Files
siloqy/prod/clean_arch/violet/test_violet_decision_engine.py
Codex a97bb90bf6 VIOLET V3.4: integrate full 5-factor VioletSizer into VioletDecisionEngine
Additive (non-breaking): decide(factors=None) keeps the V3a base-only path (existing
11 tests unchanged); decide(factors=SizingFactors(...)) produces BLUE-complete
conviction via VioletSizer (base_max=8 + dc/regime(ACB)/ob/esof, capped@9) with the
full factor breakdown on ShadowDecision (base_leverage/dc_lev_mult/regime_size_mult/
market_ob_mult/esof_size_mult, None on the base path). SizingFactors value object =
the live-plane inputs the launcher will source (V3.4b). 6 new tests incl. consistency
vs VioletSizer, STALKER cap, EsoF-stale haircut. 17 pass.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-15 23:35:00 +02:00

215 lines
8.4 KiB
Python

"""V3c: VioletDecisionEngine — muted-decision gating, cadence suppression, no exec."""
from __future__ import annotations
import sys
sys.path.insert(0, "/mnt/dolphinng5_predict")
import pytest
import re
from pathlib import Path
from prod.clean_arch.violet.cadence import Action, CadenceControlPlane, INSTA_Q_NS, SCAN_Q_NS
from prod.clean_arch.violet.decision_engine import (
STABLECOIN_SYMBOLS, ShadowDecision, SizingFactors, VioletDecisionEngine,
)
from prod.clean_arch.violet.sizing import VioletSizer
LOOKBACK = 5
def _engine(cp=None, **kw):
return VioletDecisionEngine(control_plane=cp, lookback=LOOKBACK, **kw)
def _warm(engine, n_scans: int = 8):
"""Feed a short-favorable universe (downtrending) so the selector warms + ranks."""
assets = ["AAAUSDT", "BBBUSDT", "CCCUSDT"]
for s in range(n_scans):
prices = [100.0 * (1 - 0.002 * s - 0.0005 * i) for i in range(len(assets))]
engine.observe({"assets": assets, "asset_prices": prices}, scan_number=s + 1)
def test_short_signal_produces_shadow_decision():
e = _engine()
_warm(e)
d = e.decide(now_ns=10**12, scan_number=99, capital=69_000.0, vel_div=-0.20, vol_ok=True)
assert d is None or isinstance(d, ShadowDecision)
if d is not None:
assert d.side == "SHORT"
assert d.target_exposure == pytest.approx(69_000.0 * d.notional_fraction)
assert d.actuated is True
def test_no_decision_when_vel_div_above_threshold():
e = _engine()
_warm(e)
# vel_div above entry threshold (-0.02) → no short signal
assert e.decide(now_ns=10**12, scan_number=1, capital=69_000.0, vel_div=0.05) is None
def test_no_decision_when_vol_gate_blocks():
e = _engine()
_warm(e)
assert e.decide(now_ns=10**12, scan_number=1, capital=69_000.0, vel_div=-0.20, vol_ok=False) is None
def test_no_decision_before_universe_warm():
e = _engine()
e.observe({"assets": ["AAAUSDT"], "asset_prices": [100.0]}, scan_number=1) # 1 bar << lookback
assert e.decide(now_ns=10**12, scan_number=1, capital=69_000.0, vel_div=-0.20) is None
def test_cadence_suppresses_repeat_within_quantum():
cp = CadenceControlPlane() # ENTRY default Q = scan (5s)
e = _engine(cp=cp)
_warm(e)
t0 = 10**12
d1 = e.decide(now_ns=t0, scan_number=10, capital=69_000.0, vel_div=-0.20)
# second call 1ms later: within the scan quantum → suppressed (no actuation)
d2 = e.decide(now_ns=t0 + 1_000_000, scan_number=11, capital=69_000.0, vel_div=-0.20)
if d1 is not None:
assert d2 is None
assert e.suppressed_by_cadence >= 1
# after a full scan quantum elapses → actuates again
d3 = e.decide(now_ns=t0 + SCAN_Q_NS, scan_number=12, capital=69_000.0, vel_div=-0.20)
if d1 is not None:
assert d3 is not None
def test_insta_cadence_actuates_every_call():
cp = CadenceControlPlane()
cp.set(Action.ENTRY, q_ns=INSTA_Q_NS)
e = _engine(cp=cp)
_warm(e)
t = 10**12
d1 = e.decide(now_ns=t, scan_number=1, capital=69_000.0, vel_div=-0.20)
d2 = e.decide(now_ns=t + 1, scan_number=2, capital=69_000.0, vel_div=-0.20)
if d1 is not None:
assert d2 is not None # insta → no suppression
def test_evaluate_always_ge_actuate_invariant():
e = _engine()
_warm(e)
t = 10**12
for k in range(5):
e.decide(now_ns=t + k * 1_000_000, scan_number=20 + k, capital=69_000.0, vel_div=-0.20)
assert e.evaluations >= e.actuations
def test_engine_holds_no_venue_or_kernel():
# structural no-execution guarantee: the shadow engine has no venue/kernel/submit.
e = _engine()
for attr in ("venue", "kernel", "submit", "submit_intent", "execute"):
assert not hasattr(e, attr)
def test_stablecoin_set_matches_blue_exactly():
