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analysis/Curve.py

@@ -707,7 +707,7 @@ class Curve:
     def _plot_gauge(self, ax, value):
         """Disegna un gauge per il pushing score"""
         # Sfondo gauge
-        theta = np.linspace(0, np.pi, 100)
+        theta = np.linspace(np.pi, 0, 100)
         
         # Arco di sfondo
         ax.plot(np.cos(theta), np.sin(theta), 'lightgray', linewidth=20, solid_capstyle='round')
@@ -722,60 +722,66 @@ class Curve:
         else:
             color = '#e74c3c'  # Rosso
         
-        # Disegna l'arco fino al valore
-        theta_val = np.linspace(0, np.pi * (value/100), 50)
+        # Disegna l'arco fino al valore (da sinistra a destra)
+        theta_val = np.linspace(np.pi, np.pi * (1 - value/100), 50)
         ax.plot(np.cos(theta_val), np.sin(theta_val), color, linewidth=20, solid_capstyle='round')
         
-        # Testo centrale
-        ax.text(0, -0.3, f'{value:.1f}', ha='center', va='center', 
+        # Testo centrale (numero più in alto, scritta più in basso)
+        ax.text(0, -0.25, f'{value:.1f}', ha='center', va='center', 
                 fontsize=48, fontweight='bold', color=color)
-        ax.text(0, -0.5, 'PUSHING SCORE', ha='center', va='center', 
+        ax.text(0, -0.7, 'PUSHING SCORE', ha='center', va='center', 
                 fontsize=14, color='gray')
         
         # Etichette
         ax.text(-1, 0, '0', ha='center', va='center', fontsize=12, fontweight='bold')
         ax.text(1, 0, '100', ha='center', va='center', fontsize=12, fontweight='bold')
-        ax.text(-0.7, 0.7, 'GESTIONE', ha='center', va='center', fontsize=10, color='#2ecc71')
-        ax.text(0.7, 0.7, 'SPINTA', ha='center', va='center', fontsize=10, color='#e74c3c')
+        
+        # Etichette Spinta/Gestione fuori dal cerchio
+        # Posizionate leggermente sopra e esterne
+        ax.text(-1.5, 0.6, 'GESTIONE', ha='center', va='center', fontsize=10, color='#2ecc71', fontweight='bold')
+        ax.text(1.5, 0.6, 'SPINTA', ha='center', va='center', fontsize=10, color='#e74c3c', fontweight='bold')
         
         ax.set_xlim(-1.5, 1.5)
-        ax.set_ylim(-0.7, 1.2)
+        ax.set_ylim(-0.8, 1.3)
         ax.axis('off')
         ax.set_aspect('equal')
     
-    def plot_all(self, save_path: Optional[str] = None):
+    def plot_all(self, save_path: Optional[str] = None, show_only_score=False):
         """
         Genera tutti i grafici
         save_path: se specificato, salva i grafici invece di mostrarli
+        show_only_score: se True, genera solo il grafico del pushing score
         """
         if not save_path:
             plt.close('all')
             
         print("Generazione grafici in corso...\n")
         
