initial: import DOLPHIN baseline 2026-04-21 from dolphinng5_predict working tree
Includes core prod + GREEN/BLUE subsystems: - prod/ (BLUE harness, configs, scripts, docs) - nautilus_dolphin/ (GREEN Nautilus-native impl + dvae/ preserved) - adaptive_exit/ (AEM engine + models/bucket_assignments.pkl) - Observability/ (EsoF advisor, TUI, dashboards) - external_factors/ (EsoF producer) - mc_forewarning_qlabs_fork/ (MC regime/envelope) Excludes runtime caches, logs, backups, and reproducible artifacts per .gitignore.
This commit is contained in:
hjnormey
271
nautilus_dolphin/tests/test_adaptive_circuit_breaker.py
Executable file
271
nautilus_dolphin/tests/test_adaptive_circuit_breaker.py
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"""
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Tests for Adaptive Circuit Breaker v5.
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"""
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import unittest
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from datetime import datetime
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from unittest.mock import patch, MagicMock
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import numpy as np
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from nautilus_dolphin.nautilus.adaptive_circuit_breaker import (
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AdaptiveCircuitBreaker, ACBConfig, ACBPositionSizer, get_acb_cut_for_date
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)
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class TestACBConfig(unittest.TestCase):
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"""Test ACB configuration."""
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def test_default_config(self):
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"""Test default configuration values."""
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config = ACBConfig()
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# Check cut rates (v5 configuration)
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self.assertEqual(config.CUT_RATES[0], 0.00)
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self.assertEqual(config.CUT_RATES[1], 0.15)
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self.assertEqual(config.CUT_RATES[2], 0.45)
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self.assertEqual(config.CUT_RATES[3], 0.55)
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self.assertEqual(config.CUT_RATES[4], 0.75)
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self.assertEqual(config.CUT_RATES[5], 0.80)
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# Check thresholds
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self.assertEqual(config.FUNDING_VERY_BEARISH, -0.0001)
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self.assertEqual(config.DVOL_EXTREME, 80)
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self.assertEqual(config.FNG_EXTREME_FEAR, 25)
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class TestAdaptiveCircuitBreaker(unittest.TestCase):
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"""Test Adaptive Circuit Breaker functionality."""
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def setUp(self):
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"""Set up test fixtures."""
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self.acb = AdaptiveCircuitBreaker()
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def test_signal_calculation_no_stress(self):
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"""Test signal calculation with no stress factors."""
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factors = {
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'funding_btc': 0.0001, # Positive funding (bullish)
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'dvol_btc': 40.0, # Low volatility
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'fng': 60, # Greed (bullish)
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'taker': 1.1 # Buying pressure
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}
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result = self.acb._calculate_signals(factors)
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self.assertEqual(result['signals'], 0.0)
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self.assertEqual(result['severity'], 0)
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def test_signal_calculation_funding_only(self):
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"""Test signal calculation with funding stress only."""
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factors = {
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'funding_btc': -0.00015, # Very bearish funding
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'dvol_btc': 40.0,
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'fng': 60,
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'taker': 1.1
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}
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result = self.acb._calculate_signals(factors)
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self.assertEqual(result['signals'], 1.0) # 1 signal from funding
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self.assertEqual(result['severity'], 2)
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def test_signal_calculation_multiple_stress(self):
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"""Test signal calculation with multiple stress factors."""
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factors = {
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'funding_btc': -0.00015, # Very bearish funding (1.0 signals, sev 2)
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'dvol_btc': 85.0, # Extreme volatility (1.0 signals, sev 2)
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'fng': 20, # Extreme fear (confirmed, 1.0 signals, sev 2)
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'taker': 0.75 # Selling pressure (1.0 signals, sev 1)
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}
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result = self.acb._calculate_signals(factors)
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# Should have 4 signals (funding + dvol + fng + taker)
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self.assertGreaterEqual(result['signals'], 3.0)
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self.assertGreater(result['severity'], 0)
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def test_cut_mapping(self):
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"""Test signal to cut rate mapping."""
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test_cases = [
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(0.0, 0.00), # 0 signals -> 0% cut
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(0.5, 0.00), # 0.5 signals -> 0% cut (below threshold)
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(1.0, 0.15), # 1 signal -> 15% cut
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(1.5, 0.15), # 1.5 signals -> 15% cut
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(2.0, 0.45), # 2 signals -> 45% cut
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(2.5, 0.45), # 2.5 signals -> 45% cut
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(3.0, 0.55), # 3 signals -> 55% cut
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(4.0, 0.75), # 4 signals -> 75% cut
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(5.0, 0.80), # 5 signals -> 80% cut
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]
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for signals, expected_cut in test_cases:
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cut = self.acb._get_cut_from_signals(signals)
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self.assertEqual(cut, expected_cut,
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f"Failed for signals={signals}: got {cut}, expected {expected_cut}")
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def test_apply_cut_to_position_size(self):
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"""Test applying cut to position size."""
