VIOLET V3.4c: make boost/beta, signal-gen, OB bit-identical to BLUE (+ exhaustive tests)
Operator directive: VIOLET must do IDENTICALLY what BLUE does for the three parity flags — approximation cannot guarantee bit-for-bit functioning. Reworked live_blue_source.py to call BLUE's OWN code paths, not reconstruct/substitute them. boost/beta — was reading the published DOLPHIN_FEATURES.acb_boost scalar (acb_processor_service's daily value). BLUE's trader does NOT use that for sizing; it recomputes live via acb.get_dynamic_boost_from_hz(exf_latest, w750_velocity, direction) with a bare AdaptiveCircuitBreaker() and NO ob_engine (nautilus_event_trader.py on_exf_update:4769 / rollover prewarm:2710). New _source_boost_beta replicates that call exactly (reads exf_latest + latest_eigen_scan.w750_velocity; 0.0→None like BLUE; on stale exf ValueError → neutral, mirroring BLUE's "ACB Stale Data Fallback"). The published acb_boost is never read. Test pins bit-identity against the real ACB. signal-gen (dc_status) — was AlphaSignalGenerator() bare defaults; coincidentally equal to BLUE today, but BLUE builds it from ENGINE_KWARGS (trader:128-133, threaded at esf_alpha_orchestrator.py:180-191), so a champion retune would silently diverge. Now constructed with BLUE_SIGNAL_GEN_KWARGS (vel_div_* imported from the kernel constants). Test parses ENGINE_KWARGS from the trader source and asserts each param matches — drift becomes a red test, not a silent miss. OB — was a reinvented HazelcastOBProvider reading asset_*_ob with custom parsing. Now uses BLUE's OWN HZOBProvider + OBFeatureEngine, wired exactly as _wire_obf (nautilus_event_trader.py:4967-4980): step_live(assets, bar_idx) then get_market. Engine is injectable + persistent so OB accumulation matches BLUE across scans (caller owns it). Deleted: HazelcastOBProvider, _extract_acb, the status-label mc path. mc_scale fix (begin_day cat/env thresholds) retained. Module docstring + structural-divergence doc updated: all three flags FIXED; only _derive_mc_scale remains hand-replicated (pinned by formula test). OPEN follow-up: launcher shadow_decision_step should pass a persistent ob_engine + bar_idx for cross-scan OB history. 34 tests (33 + live-HZ smoke deselected): boost/beta-vs-ACB bit-identity (incl. w750=0→None, no-exf, stale ValueError, ignores acb_boost), signal-gen ENGINE_KWARGS pin (parametrized), OB wiring (step_live call, HZ coords, neutral paths), mc_scale formula, sequence dc/selector parity, anomaly handling. violet-only; no shared-file edits. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Codex
@@ -5,33 +5,38 @@ This is VIOLET-only. BLUE is untouched.
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The adapter reads the published BLUE surfaces that already exist in HZ and
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translates them into ``SizingFactors`` for the shadow path:
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- ``posture`` from ``DOLPHIN_STATE_BLUE.latest_nautilus`` / ``engine_snapshot``
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- ``esof_score`` from ``DOLPHIN_FEATURES.esof_latest`` or ``esof_advisor_latest``
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- ``acb_boost`` / ``acb_beta`` from ``DOLPHIN_FEATURES.acb_boost``
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- ``mc_scale`` from ``DOLPHIN_FEATURES.mc_forewarner_latest``
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- OB market consensus from the live ``asset_*_ob`` maps via BLUE's own
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- ``esof_score`` from ``DOLPHIN_FEATURES.esof_latest`` or ``esof_advisor_latest`` via
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BLUE's own ``parse_esof_payload`` / ``esof_score_from_payload``
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- ``boost`` / ``beta`` RECOMPUTED via ``AdaptiveCircuitBreaker.get_dynamic_boost_from_hz``
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over ``DOLPHIN_FEATURES.exf_latest`` + ``latest_eigen_scan.w750_velocity`` — IDENTICAL
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to the trader's on_exf_update path (NOT the published ``acb_boost`` scalar)
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- ``mc_scale`` from ``DOLPHIN_FEATURES.mc_forewarner_latest`` via ``_derive_mc_scale``
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(begin_day's cat/env thresholds, not the MC service's status label)
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- OB market consensus from the live ``asset_*_ob`` maps via BLUE's own ``HZOBProvider`` +
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``OBFeatureEngine``
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- ``dc_status`` via BLUE's ``AlphaSignalGenerator`` (params pinned to BLUE's ENGINE_KWARGS)
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over the replayed scan price-history
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The remaining DC signal is left neutral here for now. It needs the same live
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signal-history path BLUE uses and should be added as a separate mirror step.
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PARITY DEBT (see prod/docs/VIOLET_BLUE_PARITY_STRUCTURAL_DIVERGENCE.md): this module
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reconstructs BLUE's factors in a DIFFERENT file/scope structure than BLUE's monolithic
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NDAlphaEngine (esf_alpha_orchestrator.py). Kernels here are WRAPPED (OBFeatureEngine,
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AlphaSignalGenerator, VioletAssetSelector — single source of truth), but two derivations
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are HAND-REPLICATED / surface-substituted and can drift silently from BLUE:
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- ``_derive_mc_scale`` transcribes begin_day's mc thresholds (no pin to BLUE's fn);
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- ``AlphaSignalGenerator()`` is built with BARE DEFAULTS, not BLUE's threaded params
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(esf_alpha_orchestrator.py:180-191) — cosmetic only while dc_leverage_boost==1.0;
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- boost/beta read the PUBLISHED ``acb_boost`` (acb_processor_service), not the trader's
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``get_dynamic_boost_from_hz`` recompute — the two surfaces may differ.
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Any change to BLUE's corresponding formula REQUIRES a matching change here + a test.
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PARITY (see prod/docs/VIOLET_BLUE_PARITY_STRUCTURAL_DIVERGENCE.md): this module reconstructs
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BLUE's factors in a DIFFERENT file/scope structure than BLUE's monolithic NDAlphaEngine.
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Every kernel is now WRAPPED, not copied (ACB, OBFeatureEngine+HZOBProvider, AlphaSignalGenerator,
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VioletAssetSelector) — so the only hand-replicated arithmetic left is ``_derive_mc_scale``
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(begin_day's thresholds; pinned by test). Remaining REAL fidelity caveats:
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- OB faithfulness needs a PERSISTENT ``ob_engine`` + per-scan ``bar_idx`` (OBFeatureEngine
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accumulates a lookback window); a single-shot engine has no cross-scan history.
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- On stale exf (>12h) the ACB raises ValueError; BLUE keeps the prior boost/beta, VIOLET
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has no prior → neutral (1.0, 0.0).
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Any change to BLUE's ENGINE_KWARGS or begin_day mc thresholds REQUIRES a matching change +
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test here (see test_signal_gen_params_match_blue_engine_kwargs / the mc_scale formula test).
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"""
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from __future__ import annotations
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import json
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import os as _os
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import sys
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from collections import deque
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from datetime import datetime, timezone
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from collections.abc import Mapping
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from dataclasses import dataclass
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from dataclasses import field
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@@ -47,14 +52,43 @@ for _p in (str(_PROJECT_ROOT), str(_PROJECT_ROOT / "nautilus_dolphin")):
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sys.path.insert(0, _p)
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from nautilus_dolphin.nautilus.ob_features import OBFeatureEngine
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from nautilus_dolphin.nautilus.ob_provider import OBSnapshot, OBProvider
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from nautilus_dolphin.nautilus.alpha_signal_generator import AlphaSignalGenerator
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from nautilus_dolphin.nautilus.hz_ob_provider import HZOBProvider
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from nautilus_dolphin.nautilus.adaptive_circuit_breaker import AdaptiveCircuitBreaker
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from nautilus_dolphin.nautilus.alpha_signal_generator import (
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AlphaSignalGenerator,
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VEL_DIV_THRESHOLD, VEL_DIV_EXTREME,
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LONG_VEL_DIV_THRESHOLD, LONG_VEL_DIV_EXTREME,
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)
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from .alpha_wrappers import VioletAssetSelector
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from .decision_engine import SizingFactors
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from .live_factor_source import esof_score_from_features, posture_from_engine_snapshot
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from .live_factors import extract_live_sizing_factors
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# Hazelcast coordinates — MUST equal nautilus_event_trader.py:107-108 (BLUE's live
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# cluster). HZOBProvider opens its own connection to these, exactly as BLUE's _wire_obf.
