.set_edge_attributes(G, 5, 'capacity')
-        R = build_residual_network(G, 'capacity')
+        nx.set_edge_attributes(G, 5, "capacity")
+        R = build_residual_network(G, "capacity")
         kwargs = dict(residual=R)
 
         for flow_func in flow_funcs:
-            kwargs['flow_func'] = flow_func
+            kwargs["flow_func"] = flow_func
             flow_value = nx.maximum_flow_value(G, 1, 2, **kwargs)
             assert flow_value == 5 * (N - 1), msg.format(flow_func.__name__)
 
@@ -92,56 +91,55 @@ class TestMaxflowLargeGraph:
         N = 10
         # N = 100 # this gives a graph with 5051 nodes
         G = gen_pyramid(N)
-        R = build_residual_network(G, 'capacity')
+        R = build_residual_network(G, "capacity")
         kwargs = dict(residual=R)
 
         for flow_func in flow_funcs:
-            kwargs['flow_func'] = flow_func
-            flow_value = nx.maximum_flow_value(G, (0, 0), 't', **kwargs)
-            assert almost_equal(flow_value, 1.), msg.format(flow_func.__name__)
+            kwargs["flow_func"] = flow_func
+            flow_value = nx.maximum_flow_value(G, (0, 0), "t", **kwargs)
+            assert almost_equal(flow_value, 1.0), msg.format(flow_func.__name__)
 
     def test_gl1(self):
-        G = read_graph('gl1')
+        G = read_graph("gl1")
         s = 1
         t = len(G)
-        R = build_residual_network(G, 'capacity')
+        R = build_residual_network(G, "capacity")
         kwargs = dict(residual=R)
 
         # do one flow_func to save time
         flow_func = flow_funcs[0]
-        validate_flows(G, s, t, 156545, flow_func(G, s, t, **kwargs),
-                       flow_func)
-#        for flow_func in flow_funcs:
-#            validate_flows(G, s, t, 156545, flow_func(G, s, t, **kwargs),
-#                           flow_func)
+        validate_flows(G, s, t, 156545, flow_func(G, s, t, **kwargs), flow_func)
+
+    #        for flow_func in flow_funcs:
+    #            validate_flows(G, s, t, 156545, flow_func(G, s, t, **kwargs),
+    #                           flow_func)
 
     def test_gw1(self):
-        G = read_graph('gw1')
+        G = read_graph("gw1")
         s = 1
         t = len(G)
-        R = build_residual_network(G, 'capacity')
+        R = build_residual_network(G, "capacity")
         kwargs = dict(residual=R)
 
         for flow_func in flow_funcs:
-            validate_flows(G, s, t, 1202018, flow_func(G, s, t, **kwargs),
-                           flow_func)
+            validate_flows(G, s, t, 1202018, flow_func(G, s, t, **kwargs), flow_func)
 
     def test_wlm3(self):
-        G = read_graph('wlm3')
+        G = read_graph("wlm3")
         s = 1
         t = len(G)
-        R = build_residual_network(G, 'capacity')
+        R = build_residual_network(G, "capacity")
         kwargs = dict(residual=R)
 
         # do one flow_func to save time
         flow_func = flow_funcs[0]
-        validate_flows(G, s, t, 11875108, flow_func(G, s, t, **kwargs),
-                       flow_func)
-#        for flow_func in flow_funcs:
-#            validate_flows(G, s, t, 11875108, flow_func(G, s, t, **kwargs),
-#                           flow_func)
+        validate_flows(G, s, t, 11875108, flow_func(G, s, t, **kwargs), flow_func)
+
+    #        for flow_func in flow_funcs:
+    #            validate_flows(G, s, t, 11875108, flow_func(G, s, t, **kwargs),
+    #                           flow_func)
 
     def test_preflow_push_global_relabel(self):
-        G = read_graph('gw1')
+        G = read_graph("gw1")
         R = preflow_push(G, 1, len(G), global_relabel_freq=50)
-        assert R.graph['flow_value'] == 1202018
+        assert R.graph["flow_value"] == 1202018