new test for n2 matching

tests/test_methods.py

@@ -521,3 +521,57 @@ def test_extra_match(self):
         assert np.isclose(dis.tpr, n2_match_span / true_spans[1])
         assert np.isclose(dis.dissimilarity, true_spans[0] - n1_match_span)
         assert np.isclose(dis.inverse_dissimilarity, true_spans[1] - n2_match_span)
+
+    def get_n2_match_ex(self, samples=None, extra_nodes=False):
+        node_times = {
+            0: 0.0,
+            1: 0.0,
+            2: 0.0,
+            3: 100.0,
+            4: 200.0,
+        }
+        if extra_nodes:
+            node_times[5] = 300.0
+            # (p, c, l, r) ordered by p[time]
+            edges = [
+                (3, 0, 0, 3),
+                (3, 1, 0, 3),
+                (4, 3, 0, 3),
+                (5, 2, 0, 3),
+                (5, 4, 0, 3)
+            ]
+        else:
+            edges = [
+                (3, 0, 0, 3),
+                (3, 1, 0, 3),
+                (4, 2, 0, 3),
+                (4, 3, 0, 3)
+            ]
+        tables = tskit.TableCollection(sequence_length=3)
+        if samples is None:
+            samples = [0, 1, 2]
+        for (
+            n,
+            t,
+        ) in node_times.items():
+            flags = tskit.NODE_IS_SAMPLE if n in samples else 0
+            tables.nodes.add_row(time=t, flags=flags)
+        for p, c, l, r in edges:
+            tables.edges.add_row(parent=p, child=c, left=l, right=r)
+        ts = tables.tree_sequence()
+        if extra_nodes is True:
+            assert ts.num_edges == 5
+        if extra_nodes is False:
+            assert ts.num_edges == 4
+        return ts
+
+    def test_n2_matching(self):
+        ts = self.get_n2_match_ex()
+        other = self.get_n2_match_ex(extra_nodes=True)
+        dis = tscompare.compare(ts, other, transform=None)
+        true_spans = (15, 18)
+        match_spans = (15, 15)
+        assert np.isclose(dis.arf, 1 - match_spans[0]/true_spans[0])
+        assert np.isclose(dis.tpr, match_spans[1]/true_spans[1])
+        assert np.isclose(dis.dissimilarity, true_spans[0] - match_spans[0])
+        assert np.isclose(dis.inverse_dissimilarity, true_spans[1] - match_spans[1])