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HZ_CLUSTER = _os.environ.get("HZ_CLUSTER", "dolphin")
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HZ_HOST = _os.environ.get("HZ_HOST", "127.0.0.1:5701")
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# AlphaSignalGenerator construction — pinned to BLUE's live ENGINE_KWARGS
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# (nautilus_event_trader.py:128-133). These equal AlphaSignalGenerator's own defaults
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# TODAY, but BLUE constructs it EXPLICITLY from ENGINE_KWARGS, so a future champion
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# retune (e.g. dc_lookback_bars→10) would silently diverge a bare AlphaSignalGenerator().
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# We pin explicitly and assert the pin in test_signal_gen_params_match_blue_engine_kwargs.
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# vel_div_* import the module constants directly so they auto-track the kernel.
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BLUE_SIGNAL_GEN_KWARGS = dict(
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vel_div_threshold=VEL_DIV_THRESHOLD, # -0.02
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vel_div_extreme=VEL_DIV_EXTREME, # -0.05
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long_vel_div_threshold=LONG_VEL_DIV_THRESHOLD, # 0.01
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long_vel_div_extreme=LONG_VEL_DIV_EXTREME, # 0.04
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dc_lookback_bars=7,
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dc_min_magnitude_bps=0.75,
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dc_skip_contradicts=True,
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dc_leverage_boost=1.0,
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dc_leverage_reduce=0.5,
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use_direction_confirm=True,
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)
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def _jsonish(value: Any) -> Any:
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if isinstance(value, str):
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@@ -121,13 +155,48 @@ def _derive_mc_scale(payload: Any) -> float:
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return 0.5 if mc_orange else 1.0
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def _extract_acb(payload: Any) -> tuple[float, float]:
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data = _jsonish(payload)
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if isinstance(data, Mapping):
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boost = _coerce_float(data.get("boost"), 1.0) or 1.0
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beta = _coerce_float(data.get("beta"), 0.0) or 0.0
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return max(0.0, boost), max(0.0, beta)
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return 1.0, 0.0
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def _source_boost_beta(
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client: hazelcast.HazelcastClient,
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*,
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date_str: str,
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trade_direction: int,
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acb: Optional[AdaptiveCircuitBreaker] = None,
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) -> tuple[float, float]:
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"""Recompute (boost, beta) EXACTLY as BLUE's live trader does — NOT from acb_boost.
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BLUE (nautilus_event_trader.py on_exf_update:4769 / rollover prewarm:2710):
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acb = AdaptiveCircuitBreaker() # bare, no args (trader 578/585)
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info = acb.get_dynamic_boost_from_hz(
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date_str=today,
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exf_snapshot=DOLPHIN_FEATURES['exf_latest'],
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w750_velocity=latest_eigen_scan['w750_velocity'] or None,
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direction=trade_direction, # NO ob_engine in the live path
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)
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boost, beta = info['boost'], info['beta']
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The published ``DOLPHIN_FEATURES['acb_boost']`` is a SEPARATE daily publish
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(acb_processor_service) and is NOT what drives BLUE's sizing, so we never read it.
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On stale exf (>12h) get_dynamic_boost_from_hz raises ValueError; BLUE logs
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'ACB Stale Data Fallback' and keeps the prior boost/beta — VIOLET has no prior, so it
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returns the neutral identity (1.0, 0.0)."""
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exf = _jsonish(_read_hz_map(client, "DOLPHIN_FEATURES", "exf_latest"))
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if not isinstance(exf, Mapping):
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return 1.0, 0.0
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eigen = _jsonish(_read_hz_map(client, "DOLPHIN_FEATURES", "latest_eigen_scan"))
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w750 = _coerce_float(eigen.get("w750_velocity"), None) if isinstance(eigen, Mapping) else None
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acb = acb or AdaptiveCircuitBreaker()
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try:
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info = acb.get_dynamic_boost_from_hz(
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date_str=date_str,
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exf_snapshot=dict(exf),
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w750_velocity=float(w750) if w750 else None, # 0.0 → None, matches BLUE
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direction=trade_direction,
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)
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except ValueError:
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return 1.0, 0.0 # ACB Stale Data Fallback (BLUE keeps prior; VIOLET neutral)
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boost = _coerce_float(info.get("boost"), 1.0) or 1.0
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beta = _coerce_float(info.get("beta"), 0.0) or 0.0
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return max(0.0, boost), max(0.0, beta)
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def _scan_view(payload: Any) -> Mapping[str, Any]:
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@@ -209,7 +278,12 @@ class LiveBlueScanHistory:
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history = self.price_history(asset[0])
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if not history:
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return "NONE"
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signal_gen = AlphaSignalGenerator()
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# BLUE constructs its signal_gen from ENGINE_KWARGS (the orchestrator threads them,
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# esf_alpha_orchestrator.py:180-191). Pin the SAME params — not bare defaults — so a
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# champion retune that changes dc_lookback_bars / dc_min_magnitude_bps / thresholds
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# diverges loudly (caught by test_signal_gen_params_match_blue_engine_kwargs), never
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# silently. dc_status is deterministic in the params + price history (counters unused).
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signal_gen = AlphaSignalGenerator(**BLUE_SIGNAL_GEN_KWARGS)
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sig = signal_gen.generate(
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vel_div=vel_div,
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vel_div_history=None,
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@@ -221,80 +295,37 @@ class LiveBlueScanHistory:
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return sig.dc_status
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class HazelcastOBProvider(OBProvider):
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"""Read the current BLUE OB shards directly from Hazelcast."""
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def _source_ob_market(
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ob_assets: list[str],
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*,
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bar_idx: int,
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ob_engine: Optional[OBFeatureEngine] = None,
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) -> tuple[Optional[float], Optional[float]]:
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"""Derive (median_imbalance, agreement_pct) EXACTLY as BLUE does, via BLUE's HZOBProvider.
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def __init__(self, client: hazelcast.HazelcastClient):
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self.client = client
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BLUE wires OB once in _wire_obf (nautilus_event_trader.py:4967-4980):
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live_ob = HZOBProvider(hz_cluster=HZ_CLUSTER, hz_host=HZ_HOST, assets=assets)
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ob_eng = OBFeatureEngine(live_ob); eng.set_ob_engine(ob_eng)
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then per scan calls ``ob_eng.step_live(assets, bar_idx)`` and the orchestrator reads
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``ob_eng.get_market(bar_idx, assets)`` (esf_alpha_orchestrator.py:590). We use BLUE's
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OWN HZOBProvider — NOT a reinvented reader — so OB parsing/shard semantics are BLUE's.
