mirror of
https://github.com/logos-blockchain/research.git
synced 2026-08-07 11:43:20 +00:00
53 lines
1.8 KiB
Python
53 lines
1.8 KiB
Python
"""Private-chain reorg-depth model: effective share, closed-form tail, MC validation."""
|
|
|
|
from __future__ import annotations
|
|
|
|
import numpy as np
|
|
|
|
from tsi_sim.reorg import alpha_effective, reorg_depth_tail, simulate_deepest_reorg
|
|
|
|
|
|
def test_alpha_effective_monotone_in_orphan_rate():
|
|
# honest forks waste honest blocks -> raise the adversary's effective share
|
|
assert alpha_effective(0.2, 0.0) == 0.2
|
|
assert alpha_effective(0.2, 0.1) > 0.2
|
|
assert alpha_effective(0.2, 0.5) > alpha_effective(0.2, 0.25)
|
|
assert alpha_effective(0.0, 0.3) == 0.0 # no adversary -> no share
|
|
|
|
|
|
def test_tail_shape():
|
|
assert reorg_depth_tail(0.3, 0) == 1.0
|
|
assert reorg_depth_tail(0.0, 3) == 0.0
|
|
assert reorg_depth_tail(0.6, 5) == 1.0 # majority -> unbounded
|
|
# geometric decay: P(>=2)/P(>=1) = beta/(1-beta)
|
|
b = 0.3
|
|
assert abs(reorg_depth_tail(b, 2) / reorg_depth_tail(b, 1) - b / (1 - b)) < 1e-12
|
|
|
|
|
|
def test_reverse_d_matches_catch_up_from_behind():
|
|
"""(beta/(1-beta))**d == P(a walker starting d behind ever reaches 0) — the reorg tail."""
|
|
rng = np.random.default_rng(7)
|
|
beta, d = 0.3, 3
|
|
hits = 0
|
|
trials = 40000
|
|
horizon = 4000
|
|
up = rng.random((trials, horizon)) < beta
|
|
for row in up:
|
|
pos = -d
|
|
for step in row:
|
|
pos += 1 if step else -1
|
|
if pos >= 0:
|
|
hits += 1
|
|
break
|
|
mc = hits / trials
|
|
cf = reorg_depth_tail(beta, d)
|
|
assert abs(mc - cf) < 0.02 # 0.0937 closed form
|
|
|
|
|
|
def test_simulate_realized_depths_are_shallow_and_bounded():
|
|
rng = np.random.default_rng(1)
|
|
d = simulate_deepest_reorg(alpha_effective(0.3, 0.0), 500_000, rng)
|
|
assert d.size > 1000
|
|
assert d.min() >= 1
|
|
assert d.mean() < 2.0 # typical opportunistic reorg is ~1 deep
|