guzhujushi
658b266614
L0 第 2 项落地。 - get_rng(int) 固定种子可复现；get_rng(Generator) 原样透传； get_rng() 跟随 set_seed 设过的全局种子，没设过则交给系统熵源 - set_seed(seed) 除记录 _GLOBAL_SEED 外，还调用 np.random.seed， 让 sklearn / statsmodels 这些走 numpy 旧全局状态的库也能复现； 这是全项目唯一碰旧接口的位置，标注了 noqa: NPY002 与理由 - 已知取舍写进 docstring：同一全局种子下多次 get_rng() 是同一条流 - tests/test_core.py：TestRandom 去掉 skip；把原来那条自证式的 test_set_seed_makes_global_reproducible 换成两条真断言 （不传 random_state 也要可复现、旧全局状态被覆盖） - STATUS.md：L0 进度 2/12，新增决策 23（允许 set_seed 碰旧接口） 与 24（不做 SeedSequence.spawn 拆分）；CHANGELOG.md 同步
118 lines
3.8 KiB
Python
118 lines
3.8 KiB
Python
"""core 包测试。
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TODO(L0)：TestValidate 实现后去掉 skip 标记（Result 与 Random 已完成）。
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"""
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from __future__ import annotations
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import numpy as np
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import pytest
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class TestRandom:
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def test_get_rng_is_reproducible(self):
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from mcm_toolkit.core import get_rng
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assert get_rng(42).random() == get_rng(42).random()
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def test_get_rng_passes_through_generator(self):
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from mcm_toolkit.core import get_rng
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g = np.random.default_rng(0)
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assert get_rng(g) is g
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def test_get_rng_default_follows_global_seed(self):
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"""set_seed 之后，不传 random_state 也必须复现——这是"论文能重跑"的底线。"""
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from mcm_toolkit.core import get_rng, set_seed
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set_seed(7)
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first = get_rng().random()
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set_seed(7)
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second = get_rng().random()
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assert first == second
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def test_set_seed_also_covers_third_party_global_state(self):
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"""sklearn / statsmodels 走的是 np.random 旧全局，set_seed 要连它一起覆盖。"""
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from mcm_toolkit.core import set_seed
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set_seed(7)
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first = np.random.random() # noqa: NPY002 - 这里就是要验证旧全局被设上了
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set_seed(7)
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second = np.random.random() # noqa: NPY002
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assert first == second
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@pytest.mark.skip(reason="未实现：见 docs/03-roadmap.md L0")
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class TestValidate:
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def test_check_same_length_raises_with_detail(self):
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from mcm_toolkit.core import check_same_length
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with pytest.raises(ValueError, match=r"2.*3|长度"):
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check_same_length([1, 2], [1, 2, 3])
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def test_check_array_rejects_nan(self):
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from mcm_toolkit.core import check_array
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with pytest.raises(ValueError):
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check_array([1.0, np.nan, 2.0], finite=True)
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def test_check_probability_bounds(self):
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from mcm_toolkit.core import check_probability
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assert check_probability(0.5) == 0.5
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with pytest.raises(ValueError):
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check_probability(1.5)
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def test_check_square_matrix(self):
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from mcm_toolkit.core import check_square_matrix
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check_square_matrix([[1, 2], [3, 4]])
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with pytest.raises(ValueError):
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check_square_matrix([[1, 2, 3], [4, 5, 6]])
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def test_result_repr_is_readable():
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from mcm_toolkit.core import Result
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text = repr(Result("demo", params={"a": 1}, metrics={"r2": 0.9}))
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# 只断言关键信息在场，不断言完整字符串——否则以后调格式会让测试集体变红
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assert "demo" in text and "r2" in text
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def test_result_repr_stays_short_and_safe():
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"""默认值、失败结果、十万级数组：repr 都不能崩，也不能刷屏。"""
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from mcm_toolkit.core import Result
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assert "empty" in repr(Result("empty"))
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failed = repr(Result("boom", success=False, message="求解未收敛"))
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assert "success=False" in failed
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assert "求解未收敛" in failed
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noisy = repr(Result("mc", data=np.arange(100_000)))
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assert "ndarray(100000)" in noisy
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assert len(noisy) < 200, "data 不应被整个打印出来"
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def test_result_summary_is_markdown_table():
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from mcm_toolkit.core import Result
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result = Result("topsis", params={"n": 3}, metrics={"best": 0.83})
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text = result.summary()
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lines = text.splitlines()
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assert lines[0] == "### topsis"
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assert lines[2] == "| 项 | 值 |"
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assert "| success | True |" in lines
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assert "| params.n | 3 |" in lines
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assert "| metrics.best | 0.83 |" in lines
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assert result.summary() == text, "summary 必须无副作用、可重复调用"
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def test_result_summary_appends_message_on_failure():
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from mcm_toolkit.core import Result
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text = Result("gm11", success=False, message="样本太少").summary()
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assert "| success | False |" in text
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assert text.rstrip().endswith("> 样本太少")
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