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def _asset_keys(self) -> list[str]:
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try:
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keys = self.client.get_map("DOLPHIN_FEATURES").blocking().key_set()
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except Exception:
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return []
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assets = []
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for key in keys:
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if not isinstance(key, str) or not key.startswith("asset_") or not key.endswith("_ob"):
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continue
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asset = key[len("asset_"):-len("_ob")]
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if asset and asset not in assets:
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assets.append(asset)
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return sorted(assets)
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def _read_snapshot(self, asset: str) -> Optional[OBSnapshot]:
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raw = _read_hz_map(self.client, "DOLPHIN_FEATURES", f"asset_{asset}_ob")
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data = _jsonish(raw)
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if not isinstance(data, Mapping):
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return None
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bid_notional = np.array(
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[_coerce_float(v, 0.0) or 0.0 for v in data.get("bid_notional", [0, 0, 0, 0, 0])][:5],
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dtype=np.float64,
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)
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ask_notional = np.array(
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[_coerce_float(v, 0.0) or 0.0 for v in data.get("ask_notional", [0, 0, 0, 0, 0])][:5],
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dtype=np.float64,
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)
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bid_depth = np.array(
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[_coerce_float(v, 0.0) or 0.0 for v in data.get("bid_depth", [0, 0, 0, 0, 0])][:5],
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dtype=np.float64,
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)
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ask_depth = np.array(
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[_coerce_float(v, 0.0) or 0.0 for v in data.get("ask_depth", [0, 0, 0, 0, 0])][:5],
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dtype=np.float64,
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)
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ts = _coerce_float(data.get("timestamp"), 0.0) or 0.0
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if (
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bid_notional.shape != (5,) or ask_notional.shape != (5,)
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or bid_depth.shape != (5,) or ask_depth.shape != (5,)
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):
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return None
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if np.any(bid_notional < 0) or np.any(ask_notional < 0):
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return None
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if np.any(bid_depth < 0) or np.any(ask_depth < 0):
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return None
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return OBSnapshot(
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timestamp=ts,
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asset=asset,
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bid_notional=bid_notional,
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ask_notional=ask_notional,
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bid_depth=bid_depth,
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ask_depth=ask_depth,
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)
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def get_snapshot(self, asset: str, timestamp: float) -> Optional[OBSnapshot]:
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return self._read_snapshot(asset)
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def get_assets(self) -> list[str]:
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return self._asset_keys()
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def get_all_timestamps(self, asset: str) -> np.ndarray:
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snap = self._read_snapshot(asset)
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if snap is None:
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return np.array([], dtype=np.float64)
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return np.array([snap.timestamp], dtype=np.float64)
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def get_snapshot_count(self, asset: str) -> int:
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return 1 if self._read_snapshot(asset) is not None else 0
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OBFeatureEngine ACCUMULATES per-asset history across scans (lookback=10), so a faithful
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mirror requires a PERSISTENT ``ob_engine`` + per-scan-incrementing ``bar_idx`` (the
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caller/shadow loop owns it, exactly as BLUE keeps one ob_eng). When no engine is passed
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this builds a single-shot HZOBProvider-backed engine — correct wiring but no cross-scan
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history; use only for one-off reads / the live smoke."""
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if not ob_assets:
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return None, None
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if ob_engine is None:
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provider = HZOBProvider(hz_cluster=HZ_CLUSTER, hz_host=HZ_HOST, assets=list(ob_assets))
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ob_engine = OBFeatureEngine(provider)
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try:
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ob_engine.step_live(list(ob_assets), bar_idx)
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market = ob_engine.get_market(bar_idx, list(ob_assets))
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return float(market.median_imbalance), float(market.agreement_pct)
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except Exception:
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return None, None
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@dataclass(frozen=True)
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@@ -314,10 +345,22 @@ def source_live_blue_sizing_factors(
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assets: Optional[Iterable[str]] = None,
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scan_history: Optional[LiveBlueScanHistory] = None,
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selector: Optional[VioletAssetSelector] = None,
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acb: Optional[AdaptiveCircuitBreaker] = None,
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ob_engine: Optional[OBFeatureEngine] = None,
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bar_idx: int = 0,
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date_str: Optional[str] = None,
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) -> LiveBlueSourceResult:
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"""Read the BLUE-published live surfaces and return a typed factor plane."""
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"""Read BLUE's live surfaces and RECONSTRUCT the factor plane the way BLUE computes it.
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boost/beta are recomputed via ``AdaptiveCircuitBreaker.get_dynamic_boost_from_hz`` (NOT
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the published acb_boost scalar); OB via BLUE's ``HZOBProvider`` + ``OBFeatureEngine``;
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dc_status via ``AlphaSignalGenerator`` pinned to BLUE's ENGINE_KWARGS. For full OB
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accumulation faithfulness the caller passes a PERSISTENT ``ob_engine`` + per-scan
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``bar_idx`` (BLUE keeps one ob_eng). ``date_str`` defaults to today's UTC date (BLUE
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uses self.current_day)."""
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scan_history = scan_history or LiveBlueScanHistory()
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selector = selector or VioletAssetSelector()
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today = date_str or datetime.now(timezone.utc).strftime("%Y-%m-%d")
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engine_snapshot_raw = _read_hz_map(client, "DOLPHIN_STATE_BLUE", "latest_nautilus")
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if engine_snapshot_raw is None:
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@@ -336,11 +379,6 @@ def source_live_blue_sizing_factors(
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esof_raw = _read_hz_map(client, "DOLPHIN_FEATURES", "esof_advisor_latest")
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esof_score = esof_score_from_features(esof_raw)
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acb_raw = _read_hz_map(client, "DOLPHIN_FEATURES", "acb_boost")
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if acb_raw is None:
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acb_raw = _read_hz_map(client, "DOLPHIN_FEATURES", "acb_boost_short")
|
||||
acb_boost, acb_beta = _extract_acb(acb_raw)
|
||||
|
||||
mc_raw = _read_hz_map(client, "DOLPHIN_FEATURES", "mc_forewarner_latest")
|
||||
mc_scale = _derive_mc_scale(mc_raw)
|
||||
|
||||
@@ -358,26 +396,23 @@ def source_live_blue_sizing_factors(
|
||||
)
|
||||
or -1
|
||||
)
|
||||
|
||||
# boost/beta — recompute via the ACB exactly as BLUE's trader does (NOT the published
|
||||
# acb_boost). Needs trade_direction, so computed after it.
|
||||
acb_boost, acb_beta = _source_boost_beta(
|
||||
client, date_str=today, trade_direction=trade_direction, acb=acb,
|
||||
)
|
||||
|
||||
candidate_market = scan_history.market_data(selector.lookback)
|
||||
pick = selector.pick(candidate_market, regime_direction=trade_direction)
|
||||
selected_asset = pick.asset if pick is not None else (scan_assets[0] if scan_assets else "")
|
||||
dc_status = scan_history.dc_status(scan, already_ingested=True)
|
||||
|
||||
ob_provider = HazelcastOBProvider(client)
|
||||
ob_engine = OBFeatureEngine(ob_provider)
|
||||
ob_assets = list(assets) if assets is not None else (scan_assets or ob_provider.get_assets())
|
||||
if ob_assets:
|
||||
try:
|
||||
ob_engine.step_live(ob_assets, bar_idx=0)
|
||||
market = ob_engine.get_market(0, ob_assets)
|
||||
ob_median_imbalance = float(market.median_imbalance)
|
||||
ob_agreement_pct = float(market.agreement_pct)
|
||||
except Exception:
|
||||
ob_median_imbalance = None
|
||||
ob_agreement_pct = None
|
||||
else:
|
||||
ob_median_imbalance = None
|
||||
ob_agreement_pct = None
|
||||
# OB market consensus — BLUE's HZOBProvider + OBFeatureEngine (persistent engine if given).
|
||||
ob_assets = list(assets) if assets is not None else scan_assets
|
||||
ob_median_imbalance, ob_agreement_pct = _source_ob_market(
|
||||
ob_assets, bar_idx=bar_idx, ob_engine=ob_engine,
|
||||
)
|
||||
|
||||
hz_snapshot = {
|
||||
"boost": acb_boost,
|
||||
|
||||
@@ -1,8 +1,19 @@
|
||||
"""V3.4c live BLUE source — BLUE-algo parity tests (boost/beta, signal-gen, OB, mc_scale).
