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MCM-ICM_Toolkit/tests/test_models.py
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guzhujushi 5319589dfd chore: 初始化 MCM/ICM Toolkit 仓库骨架
审查并精简 ChatGPT 的建库建议后落地的第一版骨架,只定接口不写实现。

- 建议审查:14 个包 → 7 个;约 250 个函数 → 约 40 个;5 个 Result 类 → 1 个
  (docs/01-suggestion-review.md)
- docs/:架构、路线图(含永久不做清单)、环境、Git 工作流、函数卡片模板
- src/mcm_toolkit/:core / data / stats / models / solve / decision / viz
  共 23 个模块,均为签名 + docstring + NotImplementedError
- tests/:9 个文件,其中 test_api_surface.py 已通过(20 passed)
- examples/ problems/ notebooks/ figures/ tables/ 骨架
- pyproject.toml(核心依赖 4 个 + 6 组 extras)、environment.yml
- scripts/:setup-venv.ps1(ASCII + LF)、setup-conda.ps1、doctor.ps1
- 环境:.venv(system-site-packages)与 conda 环境 mcm-toolkit 均已建好,
  数值栈版本与 base 完全对齐(numpy 2.4.6 / scipy 1.18.1 / pandas 3.0.6,MKL 后端)
2026-10-01 17:43:48 +08:00

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Python

"""models 包测试。"""
from __future__ import annotations
import numpy as np
import pytest
pytestmark = pytest.mark.skip(reason="未实现:见 docs/03-roadmap.md L1")
def test_fit_linear_recovers_known_coefficients(linear_data):
"""真值 y = 2x + 1,拟合系数应在 1% 内。"""
from mcm_toolkit.models import fit_linear
x, y = linear_data
r = fit_linear(x.reshape(-1, 1), y)
assert np.isclose(r.params["coef"][0], 2.0, rtol=0.01)
assert np.isclose(r.params["intercept"], 1.0, atol=0.05)
def test_fit_polynomial_matches_numpy(linear_data):
from mcm_toolkit.models import fit_polynomial
x, y = linear_data
r = fit_polynomial(x.reshape(-1, 1), y, degree=2)
assert np.allclose(r.params["coef"], np.polyfit(x, y, 2), rtol=1e-6)
def test_metrics_known_values():
from mcm_toolkit.models import mae, r2_score, rmse
y_true = np.array([1.0, 2.0, 3.0])
y_pred = np.array([1.0, 2.0, 5.0])
assert np.isclose(rmse(y_true, y_pred), np.sqrt(4 / 3))
assert np.isclose(mae(y_true, y_pred), 2 / 3)
assert r2_score(y_true, y_pred) < 1.0
def test_r2_is_one_for_perfect_fit():
from mcm_toolkit.models import r2_score
y = np.array([1.0, 2.0, 3.0, 4.0])
assert np.isclose(r2_score(y, y), 1.0)
def test_compare_models_returns_table_sorted_by_first_metric(linear_data):
from mcm_toolkit.models import compare_models, fit_linear, fit_polynomial
x, y = linear_data
X = x.reshape(-1, 1)
tbl = compare_models(
{"linear": fit_linear(X, y), "poly2": fit_polynomial(X, y, degree=2)},
X,
y,
cv=0,
)
assert set(tbl.index) >= {"linear", "poly2"}
assert "rmse" in tbl.columns