Equivalence

tests/test_counting.py

@@ -7,6 +7,7 @@
 
 import numpy as np
 import pandas as pd
+import networkx as nx
 from scipy.sparse import csr_matrix
 
 @pytest.fixture
@@ -54,6 +55,7 @@ def smp_star():
     smp = MatchingProblem(tmplt, world)
     return smp
 
+
 @pytest.fixture
 def smp_node_cover():
     """Create a subgraph matching problem requiring the use of node cover."""
@@ -178,3 +180,44 @@ def test_count_isomorphisms_overlapping_cands(self, smp_overlapping_cands):
         assert np.sum(smp_overlapping_cands.candidates()) == 7
         count = count_isomorphisms(smp_overlapping_cands, verbose=True)
         assert count == 6
+
+    def test_count_isomorphisms_random_all_matches(self):
+        """
+        Perform a test where every possible mapping of template to world nodes
+        is a match.
+        """
+        for i in range(10):
+            random_adj = np.random.random((5, 5))
+            # No self loops
+            np.fill_diagonal(random_adj, 0)
+            t_graph = Graph([csr_matrix(random_adj)])
+
+            complete_graph = nx.complete_graph(5)
+            w_graph = uclasm.from_networkx_graph(complete_graph)
+
+            smp = MatchingProblem(t_graph, w_graph)
+
+            count = count_isomorphisms(smp, verbose=True)
+            assert count == 120 # 5 factorial
+
+            eq_count = count_isomorphisms(smp, verbose=True, tmplt_equivalence=True)
+            assert count == 120
+
+    def test_count_isomorphisms_random_no_matches(self):
+        for i in range(10):
+            random_adj = np.random.random((5, 5))
+            # No self loops
+            np.fill_diagonal(random_adj, 0)
+            t_graph = Graph([csr_matrix(random_adj)])
+
+            empty_adj = csr_matrix(np.zeros((5,5)))
+            w_graph = Graph([empty_adj])
+
+            smp = MatchingProblem(t_graph, w_graph)
+
+            count = count_isomorphisms(smp, verbose=True)
+            assert count == 0
+
+            eq_count = count_isomorphisms(smp, verbose=True, tmplt_equivalence=True)
+            assert count == 0
+

tests/test_equivalence.py

@@ -0,0 +1,58 @@
+"""
+Tests for structural equivalence.
+"""
+import pytest
+import networkx as nx
+
+from uclasm.graph import from_networkx_graph
+
+
+@pytest.fixture
+def star_graph_5():
+    """
+    Creates the star graph S5, the graph with 1 central node and 5 spokes.
+    The node with index 0 should be the central node.
+    """
+    star_graph = nx.star_graph(5)
+    return from_networkx_graph(star_graph)
+
+
+@pytest.fixture
+def complete_graph_5():
+    """
+    Creates the complete graph K5, the graph with 5 nodes each connected to
+    every other node.
+    """
+    complete_graph = nx.complete_graph(5)
+    return from_networkx_graph(complete_graph)
+
+
+@pytest.fixture
+def path_graph_5():
+    """
+    Creates the path graph P5, the path graph with 5 nodes.
+    """
+    path_graph = nx.path_graph(5)
+    return from_networkx_graph(path_graph)
+
+
+def test_star_graph_equivalence(star_graph_5):
+    equiv = star_graph_5.equivalence_classes
+    assert len(equiv.classes) == 2
+    assert equiv.classes[0] == {0}
+    rep_1 = equiv.representative(1)
+    assert equiv.classes[rep_1] == {1,2,3,4,5}
+
+
+def test_complete_graph_equivalence(complete_graph_5):
+    equiv = complete_graph_5.equivalence_classes
+    assert len(equiv.classes) == 1
+    rep = equiv.representative(0)
+    assert equiv.classes[rep] == {0,1,2,3,4}
+
+
+def test_path_graph_equivalence(path_graph_5):
+    equiv = path_graph_5.equivalence_classes
+    assert len(equiv.classes) == 5
+    for i in range(5):
+        assert equiv.classes[i] == {i}

uclasm/__init__.py

@@ -7,3 +7,4 @@
 from .utils import *
 from .matching import *
 from .interface import *
+from .equivalence import *