|
||||
|
||||
These pin VIOLET's reconstruction to BLUE's ACTUAL behaviour:
|
||||
- boost/beta: bit-identical to AdaptiveCircuitBreaker.get_dynamic_boost_from_hz
|
||||
- signal-gen: params pinned to BLUE's ENGINE_KWARGS (nautilus_event_trader.py)
|
||||
- OB: BLUE's HZOBProvider + OBFeatureEngine wiring (persistent engine, step_live/get_market)
|
||||
- mc_scale: begin_day's cat/env thresholds (not the MC service status label)
|
||||
See prod/docs/VIOLET_BLUE_PARITY_STRUCTURAL_DIVERGENCE.md.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import re
|
||||
import sys
|
||||
from dataclasses import dataclass
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
@@ -12,26 +23,27 @@ import hazelcast
|
||||
|
||||
from prod.clean_arch.violet.decision_engine import SizingFactors
|
||||
from prod.clean_arch.violet.live_blue_source import (
|
||||
HazelcastOBProvider,
|
||||
BLUE_SIGNAL_GEN_KWARGS,
|
||||
HZ_CLUSTER,
|
||||
HZ_HOST,
|
||||
LiveBlueScanHistory,
|
||||
_derive_mc_scale,
|
||||
_source_boost_beta,
|
||||
_source_ob_market,
|
||||
source_live_blue_sizing_factors,
|
||||
)
|
||||
from prod.clean_arch.violet.alpha_wrappers import VioletAssetSelector
|
||||
from nautilus_dolphin.nautilus.alpha_signal_generator import AlphaSignalGenerator
|
||||
|
||||
|
||||
@dataclass
|
||||
class _FakeMap:
|
||||
payloads: dict
|
||||
|
||||
def get(self, key):
|
||||
return self.payloads.get(key)
|
||||
|
||||
def key_set(self):
|
||||
return list(self.payloads.keys())
|
||||
from nautilus_dolphin.nautilus.adaptive_circuit_breaker import AdaptiveCircuitBreaker
|
||||
from nautilus_dolphin.nautilus.alpha_signal_generator import (
|
||||
AlphaSignalGenerator,
|
||||
LONG_VEL_DIV_THRESHOLD, LONG_VEL_DIV_EXTREME,
|
||||
VEL_DIV_THRESHOLD, VEL_DIV_EXTREME,
|
||||
)
|
||||
|
||||
TRADER = Path("/mnt/dolphinng5_predict/prod/nautilus_event_trader.py")
|
||||
|
||||
|
||||
# ── fakes ────────────────────────────────────────────────────────────────────
|
||||
class _FakeBlocking:
|
||||
def __init__(self, payloads):
|
||||
self._payloads = payloads
|
||||
@@ -48,285 +60,314 @@ class _FakeClient:
|
||||
self._maps = maps
|
||||
|
||||
def get_map(self, name):
|
||||
return type("M", (), {"blocking": lambda self2: _FakeBlocking(self._maps[name])})()
|
||||
payloads = self._maps.get(name, {})
|
||||
return type("M", (), {"blocking": lambda self2, p=payloads: _FakeBlocking(p)})()
|
||||
|
||||
|
||||
def test_hz_ob_provider_filters_and_parses_latest_payload():
|
||||
client = _FakeClient(
|
||||
{
|
||||
"DOLPHIN_FEATURES": {
|
||||
"asset_BTCUSDT_ob": json.dumps(
|
||||
{"timestamp": 1.0, "bid_notional": [1, 2, 3, 4, 5], "ask_notional": [5, 4, 3, 2, 1],
|
||||
"bid_depth": [1, 1, 1, 1, 1], "ask_depth": [1, 1, 1, 1, 1]}
|
||||
),
|
||||
"asset_XRPUSDT_ob": json.dumps(
|
||||
{"timestamp": 2.0, "bid_notional": [-1, 2, 3, 4, 5], "ask_notional": [5, 4, 3, 2, 1],
|
||||
"bid_depth": [1, 1, 1, 1, 1], "ask_depth": [1, 1, 1, 1, 1]}
|
||||
),
|
||||
"acb_boost": json.dumps({"boost": 1.2, "beta": 0.3}),
|
||||
"mc_forewarner_latest": json.dumps({"catastrophic_prob": 0.15, "envelope_score": 0.5}),
|
||||
"esof_latest": json.dumps({"advisory_score": 0.4}),
|
||||
},
|
||||
"DOLPHIN_STATE_BLUE": {"latest_nautilus": json.dumps({"posture": "restored"})},
|
||||
}
|
||||
class _FakeOBEngine:
|
||||
"""Stands in for a persistent OBFeatureEngine; records step_live calls."""
|
||||
|
||||
def __init__(self, median_imbalance=0.0, agreement_pct=0.0):
|
||||
self.calls = []
|
||||
self._mi = median_imbalance
|
||||
self._ap = agreement_pct
|
||||
|
||||
def step_live(self, assets, bar_idx):
|
||||
self.calls.append((tuple(assets), bar_idx))
|
||||
|
||||
def get_market(self, bar_idx, assets):
|
||||
return type("M", (), {"median_imbalance": self._mi, "agreement_pct": self._ap})()
|
||||
|
||||
|
||||
_EXF = {"funding_btc": 0.01, "dvol_btc": 55.0, "fng": 40.0, "taker": 1.2, "_acb_ready": True}
|
||||
|
||||
|
||||
def _features(**extra):
|
||||
base = {
|
||||
"esof_latest": json.dumps({"advisory_score": 0.4}),
|
||||
"mc_forewarner_latest": json.dumps({"catastrophic_prob": 0.15, "envelope_score": 0.5}),
|
||||
"exf_latest": json.dumps(_EXF),
|
||||
}
|
||||
base.update(extra)
|
||||
return base
|
||||
|
||||
|
||||
# ── 1. boost/beta: bit-identical to the ACB recompute (NOT acb_boost) ─────────
|
||||
def test_boost_beta_recomputed_identically_to_blue_acb():
|
||||
eigen = {"w750_velocity": 0.0012, "assets": ["BTCUSDT"], "asset_prices": [100.0],
|
||||
"scan_number": 5, "vel_div": -0.03}
|
||||
client = _FakeClient({"DOLPHIN_FEATURES": _features(latest_eigen_scan=json.dumps(eigen))})
|
||||
boost, beta = _source_boost_beta(client, date_str="2026-06-16", trade_direction=-1)
|
||||
ref = AdaptiveCircuitBreaker().get_dynamic_boost_from_hz(
|
||||
date_str="2026-06-16", exf_snapshot=dict(_EXF), w750_velocity=0.0012, direction=-1,
|
||||
)
|
||||
provider = HazelcastOBProvider(client) # type: ignore[arg-type]
|
||||
assert provider.get_assets() == ["BTCUSDT", "XRPUSDT"]
|
||||
snap = provider.get_snapshot("BTCUSDT", 0.0)
|
||||
assert snap is not None
|
||||
assert snap.asset == "BTCUSDT"
|
||||
assert snap.bid_notional.tolist() == [1.0, 2.0, 3.0, 4.0, 5.0]
|
||||
assert boost == max(0.0, float(ref["boost"]))
|
||||
assert beta == max(0.0, float(ref["beta"]))
|
||||
|
||||
|
||||
def test_source_live_blue_sizing_factors_unit(monkeypatch):
|
||||
class FakeEngine:
|
||||
def __init__(self, provider):
|
||||
self.provider = provider
|
||||
def step_live(self, assets, bar_idx):
|
||||
assert "BTCUSDT" in assets
|
||||
def get_market(self, ts, assets):
|
||||
return type("M", (), {"median_imbalance": 0.12, "agreement_pct": 0.91})()
|
||||
def test_boost_beta_w750_zero_passed_as_none_like_blue():
|
||||
# BLUE: w750_velocity=float(w750) if w750 else None → 0.0 becomes None
|
||||
eigen = {"w750_velocity": 0.0, "assets": ["BTCUSDT"], "asset_prices": [100.0]}
|
||||
client = _FakeClient({"DOLPHIN_FEATURES": _features(latest_eigen_scan=json.dumps(eigen))})
|
||||
boost, beta = _source_boost_beta(client, date_str="2026-06-16", trade_direction=-1)
|
||||
ref = AdaptiveCircuitBreaker().get_dynamic_boost_from_hz(
|
||||
date_str="2026-06-16", exf_snapshot=dict(_EXF), w750_velocity=None, direction=-1,
|
||||
)
|
||||
assert (boost, beta) == (max(0.0, float(ref["boost"])), max(0.0, float(ref["beta"])))
|
||||
|
||||
monkeypatch.setattr("prod.clean_arch.violet.live_blue_source.OBFeatureEngine", FakeEngine)
|
||||
|
||||
def test_boost_beta_neutral_when_no_exf():
|
||||
client = _FakeClient({"DOLPHIN_FEATURES": {}})
|
||||
assert _source_boost_beta(client, date_str="2026-06-16", trade_direction=-1) == (1.0, 0.0)
|
||||
|
||||
|
||||
def test_boost_beta_neutral_on_stale_exf_valueerror():
|
||||
# >12h staleness → get_dynamic_boost_from_hz raises ValueError → BLUE stale fallback;
|
||||
# VIOLET has no prior → neutral identity.
|
||||
stale = dict(_EXF, _staleness_s={"funding_btc": 999999.0})
|
||||
client = _FakeClient({"DOLPHIN_FEATURES": {"exf_latest": json.dumps(stale),
|
||||
"latest_eigen_scan": json.dumps({"w750_velocity": 0.001})}})
|
||||
assert _source_boost_beta(client, date_str="2026-06-16", trade_direction=-1) == (1.0, 0.0)
|
||||
|
||||
|
||||
def test_boost_beta_does_not_read_published_acb_boost():
