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@mmore500
Created February 7, 2023 05:34
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def _estimate_rank_of_mrca_between_unbiased(
first: HereditaryStratigraphicColumn,
second: HereditaryStratigraphicColumn,
) -> typing.Optional[float]:
ranks_of_retained_commonality_between = [
*iter_ranks_of_retained_commonality_between_generic(first, second)
]
if not ranks_of_retained_commonality_between:
return None
rank_of_first_retained_disparity_between = (
calc_rank_of_first_retained_disparity_between(
first,
second,
confidence_level=0.1, # TODO why can't this be set to 0.0?
)
)
waypoints_descending = [
rank_of_first_retained_disparity_between - 1,
*reversed(ranks_of_retained_commonality_between),
]
exclusive_ub_correction = 1 / 2
expected_ranks = (
np.array(
[
waypoints_descending[:-1],
waypoints_descending[1:],
]
).mean(axis=1)
- exclusive_ub_correction
)
base = 1 / 2 ** first.GetStratumDifferentiaBitWidth()
weights = np.logspace(
0,
len(expected_ranks),
base=base,
num=len(expected_ranks),
endpoint=False,
)
# index of weights corresponds to num spurious collisions
return np.average(expected_ranks, weights=weights)
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