|
| 1 | +"""Tests for _score_params to guard against parameter passing regressions.""" |
| 2 | + |
| 3 | +import numpy as np |
| 4 | +import pytest |
| 5 | + |
| 6 | +from hyperactive.opt._common import _score_params |
| 7 | + |
| 8 | + |
| 9 | +class _DictExperiment: |
| 10 | + """Minimal experiment stub that expects params as a single dict.""" |
| 11 | + |
| 12 | + def __call__(self, params): |
| 13 | + return params["x"] ** 2 + params["y"] ** 2 |
| 14 | + |
| 15 | + |
| 16 | +class _DictOnlyExperiment: |
| 17 | + """Experiment stub that rejects keyword arguments. |
| 18 | +
|
| 19 | + Fails loudly if params are passed as **kwargs instead of a dict, |
| 20 | + directly guarding against the ``experiment(**params)`` bug. |
| 21 | + """ |
| 22 | + |
| 23 | + def __call__(self, params): |
| 24 | + if not isinstance(params, dict): |
| 25 | + raise TypeError( |
| 26 | + f"Expected a dict, got {type(params).__name__}. " |
| 27 | + "Parameters must be passed as a single dict, not as **kwargs." |
| 28 | + ) |
| 29 | + return sum(v**2 for v in params.values()) |
| 30 | + |
| 31 | + |
| 32 | +def _make_meta(experiment, error_score=np.nan): |
| 33 | + return {"experiment": experiment, "error_score": error_score} |
| 34 | + |
| 35 | + |
| 36 | +class TestScoreParams: |
| 37 | + """Tests for the _score_params helper function.""" |
| 38 | + |
| 39 | + def test_params_passed_as_dict(self): |
| 40 | + """Params must be passed as a single dict, not unpacked as **kwargs.""" |
| 41 | + exp = _DictOnlyExperiment() |
| 42 | + meta = _make_meta(exp) |
| 43 | + params = {"x": 3.0, "y": 4.0} |
| 44 | + |
| 45 | + score = _score_params(params, meta) |
| 46 | + |
| 47 | + assert score == 25.0 |
| 48 | + |
| 49 | + def test_returns_correct_score(self): |
| 50 | + """Score must match the experiment's return value.""" |
| 51 | + exp = _DictExperiment() |
| 52 | + meta = _make_meta(exp) |
| 53 | + |
| 54 | + assert _score_params({"x": 0.0, "y": 0.0}, meta) == 0.0 |
| 55 | + assert _score_params({"x": 1.0, "y": 0.0}, meta) == 1.0 |
| 56 | + assert _score_params({"x": 3.0, "y": 4.0}, meta) == 25.0 |
| 57 | + |
| 58 | + def test_returns_python_float(self): |
| 59 | + """Return type must be a Python float, not numpy scalar.""" |
| 60 | + exp = _DictExperiment() |
| 61 | + meta = _make_meta(exp) |
| 62 | + |
| 63 | + result = _score_params({"x": 1.0, "y": 1.0}, meta) |
| 64 | + assert type(result) is float |
| 65 | + |
| 66 | + def test_error_score_on_exception(self): |
| 67 | + """When the experiment raises, error_score must be returned.""" |
| 68 | + |
| 69 | + def _failing_experiment(params): |
| 70 | + raise ValueError("intentional failure") |
| 71 | + |
| 72 | + meta = _make_meta(_failing_experiment, error_score=-999.0) |
| 73 | + |
| 74 | + with pytest.warns(match="intentional failure"): |
| 75 | + result = _score_params({"x": 1.0}, meta) |
| 76 | + |
| 77 | + assert result == -999.0 |
| 78 | + |
| 79 | + def test_error_score_emits_warning(self): |
| 80 | + """A caught exception must produce a warning, never be silent.""" |
| 81 | + |
| 82 | + def _failing_experiment(params): |
| 83 | + raise RuntimeError("boom") |
| 84 | + |
| 85 | + meta = _make_meta(_failing_experiment, error_score=np.nan) |
| 86 | + |
| 87 | + with pytest.warns(match="RuntimeError"): |
| 88 | + _score_params({"x": 1.0}, meta) |
| 89 | + |
| 90 | + def test_many_params_passed_as_dict(self): |
| 91 | + """Regression: many keys must not be unpacked as keyword arguments. |
| 92 | +
|
| 93 | + With the old ``experiment(**params)`` bug, this would raise |
| 94 | + TypeError inside __call__ because it only accepts one argument. |
| 95 | + """ |
| 96 | + |
| 97 | + def _sum_experiment(params): |
| 98 | + return sum(params.values()) |
| 99 | + |
| 100 | + meta = _make_meta(_sum_experiment) |
| 101 | + params = {f"x{i}": float(i) for i in range(20)} |
| 102 | + |
| 103 | + score = _score_params(params, meta) |
| 104 | + |
| 105 | + assert score == float(sum(range(20))) |
| 106 | + |
| 107 | + def test_with_base_experiment(self): |
| 108 | + """Integration: works with a real BaseExperiment subclass.""" |
| 109 | + from hyperactive.experiment.bench import Sphere |
| 110 | + |
| 111 | + exp = Sphere(n_dim=2) |
| 112 | + meta = _make_meta(exp) |
| 113 | + |
| 114 | + # Sphere minimum is at origin, value = 0 |
| 115 | + # __call__ returns sign-adjusted score (higher is better) |
| 116 | + # Sphere is lower-is-better, so score = -evaluate |
| 117 | + score_origin = _score_params({"x0": 0.0, "x1": 0.0}, meta) |
| 118 | + score_away = _score_params({"x0": 3.0, "x1": 4.0}, meta) |
| 119 | + |
| 120 | + assert score_origin > score_away |
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