|
||||
# An acb_boost scalar is present but MUST be ignored (BLUE recomputes from exf).
|
||||
eigen = {"w750_velocity": 0.0012}
|
||||
client = _FakeClient({"DOLPHIN_FEATURES": _features(
|
||||
latest_eigen_scan=json.dumps(eigen),
|
||||
acb_boost=json.dumps({"boost": 7.77, "beta": 7.77}), # poison: must NOT surface
|
||||
)})
|
||||
boost, beta = _source_boost_beta(client, date_str="2026-06-16", trade_direction=-1)
|
||||
assert boost != 7.77 and beta != 7.77
|
||||
|
||||
|
||||
# ── 2. signal-gen params pinned to BLUE's live ENGINE_KWARGS ──────────────────
|
||||
def _blue_engine_kwargs_block() -> str:
|
||||
text = TRADER.read_text()
|
||||
start = text.index("ENGINE_KWARGS = dict(")
|
||||
end = text.index("\n)", start)
|
||||
return text[start:end]
|
||||
|
||||
|
||||
def _blue_kwarg(name: str):
|
||||
m = re.search(rf"\b{name}\s*=\s*([^\s,]+)", _blue_engine_kwargs_block())
|
||||
assert m, f"{name} not found in BLUE ENGINE_KWARGS"
|
||||
raw = m.group(1).rstrip(",")
|
||||
if raw in ("True", "False"):
|
||||
return raw == "True"
|
||||
return float(raw) if any(c in raw for c in ".-e") else int(raw)
|
||||
|
||||
|
||||
@pytest.mark.parametrize("key", [
|
||||
"vel_div_threshold", "vel_div_extreme", "dc_lookback_bars", "dc_min_magnitude_bps",
|
||||
"use_direction_confirm", "dc_skip_contradicts", "dc_leverage_boost", "dc_leverage_reduce",
|
||||
])
|
||||
def test_signal_gen_params_match_blue_engine_kwargs(key):
|
||||
# If a champion retune changes ENGINE_KWARGS, this fails — no silent divergence.
|
||||
assert BLUE_SIGNAL_GEN_KWARGS[key] == _blue_kwarg(key)
|
||||
|
||||
|
||||
def test_signal_gen_long_thresholds_track_kernel_constants():
|
||||
assert BLUE_SIGNAL_GEN_KWARGS["vel_div_threshold"] == VEL_DIV_THRESHOLD
|
||||
assert BLUE_SIGNAL_GEN_KWARGS["vel_div_extreme"] == VEL_DIV_EXTREME
|
||||
assert BLUE_SIGNAL_GEN_KWARGS["long_vel_div_threshold"] == LONG_VEL_DIV_THRESHOLD
|
||||
assert BLUE_SIGNAL_GEN_KWARGS["long_vel_div_extreme"] == LONG_VEL_DIV_EXTREME
|
||||
|
||||
|
||||
def test_dc_status_uses_pinned_signal_gen_not_bare_default():
|
||||
# dc_status must equal a BLUE signal_gen built with the SAME pinned params.
|
||||
history = LiveBlueScanHistory(maxlen=16, trade_direction=-1)
|
||||
for idx, px in enumerate([100.0, 99.5, 99.0, 98.4, 97.8, 97.0, 96.2], start=1):
|
||||
history.ingest_scan(
|
||||
{
|
||||
"scan_number": idx,
|
||||
"timestamp": float(idx),
|
||||
"vel_div": -0.031,
|
||||
"target_asset": "BTCUSDT",
|
||||
"assets": ["BTCUSDT"],
|
||||
"asset_prices": [px],
|
||||
}
|
||||
)
|
||||
client = _FakeClient(
|
||||
{
|
||||
"DOLPHIN_FEATURES": {
|
||||
"asset_BTCUSDT_ob": json.dumps(
|
||||
{"timestamp": 1.0, "bid_notional": [1, 2, 3, 4, 5], "ask_notional": [5, 4, 3, 2, 1],
|
||||
"bid_depth": [1, 1, 1, 1, 1], "ask_depth": [1, 1, 1, 1, 1]}
|
||||
),
|
||||
"acb_boost": json.dumps({"boost": 1.4, "beta": 0.2}),
|
||||
"mc_forewarner_latest": json.dumps({"catastrophic_prob": 0.15, "envelope_score": 0.5}),
|
||||
"esof_latest": json.dumps({"advisory_score": 0.4}),
|
||||
"latest_eigen_scan": json.dumps(
|
||||
{
|
||||
"scan_number": 8,
|
||||
"timestamp": 8.0,
|
||||
"vel_div": -0.031,
|
||||
"target_asset": "BTCUSDT",
|
||||
"assets": ["BTCUSDT"],
|
||||
"asset_prices": [95.5],
|
||||
}
|
||||
),
|
||||
},
|
||||
"DOLPHIN_STATE_BLUE": {"latest_nautilus": json.dumps({"posture": "stalker"})},
|
||||
}
|
||||
history.ingest_scan({"scan_number": idx, "timestamp": float(idx), "vel_div": -0.031,
|
||||
"assets": ["BTCUSDT"], "asset_prices": [px]})
|
||||
scan = {"scan_number": 8, "timestamp": 8.0, "vel_div": -0.031, "assets": ["BTCUSDT"],
|
||||
"asset_prices": [95.5]}
|
||||
got = history.dc_status(scan)
|
||||
ref = AlphaSignalGenerator(**BLUE_SIGNAL_GEN_KWARGS).generate(
|
||||
vel_div=-0.031, vel_div_history=None,
|
||||
asset_price_history=history.price_history("BTCUSDT"),
|
||||
trade_direction=-1, asset="BTCUSDT", current_timestamp=8.0,
|
||||
)
|
||||
assert got == ref.dc_status
|
||||
|
||||
|
||||
# ── 3. OB: BLUE's HZOBProvider + OBFeatureEngine wiring ───────────────────────
|
||||
def test_ob_uses_persistent_engine_step_live_then_get_market():
|
||||
eng = _FakeOBEngine(median_imbalance=0.12, agreement_pct=0.9)
|
||||
mi, ap = _source_ob_market(["BTCUSDT", "ETHUSDT"], bar_idx=3, ob_engine=eng)
|
||||
assert eng.calls == [(("BTCUSDT", "ETHUSDT"), 3)] # step_live(assets, bar_idx) — BLUE's call
|
||||
assert (mi, ap) == (0.12, 0.9)
|
||||
|
||||
|
||||
def test_ob_empty_assets_neutral():
|
||||
assert _source_ob_market([], bar_idx=0) == (None, None)
|
||||
|
||||
|
||||
def test_ob_engine_exception_neutral():
|
||||
class _Boom:
|
||||
def step_live(self, a, b):
|
||||
raise RuntimeError("x")
|
||||
|
||||
def get_market(self, b, a):
|
||||
raise AssertionError("unreachable")
|
||||
|
||||
assert _source_ob_market(["BTCUSDT"], bar_idx=0, ob_engine=_Boom()) == (None, None)
|
||||
|
||||
|
||||
def test_ob_builds_blue_hzobprovider_with_live_coords(monkeypatch):
|
||||
captured = {}
|
||||
|
||||
class _FakeProvider:
|
||||
def __init__(self, *, hz_cluster, hz_host, assets):
|
||||
captured.update(cluster=hz_cluster, host=hz_host, assets=list(assets))
|
||||
|
||||
class _FakeEngine:
|
||||
def __init__(self, provider):
|
||||
self.provider = provider
|
||||
|
||||
def step_live(self, a, b):
|
||||
pass
|
||||
|
||||
def get_market(self, b, a):
|
||||
return type("M", (), {"median_imbalance": 0.0, "agreement_pct": 0.0})()
|
||||
|
||||
monkeypatch.setattr("prod.clean_arch.violet.live_blue_source.HZOBProvider", _FakeProvider)
|
||||
monkeypatch.setattr("prod.clean_arch.violet.live_blue_source.OBFeatureEngine", _FakeEngine)
|
||||
_source_ob_market(["BTCUSDT"], bar_idx=0) # ob_engine=None → must construct BLUE's provider
|
||||
assert captured == {"cluster": HZ_CLUSTER, "host": HZ_HOST, "assets": ["BTCUSDT"]}
|
||||
|
||||
|
||||
# ── 4. mc_scale: begin_day's cat/env thresholds (the V3.4c bug fix) ───────────
|
||||
@pytest.mark.parametrize("cat, env, expected", [
|
||||
(0.15, 0.5, 0.5), # orange via cat>0.10
|
||||
(0.05, -0.5, 0.5), # orange via env<0 — old status-code returned GREEN→1.0 (bug)
|
||||
(0.10, -0.001, 0.5),
