Repository navigation
genetic_value() writes past the node array when the ancestral allele is causal #191
Description
With help from an LLM, I found that genetic_value() writes past the node array when the ancestral allele is causal - in that case tree.virtual_root is used, but the output array has space only for real nodes.
Normal execution appears correct because Numba disables bounds checking by default. The existing test passes normally:
pytest -q tests/test_genetic_value.py::TestGenotype::test_allele_freq_onegiving
. [100%]
1 passed in 8.87s
but exposes the invalid write when bounds checking is enabled:
NUMBA_BOUNDSCHECK=1 pytest -q tests/test_genetic_value.py::TestGenotype::test_allele_freq_onegiving
F [100%]
========================= FAILURES ==========================
_____________ TestGenotype.test_allele_freq_one _____________
self = <tests.test_genetic_value.TestGenotype object at 0x14a900ef0>
def test_allele_freq_one(self):
ts = binary_tree()
tables = ts.dump_tables()
tables.sites.add_row(4, "A")
tables.mutations.add_row(site=4, node=0, derived_state="T")
tables.mutations.add_row(site=4, node=0, derived_state="A", parent=9)
ts = tables.tree_sequence()
trait_df = pd.DataFrame(
{
"site_id": [4],
"effect_size": [1],
"trait_id": [0],
"causal_allele": ["A"],
}
)
> genetic_result = tstrait.genetic_value(ts=ts, trait_df=trait_df)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
tests/test_genetic_value.py:454:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tstrait/genetic_value.py:219: in genetic_value
genetic_result = genetic._run(level)
^^^^^^^^^^^^^^^^^^^
tstrait/genetic_value.py:133: in _run
genetic_value = self._node_genetic_values(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <tstrait.genetic_value._GeneticValue object at 0x14a795d30>
tree = <tskit.trees.Tree object at 0x14a6cb4d0>
site = Site(id=4, position=4.0, ancestral_state='A', mutations=[Mutation(id=9, site=4, node=0, derived_state='T', parent=-1, ...d=10, site=4, node=0, derived_state='A', parent=9, metadata=b'', time=nan, edge=0, inherited_state='T')], metadata=b'')
causal_allele = 'A', effect_size = 1
def _node_genetic_values(self, tree, site, causal_allele, effect_size):
"""
Returns a numpy array with node genetic values.
"""
has_mutation = np.zeros(self.ts.num_nodes + 1, dtype=bool)
state_transitions = {tree.virtual_root: site.ancestral_state}
for m in site.mutations:
state_transitions[m.node] = m.derived_state
has_mutation[m.node] = True
stack = numba.typed.List()
for node, allele in state_transitions.items():
if allele == causal_allele:
stack.append(node)
if len(stack) == 0:
genetic_value = np.zeros(self.ts.num_nodes)
else:
> genetic_value = _compute_nodes_genetic_value(
left_child_array=tree.left_child_array,
right_sib_array=tree.right_sib_array,
stack=stack,
has_mutation=has_mutation,
num_nodes=self.ts.num_nodes,
effect_size=effect_size,
)
E IndexError: index is out of bounds
tstrait/genetic_value.py:97: IndexError
================== short test summary info ==================
FAILED tests/test_genetic_value.py::TestGenotype::test_allele_freq_one - IndexError: index is out of bounds
1 failed in 2.53s
Not sure how serious this is! The computations seem correct. I don't know where Python writes when it is out of bounds - to another random place in memory?, if so, would be good to fix this.
Activity
gregorgorjanc commentedon Sep 1, 2026
Here is a small script
giving
jeromekelleher commentedon Sep 2, 2026
I think this is probably reasonably serious and we should fix it.
jeromekelleher commentedon Sep 2, 2026
Great catch by the way!
jeromekelleher commentedon Sep 2, 2026
I'll take a look at this now.
jeromekelleher commentedon Sep 2, 2026
Closed in #192