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feat(tick_precision): Increased regime BULL/BEAR% to two-decimal display.

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This commit is contained in:
HJ Normey
2025-09-03 20:13:44 +02:00
parent 4d8ec0ddc6
commit 4748a7ba62
1 changed files with 22 additions and 10 deletions
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32
nautilus_actor_test_implementation_5x.py
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@@ -1126,25 +1126,37 @@ class DOLPHINRegimeActor(Actor):
except Exception as e:
self.log.error(f"Nautilus ActorExecutor: Failed to publish regime result: {e}")
# Log regime changes
if not self.regime_history or regime != self.regime_history[-1]:
self.log.info(f"REGIME CHANGE: {regime.value} | Bull: {bull_ratio:.1%} "
f"Bear: {bear_ratio:.1%} Sideways: {sideways_ratio:.1%} | "
f"Confidence: {confidence:.1%} | Analyzed: {analyzed}/{total_symbols}")
self.log.info(f"REGIME CHANGE: {regime.value} | Bull: {bull_ratio:.2%} "
f"Bear: {bear_ratio:.2%} Sideways: {sideways_ratio:.2%} ({bullish}/{bearish}) | "
f"Confidence: {confidence:.2%} | Analyzed: {analyzed}/{total_symbols}")
self.regime_history.append(regime)
# Periodic regime status (even without changes)
if self.regime_calculations % 1 == 0: # Every calculation
self.log.info(f"REGIME STATUS: {regime.value} | Bull: {bull_ratio:.1%} "
f"Bear: {bear_ratio:.1%} | Processed: {self.processed_ticks} ticks")
if self.regime_calculations % 50 == 0: # Every second, approx, given avg. tick rate
# Determine color based on regime
if regime == MarketRegime.BULL:
color_code = "\033[92m" # Green
elif regime == MarketRegime.BEAR:
color_code = "\033[91m" # Red
else: # SIDEWAYS
color_code = "\033[93m" # Yellow
# Reset color code
reset_code = "\033[0m"
self.log.info(f"{color_code}REGIME STATUS: {regime.value} | Bull: {bull_ratio:.2%} "
f"Bear: {bear_ratio:.2%} ({bullish}/{bearish}) | Processed: {self.processed_ticks} ticks{reset_code}")
# NEW: Log symbol pattern and counts
if symbol_pattern: # Only if we have symbols to show
pattern_str = " ".join(symbol_pattern) + " " # Create pattern with spaces
bull_count = sum(1 for s in symbol_pattern if s.startswith("B"))
bear_count = sum(1 for s in symbol_pattern if s.startswith("X"))
self.log.info(f"{pattern_str} and totals: BULLS:{bull_count}/BEARS:{bear_count}")
self.log.debug(f"{pattern_str} and totals: BULLS:{bull_count}/BEARS:{bear_count}")
def _calculate_confidence(self, bull_ratio: float, bear_ratio: float,
analyzed: int, total: int) -> float:
@@ -1259,7 +1271,7 @@ def test_siloqy_actors_with_nautilus_process_management():
"candle_interval_ms": 15 * 60 * 1000,
"throttle_mode": True, # ENABLED: Safe for dual instance testing
"throttle_rate_limit_seconds": 10.0, # 10s between batches (vs 2.5s)
"max_symbols_throttled": 100 # Only 100 symbols (vs 2000+)
"max_symbols_throttled": 414 # Only 100 symbols (vs 2000+)
}
)
@@ -1269,7 +1281,7 @@ def test_siloqy_actors_with_nautilus_process_management():
config={
"component_id": "SILOQY-MAIN-ACTOR",
"candle_interval_ms": 15 * 60 * 1000,
"throttle_mode": True, # ENABLED: Reduced tick generation
"throttle_mode": False, # ENABLED: Reduced tick generation
"enable_real_data": True # CHANGE TO True for real WebSocket data
}
)