|
||||
(0.28, 0.5, 1.0), # red via cat>0.25 — old status-code: ORANGE→0.5 (bug)
|
||||
(0.05, -1.5, 1.0), # red via env<-1.0
|
||||
(0.30, -2.0, 1.0),
|
||||
(0.05, 0.5, 1.0), # benign
|
||||
(0.10, 0.0, 1.0),
|
||||
])
|
||||
def test_derive_mc_scale_matches_blue_begin_day_formula(cat, env, expected):
|
||||
payload = json.dumps({"catastrophic_prob": cat, "envelope_score": env, "status": "IGNORED"})
|
||||
assert _derive_mc_scale(payload) == expected
|
||||
|
||||
|
||||
def test_derive_mc_scale_neutral_when_fields_missing_or_garbage():
|
||||
assert _derive_mc_scale(json.dumps({"status": "ORANGE"})) == 1.0 # label must be ignored
|
||||
assert _derive_mc_scale(json.dumps({"catastrophic_prob": 0.15})) == 1.0
|
||||
assert _derive_mc_scale(json.dumps({"envelope_score": -0.5})) == 1.0
|
||||
assert _derive_mc_scale("not json") == 1.0
|
||||
assert _derive_mc_scale(None) == 1.0
|
||||
assert _derive_mc_scale({"catastrophic_prob": "bad", "envelope_score": 0.5}) == 1.0
|
||||
|
||||
|
||||
# ── 5. integration: full plane sourced + composed ────────────────────────────
|
||||
def _client_with_scan(scan: dict, *, posture="STALKER", **feat) -> _FakeClient:
|
||||
eigen = json.dumps({**scan, "w750_velocity": 0.0012})
|
||||
return _FakeClient({
|
||||
"DOLPHIN_FEATURES": _features(latest_eigen_scan=eigen, **feat),
|
||||
"DOLPHIN_STATE_BLUE": {"latest_nautilus": json.dumps({"posture": posture})},
|
||||
})
|
||||
|
||||
|
||||
def test_source_live_blue_sizing_factors_full_plane():
|
||||
history = LiveBlueScanHistory(maxlen=16, trade_direction=-1)
|
||||
for idx, px in enumerate([100.0, 99.5, 99.0, 98.4, 97.8, 97.0, 96.2], start=1):
|
||||
history.ingest_scan({"scan_number": idx, "timestamp": float(idx), "vel_div": -0.031,
|
||||
"assets": ["BTCUSDT"], "asset_prices": [px]})
|
||||
scan = {"scan_number": 8, "timestamp": 8.0, "vel_div": -0.031,
|
||||
"assets": ["BTCUSDT"], "asset_prices": [95.5]}
|
||||
client = _client_with_scan(scan, posture="RESTORED")
|
||||
ob = _FakeOBEngine(median_imbalance=0.12, agreement_pct=0.91)
|
||||
|
||||
res = source_live_blue_sizing_factors(
|
||||
client,
|
||||
assets=["BTCUSDT"],
|
||||
scan_history=history,
|
||||
client, assets=["BTCUSDT"], scan_history=history,
|
||||
selector=VioletAssetSelector(lookback_horizon=7),
|
||||
ob_engine=ob, bar_idx=8, date_str="2026-06-16",
|
||||
)
|
||||
assert isinstance(res.factors, SizingFactors)
|
||||
assert res.factors.posture == "STALKER"
|
||||
assert res.factors.mc_scale == 0.5
|
||||
assert res.factors.boost == 1.4
|
||||
assert res.factors.beta == 0.2
|
||||
assert res.factors.posture == "RESTORED"
|
||||
assert res.factors.esof_score == 0.4
|
||||
assert res.factors.ob_median_imbalance == 0.12
|
||||
assert res.factors.ob_agreement_pct == 0.91
|
||||
assert res.factors.mc_scale == 0.5 # cat=0.15/env=0.5 → orange
|
||||
assert res.factors.ob_median_imbalance == 0.12 and res.factors.ob_agreement_pct == 0.91
|
||||
assert ob.calls == [(("BTCUSDT",), 8)]
|
||||
# boost/beta = ACB recompute over the SAME exf+w750 (bit-identical pin)
|
||||
ref = AdaptiveCircuitBreaker().get_dynamic_boost_from_hz(
|
||||
date_str="2026-06-16", exf_snapshot=dict(_EXF), w750_velocity=0.0012, direction=-1)
|
||||
assert res.factors.boost == max(0.0, float(ref["boost"]))
|
||||
assert res.factors.beta == max(0.0, float(ref["beta"]))
|
||||
assert res.factors.dc_status == "CONFIRM"
|
||||
assert res.selected_asset == "BTCUSDT"
|
||||
|
||||
|
||||
def test_source_live_blue_sizing_factors_preserves_skip_contradict(monkeypatch):
|
||||
class FakeEngine:
|
||||
def __init__(self, provider):
|
||||
self.provider = provider
|
||||
def step_live(self, assets, bar_idx):
|
||||
pass
|
||||
def get_market(self, ts, assets):
|
||||
return type("M", (), {"median_imbalance": 0.0, "agreement_pct": 0.0})()
|
||||
|
||||
monkeypatch.setattr("prod.clean_arch.violet.live_blue_source.OBFeatureEngine", FakeEngine)
|
||||
history = LiveBlueScanHistory(maxlen=16, trade_direction=-1)
|
||||
for idx, px in enumerate([100.0, 100.5, 101.0, 101.6, 102.2, 102.9, 103.6], start=1):
|
||||
history.ingest_scan(
|
||||
{
|
||||
"scan_number": idx,
|
||||
"timestamp": float(idx),
|
||||
"vel_div": -0.031,
|
||||
"target_asset": "BTCUSDT",
|
||||
"assets": ["BTCUSDT"],
|
||||
"asset_prices": [px],
|
||||
}
|
||||
)
|
||||
client = _FakeClient(
|
||||
{
|
||||
"DOLPHIN_FEATURES": {
|
||||
"asset_BTCUSDT_ob": json.dumps(
|
||||
{"timestamp": 1.0, "bid_notional": [1, 2, 3, 4, 5], "ask_notional": [5, 4, 3, 2, 1],
|
||||
"bid_depth": [1, 1, 1, 1, 1], "ask_depth": [1, 1, 1, 1, 1]}
|
||||
),
|
||||
"acb_boost": json.dumps({"boost": 1.4, "beta": 0.2}),
|
||||
"mc_forewarner_latest": json.dumps({"catastrophic_prob": 0.02, "envelope_score": 0.9}),
|
||||
"esof_latest": json.dumps({"advisory_score": 0.4}),
|
||||
"latest_eigen_scan": json.dumps(
|
||||
{
|
||||
"scan_number": 8,
|
||||
"timestamp": 8.0,
|
||||
"vel_div": -0.031,
|
||||
"target_asset": "BTCUSDT",
|
||||
"assets": ["BTCUSDT"],
|
||||
"asset_prices": [104.2],
|
||||
}
|
||||
),
|
||||
},
|
||||
"DOLPHIN_STATE_BLUE": {"latest_nautilus": json.dumps({"posture": "APEX"})},
|
||||
}
|
||||
)
|
||||
res = source_live_blue_sizing_factors(
|
||||
client,
|
||||
assets=["BTCUSDT"],
|
||||
scan_history=history,
|
||||
selector=VioletAssetSelector(lookback_horizon=7),
|
||||
)
|
||||
assert res.factors.dc_status == "SKIP_CONTRADICT"
|
||||
def test_source_live_blue_sizing_factors_handles_anomalies():
|
||||
client = _FakeClient({
|
||||
"DOLPHIN_FEATURES": {
|
||||
"exf_latest": "not json", # → boost/beta neutral
|
||||
"mc_forewarner_latest": json.dumps({"catastrophic_prob": 0.02, "envelope_score": 0.9}),
|
||||
"esof_latest": "not json",
|
||||
"latest_eigen_scan": json.dumps({"assets": ["BTCUSDT"], "asset_prices": [0]}),
|
||||
},
|
||||
"DOLPHIN_STATE_BLUE": {"latest_nautilus": json.dumps({"posture": ""})},
|
||||
})
|
||||
res = source_live_blue_sizing_factors(client, assets=["BTCUSDT"], ob_engine=_FakeOBEngine())
|
||||
assert res.factors.posture == "APEX"
|
||||
assert res.factors.mc_scale == 1.0
|
||||
assert res.factors.boost == 1.0 and res.factors.beta == 0.0 # bad exf → ACB neutral
