Simplify testing checks

tests/test_graph_utils.py

@@ -1,38 +1,25 @@
 import numpy as np
 
 
-def _sort_key(x):
-    return str(x)
-
-
 def check_solution_pandas(solution, candidates):
     # Checks whether the solution (`pd.Series`) matches any of the list of
-    # candidates (containing `dict`)
-    if any(
-        sorted(list(zip(solution.index.to_list(), solution.to_list())), key=_sort_key)
-        == sorted(c, key=_sort_key)
-        for c in candidates
-    ):
-        return True
-    return False
+    # candidates. Each candidate is a list of tuples ((i, j), v) tuples,
+    # compare with the solution in sorted order.
+    solution_list = sorted(solution.items())
+    return any(solution_list == sorted(candidate) for candidate in candidates)
 
 
 def check_solution_scipy(solution, candidates):
     # Checks whether the solution (`sp.sparray`) matches any of the list of
     # candidates (containing `np.ndarray`)
     arr = solution.toarray()
-    if any(np.array_equal(arr, c) for c in candidates):
-        return True
-    return False
+    return any(np.array_equal(arr, c) for c in candidates)
 
 
 def check_solution_networkx(solution, candidates):
     # Checks whether the solution (`nx.DiGraph`) matches any of the list of
     # candidates (containing tuples dict `{(i, j): data}`)
-    sol_list = sorted(
+    solution_list = sorted(
         [((i, j), data["flow"]) for i, j, data in solution.edges(data=True)],
-        key=_sort_key,
     )
-    if any(sol_list == sorted(c, key=_sort_key) for c in candidates):
-        return True
-    return False
+    return any(solution_list == sorted(candidate) for candidate in candidates)