140 lines
5.0 KiB
Python
140 lines
5.0 KiB
Python
"""Unit tests for V35 market-anchored calibration (pure, no DB/model deps)."""
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import os
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import sys
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sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
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# tests must be deterministic: never consult the DB source for corrections
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os.environ["MARKET_ANCHOR_DB"] = "0"
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from models.market_anchor import devig, home_favorite_delta, apply_home_correction
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def _approx(a, b, tol=1e-9):
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return abs(a - b) <= tol
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def test_devig_sums_to_one_and_orders_by_odds():
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p = devig([2.0, 3.5, 4.0])
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assert p is not None
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assert _approx(sum(p), 1.0)
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assert p[0] > p[1] > p[2] # shorter odds -> higher prob
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def test_devig_removes_bookmaker_margin():
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# 1.61 / 3.15 / 3.77 carries ~20% margin; fair home prob must be BELOW the
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# raw implied 1/1.61, and the three must sum to exactly 1.
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p = devig([1.61, 3.15, 3.77])
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assert p is not None
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assert p[0] < 1.0 / 1.61
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assert _approx(sum(p), 1.0)
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def test_devig_rejects_missing_or_placeholder_legs():
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assert devig([1.0, 3.0, 4.0]) is None # 1.0 leg = no real price
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assert devig([None, 3.0, 4.0]) is None # missing leg
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assert devig([1.005, 3.0]) is None # <= 1.01 placeholder
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assert devig([]) is None
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assert devig([1.90, 1.90]) is not None # valid 2-way
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def test_home_correction_only_lifts_favorites():
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assert home_favorite_delta(0.30) == 0.0 # underdog/level: no bias
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assert home_favorite_delta(0.50) > 0.0
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assert home_favorite_delta(0.80) >= home_favorite_delta(0.60) # monotone
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def test_apply_home_correction_keeps_distribution_valid():
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p1, px, p2 = apply_home_correction(0.70, 0.18, 0.12)
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assert p1 > 0.70 # favourite lifted
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assert _approx(p1 + px + p2, 1.0) # still a valid distribution
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# underdog vector untouched
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q = apply_home_correction(0.30, 0.30, 0.40)
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assert _approx(q[0], 0.30)
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def test_corrections_artifact_loaded_and_fallback():
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import json
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import tempfile
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from models import market_anchor as ma
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# 1) valid artifact -> values come from the file
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with tempfile.NamedTemporaryFile(
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"w", suffix=".json", delete=False, encoding="utf-8"
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) as fh:
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json.dump(
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{"version": "test", "corrections": {"ms_home": [
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{"lo": 0.60, "hi": 0.70, "delta": 0.042},
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]}},
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fh,
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)
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path = fh.name
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try:
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os.environ["MARKET_ANCHOR_CORRECTIONS_PATH"] = path
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ma.reload_corrections()
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assert _approx(ma.home_favorite_delta(0.65), 0.042)
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# band not in the artifact -> the STATIC PRIOR applies (silence must
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# not erase proven knowledge); 0.45-0.55 static prior is 0.010
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assert _approx(ma.home_favorite_delta(0.50), 0.010)
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# 2) malformed artifact -> static fallback, never crashes
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with open(path, "w", encoding="utf-8") as fh2:
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fh2.write("{not json")
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ma.reload_corrections()
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assert ma.home_favorite_delta(0.65) > 0.0 # fallback band value
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assert _approx(ma.home_favorite_delta(0.65), 0.028)
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finally:
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os.environ.pop("MARKET_ANCHOR_CORRECTIONS_PATH", None)
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ma.reload_corrections()
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os.unlink(path)
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def test_away_corrections_only_from_artifact():
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import json
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import tempfile
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from models import market_anchor as ma
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# without an artifact: away correction must be ZERO (earned, not assumed).
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# (Point the env path at a nonexistent file: the repo now SHIPS a fitted
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# artifact, so "no artifact" must be simulated explicitly.)
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os.environ["MARKET_ANCHOR_CORRECTIONS_PATH"] = os.path.join(
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os.path.dirname(__file__), "does_not_exist.json"
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)
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ma.reload_corrections()
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assert ma.away_favorite_delta(0.65) == 0.0
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base = ma.apply_corrections(0.20, 0.20, 0.60)
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assert _approx(base[2], 0.60) # away untouched without artifact
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with tempfile.NamedTemporaryFile(
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"w", suffix=".json", delete=False, encoding="utf-8"
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) as fh:
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json.dump(
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{"version": "t2", "corrections": {
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"ms_home": [{"lo": 0.45, "hi": 0.55, "delta": 0.010}],
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"ms_away": [{"lo": 0.55, "hi": 0.65, "delta": 0.020}],
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}},
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fh,
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)
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path = fh.name
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try:
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os.environ["MARKET_ANCHOR_CORRECTIONS_PATH"] = path
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ma.reload_corrections()
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assert _approx(ma.away_favorite_delta(0.60), 0.020)
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p1, px, p2 = ma.apply_corrections(0.20, 0.20, 0.60)
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assert p2 > 0.60 # away favourite lifted
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assert _approx(p1 + px + p2, 1.0) # still a valid distribution
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assert p1 < 0.20 and px < 0.20 # others renormalised down
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finally:
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os.environ.pop("MARKET_ANCHOR_CORRECTIONS_PATH", None)
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ma.reload_corrections()
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os.unlink(path)
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if __name__ == "__main__":
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fns = [v for k, v in sorted(globals().items()) if k.startswith("test_")]
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for fn in fns:
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fn()
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print(f"PASS {fn.__name__}")
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print(f"\nAll {len(fns)} tests passed.")
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