|
||||
assert res.factors.esof_score is None
|
||||
# OB engine is healthy (the anomalies are in exf/esof/prices), so it returns its 0.0/0.0.
|
||||
assert res.factors.ob_median_imbalance == 0.0 and res.factors.ob_agreement_pct == 0.0
|
||||
assert res.factors.dc_status == "NONE"
|
||||
assert res.selected_asset == "BTCUSDT"
|
||||
|
||||
|
||||
def test_live_blue_sequence_matches_blue_selector_and_dc_at_each_step(monkeypatch):
|
||||
class FakeEngine:
|
||||
def __init__(self, provider):
|
||||
self.provider = provider
|
||||
def step_live(self, assets, bar_idx):
|
||||
pass
|
||||
def get_market(self, ts, assets):
|
||||
return type("M", (), {"median_imbalance": 0.0, "agreement_pct": 0.0})()
|
||||
def test_source_live_blue_neutral_ob_when_no_engine_and_no_assets():
|
||||
# No ob_engine + no assets discoverable → OB neutral (None), no HZOBProvider connection.
|
||||
client = _FakeClient({
|
||||
"DOLPHIN_FEATURES": _features(latest_eigen_scan=json.dumps({"assets": [], "asset_prices": []})),
|
||||
"DOLPHIN_STATE_BLUE": {"latest_nautilus": json.dumps({"posture": "APEX"})},
|
||||
})
|
||||
res = source_live_blue_sizing_factors(client) # assets=None, scan has none → []
|
||||
assert res.factors.ob_median_imbalance is None and res.factors.ob_agreement_pct is None
|
||||
|
||||
monkeypatch.setattr("prod.clean_arch.violet.live_blue_source.OBFeatureEngine", FakeEngine)
|
||||
|
||||
def test_sequence_matches_blue_selector_and_dc_at_each_step():
|
||||
selector = VioletAssetSelector(lookback_horizon=7)
|
||||
history = LiveBlueScanHistory(maxlen=16, trade_direction=-1)
|
||||
signal_gen = AlphaSignalGenerator()
|
||||
|
||||
ref_gen = AlphaSignalGenerator(**BLUE_SIGNAL_GEN_KWARGS)
|
||||
scans = [
|
||||
{
|
||||
"scan_number": 1,
|
||||
"timestamp": 1.0,
|
||||
"vel_div": -0.010,
|
||||
"assets": ["BTCUSDT", "ETHUSDT"],
|
||||
"asset_prices": [100.0, 200.0],
|
||||
},
|
||||
{
|
||||
"scan_number": 2,
|
||||
"timestamp": 2.0,
|
||||
"vel_div": -0.031,
|
||||
"assets": ["BTCUSDT", "ETHUSDT"],
|
||||
"asset_prices": [99.0, 198.0],
|
||||
},
|
||||
{
|
||||
"scan_number": 3,
|
||||
"timestamp": 3.0,
|
||||
"vel_div": -0.041,
|
||||
"assets": ["BTCUSDT", "ETHUSDT"],
|
||||
"asset_prices": [98.0, 196.0],
|
||||
},
|
||||
{
|
||||
"scan_number": 4,
|
||||
"timestamp": 4.0,
|
||||
"vel_div": -0.031,
|
||||
"assets": ["BTCUSDT", "ETHUSDT"],
|
||||
"asset_prices": [97.0, 194.0],
|
||||
},
|
||||
{"scan_number": 1, "timestamp": 1.0, "vel_div": -0.010, "assets": ["BTCUSDT", "ETHUSDT"], "asset_prices": [100.0, 200.0]},
|
||||
{"scan_number": 2, "timestamp": 2.0, "vel_div": -0.031, "assets": ["BTCUSDT", "ETHUSDT"], "asset_prices": [99.0, 198.0]},
|
||||
{"scan_number": 3, "timestamp": 3.0, "vel_div": -0.041, "assets": ["BTCUSDT", "ETHUSDT"], "asset_prices": [98.0, 196.0]},
|
||||
{"scan_number": 4, "timestamp": 4.0, "vel_div": -0.031, "assets": ["BTCUSDT", "ETHUSDT"], "asset_prices": [97.0, 194.0]},
|
||||
]
|
||||
|
||||
for idx, scan in enumerate(scans, start=1):
|
||||
client = _FakeClient(
|
||||
{
|
||||
"DOLPHIN_FEATURES": {
|
||||
"asset_BTCUSDT_ob": json.dumps(
|
||||
{"timestamp": 1.0, "bid_notional": [1, 2, 3, 4, 5], "ask_notional": [5, 4, 3, 2, 1],
|
||||
"bid_depth": [1, 1, 1, 1, 1], "ask_depth": [1, 1, 1, 1, 1]}
|
||||
),
|
||||
"asset_ETHUSDT_ob": json.dumps(
|
||||
{"timestamp": 1.0, "bid_notional": [2, 3, 4, 5, 6], "ask_notional": [6, 5, 4, 3, 2],
|
||||
"bid_depth": [1, 1, 1, 1, 1], "ask_depth": [1, 1, 1, 1, 1]}
|
||||
),
|
||||
"acb_boost": json.dumps({"boost": 1.0, "beta": 0.0}),
|
||||
"mc_forewarner_latest": json.dumps({"catastrophic_prob": 0.02, "envelope_score": 0.9}),
|
||||
"esof_latest": json.dumps({"advisory_score": 0.3}),
|
||||
"latest_eigen_scan": json.dumps({**scan, "target_asset": "BTCUSDT"}),
|
||||
},
|
||||
"DOLPHIN_STATE_BLUE": {"latest_nautilus": json.dumps({"posture": "APEX"})},
|
||||
}
|
||||
)
|
||||
for i, scan in enumerate(scans, start=1):
|
||||
client = _client_with_scan(scan, posture="APEX")
|
||||
res = source_live_blue_sizing_factors(
|
||||
client,
|
||||
assets=["BTCUSDT", "ETHUSDT"],
|
||||
scan_history=history,
|
||||
selector=selector,
|
||||
client, assets=["BTCUSDT", "ETHUSDT"], scan_history=history,
|
||||
selector=selector, ob_engine=_FakeOBEngine(), bar_idx=i,
|
||||
)
|
||||
|
||||
# BLUE selector parity
|
||||
market = history.market_data(selector.lookback)
|
||||
expected_pick = selector.pick(market, regime_direction=-1)
|
||||
expected_asset = expected_pick.asset if expected_pick is not None else "BTCUSDT"
|
||||
assert res.selected_asset == expected_asset
|
||||
|
||||
# BLUE signal parity
|
||||
expected_signal = signal_gen.generate(
|
||||
vel_div=float(scan["vel_div"]),
|
||||
vel_div_history=None,
|
||||
ref = ref_gen.generate(
|
||||
vel_div=float(scan["vel_div"]), vel_div_history=None,
|
||||
asset_price_history=history.price_history(expected_asset),
|
||||
trade_direction=-1,
|
||||
asset=expected_asset,
|
||||
current_timestamp=float(scan["timestamp"]),
|
||||
trade_direction=-1, asset=expected_asset, current_timestamp=float(scan["timestamp"]),
|
||||
)
|
||||
assert res.factors.dc_status == expected_signal.dc_status
|
||||
assert res.factors.dc_status == ref.dc_status
|
||||
|
||||
|
||||
def test_live_blue_sequence_rejects_anomalous_values_without_poisoning_history(monkeypatch):
|
||||
class FakeEngine:
|
||||
def __init__(self, provider):
|
||||
self.provider = provider
|
||||
def step_live(self, assets, bar_idx):
|
||||
pass
|
||||
def get_market(self, ts, assets):
|
||||
return type("M", (), {"median_imbalance": 0.0, "agreement_pct": 0.0})()
|
||||
|
||||
monkeypatch.setattr("prod.clean_arch.violet.live_blue_source.OBFeatureEngine", FakeEngine)
|
||||
def test_sequence_rejects_anomalous_values_without_poisoning_history():
