tests/test_factor_weight_grid_search.py

import pandas as pd

from scripts.search_factor_weight_grid import _grid_from_name, candidate_passes, search_weight_grid


def _events(rows):
    return pd.DataFrame(rows)


def test_candidate_passes_requires_accuracy_precision_signal_and_buy_cap():
    baseline = {"accuracy": 50.0, "buy_precision": 60.0, "signal_count": 10, "buy_count": 5}
    candidate = {"accuracy": 53.0, "buy_precision": 61.0, "signal_count": 9, "buy_count": 6}
    deltas = {
        "accuracy_delta_pp": 3.0,
        "buy_precision_delta_pp": 1.0,
        "direction_accuracy_delta_pp": 0.0,
    }

    passed, gate = candidate_passes(
        baseline,
        candidate,
        deltas,
        min_accuracy_delta_pp=2.0,
        min_buy_precision_delta_pp=0.0,
        min_signal_ratio=0.7,
        max_buy_count_ratio=1.3,
    )

    assert passed is True
    assert gate["buy_count_ratio"] == 1.2


def test_search_weight_grid_finds_passing_weight_combination():
    rows = []
    for i in range(12):
        rows.append(
            {
                "stock": "2330",
                "date": f"2025-04-{i + 1:02d}",
                "y_true": 1 if i in {0, 1, 2, 6, 7, 8} else 0,
                "base_pred": 1 if i in {0, 1, 6} else 0,
                "p_buy": 0.52 if i in {0, 1, 6} else 0.48,
                "p_hold": 0.51 if i not in {0, 1, 6} else 0.44,
                "p_sell": 0.01,
                "bull_score": 3.0 if i in {2, 7, 8} else 0.0,
                "bear_score": 0.0,
            }
        )

    result = search_weight_grid(
        _events(rows),
        optimize_ratio=0.5,
        min_accuracy_delta_pp=20.0,
        min_buy_precision_delta_pp=0.0,
        min_signal_ratio=0.7,
        max_buy_count_ratio=3.0,
        top_n=5,
        grid={
            "buy_bull_weight": [0.0, 0.02],
            "buy_bear_weight": [0.0],
            "sell_bear_weight": [0.0],
            "sell_bull_weight": [0.0],
            "buy_bear_gate": [None],
            "sell_bull_gate": [None],
            "hold_bias": [0.0],
        },
    )

    assert result["grid_size"] == 2
    assert result["passing_count"] == 1
    assert result["best_passing"]["config"]["buy_bull_weight"] == 0.02
    assert result["best_passing"]["validation"]["deltas"]["accuracy_delta_pp"] > 0


def test_volume_fine_grid_is_available_for_volume_factor_search():
    grid = _grid_from_name("volume_fine")

    assert 0.08 in grid["buy_bull_weight"]
    assert -0.005 in grid["buy_bear_weight"]
    assert 0.005 in grid["sell_bear_weight"]