-        # Grafico 1: G Forces
-        print("1/4 - Analisi Forze G...")
-        fig1 = self.plot_g_forces_map()
-        if save_path:
-            fig1.savefig(f'{save_path}_g_forces.png', dpi=150, bbox_inches='tight')
-            print(f"   ✓ Salvato: {save_path}_g_forces.png")
-        
-        # Grafico 2: Driver Inputs
-        print("2/4 - Input del Pilota...")
-        fig2 = self.plot_driver_inputs()
-        if save_path:
-            fig2.savefig(f'{save_path}_inputs.png', dpi=150, bbox_inches='tight')
-            print(f"   ✓ Salvato: {save_path}_inputs.png")
-        
-        # Grafico 3: Tire Management
-        print("3/4 - Gestione Gomme...")
-        fig3 = self.plot_tire_management()
-        if save_path:
-            fig3.savefig(f'{save_path}_tires.png', dpi=150, bbox_inches='tight')
-            print(f"   ✓ Salvato: {save_path}_tires.png")
-        
-        # Grafico 4: Pushing Analysis
-        print("4/4 - Analisi Spinta...")
+        if not show_only_score:
+            # Grafico 1: G Forces
+            print("1/4 - Analisi Forze G...")
+            fig1 = self.plot_g_forces_map()
+            if save_path:
+                fig1.savefig(f'{save_path}_g_forces.png', dpi=150, bbox_inches='tight')
+                print(f"   ✓ Salvato: {save_path}_g_forces.png")
+            
+            # Grafico 2: Driver Inputs
+            print("2/4 - Input del Pilota...")
+            fig2 = self.plot_driver_inputs()
+            if save_path:
+                fig2.savefig(f'{save_path}_inputs.png', dpi=150, bbox_inches='tight')
+                print(f"   ✓ Salvato: {save_path}_inputs.png")
+            
+            # Grafico 3: Tire Management
+            print("3/4 - Gestione Gomme...")
+            fig3 = self.plot_tire_management()
+            if save_path:
+                fig3.savefig(f'{save_path}_tires.png', dpi=150, bbox_inches='tight')
+                print(f"   ✓ Salvato: {save_path}_tires.png")
+        
+        # Grafico 4: Pushing Analysis (Sempre generato o solo questo se flag attivo)
+        step_msg = "4/4" if not show_only_score else "1/1"
+        print(f"{step_msg} - Analisi Spinta...")
         fig4 = self.plot_pushing_analysis()
         if save_path:
             fig4.savefig(f'{save_path}_pushing.png', dpi=150, bbox_inches='tight')
@@ -785,7 +791,11 @@ class Curve:
         
         if not save_path:
             plt.show()
-            input("\n[INVIO per continuare...]")
+            # Se stiamo mostrando solo lo score, magari non serve l'input bloccante se è un loop veloce,
+            # ma per sicurezza lo lasciamo o lo condizioniamo. 
+            # L'utente ha chiesto "solo per stampare lo score", assumiamo voglia vederlo.
+            if not show_only_score:
+                input("\n[INVIO per continuare...]")
             plt.close('all')
         else:
             plt.close('all')

analysis/curve_visualizer.py

@@ -0,0 +1,67 @@
+from src.analysis.CurveDetector import CurveDetector
+from src.models.dataset_loader import download_raw_telemetry_from_hf
+from dataclasses import dataclass
+
+
+# =============================================================================
+# CONFIGURATION
+# =============================================================================
+@dataclass
+class VisualizerConfig:
+    """Configuration for curve visualization."""
+    
+    # ----- Paths -----
+    telemetry_path: str = "data/2025-main/Italian Grand Prix/Qualifying/LEC/1_tel.json"
+    corners_path: str = "data/2025-main/Italian Grand Prix/Race/corners.json"
+    
+    # ----- Hugging Face -----
+    download_from_hf: bool = True  # True = download raw telemetry from HF
+    raw_data_subfolder: str = "2025-main"  # Subfolder to download (2024-main or 2025-main)
+    
+    # ----- Visualization -----
+    show_track: bool = False    # Show track overview with curves
+    show_score: bool = False    # Show pushing score
+
+
+CONFIG = VisualizerConfig()
+
+
+# =============================================================================
+# MAIN
+# =============================================================================
+def main(config: VisualizerConfig = CONFIG):
+    """Funzione main per visualizzazione curve."""
+    
+    print("=" * 60)
+    print("Curve Visualizer")
+    print("=" * 60)
+    
+    # Download raw data from HF if configured
+    if config.download_from_hf:
+        print("\n[1/3] Downloading raw telemetry from Hugging Face...")
+        download_raw_telemetry_from_hf(subfolder=config.raw_data_subfolder)
+    else:
+        print("\n[1/3] Using local telemetry data...")
+    
+    # Detect curves
+    print("\n[2/3] Detecting curves...")
+    curve_detector = CurveDetector(config.telemetry_path, config.corners_path)
+    curves = curve_detector.calcolo_curve()
+    print(f"Detected {len(curves)} curves")
+    
+    # Visualize
+    print("\n[3/3] Visualizing...")
+    curve_detector.grafico(curves, config.show_track)
+    curve_detector.plot_curve_trajectories(curves)
+
+    if config.show_score:
+        for curve in curves:
+            curve.plot_all(show_only_score=config.show_score)
+    
+    print("\n" + "=" * 60)
+    print("Done!")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    main()