|
||||
history = LiveBlueScanHistory(maxlen=16, trade_direction=-1)
|
||||
selector = VioletAssetSelector(lookback_horizon=7)
|
||||
scan = {
|
||||
"scan_number": 99,
|
||||
"timestamp": 99.0,
|
||||
"vel_div": -0.031,
|
||||
"assets": ["BTCUSDT", "ETHUSDT"],
|
||||
"asset_prices": [float("nan"), -1.0],
|
||||
"target_asset": "BTCUSDT",
|
||||
}
|
||||
client = _FakeClient(
|
||||
{
|
||||
"DOLPHIN_FEATURES": {
|
||||
"asset_BTCUSDT_ob": json.dumps(
|
||||
{"timestamp": 1.0, "bid_notional": [1, 2, 3, 4, 5], "ask_notional": [5, 4, 3, 2, 1],
|
||||
"bid_depth": [1, 1, 1, 1, 1], "ask_depth": [1, 1, 1, 1, 1]}
|
||||
),
|
||||
"acb_boost": json.dumps({"boost": 1.0, "beta": 0.0}),
|
||||
"mc_forewarner_latest": json.dumps({"catastrophic_prob": 0.02, "envelope_score": 0.9}),
|
||||
"esof_latest": json.dumps({"advisory_score": 0.3}),
|
||||
"latest_eigen_scan": json.dumps(scan),
|
||||
},
|
||||
"DOLPHIN_STATE_BLUE": {"latest_nautilus": json.dumps({"posture": "APEX"})},
|
||||
}
|
||||
)
|
||||
scan = {"scan_number": 99, "timestamp": 99.0, "vel_div": -0.031,
|
||||
"assets": ["BTCUSDT", "ETHUSDT"], "asset_prices": [float("nan"), -1.0]}
|
||||
client = _client_with_scan(scan, posture="APEX")
|
||||
res = source_live_blue_sizing_factors(
|
||||
client,
|
||||
assets=["BTCUSDT", "ETHUSDT"],
|
||||
scan_history=history,
|
||||
selector=selector,
|
||||
client, assets=["BTCUSDT", "ETHUSDT"], scan_history=history,
|
||||
selector=VioletAssetSelector(lookback_horizon=7), ob_engine=_FakeOBEngine(),
|
||||
)
|
||||
assert res.selected_asset == "BTCUSDT"
|
||||
assert res.factors.dc_status == "NONE"
|
||||
@@ -334,75 +375,7 @@ def test_live_blue_sequence_rejects_anomalous_values_without_poisoning_history(m
|
||||
assert history.price_history("ETHUSDT") == []
|
||||
|
||||
|
||||
def test_source_live_blue_sizing_factors_handles_anomalies(monkeypatch):
|
||||
class FakeEngine:
|
||||
def __init__(self, provider):
|
||||
self.provider = provider
|
||||
def step_live(self, assets, bar_idx):
|
||||
raise RuntimeError("boom")
|
||||
def get_market(self, ts, assets):
|
||||
return type("M", (), {"median_imbalance": 0.0, "agreement_pct": 0.0})()
|
||||
|
||||
monkeypatch.setattr("prod.clean_arch.violet.live_blue_source.OBFeatureEngine", FakeEngine)
|
||||
client = _FakeClient(
|
||||
{
|
||||
"DOLPHIN_FEATURES": {
|
||||
"asset_BTCUSDT_ob": json.dumps(
|
||||
{"timestamp": 1.0, "bid_notional": [1, 2, 3, 4, 5], "ask_notional": [5, 4, 3, 2, 1],
|
||||
"bid_depth": [1, 1, 1, 1, 1], "ask_depth": [1, 1, 1, 1, 1]}
|
||||
),
|
||||
"acb_boost": json.dumps({"boost": -9, "beta": "bad"}),
|
||||
"mc_forewarner_latest": json.dumps({"catastrophic_prob": 0.02, "envelope_score": 0.9}),
|
||||
"esof_latest": "not json",
|
||||
"latest_eigen_scan": json.dumps({"target_asset": "BTCUSDT", "assets": ["BTCUSDT"], "asset_prices": [0]}),
|
||||
},
|
||||
"DOLPHIN_STATE_BLUE": {"latest_nautilus": json.dumps({"posture": ""})},
|
||||
}
|
||||
)
|
||||
res = source_live_blue_sizing_factors(client, assets=["BTCUSDT"])
|
||||
assert res.factors.posture == "APEX"
|
||||
assert res.factors.mc_scale == 1.0
|
||||
assert res.factors.boost == 0.0
|
||||
assert res.factors.beta == 0.0
|
||||
assert res.factors.esof_score is None
|
||||
assert res.factors.ob_median_imbalance is None
|
||||
assert res.factors.ob_agreement_pct is None
|
||||
assert res.factors.dc_status == "NONE"
|
||||
assert res.selected_asset == "BTCUSDT"
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"cat, env, expected",
|
||||
[
|
||||
# mc_orange (→0.5): not red, and (env<0 OR cat>0.10)
|
||||
(0.15, 0.5, 0.5), # orange via cat>0.10
|
||||
(0.05, -0.5, 0.5), # orange via env<0 — OLD status-code returned GREEN→1.0 (the bug)
|
||||
(0.10, -0.001, 0.5), # orange via env<0 boundary (cat==0.10 not >0.10)
|
||||
# red (→1.0 here; BLUE halts separately via regime_dd_halt)
|
||||
(0.28, 0.5, 1.0), # red via cat>0.25 — OLD status-code: 0.28<0.30→ORANGE→0.5 (the bug)
|
||||
(0.05, -1.5, 1.0), # red via env<-1.0
|
||||
(0.30, -2.0, 1.0), # red via both
|
||||
# ok (→1.0): not red, not orange
|
||||
(0.05, 0.5, 1.0), # benign
|
||||
(0.10, 0.0, 1.0), # cat==0.10 (not >0.10), env==0 (not <0) → ok
|
||||
],
|
||||
)
|
||||
def test_derive_mc_scale_matches_blue_begin_day_formula(cat, env, expected):
|
||||
payload = json.dumps({"catastrophic_prob": cat, "envelope_score": env, "status": "IGNORED"})
|
||||
assert _derive_mc_scale(payload) == expected
|
||||
|
||||
|
||||
def test_derive_mc_scale_neutral_when_fields_missing_or_garbage():
|
||||
# The published `status` label must NOT be used — payloads lacking the source
|
||||
# fields derive neutral (1.0), never a haircut from a stale/foreign label.
|
||||
assert _derive_mc_scale(json.dumps({"status": "ORANGE"})) == 1.0
|
||||
assert _derive_mc_scale(json.dumps({"catastrophic_prob": 0.15})) == 1.0 # missing env
|
||||
assert _derive_mc_scale(json.dumps({"envelope_score": -0.5})) == 1.0 # missing cat
|
||||
assert _derive_mc_scale("not json") == 1.0
|
||||
assert _derive_mc_scale(None) == 1.0
|
||||
assert _derive_mc_scale({"catastrophic_prob": "bad", "envelope_score": 0.5}) == 1.0
|
||||
|
||||
|
||||
# ── 6. live HZ smoke (env-bound; deselect with -k "not live_hz_smoke") ────────
|
||||
def test_live_hz_smoke_reads_current_state():
|
||||
client = hazelcast.HazelcastClient(cluster_name="dolphin", cluster_members=["localhost:5701"])
|
||||
try:
|
||||
@@ -412,3 +385,4 @@ def test_live_hz_smoke_reads_current_state():
|
||||
assert isinstance(res.factors, SizingFactors)
|
||||
assert res.factors.posture in {"APEX", "STALKER", "RESTORED", "TURTLE", "HIBERNATE"}
|
||||
assert res.factors.mc_scale in {0.5, 1.0}
|
||||
assert res.factors.boost >= 0.0 and res.factors.beta >= 0.0
|
||||
|
||||
Reference in New Issue
Block a user