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base_size = 1000.0
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# Test with no stress (0% cut)
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with patch.object(self.acb, 'get_cut_for_date') as mock_get:
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mock_get.return_value = {'cut': 0.0, 'signals': 0.0}
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final_size, info = self.acb.apply_cut_to_position_size(base_size, '2026-02-06')
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self.assertEqual(final_size, base_size)
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# Test with moderate stress (45% cut)
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with patch.object(self.acb, 'get_cut_for_date') as mock_get:
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mock_get.return_value = {'cut': 0.45, 'signals': 2.0}
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final_size, info = self.acb.apply_cut_to_position_size(base_size, '2026-02-06')
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self.assertAlmostEqual(final_size, base_size * 0.55, places=10) # 1000 * (1 - 0.45)
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# Test with extreme stress (80% cut)
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with patch.object(self.acb, 'get_cut_for_date') as mock_get:
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mock_get.return_value = {'cut': 0.80, 'signals': 5.0}
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final_size, info = self.acb.apply_cut_to_position_size(base_size, '2026-02-06')
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self.assertAlmostEqual(final_size, base_size * 0.20, places=10) # 1000 * (1 - 0.80)
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def test_caching(self):
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"""Test that results are cached."""
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date_str = '2026-02-06'
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# First call should cache
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with patch.object(self.acb, '_load_external_factors') as mock_load:
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mock_load.return_value = {
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'funding_btc': -0.0001,
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'dvol_btc': 60,
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'fng': 40,
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'taker': 0.95
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}
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result1 = self.acb.get_cut_for_date(date_str)
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self.assertEqual(self.acb._stats['total_calls'], 1)
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self.assertEqual(self.acb._stats['cache_hits'], 0)
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# Second call should use cache
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result2 = self.acb.get_cut_for_date(date_str)
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self.assertEqual(self.acb._stats['total_calls'], 2)
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self.assertEqual(self.acb._stats['cache_hits'], 1)
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# Results should be identical
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self.assertEqual(result1['cut'], result2['cut'])
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def test_stats_tracking(self):
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"""Test statistics tracking."""
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# Clear stats
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self.acb.reset_stats()
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# Simulate some calls
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with patch.object(self.acb, '_load_external_factors') as mock_load:
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mock_load.return_value = {
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'funding_btc': -0.0001,
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'dvol_btc': 60,
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'fng': 40,
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'taker': 0.95
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}
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self.acb.get_cut_for_date('2026-02-06')
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self.acb.get_cut_for_date('2026-02-07')
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self.acb.get_cut_for_date('2026-02-06') # Should be cached
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stats = self.acb.get_stats()
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self.assertEqual(stats['total_calls'], 3)
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self.assertEqual(stats['cache_hits'], 1)
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self.assertGreater(stats['cache_hit_rate'], 0)
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class TestACBPositionSizer(unittest.TestCase):
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"""Test ACB Position Sizer."""
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def setUp(self):
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"""Set up test fixtures."""
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self.sizer = ACBPositionSizer()
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def test_enabled_disabled(self):
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"""Test enabling/disabling ACB."""
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self.assertTrue(self.sizer.is_enabled())
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self.sizer.disable()
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self.assertFalse(self.sizer.is_enabled())
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# When disabled, should return base size unchanged
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size, info = self.sizer.calculate_size(1000.0, '2026-02-06')
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self.assertEqual(size, 1000.0)
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self.assertFalse(info['enabled'])
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self.sizer.enable()
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self.assertTrue(self.sizer.is_enabled())
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def test_calculate_size_with_acb(self):
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"""Test calculate size with ACB enabled."""
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base_size = 1000.0
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with patch.object(self.sizer.acb, 'get_cut_for_date') as mock_get:
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mock_get.return_value = {
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'cut': 0.15,
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'signals': 1.0,
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'factors': {}
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}
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final_size, info = self.sizer.calculate_size(base_size, '2026-02-06')
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self.assertAlmostEqual(final_size, base_size * 0.85, places=10) # 15% cut
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self.assertEqual(info['base_size'], base_size)
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self.assertAlmostEqual(info['final_size'], final_size, places=10)
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self.assertAlmostEqual(info['reduction_pct'], 15.0, places=10)
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class TestIntegration(unittest.TestCase):
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"""Integration tests."""
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def test_feb_6_scenario(self):
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"""
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Test Feb 6, 2026 scenario (actual crash day).
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Expected signals:
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- Funding: -0.000137 (very bearish)
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- DVOL: 58.9 (elevated)
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- FNG: 14 (extreme fear)
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Expected: 3+ signals -> 55% cut
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"""
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acb = AdaptiveCircuitBreaker()
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# Mock the external factors for Feb 6
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with patch.object(acb, '_load_external_factors') as mock_load:
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mock_load.return_value = {
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'funding_btc': -0.000137, # Very bearish
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'dvol_btc': 58.9, # Elevated
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'fng': 14, # Extreme fear
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'taker': 0.85, # Mild selling
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'available': True
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}
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result = acb.get_cut_for_date('2026-02-06')
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# Should detect 3+ signals
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self.assertGreaterEqual(result['signals'], 2.0)
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# Should apply 55% or higher cut
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self.assertGreaterEqual(result['cut'], 0.45)
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def test_normal_day_scenario(self):
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"""Test normal market day scenario."""
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acb = AdaptiveCircuitBreaker()
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with patch.object(acb, '_load_external_factors') as mock_load:
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mock_load.return_value = {
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'funding_btc': 0.00005, # Slightly positive
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'dvol_btc': 45.0, # Normal volatility
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'fng': 55, # Neutral/greed
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'taker': 1.05, # Slight buying
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'available': True
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}
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result = acb.get_cut_for_date('2026-01-15')
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# Should detect 0-1 signals
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self.assertLessEqual(result['signals'], 1.0)
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# Should apply 0% or 15% cut
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self.assertLessEqual(result['cut'], 0.15)
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if __name__ == '__main__':
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unittest.main()
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