first (part 2: other directories)

2026-04-16 15:11:25 +03:00
parent 7814e0bc6b
commit 2f0b85a0c7
203 changed files with 59989 additions and 0 deletions
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+#!/usr/bin/env python3
+"""Test UpsetEngine on Bayern vs Augsburg match."""
+
+import sys
+sys.path.insert(0, 'ai-engine')
+from features.upset_engine import get_upset_engine
+from data.db import get_clean_dsn
+import psycopg2
+from psycopg2.extras import RealDictCursor
+from datetime import datetime
+
+# Get match data
+conn = psycopg2.connect(get_clean_dsn())
+cur = conn.cursor(cursor_factory=RealDictCursor)
+
+cur.execute("""
+SELECT m.id, m.home_team_id, m.away_team_id, m.score_home, m.score_away, 
+       m.ht_score_home, m.ht_score_away, m.mst_utc,
+       th.name as home_name, ta.name as away_name, l.name as league
+FROM matches m
+JOIN teams th ON m.home_team_id = th.id
+JOIN teams ta ON m.away_team_id = ta.id
+JOIN leagues l ON m.league_id = l.id
+WHERE m.id = 'en78ih6ec7exnpxcku3xc3das'
+""")
+match = cur.fetchone()
+conn.close()
+
+if match:
+    print('=== Bayern Munch vs Augsburg (24 Jan 2026) ===')
+    print(f"Actual: HT {match['ht_score_home']}-{match['ht_score_away']}, FT {match['score_home']}-{match['score_away']} (1/2 Reversal!)")
+    print()
+    
+    # Test UpsetEngine
+    engine = get_upset_engine()
+    
+    # Calculate upset potential using get_features
+    result = engine.get_features(
+        home_team_name=match['home_name'],
+        home_team_id=match['home_team_id'],
+        away_team_name=match['away_name'],
+        league_name=match['league'],
+        home_position=1,  # Bayern is typically top
+        away_position=15,  # Augsburg is typically lower
+        match_date_ms=match['mst_utc'],
+        total_teams=18,
+    )
+    
+    print('UpsetEngine Results:')
+    print(f"  Atmosphere Score: {result.get('upset_atmosphere', 0):.2f}")
+    print(f"  Motivation Score: {result.get('upset_motivation', 0):.2f}")
+    print(f"  Fatigue Score: {result.get('upset_fatigue', 0):.2f}")
+    print(f"  Historical Score: {result.get('upset_historical', 0):.2f}")
+    print(f"  TOTAL UPSET POTENTIAL: {result.get('upset_potential', 0):.2f}")
+    print()
+    
+    # Check if upset was detected
+    if result.get('upset_potential', 0) > 0.5:
+        print("🔥 HIGH UPSET POTENTIAL DETECTED!")
+    elif result.get('upset_potential', 0) > 0.3:
+        print("⚠️ MEDIUM UPSET POTENTIAL")
+    else:
+        print("❌ LOW UPSET POTENTIAL - Model did not detect this as upset")
+else:
+    print('Match not found')