101 lines
4.0 KiB
Python
101 lines
4.0 KiB
Python
from app import backtest as bt
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from app.analyzer import build_analysis_cache, build_number_weights, score_combination
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def _toy_draws(n=120):
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# 결정적 가짜 회차: 분석 캐시 구성용 (오름차순 (drw_no, [6 nums]))
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import random as _r
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_r.seed(1)
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out = []
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for i in range(1, n + 1):
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nums = sorted(_r.sample(range(1, 46), 6))
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out.append((i, nums))
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return out
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def test_grade_tickets_histogram_and_prizes():
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winning6 = [1, 2, 3, 4, 5, 6]
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bonus = 7
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tickets = [
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[1, 2, 3, 4, 5, 6], # 6일치 = 1등
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[1, 2, 3, 4, 5, 7], # 5일치 + 보너스 = 2등
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[1, 2, 3, 4, 5, 8], # 5일치 = 3등
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[1, 2, 3, 4, 9, 10], # 4일치 = 4등
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[1, 2, 3, 11, 12, 13], # 3일치 = 5등
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[40, 41, 42, 43, 44, 45], # 0일치
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]
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r = bt.grade_tickets(tickets, winning6, bonus)
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assert r["m6"] == 1
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assert r["m5"] == 2 # 5일치 총 2장(보너스 포함)
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assert r["bonus_hits"] == 1 # 그 중 보너스 1장
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assert r["m4"] == 1
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assert r["m3"] == 1
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assert r["best_match"] == 6
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# 등수 매핑 헬퍼
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prizes = bt.prize_counts(r)
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assert prizes == {"1st": 1, "2nd": 1, "3rd": 1, "4th": 1, "5th": 1}
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def test_purchase_tickets_distinct_and_count():
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draws = _toy_draws()
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cache = build_analysis_cache(draws)
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nw = build_number_weights(cache)
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pool = bt.generate_pool(cache, nw, n=2000, seed=7)
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W = [0.25, 0.30, 0.20, 0.15, 0.10]
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bought = bt.purchase_tickets(pool, cache, W, k=50)
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assert len(bought) == 50
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assert len({tuple(t) for t in bought}) == 50 # distinct
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# W로 랭킹된 상위 k → 평균 점수가 풀 전체 평균 이상이어야
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avg_bought = sum(score_combination(t, cache, W)["score_total"] for t in bought) / 50
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avg_pool = sum(score_combination(t, cache, W)["score_total"] for t in pool) / len(pool)
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assert avg_bought >= avg_pool
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def test_random_null_and_coverage_distinct():
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rnd = bt.random_null_tickets(k=50, seed=3)
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assert len(rnd) == 50 and len({tuple(t) for t in rnd}) == 50
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cov = bt.coverage_tickets(k=9, seed=3) # 9장 = 54슬롯 ≥ 45번호 전수 커버 가능
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flat = {n for t in cov for n in t}
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assert len(cov) == 9 and len({tuple(t) for t in cov}) == 9
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assert len(flat) >= 40 # 커버리지 전략은 번호를 넓게 퍼뜨림
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def test_point_in_time_excludes_target_draw():
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draws = _toy_draws(50) # drw_no 1..50
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pit = bt.point_in_time_draws(draws, target_draw_no=30)
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assert all(d < 30 for d, _ in pit) # 30 이상 제외
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assert max(d for d, _ in pit) == 29
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assert len(pit) == 29
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def test_calibrate_winner_scores_and_percentile():
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draws = _toy_draws(60)
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winning6 = [3, 11, 19, 27, 35, 44]
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res = bt.calibrate_winner_compute(draws, target_draw_no=60,
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winning6=winning6, sample_m=500, seed=9)
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assert set(res["scores"].keys()) >= {"score_total", "score_frequency",
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"score_fingerprint", "score_gap", "score_cooccur", "score_diversity"}
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assert 0.0 <= res["percentile"] <= 1.0
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assert res["cache_draws"] == 59 # 1..59
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def test_generate_pool_partial_fill(monkeypatch):
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"""weighted_sample_6이 항상 같은 조합만 반환하도록 패치 → cap에 먼저 걸려 len < n — 예외 없이 반환."""
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import random as _r
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_r.seed(42)
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tiny_draws = [(i, sorted(_r.sample(range(1, 46), 6))) for i in range(1, 10)]
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cache = build_analysis_cache(tiny_draws)
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nw = build_number_weights(cache)
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# weighted_sample_6을 항상 동일한 하나의 조합만 반환하도록 패치
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# → 두 번째 시도부터 seen에 막혀 n개를 채울 수 없고 cap=n*4 이후 종료
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import app.backtest as _bt_mod
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monkeypatch.setattr(_bt_mod, "weighted_sample_6", lambda _w: [1, 2, 3, 4, 5, 6])
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n = 50
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pool = bt.generate_pool(cache, nw, n=n, seed=0)
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# 예외 없이 반환해야 하고, 결과는 n 미만이어야 하며 모두 distinct
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assert isinstance(pool, list)
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assert len(pool) < n
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assert len({tuple(t) for t in pool}) == len(pool)
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