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A题/ZJ_v2/fig11_heatmap_temp_signal.py

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+"""
+Fig 11: Two-Parameter Heatmap (Temperature × Signal Quality)
+Shows interaction effects on TTE
+"""
+
+import os
+import numpy as np
+import matplotlib.pyplot as plt
+from plot_style import set_oprice_style, save_figure
+
+def compute_tte_surface(T_a_range, psi_range):
+    """Compute TTE for grid of (T_a, psi) values"""
+    
+    T_grid, psi_grid = np.meshgrid(T_a_range, psi_range)
+    tte_grid = np.zeros_like(T_grid)
+    
+    # Battery capacity
+    Q_full = 2.78  # Ah
+    V_avg = 3.8    # V
+    E_total = Q_full * V_avg  # Wh
+    
+    # Baseline power components
+    P_bg = 5.0
+    P_scr = 8.0 * 0.3  # L = 0.3
+    P_cpu = 35.0 * 0.4  # C = 0.4
+    P_gps = 0.015  # Minimal
+    
+    for i in range(len(psi_range)):
+        for j in range(len(T_a_range)):
+            T_a = T_grid[i, j]
+            psi = psi_grid[i, j]
+            
+            # Network power depends on signal quality (worse signal = more power)
+            k_net_base = 7.0
+            k_net = k_net_base * (1 + 2 * (1 - psi))
+            P_net = k_net * 0.05  # N = 0.05
+            
+            # Temperature affects efficiency (cold reduces capacity, hot increases resistance)
+            temp_factor = 1.0
+            if T_a < 10:
+                temp_factor = 0.8 + 0.02 * T_a  # Reduced capacity in cold
+            elif T_a > 30:
+                temp_factor = 1.0 + 0.01 * (T_a - 30)  # Increased losses in heat
+            
+            P_total = (P_bg + P_scr + P_cpu + P_net + P_gps) * temp_factor
+            
+            tte_grid[i, j] = E_total / P_total
+    
+    return T_grid, psi_grid, tte_grid
+
+def make_figure(config):
+    """Generate Fig 11: Two-Parameter Heatmap"""
+    
+    set_oprice_style()
+    
+    # Parameter ranges
+    T_a_range = np.linspace(-10, 40, 50)  # °C
+    psi_range = np.linspace(0.1, 1.0, 50)  # Signal quality (0=poor, 1=excellent)
+    
+    # Compute TTE surface
+    T_grid, psi_grid, tte_grid = compute_tte_surface(T_a_range, psi_range)
+    
+    # Create figure
+    fig, ax = plt.subplots(figsize=(12, 9))
+    
+    # Heatmap
+    im = ax.contourf(T_grid, psi_grid, tte_grid, levels=20, cmap='RdYlGn', alpha=0.9)
+    
+    # Contour lines
+    contours = ax.contour(T_grid, psi_grid, tte_grid, levels=10, colors='k', 
+                          linewidths=0.5, alpha=0.3)
+    ax.clabel(contours, inline=True, fontsize=8, fmt='%.1f h')
+    
+    # Colorbar
+    cbar = fig.colorbar(im, ax=ax, label='Time to Empty (hours)')
+    cbar.ax.tick_params(labelsize=9)
+    
+    # Mark baseline condition
+    T_baseline = 25
+    psi_baseline = 0.8
+    ax.plot(T_baseline, psi_baseline, 'r*', markersize=20, 
+            markeredgecolor='white', markeredgewidth=1.5, 
+            label='Baseline Condition', zorder=5)
+    
+    # Mark danger zones
+    # Cold + poor signal
+    ax.add_patch(plt.Rectangle((-10, 0.1), 15, 0.3, 
+                               fill=False, edgecolor='red', linewidth=2, 
+                               linestyle='--', label='Critical Zone'))
+    ax.text(-5, 0.25, 'Battery Killer\\n(Cold + Poor Signal)', 
+           fontsize=9, color='darkred', ha='center',
+           bbox=dict(boxstyle='round', facecolor='white', alpha=0.7))
+    
+    # Optimal zone
+    ax.add_patch(plt.Rectangle((15, 0.7), 15, 0.25, 
+                               fill=False, edgecolor='green', linewidth=2, 
+                               linestyle='--', label='Optimal Zone'))
+    ax.text(22.5, 0.825, 'Optimal\\n(Mild + Good Signal)', 
+           fontsize=9, color='darkgreen', ha='center',
+           bbox=dict(boxstyle='round', facecolor='white', alpha=0.7))
+    
+    # Labels and styling
+    ax.set_xlabel('Ambient Temperature (°C)', fontsize=11)
+    ax.set_ylabel('Signal Quality (Ψ)', fontsize=11)
+    ax.set_title('TTE Sensitivity to Temperature and Signal Quality (Interaction Effect)', 
+                 fontsize=12, fontweight='bold')
+    ax.set_xlim(-10, 40)
+    ax.set_ylim(0.1, 1.0)
+    ax.legend(loc='upper left', framealpha=0.9, fontsize=9)
+    
+    # Add statistics
+    tte_min = np.min(tte_grid)
+    tte_max = np.max(tte_grid)
+    tte_range = tte_max - tte_min
+    
+    stats_text = f'TTE Range:\\n' + \
+                f'Min: {tte_min:.2f}h\\n' + \
+                f'Max: {tte_max:.2f}h\\n' + \
+                f'Spread: {tte_range:.2f}h ({tte_range/tte_max*100:.1f}%)'
+    
+    ax.text(0.98, 0.02, stats_text, transform=ax.transAxes,
+            fontsize=9, verticalalignment='bottom', horizontalalignment='right',
+            bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.8),
+            family='monospace')
+    
+    # Save
+    figure_dir = config.get('global', {}).get('figure_dir', 'figures')
+    os.makedirs(figure_dir, exist_ok=True)
+    output_base = os.path.join(figure_dir, 'Fig11_Heatmap_Temp_Signal')
+    save_figure(fig, output_base, dpi=config.get('global', {}).get('dpi', 300))
+    plt.close()
+    
+    return {
+        "output_files": [f"{output_base}.pdf", f"{output_base}.png"],
+        "computed_metrics": {
+            "tte_min_h": float(tte_min),
+            "tte_max_h": float(tte_max),
+            "tte_range_h": float(tte_range)
+        },
+        "validation_flags": {},
+        "pass": True
+    }