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""""""
from typing import Dict
from ...ec.curve import EllipticCurve
from ...ec.formula import Formula
from ...ec.context import DefaultContext, local
from .zvp import unroll_formula
from operator import itemgetter, attrgetter
def formula_similarity(one: Formula, other: Formula) -> Dict[str, float]:
if one.coordinate_model != other.coordinate_model:
raise ValueError("Mismatched coordinate model.")
one_unroll = unroll_formula(one)
other_unroll = unroll_formula(other)
one_results = {name: None for name in one.outputs}
for name, value in one_unroll:
if name in one_results:
one_results[name] = value
other_results = {name: None for name in other.outputs}
for name, value in other_unroll:
if name in other_results:
other_results[name] = value
one_result_polys = set(one_results.values())
other_result_polys = set(other_results.values())
one_polys = set(map(itemgetter(1), one_unroll))
other_polys = set(map(itemgetter(1), other_unroll))
return {
"output": len(one_result_polys.intersection(other_result_polys))
/ max(len(one_result_polys), len(other_result_polys)),
"ivs": len(one_polys.intersection(other_polys))
/ max(len(one_polys), len(other_polys)),
}
def formula_similarity_fuzz(
one: Formula, other: Formula, curve: EllipticCurve, samples: int = 1000
) -> Dict[str, float]:
if one.coordinate_model != other.coordinate_model:
raise ValueError("Mismatched coordinate model.")
output_matches = 0.0
iv_matches = 0.0
for _ in range(samples):
P = curve.affine_random().to_model(one.coordinate_model, curve)
Q = curve.affine_random().to_model(other.coordinate_model, curve)
with local(DefaultContext()) as ctx:
res_one = one(curve.prime, P, Q, **curve.parameters)
action_one = ctx.actions.get_by_index([0])
ivs_one = set(
map(attrgetter("value"), sum(action_one[0].intermediates.values(), []))
)
with local(DefaultContext()) as ctx:
res_other = other(curve.prime, P, Q, **curve.parameters)
action_other = ctx.actions.get_by_index([0])
ivs_other = set(
map(attrgetter("value"), sum(action_other[0].intermediates.values(), []))
)
iv_matches += len(ivs_one.intersection(ivs_other)) / max(len(ivs_one), len(ivs_other))
one_coords = set(res_one)
other_coords = set(res_other)
output_matches += len(one_coords.intersection(other_coords)) / max(len(one_coords), len(other_coords))
return {
"output": output_matches / samples,
"ivs": iv_matches / samples
}
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