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Quick perf pass #169

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Quick perf pass #169

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29 changes: 20 additions & 9 deletions tstrait/genetic_value.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,23 +10,33 @@
def _compute_nodes_genetic_value(
left_child_array,
right_sib_array,
stack,
seed_nodes,
has_mutation,
num_nodes,
effect_size,
): # pragma: no cover
"""
Compute the genetic value of each node for the specified set of mutations
encoded in the stack.
encoded in ``seed_nodes``.
"""
genetic_value = np.zeros(num_nodes)
while len(stack) > 0:
parent_node_id = stack.pop()
stack = np.empty(num_nodes, dtype=np.int64)
top = 0

# Initialise stack with seed nodes.
for i in range(seed_nodes.shape[0]):
stack[top] = seed_nodes[i]
top += 1

while top > 0:
top -= 1
parent_node_id = stack[top]
genetic_value[parent_node_id] = effect_size
child_node_id = left_child_array[parent_node_id]
while child_node_id != -1:
if not has_mutation[child_node_id]:
stack.append(child_node_id)
stack[top] = child_node_id
top += 1
child_node_id = right_sib_array[child_node_id]
return genetic_value

Expand Down Expand Up @@ -72,18 +82,19 @@ def _individual_genetic_values(self, tree, site, causal_allele, effect_size):
for m in site.mutations:
state_transitions[m.node] = m.derived_state
has_mutation[m.node] = True
stack = numba.typed.List()
seed_nodes = []
for node, allele in state_transitions.items():
if allele == causal_allele:
stack.append(node)
seed_nodes.append(node)

if len(stack) == 0:
if len(seed_nodes) == 0:
genetic_value = np.zeros(self.ts.num_nodes)
else:
seed_nodes_array = np.array(seed_nodes, dtype=np.int64)
genetic_value = _compute_nodes_genetic_value(
left_child_array=tree.left_child_array,
right_sib_array=tree.right_sib_array,
stack=stack,
seed_nodes=seed_nodes_array,
has_mutation=has_mutation,
num_nodes=self.ts.num_nodes,
effect_size=effect_size,
Expand Down