# Drift guard: VIOLET's exclusion set MUST equal BLUE's _STABLECOIN_SYMBOLS
# (nautilus_event_trader.py), parsed from source (no heavy import).
src = Path("/mnt/dolphinng5_predict/prod/nautilus_event_trader.py").read_text()
m = re.search(r"_STABLECOIN_SYMBOLS\s*=\s*frozenset\(\{(.*?)\}\)", src, re.DOTALL)
assert m is not None
blue = set(re.findall(r"'([A-Z0-9]+)'", m.group(1)))
assert STABLECOIN_SYMBOLS == blue
def test_stablecoin_never_selected():
# Even with a strong short signal, a stablecoin must never be picked (BLUE :3906).
e = _engine()
assets = ["USDCUSDT", "BBBUSDT", "CCCUSDT"]
for s in range(8):
# USDC trends down hardest (would rank top by IRP if not excluded)
prices = [100.0 * (1 - 0.01 * s), 100.0 * (1 - 0.001 * s), 100.0 * (1 - 0.0005 * s)]
e.observe({"assets": assets, "asset_prices": prices}, scan_number=s + 1)
assert "USDCUSDT" not in e._history # never accumulated
for k in range(3):
d = e.decide(now_ns=10**12 + k * SCAN_Q_NS, scan_number=20 + k,
capital=69_000.0, vel_div=-0.20)
if d is not None:
assert d.asset != "USDCUSDT"
def test_determinism_same_inputs_same_decision():
e1, e2 = _engine(), _engine()
_warm(e1); _warm(e2)
d1 = e1.decide(now_ns=10**12, scan_number=5, capital=69_000.0, vel_div=-0.20)
d2 = e2.decide(now_ns=10**12, scan_number=5, capital=69_000.0, vel_div=-0.20)
assert (d1 is None) == (d2 is None)
if d1 is not None:
assert d1.model_dump() == d2.model_dump()
# ── V3.4: full 5-factor sizing path (SizingFactors → VioletSizer) ──────────────
def _full_factors(**kw):
base = dict(boost=1.3, beta=0.8, mc_scale=1.0, esof_score=0.3,
ob_median_imbalance=0.5, ob_agreement_pct=0.90,
dc_status="NONE", posture="APEX")
base.update(kw)
return SizingFactors(**base)
def test_sizing_factors_neutral_defaults():
f = SizingFactors()
assert f.boost == 1.0 and f.beta == 0.0 and f.mc_scale == 1.0
assert f.esof_score is None and f.dc_status == "NONE" and f.posture == "APEX"
def test_base_path_leaves_breakdown_none():
e = _engine(); _warm(e)
d = e.decide(now_ns=10**12, scan_number=99, capital=69_000.0, vel_div=-0.20)
if d is not None:
assert d.regime_size_mult is None and d.market_ob_mult is None
assert d.base_leverage is None and d.dc_lev_mult is None and d.esof_size_mult is None
def test_full_path_populates_breakdown_and_caps():
e = _engine(); _warm(e)
d = e.decide(now_ns=10**12, scan_number=99, capital=69_000.0, vel_div=-0.20,
factors=_full_factors())
if d is not None:
for v in (d.base_leverage, d.dc_lev_mult, d.regime_size_mult,
d.market_ob_mult, d.esof_size_mult):
assert v is not None
assert d.base_leverage <= 8.0 + 1e-9 # VioletSizer base_max=8
assert 0.0 <= d.conviction_leverage <= 9.0 + 1e-9 # capped @ abs_max
def test_full_conviction_matches_violet_sizer_directly():
# engine's full conviction == VioletSizer.size() on the same inputs (consistency).
e = _engine(); _warm(e)
f = _full_factors()
d = e.decide(now_ns=10**12, scan_number=99, capital=69_000.0, vel_div=-0.20, factors=f)
if d is not None:
vs = VioletSizer(base_fraction=0.20, min_leverage=0.5, base_max_leverage=8.0,
abs_max_leverage=9.0, vel_div_threshold=-0.02)
direct = vs.size(capital=69_000.0, vel_div=-0.20, boost=f.boost, beta=f.beta,
mc_scale=f.mc_scale, esof_score=f.esof_score,
ob_median_imbalance=f.ob_median_imbalance,
ob_agreement_pct=f.ob_agreement_pct, dc_status=f.dc_status,
posture=f.posture, trade_direction=-1)
assert d.conviction_leverage == direct.decision.conviction_leverage
def test_stalker_posture_caps_full_conviction_at_2():
e = _engine(); _warm(e)
d = e.decide(now_ns=10**12, scan_number=99, capital=69_000.0, vel_div=-0.20,
factors=_full_factors(posture="STALKER"))
if d is not None:
assert d.conviction_leverage <= 2.0 + 1e-9
def test_full_path_esof_stale_haircuts_below_base():
# esof_score=None -> stale fallback (<1) -> conviction at/below base (min-floored).
e = _engine(); _warm(e)
d = e.decide(now_ns=10**12, scan_number=99, capital=69_000.0, vel_div=-0.025,
factors=_full_factors(esof_score=None, boost=1.0, beta=0.0,
ob_median_imbalance=None, ob_agreement_pct=None))
if d is not None:
assert d.esof_size_mult < 1.0
assert d.conviction_leverage <= d.base_leverage + 1e-9