Throw prune_selected into the test matrix.

tests/test_ancient_samples_with_neutral_mutations.py

@@ -100,12 +100,17 @@ def simplification_inteval(request):
     return request.param
 
 
+@pytest.fixture(params=[True, False])
+def prune_selected(request):
+    return request.param
+
+
 @pytest.mark.parametrize("rng", [{"seed": 101 * 45 * 110 * 210}], indirect=True)
 @pytest.mark.parametrize(
     "mslike_pop", [{"N": 50}, {"N": 100}, {"N": 200}], indirect=True
 )
 def test_ancient_samples_and_neutral_mutations(
-    pdict, simlen, simplification_inteval, rng, mslike_pop, resetter
+    pdict, simlen, simplification_inteval, prune_selected, rng, mslike_pop, resetter
 ):
     """
     The test involving neutral mutations test GitHub issue 639 and 646
@@ -114,6 +119,7 @@ def test_ancient_samples_and_neutral_mutations(
         seed=42, samplesize=10, timepoints=[i for i in range(1, simlen + 1)]
     )
     pdict["simlen"] = simlen
+    pdict["prune_selected"] = prune_selected
     params = fwdpy11.ModelParams(**pdict)
     fwdpy11.evolvets(
         rng,
@@ -153,3 +159,5 @@ def test_ancient_samples_and_neutral_mutations(
                 assert mslike_pop.mcounts_ancient_samples[m.key] > 0
             else:
                 assert len(s) == mslike_pop.mcounts[m.key]
+                if prune_selected is True and len(s) == 2 * mslike_pop.N:
+                    assert mslike_pop.mcounts_ancient_samples[m.key] > 0