def score_linked_tree(tree, neighbor_indices):
result = 0.0
n_nodes = len(tree.children)
for i in numba.prange(n_nodes):
node = numba.int32(i)
left_child = tree.children[node][0]
right_child = tree.children[node][1]
if left_child == -1 and right_child == -1:
for j in range(tree.indices[node].shape[0]):
idx = tree.indices[node][j]
intersection = arr_intersect(neighbor_indices[idx], tree.indices[node])
result += numba.float32(intersection.shape[0] > 1)
return result / numba.float32(neighbor_indices.shape[0])
def score_tree(tree, neighbor_indices, data, rng_state):
result = 0.0
for i in numba.prange(neighbor_indices.shape[0]):
leaf_indices = search_flat_tree(
data[i],
tree.hyperplanes,
tree.offsets,
tree.children,
tree.indices,
rng_state,
)
intersection = arr_intersect(neighbor_indices[i], leaf_indices)
result += numba.float32(intersection.shape[0] > 1)
return result / numba.float32(neighbor_indices.shape[0])
