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>
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Codex
@@ -29,6 +29,7 @@ from pydantic import Field
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from .alpha_wrappers import AssetPick, SizeDecision, VioletAssetSelector, VioletBetSizer
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from .cadence import Action, CadenceControlPlane
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from .domain import StrictModel, Symbol, typed
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from .sizing import VioletSizer
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# Stablecoins / pegged assets that must NEVER be selected as a trade asset.
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@@ -42,6 +43,27 @@ STABLECOIN_SYMBOLS = frozenset({
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})
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class SizingFactors(StrictModel):
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"""Live factor inputs for BLUE's full 5-multiplier sizing (V3.4).
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Supplied by the caller (launcher) from the live planes: ACB day-state
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(``boost``/``beta`` via AdaptiveCircuitBreaker), MC-Forewarner (``mc_scale``),
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EsoF advisory (``esof_score``), OB consensus (``ob_*`` via OBFeatureEngine), the
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DC signal (``dc_status``), and the day ``posture``. When ``decide()`` is given
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these, it produces BLUE-complete conviction via ``VioletSizer``; when omitted,
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``decide()`` uses the V3a base-only sizer (legacy/no-factor path). Defaults are
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BLUE's own neutral sentinels (NOT ours) — only finite/non-negative poison guards."""
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boost: float = Field(default=1.0, ge=0.0, allow_inf_nan=False)
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beta: float = Field(default=0.0, ge=0.0, allow_inf_nan=False)
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mc_scale: float = Field(default=1.0, ge=0.0, allow_inf_nan=False)
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esof_score: Optional[float] = Field(default=None, allow_inf_nan=False)
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ob_median_imbalance: Optional[float] = Field(default=None, allow_inf_nan=False)
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ob_agreement_pct: Optional[float] = Field(default=None, allow_inf_nan=False)
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dc_status: str = "NONE"
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posture: str = "APEX"
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class ShadowDecision(StrictModel):
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"""One muted decision — what BLUE *would* do this scan. Never executed."""
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@@ -57,6 +79,14 @@ class ShadowDecision(StrictModel):
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ars_score: float = Field(allow_inf_nan=False)
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bucket_idx: int = Field(ge=0, le=3)
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actuated: bool
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# full-sizing breakdown (V3.4) — populated only when SizingFactors are supplied;
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# None for the legacy base-only path. conviction_leverage above is then the FULL
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# BLUE conviction (base × dc × regime × ob × esof, capped); these expose the factors.
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base_leverage: Optional[float] = Field(default=None, ge=0.0, allow_inf_nan=False)
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dc_lev_mult: Optional[float] = Field(default=None, ge=0.0, allow_inf_nan=False)
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regime_size_mult: Optional[float] = Field(default=None, ge=0.0, allow_inf_nan=False)
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market_ob_mult: Optional[float] = Field(default=None, ge=0.0, allow_inf_nan=False)
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esof_size_mult: Optional[float] = Field(default=None, ge=0.0, allow_inf_nan=False)
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class VioletDecisionEngine:
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@@ -84,6 +114,14 @@ class VioletDecisionEngine:
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base_fraction=base_fraction, min_leverage=min_leverage,
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max_leverage=max_leverage, vel_div_threshold=entry_vel_div_threshold,
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)
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# V3.4 full 5-factor sizer: base_max=8 (soft) + dc/regime(ACB)/ob/esof mults
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# lifting toward abs_max. Used when decide() is given live SizingFactors;
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# bit-identical to BLUE's esf_alpha_orchestrator composition (see sizing.py).
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self.full_sizer = VioletSizer(
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base_fraction=base_fraction, min_leverage=min_leverage,
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base_max_leverage=8.0, abs_max_leverage=max_leverage,
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vel_div_threshold=entry_vel_div_threshold,
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)
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self.entry_threshold = float(entry_vel_div_threshold)
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self.regime_direction = int(regime_direction)
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self.lookback = int(lookback) if lookback > 0 else self.selector.lookback
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@@ -138,6 +176,7 @@ class VioletDecisionEngine:
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def decide(
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self, *, now_ns: int, scan_number: int, capital: float,
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vel_div: float, vol_ok: bool = True,
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factors: Optional[SizingFactors] = None,
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) -> Optional[ShadowDecision]:
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"""Evaluate the would-be decision (always); actuate only when ENTRY cadence
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is due. Returns the ShadowDecision when a short signal fires, else None.
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@@ -162,9 +201,30 @@ class VioletDecisionEngine:
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self._last_entry_actuation_ns = int(now_ns)
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self.actuations += 1
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size: SizeDecision = self.sizer.calculate(
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capital=capital, vel_div=vel_div, trade_direction=self.regime_direction,
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)
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if factors is None:
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# Legacy base-only path (V3a sizer) — unchanged behavior.
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size: SizeDecision = self.sizer.calculate(
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capital=capital, vel_div=vel_div, trade_direction=self.regime_direction,
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)
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extra: Dict[str, float] = {}
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else:
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# V3.4 full BLUE sizing: base × dc × regime(ACB) × ob × esof, capped @9.
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full = self.full_sizer.size(
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capital=capital, vel_div=vel_div,
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boost=factors.boost, beta=factors.beta, mc_scale=factors.mc_scale,
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esof_score=factors.esof_score,
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ob_median_imbalance=factors.ob_median_imbalance,
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ob_agreement_pct=factors.ob_agreement_pct,
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dc_status=factors.dc_status, posture=factors.posture,
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trade_direction=self.regime_direction,
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)
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size = full.decision
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b = full.breakdown
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extra = dict(
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base_leverage=b.base_leverage, dc_lev_mult=b.dc_lev_mult,
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regime_size_mult=b.regime_size_mult, market_ob_mult=b.market_ob_mult,
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esof_size_mult=b.esof_size_mult,
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)
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return ShadowDecision(
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ts_ns=int(now_ns), scan_number=int(scan_number),
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asset=pick.asset, side=pick.side, vel_div=float(vel_div),
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@@ -172,4 +232,5 @@ class VioletDecisionEngine:
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notional_fraction=size.notional_fraction,
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target_exposure=float(capital) * size.notional_fraction,
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ars_score=pick.ars_score, bucket_idx=size.bucket_idx, actuated=True,
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**extra,
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)
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