analysis/dataset_normalization.py

@@ -31,6 +31,37 @@ PADDING_VALUE = DEFAULT_CONFIG.padding_value
 COMPOUND_CATEGORIES = list(DEFAULT_CONFIG.compound_categories)
 MAX_SAMPLES_PER_CURVE = DEFAULT_CONFIG.max_samples_per_curve
 
+# Massimo TireLife osservato per ogni compound (calcolato dal dataset 2024-2025)
+# Usato per normalizzare TireLife relativamente al compound:
+# TireLifeNorm = TireLife / max_per_compound → [0, 1]
+TIRE_LIFE_MAX_PER_COMPOUND = {
+    'SOFT': 30,
+    'MEDIUM': 40,
+    'HARD': 50,
+    'INTERMEDIATE': 35,
+    'WET': 20,
+}
+# Fallback per compound sconosciuti
+TIRE_LIFE_MAX_DEFAULT = 50
+
+
+def normalize_tire_life(life: float, compound: str) -> float:
+    """
+    Normalizza TireLife relativamente al max del compound.
+    
+    Compound diversi hanno durate diverse: una SOFT con TireLife=10
+    è molto più consumata di una HARD con TireLife=10.
+    
+    Args:
+        life: Valore grezzo di TireLife (laps)
+        compound: Nome del compound (SOFT, MEDIUM, HARD, ...)
+        
+    Returns:
+        TireLife normalizzato in [0, 1] (0=fresca, 1=fine vita)
+    """
+    max_life = TIRE_LIFE_MAX_PER_COMPOUND.get(compound, TIRE_LIFE_MAX_DEFAULT)
+    return min(life / max_life, 1.0)
+
 
 # =============================================================================
 # SINGLE CURVE NORMALIZATION (for inference)
@@ -93,8 +124,11 @@ def curve_to_raw_features(
     padding = config.padding_value
     categories = config.compound_categories
     
-    # Prepare raw features with padding
-    life = curve.life if hasattr(curve, 'life') else 0
+    # Normalize TireLife relative to compound
+    raw_life = curve.life if hasattr(curve, 'life') else 0
+    compound = curve.compound if hasattr(curve, 'compound') else 'UNKNOWN'
+    life = normalize_tire_life(raw_life, compound)
+    
     speed = pad_or_truncate(curve.speed, max_samples, padding)
     rpm = pad_or_truncate(curve.rpm, max_samples, padding)
     throttle = pad_or_truncate(curve.throttle, max_samples, padding)
@@ -484,7 +518,7 @@ def load_normalized_data(
 if __name__ == "__main__":
     # Configuration
     config = NormalizationConfig(
-        input_csv_path="data/dataset/dataset_curves.csv",
+        input_csv_path="data/dataset/dataset_curves_2024_2025.csv",
         output_dir="data/dataset",
         output_filename="normalized_dataset.npz"
     )
@@ -498,10 +532,19 @@ if __name__ == "__main__":
         decimal="."
     )
     
-    # Remove unnecessary columns
+    # Remove unnecessary columns (GrandPrix, Session, Driver, Lap, CornerID)
     df = df.drop(df.columns[:5], axis=1)
+    # Remove Stint (index 2 after dropping first 5)
     df = df.drop(df.columns[2], axis=1)
     
+    # Normalize TireLife relative to compound BEFORE Z-score
+    # Questo rende il valore comparabile tra compound diversi
+    print("Normalizing TireLife relative to compound...")
+    df['TireLife'] = df.apply(
+        lambda row: normalize_tire_life(row['TireLife'], row['Compound']), axis=1
+    )
+    print(f"  TireLife range after normalization: [{df['TireLife'].min():.4f}, {df['TireLife'].max():.4f}]")
+    
     # Remove X, Y, Z columns
     df = df.drop(df.columns[352:502], axis=1)