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pqcli used Python's global Mersenne Twister, seeded once from the clock. Upstream uses Johannes Baagøe's Alea, with Random(n) = uint32() % n, and keeps the generator state with each character. The port matches the JS output bit for bit, including UTF-16 seeding of non-BMP characters. Each Player now owns an Alea that is pickled with the save, and Simulation.tick draws from it. Saves without one get a fresh generator. As upstream does, a new character's game continues from the state the kept stat roll was made from. The parity traces are re-recorded, since every random number changes.
89 lines
2.3 KiB
Python
89 lines
2.3 KiB
Python
import pickle
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import pytest
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from pqcli import random
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from pqcli.random import Alea
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# First outputs and resulting state of upstream's JS Alea(seed).uint32()
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VECTORS = {
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"alpha": (
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[3768637044, 756790225, 3147161637, 1726577786, 279486812],
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(0.732755669625476, 0.4020002172328532, 0.06507309433072805, 368555),
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),
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"": (
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[715789690, 2091287642, 486307, 3866591158, 760028033],
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(
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0.00011322717182338238,
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0.9002609080635011,
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0.17695781611837447,
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1018452,
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),
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),
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"1697543210123": (
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[3110287155, 2843160345, 1794106530, 2361562046, 1804721005],
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(
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0.41772297816351056,
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0.5498440111987293,
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0.42019435320980847,
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1384612,
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),
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),
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# Mash hashes UTF-16 code units, so the dragon counts as two
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"Ünïcødé 🐉": (
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[4162081648, 198215584, 541466577, 6418444, 2254846220],
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(
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0.12607001163996756,
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0.0014944104477763176,
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0.5249972967430949,
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96530,
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),
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),
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}
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@pytest.mark.parametrize("seed", VECTORS)
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def test_alea_matches_upstream(seed: str) -> None:
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first, state = VECTORS[seed]
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rng = Alea(seed)
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assert [rng.uint32() for _ in first] == first
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assert rng.state() == state
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def test_alea_state_round_trip() -> None:
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rng = Alea("alpha")
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rng.uint32()
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copy = Alea.from_state(rng.state())
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assert [copy.uint32() for _ in range(100)] == [
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rng.uint32() for _ in range(100)
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]
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def test_alea_pickles_with_its_state() -> None:
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rng = Alea("alpha")
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rng.uint32()
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copy = pickle.loads(pickle.dumps(rng))
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assert copy.state() == rng.state()
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def test_unseeded_alea_differs() -> None:
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assert Alea().state() != Alea("alpha").state()
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def test_below_is_uint32_modulo() -> None:
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# Random(n) = seed.uint32() % n
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random.seed("alpha")
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assert [random.below(1000) for _ in range(5)] == [
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n % 1000 for n in VECTORS["alpha"][0]
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]
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def test_using_restores_previous_generator() -> None:
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random.seed("outer")
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expected = Alea("outer").uint32() % 1000
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inner = Alea("inner")
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with random.using(inner):
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random.below(10)
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assert inner.state() != Alea("inner").state()
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assert random.below(1000) == expected
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